Relationship between the food system and food security.
\r\n\t
",isbn:"978-1-80356-717-4",printIsbn:"978-1-80356-716-7",pdfIsbn:"978-1-80356-718-1",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"2204ff2e64bffb84a4bf1b74bb38bfa1",bookSignature:"Dr. Hector Pérez-de-Tejada",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11492.jpg",keywords:"Plasma Dynamics, Fluid Flow Description, Space Research, Technical Devices, Multinational Participation, Communication Systems, Digital Links, World Information Patterns, Global Input Response, Wave-Particle Interactions, Instrument Identification Coverage, Open Access Data",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"March 23rd 2022",dateEndSecondStepPublish:"June 1st 2022",dateEndThirdStepPublish:"July 31st 2022",dateEndFourthStepPublish:"October 19th 2022",dateEndFifthStepPublish:"December 18th 2022",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"a month",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"A seasoned researcher with over 50 years of experience in Geophysics and Space Physics, with over 200 publications, a member of the International Astronomical Union, and former president of the Mexican Geophysical Union.",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"345070",title:"Dr.",name:"Hector",middleName:null,surname:"Pérez-de-Tejada",slug:"hector-perez-de-tejada",fullName:"Hector Pérez-de-Tejada",profilePictureURL:"https://mts.intechopen.com/storage/users/345070/images/system/345070.png",biography:"Graduate of the Physics School at the National University of Mexico in Mexico City with a Masters and Doctorate degree from the University of Colorado in Boulder, Colorado (1970).\r\nFull time researcher at the Institute of Geophysics of the National University of Mexico since 1970. \r\nPresident of the Mexican Geophysical Union (1982-1984) and head of the Space Physics Department in the Institute of Geophysics (2016-2018)",institutionString:"National Autonomous University of Mexico",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"2",totalChapterViews:"0",totalEditedBooks:"0",institution:{name:"National Autonomous University of Mexico",institutionURL:null,country:{name:"Mexico"}}}],coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"10",title:"Earth and Planetary Sciences",slug:"earth-and-planetary-sciences"}],chapters:null,productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"},personalPublishingAssistant:{id:"466997",firstName:"Patricia",lastName:"Kerep",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/466997/images/21565_n.jpg",email:"patricia@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. 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Venkateswarlu",coverURL:"https://cdn.intechopen.com/books/images_new/371.jpg",editedByType:"Edited by",editors:[{id:"58592",title:"Dr.",name:"Arun",surname:"Shanker",slug:"arun-shanker",fullName:"Arun Shanker"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"72",title:"Ionic Liquids",subtitle:"Theory, Properties, New Approaches",isOpenForSubmission:!1,hash:"d94ffa3cfa10505e3b1d676d46fcd3f5",slug:"ionic-liquids-theory-properties-new-approaches",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/72.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"314",title:"Regenerative Medicine and Tissue Engineering",subtitle:"Cells and Biomaterials",isOpenForSubmission:!1,hash:"bb67e80e480c86bb8315458012d65686",slug:"regenerative-medicine-and-tissue-engineering-cells-and-biomaterials",bookSignature:"Daniel Eberli",coverURL:"https://cdn.intechopen.com/books/images_new/314.jpg",editedByType:"Edited by",editors:[{id:"6495",title:"Dr.",name:"Daniel",surname:"Eberli",slug:"daniel-eberli",fullName:"Daniel Eberli"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"57",title:"Physics and Applications of Graphene",subtitle:"Experiments",isOpenForSubmission:!1,hash:"0e6622a71cf4f02f45bfdd5691e1189a",slug:"physics-and-applications-of-graphene-experiments",bookSignature:"Sergey Mikhailov",coverURL:"https://cdn.intechopen.com/books/images_new/57.jpg",editedByType:"Edited by",editors:[{id:"16042",title:"Dr.",name:"Sergey",surname:"Mikhailov",slug:"sergey-mikhailov",fullName:"Sergey Mikhailov"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1373",title:"Ionic Liquids",subtitle:"Applications and Perspectives",isOpenForSubmission:!1,hash:"5e9ae5ae9167cde4b344e499a792c41c",slug:"ionic-liquids-applications-and-perspectives",bookSignature:"Alexander Kokorin",coverURL:"https://cdn.intechopen.com/books/images_new/1373.jpg",editedByType:"Edited by",editors:[{id:"19816",title:"Prof.",name:"Alexander",surname:"Kokorin",slug:"alexander-kokorin",fullName:"Alexander Kokorin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"2270",title:"Fourier Transform",subtitle:"Materials Analysis",isOpenForSubmission:!1,hash:"5e094b066da527193e878e160b4772af",slug:"fourier-transform-materials-analysis",bookSignature:"Salih Mohammed Salih",coverURL:"https://cdn.intechopen.com/books/images_new/2270.jpg",editedByType:"Edited by",editors:[{id:"111691",title:"Dr.Ing.",name:"Salih",surname:"Salih",slug:"salih-salih",fullName:"Salih Salih"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"16692",title:"SCIROCCO Plasma Wind Tunnel: Synergy between Numerical and Experimental Activities for Tests on Aerospace Structures",doi:"10.5772/21125",slug:"scirocco-plasma-wind-tunnel-synergy-between-numerical-and-experimental-activities-for-tests-on-aeros",body:'Spacecraft structures are subjected to aerodynamic heating during launch and re-entry phases of their operations. The design of these structures poses several challenges to structural designer since the aerodynamic heating, which is the predominant load (Kelly et al., 1983; Shih et al., 1988), induces elevated temperatures that can affect the structural behaviour in several harmful ways: degradation of the elastic material properties, reduction of allowable stresses and generation of high thermal stress due to restrained local thermal expansion/contractions.
The success of a re-entry spatial mission in the Earth atmosphere, as well known, is strongly related to the performances of the Thermal Protection Systems (TPSs), which play the most important role (Thornton, 1996). The TPS is the most critical component of a spacecraft since if they are somehow damaged during the mission, a chain reaction can be triggered, leading to a quick propagation of the damage on the whole structure, inestimable economic losses and, above all, losses of human lives. The task of a TPS is to protect the substructure of the vehicle against local and global overheating. In order to ensure the feasibility of interplanetary missions, and in general for the qualification of the critical parts of reentry vehicles, TPS concepts have to be first qualified on-ground and then tested and validated in flight conditions. Thus, Plasma Wind Tunnel facilities have a key role during this qualification process. They should be able to simulate hypersonic air flows encountered during re-entry into Earth atmosphere and to test TPS concepts on full scale demonstrator.
Nevertheless, reproducing hypersonic conditions in the wind tunnels is harder, if not impossible, with respect to other motion conditions. As matter of fact, it is very complicated to reproduce simultaneously the enthalpy, the hypersonic speed, the chemical composition of gases and the dimensions of the model, which are the main factors which characterize the motion.
As a consequence, a choose is needed between wind tunnels designed for the aerodynamic simulation and those ones designed for the thermal simulation.
Thus, wind tunnels can be classified in two categories:
Aerodynamic, for the simulation of the Mach number;
Aero-thermodynamic, for the simulation of heat fluxes.
The main feature of the “blow down” aerodynamic wind tunnels is that to reach high Mach numbers it is needed to pre-heat the air before the expansion through a nozzle. In this kind of wind tunnels, the flux is characterized by a very high stagnation pressure which is indispensable to obtain elevated Mach numbers. The duration of the tests is rather limited because it is related to the empting time of the tank. Typically, they last some dozens of seconds. The aerodynamic wind tunnels work in an intermitting fashion since it is needed to wait for a certain time to recompress the fluid, in such a time the wind tunnel is inactive.
On the other hands, the aerothermo-dynamic wind tunnels are mainly fed by an electric arc and they work in a continuous fashion. The gas heated by the arc reaches very high temperature. Such kind of wind tunnels are mainly used to reproduce heat fluxes in order to test the performances of ablative materials or TPSs, as well as to investigate aerothermo-chemical problems. In the aero-thermodynamic wind tunnels, it is very complicated to determine the thermo-fluid dynamic parameters such as Mach, Reynolds, Knudsen numbers and so on.
One of the most crucial difficulty is that after the gas has been heated by the arc-heater and has passed through the nozzle, its composition is unknown and sophisticated diagnostics techniques are needed to evaluate it. Numerical models are also conveniently used to predict the gas thermo-chemical evolution and to characterize the fluid in the test chamber.
In the mid eighties the European Space Agency (ESA) feels the need of an appropriate facility to carry out experimental ground tests. The intention was to realize a wind tunnel with high enthalpy and very large dimensions so that full scale component of spacecrafts could be tested. Indeed, in hypersonic conditions, the heat fluxes distribution is affected by the sizes of the model.
Since Italy was very interested to the project, the conceptual design, the feasibility study and the preliminary design activities were assigned to the Italian Aerospace Research Centre (CIRA) and were performed between the 1988 and 1989.
In that period was noticed the need to have stagnation temperatures close to 10000 K. Hence, such a value was used to define the technical specifications of the arc-heater.
The air flux in the wind tunnel should be characterized by very high temperature and for this reason, the name “Scirocco”, which is the warm wind coming from the Sahara Desert and acting on the Mediterranean costs, was given to the facility.
The final design started in observance to a grant agreement between ESA and the Italian Ministry of University and Scientific and Technologic Research (MURST).
The facility started to be built in December 1994 and the work finished in 2001.
As shown in Figure 1, Scirocco is the largest arc jet test facility in the world in terms of arc heater power (about 70 MW).
Moreover, a nozzle with a 2 metre diameter exit allows full-scale models of space-vehicle thermal protection systems to be tested for up to 30 minutes, a period which corresponds to the duration of re-entry. The facility, providing thermal energy to the gas, is able to generate an elevated massive flow and very high temperature, allowing hypersonic conditions to be easily reproduced. The peculiar characteristics of the hypersonic regime, extensively described above, make the requirements of the test to be very constrained.
Plasma wind tunnels in the world
The Scirocco PWT is used in the field of aerospace technology development and its main applications can be summarized as follows:
Investigate aerothermodynamic phenomena related to the re-entry of both space vehicles and capsules: this is the primary use, indeed Scirocco is able to simulate the re-entry trajectory of several space vehicles, e.g. the Space Shuttle.
Investigate the aerothermodynamic of launch vehicles during the ascending phase: problems related to the aerodynamic heating raise also in the launch phase and they are caused by the high acceleration values; such problems are similar to those ones induced by the re-entry with the difference that in this case the heating occurs in a lower atmosphere characterized by a higher value of the air density.
Investigation on exhaust nozzles for launch vehicles and missiles.
Investigation on the aerothermochemical of internal fluxes: such an analysis is aimed at developing of aerospace propulsion systems (ramjet, scramjet)
Study on the interaction between the plasma and the electromagnetic fields: in particular, the communications black-out between the ground and the vehicles occurring during the re-entry phase is investigated.
Study on industrial processes which induce a variation of the chemical composition of the used gas.
A typical test performed in the SCIROCCO wind tunnel can be sketched as shown in Figure 2 where the different phases are outlined.
An air mass flow rate varying between 0.1 and 3.5 Kg/s and with a pressure of 87 bar is supplied by a compression system and then is introduced in the arc heater together with a little argon mass flow rate which is used to help the arc heater ignition and to reduce the oxidation of the electrodes.
Once the arc heater reaches the steady state conditions, it converts the electric energy in the thermal one, thus increasing the air temperature.
The electrodes receive the electric energy which is provided by a Power Supply System. Such system converts the alternate current, coming from the external power supply, in direct current. Inside the arc heater, the air reaches pressures varying between 1 and 17 bar and temperatures varying between 2000 and 10000K. Successively, the air is expanded through a conical nozzle and crosses the test chamber at the thermodynamic conditions required by the test.
Sketch of a typical test performed at the SCIROCCO Plasma wind tunnel
After that, the test article is inserted in the plasma flow by means of an automatic robot which is named Model Support System (MSS) fixed to the base of the test chamber. The main physical parameters are monitored by means of a Data Acquisition System (DAS). Advanced instrumentations are installed both inside and outside the test chamber.
The plasma flow is then collected in the diffuser whose main task is to reduce the plasma speed from supersonic values to subsonic ones. The diffuser is made by a convergent-divergent horizontal nozzle with a long central part at uniform section and it is cooled by an external cooling system.
At the end of diffuser, the air flow encounters the heat exchanger which reduces the temperature of the air consistently with the thermal strength of the materials used for the vacuum system which is located afterwards. The vacuum system generates and keeps the vacuum conditions required by the test. All the components located between the arc heater and the heat exchanger identify the SCIROCCO Test Leg.
A system, named “DeNOx” system, follows the vacuum system and its aim is to reduce the amount of nitrogen oxide produced in the Test Leg during the test.
In order to reduce the thermal energy produced in the various components of the Test Leg a water cooling system is used. Two water cooling circuits are used with two different values of the water pressure. In both the water is demineralised for two reasons, first, to avoid the salt deposition along the exchange surfaces which may reduce the heat exchange coefficients, and second, to avoid problems related to the electric conductivity of non demineralised water. The high pressure circuit is used to cool critical component of the Test Leg where very high heat exchange coefficients are needed, the other components are cooled by the low pressure circuit. Moreover, cooling water is used both to cool some components of the facilities and to decrease the temperature of the demineralised water.
The SCIROCCO PWT has an advanced control and automation system, able to reproduce with a good accuracy the re-entry trajectory of space vehicles. Every subcomponent has a dedicated Local Central Unit (LCU) which monitors the process from an operative and safety point of view. The LCUs are connected each other and are also connected to a Central Computer System (CCS) which acts as supervisor of the whole facility. The connection between all the components is made through an high velocity transmission system.
The operating envelope of the SCIROCCO PWT, in terms of plasma total pressure and enthalpy which can be obtained in the test chamber, is shown in Figure 3.
Operating envelope of the SCIROCCO PWT
It was obtained by taking into account the operating and technological limits of the facilities which can be summarized as follows:
Minimum allowable power provided by the Power Supply System equal to 1 MW;
Minimum air pressure able to make steady the arc heater equal to 1 bar;
Maximum allowable total enthalpy of the gas equal to 45 MJ/Kg
Maximum direct current value equal to 9000 A;
Maximum allowable heat flux at the nozzle groove equal to 5 KW/cm2;
Maximum allowable power provided by the Power Supply System equal to 70 MW;
Maximum air massive flow equal to 3.5 kg/s;
Minimum allowable total enthalpy of the gas equal to 2.5 MJ/Kg
In the next paragraph, the main components of the whole facility is described in detail.
The arc heater installed at the SCIROCCO PWT is the largest of its kind in the world. It is located between the air compressor system and the nozzle and its main task is to heat the air by converting electric energy in thermal one. Such conversion is activated by a spark which is generated between an anode and a cathode having different electric potentials.
The arc heater shown in Figure 4, is made of a column 5500mm long, with an internal diameter of 110 mm. The anode and the cathode, each one made of 9 electrodes, are located at the two ends of the columns. The electric current is provided by a power cabin and the ballast resistors, which uniformly canalize the current, are installed before the electrodes.
In Table 1, the arc heater design technical specifications are reported.
The arc heater structure is divided into several blocks (in order to optimize the phase of maintenance and the cooling) and each single block consists of several discs inside which there is the passage of demineralised water at high pressure for the cooling (used because, as said, the absence of minerals makes it not electrically conductive), and compressed air coming from the external line. The air and water ducts that enter the individual blocks have different colours, and both the inlet pressure demineralised water, and the compressed air pressure vary along the length of the arc depending on the areas that need more cooling.
The anode is made of a copper alloy that resists to high thermo-mechanical stresses and it is connected with the power lines coming from the power unit.
Arc heater
Arc heater design technical specifications
In the anode high pressure argon is introduced whose primary purpose is to avoid a direct contact between the electrodes and the flow of electrons, thereby avoiding a localized corrosion of the inside of the electrodes which obviously would cause serious problems. The second purpose related to the use of argon is to help the ignition of the arc, since it increases the conductivity of the air flow. The cathode has a configuration similar to the anode and it is at the other end of the arc.
The column is inserted between the anode and the cathode. As mentioned, it has a maximum length of 5500 mm and a variable configuration (it consists of 28 members each in turn composed of 20 rings) depends on the enthalpy level required.
The column is designed to confine the plasma as possible along the axial direction and to avoid problems of corrosion and melting of materials. Between the rings there is a layer of insulator (spacer) and both demineralised water and air, which is fed into the column with a velocity component tangential to the duct, enter. Following this tangential velocity is going to settle with the axial velocity component coming from the vacuum created by the vacuum system, generating a spiral motion.
It should be noted that a part of the flow remains attached to the inner walls of the column, creating a sort of gap that prevents the fusion of this.
Inside the column there is the motion of electrons from anode (high potential) to cathode (low potential) submitted to the Lorentz force. In this phase the conversion of electrical energy into heat energy takes place, because the electrons collide with the moving particles of air and argon, heating for viscous friction and energizing the flow.
As the temperature increases to levels high enough to trigger such vibration and dissociation of molecules and ionization of atoms the gas becomes "plasma".
Immediately downstream of the cathode there is the plenum, which has a constant cross section of 172 mm and is essentially intended to lower the total enthalpy of the air below the limit imposed by the minimum value of electric current. This is done by injecting air into this section at room temperature, which generates a resulting reduction in temperature of the plasma which, of course, will change its chemical composition.
The nozzle is composed of a convergent-divergent duct that has the function to expand the flow by increasing the speed and reducing the static pressure, in order to obtain the required thermo-fluid dynamic test conditions. Table 2 shows the nozzle design specifications:
Design requirements for the nozzle
The first part of this component is a convergent trait in which the motion is subsonic. In the throat (i.e., the minimum diameter section, which in this case is 75 mm), the Mach reaches the unit value, and in the divergent part a further expansion occurs up to supersonic Mach numbers in the output section. The mach depends on the configuration of the nozzle used.
In fact it is divided into seven parts with different diameters of the output section, which allow to configure the nozzle so as to achieve different test conditions. As noted in Table 3, the maximum diameter of the outlet section is equal to 1950 mm, which corresponds to a ratio of the areas (outlet area divided by the area of the throat) equal to 676.
Nozzle configurations
The critical part in terms of thermo-mechanical stress is the throat where very high temperature can be reached. In fact, while the entire nozzle is cooled with demineralised water at low pressure (which runs in conduits placed lengthwise along the outer surface), the throat is cooled by demineralised water pipes dedicated at high pressure through a mechanism that guarantees a higher forced convection heat transfer coefficient.
At the nozzle exit, then, there are four sensors that follow the evolution of static pressure.
The Test Chamber (TC) has a cylindrical shape (Figure 5) and it is the place where the flow field to be simulated is realized (Figure 6). In fact, inside it the plasma coming from the nozzle impacts the model and the experimental measurements of pressure and temperature are carried out. Such measurements, properly treated, represent the ultimate goal of the entire system.
Test chamber
The test chamber is 9217 mm high and has an inner diameter of 5170 mm, it has three openings necessary to allow the entrance to the maintenance staff and to allow to do the assembly on the support of the model, it also has a number of side windows to allow monitoring and diagnostics of the plasma flow. This component has a sliding floor to the entrance of the model and is not cooled.
Plasma flow inside the Test Chamber.
During a test performed under special conditions, such as a low flow, it is possible to inject inside the test chamber a small amount of air called "bleed air" in order to increase the value of chamber pressure and limiting the recirculation of plasma.
In the test chamber, static pressure meters and temperature meters are located at various points, moreover, two tools called "probes" are introduced within the plasma flow before the entry of the support model.
The purpose of this process is monitoring the status of thermo-fluid dynamic conditions of plasma in terms of pressure and temperature at various locations of the jet, they are adequately cooled by a circuit of demineralised water and make an arc of a circle driven by electric motors.
The "Model Support System" (MSS), is essentially an automated arm cooled by internal circuits of demineralised water and its function is related to the proper positioning of the model within the plasma jet.
The MSS allows a maximum vertical displacement equal to 1650 mm, and can also move in the longitudinal direction, helping to compensate for positioning errors with respect to the direction of flow of plasma. The support also allows a rotational movement and thus makes it possible to make tests in a dynamic manner.
The diffuser is designed to collect the flow of plasma out of the test chamber and slow down to subsonic speed values. It consists of a short convergent, followed by a long stretch of constant section and final section of duct diverts slightly upstream of the heat exchanger (Figure 7). Part of the converging section is located inside the test chamber.
Diffuser
The geometry of the diffuser is summarized in Table.4:
Diffuser geometrical data.
The heat exchanger is used to cool the flow of plasma from diffuser up to temperatures compatible with the operation of the vacuum system which is located just downstream.
This component consists of an input section cooled by an external circuit water tower, followed by tubes that run longitudinally in the conduit and exposed to direct current. They form the part that removes heat from the plasma.
Downstream of these tubes two circular sections of different diameters are placed that allow the connection to the vacuum system. There is also an expansion joint that allows to control the thermal deformation of the various components between the test chamber and heat exchanger.
The function of the vacuum system is to maintain low pressure in the test chamber and it is located directly downstream of the heat exchanger (Figure 8).
The design specifications of the vacuum system are described in Table 5.
Design specifications of the vacuum system
The vacuum system basically consists of three lines (plus an additional line called "by-pass line, which serves to maintain the vacuum in case of pressure fluctuations).
These three lines, which can provide different operating configurations depending on the level of vacuum that is required, are as follows:
Line A: consists of 5 ejector in series (they are converging-diverging duct with circulating high temperature steam) and has a maximum capacity of 0.5 kg/s, it can work in conjunction with the other two lines;
Line B: consists of four ejectors in series and has a maximum capacity of 1 kg/s;
Line C: consists of three ejectors in series and has a maximum capacity of 2 kg/s.
The opening lines are controlled by corresponding on/off valves automatically controlled by the control system once set the conditions for conducting the test.
Vacuum System
The DeNOx system serves to substantially reduce the percentage of nitrogen oxide (NO or NOx) inevitably present in the flow of plasma.
The DeNOx is essentially composed of two large reservoirs, "scrubbler", which reduce the concentration of NO, a complex system of pumps, and three tanks. The first one is the largest and contains the washing solution, the second one contains sodium hypochlorite, NaOCl, and the third one contains caustic soda NaOH.
The DeNOx is able to maintain the concentration of nitric oxide (NO) below the limits fixed by the Italian law, and this is possible by means of a series of chemical reactions that occur within it.
The system receives electricity from two external lines and it is equipped with an internal circuit for distribution. The power supply lines, through a complex system of processors, are reduced in a single line of industrial output voltage related to two different boxes: the first one is an electrical line of medium voltage (20 KV electrical system) which is connected to different users; a second cabin is the one of very high loads (32.5 kV, main load).
The cabin of the electrical system is designed to reduce the voltage and distribute electric power to the various units. It is equipped with four resin transformers powered with a medium voltage. The first two transformers make a conversion 20-0.4 KV providing power to the laboratories, while the remaining two transformers operating a conversion KV 20-6 feeding the engine and pump system. Inside the cabin, the power systems of the control system are installed, moreover an emergency instrumentation is present which ensures the supply of electricity in case of black-out. The Power Supply System is an independent unit and receives macro-command from the central system.
This unit provides electric power to the arc, up to a maximum of 70 MW. The subsystem is also equipped with appropriate filters suppressor of particular harmonics of the network.
The Power Supply System uses oil transformers which, depending on the required load current and voltage, may give rise to two different configurations: the first one guarantees 6000 at 20,250 V and the second one 9000 at 13500 V, the change of Configuration is done with remote-controlled pneumatic arms, which open or close certain circuits.
Downstream of the processors there are the current converters (AC / DC converter) that basically consist of thyristors cooled by demineralised water. Finally, the reactors have the task of eliminating the oscillations of the current (so-called "ripple"). The final closure of the circuit is done manually and, in cases of emergency, to disconnect the arch, a "Grow bar" that dissipates current through a coil is used. Finally, the "ballast resistors" are connected to the electrodes of the arc and are of the order of micro-ohm resistors, used to distribute the current.
The Data Acquisition System (DAS) is used to acquire data from sensors of various typologies. The instrumentation system is divided broadly into two classes: the first is called field instrumentation and is the set of sensors used for the acquisition of measurements relative to the facility, the second is named test instrumentation and refers to measurement on the models or inside the test chamber (for scientific targets).
In the electric arc there is a static pressure sensor appropriately certified, while there are no temperature gauges because any intrusive sensor that would measure temperatures of 10000 K would have problems immediately.
The basic functions of the acquisition system are both the measurement of thermodynamic parameters on the model (for example, to study the behaviour of materials during the return from a space mission) and the measurement of parameters related to plasma and aerothermodynamics and, in Test Leg for that purpose, the instrumentation is divided in "virtual instruments", that means installed outside the test chamber and therefore not intrusive, and "conventional instruments", i.e. inside the test chamber instrumentation (intrusive).
At the nozzle exit section there are four static pressure gauges, they are essentially four small holes in the order of half a millimetre in diameter spaced 90 degrees from each other, used to measure static pressure fluctuations in various positions. This situation is in fact indicative of a lack of uniformity of plasma.
Inside the test chamber there are four more pressure sensors, in addition to the two probes. The latter are basically two ways that are intended to measure the thermo-fluid dynamics characteristics of the flow in terms of stagnation pressure and heat flux on the surface of the probe exposed to the plasma.
The pressure sensors are small diameter holes using a suitable transducer that guarantees operation even in environments at low pressures.
In the next paragraph the heat flow meter in the stagnation point of the probe is described.
The heat flux is measured at the probe stagnation point by means of a gardon gauge (Gardon, 1953) which is a heat flux sensor primarily intended for the measurement of high intensity radiation. It consists in a constantan foil hanging in a copper heat sink (see Figure 9). The foil is thermally and electrically connected to the copper cylinder through specific metallurgic techniques and it acts as first thermoelectrical material while the copper acts as the second thermoelectrical material. Thus, the foil and heat sink are respectively the hot and the cold joint of a thermocouple. A thin wire is then connected at the centre of the foil in order to generate a differential thermocouple which measures the temperature jump between the centre and the side of the foil.
Gardon gauge
In a polar coordinate system, the heat conduction equation can be written as:
where
Let us consider the following initial and boundary conditions:
T(r,0)=Ts per 0<r<R
T(r,t)=Ts per 0<t<
In the steady state regime and taking into account Eq.(2), the solution of Eq.(1) is:
Thus, the heat flux at the centre of the foil (r=0) is:
Equations (3) and (4) show that the temperature jump between the centre and the side of the foil is proportional to the heat flux which then can be evaluated by measuring such temperature jump.
The specific total enthalpy
Where
By using this approach and because of the uncertainty of the various measure instruments, the specific total enthalpy is estimated with an error which sometimes results notable. Such error can be computed by using Eq.(6).
The design of a test in a Plasma Wind Tunnel is complicated by the circumstance that many differences exist between flight and test chamber conditions (model size, dissociated flow conditions in test chamber, density level, etc.). All these aspects play an important role on the real gas non-equilibrium phenomena and make difficult the duplication of real flight conditions in wind tunnel. The main problem is to find the correct similitude parameters: to this effect, it is firstly needed to define the goal of the simulation, i.e. the phenomenon we are interested in reproducing; this is often a flight condition to be simulated on the test article in wind tunnel, but it can be a particular customer’s request as well (Marini et al. 2007). Hence, the design of ground-based experiments, as well the interpretation of experimental data, needs an appropriate support of numerical simulations. As matter of fact, in order to meet the specific test requirements (Stagnation heat flux, stagnation pressure, test time and test article size), Computational Fluid Dynamics (CFD) calculations are needed to accurately design the configuration of the facility. Successively, a structural safety analysis is carried out with the aim of verifying the structural integrity of the test article. After the test is performed and experimental data are acquired, numerical activities are again needed to rebuild the test and to support in the interpretation of the test results. Moreover, the ability of the developed finite element model in predicting the temperature field in the test article is verified by comparing numerical data with experimental one.
The present paragraph deals with the description of the procedure for the execution of a test in the facility SCIROCCO. An overview of the test procedure is given in the flow chart of Figure 10.
Each steps of such procedure will be described in detail hereafter:
Requirements: The first aspect that is taken into account when a test in SCIROCCO is designed is the definition of the requirements.
Requirements can be formulated in terms of heat flux (more often), or in terms of pressure, temperature or they can also be formulated in terms of scientific phenomena reproduction such as shock wave -boundary layer interaction and so on.
SCIROCCO Test Procedure
The requirements are given by the customer and a process of trade-off begins. Indeed a feasibility study verifies the compatibility of both test requirements with the PWT theoretical envelope and test article dimensions with test chamber capability, in order to avoid blockage phenomenon. Then, a first operating condition is defined by means of both engineering tools, to derive the stagnation point heat flux and pressure from requirements on the test article, and the curve-fit calibration law for fast PWT Test Setting (De Filippis et al. 2003).
Preliminary PWT operating condition: Once the first operating condition has been defined, the driving parameters of the facility (current and air mass flow) and the PWT performances in terms of reservoir pressure (P0) and reservoir enthalpy (H0) are obtained, and consequently the stagnation pressure (PS) and stagnation heat flux (QS) on the PWT calibration probe are evaluated.
CFD Simulations: Starting from the preliminary condition, the final PWT settings able to match the test requirements are defined by means of an iterative procedure, which involves both CFD computations and evaluations with simplified engineering correlations.
Free stream conditions to be used for the simulation of the flow around the model in the test chamber are obtained from the numerical computation of the nozzle flow. If the CFD simulation of the flow past the model shows that test requirements over the model are not still achieved, a new reservoir condition (P0, H0) is deduced by using simplified engineering correlations and the procedure restarts from the CFD simulation of the nozzle flow. As an alternative, test requirement fulfilment could be reached with the same reservoir conditions, properly modifying the model position inside the test chamber and/or the model attitude. In this last hypothesis only model computation has to be iterated.
Once the final PWT operating condition has been defined, simulation of the flow past the PWT calibration probe provides pressure (PS) and heat flux (QS) at the probe stagnation point. These values, measured during the test, ensure the achievement of the desired operating condition in terms of (P0, H0) in test chamber.
Thermostructural FEM-based analysis: once the PWT operating condition ensuring the achievement of test requirements has been identified, the structural integrity of the model under that conditions has to be verified. At this stage a FEM transient thermal analysis is carried out by applying on the model the heat flux distribution (usually multiplied by a safety coefficient equal to 1.2) computed by CFD simulations. The thermal analyses are highly nonlinear since radiation to the environment must be taken into account. The temperatures predicted by the FE model are checked against the temperature limits of the materials under investigation. Critical instants are then identified as those ones at which high gradients of temperature (and thus high thermal stresses) are expected. Nonlinear static structural analyses are then carried out by applying the temperature field predicted at the critical instants as a structural load. FE codes able to perform non linear contact analyses are used at this stage. Thermal and structural simulations are very useful also to identify critical parts which have to be properly monitored during the tests. In other words, expected temperatures predicted by numerical simulations are the input data for the test instrumentation plan whose objective is accurately choose the kind of instruments, their location and range, that are used to monitor the test and to reach its scientific aim.
Instrumentation plan: When the trade-off phase for the definition of the test conditions is concluded, the instrumentation setup to be used for the test is designed. Indeed, the particular environment typical of hypersonic regime and the scientific aims of the tests require a number of parameter measurements. Hence, different kind of instruments, both intrusive (thermocouples) and not intrusive (pyrometers and thermocameras), measuring at different locations have to be properly chosen.
Similarly to the test conditions definition phase, a trade-off phase for the definition of the instrumentation is performed, at the end of which the instrumentation plan is made, that is a design report containing all the information about the test instrumentation.
Test execution and post processing reporting: Once the test conditions (including test duration and all the other parameters) and the test instrumentation are fixed, the test is executed. After the test a period of time is necessary for the post processing (data treatment) and the reporting, at the end of which a complete report, the “Test Report”, is carried out.
In this document all the information about the test and all the instrumentation measured and treated data are reported.
Rebuilding: The numerical rebuilding is another important phase, that, differently from all the other phases, follows the test itself. It is performed starting from the measured values of stagnation heat flux and pressure rather than the values of reservoir pressure and enthalpy, and its aim is to provide a meaningful heat flux distribution on the model during the test as input for the thermo-structural rebuilding analysis, whose results (wall temperature distribution) can be compared with the IR thermo-graphic acquisition generally performed in PWT tests.
From a numerical point of view it determines the condition (P0, H0) that provides the better agreement with the probe measurements and then, with the same condition, the heat flux over the model is recomputed.
In order to show the importance of “rebuilding” a PWT test, this step will be presented in detail referring to a specific application.
Within the context of the research project Sharp Hot Structures (SHS), focused on the assessment of the applicability of Ultra High Temperature Ceramics (UHTCs) to the fabrication of high performance and sharp hot structures for reusable launch vehicles, the nose cap demonstrator named Nose_2 was tested in the SCIROCCO Plasma Wind Tunnel. The architecture of the nose is shown in Figure 11. The basic idea of the Nose_2 design was to couple conventional C/SiC materials to novel Ultra-High Temperature ZrB2-SiC Ceramics (UHTC) in order to create a multi-material structure able to withstand the severe condition associated with slender-shaped hot structures and non-conventional reentry mission profiles. The nose is made of two main components: the tip and the dome.
The conical tip, which was intended to sustain the greatest thermal load in the whole nose cap structure, was made of ultra-high temperature ZrB2-SiC ceramic. The tip was produced by hot pressing sintering and then finished by EDM (Electrical Discharge Machining). The outer dome was made of C/SiC and has the shape of a hollow frustum of cone. It was manufactured by Polymer Infiltration and Pyrolis (PIP) process. A ZrB2-SiC coating, about 500 µm thick, was applied by Plasma Spray Deposition technique on the external surface of the outer dome to protect the fibres from oxidation.
The inner dome was made of graphite and its main function was to increase the thermal capacity of the system. A mechanical interface in AISI304 allowed the connection between the nose cap demonstrator and the Model Support System.
Finally, the coupling between tip and dome of the nose cap was guaranteed by a coupling pin in titanium alloy which was preloaded by a spring. One end of the pin was not axial-symmetric and it was introduced into the hole and then rotated by 90 degrees in order to ensure the contact. The coupling hole dimensions are the results of a sensitivity analysis (Ferraiuolo et al., 2008) performed with the aim to reduce stress concentration next to the coupling hole of the tip component and, at the same time, to reduce the massive volume taken away by spark erosion. The bend radius, the entire length and the diameter of the hole were chosen as parameters of the sensitivity analysis.
Schematization of tip-dome coupling
In Figure 12, the experimental data, in terms of temperature curves measured by an IR thermocamera along the nose profile and at several time steps, are shown. Experimental data were not available within the range [
The enthalpy (
The change in manufacturing process passing from coupon level to sub-component level makes it very difficult to determine some experimental parameters which are needed in numerical computations. One of these experimental parameters is the catalysis of the UHTC. Hence, in order to verify the influence of catalysis on the thermal behaviour of the nose cap, both the Non-Catalytic Wall (NCW) model and the Finite Rate Catalysis (FRC) one were used to compute heat fluxes acting on its external surface.
The heat flux distributions computed by using the two different catalysis models are shown in Figure 13 where the profile of the nose (red curve) is also represented. The stagnation heat flux, that is the heat flux computed for
Experimental temperature curves at several time steps
A 3D FE model (Figure 14) was built by using the FE commercial code ANSYS which was found able to deal with these thermo-mechanical problems. The heat flux distribution computed via CFD simulation was applied on the exposed external surfaces and, in order to reproduce the same conditions occurred in the PWT during the experimental test, heat fluxes were applied constantly for 72s, then they were set to zero to simulate the cooling. The duration and the heat fluxes magnitude are representative of a re-entry trajectory which was one of the requirements of the nose design. The radiation to the environment was taken into account in the FE model.
Heat flux distribution on the profile of the nose
In Figure 15 the numerical temperature curve, predicted on the tip profile and obtained by applying NCW heat fluxes, is compared to that one obtained by applying FRC heat fluxes. The plotted curves are predicted at time 50s of the simulation and they are compared to the experimental data registered at same time instant. The NCW model was found to provide better agreement with experimental data with respect to the FRC model and was adopted for the rest of this research work.
Section of the 3D FE model
After the test, in the post-processing phase, it was found that the dome surface temperature was higher than the tip surface temperature, though the heat flux acting on the tip was considerably higher as shown in Figure 13. In order to interpret so high temperatures measured on the dome surface, a numerical study was performed. Such study was just qualitative and was focused to the improvement of knowledge on the physical phenomenon under investigation. In particular, two different simulations, with two different assumptions
Comparison between numerical and experimental tip surface temperature at 50s.
on the modelling of the C/SiC-coating interface, were carried out. Comparison between temperatures predicted by the two simulations at time 70s and those measured during the test at the same time instant are shown in Figure 16. In the first simulation, the coating layer was assumed perfectly bounded to the C/SiC, hence it was not modelled because its thermal resistance was assumed negligible. The strong discrepancy between experimental temperatures measured at the outside of the dome and those predicted by this simulation justified further investigations to better understand how to model the C/SiC – coating interface. Therefore, in the second simulation the coating layer was assumed completely detached from the C/SiC, hence it was modelled by a thin surface completely not in contact with the C/SiC, in such a manner the coating was not able to transfer heat to the C/SiC by conduction but only by internal radiation.
Comparison between numerical and experimental dome surface temperature at 70s.
Temperatures predicted in the case of coating completely detached are closer to the experimental data with respect to those predicted in the case of perfect contact suggesting that most likely the contact between the coating and C/SiC during the PWT test was neither perfect nor completely separated but local detachments occurred in unknown regions of the interface. The wavy trend of the experimental temperatures confirms this hypothesis. Indeed, where the detachment occurred, the coating was not able to transfer heat to the C/SiC and a peak in temperature was measured by the IR thermocamera. On the other hand, where the contact was perfect, the heat was drained towards the inner dome and a lower temperature value was registered. Destructive inspections confirmed later that the coating was locally detached by the outer dome in several zones.
Further investigations were made during the rebuilding phase of a second PWT test performed on the same nose cap demonstrator (Borrelli et al., 2010). Experimental data were compared with numerical results in order to help in interpreting the experimental test itself. The knowledge on the physical phenomenon under investigation was greatly improved thanks to the synergy between numerical and experimental activities. In particular, a qualitative study of the modeling of the tip-dome interface was performed in order to estimate the thermal contact resistance that heat flux encounters in passing through the demonstrator. Modeling this interface as imperfect greatly improved the accuracy of the numerical predictions.
A brief introduction on the characteristics of a plasma wind tunnel facilities, as well as their performances and applications, was provided. Particular attention was given to the SCIROCCO PWT facility, that is the plasma wind tunnel developed by CIRA, which is the World’s most powerful ground test facility. Successively, each step performed for the success of a plasma wind tunnel test was examined in detail. In particular, the synergy between the experimental team and the numerical one in each step of the test procedure was stressed by providing explanatory examples.
The authors would like to thank the entire CIRA PWT staff for providing useful information needed to write this work.
The spread of COVID-19 has severely affected the well-being of many people. It is not only the health effects but also the containment measures related to the pandemic that affects the economy. FAO estimated that 720–811 million people suffered from famine worldwide in 2020, a 9.9% increase from the previous year [1]. Even in Thailand, which can produce more food than its domestic demand, and by 2020 was the 13th largest food exporter in the world [2], in the face of the COVID-19 pandemic, it was reported that people consume less food or face starvation [3] disclosing a concern about access that surpasses availability.
In every crisis, food security awareness is raised and suggestions are made on how to solve the problems and develop food systems to ensure survival for countries’ populations. Many different proposals for food security have been advocated, ranging from global, country, community, household, to individual levels [4, 5, 6, 7, 8]. There are seemingly opposite methods, such as market dependence or self-sufficiency [9], protection of domestic markets, and the liberalization of food trade [10, 11]. Players in the food system may be centralized or decentralized, and large or small entities [12, 13]. Food production knowledge and technology may be modern or indigenous [14, 15].
The objective of this chapter is to review and analyze the impact of the COVID-19 pandemic on food security in Thailand and review and analyze food system resilience and the challenges of building such resilience in a Thai context. Then, the Food Self-Sustained Community (FSSC) model will be discussed as an innovative approach to create community food system resilience and make communities competitive in normal times and self-reliant in food in times of crisis.
The conceptual framework developed for considering the impact of the COVID-19 crisis on food security in Thailand will be based on the relationship between food systems and food security. Food systems have the following elements and activities throughout the food supply chain:
factors of food production (the supply of agrochemicals, such as fertilizers and pesticides, as well as animal feeds, water, and agricultural credit)
food production (the methods by which agricultural products are produced, namely arable farming, horticulture, animal husbandry, fishery, and forestry),
food processing (the conversion of agricultural products into consumable food, such as food manufacturing, food preparation, and food preservation),
food stock, food markets, and trade (such as food distribution channels, food marketing and sales, food exports and imports, and food aid),
and food consumption (including consumption behavior, demand, and purchasing power).
These elements and activities are linked by food transportation, logistics, and finance [6, 16, 17, 18]. The four pillars of food security are food availability, food access, food utilization, and food stability [19].
Based on literature reviews [19, 20, 21, 22], this conceptual framework assumes that the elements and activities of food systems and food security are related as follows (Table 1)—factors of food production, food production, food processing, and food stock are related to food availability and stability, as they are related to the supply of food products. Food consumption is related to food utilization. Food stocks, markets, trade, logistics, and finance are correlated with food availability, access, and stability because they are activities that relate to food distribution. In addition, the four pillars of food security are also interrelated, for example, food production and food stock affect food availability and food price stability, which affects food accessibility.
Food System | Food Security | |||
---|---|---|---|---|
Availability | Access | Utilization | Stability | |
Factors of production | X | X | ||
Production and Process | X | X | ||
Stock | X | X | X | |
Market and Trade | X | X | X | |
Consumption | X | |||
Logistics and Finance | X | X | X |
Relationship between the food system and food security.
Note: Definitions of the four pillars of food security are based on FAO’s definition in “An Introduction to the Basic Concepts of Food Security,” 2008.
For the analysis of the impact of COVID-19 on the Thailand food system, the shocks on the food system are divided into four components—health crisis (the situation due to the outbreak), containment measures (pandemic control measures such as lockdown and the closing of borders), economic crisis (economic depression due to the effects of the outbreak and the containment measures), and the international situation and the response of foreign countries (Figure 1).
Framework for analysis—The impact of COVID-19 on food security.
An analysis of food system resilience will also follow the elements and activities of food systems, classified into three periods—pre-crisis, during the crisis, and post-crisis. The term “crisis” means situations where the food system malfunctions and poses a risk of food insecurity due to COVID-19 outbreaks and the responses from governments and other sectors. The pre-crisis food system resilience consists of the ability to prevent crises (prevention), preparedness to deal with the crises (preparation), and the pre-warning system. Food system resilience during a crisis consists of protection from the impact of the crisis (protection), mitigating the effects of the crisis (mitigation), adaptation to cope with the crisis (adaptation), and recovery. Post-crisis resilience analysis is unrealized. Therefore, the analysis is based on what has been learned (learning) by the authors to provide suggestions for improvement (transformation) of food system resilience in Thailand [23, 24, 25]. Other challenges affecting food system design are then analyzed, in particular the trade-off between the system goals and future risks for food security.
The COVID-19 outbreak in Thailand commenced in January 2020 and the government announced a nationwide lockdown and closed borders for the first time in late March 2020 (these measures were relaxed 3–4 months later). In the first wave of the outbreak, 4237 people were reported as infected. A second wave of the pandemic occurred from late 2020 to March 2021, affecting some areas of the country. As a result, lockdowns were announced for five provinces that had experienced outbreaks, with a total of 24,626 people reported to be infected. Later, a third wave occurred, in April 2021, resulting in the infection of more than 2 million people, as of December 2021 [26], and prompting the government to close down establishments, department stores, restaurants and announce the imposition of a curfew until the end of August 2021. The medical care and state quarantine systems were unable to cope with the situation, therefore, it was necessary to switch to home isolation by allowing those without severe symptoms to be treated at home [27]. The Omicron variant has caused a 4th wave of the Covid-19 outbreak in Thailand, with more infections after the new year 2022. However, the number of infections in the 4th wave was not as high as expected and the symptoms of those infected are less severe, and therefore, the government relaxed closures and containment measures. Figure 2 shows the level of measures taken by the Thai government to control COVID-19 in line with the severity of the outbreak [28, 29]. The pandemic and the government control measures have resulted in a generalized economic recession. These factors and situations have affected the food system and caused food insecurity in Thailand.
The Thai government’s responses to COVID-19 and daily new cases.
Note: The Containment and Health Index is a composite index that is calculated from 14 component indicators include eight indicators related to closures and containment measures (namely school closures, workplace closures, cancelation of public events, restrictions on gatherings, reductions in public transport, stay at home requirements, restrictions on internal movement, and International travel controls) and six indicators related to health measures (namely public information campaigns, testing policy, contact tracing, facial coverings, vaccination policy, and the protection of elderly people). The Economic Support Index is a composite index that is calculated from two component indicators related to economic measures namely, Income support and Debt/contract relief for households.
Data source: Hale, Thomas, Sam Webster, Anna Petherick, Toby Phillips, and Beatriz Kira (2020). Oxford COVID-19 Government Response Tracker, Blavatnik School of Government. Data use policy: Creative Commons Attribution CC BY standard.
The COVID-19 outbreak has caused an increase in the prices of imported production factors because of the imposition of restrictions to contain outbreaks of the virus. This has been especially the case in chemical fertilizers, which have seen large price increases since the middle of 2020, due to the reduced production of raw materials for fertilizer production and the increase in shipping costs due to container shortages for international shipping [30]. For example, the Urea price increased (in USD per metric ton) from $216 in May 2020 to $418 in September 2021.
Thailand is heavily dependent on imports of chemical fertilizers, which comprise almost all of the country’s total use [31]. This means that the country’s food system will be unable to avoid the impact of COVID-19.
Thailand’s agricultural sector faces a problem of labor shortage because most of the country’s farms are small and labor-intensive. They also employ a large number of foreign workers, often seasonal migrant labor [32]. The closure of the borders to contain COVID-19 caused foreign workers to panic and many left the country and were then unable to return to Thailand [33]. In the first 6 months of 2020, there was a reduction of around 545,000 foreign workers in Thailand or 18.2% of the total usual number of migrant workers in Thailand [34].
The agricultural sector is also at risk of a shortage of funding for the production of the next cultivation due to losses and lower household income. The increased cost of inputs, with a decrease in revenue due to reduced demand for food (because the lockdown measures have caused the economic recession and have limited the travel of foreign tourists), will cause food producers to suffer losses [35]. In addition, 76% of Thai agricultural households rely on nonagricultural income and 75% of the households have members working outside the agricultural sector [36]. Owing to the recession, nonagricultural workers now have lower incomes and there is increased unemployment. This will cause the total income of agricultural households to decrease as well.
The first wave of the COVID-19 outbreak caused the GDP of Thailand’s agricultural sector in 2020 to contract by 3.3% compared to the previous year [37]. Factors that contributed to the decline in agricultural GDP were border closure and lockdown measures [38]. However, effective control measures implemented in response to the first wave of outbreak increased the export of some food products, because Thai food products were trusted to be disease-free, while other food-producing countries had more severe outbreaks [39].
However, the second wave of the pandemic, which occurred at the end of 2020, centered on the fishing industry workforce cluster and the country’s large seafood wholesale market, severely affected seafood production and caused some countries to ban the import of seafood from Thailand [40]. Similarly, during the third wave of the pandemic outbreaks occurred in factories, including a large food-processing factory. As a result, the factories were shut down to disinfect and control the outbreak among workers, resulting in some food products being in shortage of supply for a period of time [41].
In the macro view (national scale), food production in Thailand is sufficient to meet the needs of the country’s people. But in the micro view (household and individual scales), some people face the problem of not having access to food. The risk of spreading disease in restaurants, wholesale and retail markets of agricultural products caused the government to announce the closure of these places from time to time to limit the spread of the pandemic, resulting in the blockage of the usual food distribution channels [42]. Although the government allowed restaurants and food shops to offer take-home and home delivery meals, home dining behavior resulted in lower consumption than eating at restaurants and food shops. In addition, at certain times COVID-19 also affected food price stability in Thailand. For example, the lockdown during the first wave of the outbreak resulted in soaring rice prices [43] and public anxiety led to food hoarding, resulting in short-term food shortages [42].
The border closure and lockdown measures greatly reduced food demand due to the disappearance of about 40 million foreign tourists and exports. The economic recession caused by the pandemic control measures resulted in many workers suffering a reduced income and unemployment. It is estimated that up to 6 million workers experienced a reduced income or unemployment [44], especially workers in the tourism sector. Affected people, especially the poor, unemployed workers, and vulnerable groups, have a reduced ability to buy food. A survey conducted by the International Health Policy Program found that as many as 85.4% of low-income residents in urban slums experienced food insecurity due to declining incomes, higher food prices, and difficulty in purchasing food [45]. Similarly, rural smallholder farmers engaged in monocultural agriculture were affected by the lack of channels to sell their produce. Reverse immigration of household members from the city to rural areas increased the pressure on rural households, due to increased household food needs [46]. These people experiencing economic hardships had to adjust their dietary habits by reducing their food consumption and switching to cheaper and less nutritious foods [45].
The COVID-19 crisis has affected the distribution of food by reducing the flow of food products and finance in the food system. Concerns about the spread of pathogens through food transport have increased costs in food safety control processes. The closure of food retail and wholesale markets has resulted in higher food transportation and distribution costs due to a lack of distribution centers [47]. Higher food logistics costs hinder access to food for people with lower incomes and lower their purchasing power.
The lockdown has also prevented some groups of people from accessing adequate and quality food because alternative food distribution channels have not been developed to replace the old channels that have been closed. For example, patients or people who are quarantined under the home isolation system have difficulty going out to buy food because the authorities require that they must be detained at home. However, no alternative food supply system was provided for this group of people [48]. Closing schools and replacing them with online learning means that schoolchildren in poor families are not able to enjoy quality school lunches. People suffering from malnutrition have been unable to receive nutrients from medical services in hospitals because doctors and nurses have heavy workloads from caring for COVID-19 patients and also due to the cutting of the public health budget allocated for other diseases [3].
The COVID-19 crisis has prompted a response from various sectors to intervene in the food system to address food insecurity and improve the adaptation of players and elements in the system. This section comprises a review and analysis of the status of food system resilience in Thailand, both before and during the crisis. Lessons obtained are then used to suggest changes to Thailand’s food system during the post-crisis period.
Thailand’s food system is at risk of uncertainty. The agricultural sector has the highest number of poor people compared to other sectors. In addition, in this sector, the elderly account for 46% of the total workers and this percentage is likely to increase [49]. Half of the country’s farmers do not own their land and 56% of farmers owning land possess less than 10 rai (4 acres) of land [50]. Land use for energy crops and nonagricultural activities is also increasing, and only 22% of agricultural land is irrigated [51]. Moreover, most agricultural activities are dependent on inputs from foreign producers and large domestic companies, such as producers of chemical fertilizers, pesticides, plant breeding, animal breeding, and animal feed [52].
In the past, the government has continuously issued various policies and measures to solve these problems, for example, taxation of land and buildings to reduce the problem of landholding without use; provision of the Sor Por Kor 4-01 agricultural land title deeds to the poor; re-zoning of agricultural land use and zoning of food crops and energy crops; and development of water management systems and expansion of irrigated areas [53, 54]. However, the solutions to the problems are still difficult to implement. As a result, alternative economy groups have offered food sovereignty as a solution as part of a campaign to enable small farmers to own food inputs independently of the monopoly of big business [55].
To cope with the COVID crisis, the government has taken measures to alleviate short-term shortages of production factors, such as a project to support subsidies for farmers, a moratorium on debt, a reduction of debt burdens, and extending the loan repayment period for Bank for Agriculture and Agricultural Cooperatives customers [56]. The border closure measure was relaxed temporarily to allow the importation of workers to work in the agricultural sector [34].
The lesson is that Thailand is at risk of facing food insecurity due to its high dependence on imports of food production factors from abroad, especially chemical fertilizers. At the national level, the development of the production capacity of agricultural inputs is therefore an answer to prevent shocks to the food system, such as the development of the domestic fertilizer industry or promoting organic agriculture to reduce the use of agrochemicals. At the base level, it is difficult for small-scale farmers to be self-reliant on all inputs. But if farmers cannot control or rely on themselves in terms of all the factors of production, there is a risk that food production will be disrupted in times of crisis.
Although Thailand can produce more food than the demand, the risk is that the agricultural sector has the lowest productivity compared to other sectors. The agriculture sector accounts for 30% of the workforce, but only 10% of GDP [57]. Most farmers are smallholders, resulting in low productivity because they cannot use high-priced machinery and have to rely on foreign unskilled workers. Most agriculture production is monoculture, resulting in low food diversity. Agricultural products in Thailand are concentrated on just 5 or 6 crops, some of which are non-food crops or those which are low in nutritional value. Vegetable farming occupies 0.9% of the total agricultural land use and concentrates on only eight types of vegetables [58]. In response, the government has promoted large farms to improve productivity and the use of agricultural technology. The Young Smart Farmer project was established to promote the new generation of farmers in the adoption of precision agriculture. On the other hand, some NGOs are trying to promote agroecological sustainable intensification [59].
Rural areas with diverse food production or a food security system that had been set up in advance were less affected by the crisis. Meanwhile, urban slums offer less food security than rural communities and rural smallholders who cultivate monocultures, and consequently, are affected to a greater extent. Some communities (such as the Karen community, Ban Pa Tung Ngam, Chiang Mai Province) were not seriously affected by the outbreak and lockdown measures because they had a self-sufficient production system and there was a system in place for those affected to receive assistance. For example, highland hill tribe communities consist of largely self-sufficient villages and have a culture of sharing food with the poor. These communities, in addition to producing enough food to consume in the community, can also share food with the people of other communities [60].
The outbreak also led to more qualitative improvements in food production, in particular a focus on the development of food safety standards [61]. Food production for export was also forced to develop safety and sanitation standards, especially fruit exports to China. In addition, the government requires large industrial plants to use “Bubble and Seal” measures to control the spread of the disease in factories [62]. This allows better control and limits the spread of the outbreak, but creates higher costs for entrepreneurs as well.
The lesson is that the economy of scale is important to the competitiveness of food production, but the economy of scope is essential to food availability and utilization. A community that can produce its own food will be less affected by unexpected shocks than communities that are unable to produce food at all. And communities that are prepared in advance are better able to cope with crises than communities that are not ready. Development of the resilience of the food system must be done before the crisis.
Under normal circumstances, the market mechanism plays a role in ensuring food availability, stability, physical access to food through the reserve, distribution, and trade of food. Food access channels for consumers in Thailand are diverse, ranging from modern trade, e-commerce, community markets, and hawker stalls to mobile grocery stores. However, the channels through which farmers can sell their food products directly to customers and retailers are still limited. The controversy about the market system of agricultural products in Thailand concerns oligopoly or exploitation by middlemen or large businesses. Big agribusinesses will purchase food products only on a contract farming basis with the condition that the farmers must purchase all their inputs from those businesses. On the other hand, the big agribusinesses argue that the mechanism is like a service and a marketing guarantee to farmers, most of whom lack marketing capabilities [63, 64].
The COVID crisis has led to community adaptation. Community markets have been established on a local level by members of local communities for farmers to bring their products to sell locally, while some farmers have adapted to selling food products directly to consumers through networks of relatives and friends in cities and online systems or online marketplaces [65]. Meanwhile, some communities (such as Ban Pa Pae, Mae Hong Son Province) had already prepared food reserve systems to ensure that community members do not have shortages of the food products they need in times of crisis. For example, community food banks or rice banks, where people in the community stored rice in a collective barn for members to borrow for consumption, on the condition that it must be returned in kind, or as money, with interest in the following year [66].
According to economic theory, fully competitive markets make food allocation and distribution more efficient. However, the agricultural markets in Thailand are not truly competitive [67]. Moreover, crises tend to affect food markets, to a greater or lesser extent. Therefore, having a food reserve system is essential for maintaining food security at all levels. In addition, the development of marketability, alternative channels, and reserve channels in selling the products of farmers and food producers are important steps, to create continuity in food production for smallholders and reduce food waste caused by unsold products.
The food access situation in Thailand is determined by economic factors rather than social factors. Thailand has reduced the number and proportion of the poor continuously. The number of people living below the poverty line has continued to decline from 34 million, or 65.17% of the country’s total population in 1988, to 4.3 million, or 6.24% in 2019, but there are still 5.4 million near-poor people or 7.79% of the country’s population. The Thai government has provided income benefits that are quite inclusive for nearly all groups, from child support subsidies up to the age of 6, school lunch subsidies, a pension for the elderly and the disabled, to a living allowance for the 14.5 million people who hold state welfare cards. Still, these programs provide a relatively limited amount of funding. Moreover, the identification of the poor is not entirely accurate, with inclusion and exclusion errors [68].
The response to the impact of COVID-19 on food security in Thailand has emphasized the role of the government sector and demand-side interventions. For affected workers who are in the formal economy, unemployment compensation and cash transfer from the Social Security Fund will be provided. But Thailand also has a large number of informal workers, comprising around 54% of the labor force [69]. The government therefore issued economic remedial measures to address the impact of the pandemic and lockdown measures, including cash transfers, conditional cash transfers, reductions in public utility costs, a debt moratorium, and expansion of soft loans for businesses to maintain employment and maintain people’s ability to access food.
However, the government aid measures are not enough. Most of them are short-term measures, lasting only 2–3 months during the lockdown. But the economic recession has caused a large number of people to be unemployed and revenues have declined for a longer duration than just during the lockdown period. During the first wave of the pandemic, 30.5 million people, or 40% of the country’s population, received cash transfers. However, even though the government’s cash transfer measures have covered a large number of people, as many as 3 million people are still missing out on the state aid measures. These include marginalized people, bedridden patients, and those who cannot register for assistance [70].
The lesson is that tackling poverty and inequality including income insurance (unemployment insurance) is an important factor in reducing the impact of the crisis and maintaining people’s ability to access food. But a large number of informal workers creates asymmetric information problems, which prevents governments from helping people affected by food shortages. It also forces governments to take universal measures, which is ineffective in budgeting. The question is, for a developing country like Thailand with a large informal economy, how can the lack of information and income insurance for the poor, marginalized, and other vulnerable groups be solved?
Thailand lacks planning or preparation of systems for dealing with different types of crises, in particular, a system for allocation of aid and distribution of food and necessities to those affected by crises sufficiently and thoroughly. In several past crises, government measures to address food insecurity have been often ad hoc and failed to provide food for all of these vulnerable groups. Businesses and civil societies, therefore, had to come in and fill the gaps in food systems. However, it was often scattered, redundant, lacking in continuity and organization [71].
The cooperation of government, business, and civil society has a role to play in closing the gaps in state measures that are inaccessible to some vulnerable groups. Civil society organizations that were taking care of vulnerable groups before the crisis play an important role in providing food through community kitchens and food banks to groups that often do not have access to government aid measures [72]. Networks of civil society organizations also play a role in matching food supply and demand, by purchasing food from smallholder farmers who are unable to sell their products for sale or distribution to people who need food [73]. Likewise, the armed services, including the air force and army, help facilitate food exchanges between far-flung communities, for example, using planes to transport rice products from hill tribe communities in the north in exchange for dried fish, which is a food product of maritime communities in the south [74].
Business organizations’ Corporate Social Responsibility activities include the distribution of supplementary food to different groups of people, as well as encouraging people to participate in food donation campaigns. One form of food donation that was very popular in the first wave of the outbreak was “Happiness-sharing Pantries”, placing cupboards in public places for people to donate or pick up food to consume [75]. However, the assistance was done by various groups of people in an
The lesson is that cooperation between government, business, and people sectors is essential to building food security, especially the provision and delivery of food to vulnerable groups. A civil society organization that works closely with a particular community on an ongoing basis will access information on vulnerable groups and will serve as a mechanism that allows food to be delivered to those people who are in real need. But in the macro view, information systems about vulnerable groups and food aid delivery system design are required to make assistance available to everyone. Moreover, ensuring people’s food security should not be merely seen as a relief, but should also develop food self-reliance.
Building food system resilience for food security in Thailand also faces challenges due to a trade-off, or conflict, between several issues, described in the following section.
Controversies about food systems inevitably emerge during every crisis, when difficulties are created and many people are exposed to food insecurity risks. Proposals on the food system in Thailand vary between the two extremes of a continuum, self-sufficiency and free trade. The main controversy focuses on whether the Thai agricultural system should be one of market agriculture, which focuses on production for sale in response to market demand, or self-sufficiency agriculture, which focuses on production for one’s own consumption. If there is any leftover produce, then this can be sold [4].
The supporting rationale for the market-based production system is to create wealth through specialized production, which enables efficient use of economic resources. Market-based production provides food security because food production increases and prices are lower while consumers still have access to a variety of quality food through market mechanisms [77]. The potential negative aspect of this is that farmers who do not improve productivity could suffer lower incomes, putting them at risk of food insecurity.
However, it is argued that, under normal circumstances, the system of global food trade is not fully free and competition is not fair due to the implementation of measures to protect domestic agricultural markets and subsidize farmers within developed countries. In times of crisis, market mechanisms may fail, to the extent that farmers cannot rely on outside markets. Market-based production also makes the structure of food production homogenous. This makes it more dependent on food imports from foreign countries or from outside the area, which then increases the risk of food insecurity [78].
On the other hand, self-sufficiency production focuses on producing more diverse foods, which reduces the risk of food insecurity [79, 80]. The self-sufficiency production system also focuses on mixed farming and animal husbandry by imitating nature, resulting in high quality and safe food production. It also creates food sovereignty by reducing dependency on imports and inputs from large companies and maintaining the fertility of the soil, as well as water and ecosystems. However, the efficiency, competitiveness [81], and producer motivation of self-sufficiency production have been questioned, because it is seen as requiring farmers to adopt a plain lifestyle without many amenities.
There is a question about what level the unit of analysis on food security should be: individual, household, community, national or global. In the past, the food security concept emphasized a unit of analysis at the macro level, considering global or national food security. This can be observed from definitions, debates, policies recommendations, and the design of food security indicators, which generally focus on the national or international context, for example, the debates about whether to liberalize food trade or not and the development of international comparative food security indicators. Subsequently, there has been an increase in interest in food security at the micro level, that is at the community, household, and individual scales [14, 82].
Macro-level food security will ensure everyone in the world or an individual country has the opportunity for food security, but that does not mean it will always lead to micro-level food security, especially in times of crisis where food transport is limited or market systems have failed. Emphasis on achieving food self-sufficiency at the national level may distract governments from addressing food security at the household level [83]. Ensuring macro-level food security is often the role of the state, but, in practice, governments are often unable to ensure food security for all citizens because too large a unit creates asymmetric information problems. On the other hand, micro-level food security practices will help fill gaps that the government has failed to cover and alleviate the burden on the government [84]. There is still an argument that it is not possible, even at a national level, to be self-sufficient in all types of food [85]. The question is what is the optimal size of the analytical unit? Is it small enough to ensure that everyone is cared for and large enough to provide adequate food in terms of quality and quantity? In fact, food security at the household and individual levels cannot be guaranteed without national food security. Therefore, building food security may need to be undertaken at all levels but the question is how each level of food security should be organized.
A common phenomenon in Thailand is that the countryside serves as a social cushion in times of crisis. Under normal circumstances, many rural people migrate to cities in search of the better economic opportunities that they offer in comparison to rural areas. But every time there is a severe crisis, to survive, people migrate back to their rural homelands [86, 87]. This can be seen in the COVID-19 crisis, where, in the first wave of the outbreak in February–April 2020, it is estimated that 2 million people migrated back to the countryside, and, in the second half of 2020, a monthly average of 200,000 migrated back to the countryside [46]. However, this does not mean that everyone in the city has a country house to migrate back to. Consequently, many people in crisis-affected cities are still at high risk of food insecurity.
At present, the idea of urban farming is gaining more and more attention. But there is a question regarding whether it is necessary for households or urban communities to produce their own food. The price of land in the city is high, therefore, urban food production has a very high opportunity cost compared to rural food production. However, urban food production has advantages in terms of transportation and logistics costs. Would using urban land to produce food be more cost-effective than buying food from the countryside? On the contrary, if there is no preparation for hedging at all, urban communities will also suffer a lot of damage when a severe crisis occurs.
An interesting question is what should be the cost of hedging for food insecurity risks? The risk management principle states that the cost of hedging is equal to the likelihood of a crisis multiplied by the impact of the crisis. In history, severe crises are likely to occur only occasionally, or infrequently, but if they happen, the impact is so severe that there are many deaths. However, the changes in today’s world may be a catalyst for more frequent crises and increase the need for hedging.
Chareonwongsak [88] states that the world has entered the “Pandemic New Normal” era, where pandemics will become more frequent so that it becomes a new normal. The world is more connected and more people live in cities, making pandemics easier to occur and spread faster. This is consistent with the “IPBES Workshop Report on Biodiversity and Pandemics,” which indicates that future pandemics will occur more frequently, spread faster, and inflict more damage [89]. There is the possibility of a black swan or an unprecedented crisis because there are new predisposing factors, such as severe climate change and cyber-attacks on countries’ financial systems or food chains [90].
The fact that Thailand is a food producer and net exporter makes food security issues seem less of a concern. But the spread and impact of COVID-19 have helped to reveal the fact that the food system in Thailand is still vulnerable to food insecurity for many people. It also reveals the country’s under-preparedness to deal with crises. The weakness in the Thai food system is that the Thai government lacks information about people at risk of food inaccessibility due to the large proportion of informal workers while most of the workers in developed countries are formal workers. The government mainly uses macro-level measures, namely cash transfer, to address food inaccessibility. But there is a lack of an alternative system to distribute food to people who have not received help. In a world where crises are more frequent, food system resilience needs to be built to face crises of all forms and levels of severity as well as maintain food security for everyone, therefore, an innovative food system model is required. The food system must be developed at both the macro and micro levels and have the ability to maintain food security in both normal and critical times without exorbitant cost.
The FSSC model presented in this chapter is a proposal for developing food system resilience to protect food security in Thailand. This concept developed from a stream of several concepts—the Mid-stream economy [91], Self-sustained communities [92], and the Linked self-sustained communities [92], applying these concepts in the context of building food security.
This concept stream consists of four main components. First, strength-based production and liberalization of food trade to create wealth during normal times. Second, self-sufficiency in food in times of crisis and at all levels. Third, preparation of a switching mechanism/policy design for readiness in changing the mode, between liberalization in normal situations and self-sufficiency in times of crisis. And fourth, the interconnection of food systems between communities and between all levels to ensure food security at both micro and macro levels.
The development of the FSSC aims to make area-based communities self-sufficient in food in times of crisis for a number of reasons.
First of all, future crises could limit domestic and international food trade and transport. For example, a hyper-inflation crisis or a cyber-attack on the financial system of the country or the world could make it impossible to use the money to buy food. Future pandemic crises could also force governments to use lockdown measures and close borders.
Secondly, the food system at the household level is usually too small to be self-sufficient in food. Meanwhile, countries are too large to be aware of all information and to allocate timely assistance to all people during crises. Therefore, a community that is not so small that it cannot be self-sufficient, or so large that members are not related to each other, is the right unit to maintain food security in times of crisis.
Thirdly, building food security in communities in times of severe crises (which lead to food system failures through wars, disasters, hyperinflation, and similar events) must temporarily integrate all food system activities in the community, to shorten the food supply chain and to build the ability to supply enough food to the people in the community for a given period of time.
Fourth, communities should be self-sufficient in food only in times of crisis in order not to lose the opportunity to create wealth from carrying out economic activities according to the strength of the community during normal times.
The creation of the FSSC has the following strategic proposals:
FSSCs may be built on the base of existing area-based communities or create new ones by bringing together groups of people who are related and share the common intent to create an FSSC. FFSCs may develop on the concept of Work-Life Integration [93], by creating communities that facilitate people working and living in the same area, as well as the benefit of preventing the effects of epidemics that may occur in the future.
Ensuring that communities have enough food in times of crisis must come from setting goals. How many members does the community have? How much food, and how many different types are needed? How long should a community supply food to its members during a crisis? Communities must design and plan in advance where, in times of crisis, they will get their food from, what to produce, how to produce, how much, how to stock input and food products, and how to allocate food products to community members. However, the design of a community food system requires consideration of the conditions, constraints, and context of each community.
FSSC may be the solution to the problems in the Thai agricultural sector with many small farmers and elderly workers. FSSC promotes the integration of agricultural farms for joint production planning, procuring, and sharing inputs and resources, including the use of technology and agricultural machinery together which will create an economy of scale. At the same time, farmers in the FSSC may plan to produce a variety of yields to distribute products together and share revenues together. This will allow the community to produce a variety of food products. It also creates an economy of scope and diversification of risks.
Developing FSSCs to be able to switch to self-sufficiency, community systems, and infrastructures needs to be done in advance, such as community water storage, community seed banks, community gardens, community alternative energy generation systems, community food banks, community markets and food allocation systems, community data management and information systems (such as projections for production, stock, and community food needs), and community savings promotion and welfare systems.
FSSC’s food production may be unique and differ according to the context and limitations of each community. In times of crisis, where communities cannot rely on sources or agents outside the community, the FSSC food production system tends to be a closed-loop food system, where the outputs and waste from one activity are inputs to other activities until it becomes a cycle or ecosystem. Food production in urban communities with limited space, technology, and methods needs to be developed to optimize the use of space. Also, training for members of the FSSC and the promotion of food system-related R&D in the FSSC needs to be supported.
In normal times, each FSSC should have a development and production approach that matches the strengths of the community. Each FSSC development should not have the same pattern or produce the same goods and services over and over. But each community should be developed according to its strength, ideology, wisdom, identity, value, image, and uniqueness. Thus, each FSSC will have a unique selling point that will enable it to create more added value for its products and services. Then, a strong economy in a community can also be a better shield against the impact of a crisis.
The FSSC food system should be developed to be as competitive as possible under normal conditions to enable the FSSC to be able to produce and sell food continuously, without much subsidization or intervention. However, during normal times, it is not necessary for every FSSC to produce all its own food requirements. But a switching mechanism must be designed and prepared to be able to supply food to the entire community in the event of a crisis, such as preparation of a community food reserve system, transformation of vacant spaces in communities and individual households into food production areas, changing the type of food produced to be more versatile, faster yielding, changing cultivation methods for higher yields (despite the fact that the product characteristics may not be as beautiful as before, such as smaller fruits, thinner vegetables), etc. The switching mechanism encompasses the development of leadership, management, morals, and community systems such as structure, processes, rules, and culture that encourage community members to be willing to switch to a self-sufficiency mode.
In fact, it is unlikely that each community will be able to produce food for its own consumption forever without having to rely on the world outside the community at all. Therefore, FSSCs should establish a network to link with other FSSCs and to enable the trading, exchange, and sharing of knowledge, resources, products, and risks. For example, food production planning between communities, the development of food supply chains between communities, the development of food logistics, information and finance between communities, the organization of knowledge sharing and resources among the communities, and the development of food exchange and sharing systems among communities in times of crisis. The link between FSSCs will help support the development of communities in normal times and increase the ability to self-sufficiency and restoration of the community’s food system in times of crisis.
Governments should develop national policies to promote FSSC, including academic and financial support for FSSC transformation, developing prototypes and learning centers for FSSC in both urban and rural areas, designing urban development and building a community that integrates both workplaces and living facilities in the same area, land use planning and zoning of food production, developing information systems for food system management at the national level, developing early warning systems, developing public-private cooperation systems for food production and distribution in a systematic, thorough and continuous manner, developing international food security cooperation, and the development of food diplomacy.
The COVID-19 crisis has affected food security and revealed the shortcomings of the food system in Thailand. The FSSC is an innovative idea resulting from the synthesis of the good points of various food economy systems, with the aim of ensuring food security in both normal and critical times. The development of FSSCs also emphasizes preparation to prevent the impact of crises on food insecurity in communities without creating excessive expenses or opportunity costs. In normal times, FSSCs can also connect to the global market to produce goods and services according to their strengths to create wealth. But communities are designed to be ready to adapt to self-reliance in times of crisis.
However, the FSSC model is still just a concept and it has never been implemented in practice. In addition, the concept development took place from the consideration of Thailand’s context, which is a country capable of producing enough food to meet overall domestic demand. Therefore, in applying this concept to other countries with different contexts, it is necessary to adapt it appropriately to the local context. Developing FSSCs involves not just the design of food systems, but the design of communities, which is more complicated because it has to take into account the economic, societal, and political dimensions in each community and also the motivational dimensions, relationships, and other dimensions of human beings. Finally, the FSSC model also needs studies, research, and experimental development of the prototype to improve the model for practical application.
The FSSC model and its associated thoughts have overlays and differentiated parts from City Region Food Systems (CRFS) supported by RUAF [94]. Both concepts have the same goals, namely food security, sustainable development, economic development, and social inclusion and equity. FSSC has a focus on improving area-based community food security and extending communities’ connectivity. CRFS focuses on improving the food security of the city-center food system that is linked to the surrounding area. By successfully pushing the FSSC model, it is possible to learn from the CRFS, for example, building cooperation and inclusive participation, formulating an academic-based development strategy and taking into account the context of the food system in each area, developing the capacity of individuals and organizations involved, and building effective systems to drive the development.
The author acknowledges the support of the Nation-Building Institute and Institute of Future Studies for Development.
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Liu"},{id:"23596",title:"Prof.",name:"Tieli",middleName:null,surname:"Sun",slug:"tieli-sun",fullName:"Tieli Sun"}]},{id:"12652",doi:"10.5772/13281",title:"Auction and Swarm Multi-Robot Task Allocation Algorithms in Real Time Scenarios",slug:"auction-and-swarm-multi-robot-task-allocation-algorithms-in-real-time-scenarios",totalDownloads:2512,totalCrossrefCites:7,totalDimensionsCites:10,abstract:null,book:{id:"11",slug:"multi-robot-systems-trends-and-development",title:"Multi-Robot Systems",fullTitle:"Multi-Robot Systems, Trends and Development"},signatures:"Gabriel Oliver and José Guerrero",authors:[{id:"14005",title:"Dr.",name:"Gabriel",middleName:null,surname:"Oliver",slug:"gabriel-oliver",fullName:"Gabriel Oliver"},{id:"14267",title:"Dr.",name:"José",middleName:null,surname:"Guerrero",slug:"jose-guerrero",fullName:"José Guerrero"}]},{id:"12637",doi:"10.5772/13241",title:"Multirobot Cooperative Model Applied to Coverage of Unknown Regions",slug:"multirobot-cooperative-model-applied-to-coverage-of-unknown-regions",totalDownloads:2262,totalCrossrefCites:6,totalDimensionsCites:9,abstract:null,book:{id:"11",slug:"multi-robot-systems-trends-and-development",title:"Multi-Robot Systems",fullTitle:"Multi-Robot Systems, Trends and Development"},signatures:"Eduardo Gerlein and Enrique Gonzalez",authors:[{id:"14177",title:"Dr.",name:"Enrique",middleName:null,surname:"Gonzalez",slug:"enrique-gonzalez",fullName:"Enrique Gonzalez"},{id:"14178",title:"Ing.",name:"Eduardo",middleName:null,surname:"Gerlein",slug:"eduardo-gerlein",fullName:"Eduardo Gerlein"}]}],mostDownloadedChaptersLast30Days:[{id:"68525",title:"Architecture of a Microgrid and Optimal Energy Management System",slug:"architecture-of-a-microgrid-and-optimal-energy-management-system",totalDownloads:1043,totalCrossrefCites:2,totalDimensionsCites:2,abstract:"With the growing population trends, the demand for electricity is accelerating rapidly. The policy planners and developers have great focus to utilize renewable energy resources (RERs) to encounter the scarcity of energy since they offer benefits to the environment and power systems. At present, the energy generation is evolving into a smart distribution system that assimilates several energy resources assuring to generate clean energy, to have reliable operational procedures, and to enhance the energy supervision and management arrangements. Therefore, the model of a distributed microgrid (DMG) with optimal energy management strategies based on multi-agent systems (MASs) technique has been focused in this chapter. Distributed energy resources (DER) have been considered for the generation of electrical power to fulfill the consumer’s load demands. Thus, a fully controlled architecture of a grid along with concept of MAS and its development platforms, implementation, and operational procedures have been discussed in detail. In addition, agent’s operations and their coordination within the MG arrangements have been focused by considering the supervision of the entire system autonomously. Moreover, optimal procedures of a microgrid (MG) energy supervision and power distribution system have also been presented considering the cost control and optimal operations of the entire MG at the distributed level.",book:{id:"8872",slug:"multi-agent-systems-strategies-and-applications",title:"Multi Agent Systems",fullTitle:"Multi Agent Systems - Strategies and Applications"},signatures:"Muhammad Waseem Khan, Jie Wang, Linyun Xiong and Sunhua Huang",authors:[{id:"293464",title:"Dr.",name:"Muhammad Waseem",middleName:null,surname:"Khan",slug:"muhammad-waseem-khan",fullName:"Muhammad Waseem Khan"},{id:"307966",title:"Prof.",name:"Jie",middleName:null,surname:"Wang",slug:"jie-wang",fullName:"Jie Wang"},{id:"308072",title:"Dr.",name:"Linyun",middleName:null,surname:"Xiong",slug:"linyun-xiong",fullName:"Linyun Xiong"},{id:"308073",title:"Dr.",name:"Sunhua",middleName:null,surname:"Huang",slug:"sunhua-huang",fullName:"Sunhua Huang"}]},{id:"70172",title:"Applications of Multi-Agent System in Power System Engineering",slug:"applications-of-multi-agent-system-in-power-system-engineering",totalDownloads:926,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Power system needs a continuous upgrade to overcome the challenges like distributed control, self-healing, power quality, demand side management and integration of renewable system. At present, power system needs an advance and intelligent technology to perform various system level tasks. Centralized control of the system has efficient operation during integration of the renewable resources and lag of communication between the stations. Smart grid provides the intelligent and efficient power management system. Upgrade of present power system with multi-agent system (MAS) provides the solution for most of the power system issues. More number of MAS are used in the power system network based on acquires of the system. MAS are communicating with each other for the more acquired result. Better implantation of MAS can achieved by providing the high speed and secured communication protocol. In this chapter, we discussed about the MAS fundamental architecture and intelligent controller design tools and case study of real time tariff management using MAS.",book:{id:"8872",slug:"multi-agent-systems-strategies-and-applications",title:"Multi Agent Systems",fullTitle:"Multi Agent Systems - Strategies and Applications"},signatures:"G.S. Satheesh Kumar and S. Tamil Selvi",authors:[{id:"292525",title:"Mr.",name:"Satheeshkumar",middleName:null,surname:"G S",slug:"satheeshkumar-g-s",fullName:"Satheeshkumar G S"},{id:"293451",title:"Ms.",name:"Tamil",middleName:null,surname:"Selvi S",slug:"tamil-selvi-s",fullName:"Tamil Selvi S"}]},{id:"12646",title:"Time-Invariant Motion Planner in Discretized C-Spacetime for MRS",slug:"time-invariant-motion-planner-in-discretized-c-spacetime-for-mrs",totalDownloads:2125,totalCrossrefCites:2,totalDimensionsCites:3,abstract:null,book:{id:"11",slug:"multi-robot-systems-trends-and-development",title:"Multi-Robot Systems",fullTitle:"Multi-Robot Systems, Trends and Development"},signatures:"Fabio Marchese",authors:[{id:"13536",title:"Ph.D.",name:"Fabio",middleName:"Mario",surname:"Marchese",slug:"fabio-marchese",fullName:"Fabio Marchese"}]},{id:"68568",title:"A Q-Learning-Based Approach for Simple and Multi-Agent Systems",slug:"a-q-learning-based-approach-for-simple-and-multi-agent-systems",totalDownloads:670,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"This study proposes different machine learning-based solutions to both single and multi-agent systems, took place on a 2-D simulation platform, namely, Robocode. This dynamic and programmable platform allows agents to interact with the environment and each other by employing a variety of battling strategies. Q-Learning is one of the leading and popular machine learning-based solutions to be applied to such a problem. However, especially for continued spaces, the control problem gets deeper. Essentially, one of the main drawbacks of reinforcement learning (RL) is to design an appropriate reward function that the function can be described by only employing few parameters for simple tasks, whereas estimating the goal of the reward function may be a challenging problem. Recent studies prove that neural network-based approaches can handle these challenges and achieve to learn control strategies from 2-D or 1-D data. Besides those problems of RL algorithms for single robots, once the number of robots increases and the systems need to behave as multi-agent systems, the overall design requirements become more complex. Accordingly, the proposed system is validated by considering different battle scenarios. The performance of the Q-Learning-based system and the supervised learning techniques are compared by employing different scenarios for this problem. Results reveal the superiority of the ANN-based approach over other methods.",book:{id:"8872",slug:"multi-agent-systems-strategies-and-applications",title:"Multi Agent Systems",fullTitle:"Multi Agent Systems - Strategies and Applications"},signatures:"Ümit Ulusoy, Mehmet Serdar Güzel and Erkan Bostanci",authors:[{id:"168131",title:"Dr.",name:"Mehmet",middleName:"Serdar",surname:"Guzel",slug:"mehmet-guzel",fullName:"Mehmet Guzel"},{id:"296744",title:"Dr.",name:"Ümit",middleName:null,surname:"Ulusoy",slug:"umit-ulusoy",fullName:"Ümit Ulusoy"},{id:"296745",title:"Dr.",name:"Erkan",middleName:null,surname:"Bostanci",slug:"erkan-bostanci",fullName:"Erkan Bostanci"}]},{id:"70262",title:"Multi-Agent Systems Based Advanced Energy Management of Smart Micro-grid",slug:"multi-agent-systems-based-advanced-energy-management-of-smart-micro-grid",totalDownloads:807,totalCrossrefCites:1,totalDimensionsCites:3,abstract:"Microgrids play a major role in enabling the widespread adoption of renewable distributed energy resources. However, as the power generated from renewable resources is intermittent in nature, it impacts the dynamics and stability of the microgrid, and hence their integration needs new approaches to coordination and control. The existing systems lack run-time adaptive behavior. To face these constraints, the electric energy system must adapt by integrating Information and Communication Technologies (ICT). Multiagent system (MAS) is emerging as an integrated solution approach to distributed computing, communication, and data integration needs for smart grid application. Distributed and heterogeneous information can be efficiently processed locally, but utilized globally to coordinate distributed knowledge networks, resulting in reduction of information processing time and network bandwidth. Parallel operations, asynchronous communication, and autonomous actions of agents enable MAS to adapt to dynamic changes of the environment, thereby improving the reliability, responsiveness, fault tolerance, and stability of the microgrid. In this chapter, MAS is implemented with Java Agent DEvelopment (JADE) framework for advanced energy management of a microgrid. Also, MAS is linked with Arduino microcontroller for practical verification of agent operations. Three microgrids are interconnected to form a microgrid testbed, and smart grid features such as demand side management and plug and play are implemented, making it into a smart microgrid.",book:{id:"8872",slug:"multi-agent-systems-strategies-and-applications",title:"Multi Agent Systems",fullTitle:"Multi Agent Systems - Strategies and Applications"},signatures:"Leo Raju and Antony Amalraj Morais",authors:[{id:"296152",title:"Dr.",name:"Leo",middleName:null,surname:"Raju",slug:"leo-raju",fullName:"Leo Raju"},{id:"308984",title:"Mr.",name:"Antony Amalraj",middleName:null,surname:"Morais",slug:"antony-amalraj-morais",fullName:"Antony Amalraj Morais"}]}],onlineFirstChaptersFilter:{topicId:"1263",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:8,limit:8,total:0},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:89,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:104,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:32,numberOfPublishedChapters:318,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:12,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:11,numberOfPublishedChapters:141,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:8,numberOfPublishedChapters:129,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:113,numberOfOpenTopics:3,numberOfUpcomingTopics:1,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:106,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:2,numberOfUpcomingTopics:1,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:5,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:0,numberOfPublishedChapters:15,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:null,doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/3.jpg",latestPublicationDate:"May 13th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:8,editor:{id:"419588",title:"Ph.D.",name:"Sergio",middleName:"Alexandre",surname:"Gehrke",slug:"sergio-gehrke",fullName:"Sergio Gehrke",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000038WgMKQA0/Profile_Picture_2022-06-02T11:44:20.jpg",biography:"Dr. Sergio Alexandre Gehrke is a doctorate holder in two fields. The first is a Ph.D. in Cellular and Molecular Biology from the Pontificia Catholic University, Porto Alegre, Brazil, in 2010 and the other is an International Ph.D. in Bioengineering from the Universidad Miguel Hernandez, Elche/Alicante, Spain, obtained in 2020. In 2018, he completed a postdoctoral fellowship in Materials Engineering in the NUCLEMAT of the Pontificia Catholic University, Porto Alegre, Brazil. He is currently the Director of the Postgraduate Program in Implantology of the Bioface/UCAM/PgO (Montevideo, Uruguay), Director of the Cathedra of Biotechnology of the Catholic University of Murcia (Murcia, Spain), an Extraordinary Full Professor of the Catholic University of Murcia (Murcia, Spain) as well as the Director of the private center of research Biotecnos – Technology and Science (Montevideo, Uruguay). Applied biomaterials, cellular and molecular biology, and dental implants are among his research interests. He has published several original papers in renowned journals. In addition, he is also a Collaborating Professor in several Postgraduate programs at different universities all over the world.",institutionString:null,institution:{name:"Universidad Católica San Antonio de Murcia",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:8,paginationItems:[{id:"7",title:"Bioinformatics and Medical Informatics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/7.jpg",editor:{id:"351533",title:"Dr.",name:"Slawomir",middleName:null,surname:"Wilczynski",slug:"slawomir-wilczynski",fullName:"Slawomir Wilczynski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000035U1loQAC/Profile_Picture_1630074514792",biography:"Professor Sławomir Wilczyński, Head of the Chair of Department of Basic Biomedical Sciences, Faculty of Pharmaceutical Sciences, Medical University of Silesia in Katowice, Poland. 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He completed a one-year Post-Doctoral Fellowship awarded by the DFAIT (Foreign Affairs and International Trade Canada) at the Institute of Biomedical Engineering of the University of New Brunswick (Canada) in 2010. Currently, he is Professor in the Faculty of Electrical Engineering (UFU). He has authored and co-authored more than 200 peer-reviewed publications in Biomedical Engineering. He has been a researcher of The National Council for Scientific and Technological Development (CNPq-Brazil) since 2009. He has served as an ad-hoc consultant for CNPq, CAPES (Coordination for the Improvement of Higher Education Personnel), FINEP (Brazilian Innovation Agency), and other funding bodies on several occasions. He was the Secretary of the Brazilian Society of Biomedical Engineering (SBEB) from 2015 to 2016, President of SBEB (2017-2018) and Vice-President of SBEB (2019-2020). He was the head of the undergraduate program in Biomedical Engineering of the Federal University of Uberlândia (2015 - June/2019) and the head of the Centre for Innovation and Technology Assessment in Health (NIATS/UFU) since 2010. He is the head of the Postgraduate Program in Biomedical Engineering (UFU, July/2019 - to date). He was the secretary of the Parkinson's Disease Association of Uberlândia (2018-2019). Dr. Andrade's primary area of research is focused towards getting information from the neuromuscular system to understand its strategies of organization, adaptation and controlling in the context of motor neuron diseases. His research interests include Biomedical Signal Processing and Modelling, Assistive Technology, Rehabilitation Engineering, Neuroengineering and Parkinson's Disease.",institutionString:null,institution:{name:"Federal University of Uberlândia",institutionURL:null,country:{name:"Brazil"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"49517",title:"Prof.",name:"Hitoshi",middleName:null,surname:"Tsunashima",slug:"hitoshi-tsunashima",fullName:"Hitoshi Tsunashima",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYTP4QAO/Profile_Picture_1625819726528",institutionString:null,institution:{name:"Nihon University",institutionURL:null,country:{name:"Japan"}}},{id:"425354",title:"Dr.",name:"Marcus",middleName:"Fraga",surname:"Vieira",slug:"marcus-vieira",fullName:"Marcus Vieira",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003BJSgIQAX/Profile_Picture_1627904687309",institutionString:null,institution:{name:"Universidade Federal de Goiás",institutionURL:null,country:{name:"Brazil"}}},{id:"196746",title:"Dr.",name:"Ramana",middleName:null,surname:"Vinjamuri",slug:"ramana-vinjamuri",fullName:"Ramana Vinjamuri",profilePictureURL:"https://mts.intechopen.com/storage/users/196746/images/system/196746.jpeg",institutionString:"University of Maryland, Baltimore County",institution:{name:"University of Maryland, Baltimore County",institutionURL:null,country:{name:"United States of America"}}}]},{id:"9",title:"Biotechnology - Biosensors, Biomaterials and Tissue Engineering",coverUrl:"https://cdn.intechopen.com/series_topics/covers/9.jpg",editor:{id:"126286",title:"Dr.",name:"Luis",middleName:"Jesús",surname:"Villarreal-Gómez",slug:"luis-villarreal-gomez",fullName:"Luis Villarreal-Gómez",profilePictureURL:"https://mts.intechopen.com/storage/users/126286/images/system/126286.jpg",biography:"Dr. Luis Villarreal is a research professor from the Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Tijuana, Baja California, México. 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He has both an MS and Ph.D. in Biomedical Engineering. He was previously a research scientist at the University of California Los Angeles (UCLA) and visiting professor and researcher at the University of North Dakota. He is currently working in artificial intelligence and its applications in medical signal processing. In addition, he is using digital signal processing in medical imaging and speech processing. Dr. Asadpour has developed brain-computer interfacing algorithms and has published books, book chapters, and several journal and conference papers in this field and other areas of intelligent signal processing. He has also designed medical devices, including a laser Doppler monitoring system.",institutionString:"Kaiser Permanente Southern California",institution:null},{id:"169608",title:"Prof.",name:"Marian",middleName:null,surname:"Găiceanu",slug:"marian-gaiceanu",fullName:"Marian Găiceanu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/169608/images/system/169608.png",biography:"Prof. Dr. Marian Gaiceanu graduated from the Naval and Electrical Engineering Faculty, Dunarea de Jos University of Galati, Romania, in 1997. He received a Ph.D. (Magna Cum Laude) in Electrical Engineering in 2002. Since 2017, Dr. Gaiceanu has been a Ph.D. supervisor for students in Electrical Engineering. He has been employed at Dunarea de Jos University of Galati since 1996, where he is currently a professor. Dr. Gaiceanu is a member of the National Council for Attesting Titles, Diplomas and Certificates, an expert of the Executive Agency for Higher Education, Research Funding, and a member of the Senate of the Dunarea de Jos University of Galati. He has been the head of the Integrated Energy Conversion Systems and Advanced Control of Complex Processes Research Center, Romania, since 2016. He has conducted several projects in power converter systems for electrical drives, power quality, PEM and SOFC fuel cell power converters for utilities, electric vehicles, and marine applications with the Department of Regulation and Control, SIEI S.pA. (2002–2004) and the Polytechnic University of Turin, Italy (2002–2004, 2006–2007). He is a member of the Institute of Electrical and Electronics Engineers (IEEE) and cofounder-member of the IEEE Power Electronics Romanian Chapter. He is a guest editor at Energies and an academic book editor for IntechOpen. He is also a member of the editorial boards of the Journal of Electrical Engineering, Electronics, Control and Computer Science and Sustainability. Dr. Gaiceanu has been General Chairman of the IEEE International Symposium on Electrical and Electronics Engineering in the last six editions.",institutionString:'"Dunarea de Jos" University of Galati',institution:{name:'"Dunarea de Jos" University of Galati',country:{name:"Romania"}}},{id:"4519",title:"Prof.",name:"Jaydip",middleName:null,surname:"Sen",slug:"jaydip-sen",fullName:"Jaydip Sen",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/4519/images/system/4519.jpeg",biography:"Jaydip Sen is associated with Praxis Business School, Kolkata, India, as a professor in the Department of Data Science. His research areas include security and privacy issues in computing and communication, intrusion detection systems, machine learning, deep learning, and artificial intelligence in the financial domain. He has more than 200 publications in reputed international journals, refereed conference proceedings, and 20 book chapters in books published by internationally renowned publishing houses, such as Springer, CRC press, IGI Global, etc. Currently, he is serving on the editorial board of the prestigious journal Frontiers in Communications and Networks and in the technical program committees of a number of high-ranked international conferences organized by the IEEE, USA, and the ACM, USA. He has been listed among the top 2% of scientists in the world for the last three consecutive years, 2019 to 2021 as per studies conducted by the Stanford University, USA.",institutionString:"Praxis Business School",institution:null},{id:"320071",title:"Dr.",name:"Sidra",middleName:null,surname:"Mehtab",slug:"sidra-mehtab",fullName:"Sidra Mehtab",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002v6KHoQAM/Profile_Picture_1584512086360",biography:"Sidra Mehtab has completed her BS with honors in Physics from Calcutta University, India in 2018. She has done MS in Data Science and Analytics from Maulana Abul Kalam Azad University of Technology (MAKAUT), Kolkata, India in 2020. Her research areas include Econometrics, Time Series Analysis, Machine Learning, Deep Learning, Artificial Intelligence, and Computer and Network Security with a particular focus on Cyber Security Analytics. Ms. Mehtab has published seven papers in international conferences and one of her papers has been accepted for publication in a reputable international journal. She has won the best paper awards in two prestigious international conferences – BAICONF 2019, and ICADCML 2021, organized in the Indian Institute of Management, Bangalore, India in December 2019, and SOA University, Bhubaneswar, India in January 2021. Besides, Ms. Mehtab has also published two book chapters in two books. Seven of her book chapters will be published in a volume shortly in 2021 by Cambridge Scholars’ Press, UK. Currently, she is working as the joint editor of two edited volumes on Time Series Analysis and Forecasting to be published in the first half of 2021 by an international house. Currently, she is working as a Data Scientist with an MNC in Delhi, India.",institutionString:"NSHM College of Management and Technology",institution:null},{id:"226240",title:"Dr.",name:"Andri Irfan",middleName:null,surname:"Rifai",slug:"andri-irfan-rifai",fullName:"Andri Irfan Rifai",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/226240/images/7412_n.jpg",biography:"Andri IRFAN is a Senior Lecturer of Civil Engineering and Planning. He completed the PhD at the Universitas Indonesia & Universidade do Minho with Sandwich Program Scholarship from the Directorate General of Higher Education and LPDP scholarship. He has been teaching for more than 19 years and much active to applied his knowledge in the project construction in Indonesia. His research interest ranges from pavement management system to advanced data mining techniques for transportation engineering. He has published more than 50 papers in journals and 2 books.",institutionString:null,institution:{name:"Universitas Internasional Batam",country:{name:"Indonesia"}}},{id:"314576",title:"Dr.",name:"Ibai",middleName:null,surname:"Laña",slug:"ibai-lana",fullName:"Ibai Laña",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314576/images/system/314576.jpg",biography:"Dr. Ibai Laña works at TECNALIA as a data analyst. He received his Ph.D. in Artificial Intelligence from the University of the Basque Country (UPV/EHU), Spain, in 2018. He is currently a senior researcher at TECNALIA. His research interests fall within the intersection of intelligent transportation systems, machine learning, traffic data analysis, and data science. He has dealt with urban traffic forecasting problems, applying machine learning models and evolutionary algorithms. He has experience in origin-destination matrix estimation or point of interest and trajectory detection. Working with large volumes of data has given him a good command of big data processing tools and NoSQL databases. He has also been a visiting scholar at the Knowledge Engineering and Discovery Research Institute, Auckland University of Technology.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"314575",title:"Dr.",name:"Jesus",middleName:null,surname:"L. Lobo",slug:"jesus-l.-lobo",fullName:"Jesus L. Lobo",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/314575/images/system/314575.png",biography:"Dr. Jesús López is currently based in Bilbao (Spain) working at TECNALIA as Artificial Intelligence Research Scientist. In most cases, a project idea or a new research line needs to be investigated to see if it is good enough to take into production or to focus on it. That is exactly what he does, diving into Machine Learning algorithms and technologies to help TECNALIA to decide whether something is great in theory or will actually impact on the product or processes of its projects. So, he is expert at framing experiments, developing hypotheses, and proving whether they’re true or not, in order to investigate fundamental problems with a longer time horizon. He is also able to design and develop PoCs and system prototypes in simulation. He has participated in several national and internacional R&D projects.\n\nAs another relevant part of his everyday research work, he usually publishes his findings in reputed scientific refereed journals and international conferences, occasionally acting as reviewer and Programme Commitee member. Concretely, since 2018 he has published 9 JCR (8 Q1) journal papers, 9 conference papers (e.g. ECML PKDD 2021), and he has co-edited a book. He is also active in popular science writing data science stories for reputed blogs (KDNuggets, TowardsDataScience, Naukas). Besides, he has recently embarked on mentoring programmes as mentor, and has also worked as data science trainer.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"103779",title:"Prof.",name:"Yalcin",middleName:null,surname:"Isler",slug:"yalcin-isler",fullName:"Yalcin Isler",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRyQ8QAK/Profile_Picture_1628834958734",biography:"Yalcin Isler (1971 - Burdur / Turkey) received the B.Sc. degree in the Department of Electrical and Electronics Engineering from Anadolu University, Eskisehir, Turkey, in 1993, the M.Sc. degree from the Department of Electronics and Communication Engineering, Suleyman Demirel University, Isparta, Turkey, in 1996, the Ph.D. degree from the Department of Electrical and Electronics Engineering, Dokuz Eylul University, Izmir, Turkey, in 2009, and the Competence of Associate Professorship from the Turkish Interuniversity Council in 2019.\n\nHe was Lecturer at Burdur Vocational School in Suleyman Demirel University (1993-2000, Burdur / Turkey), Software Engineer (2000-2002, Izmir / Turkey), Research Assistant in Bulent Ecevit University (2002-2003, Zonguldak / Turkey), Research Assistant in Dokuz Eylul University (2003-2010, Izmir / Turkey), Assistant Professor at the Department of Electrical and Electronics Engineering in Bulent Ecevit University (2010-2012, Zonguldak / Turkey), Assistant Professor at the Department of Biomedical Engineering in Izmir Katip Celebi University (2012-2019, Izmir / Turkey). He is an Associate Professor at the Department of Biomedical Engineering at Izmir Katip Celebi University, Izmir / Turkey, since 2019. In addition to academics, he has also founded Islerya Medical and Information Technologies Company, Izmir / Turkey, since 2017.\n\nHis main research interests cover biomedical signal processing, pattern recognition, medical device design, programming, and embedded systems. He has many scientific papers and participated in several projects in these study fields. He was an IEEE Student Member (2009-2011) and IEEE Member (2011-2014) and has been IEEE Senior Member since 2014.",institutionString:null,institution:{name:"Izmir Kâtip Çelebi University",country:{name:"Turkey"}}},{id:"339677",title:"Dr.",name:"Mrinmoy",middleName:null,surname:"Roy",slug:"mrinmoy-roy",fullName:"Mrinmoy Roy",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/339677/images/16768_n.jpg",biography:"An accomplished Sales & Marketing professional with 12 years of cross-functional experience in well-known organisations such as CIPLA, LUPIN, GLENMARK, ASTRAZENECA across different segment of Sales & Marketing, International Business, Institutional Business, Product Management, Strategic Marketing of HIV, Oncology, Derma, Respiratory, Anti-Diabetic, Nutraceutical & Stomatological Product Portfolio and Generic as well as Chronic Critical Care Portfolio. A First Class MBA in International Business & Strategic Marketing, B.Pharm, D.Pharm, Google Certified Digital Marketing Professional. Qualified PhD Candidate in Operations and Management with special focus on Artificial Intelligence and Machine Learning adoption, analysis and use in Healthcare, Hospital & Pharma Domain. Seasoned with diverse therapy area of Pharmaceutical Sales & Marketing ranging from generating revenue through generating prescriptions, launching new products, and making them big brands with continuous strategy execution at the Physician and Patients level. Moved from Sales to Marketing and Business Development for 3.5 years in South East Asian Market operating from Manila, Philippines. Came back to India and handled and developed Brands such as Gluconorm, Lupisulin, Supracal, Absolut Woman, Hemozink, Fabiflu (For COVID 19), and many more. In my previous assignment I used to develop and execute strategies on Sales & Marketing, Commercialization & Business Development for Institution and Corporate Hospital Business portfolio of Oncology Therapy Area for AstraZeneca Pharma India Ltd. Being a Research Scholar and Student of ‘Operations Research & Management: Artificial Intelligence’ I published several pioneer research papers and book chapters on the same in Internationally reputed journals and Books indexed in Scopus, Springer and Ei Compendex, Google Scholar etc. Currently, I am launching PGDM Pharmaceutical Management Program in IIHMR Bangalore and spearheading the course curriculum and structure of the same. I am interested in Collaboration for Healthcare Innovation, Pharma AI Innovation, Future trend in Marketing and Management with incubation on Healthcare, Healthcare IT startups, AI-ML Modelling and Healthcare Algorithm based training module development. I am also an affiliated member of the Institute of Management Consultant of India, looking forward to Healthcare, Healthcare IT and Innovation, Pharma and Hospital Management Consulting works.",institutionString:null,institution:{name:"Lovely Professional University",country:{name:"India"}}},{id:"310576",title:"Prof.",name:"Erick Giovani",middleName:null,surname:"Sperandio Nascimento",slug:"erick-giovani-sperandio-nascimento",fullName:"Erick Giovani Sperandio Nascimento",position:null,profilePictureURL:"https://intech-files.s3.amazonaws.com/0033Y00002pDKxDQAW/ProfilePicture%202022-06-20%2019%3A57%3A24.788",biography:"Prof. Erick Sperandio is the Lead Researcher and professor of Artificial Intelligence (AI) at SENAI CIMATEC, Bahia, Brazil, also working with Computational Modeling (CM) and HPC. He holds a PhD in Environmental Engineering in the area of Atmospheric Computational Modeling, a Master in Informatics in the field of Computational Intelligence and Graduated in Computer Science from UFES. He currently coordinates, leads and participates in R&D projects in the areas of AI, computational modeling and supercomputing applied to different areas such as Oil and Gas, Health, Advanced Manufacturing, Renewable Energies and Atmospheric Sciences, advising undergraduate, master's and doctoral students. He is the Lead Researcher at SENAI CIMATEC's Reference Center on Artificial Intelligence. In addition, he is a Certified Instructor and University Ambassador of the NVIDIA Deep Learning Institute (DLI) in the areas of Deep Learning, Computer Vision, Natural Language Processing and Recommender Systems, and Principal Investigator of the NVIDIA/CIMATEC AI Joint Lab, the first in Latin America within the NVIDIA AI Technology Center (NVAITC) worldwide program. He also works as a researcher at the Supercomputing Center for Industrial Innovation (CS2i) and at the SENAI Institute of Innovation for Automation (ISI Automação), both from SENAI CIMATEC. He is a member and vice-coordinator of the Basic Board of Scientific-Technological Advice and Evaluation, in the area of Innovation, of the Foundation for Research Support of the State of Bahia (FAPESB). He serves as Technology Transfer Coordinator and one of the Principal Investigators at the National Applied Research Center in Artificial Intelligence (CPA-IA) of SENAI CIMATEC, focusing on Industry, being one of the six CPA-IA in Brazil approved by MCTI / FAPESP / CGI.br. He also participates as one of the representatives of Brazil in the BRICS Innovation Collaboration Working Group on HPC, ICT and AI. He is the coordinator of the Work Group of the Axis 5 - Workforce and Training - of the Brazilian Strategy for Artificial Intelligence (EBIA), and member of the MCTI/EMBRAPII AI Innovation Network Training Committee. He is the coordinator, by SENAI CIMATEC, of the Artificial Intelligence Reference Network of the State of Bahia (REDE BAH.IA). He leads the working group of experts representing Brazil in the Global Partnership on Artificial Intelligence (GPAI), on the theme \"AI and the Pandemic Response\".",institutionString:"Manufacturing and Technology Integrated Campus – SENAI CIMATEC",institution:null},{id:"1063",title:"Prof.",name:"Constantin",middleName:null,surname:"Volosencu",slug:"constantin-volosencu",fullName:"Constantin Volosencu",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1063/images/system/1063.png",biography:"Prof. Dr. Constantin Voloşencu graduated as an engineer from\nPolitehnica University of Timișoara, Romania, where he also\nobtained a doctorate degree. He is currently a full professor in\nthe Department of Automation and Applied Informatics at the\nsame university. Dr. Voloşencu is the author of ten books, seven\nbook chapters, and more than 160 papers published in journals\nand conference proceedings. He has also edited twelve books and\nhas twenty-seven patents to his name. He is a manager of research grants, editor in\nchief and member of international journal editorial boards, a former plenary speaker, a member of scientific committees, and chair at international conferences. His\nresearch is in the fields of control systems, control of electric drives, fuzzy control\nsystems, neural network applications, fault detection and diagnosis, sensor network\napplications, monitoring of distributed parameter systems, and power ultrasound\napplications. He has developed automation equipment for machine tools, spooling\nmachines, high-power ultrasound processes, and more.",institutionString:"Polytechnic University of Timişoara",institution:{name:"Polytechnic University of Timişoara",country:{name:"Romania"}}},{id:"221364",title:"Dr.",name:"Eneko",middleName:null,surname:"Osaba",slug:"eneko-osaba",fullName:"Eneko Osaba",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/221364/images/system/221364.jpg",biography:"Dr. Eneko Osaba works at TECNALIA as a senior researcher. He obtained his Ph.D. in Artificial Intelligence in 2015. He has participated in more than twenty-five local and European research projects, and in the publication of more than 130 papers. He has performed several stays at universities in the United Kingdom, Italy, and Malta. Dr. Osaba has served as a program committee member in more than forty international conferences and participated in organizing activities in more than ten international conferences. He is a member of the editorial board of the International Journal of Artificial Intelligence, Data in Brief, and Journal of Advanced Transportation. He is also a guest editor for the Journal of Computational Science, Neurocomputing, Swarm, and Evolutionary Computation and IEEE ITS Magazine.",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"275829",title:"Dr.",name:"Esther",middleName:null,surname:"Villar-Rodriguez",slug:"esther-villar-rodriguez",fullName:"Esther Villar-Rodriguez",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/275829/images/system/275829.jpg",biography:"Dr. Esther Villar obtained a Ph.D. in Information and Communication Technologies from the University of Alcalá, Spain, in 2015. She obtained a degree in Computer Science from the University of Deusto, Spain, in 2010, and an MSc in Computer Languages and Systems from the National University of Distance Education, Spain, in 2012. Her areas of interest and knowledge include natural language processing (NLP), detection of impersonation in social networks, semantic web, and machine learning. Dr. Esther Villar made several contributions at conferences and publishing in various journals in those fields. Currently, she is working within the OPTIMA (Optimization Modeling & Analytics) business of TECNALIA’s ICT Division as a data scientist in projects related to the prediction and optimization of management and industrial processes (resource planning, energy efficiency, etc).",institutionString:"TECNALIA Research & Innovation",institution:{name:"Tecnalia",country:{name:"Spain"}}},{id:"49813",title:"Dr.",name:"Javier",middleName:null,surname:"Del Ser",slug:"javier-del-ser",fullName:"Javier Del Ser",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/49813/images/system/49813.png",biography:"Prof. Dr. Javier Del Ser received his first PhD in Telecommunication Engineering (Cum Laude) from the University of Navarra, Spain, in 2006, and a second PhD in Computational Intelligence (Summa Cum Laude) from the University of Alcala, Spain, in 2013. He is currently a principal researcher in data analytics and optimisation at TECNALIA (Spain), a visiting fellow at the Basque Center for Applied Mathematics (BCAM) and a part-time lecturer at the University of the Basque Country (UPV/EHU). His research interests gravitate on the use of descriptive, prescriptive and predictive algorithms for data mining and optimization in a diverse range of application fields such as Energy, Transport, Telecommunications, Health and Industry, among others. In these fields he has published more than 240 articles, co-supervised 8 Ph.D. theses, edited 6 books, coauthored 7 patents and participated/led more than 40 research projects. He is a Senior Member of the IEEE, and a recipient of the Biscay Talent prize for his academic career.",institutionString:"Tecnalia Research & Innovation",institution:null},{id:"278948",title:"Dr.",name:"Carlos Pedro",middleName:null,surname:"Gonçalves",slug:"carlos-pedro-goncalves",fullName:"Carlos Pedro Gonçalves",position:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRcmyQAC/Profile_Picture_1564224512145",biography:'Carlos Pedro Gonçalves (PhD) is an Associate Professor at Lusophone University of Humanities and Technologies and a researcher on Complexity Sciences, Quantum Technologies, Artificial Intelligence, Strategic Studies, Studies in Intelligence and Security, FinTech and Financial Risk Modeling. He is also a progammer with programming experience in:\n\nA) Quantum Computing using Qiskit Python module and IBM Quantum Experience Platform, with software developed on the simulation of Quantum Artificial Neural Networks and Quantum Cybersecurity;\n\nB) Artificial Intelligence and Machine learning programming in Python;\n\nC) Artificial Intelligence, Multiagent Systems Modeling and System Dynamics Modeling in Netlogo, with models developed in the areas of Chaos Theory, Econophysics, Artificial Intelligence, Classical and Quantum Complex Systems Science, with the Econophysics models having been cited worldwide and incorporated in PhD programs by different Universities.\n\nReceived an Arctic Code Vault Contributor status by GitHub, due to having developed open source software preserved in the \\"Arctic Code Vault\\" for future generations (https://archiveprogram.github.com/arctic-vault/), with the Strategy Analyzer A.I. module for decision making support (based on his PhD thesis, used in his Classes on Decision Making and in Strategic Intelligence Consulting Activities) and QNeural Python Quantum Neural Network simulator also preserved in the \\"Arctic Code Vault\\", for access to these software modules see: https://github.com/cpgoncalves. He is also a peer reviewer with outsanding review status from Elsevier journals, including Physica A, Neurocomputing and Engineering Applications of Artificial Intelligence. Science CV available at: https://www.cienciavitae.pt//pt/8E1C-A8B3-78C5 and ORCID: https://orcid.org/0000-0002-0298-3974',institutionString:"University of Lisbon",institution:{name:"Universidade Lusófona",country:{name:"Portugal"}}},{id:"241400",title:"Prof.",name:"Mohammed",middleName:null,surname:"Bsiss",slug:"mohammed-bsiss",fullName:"Mohammed Bsiss",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/241400/images/8062_n.jpg",biography:null,institutionString:null,institution:null},{id:"276128",title:"Dr.",name:"Hira",middleName:null,surname:"Fatima",slug:"hira-fatima",fullName:"Hira Fatima",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/276128/images/14420_n.jpg",biography:"Dr. Hira Fatima\nAssistant Professor\nDepartment of Mathematics\nInstitute of Applied Science\nMangalayatan University, Aligarh\nMobile: no : 8532041179\nhirafatima2014@gmal.com\n\nDr. Hira Fatima has received his Ph.D. degree in pure Mathematics from Aligarh Muslim University, Aligarh India. Currently working as an Assistant Professor in the Department of Mathematics, Institute of Applied Science, Mangalayatan University, Aligarh. She taught so many courses of Mathematics of UG and PG level. Her research Area of Expertise is Functional Analysis & Sequence Spaces. She has been working on Ideal Convergence of double sequence. She has published 17 research papers in National and International Journals including Cogent Mathematics, Filomat, Journal of Intelligent and Fuzzy Systems, Advances in Difference Equations, Journal of Mathematical Analysis, Journal of Mathematical & Computer Science etc. She has also reviewed few research papers for the and international journals. 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