Different turbulent models.
\r\n\t
",isbn:"978-1-83969-561-2",printIsbn:"978-1-83969-560-5",pdfIsbn:"978-1-83969-562-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,hash:"65f2a1fef9c804c29b18ef3ac4a35066",bookSignature:"Dr. Luis Loures",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/10756.jpg",keywords:"Urban Processes, Urban Patterns, Redevelopment Strategies, Landscape, Land Transformation, Urban Models, Urban Evolution, Urban Organisation, Legislation, Sustainable Development, Green Infrastructure, Regional Planning",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"February 23rd 2021",dateEndSecondStepPublish:"March 22nd 2021",dateEndThirdStepPublish:"May 21st 2021",dateEndFourthStepPublish:"August 9th 2021",dateEndFifthStepPublish:"October 8th 2021",remainingDaysToSecondStep:"14 days",secondStepPassed:!1,currentStepOfPublishingProcess:2,editedByType:null,kuFlag:!1,biosketch:"Dr. Loures has worked on pioneering research on circular planning applied to post-industrial landscape redevelopment. Since he graduated he has published several peer-reviewed papers at the national and international levels and he has been a guest researcher and lecturer both at Michigan State University (USA) and at the University of Toronto (Canada) where he has developed part of his Ph.D. research with the Financial support from the Portuguese Foundation for Science and Technology (Ph.D. grant).",coeditorOneBiosketch:null,coeditorTwoBiosketch:null,coeditorThreeBiosketch:null,coeditorFourBiosketch:null,coeditorFiveBiosketch:null,editors:[{id:"108118",title:"Dr.",name:"Luis",middleName:null,surname:"Loures",slug:"luis-loures",fullName:"Luis Loures",profilePictureURL:"https://mts.intechopen.com/storage/users/108118/images/system/108118.png",biography:"Luís Loures is a Landscape Architect and Agronomic Engineer, Vice-President of the Polytechnic Institute of Portalegre, who holds a Ph.D. in Planning and a Post-Doc in Agronomy. Since he graduated, he has published several peer reviewed papers at the national and international levels and he has been a guest researcher and lecturer both at Michigan State University (USA), and at University of Toronto (Canada) where he has developed part of his Ph.D. research with the Financial support from the Portuguese Foundation for Science and Technology (Ph.D. grant).\nDuring his academic career he had taught in several courses in different Universities around the world, mainly regarding the fields of landscape architecture, urban and environmental planning and sustainability. Currently, he is a researcher both at VALORIZA - Research Centre for Endogenous Resource Valorization – Polytechnic Institute of Portalegre, and the CinTurs - Research Centre for Tourism, Sustainability and Well-being, University of Algarve where he is a researcher on several financed research projects focusing several different investigation domains such as urban planning, landscape reclamation and urban redevelopment, and the use of urban planning as a tool for achieving sustainable development.",institutionString:"Polytechnic Institute of Portalegre",position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"8",totalChapterViews:"0",totalEditedBooks:"2",institution:{name:"Polytechnic Institute of Portalegre",institutionURL:null,country:{name:"Portugal"}}}],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:"205697",firstName:"Kristina",lastName:"Kardum Cvitan",middleName:null,title:"Ms.",imageUrl:"https://mts.intechopen.com/storage/users/205697/images/5186_n.jpg",email:"kristina.k@intechopen.com",biography:"As an Author Service Manager my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review, to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."}},relatedBooks:[{type:"book",id:"5962",title:"Estuary",subtitle:null,isOpenForSubmission:!1,hash:"43058846a64b270e9167d478e966161a",slug:"estuary",bookSignature:"William Froneman",coverURL:"https://cdn.intechopen.com/books/images_new/5962.jpg",editedByType:"Edited by",editors:[{id:"109336",title:"Prof.",name:"William",surname:"Froneman",slug:"william-froneman",fullName:"William Froneman"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"1591",title:"Infrared Spectroscopy",subtitle:"Materials Science, Engineering and Technology",isOpenForSubmission:!1,hash:"99b4b7b71a8caeb693ed762b40b017f4",slug:"infrared-spectroscopy-materials-science-engineering-and-technology",bookSignature:"Theophile Theophanides",coverURL:"https://cdn.intechopen.com/books/images_new/1591.jpg",editedByType:"Edited by",editors:[{id:"37194",title:"Dr.",name:"Theophanides",surname:"Theophile",slug:"theophanides-theophile",fullName:"Theophanides Theophile"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3092",title:"Anopheles mosquitoes",subtitle:"New insights into malaria vectors",isOpenForSubmission:!1,hash:"c9e622485316d5e296288bf24d2b0d64",slug:"anopheles-mosquitoes-new-insights-into-malaria-vectors",bookSignature:"Sylvie Manguin",coverURL:"https://cdn.intechopen.com/books/images_new/3092.jpg",editedByType:"Edited by",editors:[{id:"50017",title:"Prof.",name:"Sylvie",surname:"Manguin",slug:"sylvie-manguin",fullName:"Sylvie Manguin"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"3161",title:"Frontiers in Guided Wave Optics and Optoelectronics",subtitle:null,isOpenForSubmission:!1,hash:"deb44e9c99f82bbce1083abea743146c",slug:"frontiers-in-guided-wave-optics-and-optoelectronics",bookSignature:"Bishnu Pal",coverURL:"https://cdn.intechopen.com/books/images_new/3161.jpg",editedByType:"Edited by",editors:[{id:"4782",title:"Prof.",name:"Bishnu",surname:"Pal",slug:"bishnu-pal",fullName:"Bishnu Pal"}],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:"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:"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:"371",title:"Abiotic Stress in Plants",subtitle:"Mechanisms and Adaptations",isOpenForSubmission:!1,hash:"588466f487e307619849d72389178a74",slug:"abiotic-stress-in-plants-mechanisms-and-adaptations",bookSignature:"Arun Shanker and B. 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:"878",title:"Phytochemicals",subtitle:"A Global Perspective of Their Role in Nutrition and Health",isOpenForSubmission:!1,hash:"ec77671f63975ef2d16192897deb6835",slug:"phytochemicals-a-global-perspective-of-their-role-in-nutrition-and-health",bookSignature:"Venketeshwer Rao",coverURL:"https://cdn.intechopen.com/books/images_new/878.jpg",editedByType:"Edited by",editors:[{id:"82663",title:"Dr.",name:"Venketeshwer",surname:"Rao",slug:"venketeshwer-rao",fullName:"Venketeshwer Rao"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}},{type:"book",id:"4816",title:"Face Recognition",subtitle:null,isOpenForSubmission:!1,hash:"146063b5359146b7718ea86bad47c8eb",slug:"face_recognition",bookSignature:"Kresimir Delac and Mislav Grgic",coverURL:"https://cdn.intechopen.com/books/images_new/4816.jpg",editedByType:"Edited by",editors:[{id:"528",title:"Dr.",name:"Kresimir",surname:"Delac",slug:"kresimir-delac",fullName:"Kresimir Delac"}],productType:{id:"1",chapterContentType:"chapter",authoredCaption:"Edited by"}}]},chapter:{item:{type:"chapter",id:"60239",title:"Gas-Liquid Stratified Flow in Pipeline with Phase Change",doi:"10.5772/intechopen.74102",slug:"gas-liquid-stratified-flow-in-pipeline-with-phase-change",body:'\nCondensation occurs when the natural gas with vapor is flowing in production pipeline and leads to serious problems such as condensed liquid accumulation, pressure and flow rate fluctuations, and pipeline blockage or corrosion. The pipe flow together with phase change is commonly encountered in various heat and mass transfer processes over the past four decades, for instance, in petroleum and chemical processing industry, steam-generating equipment, nuclear reactors, geothermal fields, heat exchangers, cooling systems, and solar energy system [1, 2, 3, 4]. In petroleum transportation, two-phase flow characterization is a very common and economic technique, where vapor-liquid two-phase stratified flow is often observed in horizontal or slightly inclined systems [5, 6].
\nThere exist several problems in the pipeline network system that the saturated vapor in gas would condense due to pressure and temperature drop [7, 8]. The condensate would attach to the pipe wall as a form of film or droplet [9, 10]. The condensation will decrease the effective cross-sectional area and cause the increase of pressure drop which may lead to system shutdown [11, 16]. Generally, the condensed water accumulates at the lower parts of the pipeline due to the hilly pipeline route topography, which results in a continuous change of liquid holdup along the pipeline [12, 13, 14]. The changing liquid holdup and flow area are bounded to affect the flow patterns which inevitably influence the operating pressure and temperature inversely. Thus, the flow of condensed water and water-bearing gas in production pipelines is a complex process with coupling of hydraulic, thermal, and phase change phenomena [14, 15, 16, 17]. Researchers have investigated the gas-liquid two-phase pipe flow system by experiments or hydrodynamic and thermodynamic models.
\nIt has been observed experimentally that when phase change occurs during the saturated vapor pipeline transportation process, the thermal gradients are created in the wall of the pipeline that lead to severe liquid condensation and stratified vapor-liquid two-phase flow [17, 18]. The fundamental engineering parameters are the pressure drop, liquid holdup, phase fraction, phase flow rate, temperature, thermo-physical properties of the fluids, and pipeline geometry [19].
\nNot limited to hydraulic parameters, more recent attention has turned to non-isothermal flow in a pipe or plane channel where some numerical studies are also found [20, 21, 22, 23, 24, 25, 26, 27]. The detailed characteristic of heat transfer is taken into consideration in these mentioned models instead of an average value being represented for the temperature profiles in a pipe [28, 29]. According to their studies, the wall temperature distribution is different from the assumption of fully developed isothermal state [30]. The energy transfer model has been taken into the flow progress for the optimization of transportation, estimation of corrosion, or prediction of wax deposition [31, 32]. Concretely, the two-dimensional (2D) momentum and three-dimensional (3D) energy equations for both phases have been established for dynamic and thermal numerical simulation [8, 27, 30, 33]. The smooth or wavy interface between phases was obtained in a different range of flow rates [17]. For such a two-phase non-isothermal stratified flow, analytical and numerical heat transfer solutions limited to laminar flow and without phase change have been obtained for fully developed stratified flow under different thermal boundary conditions [27]. Then, solutions which are more applicable to fully developed turbulent gas-liquid smooth stratified flow have been obtained through the use of high Reynolds model [30]. Recently, the steady-state axial momentum and energy equations coupled with a low Reynolds model were established and solved [34]. The pressure drop, liquid height, and temperature field which are included in the solutions could match well with the experimental data. However, although equation of state (EOS) was utilized in previous one-dimensional (1D) models to calculate the phase fraction [10, 12, 16, 22, 34, 41, 44], the flow rate, temperature, and pressure were not coupled with the varying liquid level.
\nAccording to the description of the physical process of gas-liquid two-phase pipe flow, the model can be divided into isothermal model, gas-liquid two-phase pipe flow model coupled with heat and gas-liquid two-phase pipe flow model coupled with heat and mass transfer. In the gas-liquid two-phase pipe flow model under the isothermal condition, it is assumed that all phases are in thermodynamic equilibrium state without considering the heat transfer process between pipe flow and environment, and the physical parameters of gas-liquid two-phase are just the single value function of pressure. In the gas-liquid two-phase flow model coupled with heat, the heat transfer of gas-liquid and surrounding environment is considered. In the gas-liquid two-phase flow model coupled with heat and mass transfer, the coupling effect of flow, heat transfer, and mass transfer are considered simultaneously.
\nThe two-dimensional (2D) or three-dimensional (3D) stratified gas-liquid two-phase model including mass conversation equation, momentum conversation equation, turbulence model equation, boundary conditions, and related auxiliary equations for model closure were applied to describe the flow in pipelines. Differences among them mainly existed in two aspects. On the one hand, different turbulence models were built including Spalart-Allmaras Model (SAM), \n
Recently, attempts have been made to introduce energy equation into the improved model and the detailed solutions about temperature distribution have also been worked out by considering potential energy, kinetic energy, heat transfer, and Joule-Thomson effect [17, 35, 36, 37, 38]. The phase change was ignored in these models. Although equation of state (EOS) was utilized in previous studies to calculate gas condensation of gas-condensate flow in pipelines [12, 13, 14, 15, 17, 18, 19, 20, 39], the flow rate, temperature, pressure were not coupled with liquid level. Turbulent flow is not considered, which would lead to different numerical results in their one-dimensional (1D) model. Moreover, 1D model could not present the detailed distribution of hydraulic and thermal parameters at pipe cross-section.
\nThis chapter mainly introduces the different turbulence models, the interface shape model, and the phase transition model in the process of gas-liquid two-phase stratified flow in the horizontal pipeline. The turbulence model mainly includes the \n
Since pressure and temperature drop along the pipeline, the saturated vapor of hydrocarbons would condenses gradually, as shown in Figure 1. The condensed liquid would attach to the pipe wall as liquid film or accumulate at the lower part of the pipeline, which could result in continuous change of the liquid level [17, 29, 30].
\nVapor-liquid two-phase flow coupled with heat and mass transfer.
Thus, some models of stratified vapor-liquid two-phase flow coupled with phase change were proposed. Assumptions could be made as follows: (1) precipitation of condensed liquid is a flash evaporation equilibrium process which occurs in a short moment; (2) regardless of the attachment to inner wall of the pipe, all the condensed liquid accumulates at the bottom of the pipe; (3) two-phase flow in vapor-liquid pipeline has a stratified flow pattern as well as a stable developing flow area in every calculated pipeline segment; (4) the smooth vapor-liquid interface model is adopted to describe the interface shape; (5) the heavy components of hydrocarbon are simplified as pseudo-component\n
Several kinds of flow patterns are likely to form for vapor/condensation flowing in pipeline: stratified flow, slug flow, annular flow, and stratified-dispersed flow. It is hard to calculate the liquid level, the exact position of liquid film, and the migration patterns of condensed liquid (as shown in Figure 1) via one-dimensional model which could not present the detailed distribution of hydraulic and thermal parameters at pipe cross section. Moreover, the 1D model does not consider the turbulent flow which would lead to different numerical results. Hence, the control volume in three-dimensional coordinates is adopted to discretize the calculating area, as shown in Figure 2.
\nSchematic illustration of stratified vapor–liquid flow with phase change.
In this section, the governing equations based on physical conservation are chosen and established in three-dimensional coordinates, which include mass conservation equation, momentum conservation equation, energy conservation equation, turbulent flow model, and phase change model.
\nThe total mass flow rate \n
The mass transfer rate of phase-change within pipe segment has been taken into consideration due to the vapor phase gradually condensing or the liquid evaporating during the flow process. The change of vapor mass flow rate \n
The liquid volume fraction \n
The law of momentum conservation is a universal principle for any flow system that the varying rate of momentum is equal to the sum of the forces imposed on the control volume. Considering the compressibility of vapor and liquid, the equation of momentum is as follows:
\nhere \n
\n\n
According to the theory of CFD, the N-S equation is applicable to any kind of flow. A direct calculation of N-S equation requires a high computer capacity which is not practical in engineering. Hence, an item of Reynolds is introduced, and the final momentum equation for vapor and liquid stratified flow is as follows:
\nwhere \n
Following a similar approach as Xiao et al. [36] and Reboux et al. [37, 38] for two-phase turbulent flow, the eddy viscosity is modeled using the large eddy simulation (LES) turbulence model based on the assumption of non-isotropic turbulence. Meanwhile, changes are made to take account of the progressive attenuation of turbulence close to the wall. LES model is applicable to the flow with different Reynolds number. The subgrid scale viscosity is written as:
\nThe Smagorinsky constant is \n
The filter width \n
And \n
The choice of turbulence model is crucial for this sort of study, due to the presence of these secondary flows. Nallasamy and Rodi explained that the well-known \n
Formula name | \nexpression | \n
---|---|
Duan et al. [5] | \nLow Reynolds number model: \n\n \n\n \n\n \n\n \n\n \n\n | \n
Jiang et al. [40] | \nLES model: \n\n | \n
Different turbulent models.
It is of great significance to study turbulent flow and heat-transfer mechanism due to the frequent occurrence in many industrial applications, such as heat exchangers, vapor turbines, cooling systems, and nuclear reactors [27]. In this study, a quasi-steady state of temperature profile is calculated where axial thermal conduction is neglected. Since the operating temperature is influenced by ambient temperature, fluid properties, and hydraulic parameters such as flow rate and liquid level; a heat-transfer model for vapor-liquid flow is established.
\nEnergy equation means the increase of energy, which is equal to the result of heat flux entering the representative-element volume deducting the work from internal force. Ignoring axial heat conduction and viscous dispersive item, the equation of energy conservation is as follows:
\n\n\n
The pressure and temperature drop along pipelines, which incurs the change of ratio of gas mass volume and liquid mass volume. It is prone to evoke P–T flash evaporation in each component. The mass percentage would change accordingly, influencing the parameters like molar mass, density, viscosity, heat capacity and thermal conductivity. The vapor enthalpy would change during the process of phase change and dissipate into the vapor or liquid in the form of phase change heat which results in variation of fluid temperature [22, 32, 45].
\nCong Guo et al. considered a modification of the original model, in which the rate of conductive heat through the tube wall due to temperature difference can be calculated [43]. Peneloux et al. proposed the concept of volume translation. They argue that the volume obtained using SRKEOS is a “pseudo-volume” and proposed a method of calculating the “pseudo volume” [44]. Sadegh et al. proposed an equilibrium criterion for the Peng-Robinson equation of state (PREOS) based on the volume translated Peng-Robinson equation of state (VTPREOS) and a translated functional relationship is used based on the theory of Peneloux et al. to discuss the volume translation technique [45]. The study of Li Zhang et al. shows that the condensation heat transfer coefficient reduces with the increase of wall subcooling from around 2 to 14°C. With the rise in the wall subcooling, the heat flux increases, resulting in an increasing rate of steam condensation, which brings forth a thicker condensate film on the tube surface. The thicker condensate film around the tube offers a higher thermal resistance to steam condensation and in turn reduces the condensation heat transfer coefficient [22]. Considering the volume addition of LSI phase due to the coalescence, Kai Yan et al. used the additional velocity and considered all the conditions when some portion of SSI phase can come into LSI phase [46]. Bonizzi proposed a model for calculating the atomization flux and the bulk concentration based on the recommendation by Williams et al. and Pan and Hanratty [47, 48, 49, 50, 51]. Vinesh et al. showed the physical model, considered for phase change which corresponds to hydrodynamically as well as thermally developing vapor-liquid stratified flow in a plane channel, with heating from the top and cooling from the bottom wall [52] (Table 2).
\nFormula name | \nExpression | \n
---|---|
Cong Guo et al. [43] | \nThe rate of conductive heat through the tube wall: \n\n The temperature of the condensate around circumferential wall: \n\n | \n
Peneloux et al. [44] | \nThe “pseudo-volume” obtained using SRKEOS: \n\n The definition of “pseudo volume”: \n\n | \n
Sadegh et al. [45] | \nThe “pseudo partial volume” can be defined as: \n\n With this definition “pseudo fugacity coefficients” can be defined as: \n\n | \n
Kai Yan et al. [46] | \nThe expression of the additional velocity \n \n\n | \n
Williams et al. & Pan and Hanratty [47, 48] | \nThe atomization flux: \n\n In which \n | \n
Bonizzi et al. [51] | \nThe flux of droplet deposition is usually expressed as: \n\n \n\n | \n
Different phase change models.
The equation of state in P–T Flash involves Peng-Robinson (PR) equation, which was proposed by Peng-Robinson in 1976. It can predict the molar volume more accurately than SRK equation and can be applied for polar compounds. Apart from that, the equation is applicable to vapor and liquid at the same time and widely used in the calculation of phase equilibrium.
\nDuring the P–T flash calculation process, the required parameters are the component of light hydrocarbon, gasification rate, density, molar mass, and enthalpy. The relation between input and output is explained in Figures 3 and 4.
\nInput and output of P–T flash calculation.
The illustration of the way to obtain the mole fraction by P–T flash in each grid cell.
The fluid in the pipe includes \n
Therefore, the latent heat may result in the temperature change of the vapor-liquid system. The enthalpy difference in the process of vaporization or condensation can be obtained by virtue of P–T flash calculation. The latent heat helps to retard the temperature change. The process can be calculated as follows:
\nThe parameters of flow state and related dimensionless parameters are given by:
\nThe properties of fluids are calculated by:
\nBoth gas and liquid phases are not ideal fluids. Vapor phase is a mixture of multi-component light hydrocarbons. Thus, the property of vapor phase is a combination of their quality weighting. The PREOS equation is currently acknowledged as the most accurate formula to calculate the density of mixed vapor. If the pressure, temperature, and relative density of light hydrocarbon are known, the viscosity can be calculated using experimental formulas. Both the thermal conductivity and the heat capacity at constant pressure for vapor mixture are related to temperature and pressure, which also can be calculated using the experimental formulas. For the liquid phase, the density is calculated by PR EOS. The other physical properties including viscosity, thermal conductivity, and specific heat capacity are respectively a function of temperature, density, and other critical properties of components.
\nThe relationship between liquid level \n
The value of\n
As shown in Figure 6, the evaporation fraction, density, and molar weight of vapor and liquid phase can be obtained with the known mole fraction of each component since the temperature and pressure are the same as inlet data in the first cross section. The liquid hold-up can be calculated as follows:
\nThe temperature, pressure, and mole fraction vary in the second and other subsequent cross section due to the influence of thermal conduction, pressure drop, and phase change but can be derived from the former section. Hence, it requires the calculation of the evaporation fraction, density, and molar weight in each grid cell. The liquid holdup can be calculated as follows:
\nThen, the liquid level \n
\n\n
Dimensionless shift at wavy gas-liquid interface is defined as:
\nIt can be calculated by (Cebeci and Smith, 1974):
\nThe abovementioned correlation is based on the data fit, the lower limit corresponds to a smooth surface, where \n
The \n
where \n
The flow geometry of stratified flow in circular receiver is very complex. In order to simplify the model, many researchers use different models in their researches. The following are some models.
\nThe boundary conditions included in vapor-liquid two-phase stratified pipe flow with heat transfer and phase change involve vapor-liquid interface condition, wall boundary condition, symmetrical boundary condition and inlet boundary condition. As for the vapor-liquid interface, in order to illustrate the mutual influences among flow, heat transfer and phase change, the equal interfacial shear stress has been prescribed as the vapor-liquid interface condition which is related to the fluid properties and velocity distribution and can be calculated as:
\nThe temperature and heat flux of two phases are respectively equal at vapor liquid interface (Table 3).
\nDifferent gas-liquid interface models.
At the pipe wall, the non-slip condition is applied for velocity in both two phases.
\nThe temperature boundary condition at pipe wall of vapor and liquid phases are convective heat transfer and its coefficient of pipeline outer wall remains constant.
\nThe gradients of velocity and temperature are zero at the symmetrical boundary.
\nAt the inlet of pipeline, the velocity and temperature filed of two phases are respectively equal to the pipe inlet values.
Based on the theory of flow and heat transfer, turbulent flow and phase equilibrium, the model is solved by multi-physical field coupling numerical simulation. The non-circular liquid and vapor domains in stratified pipe flow can be simply modeled with the bipolar coordinate system, which is helpful in solving the problem caused by the inhomogeneity of boundaries. Bipolar cylindrical coordinate is composed of two orthogonal circles in rectangular coordinate. As the flow field in both phases is bounded by a circular pipe wall and a plane interface, the calculation domain has been converted to rectangle form from the anomalous physical domain by adopting the bipolar coordinate system.
\nWith the increase of axial distance, the liquid level in pipeline changes constantly and leads to the change of flow area in both phases. The grid size changes adaptively along with the flow area, where the flow area is determined by the height of gas-liquid interface. Variable-size grid has advantages in calculating the changing interface. The grid number remains unchangeable. The location of the gas-liquid interface is obtained by the secant method, and the convergence condition is that the conservation of the mass flow rate of the gas-liquid phase and the total mass flow rate equal to the inlet mass flow rate. In this way, the interface is detected.
\nVapor-liquid two phase flow and heat transfer coupled with phase change have been simulated in this section. The simulated pipeline is with inner diameter of 100 mm and total length of 6000 m. The superficial velocities of vapor and liquid are respectively \n
Compound | \nCH4 | \nC2H6 | \nC3H8 | \ni-C4H10 | \nn-C4H10 | \ni-C5H12 | \nn-C5H12 | \nn-C6H14 | \n\n\n | \n
---|---|---|---|---|---|---|---|---|---|
Mole percent (%) | \n78.03 | \n4.73 | \n5.98 | \n3.05 | \n3.54 | \n2.85 | \n0.54 | \n0.69 | \n0.59 | \n
Chemical composition of the light hydrocarbons used in current study.
The mole fractions of each component, density distribution, temperature distribution, and liquid level along the pipeline are obtained in the condition of condensation production.
\nMole fractions of each component at pipe inlet in both phases are shown in Table 5. In vapor phase, the mole fraction of methane is larger than all the other light hydrocarbons (\n
Compound | \nCH4 | \nC2H6 | \nC3H8 | \ni-C4H10 | \nn-C4H10 | \ni-C5H12 | \nn-C5H12 | \nn-C6H14 | \n\n\n | \nTotal | \n
---|---|---|---|---|---|---|---|---|---|---|
Mole fraction in vapor phase (%) | \n80.54 | \n4.69 | \n5.61 | \n2.71 | \n3.05 | \n2.25 | \n0.41 | \n0.44 | \n0.30 | \n100 | \n
Mole fraction in liquid phase (%) | \n43.31 | \n5.35 | \n11.05 | \n7.82 | \n10.30 | \n11.21 | \n2.32 | \n4.10 | \n4.54 | \n100 | \n
Mole fraction of each component at pipe inlet in both phases.
Mole fractions of each component in both vapor and liquid phase are shown in Figure 5. The content of methane in vapor phase increases when flowing in the pipe while the content of the other light hydrocarbons become less and less in vapor phase. During the condensing process which is dominated by temperature drop, the methane keeps evaporating; while during the evaporating process which is dominated by pressure drop, the other light hydrocarbons keep condensing. Meanwhile, the bigger the molar mass is, the faster the condensing rate is.
\nMole fraction of each component changes along pipeline. (left) vapor phase; (right) liquid phase.
Six pipe cross sections located at every 1000 m along the pipeline are selected to illustrate the change of density and temperature distribution, as shown in Figures 6 and 7. It is exactly because the pressure on the cross section is the same, so the uneven distribution of the temperature leads to the uneven distribution of the fluid density. In the two phases, the density distribution is opposite to the temperature distribution. The high temperature means low density. The temperature value distributed at every single cross section can be ranked in descending order: the interior of liquid phase, most parts in vapor phase, vapor phase near the top wall. However, the descending rank of density is liquid phase, vapor phase near the top wall, and the interior of vapor phase. Along the pipeline, the temperature in the area referenced above decreases gradually while the density increases gradually. Therefore, the temperature of the sequential cross sections tends to be the same and the density distribution within the two phases gradually becomes uniform.
\nDensity (dimensionless) distribution depicted in 6 pipe cross sections along the pipeline (every 1000 m).
Temperature (K) depicted in 6 pipe cross sections along the pipeline (every 1000 m).
Figure 8 illustrates the selected 12 pipe cross sections located at every 500 m along the pipeline, where the varying trend of liquid level are presented in three-dimensional coordinate system. The minimum liquid level is 7.82 mm at pipeline inlet. The liquid level at outlet is about 16.18 mm and keeps declining trend, which can also be found in Figure 9(b).
\nLiquid level depicted in 12 pipe cross sections along the pipeline (every 500 m).
Pressure gradient, liquid level, fluid mass flow rate, and temperature along the pipeline. (a) pressure gradient, (b) liquid level, (c) mass flow rate, and (d) bulk temperature.
The pressure gradient, liquid level, fluid mass flow rate, and temperature along the pipeline obtained in the condition of condensation production have been compared with that found in literature.
\nWhen the phase change behavior is considered along pipe flow, the vapor in gas phase starts to condense to liquid which begins from the pipe inlet due to the significant temperature drop at pipe wall. The pressure drop fit well with the simulated results presented by Sadegh, as shown in Figure 9(a) [16].
\nDuring the condensing process, vapor mass flow rate gradually reduces, as shown in Figure 9(c), and the liquid mass flow rate increases due to the constant total mass flow rate. The increase of liquid mass flow rate leads to further rise of liquid level, as shown in Figure 9(b).
\nThe liquid holdup firstly increases until it reaches a maximum value and then gradually decreases. The reason behind this is as follows: The increase of liquid holdup results from the liquid precipitation caused by dominant temperature drop. Due to the large difference between fluid temperature and ambient temperature, the amount of liquid precipitation is greater than liquid evaporation. On the contrary, the decrease of liquid holdup is leaded by liquid evaporation due to dominant pressure drop. Being same to liquid holdup, the liquid mass flow rate maintains the same trend, that is, gradually increasing to reach a maximum value and then gradually reduced, which is depicted in Figure 9(c). As the total mass flow is constant, the mass flow rate of the vapor phase decreases first and then increases. When compared with the process of evaporation, the precipitation process caused by temperature drop is transient and intense, which is related to the temperature difference between the inside and outside of the pipeline and to the convective heat transfer coefficient.
\nThe tendency of temperature drop is similar to that in the existing research [16]. But there also exists difference between vapor bulk temperature, liquid bulk temperature, and the total bulk temperature, which cannot be revealed by one-dimensional model. The liquid bulk temperature is always higher than the vapor bulk temperature while the vapor bulk temperature is almost always equal to the total bulk temperature. Latent heat is revealed during the vapor condensing process which slows down the temperature drop, as shown in Figure 9(d).
\nThrough solving the model, with phase change happening, it can be obtained that the pressure gradient is 21.29 Pa/m and the liquid level is 16.02 mm when axial distance reaches 3000 m.
\nFigure 10(a) shows that the velocity of vapor phase slows down while approaching either the pipe wall or the vapor-liquid interface because of the hindering effects and fluid viscosity. The velocity of liquid phase keeps increasing from pipe wall to the interface. The maximum velocity at the pipe cross section occurs within the vapor phase.
\nVelocity and temperature distribution at pipe length of 3000 m. (a) Velocity profile at pipe cross section; (b) temperature profile at pipe cross section; (c) velocity profile at vertical centerline; and (d) temperature profile at vertical centerline.
In Figure 10(b) shows that the temperatures of both vapor and liquid phase drop while approaching the pipe wall because of the lowest ambient temperature and the convective heat transfer effects. The temperature of liquid phase keeps increasing from pipe wall to the interface. The maximum temperature at the pipe cross section exists within the liquid phase near the interface.
\nFigure 10(c) shows that the temperature at pipe wall of vapor phase is lower than that of liquid phase when convective heat transfer exists due to the smaller heat carried by the vapor phase than liquid phase. Thus, lower specific heat capacity results in bigger temperature drop at pipe wall of vapor phase. The thermal conductivity of the liquid phase is greater than vapor phase, hence, the temperature gradient in liquid phase is smaller than that in vapor phase, and the bulk average temperature of the liquid phase is higher than the vapor phase. Heat is transferring from liquid phase to vapor phase through the interface, which makes the temperature drop of the liquid phase and reduces the temperature difference between the two phases.
\nFigure 10(d) reveals the velocity distribution at the centerline of the pipe. By the dragging force of the interface, the velocity of liquid phase reaches the maximum value at the interface while the velocity of vapor phase reaches the maximum value at the location between the interface and its bulk center. The liquid phase slows down while approaching the pipe wall because of the hindering of the pipe wall and its high viscosity.
\nThe vapor-liquid two-phase pipe flow and heat transfer are studied by virtue of numerical simulation in light hydrocarbon transportation pipeline coupled with hydraulics, thermodynamics, and phase change. A three-dimensional non-isothermal vapor-liquid stratified flow model including phase change model in bipolar coordinate system has been established, where LES turbulence model is utilized to simulate the turbulence flow and the wall attenuation function is used to describe the inadequacy performance of vapor-liquid interface. The vapor phase and the liquid phase are both considered to be compressible and the PR equation of state is chosen for the vapor-liquid equilibrium calculation where the multi-component hydrocarbon flash calculation is used to evaluate the physical properties, gasification rate, and enthalpy departure of the phases. The P–T flash calculation has been applied to predict the varying liquid level and the multi-component mass fraction in each phase during the process of vapor/liquid stratified pipe flow. The axial pressure gradient, liquid holdup, velocity, and temperature fields have been presented. The fluid mass flow rate, mole fraction, density distribution, and liquid level along the pipeline are also given out.
\nThe simulation results indicate that the influence of pressure and temperature on liquid holdup is different. During the light hydrocarbon transportation process in pipeline, the temperature drop leads to the reduction of vapor mass flow rate and the rise of liquid level as well as mass flow rate. Larger temperature drop results in bigger liquid holdup while larger pressure drop causes smaller liquid holdup due to the change of physical properties and phase equilibrium. After the increase of liquid holdup caused by dominant temperature drop reaching the maximum value, then the decrease of liquid holdup maintains its trend till the pipe outlet, which results from liquid evaporation due to dominant pressure drop.
\nThe highest velocity locates in vapor phase while the highest temperature locates in liquid phase. The liquid bulk temperature is always higher than the vapor bulk temperature. The vapor bulk temperature is almost always equal to the total bulk temperature, which cannot be revealed by one-dimensional model. Latent heat is revealed during the vapor condensing process which slows down the temperature drop. The average velocity of liquid is lower than that of vapor, but the temperature of liquid is higher than vapor.
\nWhen the fluid flows in the pipeline, the content of methane in vapor phase increases all the time while the content of the other light hydrocarbons (\n
Thus, models in this chapter can be utilized to accurately predict pressure gradient, velocity, temperature field, liquid holdup, fluid physical properties, and mole fraction, which are essential to the determination of pipe size, design of downstream equipment, and guarantee of flow assurance.
\nThis work was supported by the National Natural Science Foundation of China [Grant number 51474228]; and the Beijing Scientific Research and Graduate Joint Training Program [Grant number ZX20150440].
\nAccording to the definition adopted by the National Nanotechnology Initiative, nanotechnology is the manipulation of matter with at least one dimension in the range of 1–100 nanometres [1]. At the moment nanotechnology, an interdisciplinary field having confluence of physics, chemistry and engineering [2] is one of the most attractive areas of science [3], with applications in various domains, which radically effected progress in the field of material science [4]. Nanofibre technology, which comprises the synthesis, processing, fabrication and application of nanoscale fibres [5], is one of the main progressions in nanotechnology [6].
\nAmong the technologies that can be used to obtain nanofibres (phase separation, template synthesis, self-assembly, melt blowing) [7], electrospinning is one of the most promising technologies, being commonly used for producing nanosize filaments from both organic polymers and inorganic materials [8], as it is uncomplicated, versatile and capable of producing controlled size fibres with high surface to volume ratio, hence more capable to interrelate with the surrounding environment. In addition, the electrospun nanofibre structures are characterised by complex three-dimensional open porous assembly, facilitating even more the interactions with the adjacent environment. The fact that nanofibres have only one dimension at nanoscale, since the others are at macroscopic one, makes it possible to mingle the advantages of nanostructures (high chemical and biological reactivity and electroactivity) with those of conventional solid membranes, such as comfortable manipulation and easy applicability.
\nA polymer solution or melt can be electrospun if it is able to carry an electric charge and has enough viscosity to be strained without breaking up into droplets. Up to now, more than 200 types of materials have been electrospun into nanofibres, among which natural and synthetic polymers and many hybrid blends [6].
\nThe principle of electrospinning is quite simple: by applying high voltages electrostatic field (e.g. 10–50 kV) to a polymer solution or a polymer melt, the surface of the fluid elongates and first forms a conical shape, known as the Taylor cone. Then, when the electric voltage reaches a threshold value, the jet of charged liquid overcomes the surface tension, leaves the Taylor cone and is drawn to the collector of different potential, forming a nanofibre net [9].
\nIn addition to the classic electrospinning process, many variants have been developed, capable of producing nanofibres with special features: core/sheath nanofibres [10], nanofibres with hollow structures, nanofibres with porous structures [11] and necklace-like and ribbon nanofibres [12].
\nThe elementary electrospinning setup has four parts: a reservoir of polymer in melt or solution form, a spinneret (in the simplest cases, a syringe), the high voltage power supply and the collector, which acts as a counter electrode (Figure 1).
\nTypical solution electrospinning setup.
Developments in electrospinning technology have made it possible to electrospin, besides polymers, polymers loaded with nanoparticles and functional molecules, ceramic materials and metal oxides. In addition, there have been developed fibres with new special structures [13].
\nIn addition to this basic setup showed in Figure 1, there are relatively many other approaches to the process, but in all cases the electrospinning process is influenced by the following three categories of factors: the particularities of the spinning polymer solution/melt, the parameters of the electrospinning process and the environment factors.
\nThe main characteristics of the polymer solution with a significant role in the result obtained after electrospinning are concentration, viscosity, conductivity, superficial tension and the volatility characteristics of the solvent.
\nThe solution viscosity is considered to be the dominant variable that determines the fibre diameter. To make electrospinning possible, the viscosity of the electrospun polymer solution must be within a precisely defined range. A too low viscosity leads to interrupted polymer filaments and the appearance of polymer droplets [14], while too high viscosity makes polymer extrusion impossible. The optimum values of viscosity differ according to the molecular weight of the polymer and the solvent used. Of course, there is a close correlation between the concentration of the polymer solution and its viscosity.
\nAn innovative approach to reducing the viscosity of the polymer solution is to apply low-frequency vibrations during the process [15, 16], when vibrations disrupt some of the van der Waals interchain interactions, disordering the polymer chains, which leads to a decrease in the solution viscosity.
\nElectrospinning fundamentally requires the transfer of electrical charge from the electrode to the polymer droplet at the end point of the syringe needle, so a minimum electrical conductivity in solution is therefore essential for the process; solutions lacking conductivity cannot be electrospun.
\nA correction of insufficient polymer solution conductivity can be obtained by adding an electrolyte, when the increased number of charges results in an increase in the solution elongation capacity, favouring the formation of smooth, small diameter fibres [17].
\nSurface tension, strongly influenced by the nature of solvent, is a very important factor in electrospinning; basically, if all the other conditions are established, surface tension controls the upper and lower limits of the range in which the electrospinning can be achieved [18, 19]. Surface tension can be adjusted by varying the polymer/solvent ratio in the spinning solution or by adding surfactant to the solution, which ensures the formation of more uniform fibres [20].
\nThe applied voltage is one of the most important parameters of the electrospinning process, as it influences directly both the dynamics of fluid flow and the morphological characteristics of the electrospun fibres.
\nOnly when the applied voltage exceeds a certain threshold value, load charged polymer jets are ejected from the Taylor cone. The size of this threshold voltage depends on the nature of the polymer-solvent system [21].
\nIt is generally accepted that an increase in the applied voltage leads to an increase in the deposition rate, thus there is a greater probability of defect formation [22, 23]. The length and diameter of the electrospun fibres decrease with the increase in applied voltage without any change in pore size [20]. For nanofibres produced with low voltage, a uniform morphology with fewer defects and drops is obtained [24].
\nThe distance between the electrode and the collector is important because, if correctly set, can control the morphology and diameters of the nanospun fibres. If the distance is too small, the fibres will not have enough time to solidify before reaching the collector, while if the distance is too long, it is possible to obtain fibre with beds at the surface [25]. A slight change in this distance significantly influences the characteristics of the fibres, the diameter of which becoming smaller as the distance to the collector increases.
\nThe flow rate of the polymer solution within the syringe is an important process parameter; generally, a lower flow rate is recommended to give the polymer solution sufficient time for polarisation. If the flow rate is too high, fibres with many beads are formed due to the insufficient time for the polymer filament to solidify before reaching the collector [26].
\nThe influence of the humidity of the environment in which electrospinning takes place is manifested in terms of fibre morphology, deposition orientation and solvent evaporation rate [27]. At very low humidity, a volatile solvent can be dried very quickly, while high humidity helps to discharge static electricity to electrospun fibres. In addition, at high humidity, condensation may occur at the surface of the fibre due to the cooling of the surface of the jet determined by the rapid evaporation of the solvent, and the air flow can interrupt the formation of fibres, causing ruptures [20].
\nThe temperature of the electrospinning environment has a significant influence on the process, as the evaporation rate of the solvent decreases exponentially with the decrease in temperature; when the evaporation process of the solvent becomes slower, the jet takes a longer time to solidify, which can lead to defects in fibre formation [28]. Consequently, temperature control is essential to adjust the evaporation rate of the solvent and the viscosity of the solution [29].
\nAt low atmospheric pressure, the polymer solution in the syringe tends to flow, causing an unstable jet initiation, and at very low pressures, electrospinning cannot be achieved due to direct discharge of electrical charges.
\nMelt electrospinning has a number of advantages over solution electrospinning, mainly linked to the absence of solvent, which reduces costs and makes the process more environmentally friendly [30]. In addition, by melt electrospinning, it is possible to transform into nanofibre polymers for which there are no suitable solvents, such as polyolefin or polyethylene terephthalate, or mixtures of polymers for which it is difficult to find an unique solvent for all the components [31, 32]. Unlike the solution electrospinning, where frequently a nonwoven fibrous mat is obtained, the melt electrospinning can produce filaments which can be used in knitting or weaving processes [33]. In this case, the melt electrospinning process (known as melt electrospinning writing) uses a moving collector, which exerts a translational movement sufficiently fast for the rectilinear deposition of the polymer jet [34].
\nIn addition to these advantages, there are difficulties arising from the particular equipment required (Figure 2) and the high viscosity and low electrical conductivity of melt polymers.
\nMelt electrospinning setup.
The main feature of the polymer melt that influences electrospinning is viscosity. As the viscosity of the melt is at least one order of magnitude greater than that of the polymer solutions, it is essential to reduce it. This is usually done by raising the temperature (without degrading the polymer) or by adding additives such as cationic surfactants [35, 36].
\nAnother parameter related to the polymer melt is the molecular weight of the polymer, which influences the diameter of the obtained nanofibres. When the molecular weight of the electrospun polymer is higher, the Melt flow index is lower and the diameter of the fibres is bigger. Because in the melt electrospinning, the viscosity cannot be controlled by adjusting the polymer/solvent ratio, like in the solution electrospinning, it is essential to choose a suitable molecular weight of the polymer to achieve a stable and reproducible electrospinning process [33]. It is believed that the optimal range of molecular weights for melt electrospinning is substantially lower than that characteristic of solution electrospinning. The process is also influenced by the stereoregularity of the polymer, the isotactic polymers producing finer fibres than the atactic ones [32].
\nThe conductivity of the polymer melt decisively influences the stability of the extruded polymer jet. A too high conductivity determines the jet’s instability, while a too small one will cause reduced electrostatic traction forces. It is considered that average conductivity values in the range of 10−6–10−8 S/m prerequisites for a stable electrospinning process [33].
\nIn what regards the processing parameters that influence the melt electrospinning process, it can be seen that, unlike the solution electrospinning, there is a direct proportionality relationship between the fibre diameter and the melt polymer flow rate.
\nConcerning the effect of the applied voltage on the diameter of the fibres, information is contradictory, but the overall conclusion is that for each polymer there is an optimum voltage range [37, 38, 39, 40].
\nThe distance between the spinneret and the collector is relatively lower in melt electrospinning than in the solution process (usually 3–5 cm). This distance influences the cooling process of the polymer melt jet and the shape of the fibres. Flat fibres may appear at smaller spinneret to collector distances, while larger distances affect the accuracy of depositing filaments on the collector in the melt electrospinning writing process [34].
\nSensors, which convert energy to detect concentration changes of a specific substance and communicate the information in the form of an electrical or optical signal [41], have gained special importance in recent decades, due to their numerous applications in areas such as monitoring environmental factors, health and wellbeing or detection of dangerous vapours [42].
\nA high specific surface area and a very porous structure are vital for high sensitivity and quick response of a sensor [31]. This is why electrospun nanomaterials, having large specific surface area and high and tunable porosity [43], have found frequent use in the field of sensors of many types, such as chemiresistive, optic (fluorescent and colorimetric), acoustic wave (piezoelectric) or photoelectric [13]. Electrospun nanostructured sensors display faster adsorption and minimised bulk effects when compared to the conventional sensors [44].
\nChemiresistive sensors, which work by measuring resistance variation when in contact with the substance to be detected, have a high miniaturisation potential, making them applicable to portable devices. Semiconductive polymers, metal oxides, metals and conjugated compounds are used to obtain such sensors [42, 45].
\nPolymers that exhibit conductivity, such as polyaniline (PANI), polypyrrole (PPY) and poly (3, 4-ethylenedioxythiophene) (PEDOT), are used as gas sensors [46]. For example, PEDOT, insoluble in pure state, becomes dispersible in water after doping with poly (styrenesulfonate) (PSS) and can be electrospun, the obtained nanofibres being used for the detection of inorganic compounds such as nitrogen oxide and ammonia and organic substances (ethanol, methanol and acetone) by measuring resistance variation [47, 48].
\nPolyaniline (PAni) doped with (+)-camphor-10-sulfonic acid (HCSA) has been electrospun and proved to be excellent ammonia sensors, while the electrospun fibres obtained from undoped PAni exhibited very good nitrogen oxide detection capabilities [49]. Polyaniline electrospun nanofibres also proved to be effective as moisture sensor, when the response to changes was given by impedance variation. It was found that the sensor exhibited a rapid, reversible and very sensitive change in impedance as a function of adsorbed water molecules [50]. A sensor from electrospun nanofibres from polyaniline/polyethylene oxide (PAni-PEO) doped with 10-camphosulfonic acid (HCSA) and deposited on a pair of gold electrodes modifies resistance, having a 0.5 ppm detection threshold for ammonia [51].
\nChemiresistive sensors from PAN/PAni electrospun fibres showed good sensitivity to NH3 gas at room temperature and this sensitivity increased with increasing gas concentration [52].
\nAmmonia sensors from quartz crystal microbalance coated with electrospun polyacrylic acid (PAA) membranes showed high sensitivity at low ppb level, but this sensitivity depended on the morphology of the nanofibres, the load of the quartz crystal microbalance with the electrospun membrane and the relative humidity [53].
\nAnother ammonia sensor was obtained by depositing a P-type conductive PAni onto the surface of n-type semiconductive TiO2 electrospun fibres. The sensitivity of this sensor substantially increases with the increase of NH3 concentration [54].
\nElectrospun nanofibres from PANI and PANI/ZnO were used to detect HCl and NH3 vapours at room temperature, recording a decrease in the resistance of the sensors when exposed to HCl vapour, respectively an increase in resistance when exposure to NH3 vapours. The PAni/ZnO sensor has a high sensitivity response at room temperature with better repeatability compared to that of the pure PANI sensor [55].
\nAn ammonia sensor based on a single PAni nanofibre demonstrated a very low detection value (under 1 ppm) and a response time under 10 s [56].
\nElectrospun nanofibres of poly (o-anisidine)-polystyrene doped with (+)-camphor-10-sulfonic acid proved to be effective in water and ethanol determination, showing a high sensitivity and rapid response and recovery [57].
\nElectrospun conductive polypyrrole nanofibres coating a copper interdigital electrode has been used to produce an aliphatic amines gas sensor with low detection limit (0.42 ppm for n-butylamine), quick response and good repeatability at temperatures between 90 and 200°C [58]. PAni/poly (vinyl pyrrolidone) nanofibres containing urease have been used as NO2 sensors, showing a significant conductivity increase in the presence of levels of NO2 in the range of 1–7 ppm [59].
\nElectrospun nanofibres of Al-SnO2/PAni were used as hydrogen sensors, having high sensitivity at low temperature (48°C) [60], while sensors made of PAni/TiO2:SnO2 nanofibres placed onto an epoxy glass substrate detected hydrogen at even lower temperature (27°C) showing good sensitivity [61].
\nElectrospun polyamide nanofibrous membranes have been proved to be effective as glucose biosensors, displaying a sensitivity of 1.11 μA/mM and a detection limit of 2.5 × 10−6 M [62].
\nTiO2 fibre mats obtained by electrospinning from a dimethyl formamide solution of poly (vinyl acetate) showed high sensitivity to NO2 and H2 with reversible response and a response times of the order of 1 min [63].
\nSensors for humidity and KCl were obtained from electrospun poly (lactic acid)/polyaniline fibres deposited onto interdigitated microelectrodes. The sensitivity of the sensor depends on the poly (lactic acid)/polyaniline ratio in the blend [64].
\nElectrospun nanofibre sensors have found applications in the medical field as well. A sensor composed of a electrospun conductive nanofibres mat with polyacrylic acid grafted on its surface and a sensing element made of conducting polymer with covalently attached oligonucleotide probes is effective in determining the non-Hodgkin’s lymphoma gene, with a detection limit of 1 aM (1 × 10–18 mol/L) and high selectivity [65].
\nSensing electrodes for catechol detection were obtained by electrospinning a PAni solution with dispersed multiwall carbon nanotubes followed by the reduction of the amino groups and the addition of polyphenol oxidase on the nanofibres [66].
\nOptical sensors work by altering the colour or intensity of their fluorescence by the analyte [42]. These sensors, which are usually based on a technology that allows miniaturisation, low cost and in-situ usage, show high sensitivity and selective response towards various analytes [67].
\nCompared to other methods of obtaining nanofibres, electrospinning provides nanofibres for optical sensors, which are easy to manufacture and operate, relatively low-priced and with customizable properties, such as diameter, morphology and porosity [68].
\nThere are three ways to obtain optical sensors by electrospinning: inserting chromophores into a transparent polymer without optical properties; using as substrate polymers having the ability to absorb/emit light and the functionalization of the electrospun polymer with active optical nanosystems [42].
\nElectrospun core-shell nanofibre with polymethyl methacrylate shell and a core made of phase change thermochromic material show thermochromic phase change comportment and can be used in detecting foreign materials in a specific environment [69].
\nA colorimetric sensor made of electrospun porphyrinated polyimide (PPI) nanofibrous membrane proved to be effective in hydrogen chloride detection, showing high sensitivity and fast response time. When exposed cu HCl vapours, the polymer changes its colour from pink to green, as a result of the protonation of the neutral porphyrin [70], and the colour intensity increases as the concentration of HCl is higher.
\nColorimetric strip sensors to detect uranyl (UO22+) have been produced using electrospun cellulose acetate nanofibre mats that incorporated 2-(5-Bromo-2-pyridylazo)-5-(diethylamino) phenol. The colour in these sensors changes from yellow to purple in the presence of uranyl at pH 6.0, and the detection limit can extend to 50 ppb, with very low interference ability in the presence of other metal ions [71].
\nColorimetric sensors have been produced incorporating gold nanoparticles into electrospun polystyrene nanofibres. These sensors, which do not employ any complex instrumentation, showed very good response towards oestrogenic compounds such as 17β-estradiol, with high sensitivity [72].
\nOptically active electrospun nanofibres can be used as sensors to detect heavy metals using colorimetry and fluorescence methods [68].
\nColorimetric sensors based on nanofibres electrospun from a mixture of 10, 12-pentacosadiynoic acid and poly (ethylene oxide) and polyurethane can be used to detect Escherichia coli [73].
\nMembranes from electrospun polyamide 66/cobalt chloride proved to be effective in determining humidity, due to the colour change property of cobalt salt, which turns from blue to pink as the relative humidity increases over 12.4%. The sensor has high sensitivity, fast response time, good reproducibility and long-time stability [74].
\nMats from electrospun cellulose acetate fibres doped with the chromogenic and fluorogenic amine-reactive blue dye Py-1 act as colorimetric sensors detecting biogenic amines [75].
\nA nanofibre-based fluorescent sensor for Ni2+ determination, even in the presence of other competing metal ions, was obtained by electrospinning pyridylazo-2-naphthol-poly(acrylic acid) polymer functionalized with 1,10-carbonyldiimidazole and 1,8-diazabicyclo[5.4.0]undec-7-ene [76]. The sensor showed high sensitivity and selectivity in its fluorescence towards Ni2+, and the detection was simple, rapid and selective, without any need of additional sample handling phases.
\nOptical fluorescence sensors based on poly (acrylic acid)-poly (pyrenemethanol) polymers have proven effective for the detection of metal ions (Fe3+ and Hg2+) and 2,4-dinitrotoluene (DNT), showing high sensitivity due to the high-volume surface ratio of the nanofibre membrane structures [77].
\nA fluorescence sensor based on a pentiptycene conjugated polymer was used for Copper (II) cation detection, with high selectivity and sensitivity [78].
\nA fluorescent film sensor made of electrospun nanofibres from a copolymer of vinyl naphthalimide and methyl methacrylate was used for Cu2+ detection, showing high sensitivity (a detection limit of 20 × 10−6 M Cu2+) [79].
\nA picric acid fluorescent sensor was obtained by electrospinning a solution of 5-(N-carbazole styryl)-1, 3-dimethyl-barbituric acid and polystyrene in dimethyl formaldehyde/tetrahydrofuran upon an amino-functionalized glass. The emission intensity of the fluorescent sensor is not significantly influenced by common interferents and the fluorescent nanofibres can be regenerated [80].
\nFluorescence sensors for detecting traces of toluene vapours have been produced by embedding fluorescent CdTe quantum dots in electrospun polyvinyl alcohol nanofibres, showing sensitivity and fast time response [81].
\nA fluorescence sensor for Cu2+ sensing, which displays good sensitivity and selectivity, was obtained from electrospun rhodamine dye-doped polyester nanofibres [82].
\nA fluorescent sensor for the rapid detection of bacteria was made from electrospun membranes of a boronic acid copolymer, poly (4-vinylphenylboronic acid-co-2-(dimethylamino) ethyl methacrylate-co-n-butyl methacrylate), showing high affinity and towards both Gram-negative and Gram-positive bacteria [83].
\nOptical sensors based on electrospun polyvinyl alcohol nanofibres with embedded nanocomposite cerium oxide nanoparticles can be used to detect radicals in solutions. These nanocomposite nanoparticles are fluorescent with observable emission under near-UV excitation [84].
\nBesides the chemiresistive and optical sensors, other categories of electrospun nanofibre sensors have been developed.
\nAn electrospun nanofibre piezoelectric sensor made of polyvinylidene fluoride (PVDF) nanofibre nonwoven webs proved to be effective in acoustic sensing for various applications [85].
\nA humidity sensor was obtained by depositing polyaniline composite nanofibres on surface acoustic wave resonator, demonstrating very high sensitivity, fast response and good sensing linearity [86].
\nSensors based on gas adsorption on electrospun PAni fibre mats have been used to determine carbon dioxide. The process is reversible, and the adsorption process is fast enough to make quick detection possible [87].
\nSurface acoustic wave sensors are piezoresistive sensors [88]. Such a sensor based on creased polypyrrole film with electrospun polyvinyl alcohol nanowires as spacer showed high sensitivity, low detection limit and good stability [89]. Other piezoresistive sensors have been obtained from polyvinylidene fluoride and its blend with polyoctafluoropentyl acrylate [90].
\nDue to their small size and high surface-to-volume ratio, many sensors based on electrospun nanofibres have been used lately for analyte detection, proving great sensitivity and very rapid response time, all in elevated stability conditions. Nanotechnology is constantly developing towards new challenges in many areas including sensors. In future developments, it can be expected that the problems that affect the efficacy of electrospun nanofibre sensors are to be addressed and solved, beginning with a more accurate control of the process in order to achieve better control over the size and morphology of the nanofibres and continuing with increasing pore uniformity for more sensitivity and improving the reversibility of the sensors.
\nThis work was supported by a grant from the Romanian National Authority for Scientific Research and Innovation.
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\\n\\nIntechOpen will help you complete your payment safely and securely, keeping your personal, professional and financial information safe.
\\n\\n7. ONLINE PUBLICATION, PRINT AND DELIVERY OF THE BOOK
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