",isbn:"978-1-83881-111-2",printIsbn:"978-1-83880-992-8",pdfIsbn:"978-1-83881-112-9",doi:null,price:0,priceEur:0,priceUsd:0,slug:null,numberOfPages:0,isOpenForSubmission:!0,isSalesforceBook:!1,isNomenclature:!1,hash:"acb2875b3bfc189c9881a9b44b6a5184",bookSignature:"Dr. Abdo Abou Jaoudé",publishedDate:null,coverURL:"https://cdn.intechopen.com/books/images_new/11865.jpg",keywords:"Linear Operators, Normal Operators, Spectral Theorem, Applications, Differential Operators, Integral Operators, Functional Calculus, Complex Variables, Complex Analysis, Theory, Recent Advances, Latest Trends",numberOfDownloads:null,numberOfWosCitations:0,numberOfCrossrefCitations:null,numberOfDimensionsCitations:null,numberOfTotalCitations:null,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"April 13th 2022",dateEndSecondStepPublish:"June 21st 2022",dateEndThirdStepPublish:"August 20th 2022",dateEndFourthStepPublish:"November 8th 2022",dateEndFifthStepPublish:"January 7th 2023",dateConfirmationOfParticipation:null,remainingDaysToSecondStep:"2 months",secondStepPassed:!0,areRegistrationsClosed:!1,currentStepOfPublishingProcess:3,editedByType:null,kuFlag:!1,biosketch:"Abdo Abou Jaoudé is a pioneering Associate Professor of Mathematics and Statistics at Notre Dame University-Louaizé. 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1. Introduction
Turbulent flow is the most common flow in industrial applications and atmospheric phenomena. The random motion inherent in the flow contributes the largest share of fluid mixing and interaction with solid surfaces (e.g. friction, heating, and pollutant dispersion). Natural ventilation in modern cities, flow-induced vibrations of large civil structures, performance of windmills, etc. keep the topic ever interesting. Hundreds of researches have been devoted to the subject aiming at characterizing this randomness. The main objectives are (1) to set an exact solution (or at least a mathematical model) to the turbulent flow problem and (2) to control it, for example, modify vortices and thereby reduce the drag on surfaces.
The random appearance of turbulent flow is violated by many well-established evidences. For instance, compared to a random signal, the turbulent velocity signal displays non-zero trends in both the energy spectrum (Figure 1) and autocorrelation (Figure 2) analyses. These examples, among many others, reveal the existence of organized motions within the irregular background. These organized motions are termed turbulence coherent structures (TCSs). Thus, TCSs are either vortices or uniform-momentum regions within the turbulent flow; these structures maintain their coherence over remarkable extents in time and space. The TCSs play a prominent role in the transport and mixing processes within the turbulent flow. Accordingly, few friction-reduction schemes target manipulating the TCSs. Furthermore, few researches attribute large parts of the loading on windmills to the TCSs. It follows that the understanding of TCSs is inevitable in solving and controlling turbulent flows.
Figure 1.
Energy spectrum of turbulent flow compared to a random signal.
Figure 2.
Autocorrelation function of turbulent flow compared to a random signal.
In this chapter, we focus on the basic kinds of TCSs and their presumable generation mechanisms. We start with the hairpin vortex, which is the elementary building block of TCSs. We characterize the hairpin vortex and detail its popular bursting theory of generation. Afterwards, we discuss the vortex packets and superstructures, which form the turbulent/non-turbulent interface bulges and contribute around half the turbulent kinetic energy and turbulent transport. Finally, we review the theories of TCS generation in high-Reynolds number flows.
2. The hairpin vortex
The first conceptual model for TCSs was proposed by Theodorsen [1]. From his observations, he noticed the turbulence vortex to take a hairpin or horseshoe shape with the legs aligned streamwise and the head located downstream and curved up, Figure 3. Theodorsen applied a vorticity-based version of Navier-Stokes equations to the proposed model vortex. He hypothesized the head to be inclined at an angle 45° to the mean flow direction since it subjects the hairpin to the maximum stretching from the mean flow and hence achieves the maximum turbulence production. The legs (streamwise vortices) induce upward flow on the head, which causes it to be lifted up. The vortex is then subjected to stretching by the mean flow since the head lies in a higher-velocity region than the legs (shear effect), see Figure 4. This shear causes the vortex to extend in length and compress in diameter. Consequently, the vorticity intensifies, that is, rotation becomes faster and hence more lifting force is generated and the head moves up further. This sequence is resisted only by the shear stress which, although lengthening the vortex, exerts a restoring moment on the head to return it to the zero-shear horizontal position. The inclination angle of the vortex will depend on the balance between the two conflicting effects. The hairpin vortex model was first verified experimentally by Head and Bandyopadhyay [2] through a smoke visualization experiment. They measured the angle and found it to fall well between 40 and 50°. As justified by Head and Bandyopadhyay, the angle of principal stress in the pure shear flow is 45°. Brief reviews of Theodorsen’s paper are found in [2, 3, 4].
Figure 3.
Illustration of the hairpin vortex model; vortex head lifting by induction from the legs.
Figure 4.
Hairpin vortex stretching.
Long before the first documented visualization of the hairpin vortices, Theodorsen’s model was confirmed, partly, by the correlation analysis of Townsend [5] and Grant [6] which was developed in [7]. Townsend depicted the dominant TCSs as randomly located couples of counter-rotating vortices aligned in the streamwise direction. These vortices (eddies) are of cone-like structure with the vertex upstream and the base downstream. An eddy size scales with its distance from the wall; hence his model is named the attached eddy model. The attached eddies can be thought of as headless hairpin vortices. In addition to Townsend, Willmarth, and Tu [8] conducted pressure-velocity correlation analysis that demonstrated the turbulence coherent structure as a transverse row of inclined triangular tubular vortices.
The symmetric structure of the hairpin vortex is the exception rather than the rule [3, 9, 10, 11, 12, 13]. The turbulence-inherent perturbations of the background flow cause the generated hairpin to be born distorted, for example, one-legged. Zhou et al. [14] examined the conditions to synthesize hairpin vortices by utilizing direct numerical simulation (DNS). They found the asymmetric hairpins to form more readily in rapid succession and at smaller streamwise separation. In the same article, Zhou et al. explained how the induction of the hairpin legs could cause the head to deform into an Ω-shaped structure. Thus, the transverse vortex can exist in many forms; cane, hairpin, horseshoe, or Ω -shaped vortices and deformed versions.
With or without the legs being attached to the wall, a hairpin vortex persistently rises across the boundary layer. The vortex envelope expands in the wall-normal and spanwise directions. The vortex core enlarges and weakens due to shear relaxation in the outer layer. Along the way up, hairpin-hairpin merging occurs to form larger and stronger vortices [15]. The hairpins align streamwise in groups (packets) to form the bulges at the edge of the turbulent boundary layer [2, 16, 17, 18], see Figure 5. Ultimately, under excessive stretching, the hairpin legs get very close and cancel each other i.e. the vortex dies [18]. However, the vortex dies anyway after a while by viscous diffusion. The debris from the dead eddies is convected away from the wall and undergoes stretching and distortion by live eddies to form isotropic fine-scale eddies surrounding the attached eddies [15]. Lozano-Durán and Jiménez [19] performed a DNS to inspect the evolution of coherent structures. They argue the tendency of eddies to remain small and die shortly; few eddies only attach to the wall and expand self-similarly across the logarithmic layer. These hold-on for lifetimes, which are proportional to their distances from the wall. These eddies are responsible for the vast majority of momentum transport. The hairpin vortices transport the low-momentum fluid from the wall layer to the outer layer. The hairpins are the main elements responsible also for vortex regeneration and hence the self-sustenance of flow turbulence [20, 21].
Figure 5.
Hairpin vortices may reach the end of the TBL to compose the turbulent/non-turbulent interface bulges.
3. From eddies to turbulence
The coordinate system is defined by x, y, and z as the streamwise, spanwise, and wall-normal directions and the velocity components are given by u, v, and w, respectively. The time-mean and fluctuating components are referred to by capital letters and (‘) signs. The stirring effect of the vortices is illustrated in Figure 6. The rotation of the hairpin vortices, either the head or legs, disturbs the fluid in two ways. The low-speed fluid (−u′) from the bottom layers is pumped upward (+w′), an event named second-quadrant or Q2 event, whereas the high-speed fluid (+u′) from the top layers is pumped downward (−w′), an event named fourth-quadrant or Q4 event. Experiments held by [22] have proven the Reynolds’ turbulent stresses u′w′¯ to be formed up of mainly Q2 and Q4 events. That means, the Q2 and Q4 fluctuations are more probable than Q1 and Q3 ones [3]. The turbulent kinetic energy is defined as k=12u′2+v′2+w′2¯. The literature, especially of numerical analysis, defines the production of the turbulent kinetic energy as u′w′¯∂U∂z [23]. Hence, it can be said that hairpin vortices by their stirring action are the turbulence producers i.e. they cause the fluctuations read by the hotwire probe or pressure transducer. Some researchers like to make a shortcut by identifying vortex generation as turbulence production.
Figure 6.
Q2 and Q4 events.
4. Generation of the hairpin vortex
The generation of hairpin vortices is attributed mainly to what is called the bursting process [3, 10], which occurs in the buffer layer. Before proceeding with the bursting process, it is better to introduce the low-speed streak, which is the key element in the bursting process. The low-speed streaks are long, narrow, uniform-momentum regions aligned quasi-streamwise, see Figure 7. They exist exclusively in the inner layer (below z+~10) and move downstream at speeds lower than the mean flow speed (where z+=u∗zν, ν is the kinematic viscosity, and u∗ is the friction velocity). The streaks were first observed by Francis Hama [24] and concurrently by Ferrell et al. [25] in tube flow by injecting dye through a slot in the wall in the first experiment and by flushing a flow of colored water by a clear fluid in the second experiment.
Figure 7.
Low-speed streaks.
The streaks can extend in length to 1000 viscous (wall) units [26, 27] (one viscous unit =u∗ν) and in width to 20 viscous units [28]. The transverse spacing between streaks depends on the turbulent Reynolds number, Reτ=δu∗ν, or momentum-thickness Reynolds numbers, Reθ=θU∞ν, [29] (where θ is the momentum thickness). The streak transverse spacing is equal to λy+=100 at Reθ=2000 [30] and widens to λy+=200 at Reθ=40,000 [8, 31]. Nevertheless, a later study by Smith and Metzler [32] for 740<Reθ<5830 suggested the low-speed streaks to have an invariant spacing of λy+=100. This value was found to provide the maximum energy amplification of a perturbation in turbulent flow [33, 34, 35]. It is worth noting that a flow domain of spanwise extent less than λy+=100 cannot sustain turbulence [36].
5. The bursting process
The bursting process as described by Kline et al. [37] and Kim et al. [29], with updates from later observations, passes through three stages:
Streak-lifting: The streak moves downstream and migrates gradually from the wall. The streak becomes thinner as it drifts outward. After a certain critical distance, the streak is lifted up rapidly away from the wall. This streak transports the low-momentum fluid near the wall to the upper layers, which causes an inflection in the streamwise instantaneous velocity profile. A spanwise shear layer is formed atop the streak upstream or downstream the crest. The shear layer (vorticity layer) is a circulating area of fluid of elliptic or generally non-circular shape. The shear layer rolls up in a circular form to generate a spanwise vortex (circular shear layer). The vortex is then stretched and lifted by the mean shear to form a streamwise and/or a hairpin vortex. Thus, streamwise and/or spanwise vortices propagate downstream the inflection point.
Oscillation: When the streak reaches a height of z+=8−12, it starts to oscillate. The oscillations are three-dimensional, that is, can be seen in both x−z and x−y planes and tend to be regular and organized.
Break-up: After a certain number of oscillations (3–10) the motion turns to be random and violent. This ends up with the streak broken-up and disappeared.
It follows then a quiescent period before the cycle is repeated. An illustration of the bursting process is shown in Figure 8. The oscillations of the streak are actually due to the formation and stretching of the born vortices. The concluding violent motion is imputed to the vortex stretching under the combined effect of turbulent background and successive-ascent through higher-faster-layers [38]. Smith and Metzler [32] discovered that the streak does not break down after the bursting process. It rather persists owing to the reinforcement by the legs of the new hairpins.
Figure 8.
The bursting process as described by Kim et al. [29]. (a) Low-speed streak moving downstream and gradually lifting away from the wall. (b) Streak-lifting: the streak is lifted rapidly. (c) Oscillation: the streak starts an organized 3-D oscillation. (d) Break-up: random, violent oscillations that end with the streak broken up into small motions.
Corino and Brodkey [39] complemented the picture with a sweep at the onset of the burst sequence and multiple ejections of low-momentum fluid followed by a sweep at the end of process. An ejection is a Q2 event, while a sweep is a Q4 event. The sweep at the onset of the burst may be responsible for lifting the streak. As elucidated by Grass [40], the sweep (inrush) stream triggers the bursting process, while the ejection stream is a consequence of the bursting process and can extend across the entire boundary layer. On the other hand, Nakagawa and Nezu [41] and Smith [42] suggested the final ejections and sweep to be invoked by the generated hairpin vortices. The inward side of the vortex entrains low-momentum fluid from the streak and pumps it upward. The vortex navigation over the streak appears like multiple rapid ejections, whereas the outboard side entrains high-momentum fluid from the upper layers and pumps it toward the lateral extremes of the streak. Since the vortex is already inclined to the flow direction, the ejection and sweep appear as Q2 and Q4 events, see Figure 9.
Figure 9.
Ejection and sweep events caused by a hairpin vortex.
Smith [42] considered each burst to be responsible for generating 2–5 vortices. Kline et al. [37] also estimated the frequency of bursts and found it to match with the dominant frequency in the wall-pressure spectrum analysis held by Black [43]. Kim et al. [29] found that most/all occurrences of turbulent stresses (−u′w′¯) take place not only in the near-wall region but entirely during the bursting process, which opts the bursting to be the main turbulence producer. This harmonizes with the early predictions of Runstadler et al. [44]. Kline et al. [37] anticipated the death of turbulence (flow relaminarization) when suppressing the bursting process and fetched many examples in this context:
Relaminarizing turbulent boundary layer flow by applying a favorable pressure gradient; the pressure gradient hinders the lift-up process (a conclusion of the same paper [37] and other later, more comprehensive researches [45, 46]).
Relaminarizing turbulent flow in a tube by rotating the tube about its axis; the centrifugal force affixes the streaks to the tube wall [47].
Relaminarizing turbulent flow in a 2-D channel by rotating the channel about an axis fixed at one of the narrow walls and perpendicular to the mean flow direction; the Coriolis force suppresses turbulence at one wall and strengthens it at the other wall [48].
6. Streak generation
The streaks are created by streamwise vortices occupying the wall region [28, 49, 50]. Each streamwise vortex pumps the fast fluid from upper layers in one y direction and the slow fluid from wall-vicinity in the second direction. This action packs a body of high streamwise velocity at one side of the vortex and another of low streamwise velocity at the other side. These are termed the high-speed and low-speed streaks, see Figure 10.
Figure 10.
High- and low-speed streak generation by streamwise counter-rotating vortices.
For dye injected (or hydrogen bubbles generated) near the wall, the pumping action of the vortices accumulates the dye together with the wall-adjacent fluid in the low-speed streak. This is why the low-speed streaks appear in flow visualization experiments. It has been recorded that a streak can exist by its own [51], that is, the streamwise vortices form the streak and leave it behind. The streamwise vortices can be the legs of hairpin vortices. This means the streaks generate the hairpin vortices which in turn generate new streaks. This closes the turbulence self-sustenance cycle. The streak-hairpin-streamwise vortex mechanism is only one presumable mechanism for turbulence generation/maintenance among few others.
Robinson [10] and Schwartz [52] believed the low-speed streak to be lifted up or kinked by flow-induction from a streamwise vortex. Offen and Kline [53, 54] and Smith [42] have a somehow longer explanation. The vortical remnant from an upstream burst forms a traveling pressure disturbance (instability). This traveling disturbance if passed over a low-speed streak impresses a local adverse pressure gradient upon a portion of it. This decelerates a part of the streak and hence lifts it up.
7. Generation of streamwise vortices
The streamwise, quasi-streamwise, vortices or rolls are the main turbulence producers in the viscous sublayer and responsible for low-speed streak formation. They are generated by different mechanisms:
They can be simply the legs of hairpin vortices. The legs of a hairpin vortex are quasi-streamwise and are usually attached to the wall i.e. lie in the sublayer. They range in length between 100 and 200 wall units [14]. There are two theories to interpret how these relatively short legs can produce the long streaks (∆x+~1,000). First, they sweep downstream along the wall, pack the streak and leave it behind in the long trails [55]. Second, many legs coalesce together and create the streak [21, 42, 56].
The streamwise vortices can be regenerated by other streamwise vortices [4, 14, 57, 58]. The shear (velocity gradient, ∂U∂z) causes the quasi-streamwise vortices to be stretched and lifted, that is, the upstream side is attached and the downstream side is detached from the wall (~9° inclination angle). Besides, the flow induced by other neighboring vortices tilts them in the spanwise direction (±4°). The wall-normal detachment motion and spanwise tilt motion provoke high vorticity in the wall-normal direction. This wall-normal vorticity is then affected by the shear that stretches it and turns it in the streamwise direction. A child vortex is then born on the downwash side (flow toward the wall) at either the upstream or the downstream ends of the parent vortex. The direction of rotation of the child vortex is opposite to that of the parent vortex. The flow induced by the parent tilts the child in spanwise direction. The legs of a hairpin vortex can produce two pairs of streamwise vortices, inboard and outboard the hairpin [59]. Finally, we get a corrugated line of quasi-streamwise vortices.
The streamwise vortices can be generated during the bursting process [60]. Although the interaction between the low-speed streak and the mean flow produces a spanwise shear (vorticity) layer, this can turn in the streamwise direction to form a streamwise vortex. Depending on the presence of the streamwise vortex that lifts the streak, different types of vortices can be generated. If one lifting streamwise vortex is present at one side of the streak, the new vortex extends over it downstream such that the direction of rotation of the new vortex is opposing the old one, while if no streamwise vortices are present beside the streak, then the new vortex evolves in an arch vortex, see Figure 11.
The streamwise vortices, and even the spanwise vortices, can be produced by some low-speed streak instability [10, 50, 55, 61, 62]. An instability (waviness) in the spanwise direction can be excited by the asymmetric flanking-vortices. The waviness generates a streamwise vorticity layer. Once the waviness grows enough, it produces a strong velocity gradient in the streamwise direction, ∂u∂x. This gradient is responsible for stretching the aforementioned layer and collapsing (compressing) it into a streamwise vortex (circular vorticity layer). Schoppa and Hussain [61] proposed three possible processes for vortex generation by streak instability—namely Process A: regeneration within gaps between consequent vortices; Process B: regeneration from an existing spanwise (arch) vortex, whose spanwise profile, excites streak instability to produce a pair of new streamwise vortices; and Process C: regeneration at trailing ends of low-speed streaks. Since the spawned vortices travel faster than the streak, they totally advect the streak leaving it behind and a new set of vortices are spawned.
Finally, streamwise vortices may generate from existing streamwise vorticity layers [63]. These vorticity layers were observed to evidence near the edge of the viscous sublayer. One layer tends to roll up into a compact streamwise core either due to the mutual induction with its image vorticity layer [50, 64] or by ejection from a parent, opposite signed, vortex [65]. The two mechanisms are illustrated in Figures 12 and 13, respectively.
Figure 11.
Generation of a streamwise vortex during the bursting process. (a) Lifted low-speed streak, (b) presence of the lifting streamwise vortex at one side of the streak, and (c) absence of the lifting vortex and generation of an arch vortex.
Figure 12.
Roll-up of a streamwise shear layer by mutual induction with its image.
Figure 13.
Roll-up of a streamwise shear layer by ejection from a parent vortex.
Either theory of the streamwise vortices implies that they are the main occupants of the viscous sublayer, whereas the outer layer is dominated by transverse vortices (heads of the hairpins). Bearing in mind their extended lengths compared to the spanwise (arch) vortices, the streamwise vortices are the main contributors to Reynolds stress in the sublayer [9, 27, 60, 66, 67, 68, 69, 70, 71].
8. Turbulence sustenance by instability
In the foregoing discussion, the bursting process, and hence vortex generation, was almost totally undertaken by other coherent structures. This is termed the parent-offspring mechanism for turbulence production. On the contrary, a broad team of researchers designates a role in the vortex regeneration process to flow instabilities. The instabilities are supposed to take many forms and play different roles in turbulence generation [50, 72, 73, 74].
According to Swearingen and Blackwelder [75], instabilities motivate the generation of streamwise vortices and then trigger the generation of the hairpin vortices. Taylor-Görtler instabilities prevail near the wall due to streamline curvature, either as an inherent property of the TBL profile [73] or a result of the passage of a large-scale disturbance [36]. These can produce a system of streamwise vortices. The streamwise vortices in turn pump the fluid to build the low- and high-speed streaks. Consequently, two inflectional velocity profiles are formed (Uz and Uy). From Rayleigh’s criterion which has been upgraded by Fjørtoft’s theorem, these inflectional profiles are inherently unstable [40, 55]. Thus, a secondary instability is generated which causes the streak lift-up, giving birth to new horseshoe vortices. Recall that the streak oscillations were interpreted by Kline et al. [37] as Kelvin-Helmholtz instabilities due to the growth and roll-up of the shear layer formed above the streak.
9. Large-scale motions (LSMs, vortex packets)
A vortex packet or large-scale motion is a bundle of hairpin vortices comprising 2–10 vortices aligned streamwise and traveling together. The inboard inductions of the hairpins against the mainstream combine together to form a relatively large region of uniform low momentum. The length of the packet ranges within 2–3δ. The recognition of vortex packets dates back to the early hairpin vortex visualizations [76]. According to Smith [42], the arrangement of the hairpins in packets is a natural consequence of their production as groups (2–5 vortices) in the bursting process. Zhou et al. [14] conducted a DNS to study the mechanism of generation of vortex packets. The simulation started with a pair of counter-rotating streamwise vortices which evolved into a hairpin. If this primary hairpin is strong enough, its induced flow interacts with the mean flow or induced flow from another hairpin to deliver secondary, tertiary, and downstream vortices. This vortex spawning complies with the findings of Doligalski et al. [77]. The final tent-like shape of the packet is very similar to the early hypothesis of Head and Bandyopadhyay [76].
The primary vortex and its offspring flock together as a packet. Adrian and his team [21, 78] further extended their vortex packet paradigm through experimentally studying the vortex packet behavior in the outer layer. The inboard induction of the packet hairpins against the main stream causes the packet to travel at a speed slower than the mean flow (~0.8U∞). As the hairpin ages, it expands in size and hence the induction is attenuated. Thus, the upstream parent hairpin moves faster than the downstream offspring; the packet stretches in the streamwise direction. Progressively, the overall induction of the packet hairpins is weakened. In addition, the hairpins move to higher faster fluid layers. Consequently, older packets move faster than younger packets and may overrun them. Packets can also merge with adjacent packets either streamwise or spanwise to form larger, stronger ones [79]. A vortex packet can extend to the edge of the boundary layer to form at least part of the turbulent bulges [3, 80]. Surprisingly, the description of the turbulent bulges introduced by Kovasznay et al. [81] agrees with that of the vortex packets. Moreover, Brown and Thomas [73] conducted correlation analysis across 75% of the TBL. They recognized large structures of length 2δ and 18° inclination angle. From their PIV analysis, Ganapathisubramani et al. [82] confirmed the existence of the hairpin vortex packets. They could identify packets as long as 2δ. The packets hold more than 25% of Reynolds stress although occupying less than 4% of the total area. However, Ganapathisubramani et al. expected the packets to break down outside the logarithmic layer. While the angle of inclination of the hairpin vortex fluctuates around 45°, the packet as a whole leans against the wall at an angle of 10.5–13° [21, 78]. The LSMs are accompanied on either side with somehow shorter high-speed structures [13].
The vortex packet paradigm [21] assumes some kind of interaction between the large and small vortex packets. The larger packets move at higher speeds than the smaller ones such that they overtake them. As such, the smaller packets are liable to be enclosed in the uniform momentum zones of larger packets. As a consequence, the velocity vectors of the small scales undergo modulation by the larger ones. A modulating role for the large scales on the near-wall streaks was proven by Toh and Itano [83]. The modulation comprises the three velocity components [84] and extends to the frequency [85]. However, Hutchins [86] seizes the modulation to the near-wall region and interprets the similarity in amplitude between the scales outside it as a mere matter of preferential arrangement.
10. Very large scale motions (VLSMs, superstructures)
From their power spectral analysis of the streamwise velocity signal in channel and pipe flows, Jiménez [87] and Kim and Adrian [80] discovered a bimodal trend for the premultiplied spectrum. The two spectrum peaks correspond to wavelengths of 2–3 δ and 12–20δ. The former was attributed to vortex packets (or turbulent bulges) whereas the latter was attributed to a turbulence coherent structure that extends very long streamwise. It was therefore named the very large scale motion (VLSM) or superstructure. Kim and Adrian conjectured that hairpins align in groups to form long LSMs, and LSMs in turn align coherently to form superstructures, see Figure 14. This hierarchical structure has been proven by Baltzer et al. [88] and received approbation from other authors [79, 89]. Nevertheless, Bailey et al. [90] found a disparity between the transverse (azimuthal) scales of both LSMs and superstructures that suggests the latter to be formed either by alignment of the biggest LSMs or separately from flow instabilities. Moreover, Hwang and Cossu [91, 92, 93] found from large eddy simulations (LESs) that the superstructures self-sustain even when the small-scale structures in the buffer and logarithmic layers are artificially quenched.
Figure 14.
A VLSM turns out from agglomeration of several vortex packets aligned in the streamwise direction.
Superstructures were recorded over the lower half of the turbulent boundary layer, including the logarithmic region [89]. The superstructures contribute 50% to the turbulent kinetic energy and more than 50% to the Reynolds shear stress [94, 95]. Dennis and Nickels [89] conducted experimental (3D PIV + Talyor’s hypothesis) tests on boundary layer flow from which they estimated the length of superstructures to be limited to 7 δ. However, superstructures as large as 30 δ were found in pipe flow by DNS held by Lee and Sung [96] and by hotwire measurements held by Monty et al. [97]. The large difference between the two turbulent flows is caused by the free surface in case of TBL where entrainment occurs of large plumes from the free stream into the TBL. This entrainment breaks down the long coherent structures. Hutchins and Marusic [98] provided direct evidence of the superstructures in the logarithmic and lower wake regions of the turbulent boundary layer and atmospheric surface layer through velocity contours obtained from a rack of hotwires and sonic anemometers. Moreover, they found the superstructures to meander extremely along their length. The low-speed superstructures are usually twinned with high-speed structures of comparable lengths, probably induced by hairpin vortex legs [89]. The superstructure resembles an outer-layer counterpart of the low-speed streak [33]. The first is 12–20 δ long and 3–4 δ spanwise spaced, whereas the second is 1000 wall-units long and 100 wall-units spanwise spaced. Carlotti [99] differentiates between the two structures based on spectral analysis; the superstructures produce a “-1” power slope and the low-speed streaks produce a “-2” power slope.
The newly discovered coherent structures (LSM and VLSMs) have been used to develop the old attached eddy model of Townsend [7]. Perry and co-authors [15, 18] devised a model to predict turbulence statistics by applying the attached eddy hypotheses to a forest of hairpin vortices of sizes proportional to their height from the wall. The model has been further polished by Marusic [100] who found the vortex packet to best resemble the attached eddies and prescribe turbulence statistics. Exactly the same was deduced by Dennis and Nickels [13]. Del Álamo et al. [101] inferred that the logarithmic region is populated with two classes of clusters; small detached vortex packets and tall attached packets. Hwang and Cossu [91, 92, 93] displayed that the energy-containing motions at a given spanwise length scale can self-sustain themselves by extracting energy directly from the mean flow even with the absence of any larger or smaller structures. They found the sizes of these energy-containing motions to be proportional to their distances from the wall, which makes them good candidates to be Townsend’s attached eddies. However, they anticipated each of these eddies to be composed of two elements, a long streaky structure and a vortical structure. In the sublayer, these are the low-speed streak and the quasi-streamwise vortices flanking it and in the logarithmic and wake layers, these are the superstructures and the vortex packets aligning along them.
11. Generation of mechanical coherent structures in the ABL
The outer layer flow has generally been neutralized in the discussion about coherent structure generation. It was assumed that the structures are pure products of surface-instability interactions. This bottom-up model is convincing at low Reτ where the inner layer resembles a considerable portion of the whole boundary layer depth. Nevertheless, as Reτ increases, the inner and outer scales separate. For instance, the atmospheric boundary layer (ABL) can extend in height up to 1000 m but its inner layer is no more than few centimeters. It follows that, the bottom-up mechanism presupposes that a vortex packet of 5-cm size is to enlarge persistently tens of meters within a high Reτ turbulent flow field until reaching the turbulent/non-turbulent interface.
Many authors [16, 17, 38, 40, 54, 73, 102, 103] recorded that the structures within the outer layer can trigger the bursting process, top-down models. Based on the synchronization between the bursting process and the passage of turbulent bulges in the turbulent/non-turbulent interface, Blackwelder and coworkers [28, 104, 105] conjectured that either the bursting phenomenon controls the outer flow field by developing the large-scale bulges, or else the outer field drives the bursts. Falco [106] observed the bulges at the turbulent/non-turbulent interface. He found the bulges to encompass typical eddies. These are ring or hairpin eddies found in almost all turbulent flows; wakes, jets, grid-generated turbulence; turbulent boundary layers, etc. In their proposed Overall Production Module, Falco, Klewicki, and Pan [107] hypothesized the bursting process to be triggered by a typical eddy moving toward the wall. The typical eddy when passing over a pair of low-speed streaks provokes the generation of two spanwise vortices within the streak pair, a primary vortex and a pocket vortex. The pocket in between opens up by self-induction and a sweep stream is created. Secondary hairpin vortices form across each streak. They are then twisted and rotated back toward the wall into the center of the pocket. This model largely coincides with the observations of Haidari and Smith [108].
Jiménez and Pinelli [62] utilized the capabilities of DNS to isolate the different turbulence sustenance mechanisms. They found that, at the studied Reτ, turbulence can feed solely on the inner-layer cycle without any perturbations from the outer layer. However, Jiménez and Pinelli believe that the outer-layer perturbations still can maintain turbulence, yet at a lower activity. Between the bottom-up and top-down supporters, a third group of researchers [55, 109, 110] reckons that both models do coexist all the time with the former prevailing at low Reτ and the latter at high Reτ. Hunt and Morrison [103] suggest an Reτ of 104 as a limiting value between the dominance regimes of both models.
Lin et al. [111] conducted an LES for neutral ABL. They employed a conditional sampling technique to track the evolution of the coherent structures. They concluded that hairpin vortices can be spawned by interaction between the ejection stream and either the mean flow or a sweep stream, a fact that has been confirmed later via DNS [14] and PIV [21]. The most interesting result among theirs is that they confirmed the top-down mechanism to generate vortices; a sweep stream when it impinges onto the ground, generates an ejection stream. However, they found these ejection-induced streams not to correlate with the strong ejection streams dominating the surface layer. Hunt and Morrison [103] and coworkers [99, 112, 113] developed the top-down model originally proposed by Falco [106] to comply with the ABL. Their conjecture is that the large eddies impinge and scrape along the surface, forming an internal boundary layer. As such, streamwise vortices of lengths several times the boundary layer height are generated alongside the impinging eddy. When the generated vortices interact with others, they are lifted far upward. The theory further splits the atmospheric surface layer into two sublayers: the shear layer and the eddy surface layer. The shear dominates the spectra in the first by distorting turbulence isotropy, while in the second the statistics are dominated by the ground-blocking effect on the impinging eddies (normal velocity suppression). They supported their theory by observations from atmospheric flow and spectrum analysis from the near surface region. The layer division was proven by spectral analysis of field measurements undertaken by [114]. Likewise, McNaughton and Brunet [115] postulated that the outer-layer eddies overtake the superstructures and induce hairpin vortices in a similar fashion to the near-wall cycle proposed by Kline et al. [37].
12. Conclusion
The turbulent flow stays as one of the most difficult scientific problems man has encountered. Despite the great deal of advance in the field, the path from the mean flow to the random fluctuations is still controversial. The modern experimental and numerical techniques are either one-eyed or biased toward the flow conditions synthesized by the researchers. This chapter reviewed the accumulated knowledge of TCSs and unfolded and compared their different mechanisms of generation. The scope was confined to turbulent boundary layer flow and atmospheric flow.
In boundary layer flows, turbulence is sustained by two concurrent mechanisms, the bottom-up mechanism and the top-down mechanism. The former dominates in low-Reynolds number (FPBL) flows and the latter dominates in high-Reynolds number (atmospheric) flows. The bottom-up mechanism generates turbulence coherent structures by surface-instability interaction, whereas the top-down mechanism relies on large outer-layer structures to trigger the generation process. Both the FPBL flow and the atmospheric flow share common features and are occupied by similar turbulence coherent structures, namely, the streamwise vortices, the low-speed streaks, the hairpin vortices, the vortex packets, and the superstructures. However, the large scale in atmospheric flow neutralizes the role of the low-speed streaks and streamwise vortices. Many conceptual and numerical models have been set forth to enhance our understanding of turbulent flows. The research is always aiming to achieve a model that can be implemented in numerical simulations or drag reduction applications. In the end, despite the vast knowledge of turbulent flow structure, turbulence continues to be an unsolved or not thoroughly understood phenomenon.
\n',keywords:"boundary layer, turbulence, coherent structures, generation, ejection, sweep",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/63059.pdf",chapterXML:"https://mts.intechopen.com/source/xml/63059.xml",downloadPdfUrl:"/chapter/pdf-download/63059",previewPdfUrl:"/chapter/pdf-preview/63059",totalDownloads:3734,totalViews:231,totalCrossrefCites:4,totalDimensionsCites:5,totalAltmetricsMentions:0,introChapter:null,impactScore:2,impactScorePercentile:79,impactScoreQuartile:4,hasAltmetrics:0,dateSubmitted:"January 30th 2018",dateReviewed:"March 28th 2018",datePrePublished:"November 5th 2018",datePublished:"April 17th 2019",dateFinished:"August 13th 2018",readingETA:"0",abstract:"Turbulence stands as one of the most complicated and attractive physical phenomena. The accumulated knowledge has shown turbulent flow to be composed of islands of vortices and uniform-momentum regions, which are coherent in both time and space. Research has been concentrated on these structures, their generation, evolution, and interaction with the mean flow. Different theories and conceptual models were proposed with the aim of controlling the boundary layer flow and improving numerical simulations. Here, we review the different classes of turbulence coherent structures and the presumable generation mechanisms for each. The conceptual models describing the generation of turbulence coherent structures are generally classified under two categories, namely, the bottom-up mechanisms and the top-down mechanisms. The first assumes turbulence to be generated near the surface by some sort of instabilities, whereas the second assigns an active role to the large outer layer structures, perhaps the turbulent bulges. Both categories of models coexist in the flow with the first dominating turbulence generation at low Reynolds number and the second at high Reynolds number, such as the case in the atmospheric boundary layer.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/63059",risUrl:"/chapter/ris/63059",book:{id:"7214",slug:"turbulence-and-related-phenomena"},signatures:"Zambri Harun and Eslam Reda Lotfy",authors:[{id:"243152",title:"Dr.",name:"Zambri",middleName:null,surname:"Harun",fullName:"Zambri Harun",slug:"zambri-harun",email:"zambri@ukm.edu.my",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/243152/images/system/243152.jpg",institution:null},{id:"252195",title:"Dr.",name:"Eslam",middleName:null,surname:"Reda",fullName:"Eslam Reda",slug:"eslam-reda",email:"eslamredalotfy1985@yahoo.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. The hairpin vortex",level:"1"},{id:"sec_3",title:"3. From eddies to turbulence",level:"1"},{id:"sec_4",title:"4. Generation of the hairpin vortex",level:"1"},{id:"sec_5",title:"5. The bursting process",level:"1"},{id:"sec_6",title:"6. Streak generation",level:"1"},{id:"sec_7",title:"7. Generation of streamwise vortices",level:"1"},{id:"sec_8",title:"8. Turbulence sustenance by instability",level:"1"},{id:"sec_9",title:"9. Large-scale motions (LSMs, vortex packets)",level:"1"},{id:"sec_10",title:"10. Very large scale motions (VLSMs, superstructures)",level:"1"},{id:"sec_11",title:"11. Generation of mechanical coherent structures in the ABL",level:"1"},{id:"sec_12",title:"12. Conclusion",level:"1"}],chapterReferences:[{id:"B1",body:'Theodorsen T. Mechanism of turbulence. In: Proceedings of the Second Midwestern Conference on Fluid Mechanics. Vol. 1719; 1952'},{id:"B2",body:'Head MR, Bandyopadhyay P. 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Annual Review of Fluid Mechanics. 1994;26:573-616'},{id:"B78",body:'Christensen KT, Adrian RJ. Statistical evidence of hairpin vortex packets in wall turbulence. Journal of Fluid Mechanics. 2001;431:433-443'},{id:"B79",body:'Lee JH, Sung HJ. Very-large-scale motions in a turbulent boundary layer. Journal of Fluid Mechanics. 2011;673:80-120'},{id:"B80",body:'Kim KC, Adrian RJ. Very large-scale motion in the outer layer. Physics of Fluids. 1999;11:417-422'},{id:"B81",body:'Kovasznay LSG, Kibens V, Blackwelder RF. Large-scale motion in the intermittent region of a turbulent boundary layer. Journal of Fluid Mechanics. 1970;41:283-325'},{id:"B82",body:'Ganapathisubramani B, Longmire EK, Marusic I. Characteristics of vortex packets in turbulent boundary layers. Journal of Fluid Mechanics. 2003;478:35-46'},{id:"B83",body:'Toh S, Itano T. Interaction between a large-scale structure and near-wall structures in channel flow. Journal of Fluid Mechanics. 2005;524:249-262'},{id:"B84",body:'Talluru KM, Baidya R, Hutchins N, Marusic I. Amplitude modulation of all three velocity components in turbulent boundary layers. Journal of Fluid Mechanics. 2014;746:R1'},{id:"B85",body:'Baars WJ, Talluru KM, Hutchins N, Marusic I. Wavelet analysis of wall turbulence to study large-scale modulation of small scales. Experiments in Fluids. 2015;56:188'},{id:"B86",body:'Hutchins N. Large-scale structures in high Reynolds number wall-bounded turbulence. Progress in Turbulence V. Berlin: Springer; 2014, p. 75-83'},{id:"B87",body:'Jiménez J. The largest scales of turbulent wall flows. CTR Annual Research Briefs. 1998;137:54'},{id:"B88",body:'Baltzer JR, Adrian RJ, Wu X. Structural organization of large and very large scales in turbulent pipe flow simulation. Journal of Fluid Mechanics. 2013;720:236-279'},{id:"B89",body:'Dennis DJC, Nickels TB. Experimental measurement of large-scale three-dimensional structures in a turbulent boundary layer. Part 2. Long structures. Journal of Fluid Mechanics. 2011;673:218-244'},{id:"B90",body:'Bailey SCC, Hultmark M, Smits AJ, Schultz MP. Azimuthal structure of turbulence in high Reynolds number pipe flow. Journal of Fluid Mechanics. 2008;615:121-138'},{id:"B91",body:'Hwang Y, Cossu C. Self-sustained process at large scales in turbulent channel flow. Physical Review Letters. 2010;105:44505'},{id:"B92",body:'Cossu C, Hwang Y. Self-sustaining processes at all scales in wall-bounded turbulent shear flows. Philosophical Transactions of the Royal Society A. 2017;375:20160088'},{id:"B93",body:'Hwang Y. Statistical structure of self-sustaining attached eddies in turbulent channel flow. Journal of Fluid Mechanics. 2015;767:254-289'},{id:"B94",body:'Guala M, Hommema SE, Adrian RJ. Large-scale and very-large-scale motions in turbulent pipe flow. Journal of Fluid Mechanics. 2006;554:521-542'},{id:"B95",body:'Jimenez J, Del Alamo JC, Flores O. The large-scale dynamics of near-wall turbulence. Journal of Fluid Mechanics. 2004;505:179-199'},{id:"B96",body:'Lee JH, Sung HJ. Comparison of very-large-scale motions of turbulent pipe and boundary layer simulations. Physics of Fluids. 2013;25:45103'},{id:"B97",body:'Monty JP, Stewart JA, Williams RC, Chong MS. Large-scale features in turbulent pipe and channel flows. Journal of Fluid Mechanics. 2007;589:147-156'},{id:"B98",body:'Hutchins N, Marusic I. Evidence of very long meandering features in the logarithmic region of turbulent boundary layers. Journal of Fluid Mechanics. 2007;579:1-28'},{id:"B99",body:'Carlotti P. Two-point properties of atmospheric turbulence very close to the ground: Comparison of a high resolution LES with theoretical models. Boundary-Layer Meteorology. 2002;104:381-410'},{id:"B100",body:'Marusic I. On the role of large-scale structures in wall turbulence. Physics of Fluids. 2001;13:735-743'},{id:"B101",body:'Del Álamo JC, Jimenez J, Zandonade P, Moser RD. Self-similar vortex clusters in the turbulent logarithmic region. Journal of Fluid Mechanics. 2006;561:329-358'},{id:"B102",body:'Rao KN, Narasimha R, Narayanan MAB. The “bursting”phenomenon in a turbulent boundary layer. Journal of Fluid Mechanics. 1971;48:339-352'},{id:"B103",body:'Hunt JCR, Morrison JF. Eddy structure in turbulent boundary layers. European Journal of Mechanics - B/Fluids. 2000;19:673-694'},{id:"B104",body:'Blackwelder RF, Kaplan RE. On the wall structure of the turbulent boundary layer. Journal of Fluid Mechanics. 1976;76:89-112'},{id:"B105",body:'Blackwelder R. An experimental model for near-wall structure. In: 29th AIAA, Fluid Dynamics Conference; 1997. p. 2960'},{id:"B106",body:'Falco RE. Coherent motions in the outer region of turbulent boundary layers. Physics of Fluids. 1977;20:S124-S132'},{id:"B107",body:'Falco RE, Klewicki JC, Pan K. Production of turbulence in boundary layers and potential for modification of the near wall region. Structure of Turbulence and Drag Reduction. Berlin: Springer; 1990, p. 59-68'},{id:"B108",body:'Haidari AH, Smith CR. The generation and regeneration of single hairpin vortices. Journal of Fluid Mechanics. 1994;277:135-162'},{id:"B109",body:'Hutchins N, Chauhan K, Marusic I, Monty J, Klewicki J. Towards reconciling the large-scale structure of turbulent boundary layers in the atmosphere and laboratory. Boundary-Layer Meteorology. 2012;145:273-306'},{id:"B110",body:'Mathis R, Hutchins N, Marusic I. Large-scale amplitude modulation of the small-scale structures in turbulent boundary layers. Journal of Fluid Mechanics. 2009;628:311-337'},{id:"B111",body:'Lin C-L, McWilliams JC, Moeng C-H, Sullivan PP. Coherent structures and dynamics in a neutrally stratified planetary boundary layer flow. Physics of Fluids. 1996;8:2626-2639'},{id:"B112",body:'Högström U, Hunt JCR, Smedman A-S. Theory and measurements for turbulence spectra and variances in the atmospheric neutral surface layer. Boundary-Layer Meteorology. 2002;103:101-124'},{id:"B113",body:'Hunt JCR, Carlotti P. Statistical structure at the wall of the high Reynolds number turbulent boundary layer. Flow, Turbulence and Combustion. 2001;66:453-475'},{id:"B114",body:'Drobinski P, Carlotti P, Newsom RK, Banta RM, Foster RC, Redelsperger J-L. The structure of the near-neutral atmospheric surface layer. Journal of the Atmospheric Sciences. 2004;61:699-714'},{id:"B115",body:'McNaughton KG, Brunet Y. Townsend’s hypothesis, coherent structures and Monin–Obukhov similarity. Boundary-Layer Meteorology. 2002;102:161-175'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Zambri Harun",address:"zambri@ukm.edu.my",affiliation:'
Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Malaysia
'},{corresp:null,contributorFullName:"Eslam Reda Lotfy",address:null,affiliation:'
Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Malaysia
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Research suggests that these monoculture practices have led to adverse impacts both on natural and human systems and smallholder farmers have been severely impacted by these unsustainable practices. This chapter aims to analyze how oil palm agroforestry (OPAF) has been adopted by smallholder farmers in the Jambi and Central Kalimantan provinces of Indonesia as part of the social forestry (SF) program to solve the tenure-related conflict in the designated forest areas which are disturbed by monoculture oil palm plantations managed by smallholder farmers. This chapter shows that although oil palm is widely adopted as monoculture plantations for the sake of high yielding, smallholder farmers tend to adopt OPAF to maintain the stability of household incomes amidst the uncertainty of oil palm price in the global market and secure their tenurial access to the designated forest lands. Their perception of OPAF is influenced by their knowledge and determines their decision in adopting OPAF. However, peer pressure and external supports also play important roles in accelerating the adoption of OPAF. 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IntechOpen’s Academic Editors and Authors have received funding for their work through many well-known funders, including: the European Commission, Bill and Melinda Gates Foundation, Wellcome Trust, Chinese Academy of Sciences, Natural Science Foundation of China (NSFC), CGIAR Consortium of International Agricultural Research Centers, National Institute of Health (NIH), National Science Foundation (NSF), National Aeronautics and Space Administration (NASA), National Institute of Standards and Technology (NIST), German Research Foundation (DFG), Research Councils United Kingdom (RCUK), Oswaldo Cruz Foundation, Austrian Science Fund (FWF), Foundation for Science and Technology (FCT), Australian Research Council (ARC).
Open Access publication costs can often be designated directly in the grants or in specific budgets allocated for that purpose. Many of the most important funding organisations encourage, and even request, that the projects they fund are made available at no cost to the wider public. IntechOpen strives to maintain excellent relationships with these funders and ensures compliance with mandates.
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In order to help Authors identify appropriate funding agencies and institutions, we have created a list, based on extensive research on various OA resources (including ROARMAP and SHERPA/JULIET) of organizations that have funds available. Before consulting our list we encourage you to petition your own institution or organization for Open Access funds or check the specifications of your grant with your funder to ascertain if publication costs are included. Where you are in receipt of a grant you should clarify:
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Does your institution already have a budget for covering Open Access publication costs?
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Does your grant list Open Access publication fees as legitimate direct/indirect costs?
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If you are associated with any of the institutions in our list below, you can apply to receive OA publication funds by following the instructions provided in the links. Please consult the Open Access policies or grant Terms and Conditions of any institution with which you are linked to explore ways to cover your publication costs (also accessible by clicking on the link in their title).
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Please note that this list is not a definitive one and is updated regularly. To suggest possible modifications or the inclusion of your institution/funder, please contact us at funders@intechopen.com
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Please be aware that you must be a member, or grantee, of the institutions/funders listed in order to apply for their Open Access publication funds.
Open Access publication costs can often be designated directly in the grants or in specific budgets allocated for that purpose. Many of the most important funding organisations encourage, and even request, that the projects they fund are made available at no cost to the wider public. IntechOpen strives to maintain excellent relationships with these funders and ensures compliance with mandates.
\n\n
In order to help Authors identify appropriate funding agencies and institutions, we have created a list, based on extensive research on various OA resources (including ROARMAP and SHERPA/JULIET) of organizations that have funds available. Before consulting our list we encourage you to petition your own institution or organization for Open Access funds or check the specifications of your grant with your funder to ascertain if publication costs are included. Where you are in receipt of a grant you should clarify:
\n\n
\n\t
Does your institution already have a budget for covering Open Access publication costs?
\n\t
Does your grant list Open Access publication fees as legitimate direct/indirect costs?
\n
\n\n
If you are associated with any of the institutions in our list below, you can apply to receive OA publication funds by following the instructions provided in the links. Please consult the Open Access policies or grant Terms and Conditions of any institution with which you are linked to explore ways to cover your publication costs (also accessible by clicking on the link in their title).
\n\n
Please note that this list is not a definitive one and is updated regularly. To suggest possible modifications or the inclusion of your institution/funder, please contact us at funders@intechopen.com
\n\n
Please be aware that you must be a member, or grantee, of the institutions/funders listed in order to apply for their Open Access publication funds.
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In all cases, cyclical ups and downs depend not only on internal system cyclical processes and their factors in countries but also on the consequences of intercountry interaction. The ability to measure and predict business cycles, taking into account their mutual influence, is a prerequisite for the development of an adequate business policy of countries and their associations.",book:{id:"6703",slug:"statistics-growing-data-sets-and-growing-demand-for-statistics",title:"Statistics",fullTitle:"Statistics - Growing Data Sets and Growing Demand for Statistics"},signatures:"Elena Zarova",authors:null},{id:"54366",title:"Solution of Differential Equations with Applications to Engineering Problems",slug:"solution-of-differential-equations-with-applications-to-engineering-problems",totalDownloads:6866,totalCrossrefCites:5,totalDimensionsCites:8,abstract:"Over the last hundred years, many techniques have been developed for the solution of ordinary differential equations and partial differential equations. While quite a major portion of the techniques is only useful for academic purposes, there are some which are important in the solution of real problems arising from science and engineering. In this chapter, only very limited techniques for solving ordinary differential and partial differential equations are discussed, as it is impossible to cover all the available techniques even in a book form. The readers are then suggested to pursue further studies on this issue if necessary. After that, the readers are introduced to two major numerical methods commonly used by the engineers for the solution of real engineering problems.",book:{id:"5513",slug:"dynamical-systems-analytical-and-computational-techniques",title:"Dynamical Systems",fullTitle:"Dynamical Systems - Analytical and Computational Techniques"},signatures:"Cheng Yung Ming",authors:[{id:"191017",title:"Dr.",name:"Cheng",middleName:null,surname:"Y.M.",slug:"cheng-y.m.",fullName:"Cheng Y.M."}]},{id:"56538",title:"Stochastic Resonance and Related Topics",slug:"stochastic-resonance-and-related-topics",totalDownloads:1718,totalCrossrefCites:1,totalDimensionsCites:1,abstract:"The stochastic resonance (SR) is the phenomenon which can emerge in nonlinear dynamic systems. In general, it is related with a bistable nonlinear system of Duffing type under additive excitation combining deterministic periodic force and Gaussian white noise. It manifests as a stable quasiperiodic interwell hopping between both stable states with a small random perturbation. Classical definition and basic features of SR are regarded. The most important methods of investigation outlined are: analytical, semi-analytical, and numerical procedures of governing physical systems or relevant Fokker-Planck equation. Stochastic simulation is mentioned and experimental way of results verification is recommended. Some areas in Engineering Dynamics related with SR are presented together with a particular demonstration observed in the aeroelastic stability. Interaction of stationary and quasiperiodic parts of the response is discussed. Some nonconventional definitions are outlined concerning alternative operators and driving processes are highlighted. The chapter shows a large potential of specific basic, applied and industrial research in SR. This strategy enables to formulate new ideas for both development of nonconventional measures for vibration damping and employment of SR in branches, where it represents an operating mode of the system itself. 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He was elected a Yangtze River Scholars Distinguished Professor in 2013, a member of the International Statistical Institute (ISI) in 2016, a member of the board of the International Chinese Statistical Association (ICSA) in 2018, and a fellow of the Institute of Mathematical Statistics (IMS) in 2021. He received the ICSA Outstanding Service Award in 2018 and the National Science Foundation for Distinguished Young Scholars of China in 2012. He serves as a member of the editorial board of Statistics and Its Interface and Journal of Systems Science and Complexity. He is also a field editor for Communications in Mathematics and Statistics. His research interests include biostatistics, empirical likelihood, missing data analysis, variable selection, high-dimensional data analysis, Bayesian statistics, and data science. He has published more than 190 research papers and authored five books.",institutionString:"Yunnan University",institution:{name:"Yunnan University",country:{name:"China"}}},{id:"1177",title:"Prof.",name:"António",middleName:"J. R.",surname:"José Ribeiro Neves",slug:"antonio-jose-ribeiro-neves",fullName:"António José Ribeiro Neves",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/1177/images/system/1177.jpg",biography:"Prof. António J. R. Neves received a Ph.D. in Electrical Engineering from the University of Aveiro, Portugal, in 2007. Since 2002, he has been a researcher at the Institute of Electronics and Informatics Engineering of Aveiro. Since 2007, he has been an assistant professor in the Department of Electronics, Telecommunications, and Informatics, University of Aveiro. He is the director of the undergraduate course on Electrical and Computers Engineering and the vice-director of the master’s degree in Electronics and Telecommunications Engineering. He is an IEEE Senior Member and a member of several other research organizations worldwide. His main research interests are computer vision, intelligent systems, robotics, and image and video processing. He has participated in or coordinated several research projects and received more than thirty-five awards. He has 161 publications to his credit, including books, book chapters, journal articles, and conference papers. He has vast experience as a reviewer of several journals and conferences. 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His areas of scientific interest are signal and image processing, filtering, steganography, segmentation, pattern recognition, biomedical signal processing, sensors, and real-time applications.",institutionString:"Instituto Politécnico Nacional",institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"428449",title:"Dr.",name:"Ronaldo",middleName:null,surname:"Ferreira",slug:"ronaldo-ferreira",fullName:"Ronaldo Ferreira",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/428449/images/21449_n.png",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"165328",title:"Dr.",name:"Vahid",middleName:null,surname:"Asadpour",slug:"vahid-asadpour",fullName:"Vahid Asadpour",position:null,profilePictureURL:"https://mts.intechopen.com/storage/users/165328/images/system/165328.jpg",biography:"Vahid Asadpour, MS, Ph.D., is currently with the Department of Research and Evaluation, Kaiser Permanente Southern California. 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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:{name:"Association for Computing Machinery",country:{name:"United States of America"}}},{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:"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:'"Politechnica" University Timişoara',institution:null},{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:{name:"Tecnalia",country:{name:"Spain"}}},{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:"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:null,institution:null},{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. She is a member of Indian Mathematical Society.",institutionString:null,institution:null},{id:"417317",title:"Mrs.",name:"Chiedza",middleName:null,surname:"Elvina Mashiri",slug:"chiedza-elvina-mashiri",fullName:"Chiedza Elvina Mashiri",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"352140",title:"Dr.",name:"Edina",middleName:null,surname:"Chandiwana",slug:"edina-chandiwana",fullName:"Edina Chandiwana",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"342259",title:"B.Sc.",name:"Leonard",middleName:null,surname:"Mushunje",slug:"leonard-mushunje",fullName:"Leonard Mushunje",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"347042",title:"Mr.",name:"Maxwell",middleName:null,surname:"Mashasha",slug:"maxwell-mashasha",fullName:"Maxwell Mashasha",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Midlands State University",country:{name:"Zimbabwe"}}},{id:"2941",title:"Dr.",name:"Alberto J.",middleName:"Jorge",surname:"Rosales-Silva",slug:"alberto-j.-rosales-silva",fullName:"Alberto J. Rosales-Silva",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"437913",title:"Dr.",name:"Guillermo",middleName:null,surname:"Urriolagoitia-Sosa",slug:"guillermo-urriolagoitia-sosa",fullName:"Guillermo Urriolagoitia-Sosa",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"435126",title:"Prof.",name:"Joaquim",middleName:null,surname:"José de Castro Ferreira",slug:"joaquim-jose-de-castro-ferreira",fullName:"Joaquim José de Castro Ferreira",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"University of Aveiro",country:{name:"Portugal"}}},{id:"437899",title:"MSc.",name:"Miguel Angel",middleName:null,surname:"Ángel Castillo-Martínez",slug:"miguel-angel-angel-castillo-martinez",fullName:"Miguel Angel Ángel Castillo-Martínez",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Instituto Politécnico Nacional",country:{name:"Mexico"}}},{id:"289955",title:"Dr.",name:"Raja",middleName:null,surname:"Kishor Duggirala",slug:"raja-kishor-duggirala",fullName:"Raja Kishor Duggirala",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",biography:null,institutionString:null,institution:{name:"Jawaharlal Nehru Technological University, Hyderabad",country:{name:"India"}}}]}},subseries:{item:{id:"3",type:"subseries",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
",coverUrl:"https://cdn.intechopen.com/series_topics/covers/3.jpg",hasOnlineFirst:!0,hasPublishedBooks:!0,annualVolume:11399,editor:{id:"205604",title:"Dr.",name:"Tomas",middleName:null,surname:"Jarzembowski",slug:"tomas-jarzembowski",fullName:"Tomas Jarzembowski",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRKriQAG/Profile_Picture_2022-06-16T11:01:31.jpg",biography:"Tomasz Jarzembowski was born in 1968 in Gdansk, Poland. He obtained his Ph.D. degree in 2000 from the Medical University of Gdańsk (UG). After specialization in clinical microbiology in 2003, he started studying biofilm formation and antibiotic resistance at the single-cell level. In 2015, he obtained his D.Sc. degree. His later study in cooperation with experts in nephrology and immunology resulted in the designation of the new diagnostic method of UTI, patented in 2017. He is currently working at the Department of Microbiology, Medical University of Gdańsk (GUMed), Poland. Since many years, he is a member of steering committee of Gdańsk branch of Polish Society of Microbiologists, a member of ESCMID. He is also a reviewer and a member of editorial boards of a number of international journals.",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorTwo:{id:"484980",title:"Dr.",name:"Katarzyna",middleName:null,surname:"Garbacz",slug:"katarzyna-garbacz",fullName:"Katarzyna Garbacz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003St8TAQAZ/Profile_Picture_2022-07-07T09:45:16.jpg",biography:"Katarzyna Maria Garbacz, MD, is an Associate Professor at the Medical University of Gdańsk, Poland and she is head of the Department of Oral Microbiology of the Medical University of Gdańsk. She has published more than 50 scientific publications in peer-reviewed journals. She has been a project leader funded by the National Science Centre of Poland. Prof. Garbacz is a microbiologist working on applied and fundamental questions in microbial epidemiology and pathogenesis. Her research interest is in antibiotic resistance, host-pathogen interaction, and therapeutics development for staphylococcal pathogens, mainly Staphylococcus aureus, which causes hospital-acquired infections. Currently, her research is mostly focused on the study of oral pathogens, particularly Staphylococcus spp.",institutionString:"Medical University of Gdańsk, Poland",institution:null},editorThree:null,series:{id:"6",title:"Infectious Diseases",doi:"10.5772/intechopen.71852",issn:"2631-6188"},editorialBoard:[{id:"190041",title:"Dr.",name:"Jose",middleName:null,surname:"Gutierrez Fernandez",slug:"jose-gutierrez-fernandez",fullName:"Jose Gutierrez Fernandez",profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institutionString:null,institution:{name:"University of Granada",institutionURL:null,country:{name:"Spain"}}},{id:"156556",title:"Prof.",name:"Maria Teresa",middleName:null,surname:"Mascellino",slug:"maria-teresa-mascellino",fullName:"Maria Teresa Mascellino",profilePictureURL:"https://mts.intechopen.com/storage/users/156556/images/system/156556.jpg",institutionString:"Sapienza University",institution:{name:"Sapienza University of 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to collaborate with more research groups interested in animal nutrition, leading to the development of new feeding strategies and food valuation while being more sustainable with the environment, allowing more readers to learn about the subject.",author:{id:"175967",name:"Manuel",surname:"Gonzalez Ronquillo",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/175967/images/system/175967.png",slug:"manuel-gonzalez-ronquillo",institution:{id:"6221",name:"Universidad Autónoma del Estado de México",country:{id:null,name:"Mexico"}}}},{id:"18",text:"It was great publishing with IntechOpen, the process was straightforward and I had support all along.",author:{id:"71579",name:"Berend",surname:"Olivier",institutionString:"Utrecht University",profilePictureURL:"https://mts.intechopen.com/storage/users/71579/images/system/71579.png",slug:"berend-olivier",institution:{id:"253",name:"Utrecht 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\r\n\tThe integration of tissues and organs throughout the mammalian body, as well as the expression, structure, and function of molecular and cellular components, is essential for modern physiology. The following concerns will be addressed in this Cell Physiology subject, which will consider all organ systems (e.g., brain, heart, lung, liver; gut, kidney, eye) and their interactions: (1) Neurodevelopment and Neurodevelopmental Disease (2) Free Radicals (3) Tumor Metastasis (4) Antioxidants (5) Essential Fatty Acids (6) Melatonin and (7) Lipid Peroxidation Products and Aging Physiology.
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Ongoing issues, recent advances, and future diagnostic approaches and therapeutic strategies will also be discussed. This book series will focus on various aspects and properties of infectious diseases whose deep understanding is essential for safeguarding the human race from losing resources and economies due to pathogens.",coverUrl:"https://cdn.intechopen.com/series/covers/6.jpg",latestPublicationDate:"August 16th, 2022",hasOnlineFirst:!0,numberOfOpenTopics:4,numberOfPublishedChapters:124,numberOfPublishedBooks:13,editor:{id:"131400",title:"Prof.",name:"Alfonso J.",middleName:null,surname:"Rodriguez-Morales",fullName:"Alfonso J. Rodriguez-Morales",profilePictureURL:"https://mts.intechopen.com/storage/users/131400/images/system/131400.png",biography:"Dr. Rodriguez-Morales is an expert in tropical and emerging diseases, particularly zoonotic and vector-borne diseases (especially arboviral diseases). He is the president of the Travel Medicine Committee of the Pan-American Infectious Diseases Association (API), as well as the president of the Colombian Association of Infectious Diseases (ACIN). He is a member of the Committee on Tropical Medicine, Zoonoses, and Travel Medicine of ACIN. He is a vice-president of the Latin American Society for Travel Medicine (SLAMVI) and a Member of the Council of the International Society for Infectious Diseases (ISID). Since 2014, he has been recognized as a Senior Researcher, at the Ministry of Science of Colombia. He is a professor at the Faculty of Medicine of the Fundacion Universitaria Autonoma de las Americas, in Pereira, Risaralda, Colombia. He is an External Professor, Master in Research on Tropical Medicine and International Health, Universitat de Barcelona, Spain. He is also a professor at the Master in Clinical Epidemiology and Biostatistics, Universidad Científica del Sur, Lima, Peru. In 2021 he has been awarded the “Raul Isturiz Award” Medal of the API. Also, in 2021, he was awarded with the “Jose Felix Patiño” Asclepius Staff Medal of the Colombian Medical College, due to his scientific contributions to COVID-19 during the pandemic. He is currently the Editor in Chief of the journal Travel Medicine and Infectious Diseases. His Scopus H index is 47 (Google Scholar H index, 68).",institutionString:"Institución Universitaria Visión de las Américas, Colombia",institution:null},subseries:[{id:"3",title:"Bacterial Infectious Diseases",keywords:"Antibiotics, Biofilm, Antibiotic Resistance, Host-microbiota Relationship, Treatment, Diagnostic Tools",scope:"
\r\n\tThe era of antibiotics led us to the illusion that the problem of bacterial infection is over. However, bacterial flexibility and adaptation mechanisms allow them to survive and grow in extreme conditions. The best example is the formation of a sophisticated society of bacteria defined as a biofilm. Understanding the mechanism of bacterial biofilm formation has changed our perception of the development of bacterial infection but successfully eradicating biofilm remains a challenge. Considering the above, it is not surprising that bacteria remain a major public health threat despite the development of many groups of antibiotics. Additionally, increasing prevalence of acquired antibiotic resistance forces us to realize that we are far from controlling the development of bacterial infections. On the other hand, many infections are endogenous and result from an unbalanced relationship between the host and the microorganism. The increasing use of immunosuppressants, such as chemotherapy or organ transplantation, increases the incidence of patients highly susceptible to bacterial infections in the population.
\r\n
\r\n\tThis topic will focus on the current challenges and advantages in the diagnosis and treatment of bacterial infections. We will discuss the host-microbiota relationship, the treatment of chronic infections due to biofilm formation, and the development of new diagnostic tools to rapidly distinguish between colonization and probable infection.
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Fungal infectious illness prevalence and prognosis are determined by the exposure between fungi and host, host immunological state, fungal virulence, and early and accurate diagnosis and treatment. \r\nPatients with both congenital and acquired immunodeficiency are more likely to be infected with opportunistic mycosis. Fungal infectious disease outbreaks are common during the post- disaster rebuilding era, which is characterised by high population density, migration, and poor health and medical conditions.\r\nSystemic or local fungal infection is mainly associated with the fungi directly inhaled or inoculated in the environment during the disaster. The most common fungal infection pathways are human to human (anthropophilic), animal to human (zoophilic), and environment to human (soilophile). Diseases are common as a result of widespread exposure to pathogenic fungus dispersed into the environment. \r\nFungi that are both common and emerging are intertwined. In Southeast Asia, for example, Talaromyces marneffei is an important pathogenic thermally dimorphic fungus that causes systemic mycosis. Widespread fungal infections with complicated and variable clinical manifestations, such as Candida auris infection resistant to several antifungal medicines, Covid-19 associated with Trichoderma, and terbinafine resistant dermatophytosis in India, are among the most serious disorders. \r\nInappropriate local or systemic use of glucocorticoids, as well as their immunosuppressive effects, may lead to changes in fungal infection spectrum and clinical characteristics. Hematogenous candidiasis is a worrisome issue that affects people all over the world, particularly ICU patients. CARD9 deficiency and fungal infection have been major issues in recent years. Invasive aspergillosis is associated with a significant death rate. Special attention should be given to endemic fungal infections, identification of important clinical fungal infections advanced in yeasts, filamentous fungal infections, skin mycobiome and fungal genomes, and immunity to fungal infections.\r\nIn addition, endemic fungal diseases or uncommon fungal infections caused by Mucor irregularis, dermatophytosis, Malassezia, cryptococcosis, chromoblastomycosis, coccidiosis, blastomycosis, histoplasmosis, sporotrichosis, and other fungi, should be monitored. \r\nThis topic includes the research progress on the etiology and pathogenesis of fungal infections, new methods of isolation and identification, rapid detection, drug sensitivity testing, new antifungal drugs, schemes and case series reports. It will provide significant opportunities and support for scientists, clinical doctors, mycologists, antifungal drug researchers, public health practitioners, and epidemiologists from all over the world to share new research, ideas and solutions to promote the development and progress of medical mycology.",annualVolume:11400,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/4.jpg",editor:{id:"174134",title:"Dr.",name:"Yuping",middleName:null,surname:"Ran",fullName:"Yuping Ran",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bS9d6QAC/Profile_Picture_1630330675373",institutionString:null,institution:{name:"Sichuan University",institutionURL:null,country:{name:"China"}}},editorTwo:null,editorThree:null,editorialBoard:[{id:"302145",title:"Dr.",name:"Felix",middleName:null,surname:"Bongomin",fullName:"Felix Bongomin",profilePictureURL:"https://mts.intechopen.com/storage/users/302145/images/system/302145.jpg",institutionString:null,institution:{name:"Gulu University",institutionURL:null,country:{name:"Uganda"}}},{id:"45803",title:"Ph.D.",name:"Payam",middleName:null,surname:"Behzadi",fullName:"Payam Behzadi",profilePictureURL:"https://mts.intechopen.com/storage/users/45803/images/system/45803.jpg",institutionString:"Islamic Azad University, Tehran",institution:{name:"Islamic Azad University, Tehran",institutionURL:null,country:{name:"Iran"}}}]},{id:"5",title:"Parasitic Infectious Diseases",keywords:"Blood Borne Parasites, Intestinal Parasites, Protozoa, Helminths, Arthropods, Water Born Parasites, Epidemiology, Molecular Biology, Systematics, Genomics, Proteomics, Ecology",scope:"Parasitic diseases have evolved alongside their human hosts. In many cases, these diseases have adapted so well that they have developed efficient resilience methods in the human host and can live in the host for years. Others, particularly some blood parasites, can cause very acute diseases and are responsible for millions of deaths yearly. Many parasitic diseases are classified as neglected tropical diseases because they have received minimal funding over recent years and, in many cases, are under-reported despite the critical role they play in morbidity and mortality among human and animal hosts. The current topic, Parasitic Infectious Diseases, in the Infectious Diseases Series aims to publish studies on the systematics, epidemiology, molecular biology, genomics, pathogenesis, genetics, and clinical significance of parasitic diseases from blood borne to intestinal parasites as well as zoonotic parasites. We hope to cover all aspects of parasitic diseases to provide current and relevant research data on these very important diseases. In the current atmosphere of the Coronavirus pandemic, communities around the world, particularly those in different underdeveloped areas, are faced with the growing challenges of the high burden of parasitic diseases. At the same time, they are faced with the Covid-19 pandemic leading to what some authors have called potential syndemics that might worsen the outcome of such infections. 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The emergence of any viral disease is hard to anticipate, which often contributes to death. A viral disease can be defined as an infectious disease that has recently appeared within a population or exists in nature with the rapid expansion of incident or geographic range. This series will focus on various crucial factors related to emerging viral infectious diseases, including epidemiology, pathogenesis, host immune response, clinical manifestations, diagnosis, treatment, and clinical recommendations for managing viral infectious diseases, highlighting the recent issues with future directions for effective therapeutic strategies.",annualVolume:11402,isOpenForSubmission:!0,coverUrl:"https://cdn.intechopen.com/series_topics/covers/6.jpg",editor:{id:"158026",title:"Prof.",name:"Shailendra K.",middleName:null,surname:"Saxena",fullName:"Shailendra K. 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