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Modeling Approaches and Computational Methods for Particle-laden Turbulent Flows [Pehme köide]

Edited by (Professor, Department of Mechanical Engineering, Iowa State University, Ames, Iowa, United States of America; Founding Director, Center for Multiphase Flow Research and Education, Ames, Iowa, USA), Edited by (William F. Powers Professor and Disti)
  • Formaat: Paperback / softback, 586 pages, kõrgus x laius: 229x152 mm, kaal: 910 g, 100 illustrations (25 in full color); Illustrations
  • Sari: Computation and Analysis of Turbulent Flows
  • Ilmumisaeg: 25-Oct-2022
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0323901336
  • ISBN-13: 9780323901338
Teised raamatud teemal:
  • Formaat: Paperback / softback, 586 pages, kõrgus x laius: 229x152 mm, kaal: 910 g, 100 illustrations (25 in full color); Illustrations
  • Sari: Computation and Analysis of Turbulent Flows
  • Ilmumisaeg: 25-Oct-2022
  • Kirjastus: Academic Press Inc
  • ISBN-10: 0323901336
  • ISBN-13: 9780323901338
Teised raamatud teemal:

Modelling Approaches and Computational Methods for Particle-laden Turbulent Flows introduces the principal phenomena observed in applications where turbulence in particle-laden flow is encountered while also analyzing the main methods for analyzing numerically. The book takes a practical approach, providing advice on how to select and apply the correct model or tool by drawing on the latest research. Sections provide scales of particle-laden turbulence and the principal analytical frameworks and computational approaches used to simulate particles in turbulent flow. Each chapter opens with a section on fundamental concepts and theory before describing the applications of the modelling approach or numerical method.

Featuring explanations of key concepts, definitions, and fundamental physics and equations, as well as recent research advances and detailed simulation methods, this book is the ideal starting point for students new to this subject, as well as an essential reference for experienced researchers.

  • Provides a comprehensive introduction to the phenomena of particle laden turbulent flow
  • Explains a wide range of numerical methods, including Eulerian-Eulerian, Eulerian-Lagrange, and volume-filtered computation
  • Describes a wide range of innovative applications of these models
Contributors xi
About the editors xv
Preface xvii
References xvii
Acknowledgment xix
1 Introduction
1(42)
Shankar Subramaniam
S. Balachandar
1.1 Physical description
1(4)
1.2 Scope
5(2)
1.3 Deterministic descriptions
7(5)
1.4 Statistical descriptions
12(8)
1.5 Important non-dimensional quantities
20(5)
1.6 Multiscale nature of turbulent particle-laden flows
25(6)
1.7 Outline of the book
31(12)
Nomenclature
36(2)
References
38(5)
2 Particle dispersion and preferential concentration in particle-laden turbulence
43(38)
Andrew J. Banko
John K. Eaton
2.1 Introduction
43(1)
2.2 Particle dispersion
44(7)
2.3 Preferential concentration of particles by turbulence
51(21)
2.4 Turbophoresis
72(9)
References
75(6)
3 Physics of two-way coupling in particle-laden homogeneous isotropic turbulence
81(30)
Antonino Ferrante
Said Elghobashi
3.1 Introduction
81(3)
3.2 Particle-laden flows with dp > n
84(9)
3.3 Particle-laden flows with dp < n
93(18)
Appendix 3.A Governing equations
103(3)
Appendix 3.B Equations of conservation of linear and angular momenta for a solid particle moving in an incompressible fluid
106(2)
References
108(3)
4 Coagulation in turbulent particle-laden flows
111(36)
Lian-Ping Wang
4.1 Introduction
111(3)
4.2 Geometric collision kernel
114(14)
4.3 Collision efficiency
128(3)
4.4 Modeling the evolution of particle size distribution
131(4)
4.5 A specific application: turbulent collision coalescence of cloud droplets and its impact on warm rain precipitation
135(3)
4.6 Summary and outlook
138(9)
Acknowledgments
140(1)
References
140(7)
5 Efficient methods for particle-resolved direct numerical simulation
147(38)
Markus Uhlmann
Jos Derksen
Anthony Wachs
Lian-Ping Wang
Manuel Moriche
5.1 Introduction
147(2)
5.2 The immersed boundary method in Navier-Stokes-based solvers
149(8)
5.3 Distributed Lagrange multiplier methods
157(3)
5.4 Boltzmann equation-based mesoscopic methods
160(14)
5.5 Reference datasets
174(2)
5.6 Comparing PR-DNS methods: a difficult exercise
176(1)
5.7 Conclusion and outlook
177(8)
Acknowledgment
178(1)
References
178(7)
6 Results from particle-resolved simulations
185(32)
Agathe Chouippe
Aman G. Kidanemariam
Jos Derksen
Anthony Wachs
Markus Uhlmann
6.1 Introduction
185(1)
6.2 PR-DNS of dense fluidized systems for drag force parameterizations based on dynamic simulations
186(6)
6.3 PR-DNS of unbounded flows in the dilute regime
192(7)
6.4 PR-DNS of wall-bounded shear flows
199(9)
6.5 Conclusions and outlook
208(9)
References
209(8)
7 Modeling of short-range interactions between both spherical and non-spherical rigid particles
217(48)
Anthony Wachs
Markus Uhlmann
Jos Derksen
Damien P. Huet
7.1 Introduction
218(2)
7.2 Motion of a non-spherical rigid body
220(3)
7.3 Geometric description of a non-spherical rigid body and the problem of collision detection of non-spherical rigid bodies
223(6)
7.4 Non-collisional short-range hydrodynamic interactions: lubrication in dilute regime
229(2)
7.5 Methods for Lagrangian tracking of non-spherical rigid bodies with collisions
231(15)
7.6 Efficient and parallel implementation of granular dynamics solvers and their parallel coupling to the fluid solver
246(4)
7.7 Test cases
250(4)
7.8 Outlook
254(11)
References
255(10)
8 Improved force models for Euler-Lagrange computations
265(34)
Jeremy A.K. Horwitz
8.1 Introduction
265(3)
8.2 Undisturbed quantities
268(3)
8.3 Stochastic effects in Euler-Lagrange simulation for unresolved fields
271(2)
8.4 Fluid equations for dilute flows modeled with the Euler-Lagrange method
273(1)
8.5 Particle equation of motion
273(9)
8.6 Eulerian-Lagrangian data transfer
282(2)
8.7 Correction schemes for the undisturbed quantities
284(8)
8.8 Summary and future directions
292(1)
8.9 Discussion questions
292(7)
Acknowledgments
293(1)
References
293(6)
9 Deterministic extended point-particle models
299(32)
S. Balachandar
Martin R. Maxey
9.1 Motivation to go beyond the point-particle model
299(2)
9.2 Neighbor influence
301(2)
9.3 Undisturbed flow prediction
303(4)
9.4 Deterministic particle force prediction using the PIEP model
307(5)
9.5 Beyond pairwise approximation using machine learning
312(3)
9.6 Concept and statement of the force coupling method
315(3)
9.7 FCM results for individual particles
318(6)
9.8 Examples of FCM applications
324(1)
9.9 Comments
325(6)
References
327(4)
10 Stochastic models
331(52)
Aaron M. Lattanzi
Shankar Subramaniam
10.1 Motivation for stochastic models
332(2)
10.2 Dispersion of inertial particles from a point source
334(7)
10.3 Lagrangian particle description
341(13)
10.4 Challenges in modeling turbulent particle-laden flow
354(1)
10.5 Models for inertial particles in turbulence
355(13)
10.6 Numerical considerations
368(4)
10.7 Summary and extensions
372(11)
Appendix 10.A Details of numerical integration of SDEs
373(2)
Appendix 10.B Fast and slow variables
375(2)
References
377(6)
11 Volume-filtered Euler-Lagrange method for strongly coupled fluid-particle flows
383(36)
Jesse Capecelatro
Olivier Desjardins
11.1 Strongly coupled fluid-particle flows
383(2)
11.2 Microscale description
385(2)
11.3 Volume-filtering
387(7)
11.4 Closure modeling
394(3)
11.5 Numerical implementation
397(6)
11.6 Application to the study of strongly coupled particle-laden flows
403(5)
11.7 Extensions
408(5)
11.8 Concluding remarks
413(6)
References
414(5)
12 Quadrature-based moment methods for particle-laden flows
419(30)
Alberto Passalacqua
Rodney O. Fox
12.1 Introduction
419(3)
12.2 The kinetic equation and its generalization
422(5)
12.3 Generalities on moment methods
427(4)
12.4 Quadrature-based moment closures
431(6)
12.5 Anisotropic Gaussian closure for monodisperse flows
437(5)
12.6 Anisotropic Gaussian closure for polydisperse flows
442(2)
12.7 Closure
444(5)
References
444(5)
13 Eulerian-Eulerian modeling approach for turbulent particle-laden flows
449(34)
Berend van Wachem
13.1 Introduction
449(3)
13.2 Derivation of the Eulerian-Eulerian model for fluid-solid flows
452(5)
13.3 Probability density function
457(10)
13.4 Closure relations
467(12)
13.5 Outlook and conclusions
479(4)
References
480(3)
14 Multiscale modeling of gas-fluidized beds
483(54)
Yali Tang
Jam (Hans) Kuipers
14.1 Introduction
483(9)
14.2 Multiscale modeling
492(27)
14.3 Outlook
519(18)
Acknowledgment
522(1)
References
522(15)
15 Future directions
537(12)
Shankar Subramaniam
S. Balachandar
15.1 Future directions
537(1)
15.2 Mapping the high-dimensional parameter space
538(2)
15.3 Discovery and quantification of flow physics
540(1)
15.4 Theoretical challenges
541(1)
15.5 Modeling needs
542(4)
15.6 Need for collaborative efforts
546(3)
References
546(3)
Index 549
Shankar Subramaniam is a Professor in the Department of Mechanical Engineering at Iowa State University and Founding Director of the Center for Multiphase Flow Research and Education. He received his B. Tech. in aeronautical engineering from the Indian Institute of Technology, Bombay (Mumbai) in 1988 and is a recipient of the Presidents Silver Medal. He earned his PhD at Cornell University, after an MS in Aerospace Engineering at the University of Notre Dame, USA. Prior to joining the ISU faculty in 2002, Subramaniam was an assistant professor at Rutgers University. He is a recipient of the US Department of Energys Early Career Principal Investigator award. His areas of expertise are theory, modelling and simulation of multiphase flows including sprays, particle-laden flows, colloids and granular mixtures, turbulence, mixing, and reacting flows. S. Balachandar is currently the William F. Powers Professor and University Distinguished Professor in the Department of Mechanical and Aerospace Engineering at the University of Florida. From 2005 to 2011, he was the Chairman of the department. He is the inaugural Director of the Herbert Wertheim College of Engineering Institute for Computational Engineering (ICE). Professor Balachandars expertise is in computational multiphase flow, direct and large eddy simulations of transitional, turbulent flows, and integrated multiphysics simulations of complex problems. He is a fellow of the American Physical Society and the American Society of Mechanical Engineers. Professor Balachandar received the Francois Frenkiel Award from the American Physical Society Division of Fluid Dynamics in 1996 and the Arnold O. Beckman Award and the University Scholar Award from the University of Illinois.