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The Finite Element Method for Fluid Dynamics
- 8th Edition - December 2, 2024
- Authors: R. L. Taylor, P. Nithiarasu
- Language: English
- Hardback ISBN:9 7 8 - 0 - 3 2 3 - 9 5 8 8 6 - 8
- eBook ISBN:9 7 8 - 0 - 3 2 3 - 9 5 8 8 7 - 5
The Finite Element Method for Fluid Dynamics provides a comprehensive introduction to the application of the finite element method in fluid dynamics. The book begins with a useful… Read more
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Request a sales quoteThe Finite Element Method for Fluid Dynamics provides a comprehensive introduction to the application of the finite element method in fluid dynamics. The book begins with a useful summary of all relevant partial differential equations, progressing to the discussion of convection stabilization procedures, steady and transient state equations, and numerical solution of fluid dynamic equations.
In this expanded eighth edition, the book starts by explaining the character-based split (CBS) scheme, followed by an exploration of various other methods, including SUPG/PSPG, space-time, and VMS methods. Emphasising the fundamental knowledge, mathematical, and analytical tools necessary for successful implementation of computational fluid dynamics (CFD), The Finite Element Method for Fluid Dynamics stands as the authoritative introduction of choice for graduate level students, researchers, and professional engineers.
- A proven keystone reference in the library for engineers seeking to grasp and implement the finite element method in fluid dynamics
- Founded by a prominent pioneer in the field, this eighth edition has been updated by distinguished academics who worked closely with Olgierd C. Zienkiewicz
- Includes new chapters on data-driven computational fluid dynamics and independent adaptive mesh and buoyancy driven flow chapters.
Mechanical, Aerospace, Automotive, Marine, Biomedical, Environmental and Civil Engineers, applied mathematicians and computer aided engineering software developers
1. The equations of fluid dynamics
2. The finite element approximation
3. Convection dominated problems – finite element approximations to the convection–diffusion–reaction equation
4. Fractional step methods: the characteristic-based split (CBS) algorithm for compressible and incompressible flows
5. Incompressible Newtonian laminar flows
6. Incompressible non-Newtonian flows
7. Free surface flows
8. Buoyancy driven flows
9. Compressible high-speed gas flow
10. Adaptive mesh refinement
11. Turbulent flows
12. Flow and heat transport in porous media
13. Shallow-water problems
14. Long and medium waves
15. Short waves
16. Fluid–structure interaction
17. Biofluid dynamics – blood flow
18. Data-driven methods
19. Computer implementation of the CBS algorithm
Appendix A: Self-adjoint differential equations
Appendix B: Non-conservative form of Navier–Stokes equations
Appendix C: Computing drag force and stream function
Appendix D: Convection–diffusion equations: vector-valued variables
Appendix E: Integration formulae
Appendix F: Edge-based finite element formulation
Appendix G: Boundary layer–inviscid flow coupling
Appendix H: Multigrid method
Appendix I: Mass-weighted averaged turbulence transport equations
Appendix J: Introduction to neural networks
2. The finite element approximation
3. Convection dominated problems – finite element approximations to the convection–diffusion–reaction equation
4. Fractional step methods: the characteristic-based split (CBS) algorithm for compressible and incompressible flows
5. Incompressible Newtonian laminar flows
6. Incompressible non-Newtonian flows
7. Free surface flows
8. Buoyancy driven flows
9. Compressible high-speed gas flow
10. Adaptive mesh refinement
11. Turbulent flows
12. Flow and heat transport in porous media
13. Shallow-water problems
14. Long and medium waves
15. Short waves
16. Fluid–structure interaction
17. Biofluid dynamics – blood flow
18. Data-driven methods
19. Computer implementation of the CBS algorithm
Appendix A: Self-adjoint differential equations
Appendix B: Non-conservative form of Navier–Stokes equations
Appendix C: Computing drag force and stream function
Appendix D: Convection–diffusion equations: vector-valued variables
Appendix E: Integration formulae
Appendix F: Edge-based finite element formulation
Appendix G: Boundary layer–inviscid flow coupling
Appendix H: Multigrid method
Appendix I: Mass-weighted averaged turbulence transport equations
Appendix J: Introduction to neural networks
- No. of pages: 596
- Language: English
- Edition: 8
- Published: December 2, 2024
- Imprint: Butterworth-Heinemann
- Hardback ISBN: 9780323958868
- eBook ISBN: 9780323958875
RT
R. L. Taylor
R.L Taylor is a Professor of the Graduate School at the Department of Civil and Environmental Engineering, University of California, Berkeley, USA. Awarded the Daniel C. Drucker Medal by the American Society of Mechanical Engineering in 2005, the Gauss-Newton Award and Congress Medal by the International Association for Computational Mechanics in 2002, and the Von Neumann Medal by the US Association for Computational Mechanics in 1999.
Affiliations and expertise
Emeritus Professor of Engineering, University of California, Berkeley, USAPN
P. Nithiarasu
P. Nithiarasu is Professor at Zienkiewicz Institute for Modelling, Data and AI and Associate Dean for Research, Innovation and Impact, Faculty of Science and Engineering, Swansea University. Previously he has served as the Head of Zienkiewicz Centre for Computational Engineering, Deputy Head of College of Engineering and Dean of Academic Leadership. He was awarded the Zienkiewicz silver medal from the ICE London in 2002, the ECCOMAS Young Investigator award in 2004, and the prestigious EPSRC Advanced Fellowship in 2006.
Affiliations and expertise
Professor, Zienkiewicz Institute for Modelling, Data and AI and Associate Dean for Research, Innovation and Impact, Faculty of Science and Engineering, Swansea University