
CFD Error Elimination with Optimal Finite Element Constructions
A.J. Baker(Author)
Elsevier (Publisher)
Will be published approx. on 1. January 2029
Book
Paperback/Softback
250 pages
978-0-323-85211-1 (ISBN)
Description
CFD Error Elimination with Optimal Finite Element Constructions contains the theoretical basis, equation development, and algorithm development steps needed to generate a significantly improved AD methodology for CFD users and code developers worldwide. By informing users of the presence of these errors and the possibility that the solution they are obtaining could have embedded errors, this book aims to improve the accuracy of research carried out across fluid mechanics, particularly in turbulence and heat transfer.
In general, the field of computational fluid dynamics (CFD) involves the numerical solution of the Navier Stokes equations, the alternate compressible form, and the required constitutive equations to close the solution. These equations are inherently unstable and require some form of artificial dissipation (AD) in order to stabilize the numerical solution. One distinguishing factor in all CFD computer software is how they handle this AD and how accurately the code results compare to known solutions, i.e., validation. The accuracy of all existing methods can be improved and is nowhere near perfect.
In general, the field of computational fluid dynamics (CFD) involves the numerical solution of the Navier Stokes equations, the alternate compressible form, and the required constitutive equations to close the solution. These equations are inherently unstable and require some form of artificial dissipation (AD) in order to stabilize the numerical solution. One distinguishing factor in all CFD computer software is how they handle this AD and how accurately the code results compare to known solutions, i.e., validation. The accuracy of all existing methods can be improved and is nowhere near perfect.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
College/higher education
Researchers in academia and industry with an interest in fluid mechanics, heat transfer and computational sciences.
Product notice
Paperback (trade)
Unsewn / adhesive bound
Dimensions
Height: 229 mm
Width: 152 mm
ISBN-13
978-0-323-85211-1 (9780323852111)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
A.J. Baker is an Emeritus Professor at the Dept of Mechanical, Aerospace, and Biomedical Engineering of the University of Tennessee, Knoxville, USA. He has had a career of over 60 years in mechanical engineering, including spells in industry as well as academia, with most of that time spent working on computational fluid dynamics. He has published over 300 publications, including 5 books, and holds 2 US patents.
Author
Emeritus Professor, Department of Mechanical, Aerospace, and Biomedical Engineering, University of Tennessee, Knoxville, USA
Content
1. Introduction to CFD
2. A brief history of CFD legacy code creation
3. Navier-Stokes PDE Statements
4. NS spatial discretization O(h2) truncation error (TE)
5. RaNS/LES spatial discretization O(h2) TE annihilation
6. NS temporal/phase discretization O(?t3, mp) TE annihilation
7. Radiation, Stefan-Boltzmann, radiosity, efficiency
8. Weak form theory, attributes, O(h4, m4, ?t4) CFD algorithms/codes
9. Space filtered NS PDE system closed modeling free
10. Filtered NS (FaNS) theory rendered bounded domain well-posed
11. Validation, FaNS theory laminar dominated predictions Re < 4000
12. FaNS theory periodic, multi-scale, transitional prediction, Re ? 12,000
2. A brief history of CFD legacy code creation
3. Navier-Stokes PDE Statements
4. NS spatial discretization O(h2) truncation error (TE)
5. RaNS/LES spatial discretization O(h2) TE annihilation
6. NS temporal/phase discretization O(?t3, mp) TE annihilation
7. Radiation, Stefan-Boltzmann, radiosity, efficiency
8. Weak form theory, attributes, O(h4, m4, ?t4) CFD algorithms/codes
9. Space filtered NS PDE system closed modeling free
10. Filtered NS (FaNS) theory rendered bounded domain well-posed
11. Validation, FaNS theory laminar dominated predictions Re < 4000
12. FaNS theory periodic, multi-scale, transitional prediction, Re ? 12,000