Using HPC for Computational Fluid Dynamics

A Guide to High Performance Computing for CFD Engineers

Shamoon Jamshed

• Publisher: Academic Press
• Year: 2015
• ISBN:
  9780128017517
• Topic: Ciencias físicas
• Subtopic: Mecánica de fluidos

Using HPC for Computational Fluid Dynamics: A Guide to High Performance Computing for CFD Engineers offers one of the first self-contained guides on the use of high performance computing for computational work in fluid dynamics.

Beginning with an introduction to HPC, including its history and basic terminology, the book moves on to consider how modern supercomputers can be used to solve common CFD challenges, including the resolution of high density grids and dealing with the large file sizes generated when using commercial codes.

Written to help early career engineers and post-graduate students compete in the fast-paced computational field where knowledge of CFD alone is no longer sufficient, the text provides a one-stop resource for all the technical information readers will need for successful HPC computation.

• Offers one of the first self-contained guides on the use of high performance computing for computational work in fluid dynamics
• Tailored to the needs of engineers seeking to run CFD computations in a HPC environment

Chapter 1

Introduction to CFD

Abstract

This chapter is an introduction to Computational Fluid Dynamics (CFD). Many organizations implement CFD in the computer-aided engineering phase. However, most of the time, higher management is not interested, perhaps because of the lengthy simulations or uncertainty regarding results. These issues are discussed and various misconceptions about CFD are explored and cleared up. The basics of CFD with governing equations are also discussed.

Keywords

CFD; Governing equations; Simulations; Uncertainty

1. Colorful Dynamics or Computational Fluid Dynamics?

Computational fluid dynamics (CFD) is one of the most quickly emerging fields in applied sciences. When computers were not mature enough to solve large numerical problems, two methods were used to solve fluid dynamics problems: analytical and experimental. Analytical methods were limited to simplified cases such as solving one-dimensional (1D) or 2D geometry, 1D flow, and steady flow. However, experimental methods demanded a lot of resources such as electricity, expensive equipment, data monitoring, and data post-processing. Sometimes for engineering analysis work, it is not within the budget of a small organization to establish such a facility. However, with the advent of modern computers and supercomputers, life has become much easier. With the passage of time numerical methods got matured and are now used to solve complex fluid dynamics problems in a short time. Thus, today, with a small investment, some good configuration personal computers can be bought and used to run CFD code that can handle complex flow geometries easily. The results can be achieved more quickly if some of the computers are joined or clustered together.

From an overall perspective, CFD is more economical than experiments. The twentieth century has seen the computer age move with cutting-edge changes, and problems or experiments that had never been thought possible to be performed experimentally or were difficult to perform because of limited resources are now possible with the modern technology. It can be said that CFD is more economical than experiments. With the advent of modern computer technology, it has gained in popularity as well because advanced methods for solving fluid dynamics equations can be analyzed quickly and efficiently.

In terms of accuracy, CFD lies in between the domain of theory and experiments. Because experiments mostly replicate real phenomena, they are much reliable. Analytical method is second because of certain assumptions involved while solving a particular problem. CFD is last because of it involves truncation errors, rounding off errors, and machine errors in numerical methods. To avoid making it “colorful dynamics,” it is the responsibility ...