Multiphysics Modeling

Materials, Components, and Systems

Murat Peksen

• Publisher: Academic Press
• Year: 2018
• ISBN:
  9780128119037
• Topic: Technology & Engineering
• Subtopic: Mechanical Engineering
• Index: Technology & Engineering

Multiphysics Modelling: Materials, Components, and System s focuses on situations where coupled phenomena involving a combination of thermal, fluid, and solid mechanics occur. Important fundamentals of the various physics that are required in multiphysics modelling are introduced and supported with practical problems. More advanced topics such as creep deformation, fatigue and fracture, multiphase flow or melting in porous media are tackled. 3D interactions in system architectures and energy systems such as batteries, reformer or fuel cells, and modelling of high-performance materials are exemplified. Important multiphysics modelling issues are highlighted. In addition to theory, solutions to problems, such as in linear and non-linear situations are addressed, as well as specific solutions for multiphysics modelling of fluid-solid, solid-solid and fluid-fluid interactions are given. Drawing on teaching experience, industry solutions, and the latest research, this book is the most complete guide to multiphysics modelling available for students and researchers in diverse science and engineering disciplines.

• Provides a thorough intro to the theory behind multiphysics modeling
• Covers both linear and non-linear material behaviors
• Helps to answer practical questions such as when to use 2D or 3D modeling

Chapter 1

Introduction to Multiphysics Modelling

Abstract

MULTIPHYSICS is the science, studying multiple interacting phenomena. With its complexity and covering a wide range of physical fields, multiphysics modelling is the royal discipline of numerical modelling to solve engineering problems. Numerical methods are the essential tool for predicting and simulating the multiphysical behaviour of interacting complex engineering systems. Therefore, multiphysics modelling has witnessed many significant developments in the last century, due to the progress in numerical methods. The historical development of numerical methods show that they are attributed to astronomers and applied mathematicians who were concerned to transform their physical problem into a mathematical description, which they called modelling. This is the reason why most of the solvers of numerical codes are endorsed to the famous astronomers like Newton, Gauss or Euler etc. The fundamentals of numerical analyses i.e. algorithms-algebra, however, originate even to earlier times as it was for the first time used and named after another great scientific mind Abu Ja’far Muhammad ibn Musa al-Khwarizmi [1] who lived in the 8th Century during the Islamic empire in Todays Khiva, Uzbekistan (Figure 1.1). The progress in numerical analyses continued until today and will continue further. The work of Brezinski and Wuytack [2] depicts the historical development of numerical analyses that gives an idea about where the roots of the subject multiphysics modelling has been established. Accordingly, it was John von Neumann (1903–1957) [3] who recognised for the first time the power of scientific computing using computers in solving complex problems, which is required to handle the complex interactions.

Keywords

Multiphysics; modelling; numerical analysis; CFD; FEM

Chapter Outline

• 1.1 Multiphysics Classification 4
• 1.2 Multiphysics Methodology 5
  • 1.2.1 Pre-Processing 6
  • 1.2.2 Numerical Simulation 24
  • 1.2.3 Post-Processing 28
• References 29

MULTIPHYSICS is the science, studying multiple interacting phenomena. With its complexity and covering a wide range of physical fields, multiphysics modelling is the royal discipline of numerical modelling to solve engineering problems. Numerical methods are the essential tool for predicting and simulating the multiphysical behaviour of interacting complex engineering systems. Therefore, multiphysics modelling has witnessed many significant developments in the last century, due to the progress in numerical methods. The historical development of numerical methods show that they are attributed to astronomers and applied mathematicians who were concerned to transform their physical problem into a mathematical description, which they called modelling. This is the reason why most of the solvers of numerical codes are endorsed to the famous astronomers like Newton, Gauss or Euler etc. The fundamentals of numerical analyses i.e. algorithms-algebra, however, originate even to earlier times as it was for the first time used and named after another great scientific mind Abu Ja’far Muhammad ibn Musa al-Khwarizmi [1] who lived in the 8th Century during the Islamic empire in Todays Khiva, Uzbekistan (Fig. 1.1). The progress in numerical analyses continued until today and will continue further. The work of Brezinski and Wuytack [2] depicts the historical development of numerical analyses that gives an idea about where the roots of the subject multiphysics modelling has been established. Accordingly, it was John von Neumann (1903-1957) [3] who recognised for the first time the power of scientific computing using computers in solving complex problems, which is required to handle the complex interactions.

Figure 1.1 Script from al-Kitâb al-mukhtasar fî hisâb al-jabr wa l-muqâbala and the modern statue of al-Khwarizmi at Khiva, in Ouzbekistan. Photo Alain Juhel [4].

Hence, computer aided modelling has become more and more popular. Today it has been an essential tool for predicting and simulating the multiphysical behaviour of complex engineering systems. Parallel to the high-performance computer hardware development, there have been many software on the market, comprising various numerical algorithms to solve such complex problems.

These advances have contributed to an upsurge of multiphysics modelling, which has been increased since coupled phenomena such as thermal, flow and mechanics very often occur. This makes multiphysics modelling a vital component in the design development and optimisation of materials, components and systems. Today, most of the commercial programs have gained common acceptance among engineers in the industry and scientists. These extend increasingly their capabilities to take into account the interactions of various phenomena.

This will avoid the extreme simplifications on problems that are usually performed. Because the devised solutions to complex multiphysics problems via simplified mathematical models or ignored physical complexities will have an effect on the results. Moreover, to perform and evaluate the predictions still requires expertise from interdisciplinary fields comprising computer science, mathematics and many engineering fields. This is comparable to someone who knows how to read and write and uses any means of tool, such a software, pencil, typewriter to convert his knowledge into practice. Hence, the synergy between theory and the practice of multiphysics is extremely important.

But why should we consider using multiphysics modelling? First of all, there are several technical advantages employing multiphysics modelling. It is capable of reducing the time and costs of the pre-development phase of a product, substantially. Using experimental measurements are in most scientific and engineering cases very prohibitive. Setting up and performing those tests may take very long operation times. For instance, the ability to control and investigate large-scale systems or very complex systems is very difficult. To perform measurements or safety studies that are operating under hazardous conditions and are not possible, suggests the support of multiphysics modelling and simulation. Moreover, parameter studies or long-term behaviour studies that require tremendous measurement time, cost and create large data pool may benefit from the substantial reduced efforts using multiphysics modelling. Other advantages would be the detailed visualisation and analysis capabilities given by multiphysics that will improve the knowledge about the material, component process or overall system behaviour.

In contrast, the estimate expenses for the multiphysics modelling approach are based on a suitable computer hardware (~5000 €–10000 €) and software that typically ranges upon its nature, whether it is an open source, house-in code, or a commercial one perpetual/annual licence fees. The latter one has a wide range on the market from estimated ~2000 € to 30000 €, depending on the capabilities and features required.

In overall, for most engineering design, material and system development, these costs are very good value, considering the gain, time and personnel. The most expensive investment for the organisation would be the multiphysics expert. These people are extremely qualified and have may scientific and technical skills that are gathered over many years of education, training and practical experience. It should be noted that multiphysics simulations are working in synergy with experimental scientists and should not be seen as competitive, as both complement each other. Experimental activities and results are required both for data input for the numerical predictions, as well as provide data or practical knowledge to evaluate the accuracy of the analyses.

1.1 Multiphysics Classification

Multiphysics modelling of components materials and systems can consider interactions of a single discipline such as fluid flow coupled with heat transfer, chemically reacting flow etc. However, it can also comprise physics from various disciplines that range from solid mechanics to electromagnetism. The procedure for a coupled analysis depends on which fields are being coupled, but basically two main methods can be used namely, the load transfer and direct method. The direct method usually deals with just one analysis that uses a coupled-field element type, containing all necessary degrees of freedom. The coupling is handled by calculating mathematical element matrices or element load vectors that contain all necessary terms.

The load transfer method involves two or more analyses, each belonging to a different field. The two fields are coupled by utilising results from one analysis as input for another analysis. Some analyses can have one-way coupling. For example, in a thermal stress problem, the temperature field introduces thermal strains in the structural field, but the structural strains generally do not affect the temperature distribution back. In such cases, there is no need to iterate between the two field solutions. More complicated cases involve two-way coupling. A piezoelectric analysis, for example, handles the interaction between the structural and electric fields together; it solves for the voltage distribution due to applied displacements, or vice versa. In a fluid-structure interaction problem, the fluid pressure causes the structure to deform, which in turn causes the fluid solution to change.

This problem requires iterations performed between the two physics fields for convergence. Moreover, the numerical grid needs to be adapted each time, as the compute...

Table of contents

• Cover image
• Title page
• Table of Contents
• Copyright
• Dedication
• The Very First Page
• List of Figures
• List of Tables
• About the Author
• Preface
• Acknowledgements
• Chapter 1. Introduction to Multiphysics Modelling
• Chapter 2. Multiphysics Modelling of Fluid Flow Systems
• Chapter 3. Multiphysics Modelling of Thermal Environments
• Chapter 4. Multiphysics Modelling of Structural Components and Materials
• Chapter 5. Multiphysics Modelling of Interactions in Systems
• Chapter 6. Thermomechanical Modelling of Materials and Components
• Chapter 7. Multiphysics Modelling of High-Performance Materials
• Chapter 8. Multiphysics Modelling of Energy Systems
• Chapter 9. Multiphysics Modelling Issues
• Index