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2020 | Buch

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Numerical Simulation-based Design

Theory and Methods

verfasst von: Xu Han, Dr. Jie Liu

Verlag: Springer Singapore

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

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Über dieses Buch

This book focuses on numerical simulation-based design theory and methods in
mechanical engineering. The simulation-based design of mechanical equipmentinvolves considerable scientific challenges including extremely complex systems,extreme working conditions, multi-source uncertainties, multi-physics coupling, andlarge-scale computation. In order to overcome these technical difficulties, this booksystematically elaborates upon the advanced design methods, covering high-fidelitysimulation modeling, rapid structural analysis, multi-objective design optimization,uncertainty analysis and optimization, which can effectively improve the designaccuracy, efficiency, multi-functionality and reliability of complicated mechanicalstructures.
This book is primarily intended for researchers, engineers and postgraduate studentsin mechanical engineering, especially in mechanical design, numerical simulation andengineering optimization.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract

In the current development trend of informatization, digitalization, and intelligentization, different disciplines are comprehensively intersecting. Digital technologies unprecedentedly permeate and facilitate to realize the advanced design and manufacturing technologies, which lead to significant progress of the manufacturing industry in concurrence with both great opportunities and challenges.

Xu Han, Jie Liu

Chapter 2. Introduction to High-Fidelity Numerical Simulation Modeling Methods

Abstract

In the design and development process of mechanical equipment, effects of the different working conditions and the design variables on the equipment performance should be comprehensively explored and appropriately addressed. Physical experiments on the equipment are usually very effective to shed lights on the intricate mechanisms.

Xu Han, Jie Liu

Chapter 3. Computational Inverse Techniques

Abstract

The computational inverse technique-based high-fidelity numerical modeling is a comprehensive analysis of the experimental data and the numerical simulation model instead of a simple modeling analysis process or an optimal iteration process. Appropriate physical experiments are required to ensure the relatively strong sensitivity between the measured responses and the modeling parameters, while the numerical solution is expected to be available. In addition, the identification of the model parameters should address three problems, i.e., high computational intensity and the ill-posedness of the system, improvement for the identification efficiency and stability and the optimality of the solution to a specific extent.

Xu Han, Jie Liu

Chapter 4. Computational Inverse for Modeling Parameters

Abstract

In the last chapter, the model parameters are classified according to the requirements of the specific numerical simulation and the respective type of the parameters themselves. Based on this, the basic calculation procedure on the inverse problem for the model parameters is specified, and several practical computational inverse techniques are discussed. It is understood that the physical experimental test serves as the base for the model parameter identification.

Xu Han, Jie Liu

Chapter 5. Introduction to Rapid Structural Analysis

Abstract

With the increases of the complexity of practical equipment and the more stringent requirements for the high-fidelity modeling, the numerical simulation model becomes more and more comprehensive which leads to intractable computational intensity.

Xu Han, Jie Liu

Chapter 6. Rapid Structural Analysis Based on Surrogate Models

Abstract

The efficiency and precision of the surrogate model are the linchpins to ensure the proficiency of the rapid structural analysis and the performance of structural optimization design. This chapter will expose three types of generally applied surrogate models, i.e., the polynomial RS, the RBF, and the high-dimensional surrogate model. The traditional polynomial construction method based on the least square fitting does not differentiate the terms in view of their respective contribution, and thus, it tends to ensue instability for the fitting results due to the redundancy of the terms. To make amendment, a polynomial structural selection technique based on error reduction ratio is proposed to evaluate the sensitivity degree of each term of the polynomial RS to construct the optimal RS through eliminating the terms with insignificant influence.

Xu Han, Jie Liu

Chapter 7. Rapid Structural Analysis Based on Reduced Basis Method

Abstract

For the rapid analysis methods, on the one hand, it is usually required to reduce the calculation intensity substantially, while on the other hand, it is expected to maintain the physical properties of the original structure to ensure the reliability of the analysis results.

Xu Han, Jie Liu

Chapter 8. Introduction to Multi-objective Optimization Design

Abstract

In view of the constantly increasing design demands, such as multifunction of structures, high performance and low cost, multiple-objective optimization design has become a significant and indispensable approach to fulfill these comprehensive performance requirements in the design of mechanical equipment.

Xu Han, Jie Liu

Chapter 9. Micro Multi-objective Genetic Algorithm

Abstract

As a global search approach based on population evolution, the genetic algorithm (GA) has great advantage in solving MOPs. For most of the multi-objective genetic algorithms (MOGAs), a large size of evolutionary population is adopted in the process of fitness evaluation and selection operation to make the evolution direction towards the non-dominated optimal solution set and to guarantee the population diversity and the distribution uniformity.

Xu Han, Jie Liu

Chapter 10. Multi-objective Optimization Design Based on Surrogate Models

Abstract

With the increase of the complexity of engineering problems and the high-fidelity requirements for numerical simulation, the numerical model becomes more and more complex and computationally intensive. In view of the intractable computational intensity for the optimization design of practical engineering structures, highly efficient multi-objective optimization methods, as alternatives, have been extensively explored.

Xu Han, Jie Liu

Chapter 11. Introduction to Uncertain Optimization Design

Abstract

Generally, structural analysis and optimization design are implemented based on the deterministic system and models.

Xu Han, Jie Liu

Chapter 12. Uncertain Optimization Design Based on Interval Structure Analysis

Abstract

An uncertain optimization problem is usually transformed into a corresponding deterministic optimization problem.

Xu Han, Jie Liu

Chapter 13. Interval Optimization Design Based on Surrogate Models

Abstract

In this chapter, two efficient algorithms for nonlinear uncertain interval optimization are proposed with application of the surrogate model techniques.

Xu Han, Jie Liu

Titel: Numerical Simulation-based Design
verfasst von: Xu Han
Dr. Jie Liu
Verlag: Springer Singapore
Electronic ISBN: 978-981-10-3090-1
Print ISBN: 978-981-10-3089-5
DOI: https://doi.org/10.1007/978-981-10-3090-1

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