دانلود کتاب Design optimization of fluid machinery: applying computational fluid dynamics and numerical optimization

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Content: Cover
Title Page
Copyright
Contents
Preface
Chapter 1 Introduction
1.1 Introduction
1.2 Fluid Machinery: Classification and Characteristics
1.3 Analysis of Fluid Machinery
1.4 Design of Fluid Machinery
1.4.1 Design Requirements
1.4.2 Determination of Meanline Parameters
1.4.3 Meanline Analysis
1.4.4 3D Blade Design
1.4.5 Quasi 3D Through‐Flow Analysis
1.4.6 Full 3D Flow Analysis
1.4.7 Design Optimization
1.5 Design Optimization of Turbomachinery
References
Chapter 2 Fluid Mechanics and Computational Fluid Dynamics
2.1 Basic Fluid Mechanics
2.1.1 Introduction 2.1.2 Classification of Fluid Flow2.1.2.1 Based on Viscosity
2.1.2.2 Based on Compressibility
2.1.2.3 Based on Flow Speed (Mach Number)
2.1.2.4 Based on Flow Regime
2.1.2.5 Based on Number of Phases
2.1.3 One‐, Two‐, and Three‐Dimensional Flows
2.1.3.1 One‐Dimensional Flow
2.1.3.2 Two‐ and Three‐Dimensional Flow
2.1.4 External Fluid Flow
2.1.5 The Boundary Layer
2.1.5.1 Transition from Laminar to Turbulent Flow
2.2 Computational Fluid Dynamics (CFD)
2.2.1 CFD and its Application in Turbomachinery
2.2.1.1 Advantages of Using CFD
2.2.1.2 Limitations of CFD in Turbomachinery 2.2.2 Basic Steps Involved in CFD Analysis2.2.2.1 Problem Statement
2.2.2.2 Mathematical Model
2.2.3 Governing Equations
2.2.3.1 Mass Conservation
2.2.3.2 Momentum Conservation
2.2.3.3 Energy Conservation
2.2.4 Turbulence Modeling
2.2.4.1 What is Turbulence?
2.2.4.2 Need for Turbulence Modeling
2.2.4.3 Reynolds‐Averaged Navier-Stokes Equations
2.2.4.4 Turbulence Closure Models
2.2.4.5 Large Eddy Simulation (LES)
2.2.4.6 Direct Numerical Simulation (DNS)
2.2.5 Boundary Conditions
2.2.5.1 Inlet/Outlet Boundary Conditions
2.2.5.2 Wall Boundary Conditions 2.2.5.3 Periodic/Cyclic Boundary Conditions2.2.5.4 Symmetry Boundary Conditions
2.2.6 Moving Reference Frame (MRF)
2.2.7 Verification and Validation
2.2.8 Commercial CFD Software
2.2.9 Open Source Codes
2.2.9.1 OpenFOAM
References
Chapter 3 Optimization Methodology
3.1 Introduction
3.1.1 Engineering Optimization Definition
3.1.2 Design Space
3.1.3 Design Variables and Objectives
3.1.4 Optimization Procedure
3.1.5 Search Algorithm
3.2 Multi‐Objective Optimization (MOO)
3.2.1 Weighted Sum Approach
3.2.2 Pareto‐Optimal Front 3.3 Constrained, Unconstrained, and Discrete Optimization3.3.1 Constrained Optimization
3.3.2 Unconstrained Optimization
3.3.3 Discrete Optimization
3.4 Surrogate Modeling
3.4.1 Overview
3.4.2 Optimization Procedure
3.4.3 Surrogate Modeling Approach
3.4.3.1 Response Surface Approximation (RSA) Model
3.4.3.2 Artificial Neural Network (ANN) Model
3.4.3.3 Kriging Model (KRG) Model
3.4.3.4 PRESS‐Based‐Averaging (PBA) Model
3.4.3.5 Simple Average (SA) Model
3.5 Error Estimation
3.5.1 General Errors When Simulating and Optimizing a Turbomachinery System