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Optimal Design of Complex Mechanical Systems

by: Mastinu, G.; Gobbi, M.; Miano, C.

Optimal Design of Complex Mechanical Systems

by: Mastinu, G.; Gobbi, M.; Miano, C.

ISBN 13:
9783540343547
ISBN 10:
3540343547
Edition: 1st
Format: Hardcover
Copyright: 10/31/2006
Publisher: Springer Verlag

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Summary

"Optimal Design of Complex Mechanical Systems" presents the foundations and practical application of multi-objective optimization methods to Vehicle Design Problems with an extensive overview of examples. The first part provides an introduction and a general theoretical information about the optimization of complex mechanical systems and multi-objective optimization methods. Several presented applications such as the global approximation approach are brand new in literature and extensively exposed the first time in this book. The second Part of the book shows some examples of the application of the proposed methods to the solution of real vehicle design problems.

Part I Theory

1 Introduction to the Optimal Design of Complex Mechanical Systems

(22)

1.1 On the Optimal Design of Complex Systems

(9)

1.2 Finding the Pareto-optimal Sets

(9)

1.2.1 Exhaustive Method

(2)

1.2.2 Uniformly Distributed Sequences and Random Search

(1)

1.2.3 Genetic Algorithms

(1)

1.2.4 Comparison of Broadly Applicable Methods to Solve Optimisation Problems

(1)

1.2.5 Global Approximation

(3)

1.2.6 Multi-objective Programming via Non-linear Programming

(2)

1.2.7 Algorithms to Solve Optimisation Problems in Scalar Form

(1)

1.3 Understanding Pareto-optimal Solutions

(4)

2 Engineering Design and Optimal Design of Complex Mechanical Systems: Definitions

(22)

2.1 Engineering Design

(3)

2.1.1 Stages of the Design Process

(2)

2.1.2 Creativity

(1)

2.2 Optimal Design of Complex Mechanical Systems

(2)

2.2.1 Fundamental Hypothesis

(1)

2.2.2 Single– and Multi-criteria Optimisation

(1)

2.2.3 Multi-criteria Optimisation (MCO)

(1)

2.2.4 multi-objective Optimisation (MOO)

(1)

2.2.5 Multi-objective Programming (MOP)

(1)

2.3 Complex Systems

(1)

2.4 System Models

(1)

2.5 System Performances, Criteria, Objective Functions

(1)

2.6 System Parameters, Design Variables

(1)

2.7 Constraints

(1)

2.8 Space of Design Variables, Space of Objective Functions

(1)

2.9 Feasible Design Variables Domain, Design Solution

(1)

2.9.1 Conflict

(1)

2.10 Multi-objective Programming (MOP)

(10)

2.10.1 Non-linear Programming (NLP) and Constrained Minimisation

(3)

2.10.2 Multi-objective Programming: Definition

(1)

2.10.3 Pareto-optimal Solutions and Pareto-optimal Set

(3)

2.10.4 Ideal and Nadir Design Solutions

(1)

2.10.5 Related Concepts

(1)

2.10.6 Basic Problems and Capabilities of Multi-objective Optimisation

(1)

2.11 Decomposition of Design Problems

(3)

3 Multi-objective Optimisation

(52)

3.1 Methods to Solve Multi-objective Programming (MOP) Problems

(1)

3.2 Pareto-optimal Set Generation Methods

(2)

3.3 Global Sensitivity Analysis

(6)

3.3.1 Global Sensitivity Analysis Based on Linear Regression Methods

(2)

3.3.2 Sobol Method

(1)

3.3.3 Spearman Rank Correlation Coefficient

(3)

3.3.4 Global Sensitivity Via Artificial Neural Network

(1)

3.4 Pareto-optimal Set Computation

(27)

3.4.1 Exhaustive Method

(1)

3.4.2 Low Discrepancy Sequences

(10)

3.4.3 Selection of the Pareto-optimal Set

(1)

3.4.4 Genetic Algorithms

(7)

3.4.5 Unconstrained Minimisation

(1)

3.4.6 Simplex Method

(1)

3.4.7 Sequential Unconstrained Minimisation Techniques

(2)

3.4.8 Method of Feasible Directions, Sequential Quadratic Programming

(1)

3.4.9 Weighted Sum

(1)

3.4.10 Constraints Method

(3)

3.5 Design Synthesis — Choosing a Final Design Solution

(6)

3.5.1 Utility Function

(1)

3.5.2 Lexicographic Ordering

(1)

3.5.3 Goal Programming

(1)

3.5.4 Preference Via Trained Artificial Neural Network

(1)

3.5.5 Min—Max Methods

(2)

3.5.6 Hierarchical Optimisation Method

(1)

3.5.7 Normal–Boundary Intersection Method

(1)

3.6 Interactive Methods

(6)

3.6.1 Interactive Computation of the Pareto-optimal Solutions and Pareto-optimal Set Boundaries Through Pareto Sensitivity Analysis

(4)

3.7 Symbolical Derivation of PO Sets

(2)

3.7.1 Theorems of Monotonicity (Optimisation Problems with Constraints)

(1)

3.7.2 Theorems of Monotonicity (Optimisation Problems without Constraints)

(1)

3.8 Illustrating the Pareto-optimal Set

(2)

4 Global Approximation

(22)

4.1 Global Approximation Techniques

100

(1)

4.2 Training Data Generation

101

(1)

4.2.1 (Fractional) Factorial Designs

101

(1)

4.2.2 Uniformly Distributed Sequences and Orthogonal Array

102

(1)

4.3 Selection of the Global Approximation Model

102

(2)

4.3.1 Polynomial Linear and Quadratic Interpolation

102

(2)

4.4 Least Squares Regression Polynomial Approximation

104

(2)

4.5 Kriging Interpolating Models

106

(1)

4.6 Artificial Neural Networks

106

(15)

4.6.1 Multi-layer Perceptron Neural Network

107

(5)

4.6.2 Radial Basis Function Neural Network

112

(9)

Part II Applications

5 Optimal Ride Comfort and Active Safety of Road Vehicles

121

(38)

5.1 System Model of a Passively Suspended Vehicle

122

(10)

5.1.1 Equations of Motion and Response to Stochastic Excitation

122

(2)

5.1.2 Derivation of Standard Deviations in Analytical Form

124

(4)

5.1.3 Parameter Sensitivity Analysis

128

(4)

5.2 Passively Suspended Vehicle System Optimisation

132

(10)

5.2.1 Problem Formulation

132

(1)

5.2.2 Optimal Performances and Suspension Design Variables

132

(10)

5.3 System Model of an Actively Suspended Road Vehicle

142

(5)

5.3.1 Equations of Motion and Response to Stochastic Excitation

142

(1)

5.3.2 Derivation of Standard Deviations in Analytical Form

143

(3)

5.3.3 Comparison of 1S-PSD and 2S-PSD Formulae

146

(1)

5.3.4 Validation Problems and Usefulness of the Presented Theory

146

(1)

5.4 Actively Suspended Vehicle System Optimisation

147

(10)

5.4.1 Optimal Performances and Suspension Design Variables

147

(10)

5.5 Conclusion

157

(1)

5.6 Appendix: Tabulated Values of the Integral Form

158

(1)

6 Optimal Handling and Active Safety of Road Vehicles

159

(32)

6.1 System Model

160

(13)

6.1.1 Vehicle Response to a Steering Step Input: Linear Model

162

(3)

6.1.2 Vehicle Response to a Steering Step Input: Non-Linear Model

165

(3)

6.1.3 Objective Functions

168

(5)

6.2 Results of the Optimisation

173

(9)

6.2.1 Analytical Solution (Linear Case)

174

(5)

6.2.2 Numerical Solutions (Linear Case)

179

(1)

6.2.3 Numerical Solution (Non-Linear Case)

180

(2)

6.3 Validation

182

(5)

6.3.1 Validation of the Model

182

(3)

6.3.2 Validation of the Optimisation Process

185

(2)

6.4 Conclusion

187

(4)

7 Optimal Design of the Tyre-Suspension System of a Racing Car

191

(24)

7.1 System Model

192

(2)

7.1.1 Vehicle Model

192

(1)

7.1.2 Tyre Model

193

(1)

7.1.3 Validation

193

(1)

7.2 Design Variables

194

(5)

7.2.1 Suspension System

196

(2)

7.2.2 Tyre Characteristic

198

(1)

7.3 Running Situations and Objective Functions

199

(4)

7.3.1 Steady-state Turning

199

(2)

7.3.2 J-Turn

201

(1)

7.3.3 Power On–Off while Steering

201

(1)

7.3.4 Braking into a Bend

202

(1)

7.3.5 Passing over a Kerb While Steering

202

(1)

7.4 Search Method

203

(2)

7.4.1 Reduction of Objective Functions

203

(1)

7.4.2 Pareto-optimal Solutions

203

(2)

7.5 Results

205

(7)

7.5.1 Comparison of the Performances of Global Approximation Methods

206

(6)

7.6 Conclusion

212

(3)

8 Integrated Controls for the Improvement of Ride, Comfort, Handling and Active Safety of Road Vehicles

215

(30)

8.1 System Models and Reference Driving Situations

216

(7)

8.1.1 System Models

216

(1)

8.1.2 Reference Driving Situations

216

(7)

8.2 Numerical Application

223

(20)

8.2.1 First Iteration

223

(9)

8.2.2 Second (and Final) Iteration

232

(11)

8.3 Conclusions

243

(2)

9 Optimal Design of a Double-Cone Synchroniser

245

(18)

9.1 Synchroniser System Model

246

(3)

9.1.1 Physical Model

246

(3)

9.2 Formulation of the Design Problem for the Optimisation of a Synchroniser

249

(4)

9.2.1 Design Variables

249

(1)

9.2.2 Objective Functions

249

(2)

9.2.3 Constraints

251

(2)

9.3 Method for the Optimal Design of a Synchroniser

253

(5)

9.3.1 Feasible Design Variables Domain

253

(1)

9.3.2 Global Sensitivity Analysis

253

(2)

9.3.3 Global Approximation

255

(1)

9.3.4 Quasi-Monte Carlo Search

256

(1)

9.3.5 Multi-Objective Optimisation

257

(1)

9.3.6 Robust Design and Synthesis of Optimal Design Solutions

257

(1)

9.4 Optimal Design of a Synchroniser

258

(2)

9.5 Conclusion

260

(3)

10 Optimal Design of the Suspension System of Railway Vehicles

263

(22)

10.1 System Model

263

(11)

10.1.1 Equations of Motion and Responses to Stochastic Excitation

263

(4)

10.1.2 Derivation of Standard Deviations in Analytical Form

267

(2)

10.1.3 Complete Formulae Using the 1S-PSD (Eq. (10.7))

269

(1)

10.1.4 Formulae for Vanishing Primary Damping Using the 1S-PSD (Eq. (10.7))

270

(1)

10.1.5 Simplified Formulae Using the 1S-PSD (Eq. (10.7))

271

(1)

10.1.6 Complete Formulae Using the 2S-PSD (Eq. (10.8))

272

(1)

10.1.7 Formulae for Vanishing Primary Damping Using the 2S-PSD (Eq. (10.8))

272

(1)

10.1.8 Simplified Formulae Using the 2S-PSD (Eq. (10.8))

273

(1)

10.2 Validation

274

(2)

10.2.1 Primary Stiffness

274

(1)

10.2.2 Natural Frequency

275

(1)

10.2.3 Damping Ratio

275

(1)

10.3 Parameter Sensitivity Analysis

276

(7)

10.3.1 Standard Deviation of Force on Axle-box

276

(1)

10.3.2 Standard Deviation of Body Acceleration

277

(1)

10.3.3 Standard Deviation of Secondary Stroke

278

(1)

10.3.4 Optimal Secondary Suspension Design Variables

279

(4)

10.4 Conclusion

283

(2)

11 Optimal Design of the Layout of Railway Passenger Vehicles

285

(18)

11.1 Design Aims and Related Objective Functions

286

(2)

11.2 Design Variables to Be Tuned

288

(1)

11.3 Constraints

288

(2)

11.4 Objective Functions

290

(6)

11.4.1 Unloaded Vehicle Mass/Fully Loaded Vehicle Mass

290

(3)

11.4.2 Vehicle Length/Payload

293

(1)

11.4.3 Ride Comfort

293

(1)

11.4.4 Vehicle/Track Dynamic Interaction

293

(1)

11.4.5 Three Degrees of Freedom Model

294

(2)

11.4.6 Other Indices

296

(1)

11.5 Analysis and Choice of Preferred Optimal Solutions

296

(5)

11.5.1 Inter-city Cars

298

(1)

11.5.2 Sub-urban Cars

298

(1)

11.5.3 Urban Cars

299

(2)

11.6 Conclusion

301

(2)

12 Optimal Design of Helical Spring

303

(28)

12.1 Fundamentals of. Optimal Design of Springs

304

(4)

12.2 Composite Tubular Spring Models

308

(10)

12.2.1 Stress, Strain and Spring Stiffness

309

(4)

12.2.2 Global Stability

313

(1)

12.2.3 Local Stability

313

(3)

12.2.4 Vibrations

316

(1)

12.2.5 Spring Material Strength

317

(1)

12.3 Model Validation

318

(3)

12.4 Numerical Application

321

(7)

12.4.1 Design Aims and Related Objective Functions

321

(1)

12.4.2 Design Variables to Be Tuned

322

(1)

12.4.3 Constraints

323

(1)

12.4.4 Finding Optimal Solutions

324

(1)

12.4.5 Analysis of the Optimal Solutions

324

(4)

12.5 Conclusions

328

(1)

12.6 Appendix: Analytical Expression of Critical Load

329

(2)

13 Interactive Optimisation of a Flywheel

331

(12)

13.1 System Model

332

(2)

13.2 Objective Functions

334

(1)

13.3 Design Variables

335

(1)

13.4 Results

336

(7)

References

343

(12)

Index

355

Amazon no longer offers textbook rentals. We do!

Optimal Design of Complex Mechanical Systems

Optimal Design of Complex Mechanical Systems

9783540343547

3540343547

Summary

Table of Contents

Supplemental Materials

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