Optimal Design of Complex Mechanical Systems: With Applications to Vehicle Engineering
Gespeichert in:
| Hauptverfasser: | , , |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Springer Berlin
2006
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| Ausgabe: | 1. Ed. |
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| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XLIV, 359 S. Ill., graph. Darst. 235 mm x 155 mm |
| ISBN: | 3540343547 9783540343547 |
Internformat
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| 100 | 1 | |a Mastinu, Giampiero |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Optimal Design of Complex Mechanical Systems |b With Applications to Vehicle Engineering |c Giampiero Mastinu ; Massimiliano Gobbi ; Carlo Miano |
| 250 | |a 1. Ed. | ||
| 264 | 1 | |a Berlin |b Springer Berlin |c 2006 | |
| 300 | |a XLIV, 359 S. |b Ill., graph. Darst. |c 235 mm x 155 mm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 4 | |a Experimental design | |
| 650 | 4 | |a Optimal designs (Statistics) | |
| 650 | 4 | |a Structural optimization | |
| 650 | 4 | |a Vehicles |x Design and construction | |
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| 650 | 0 | 7 | |a Fahrzeug |0 (DE-588)4016320-9 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Mehrkörpersystem |0 (DE-588)4038390-8 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a Konstruktionselement |0 (DE-588)4165100-5 |2 gnd |9 rswk-swf |
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| 700 | 1 | |a Gobbi, Massimiliano |e Verfasser |4 aut | |
| 700 | 1 | |a Miano, Carlo |e Verfasser |4 aut | |
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Datensatz im Suchindex
| _version_ | 1804136241899241472 |
|---|---|
| adam_text | G. MASTINU M. GOBBI C. MIANO
OPTIMAL DESIGN OF COMPLEX
MECHANICAL SYSTEMS
WITH APPLICATIONS TO VEHICLE ENGINEERING
WITH 161 FIGURES 62 TABLES
4Y SPRINGER
CONTENTS
PART I THEOR
Y
INTRODUCTIO
N T
O TH
E OPTIMA
L DESIG
N
OF COMPLE
X MECHANICA
L SYSTEM
S
3
1.1 ON THE OPTIMAL DESIGN OF COMPLEX SYSTEMS 3
1.2 FINDING TH
E PARETO-OPTIMAL SETS 12
1.2.1 EXHAUSTIVE METHOD 12
1.2.2 UNIFORMLY DISTRIBUTED SEQUENCES AND RANDOM SEARCH. . 14
1.2.3 GENETIC ALGORITHMS 15
1.2.4 COMPARISON OF BROADLY APPLICABLE METHODS
T
O SOLVE OPTIMISATION PROBLEMS 16
1.2.5 GLOBAL APPROXIMATION 16
1.2.6 MULTI-OBJECTIVE PROGRAMMING VIA NON-LINEAR
PROGRAMMING 19
1.2.7 ALGORITHMS TO SOLVE OPTIMISATION PROBLEMS
IN SCALAR FORM 21
1.3 UNDERSTANDING PARETO-OPTIMAL SOLUTIONS 21
ENGINEERIN
G DESIG
N AND OPTIMA
L DESIG
N
OF COMPLE
X MECHANICA
L SYSTEMS
: DEFINITION
S
25
2.1 ENGINEERING DESIGN 25
2.1.1 STAGES OF THE DESIGN PROCESS 25
2.1.2 CREATIVITY 27
2.2 OPTIMAL DESIGN OF COMPLEX MECHANICAL SYSTEMS 28
2.2.1 FUNDAMENTAL HYPOTHESIS 28
2.2.2 SINGLE- AND MULTI-CRITERIA OPTIMISATION 28
2.2.3 MULTI-CRITERIA OPTIMISATION (MCO) 28
2.2.4 MULTI-OBJECTIVE OPTIMISATION (MOO) 29
2.2.5 MULTI-OBJECTIVE PROGRAMMING (MOP) 29
2.3 COMPLEX SYSTEMS 30
2.4 SYSTEM MODELS 31
XII CONTENTS
2.5 SYSTEM PERFORMANCES, CRITERIA, OBJECTIVE FUNCTIONS 32
2.6 SYSTEM PARAMETERS
, DESIGN VARIABLES 33
2.7 CONSTRAINTS 33
2.8 SPACE OF DESIGN VARIABLES, SPACE OF OBJECTIVE FUNCTIONS 34
2.9 FEASIBLE DESIGN VARIABLES DOMAIN, DESIGN SOLUTION 34
2.9.1 CONFLICT 34
2.10 MULTI-OBJECTIVE PROGRAMMING (MOP) 34
2.10.1 NON-LINEAR PROGRAMMING (NLP)
AND CONSTRAINED MINIMISATION 34
2.10.2 MULTI-OBJECTIVE PROGRAMMING: DEFINITION 37
2.10.3 PARETO-OPTIMAL SOLUTIONS AND PARETO-OPTIMAL SET 38
2.10.4 IDEAL AND NADIR DESIGN SOLUTIONS 41
2.10.5 RELATED CONCEPTS 42
2.10.6 BASIC PROBLEMS AND CAPABILITIES
OF MULTI-OBJECTIVE OPTIMISATION 43
2.11 DECOMPOSITION OF DESIGN PROBLEMS 44
3 MULTI-OBJECTIV
E OPTIMISATIO
N
47
3.1 METHODS T
O SOLVE MULTI-OBJECTIVE PROGRAMMING (MOP)
PROBLEMS 47
3.2 PARETO-OPTIMAL SET GENERATION METHODS 48
3.3 GLOBAL SENSITIVITY ANALYSIS 50
3.3.1 GLOBAL SENSITIVITY ANALYSIS BASED
ON LINEAR REGRESSION METHODS 50
3.3.2 SOBOL METHOD 52
3.3.3 SPEARMAN RANK CORRELATION COEFFICIENT 53
3.3.4 GLOBAL SENSITIVITY VIA ARTIFICIAL NEURAL NETWORK 56
3.4 PARETO-OPTIMAL SET COMPUTATION 56
3.4.1 EXHAUSTIVE METHOD 57
3.4.2 LOW DISCREPANCY SEQUENCES 57
3.4.3 SELECTION OF TH
E PARETO-OPTIMAL SET 67
3.4.4 GENETIC ALGORITHMS 68
3.4.5 UNCONSTRAINED MINIMISATION 75
3.4.6 SIMPLEX METHOD 76
3.4.7 SEQUENTIAL UNCONSTRAINED MINIMISATION TECHNIQUES ...
. 76
3.4.8 METHOD OF FEASIBLE DIRECTIONS, SEQUENTIAL QUADRATIC
PROGRAMMING 78
3.4.9 WEIGHTED SUM 79
3.4.10 CONSTRAINTS METHOD 80
3.5 DESIGN SYNTHESIS - CHOOSING A FINAL DESIGN SOLUTION 83
3.5.1 UTILITY FUNCTION 83
3.5.2 LEXICOGRAPHIC ORDERING 84
3.5.3 GOAL PROGRAMMING 85
3.5.4 PREFERENCE VIA TRAINED ARTIFICIAL NEURAL NETWORK 86
3.5.5 MIN-MAX METHODS 86
CONTENTS XIII
3.5.6 HIERARCHICAL OPTIMISATION METHOD 88
3.5.7 NORMAL-BOUNDARY INTERSECTION METHOD 88
3.6 INTERACTIVE METHODS 89
3.6.1 INTERACTIVE COMPUTATION OF TH
E PARETO-OPTIMAL
SOLUTIONS AND PARETO-OPTIMAL SET BOUNDARIES THROUGH
PARETO SENSITIVITY ANALYSIS 91
3.7 SYMBOLICAL DERIVATION OF PO SETS 95
3.7.1 THEOREMS OF MONOTONICITY (OPTIMISATION PROBLEMS
WITH CONSTRAINTS) 95
3.7.2 THEOREMS OF MONOTONICITY (OPTIMISATION PROBLEMS
WITHOUT CONSTRAINTS) 96
3.8 ILLUSTRATING TH
E PARETO-OPTIMAL SET 97
GLOBA
L APPROXIMATIO
N
99
4.1 GLOBAL APPROXIMATION TECHNIQUES 100
4.2 TRAINING DAT
A GENERATION 101
4.2.1 (FRACTIONAL) FACTORIAL DESIGNS 101
4.2.2 UNIFORMLY DISTRIBUTED SEQUENCES
AND ORTHOGONAL ARRAY 102
4.3 SELECTION OF TH
E GLOBAL APPROXIMATION MODEL 102
4.3.1 POLYNOMIAL LINEAR AND QUADRATIC INTERPOLATION 102
4.4 LEAST SQUARES REGRESSION POLYNOMIAL APPROXIMATION 104
4.5 KRIGING INTERPOLATING MODELS 106
4.6 ARTIFICIAL NEURAL NETWORKS 106
4.6.1 MULTI-LAYER PERCEPTRON NEURAL NETWORK 107
4.6.2 RADIAL BASIS FUNCTION NEURAL NETWORK 112
PART I
I APPLICATION
S
5 OPTIMA
L RID
E COMFORT AN
D ACTIV
E SAFET
Y
OF ROA
D VEHICLE
S
121
5.1 SYSTEM MODEL OF A PASSIVELY SUSPENDED VEHICLE 122
5.1.1 EQUATIONS OF MOTION AND RESPONSE T
O STOCHASTIC
EXCITATION 122
5.1.2 DERIVATION OF STANDARD DEVIATIONS IN ANALYTICAL FORM.
. 124
5.1.3 PARAMETER SENSITIVITY ANALYSIS 128
5.2 PASSIVELY SUSPENDED VEHICLE SYSTEM OPTIMISATION 132
5.2.1 PROBLEM FORMULATION 132
5.2.2 OPTIMAL PERFORMANCES AND SUSPENSION
DESIGN VARIABLES 132
5.3 SYSTEM MODEL OF AN ACTIVELY SUSPENDED ROAD VEHICLE 142
5.3.1 EQUATIONS OF MOTION AND RESPONSE T
O STOCHASTIC
EXCITATION 142
5.3.2 DERIVATION OF STANDARD DEVIATIONS IN ANALYTICAL FORM.
. 143
XIV CONTENTS
5.3.3 COMPARISON OF 1S-PSD AND 2S-PSD FORMULAE 146
5.3.4 VALIDATION PROBLEMS AND USEFULNESS
OF THE PRESENTED THEORY 146
5.4 ACTIVELY SUSPENDED VEHICLE SYSTEM OPTIMISATION 147
5.4.1 OPTIMAL PERFORMANCES AND SUSPENSION DESIGN VARIABLES 147
5.5 CONCLUSION 157
5.6 APPENDIX: TABULATED VALUES OF THE INTEGRAL FORM 158
6 OPTIMA
L HANDLIN
G AN
D ACTIV
E SAFETY OF ROA
D VEHICLE
S
159
6.1 SYSTEM MODEL 160
6.1.1 VEHICLE RESPONSE T
O A STEERING STEP INPUT:
LINEAR MODEL 162
6.1.2 VEHICLE RESPONSE T
O A STEERING STEP INPUT:
NON-LINEAR MODEL 165
6.1.3 OBJECTIVE FUNCTIONS 168
6.2 RESULTS OF THE OPTIMISATION 173
6.2.1 ANALYTICAL SOLUTION (LINEAR CASE) 174
6.2.2 NUMERICAL SOLUTIONS (LINEAR CASE) 179
6.2.3 NUMERICAL SOLUTION (NON-LINEAR CASE) 180
6.3 VALIDATION 182
6.3.1 VALIDATION OF THE MODEL 182
6.3.2 VALIDATION OF THE OPTIMISATION PROCESS 185
6.4 CONCLUSION 187
7 OPTIMAL DESIG
N OF TH
E TYRE-SUSPENSIO
N SYSTE
M
OF A RACIN
G CAR
191
7.1 SYSTEM MODEL 192
7.1.1 VEHICLE MODEL 192
7.1.2 TYRE MODEL 193
7.1.3 VALIDATION 193
7.2 DESIGN VARIABLES 194
7.2.1 SUSPENSION SYSTEM 196
7.2.2 TYRE CHARACTERISTIC 198
7.3 RUNNING SITUATIONS AND OBJECTIVE FUNCTIONS 199
7.3.1 STEADY-STATE TURNING 199
7.3.2 J-TURN 201
7.3.3 POWER ON-OFF WHILE STEERING 201
7.3.4 BRAKING INTO A BEND 202
7.3.5 PASSING OVER A KERB WHILE STEERING 202
7.4 SEARCH METHOD 203
7.4.1 REDUCTION OF OBJECTIVE FUNCTIONS 203
7.4.2 PARETO-OPTIMAL SOLUTIONS 203
7.5 RESULTS 205
/7.5.1 COMPARISON OF THE PERFORMANCES OF GLOBAL
APPROXIMATION METHODS 206
7.6 CONCLUSION 212
CONTENTS XV
8 INTEGRATE
D CONTROLS FOR TH
E IMPROVEMEN
T
OF RIDE
, COMFORT, HANDLIN
G AND ACTIV
E SAFETY
OF ROA
D VEHICLES
215
8.1 SYSTEM MODELS AND REFERENCE DRIVING SITUATIONS 216
8.1.1 SYSTEM MODELS 216
8.1.2 REFERENCE DRIVING SITUATIONS 216
8.2 NUMERICAL APPLICATION 223
8.2.1 FIRST ITERATION 223
8.2.2 SECOND (AND FINAL) ITERATION 232
8.3 CONCLUSIONS 243
9 OPTIMAL DESIG
N OF A DOUBLE-CON
E SYNCHRONISER
245
9.1 SYNCHRONISER SYSTEM MODEL 246
9.1.1 PHYSICAL MODEL 246
9.2 FORMULATION OF TH
E DESIGN PROBLEM FOR THE OPTIMISATION
OF A SYNCHRONISER 249
9.2.1 DESIGN VARIABLES 249
9.2.2 OBJECTIVE FUNCTIONS 249
9.2.3 CONSTRAINTS 251
9.3 METHOD FOR THE OPTIMAL DESIGN OF A SYNCHRONISER 253
9.3.1 FEASIBLE DESIGN VARIABLES DOMAIN 253
9.3.2 GLOBAL SENSITIVITY ANALYSIS 253
9.3.3 GLOBAL APPROXIMATION 255
9.3.4 QUASI-MONTE CARLO SEARCH 256
9.3.5 MULTI-OBJECTIVE OPTIMISATION 257
9.3.6 ROBUST DESIGN AND SYNTHESIS OF OPTIMAL DESIGN
SOLUTIONS 257
9.4 OPTIMAL DESIGN OF A SYNCHRONISER 258
9.5 CONCLUSION 260
10 OPTIMAL DESIG
N OF TH
E SUSPENSIO
N SYSTE
M OF RAILWAY
VEHICLES
263
10.1 SYSTEM MODEL 263
10.1.1 EQUATIONS OF MOTION AND RESPONSES TO STOCHASTIC
EXCITATION 263
10.1.2 DERIVATION OF STANDARD DEVIATIONS IN ANALYTICAL FORM. . 267
10.1.3 COMPLETE FORMULAE USING THE 1S-PSD (EQ. (10.7)) ...
. 269
10.1.4 FORMULAE FOR VANISHING PRIMARY DAMPING USING
THE 1S-PSD (EQ. (10.7)) 270
10.1.5 SIMPLIFIED FORMULAE USING THE 1S-PSD (EQ. (10.7)) 271
10.1.6 COMPLETE FORMULAE USING THE 2S-PSD (EQ. (10.8)) 272
10.1.7 FORMULAE FOR VANISHING PRIMARY DAMPING
USING TH
E 2S-PSD (EQ. (10.8)) 272
10.1.8 SIMPLIFIED FORMULAE USING THE 2S-PSD (EQ. (10.8)) ...
. 273
10.2 VALIDATION 274
XVI CONTENTS
10.2.1 PRIMARY STIFFNESS 274
10.2.2 NATURAL FREQUENCY 275
10.2.3 DAMPING RATIO 275
10.3 PARAMETER SENSITIVITY ANALYSIS 276
10.3.1 STANDARD DEVIATION OF FORCE ON AXLE-BOX 276
10.3.2 STANDARD DEVIATION OF BODY ACCELERATION 277
10.3.3 STANDARD DEVIATION OF SECONDARY STROKE 278
10.3.4 OPTIMAL SECONDARY SUSPENSION DESIGN VARIABLES 279
10.4 CONCLUSION 283
11 OPTIMAL DESIG
N OF TH
E LAYOUT
OF RAILWAY PASSENGE
R VEHICLES
285
11.1 DESIGN AIMS AND RELATED OBJECTIVE FUNCTIONS 286
11.2 DESIGN VARIABLES T
O BE TUNED 288
11.3 CONSTRAINTS 288
11.4 OBJECTIVE FUNCTIONS 290
11.4.1 UNLOADED VEHICLE MASS/FULLY LOADED VEHICLE MASS 290
11.4.2 VEHICLE LENGTH/PAYLOAD 293
11.4.3 RIDE COMFORT 293
11.4.4 VEHICLE/TRACK DYNAMIC INTERACTION 293
11.4.5 THREE DEGREES OF FREEDOM MODEL 294
11.4.6 OTHER INDICES 296
11.5 ANALYSIS AND CHOICE OF PREFERRED OPTIMAL SOLUTIONS 296
11.5.1 INTER-CITY CARS 298
11.5.2 SUB-URBAN CARS 298
11.5.3 URBAN CARS 299
11.6 CONCLUSION 301
12 OPTIMAL DESIG
N OF HELICAL SPRING
303
12.1 FUNDAMENTALS OF OPTIMAL DESIGN OF SPRINGS 304
12.2 COMPOSITE TUBULAR SPRING MODELS 308
12.2.1 STRESS, STRAIN AND SPRING STIFFNESS 309
12.2.2 GLOBAL STABILITY 313
12.2.3 LOCAL STABILITY 313
12.2.4 VIBRATIONS 316
12.2.5 SPRING MATERIAL STRENGTH 317
12.3 MODEL VALIDATION 318
12.4 NUMERICAL APPLICATION 321
12.4.1 DESIGN AIMS AND RELATED OBJECTIVE FUNCTIONS 321
12.4.2 DESIGN VARIABLES T
O BE TUNED 322
12.4.3 CONSTRAINTS 323
12.4.4 FINDING OPTIMAL SOLUTIONS 324
12.4.5 ANALYSIS OF TH
E OPTIMAL SOLUTIONS 324
12.5. CONCLUSIONS 328
12.6 APPENDIX: ANALYTICAL EXPRESSION OF CRITICAL LOAD 329
CONTENTS XVII
13 INTERACTIV
E OPTIMISATIO
N OF A FLYWHEE
L
331
13.1 SYSTEM MODEL 332
13.2 OBJECTIVE FUNCTIONS 334
13.3 DESIGN VARIABLES 335
13.4 RESULTS 336
REFERENCES
343_
INDEX
355
|
| adam_txt |
G. MASTINU M. GOBBI C. MIANO
OPTIMAL DESIGN OF COMPLEX
MECHANICAL SYSTEMS
WITH APPLICATIONS TO VEHICLE ENGINEERING
WITH 161 FIGURES 62 TABLES
4Y SPRINGER
CONTENTS
PART I THEOR
Y
INTRODUCTIO
N T
O TH
E OPTIMA
L DESIG
N
OF COMPLE
X MECHANICA
L SYSTEM
S
3
1.1 ON THE OPTIMAL DESIGN OF COMPLEX SYSTEMS 3
1.2 FINDING TH
E PARETO-OPTIMAL SETS 12
1.2.1 EXHAUSTIVE METHOD 12
1.2.2 UNIFORMLY DISTRIBUTED SEQUENCES AND RANDOM SEARCH. . 14
1.2.3 GENETIC ALGORITHMS 15
1.2.4 COMPARISON OF BROADLY APPLICABLE METHODS
T
O SOLVE OPTIMISATION PROBLEMS 16
1.2.5 GLOBAL APPROXIMATION 16
1.2.6 MULTI-OBJECTIVE PROGRAMMING VIA NON-LINEAR
PROGRAMMING 19
1.2.7 ALGORITHMS TO SOLVE OPTIMISATION PROBLEMS
IN SCALAR FORM 21
1.3 UNDERSTANDING PARETO-OPTIMAL SOLUTIONS 21
ENGINEERIN
G DESIG
N AND OPTIMA
L DESIG
N
OF COMPLE
X MECHANICA
L SYSTEMS
: DEFINITION
S
25
2.1 ENGINEERING DESIGN 25
2.1.1 STAGES OF THE DESIGN PROCESS 25
2.1.2 CREATIVITY 27
2.2 OPTIMAL DESIGN OF COMPLEX MECHANICAL SYSTEMS 28
2.2.1 FUNDAMENTAL HYPOTHESIS 28
2.2.2 SINGLE- AND MULTI-CRITERIA OPTIMISATION 28
2.2.3 MULTI-CRITERIA OPTIMISATION (MCO) 28
2.2.4 MULTI-OBJECTIVE OPTIMISATION (MOO) 29
2.2.5 MULTI-OBJECTIVE PROGRAMMING (MOP) 29
2.3 COMPLEX SYSTEMS 30
2.4 SYSTEM MODELS 31
XII CONTENTS
2.5 SYSTEM PERFORMANCES, CRITERIA, OBJECTIVE FUNCTIONS 32
2.6 SYSTEM PARAMETERS
, DESIGN VARIABLES 33
2.7 CONSTRAINTS 33
2.8 SPACE OF DESIGN VARIABLES, SPACE OF OBJECTIVE FUNCTIONS 34
2.9 FEASIBLE DESIGN VARIABLES DOMAIN, DESIGN SOLUTION 34
2.9.1 CONFLICT 34
2.10 MULTI-OBJECTIVE PROGRAMMING (MOP) 34
2.10.1 NON-LINEAR PROGRAMMING (NLP)
AND CONSTRAINED MINIMISATION 34
2.10.2 MULTI-OBJECTIVE PROGRAMMING: DEFINITION 37
2.10.3 PARETO-OPTIMAL SOLUTIONS AND PARETO-OPTIMAL SET 38
2.10.4 IDEAL AND NADIR DESIGN SOLUTIONS 41
2.10.5 RELATED CONCEPTS 42
2.10.6 BASIC PROBLEMS AND CAPABILITIES
OF MULTI-OBJECTIVE OPTIMISATION 43
2.11 DECOMPOSITION OF DESIGN PROBLEMS 44
3 MULTI-OBJECTIV
E OPTIMISATIO
N
47
3.1 METHODS T
O SOLVE MULTI-OBJECTIVE PROGRAMMING (MOP)
PROBLEMS 47
3.2 PARETO-OPTIMAL SET GENERATION METHODS 48
3.3 GLOBAL SENSITIVITY ANALYSIS 50
3.3.1 GLOBAL SENSITIVITY ANALYSIS BASED
ON LINEAR REGRESSION METHODS 50
3.3.2 SOBOL METHOD 52
3.3.3 SPEARMAN RANK CORRELATION COEFFICIENT 53
3.3.4 GLOBAL SENSITIVITY VIA ARTIFICIAL NEURAL NETWORK 56
3.4 PARETO-OPTIMAL SET COMPUTATION 56
3.4.1 EXHAUSTIVE METHOD 57
3.4.2 LOW DISCREPANCY SEQUENCES 57
3.4.3 SELECTION OF TH
E PARETO-OPTIMAL SET 67
3.4.4 GENETIC ALGORITHMS 68
3.4.5 UNCONSTRAINED MINIMISATION 75
3.4.6 SIMPLEX METHOD 76
3.4.7 SEQUENTIAL UNCONSTRAINED MINIMISATION TECHNIQUES .
. 76
3.4.8 METHOD OF FEASIBLE DIRECTIONS, SEQUENTIAL QUADRATIC
PROGRAMMING 78
3.4.9 WEIGHTED SUM 79
3.4.10 CONSTRAINTS METHOD 80
3.5 DESIGN SYNTHESIS - CHOOSING A FINAL DESIGN SOLUTION 83
3.5.1 UTILITY FUNCTION 83
3.5.2 LEXICOGRAPHIC ORDERING 84
3.5.3 GOAL PROGRAMMING 85
3.5.4 PREFERENCE VIA TRAINED ARTIFICIAL NEURAL NETWORK 86
3.5.5 MIN-MAX METHODS 86
CONTENTS XIII
3.5.6 HIERARCHICAL OPTIMISATION METHOD 88
3.5.7 NORMAL-BOUNDARY INTERSECTION METHOD 88
3.6 INTERACTIVE METHODS 89
3.6.1 INTERACTIVE COMPUTATION OF TH
E PARETO-OPTIMAL
SOLUTIONS AND PARETO-OPTIMAL SET BOUNDARIES THROUGH
PARETO SENSITIVITY ANALYSIS 91
3.7 SYMBOLICAL DERIVATION OF PO SETS 95
3.7.1 THEOREMS OF MONOTONICITY (OPTIMISATION PROBLEMS
WITH CONSTRAINTS) 95
3.7.2 THEOREMS OF MONOTONICITY (OPTIMISATION PROBLEMS
WITHOUT CONSTRAINTS) 96
3.8 ILLUSTRATING TH
E PARETO-OPTIMAL SET 97
GLOBA
L APPROXIMATIO
N
99
4.1 GLOBAL APPROXIMATION TECHNIQUES 100
4.2 TRAINING DAT
A GENERATION 101
4.2.1 (FRACTIONAL) FACTORIAL DESIGNS 101
4.2.2 UNIFORMLY DISTRIBUTED SEQUENCES
AND ORTHOGONAL ARRAY 102
4.3 SELECTION OF TH
E GLOBAL APPROXIMATION MODEL 102
4.3.1 POLYNOMIAL LINEAR AND QUADRATIC INTERPOLATION 102
4.4 LEAST SQUARES REGRESSION POLYNOMIAL APPROXIMATION 104
4.5 KRIGING INTERPOLATING MODELS 106
4.6 ARTIFICIAL NEURAL NETWORKS 106
4.6.1 MULTI-LAYER PERCEPTRON NEURAL NETWORK 107
4.6.2 RADIAL BASIS FUNCTION NEURAL NETWORK 112
PART I
I APPLICATION
S
5 OPTIMA
L RID
E COMFORT AN
D ACTIV
E SAFET
Y
OF ROA
D VEHICLE
S
121
5.1 SYSTEM MODEL OF A PASSIVELY SUSPENDED VEHICLE 122
5.1.1 EQUATIONS OF MOTION AND RESPONSE T
O STOCHASTIC
EXCITATION 122
5.1.2 DERIVATION OF STANDARD DEVIATIONS IN ANALYTICAL FORM.
. 124
5.1.3 PARAMETER SENSITIVITY ANALYSIS 128
5.2 PASSIVELY SUSPENDED VEHICLE SYSTEM OPTIMISATION 132
5.2.1 PROBLEM FORMULATION 132
5.2.2 OPTIMAL PERFORMANCES AND SUSPENSION
DESIGN VARIABLES 132
5.3 SYSTEM MODEL OF AN ACTIVELY SUSPENDED ROAD VEHICLE 142
5.3.1 EQUATIONS OF MOTION AND RESPONSE T
O STOCHASTIC
EXCITATION 142
5.3.2 DERIVATION OF STANDARD DEVIATIONS IN ANALYTICAL FORM.
. 143
XIV CONTENTS
5.3.3 COMPARISON OF 1S-PSD AND 2S-PSD FORMULAE 146
5.3.4 VALIDATION PROBLEMS AND USEFULNESS
OF THE PRESENTED THEORY 146
5.4 ACTIVELY SUSPENDED VEHICLE SYSTEM OPTIMISATION 147
5.4.1 OPTIMAL PERFORMANCES AND SUSPENSION DESIGN VARIABLES 147
5.5 CONCLUSION 157
5.6 APPENDIX: TABULATED VALUES OF THE INTEGRAL FORM 158
6 OPTIMA
L HANDLIN
G AN
D ACTIV
E SAFETY OF ROA
D VEHICLE
S
159
6.1 SYSTEM MODEL 160
6.1.1 VEHICLE RESPONSE T
O A STEERING STEP INPUT:
LINEAR MODEL 162
6.1.2 VEHICLE RESPONSE T
O A STEERING STEP INPUT:
NON-LINEAR MODEL 165
6.1.3 OBJECTIVE FUNCTIONS 168
6.2 RESULTS OF THE OPTIMISATION 173
6.2.1 ANALYTICAL SOLUTION (LINEAR CASE) 174
6.2.2 NUMERICAL SOLUTIONS (LINEAR CASE) 179
6.2.3 NUMERICAL SOLUTION (NON-LINEAR CASE) 180
6.3 VALIDATION 182
6.3.1 VALIDATION OF THE MODEL 182
6.3.2 VALIDATION OF THE OPTIMISATION PROCESS 185
6.4 CONCLUSION 187
7 OPTIMAL DESIG
N OF TH
E TYRE-SUSPENSIO
N SYSTE
M
OF A RACIN
G CAR
191
7.1 SYSTEM MODEL 192
7.1.1 VEHICLE MODEL 192
7.1.2 TYRE MODEL 193
7.1.3 VALIDATION 193
7.2 DESIGN VARIABLES 194
7.2.1 SUSPENSION SYSTEM 196
7.2.2 TYRE CHARACTERISTIC 198
7.3 RUNNING SITUATIONS AND OBJECTIVE FUNCTIONS 199
7.3.1 STEADY-STATE TURNING 199
7.3.2 J-TURN 201
7.3.3 POWER ON-OFF WHILE STEERING 201
7.3.4 BRAKING INTO A BEND 202
7.3.5 PASSING OVER A KERB WHILE STEERING 202
7.4 SEARCH METHOD 203
7.4.1 REDUCTION OF OBJECTIVE FUNCTIONS 203
7.4.2 PARETO-OPTIMAL SOLUTIONS 203
7.5 RESULTS 205
/7.5.1 COMPARISON OF THE PERFORMANCES OF GLOBAL
APPROXIMATION METHODS 206
7.6 CONCLUSION 212
CONTENTS XV
8 INTEGRATE
D CONTROLS FOR TH
E IMPROVEMEN
T
OF RIDE
, COMFORT, HANDLIN
G AND ACTIV
E SAFETY
OF ROA
D VEHICLES
215
8.1 SYSTEM MODELS AND REFERENCE DRIVING SITUATIONS 216
8.1.1 SYSTEM MODELS 216
8.1.2 REFERENCE DRIVING SITUATIONS 216
8.2 NUMERICAL APPLICATION 223
8.2.1 FIRST ITERATION 223
8.2.2 SECOND (AND FINAL) ITERATION 232
8.3 CONCLUSIONS 243
9 OPTIMAL DESIG
N OF A DOUBLE-CON
E SYNCHRONISER
245
9.1 SYNCHRONISER SYSTEM MODEL 246
9.1.1 PHYSICAL MODEL 246
9.2 FORMULATION OF TH
E DESIGN PROBLEM FOR THE OPTIMISATION
OF A SYNCHRONISER 249
9.2.1 DESIGN VARIABLES 249
9.2.2 OBJECTIVE FUNCTIONS 249
9.2.3 CONSTRAINTS 251
9.3 METHOD FOR THE OPTIMAL DESIGN OF A SYNCHRONISER 253
9.3.1 FEASIBLE DESIGN VARIABLES DOMAIN 253
9.3.2 GLOBAL SENSITIVITY ANALYSIS 253
9.3.3 GLOBAL APPROXIMATION 255
9.3.4 QUASI-MONTE CARLO SEARCH 256
9.3.5 MULTI-OBJECTIVE OPTIMISATION 257
9.3.6 ROBUST DESIGN AND SYNTHESIS OF OPTIMAL DESIGN
SOLUTIONS 257
9.4 OPTIMAL DESIGN OF A SYNCHRONISER 258
9.5 CONCLUSION 260
10 OPTIMAL DESIG
N OF TH
E SUSPENSIO
N SYSTE
M OF RAILWAY
VEHICLES
263
10.1 SYSTEM MODEL 263
10.1.1 EQUATIONS OF MOTION AND RESPONSES TO STOCHASTIC
EXCITATION 263
10.1.2 DERIVATION OF STANDARD DEVIATIONS IN ANALYTICAL FORM. . 267
10.1.3 COMPLETE FORMULAE USING THE 1S-PSD (EQ. (10.7)) .
. 269
10.1.4 FORMULAE FOR VANISHING PRIMARY DAMPING USING
THE 1S-PSD (EQ. (10.7)) 270
10.1.5 SIMPLIFIED FORMULAE USING THE 1S-PSD (EQ. (10.7)) 271
10.1.6 COMPLETE FORMULAE USING THE 2S-PSD (EQ. (10.8)) 272
10.1.7 FORMULAE FOR VANISHING PRIMARY DAMPING
USING TH
E 2S-PSD (EQ. (10.8)) 272
10.1.8 SIMPLIFIED FORMULAE USING THE 2S-PSD (EQ. (10.8)) .
. 273
' 10.2 VALIDATION 274
XVI CONTENTS
10.2.1 PRIMARY STIFFNESS 274
10.2.2 NATURAL FREQUENCY 275
10.2.3 DAMPING RATIO 275
10.3 PARAMETER SENSITIVITY ANALYSIS 276
10.3.1 STANDARD DEVIATION OF FORCE ON AXLE-BOX 276
10.3.2 STANDARD DEVIATION OF BODY ACCELERATION 277
10.3.3 STANDARD DEVIATION OF SECONDARY STROKE 278
10.3.4 OPTIMAL SECONDARY SUSPENSION DESIGN VARIABLES 279
10.4 CONCLUSION 283
11 OPTIMAL DESIG
N OF TH
E LAYOUT
OF RAILWAY PASSENGE
R VEHICLES
285
11.1 DESIGN AIMS AND RELATED OBJECTIVE FUNCTIONS 286
11.2 DESIGN VARIABLES T
O BE TUNED 288
11.3 CONSTRAINTS 288
11.4 OBJECTIVE FUNCTIONS 290
11.4.1 UNLOADED VEHICLE MASS/FULLY LOADED VEHICLE MASS 290
11.4.2 VEHICLE LENGTH/PAYLOAD 293
11.4.3 RIDE COMFORT 293
11.4.4 VEHICLE/TRACK DYNAMIC INTERACTION 293
11.4.5 THREE DEGREES OF FREEDOM MODEL 294
11.4.6 OTHER INDICES 296
11.5 ANALYSIS AND CHOICE OF PREFERRED OPTIMAL SOLUTIONS 296
11.5.1 INTER-CITY CARS 298
11.5.2 SUB-URBAN CARS 298
11.5.3 URBAN CARS 299
11.6 CONCLUSION 301
12 OPTIMAL DESIG
N OF HELICAL SPRING
303
12.1 FUNDAMENTALS OF OPTIMAL DESIGN OF SPRINGS 304
12.2 COMPOSITE TUBULAR SPRING MODELS 308
12.2.1 STRESS, STRAIN AND SPRING STIFFNESS 309
12.2.2 GLOBAL STABILITY 313
12.2.3 LOCAL STABILITY 313
12.2.4 VIBRATIONS 316
12.2.5 SPRING MATERIAL STRENGTH 317
12.3 MODEL VALIDATION 318
12.4 NUMERICAL APPLICATION 321
12.4.1 DESIGN AIMS AND RELATED OBJECTIVE FUNCTIONS 321
12.4.2 DESIGN VARIABLES T
O BE TUNED 322
12.4.3 CONSTRAINTS 323
12.4.4 FINDING OPTIMAL SOLUTIONS 324
12.4.5 ANALYSIS OF TH
E OPTIMAL SOLUTIONS 324
12.5. CONCLUSIONS 328
12.6 APPENDIX: ANALYTICAL EXPRESSION OF CRITICAL LOAD 329
CONTENTS XVII
13 INTERACTIV
E OPTIMISATIO
N OF A FLYWHEE
L
331
13.1 SYSTEM MODEL 332
13.2 OBJECTIVE FUNCTIONS 334
13.3 DESIGN VARIABLES 335
13.4 RESULTS 336
REFERENCES
343_
INDEX
355 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Mastinu, Giampiero Gobbi, Massimiliano Miano, Carlo |
| author_facet | Mastinu, Giampiero Gobbi, Massimiliano Miano, Carlo |
| author_role | aut aut aut |
| author_sort | Mastinu, Giampiero |
| author_variant | g m gm m g mg c m cm |
| building | Verbundindex |
| bvnumber | BV022247410 |
| callnumber-first | T - Technology |
| callnumber-label | TA658 |
| callnumber-raw | TA658.8 |
| callnumber-search | TA658.8 |
| callnumber-sort | TA 3658.8 |
| callnumber-subject | TA - General and Civil Engineering |
| classification_rvk | UF 1500 ZO 4210 |
| classification_tum | VER 205f TEC 630f VER 029f |
| ctrlnum | (OCoLC)71336364 (DE-599)BVBBV022247410 |
| dewey-full | 624.1/7713 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 624 - Civil engineering |
| dewey-raw | 624.1/7713 |
| dewey-search | 624.1/7713 |
| dewey-sort | 3624.1 47713 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Maschinenbau / Maschinenwesen Physik Technik Bauingenieurwesen Verkehrstechnik Verkehr / Transport |
| discipline_str_mv | Maschinenbau / Maschinenwesen Physik Technik Bauingenieurwesen Verkehrstechnik Verkehr / Transport |
| edition | 1. Ed. |
| format | Book |
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| id | DE-604.BV022247410 |
| illustrated | Illustrated |
| index_date | 2024-07-02T16:38:13Z |
| indexdate | 2024-07-09T20:53:17Z |
| institution | BVB |
| isbn | 3540343547 9783540343547 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-015458247 |
| oclc_num | 71336364 |
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| owner_facet | DE-573 DE-706 DE-91G DE-BY-TUM DE-83 |
| physical | XLIV, 359 S. Ill., graph. Darst. 235 mm x 155 mm |
| publishDate | 2006 |
| publishDateSearch | 2006 |
| publishDateSort | 2006 |
| publisher | Springer Berlin |
| record_format | marc |
| spelling | Mastinu, Giampiero Verfasser aut Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering Giampiero Mastinu ; Massimiliano Gobbi ; Carlo Miano 1. Ed. Berlin Springer Berlin 2006 XLIV, 359 S. Ill., graph. Darst. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Experimental design Optimal designs (Statistics) Structural optimization Vehicles Design and construction Strukturoptimierung (DE-588)4183811-7 gnd rswk-swf Fahrzeug (DE-588)4016320-9 gnd rswk-swf Mehrkörpersystem (DE-588)4038390-8 gnd rswk-swf Konstruktionselement (DE-588)4165100-5 gnd rswk-swf Mehrkörpersystem (DE-588)4038390-8 s Strukturoptimierung (DE-588)4183811-7 s DE-604 Fahrzeug (DE-588)4016320-9 s Konstruktionselement (DE-588)4165100-5 s Gobbi, Massimiliano Verfasser aut Miano, Carlo Verfasser aut text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2795621&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015458247&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Mastinu, Giampiero Gobbi, Massimiliano Miano, Carlo Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering Experimental design Optimal designs (Statistics) Structural optimization Vehicles Design and construction Strukturoptimierung (DE-588)4183811-7 gnd Fahrzeug (DE-588)4016320-9 gnd Mehrkörpersystem (DE-588)4038390-8 gnd Konstruktionselement (DE-588)4165100-5 gnd |
| subject_GND | (DE-588)4183811-7 (DE-588)4016320-9 (DE-588)4038390-8 (DE-588)4165100-5 |
| title | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering |
| title_auth | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering |
| title_exact_search | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering |
| title_exact_search_txtP | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering |
| title_full | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering Giampiero Mastinu ; Massimiliano Gobbi ; Carlo Miano |
| title_fullStr | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering Giampiero Mastinu ; Massimiliano Gobbi ; Carlo Miano |
| title_full_unstemmed | Optimal Design of Complex Mechanical Systems With Applications to Vehicle Engineering Giampiero Mastinu ; Massimiliano Gobbi ; Carlo Miano |
| title_short | Optimal Design of Complex Mechanical Systems |
| title_sort | optimal design of complex mechanical systems with applications to vehicle engineering |
| title_sub | With Applications to Vehicle Engineering |
| topic | Experimental design Optimal designs (Statistics) Structural optimization Vehicles Design and construction Strukturoptimierung (DE-588)4183811-7 gnd Fahrzeug (DE-588)4016320-9 gnd Mehrkörpersystem (DE-588)4038390-8 gnd Konstruktionselement (DE-588)4165100-5 gnd |
| topic_facet | Experimental design Optimal designs (Statistics) Structural optimization Vehicles Design and construction Strukturoptimierung Fahrzeug Mehrkörpersystem Konstruktionselement |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=2795621&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015458247&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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