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| موضوع: كتاب Mechanical Design Optimization Using Advanced Optimization Techniques الإثنين 01 مايو 2023, 2:41 am | |
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أخواني في الله أحضرت لكم كتاب Mechanical Design Optimization Using Advanced Optimization Techniques R. Venkata Rao , Vimal J. Savsani
و المحتوى كما يلي :
Contents 1 Introduction 1 2 Advanced Optimization Techniques . 5 2.1 Genetic Algorithm 6 2.1.1 Selection . 6 2.1.2 Crossover 7 2.1.3 Mutation . 7 2.2 Artificial Immune Algorithm . 8 2.3 Differential Evolution 10 2.4 Biogeography-Based Optimization . 11 2.4.1 Migration 12 2.4.2 Mutation . 12 2.5 Particle Swarm Optimization . 14 2.5.1 Modifications in PSO 16 2.6 Artificial Bee Colony Algorithm 17 2.6.1 Modifications in ABC . 19 2.7 Harmony Elements Algorithm 20 2.7.1 Modifications in HEA . 20 2.8 Hybrid Algorithms 23 2.8.1 HPABC . 24 2.8.2 HBABC . 25 2.8.3 HDABC . 26 2.8.4 HGABC . 27 2.9 Shuffled Frog Leaping Algorithm . 28 2.10 Grenade Explosion Algorithm 29 References 32 ix3 Mechanical Design Optimization Using the Existing Optimization Techniques . 35 3.1 Description of Different Mechanical Design Optimization Problems . 35 3.1.1 Example 1: Optimization of a Gear Train 35 3.1.2 Example 2: Optimization of a Radial Ball Bearing 39 3.1.3 Example 3: Optimization of a Belleville Spring 44 3.1.4 Example 4: Optimization of a Multiple Disc Clutch Brake 46 3.1.5 Example 5: Optimization of a Robot Gripper . 47 3.1.6 Example 6: Optimization of a Hydrodynamic Thrust Bearing . 49 3.1.7 Example 7: Discrete Optimization of a Four Stage Gear Train . 51 3.2 Applications of Advanced Optimization Techniques to Different Design Optimization Problems of Mechanical Elements 55 3.2.1 Example 1: Optimization of Gear Train . 55 3.2.2 Example 2: Optimization of Radial Ball Bearing . 57 3.2.3 Example 3: Optimization of Belleville Spring . 59 3.2.4 Example 4: Optimization of Multiple Disc Clutch Brake 60 3.2.5 Example 5: Optimization of a Robotic Gripper 61 3.2.6 Example 6: Optimization of a Hydrostatic Thrust Bearing . 62 3.2.7 Example 7: Discrete Optimization of a Four Stage Gear Train . 63 References 67 4 Applications of Modified Optimization Algorithms to the Unconstrained and Constrained Problems 69 4.1 Unconstrained Benchmark Functions (BM-UC) 69 4.2 Constrained Benchmark Functions (BM-C) . 72 4.3 Additional Mechanical Element Design Optimization Problems (MD) 87 4.3.1 Example 8: Design of Pressure Vessel 87 4.3.2 Example 9: Design of Welded Beam . 88 4.3.3 Example 10: Design of Tension/Compression Spring . 90 4.3.4 Example 11: Design of a Speed Reducer 91 4.3.5 Example 12: Design of Stiffened Cylindrical Shell . 92 4.3.6 Example 13: Design of Step Cone Pulley 97 4.3.7 Example 14: Design of Screw Jack 98 4.3.8 Example 15: Design of C-Clamp 100 4.3.9 Example 16: Design of Hydrodynamic Bearing 101 x Contents4.3.10 Example 17: Design of Cone Clutch . 103 4.3.11 Example 18: Design of Cantilever Support . 104 4.3.12 Example 19: Design of Hydraulic Cylinder . 109 4.3.13 Example 20: Design of Planetary Gear Train . 110 4.4 Applications of Modified PSO 113 4.5 Applications of Modified ABC . 115 4.6 Applications of Modified HEA . 116 References 119 5 Applications of Hybrid Optimization Algorithms to the Unconstrained and Constrained Problems 123 5.1 Applications of Hybrid Optimization Algorithms . 126 6 Development and Applications of a New Optimization Algorithm 133 6.1 Teaching–Learning-Based Optimization . 134 6.1.1 Teacher Phase . 134 6.1.2 Learner Phase . 135 6.2 Demonstration of TLBO for Optimization 137 6.3 Comparison of TLBO with Other Optimization Techniques . 140 6.4 Implementation of TLBO for the Optimization of Unconstrained Problems 140 6.4.1 Experiment 1 143 6.4.2 Experiment 2 144 6.4.3 Experiment 3 145 6.4.4 Experiment 4 146 6.4.5 Experiment 5 148 6.4.6 Experiment 6 149 6.5 Implementation of TLBO for the Optimization of Constrained Benchmark Functions . 151 6.5.1 Experiment 7 151 6.5.2 Experiment 8 153 6.5.3 Experiment 9 154 6.6 Implementation of TLBO for the Design Optimization of Mechanical Elements 154 6.6.1 Experiment 10 . 154 6.6.2 Experiment 11 . 157 6.6.3 Experiment 12 . 159 6.7 Implementation of TLBO for the Real Parameter Optimization 163 6.7.1 Experiment 1 163 6.7.2 Experiment 2 165 6.7.3 Experiment 3 167 References 193 Contents xi7 Design Optimization of Selected Thermal Equipment Using Advanced Optimization Techniques 195 7.1 Design Optimization of Thermoelectric Cooler 195 7.1.1 Thermal Modeling of Two-Stage TECs . 197 7.1.2 Multi-Objective Optimization and Formulation of Objective Functions . 200 7.1.3 Application Example of a Two-Stage TEC . 201 7.2 Design Optimization of Shell and Tube Heat Exchanger Using Shuffled Frog Leaping Algorithm . 207 7.2.1 Mathematical Model . 214 7.2.2 Case Study . 219 7.3 Design Optimization of Heat Pipe Using Grenade Explosion Algorithm 223 7.3.1 Case Study . 226 References 228 8 Conclusions . 231 Appendix 1: Additional Demonstrative Examples Solved by TLBO Algorithm . 235 Appendix 2: Sample Codes 295 Authors’ Biographies . 317 Index 319 Index A Ackley function, 270 Artificial bee colony, 2, 5, 17, 19, 24, 32, 33, 86, 87, 89, 119, 120, 125, 144, 192, 232 Artificial immune algorithm, 2, 5, 8, 9 B Belleville spring, 35, 44, 45, 59, 60, 128, 129, 231 Biogeography-based optimization, 5, 11, 13, 26, 33, 119 C Cantilever support, 103, 106, 107, 113, 117, 128, 129, 159, 160 C-clamp, 99, 106, 107, 113, 117, 128, 129, 159, 160 Cone clutch, 102, 103, 106, 107, 113, 117, 128, 129, 159, 160 Constrained benchmark functions, 64, 71, 72, 74, 76, 78, 80, 82, 84, 86, 105, 111, 112, 114–116, 118, 126, 127, 130, 152, 153, 155, 156, 158, 163, 164, 174, 176, 178, 184, 188, 231 D Differential evolution, 2, 5, 10, 11, 24, 26, 27, 33, 86, 87, 89, 119, 120, 152, 155, 191, 192, 194, 209, 228 F Four stage gear train, 35, 51 G Gear train, 35, 51, 55, 56, 63, 106, 107, 109, 113, 117, 128, 129, 159, 160, 231 Genetic algorithm, 2, 5–7, 15, 24, 27, 28, 32, 33, 40, 55, 67, 118, 119, 125, 132, 152, 192, 196, 209–212, 228, 229, 232 Grenade explosion algorithm, 29, 31, 225, 227 Griewank function, 127, 144, 147 H Harmony elements algorithm, 20, 21, 23, 32 Heat pipe, 223–227, 229 Heat transfer, 204, 206, 208–212, 214–217, 220–223, 225, 227–229 Himmelblau function, 286 HGABC, 24, 27, 28, 125–130, 149–151, 155, 156, 159, 160, 232 HPABC, 24, 25, 125–130, 149–151, 155, 156, 159, 160, 232 HBABC, 24–26, 125, 126–130, 149–151, 155, 156, 159, 160, 232 HDABC, 24, 26, 27, 125–130, 149, 150, 151, 155, 156, 158–162, 232, 233 Hybrid algorithms, 2, 3, 23–25, 27, 118, 122, 127, 130, 149, 153, 158, 232, 233 Hydraulic cylinder, 106–108, 113, 117, 128, 129, 159, 160, 231 H (cont.) Hybrid biogeography-based artificial bee colony algorithm, 24, 126 Hybrid differential evolution based artificial bee colony algorithm, 24, 126 Hybrid genetic algorithm based artificial bee colony algorithm, 24, 126 Hybrid particle swarm based artificial bee colony algorithm (HPABC), 24, 126 Hydrodynamic thrust bearing, 49 Hydrostatic thrust bearing, 35, 49, 62 M Mechanical design, 1–3, 5, 35–56, 58, 60, 62, 64, 66–68, 86, 106, 107, 113–115, 117–119, 122, 128–130, 132, 153, 155, 157–161, 165–167, 193, 195, 231, 232 Modified ABC, 64, 114, 150 Modified HEA, 64, 115, 116, 118, 232 Modified PSO, 32, 64, 112, 114, 119, 150, 232 Multi-objective optimization, 2, 44, 58, 59, 193, 197, 200, 203, 210, 228, 229 Multiple disc clutch brake, 46, 47, 60 O Objective function, 1, 5, 8–13, 16, 18, 19, 21, 23, 29, 35, 36, 39–42, 44, 56–64, 66, 71, 91, 93, 101–103, 137–140, 150, 153, 165–167, 195, 197, 200, 201, 203, 208, 210–212, 218, 226 P Particle swarm optimization, 2, 5, 14, 15, 17, 24, 25, 28, 32, 33, 86, 87, 89, 90, 119, 120, 143, 155, 192, 229 Penalty1 function, 278 Penalty2 function, 282 Planetary gear train, 109 Pressure drop, 206–209, 211, 212, 214, 217, 219, 226 Pressure vessel, 86, 87, 106, 107, 113, 117, 128, 129, 153, 156, 159, 160, 206 Q Quartic function, 112, 127, 158 R Radial ball bearing, 35, 39, 40, 57, 59, 231 Rastrigin function, 136, 144 Real parameter optimization, 162, 164, 166, 168, 170, 172, 174, 176, 178, 180, 182, 184, 186, 188, 190 Robot gripper, 2, 35, 47, 48, 61, 62, 67, 106, 107, 113, 117, 128, 129, 159, 160, 231 Rosenbrock function, 143, 145, 147 S Schwefel 1.2 function, 243 Schwefel 2.21 function, 247 Schwefel 2.22 function, 239 Schwefel 2.26 function, 263 Screw jack, 97, 98, 106, 107, 113, 117, 128, 129, 159, 160 Shell and tube heat exchanger, 204, 206, 209–212, 227–229 Shuffled frog leaping algorithm, 28, 29, 32, 204, 218 Speed reducer, 90, 106, 107, 113, 117, 128, 129, 153, 159, 160 Step-cone pulley, 97 Step function, 112, 127 Stiffened cylindrical shell, 91, 92, 120 T Thermoelectric cooler, 195, 197, 199, 201, 203, 228, 233 U Unconstrained benchmark functions, 3, 68–70, 104, 108, 112, 114, 115, 118, 122–125, 127, 130, 148, 149, 158, 231 W Welded beam, 87, 88, 106, 107, 113, 117, 128, 129, 153, 156, 159, 160
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