Numerical Optimization in Engineering and Sciences (eBook)

Contents 6
About the Editors 11
Hydro-Chemistry for the Analysis of Sub-surface Water Quality in North-Eastern Haryana: A Fast-Urbanizing Region 12
1 Introduction 13
2 Materials and Methods 14
2.1 Region of Study 14
2.2 Methodology 16
3 Results and Discussion 16
3.1 Hydro-Chemical Indices 17
3.2 Hydro-Chemical Process Assessment 18
4 Quality of Water 20
4.1 Quality of Domestic Water 20
4.2 Total Hardness (TH) 21
4.3 Base-Exchange Index (BEI) 22
5 Conclusions 22
References 23
Numerical Optimization of Pile Foundation in Non-liquefiable and Liquefiable Soils 25
1 Introduction 25
1.1 Topology Optimization of Pile Foundation 26
1.2 Cost Optimization of Pile Foundation with a Raft 26
2 Topology Optimization of Pile Foundation 27
2.1 FE Modelling 28
2.2 Results and Discussion 29
3 Cost Optimization of a Pile Foundation with Raft 31
3.1 Objective Function and Constraints of the Optimization Algorithm 31
3.2 Results and Discussion 32
4 Conclusion 32
References 33
Nonlinear Regression for Identifying the Optimal Soil Hydraulic Model Parameters 34
1 Introduction 34
2 Materials and Methods 35
2.1 Analytical Models 35
2.2 Experimental Data 36
2.3 Nonlinear Regression 36
2.4 HYDRUS 37
3 Results and Discussion 37
3.1 Soil Moisture Characteristics 37
3.2 Soil Hydraulic Parameter Estimation 38
3.3 SMC Comparison 40
4 Conclusion 42
Appendix 42
References 43
Assessment of Microphysical Parameterization Schemes on the Track and Intensity of Titli Cyclone Using ARW Model 44
1 Introduction 44
2 Data and Methodology 45
2.1 ARW Model 45
3 Data Used 46
4 Numerical Experiments 46
5 Results and Discussions 47
6 Sensitivity of Microphysics Parameterization Schemes 47
7 Track and Intensity Errors 48
8 Summary and Conclusions 50
References 51
Topology Optimization of Concrete Dapped Beams Under Multiple Constraints 52
1 Introduction 52
2 Modeling of Dapped End Beams 53
3 Formulation of Topology Optimization Problems 54
4 Results and Discussion 55
4.1 Problem 1 56
4.2 Problem 2 57
4.3 Problem 3 58
4.4 Problem4 59
5 Conclusions 59
References 60
Selecting Optimized Mix Proportion of Bagasse Ash Blended Cement Mortar Using Analytic Hierarchy Process (AHP) 61
1 Introduction 61
2 Optimization Methodology 63
3 Methodology for Optimization of Bagasse Ash Blended Cement Mortar 65
4 Results and Discussions 66
4.1 Generating Pair-Wise Comparison Matrix 66
4.2 Sub-criteria Weights 66
4.3 Finding Consistency Ratio 68
4.4 Normalized Weights and Ranking 69
5 Conclusion 69
References 70
Regional Optimization of Global Climate Models for Maximum and Minimum Temperature 71
1 Introduction 71
2 Study Area 72
3 Observed and Climate Data 72
4 Methodology 73
4.1 Statistical Metrics 73
5 Results and Discussion 74
5.1 Analysis of Maximum Temperature 75
5.2 Analysis of Minimum Temperature 75
6 Conclusion 78
References 78
Numerical Optimization of Settlement in Geogrid Reinforced Landfill Clay Cover Barriers 80
1 Introduction 80
2 Materials Used 82
2.1 Soil 82
2.2 Geogrids 83
3 Experimental Testing Procedure 84
4 Results and Discussion 84
4.1 Effect of Number of Layers of Geogrids 84
4.2 Effect of Type of Geogrid 85
5 Regression Analysis 86
6 Conclusion 88
References 88
Optimization of Bias Correction Methods for RCM Precipitation Data and Their Effects on Extremes 90
1 Introduction 91
2 Materials and Methodology 92
2.1 Bias Correction Methods 92
2.2 Evaluation Methodology 94
3 Results 94
4 Conclusion 97
References 97
Regional Optimization of Existing Groundwater Network Using Geostatistical Technique 99
1 Introduction 100
2 Study Area 101
3 Methodology 101
3.1 Geostatistical Method 101
3.2 Cross-Validation 102
3.3 Thematic Maps Preparation 103
3.4 Estimating Optimum Observation Wells 103
4 Results and Discussions 104
4.1 Cross-Validation of GWL Fluctuations 104
4.2 Multi-parameter Impact on GLFs 104
4.3 GLFs with Reference to Geological Features 105
4.4 GLFs with Reference to Lineaments 105
4.5 GLFs with Reference to Groundwater Recharge 109
4.6 Optimization 109
5 Conclusion 111
References 111
Water Quality Analysis Using Artificial Intelligence Conjunction with Wavelet Decomposition 113
1 Introduction 114
2 Data Collection/Assessment 115
3 Mathematical Prototyping 116
3.1 Wavelet Analysis 116
3.2 Least Squares Support Vector Regression (LSSVR) 120
3.3 Wavelet LSSVR Prototype 120
4 Simulation Errors 122
4.1 Root-Mean-Square Error (RMSE) 122
4.2 Coefficient of Determination (R2) 122
4.3 Mean Absolute Error (MAE) 122
5 Results and Discussions 123
6 Conclusion 124
References 129
Performance Evaluation of Line of Sight (LoS) in Mobile Ad hoc Networks 130
1 Introduction 130
2 Literature Survey 131
3 Methodology 133
3.1 Two Host Communicative Wirelessly 133
3.2 Adding More Nodes and Decreasing the Communication Range 134
3.3 Establishment of Static Routing 134
3.4 Power Consumption 135
3.5 Configuring Node Movements 135
3.6 Configuring ad hoc Routing (AODV) 136
3.7 Adding Obstacles to the Environment 136
3.8 Changing to a More Realistic Radio Model 137
3.9 Configuring a More Accurate Path Loss Model 137
3.10 Introducing Antenna Gain 138
4 Result Analysis 138
5 Conclusion 143
References 143
Activeness Based Propagation Probability Initializer for Finding Information Diffusion in Social Network 145
1 Introduction 145
2 Background 146
2.1 Research Problem 146
3 Activeness Based Propagation Probability Initializer (APPI) 147
3.1 Activeness Value Finder 147
3.2 Propagation Probability Initializer 148
4 Experimental Results and Discussion 148
4.1 Implementation 148
4.2 Results for Synthetic Network 149
4.3 Real-World Network 150
5 Conclusion and Future Work 150
References 151
Solving Multi-attribute Decision-Making Problems Using Probabilistic Interval-Valued Intuitionistic Hesitant Fuzzy Set and Particle Swarm Optimization 152
1 Introduction 152
2 Preliminaries 153
3 Proposed Algorithm 156
4 Numerical Example 157
5 Conclusion 160
References 160
Assessment of Stock Prices Variation Using Intelligent Machine Learning Techniques for the Prediction of BSE 162
1 Introduction 162
2 Methodology 163
2.1 Data Collection 163
2.2 M5 Prime Regression Tree (M5’) 164
2.3 Multivariate Adaptive Regression Splines (MARS) 164
3 Results and Discussions 164
4 Classification and Regression Tree (CART) 165
5 Conclusion 168
References 169
Short-Term Electricity Load Forecast Using Hybrid Model Based on Neural Network and Evolutionary Algorithm 170
1 Introduction 170
2 Background Details 171
3 Short-Term Electricity Load Forecast 172
4 Experiments and Result Analysis 174
5 Conclusion 178
References 178
Diagnostics Relevant Modeling of Squirrel-Cage Induction Motor: Electrical Faults 180
1 Introduction 180
2 Extended State-Space Model of SCIM 181
2.1 SCIM Models 182
2.2 Key Parameters for SCIM Models 184
3 Squirrel-Cage Induction Motor State Estimation Using Extended Kalman Filter and Discriminatory Ability Index for Model-Based Fault Diagnosis 185
4 Main Simulation Results and Observations 185
4.1 Stator Inter-Turn Fault and Rotor Inter-Turn Fault 185
4.2 Robustness to Parameter Variations 188
5 Conclusion 189
Appendix 190
References 191
Comparative Study of Perturb & Observe (P&
1 Introduction 193
2 Solar Power Generation 194
3 Maximum Power Point Tracking (MPPT) Algorithm 195
4 Simulation Result: Comparison and Discussion 197
5 Conclusion 199
References 200
Conceptualization of Finite Capacity Single-Server Queuing Model with Triangular, Trapezoidal and Hexagonal Fuzzy Numbers Using ?-Cuts 202
1 Introduction 202
2 Essential Ideas and Definitions 203
2.1 Fuzzy Number [5] 203
2.2 ?-Cut [5] 203
2.3 Triangular Fuzzy Number [8] 203
2.4 Trapezoidal Fuzzy Number [9] 204
2.5 Hexagonal Fuzzy Number [10] 204
2.6 Arithmetic for Interval Analysis [12] 204
3 The Documentations and Suspicions 205
3.1 Suspicions 205
3.2 Documentations 205
4 Formulation of Proposed Lining Miniature 206
5 Solution Approach 206
6 Numerical Illustrations 207
7 Comparison of Triangular, Trapezoidal and Hexagonal Fuzzy Numbers at Various ? Values 210
8 Results and Discussions 211
9 Limitations of the Proposed Model 212
10 Conclusion 212
References 212
A Deteriorating Inventory Model with Uniformly Distributed Random Demand and Completely Backlogged Shortages 214
1 Introduction 214
2 Documentations and Assumptions 216
2.1 Notations 216
2.2 Assumptions 216
3 Mathematical Model 217
4 Algorithm 219
5 Numerical Examples 220
6 Post-Optimal Analysis 220
7 Observations 220
8 Conclusion 221
References 224
Analysis of M/EK/1 Queue Model in Bulk Service Environment 225
1 Introduction 225
2 M/Ek/1 Model in Bulk Service Environment 226
3 Generating Function of the State Probabilities Based on Ambulance Capacity 229
4 Conclusion 230
References 230
Role of Consistency and Random Index in Analytic Hierarchy Process—A New Measure 232
1 Introduction 232
2 Study of Random Index Values 233
2.1 First Attempt to Estimate Random Index Values Using Cubic Function 233
2.2 Least Squares Cubic Function for ‘x’ and R.I(x) 233
2.3 Second Attempt to Evaluate Random Index Values by a New Measure 235
2.4 Least Squares Straight Line for ‘x’ and  bar?max 235
3 Illustrations 236
3.1 Comparison Matrix of Dimension ‘4’ 236
3.2 Comparison Matrix of Dimension ‘5’ 237
4 Limitations 237
5 Conclusion 237
References 238
Sensitivity Analysis Through RSAWM—A Case Study 239
1 Introduction 239
2 Methodology 240
2.1 Algorithm of RSAW Method 240
2.2 Sensitivity Analysis 240
3 Illustration 241
4 Ranks of the Alternatives by RSAWM 242
5 Changing the Weight of Criteria 242
5.1 Highest Ranked Criteria 243
5.2 Criteria at Random 243
5.3 Least Ranked Criteria 243
6 Conclusion 243
References 243
RSAWM for the Selection of All Round Excellence Award—An Illustration 245
1 Introduction 245
2 Methodology 246
2.1 Algorithm of RSAW Method 246
2.2 Sensitivity Analysis 246
3 Illustration 247
4 Ranks of the Alternatives by RSAWM 247
5 Changing the Weight of Criteria 247
5.1 Highest Ranked Criteria 252
5.2 Criteria at Random 252
5.3 Least Ranked Criteria 252
6 Conclusion 252
Appendix 1 252
Appendix 2 254
Appendix 3 255
References 262
Solving Bi-Level Linear Fractional Programming Problem with Interval Coefficients 263
1 Introduction 263
2 Preliminaries 264
2.1 Arithmetic Operations on Intervals 264
2.2 Variable Transformation Method 265
3 Problem Formulation 265
4 Proposed Method of Solution 266
5 Numerical Example 268
6 Conclusion 270
References 271
RBF-FD Based Method of Lines with an Optimal Constant Shape Parameter for Unsteady PDEs 272
1 Introduction 272
2 RBF-FD Based MOL for Unsteady PDEs 273
3 Optimal Shape Parameter 274
4 Validation 275
5 Conclusion 277
References 277
Parametric Accelerated Over Relaxation (PAOR) Method 279
1 Introduction 279
2 PAOR Method 280
3 Choice of the Parameters ?,r and ? 282
4 Numerical Examples 283
5 Conclusion 284
References 284
Solving Multi-choice Fractional Stochastic Transportation Problem Involving Newton's Divided Difference Interpolation 285
1 Introduction 285
2 Problem Statement 286
3 Solution Methodology 287
3.1 Newton's Divided Difference Interpolating Polynomial for Multi-choice Parameters 287
3.2 Conversion of Probabilistic Constraints 289
4 Numerical Example 291
5 Results and Discussion 293
6 Conclusion 293
References 293
On Stability of Multi-quadric-Based RBF-FD Method for a Second-Order Linear Diffusion Filter 295
1 Introduction 295
2 An RBF-FD Scheme for Unsteady Problems 296
3 Linear Diffusion Filter 297
3.1 Stability of RBF-FD Scheme 298
4 Conclusion 300
References 301
Portfolio Optimization Using Particle Swarm Optimization and Invasive Weed Optimization 302
1 Introduction 302
2 Preliminaries 303
2.1 Risk–Return Portfolio Analysis 303
2.2 Particle Swarm Optimization 304
2.3 Invasive Weed Optimization 305
3 Results and Discussions 305
4 Concluding Remarks 308
References 308
The Influence of Lewis Number on Natural Convective Nanofluid Flows in an Enclosure: Buongiorno’s Mathematical Model: A Numerical Study 310
1 Introduction 310
2 Mathematical Governing Equations 311
3 Numerical Method and Validation 313
4 Results and Discussion 314
5 Conclusion 320
References 320
Reliability Model for 4-Modular and 5-Modular Redundancy System by Using Markov Technique 323
1 Introduction 324
2 Reliability Modelling of a 4-Modular Redundancy System 325
2.1 At Least Two Modules Must Operate for Functioning of the System 325
2.2 At Least Three Modules Must Operate for Functioning of the System 327
3 Reliability Modelling of a 5-Modular Redundancy System 328
3.1 At Least Two Modules Must Operate for Functioning of the System 328
3.2 At Least Three Modules Must Operate for Functioning of the System 329
4 Numerical Results 330
5 Conclusion 332
References 332
An Improved Secant-Like Method and Its Convergence for Univariate Unconstrained Optimization 333
1 Introduction 333
2 An Improved Secant-Like Method 335
3 Numerical Test 337
4 Conclusion 339
References 339
Integrability Aspects of Deformed Fourth-Order Nonlinear Schrödinger Equation 340
1 Introduction 340
2 Lax Pair and Soliton Solutions of D4oNLS Equation 342
2.1 Lax Pair 342
2.2 Soliton Solutions 342
3 Conclusion 348
References 349
A New Approach for Finding a Better Initial Feasible Solution to Balanced or Unbalanced Transportation Problems 351
1 Introduction 351
2 Proposed Method 353
3 Numerical Illustration 355
4 Conclusion 359
References 360
Heat Transfer to Peristaltic Transport in a Vertical Porous Tube 362
1 Introduction 362
2 Mathematical Formulation 363
3 Analysis 365
4 Results and Discussion 367
5 Conclusion 370
References 370
Geometrical Effects on Natural Convection in 2D Cavity 371
1 Introduction 371
2 Governing Equations 372
3 Results and Discussion 373
4 Conclusion 376
References 377
Convection Dynamics of SiO2 Nanofluid 378
1 Introduction 379
2 Mathematical Modeling 379
2.1 Stability Analysis 382
3 Results and Discussions 383
4 Conclusion 385
References 386
Development of a Simple Gasifier for Utilization of Biomass in Rural Areas for Transportation and Electricity Generation 387
1 Introduction 388
2 Experimental Setup 389
3 Results and Discussions 390
4 Conclusion 391
References 391
Identification of Parameters in Moving Load Dynamics Problem Using Statistical Process Recognition Approach 393
1 Introduction 393
2 The Problem Definition 394
3 Statistical Process Recognition (SPR) Approach 396
4 Results and Discussions 398
5 Conclusion 399
References 399
TIG Welding Process Parameter Optimization for Aluminium Alloy 6061 Using Grey Relational Analysis and Regression Equations 400
1 Introduction 400
2 Experimental Work 402
2.1 Design of Experiments (DOE) 402
2.2 Specimen Preparation 404
2.3 Tensile Test 404
2.4 Hardness Test 405
2.5 Optimization Techniques 406
3 Results and Discussion 406
3.1 Grey Relational Analysis (GRA) 406
3.2 Regression Analysis 408
4 Conclusion 410
References 411
Mathematical Modeling in MATLAB for Convection Through Porous Medium and Optimization Using Artificial Bee Colony (ABC) Algorithm 413
1 Introduction 413
2 Mathematical Modeling 414
2.1 ABC Algorithm 415
3 Result and Discussion 415
3.1 Mathematical Modeling with Optimization Techniques 416
3.2 Iteration-Based Graph for Different Algorithms 417
4 Conclusion 419
References 421
Utility Theory Embedded Taguchi Optimization Method in Machining of Graphite-Reinforced Polymer Composites (GRPC) 422
1 Introduction 423
2 Literature Review 423
3 Experimental Details 424
3.1 Materials Used for Fabrication Work 425
3.2 Specification of CNC Vertical Machining Center 426
3.3 Equipment Used for Measuring Responses (Thrust and Torque) During Machining 427
3.4 Metal Removal Rate (MRR) 427
3.5 Surface Roughness (Ra) 428
4 Parametric Optimization: Utility Theory 428
5 Results and Discussions 430
6 Conclusion 431
References 432
Optimization of Micro-electro Discharge Drilling Parameters of Ti6Al4V Using Response Surface Methodology and Genetic Algorithm 433
1 Introduction 434
2 Exper?mentat?on Deta?ls 434
2.1 Work Piece, Tool Material and Dielectric Materials 434
3 Analysis of Variance 436
3.1 Estimation of Recast Layer Thickness, Change in Micro-Hardness Using ANOVA 436
3.2 Optimization Using Genetic Algorithm 437
4 Results and Discussions 439
5 Conclusion 440
References 440
Multi-response Optimization of 304L Pulse GMA Weld Characteristics with Application of Desirability Function 441
1 Introduction 441
2 Experimental Methodology 443
2.1 Fixing the Range of Independent Process Variables 443
2.2 Measurement of Weld Geometrical, Metallurgical and Mechanical Characteristics 444
2.3 Development of Predictive Model 444
2.4 Analysis of Variance for Developed Predictive Models 447
3 Optimization of Process Parameters/Responses with RSM-Based Desirability Approach 448
4 Effect of Preferred Process Variables on Desirability 450
5 Conclusion 451
References 451
Simulation Study on the Influence of Blank Offset in Deep Drawing of Circular Cups 453
1 Introduction 453
2 Tool Setup Design 454
3 Simulation Tests 455
4 Conclusion 459
References 460
PCA-GRA Coupled Multi-criteria Optimisation Approach in Machining of Polymer Composites 461
1 Introduction 461
1.1 Literature Review 462
2 Experimental Detail 463
3 Concept of GRA and PCA 465
4 Results and Discussions 468
5 Conclusion 470
References 471
FEA-Based Electrothermal Modeling of a Die-Sinker Electro Discharge Machining (EDM) of an Aluminum Alloy AA6061 472
1 Introduction 473
2 Numerical Modeling of EDM Process 474
3 Results and Discussions 476
3.1 Calculation of the Theoretical Material Removal Rate, MRRth (Mm3/Min) 476
3.2 Calculation of the Experimental Material Removal Rate, MRRexp (Mm3/Min) 479
4 Conclusion 481
References 482
Modeling of Material Removal Rate and Hole Circularity on Soda–Lime Glass for Ultrasonic Drilling 484
1 Introduction 484
2 Experimental Details 486
3 Methodology 488
4 Results and Discussions 489
5 Conclusion 493
References 494
Experimental Investigation on Chemical-Assisted AISI 52100 Alloy Steel Using MAF 496
1 Introduction 496
2 Experimental Detail 497
2.1 Work Material 497
2.2 Experimental Set-up 498
2.3 Selection of Process Parameters and Their Range 498
2.4 RSM for Parameter Design 498
2.5 Process Variables 500
3 Results and Discussions 501
3.1 Model Summary 502
3.2 Interactive Effects of Inputs Parameters on Surface Roughness 502
3.3 Single Optimisation Through Response Surface Methodology 504
4 Conclusion 505
References 505
Modeling for Rotary Ultrasonic Drilling of Soda Lime Glass Using Response Surface Methodology 506
1 Introduction 506
2 Experimental Details 507
2.1 Selection of Process Parameters and Their Range 508
2.2 RSM for Parameter Design 509
2.3 Process Variables 509
3 Results and Discussions 511
3.1 Mathematical Model 511
3.2 Effect of Process Parameters on MRR and Hole Circularity 512
4 Conclusion 515
References 515
Process Optimization of Digital Conjugate Surfaces: A Review 517
1 Introduction 517
1.1 Conjugate Surface Concept 518
2 Literature Review 520
3 Conclusion 523
References 523
Optimization of Wear Parameters of AA7150-TiC Nanocomposites by Taguchi Technique 525
1 Introduction 525
2 Materials and Methods 526
3 Results and Discussions 529
4 Conclusion 531
References 532
Influence of Pulse GMA Process Variables on Penetration Shape Factor of AISI 304L Welds 533
1 Introduction 533
2 Experimental Methodology 535
2.1 Fixing the Range of Independent Process Variables 535
2.2 Measurement of Weld Geometrical Features 536
3 Application of Analysis of Variance (ANOVA) 536
4 Validation of Results 539
5 Effect of Process Variables on WPSF 540
5.1 Direct Effect of Shielding Gas Flow Rate on WPSF 540
5.2 Direct Effect of Welding Current on WPSF 541
5.3 Direct Effect of Arc Voltage on WPSF 541
5.4 Interactive Effects Among Welding Current and Voltage on WPSF 541
5.5 Interactive Effects of Shielding Gas Flow Rate and Welding Current on WPSF 542
5.6 Interactive Effects of Arc Voltage and Shielding Gas Flow Rate on WPSF 543
6 Conclusion 543
References 545
Numerical Optimization of Trench Film Cooling Parameters Using Response Surface Approach 546
1 Introduction 546
2 Response Surface Approaches 547
2.1 Numerical and Experimental Details 548
3 Results and Discussions 549
4 Conclusion 551
References 552
Analysis of Low Molecular Proteins Obtained from Human Placental Extract Considered as New Strategic Biomaterial for Pulp-Dentinal Regeneration 553
1 Introduction 554
2 Experimental Procedure 555
3 Results and Discussions 556
3.1 Determination of pH of the Solution 557
3.2 Determination of Protein Concentration by Bradford Assay 557
3.3 Identification of Potential Proteins of Interest (Table 3) 558
4 Conclusion 560
References 561
Predictive Data Optimization of Doppler Collision Events for NavIC System 563
1 Introduction 563
2 DC Predictive Analysis Methods for NavIC 564
2.1 Moving Average Filter Method 564
3 Results and Discussions 566
4 Conclusion 568
References 568