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E-raamat: Antenna Design by Simulation-Driven Optimization

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  • Formaat: PDF+DRM
  • Sari: SpringerBriefs in Optimization
  • Ilmumisaeg: 12-Feb-2014
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319043678
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Antenna Design by Simulation-Driven OptimizationSuurem pilt
  • Formaat: PDF+DRM
  • Sari: SpringerBriefs in Optimization
  • Ilmumisaeg: 12-Feb-2014
  • Kirjastus: Springer International Publishing AG
  • Keel: eng
  • ISBN-13: 9783319043678
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This Brief reviews a number of techniques exploiting the surrogate-based optimization concept and variable-fidelity EM simulations for efficient optimization of antenna structures. The introduction of each method is illustrated with examples of antenna design. The authors demonstrate the ways in which practitioners can obtain an optimized antenna design at the computational cost corresponding to a few high-fidelity EM simulations of the antenna structure. There is also a discussion of the selection of antenna model fidelity and its influence on performance of the surrogate-based design process. This volume is suitable for electrical engineers in academia as well as industry, antenna designers and engineers dealing with computationally-expensive design problems.
1 Introduction 1(4)
2 Antenna Design Using Electromagnetic Simulations 5(8)
2.1 Antenna Design Task as an Optimization Problem
5(2)
2.2 Gradient-Based Optimization Methods
7(2)
2.3 Derivative-Free Optimization Methods
9(1)
2.4 Metaheuristics and Global Optimization
10(2)
2.5 Challenges of Conventional Optimization Toward Design Using Surrogate Models
12(1)
3 Surrogate-Based Optimization 13(12)
3.1 Surrogate-Based Optimization Basics
13(2)
3.2 Surrogate Model Construction: Function Approximation and Physics-Based Surrogates
15(8)
3.2.1 Approximation-Based Surrogate Models
16(4)
3.2.2 Physics-Based Surrogate Models
20(3)
3.3 Exploration Versus Exploitation
23(2)
4 Methodologies for Variable-Fidelity Optimization of Antenna Structures 25(20)
4.1 Antenna-Specific Challenges of Surrogate-Based Optimization
25(1)
4.2 Space Mapping
26(5)
4.2.1 Space Mapping Concept
26(1)
4.2.2 Aggressive Space Mapping
27(1)
4.2.3 Parametric Space Mapping
28(2)
4.2.4 Space Mapping with Response Surface Approximations
30(1)
4.3 Shape-Preserving Response Prediction
31(4)
4.3.1 SPRP Concept
31(1)
4.3.2 SPRP Formulation
32(1)
4.3.3 Illustration Example
33(1)
4.3.4 Practical Issues
34(1)
4.4 Adaptive Response Correction
35(2)
4.5 Manifold Mapping
37(2)
4.6 Adaptively Adjusted Design Specifications
39(2)
4.7 Multi-fidelity Design Optimization
41(4)
5 Low-Fidelity Antenna Models 45(8)
5.1 Low-Fidelity Models in Simulation-Driven Optimization
45(2)
5.2 Coarse-Discretization Antenna Models as a Basis for Low-Fidelity Antenna Models
47(2)
5.3 Additional Simplifications of Low-Fidelity Antenna Models
49(3)
5.4 Need for Automated Selection of Model Fidelity
52(1)
6 Simulation-Based UWB Antenna Design 53(8)
6.1 UWB Monopole Matching with Manifold Mapping and Kriging
53(2)
6.2 UWB Dipole
55(1)
6.3 UWB Vivaldi Antenna
56(3)
6.4 Discussion
59(2)
7 Optimization of Dielectric Resonator Antennas 61(12)
7.1 DRA with a Substrate-Integrated Cavity
61(5)
7.2 Suspended Brick DRA
66(2)
7.3 Optimization of DRA for Two Installation Scenarios
68(4)
7.4 Conclusions
72(1)
8 Surrogate-Based Optimization of Microstrip Broadband Antennas 73(10)
8.1 Wideband Microstrip Antenna
73(3)
8.2 Double-Ring Antenna
76(3)
8.3 Microstrip Antenna with U-Shape Parasitic Patches
79(1)
8.4 Conclusions
80(3)
9 Simulation-Driven Antenna Array Optimization 83(10)
9.1 5 x 5 Antenna Array
83(4)
9.2 Optimization of a 7 x 7 Array Using Analytical and Discrete Models
87(3)
9.3 Discussion and Conclusion
90(3)
10 Antenna Optimization with Surrogates and Adjoint Sensitivities 93(12)
10.1 Surrogate-Based Optimization with Adjoint Sensitivity
94(1)
10.1.1 Generic Surrogate-Based Optimization Algorithm
94(1)
10.1.2 Robustness of the SBO Process
94(1)
10.2 SBO with First-Order Taylor Model and Trust Regions
95(4)
10.2.1 Planar Inverted-F Antenna (PIFA)
96(2)
10.2.2 Wideband Hybrid Antenna
98(1)
10.3 SBO with Space Mapping and Manifold Mapping
99(4)
10.3.1 Surrogate Construction Using SM and Sensitivity Data
99(1)
10.3.2 Surrogate Construction Using MM and Sensitivity Data
100(1)
10.3.3 Fast Parameter Extraction and Surrogate Model Optimization
101(1)
10.3.4 UWB Monopole Optimization Using SM and MM Surrogates
101(2)
10.4 SPRP with Adjoint Sensitivity
103(1)
10.5 Discussion and Conclusion
104(1)
11 Simulation-Based Multi-objective Antenna Optimization with Surrogate Models 105(14)
11.1 Multi-objective Antenna Design Using Surrogate Modeling and Evolutionary Algorithms
106(2)
11.1.1 Multi-objective Antenna Design Problem
106(1)
11.1.2 Optimization Algorithm
106(2)
11.2 Application: A UWB Monopole
108(4)
11.2.1 UWB Monopole: Geometry and Problem Statement
108(1)
11.2.2 UWB Monopole: Results
108(4)
11.3 Application: A Planar Yagi Antenna
112(3)
11.3.1 Planar Yagi Antenna: Geometry, Models, and Problem Statement
112(1)
11.3.2 Planar Yagi Antenna: Surrogate Models
113(2)
11.3.3 Planar Yagi Antenna: Results
115(1)
11.4 Summary
115(4)
12 Practical Aspects of Surrogate-Based Antenna Design: Selecting Model Fidelity 119(6)
12.1 Selecting Model Fidelity: Speed Versus Accuracy Trade-Offs
119(1)
12.2 Case Study 1: Design of Broadband Slot Antenna Using Output Space Mapping
120(1)
12.3 Case Study 2: Model Management for Hybrid DRA
121(2)
12.4 Discussion and Recommendations
123(2)
13 Discussion and Recommendations 125(6)
13.1 SBO Methods Highlights
125(3)
13.2 Discussion and Recommendations
128(1)
13.3 Prospective Look
129(2)
References 131(8)
Index 139
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