Search
Search results for: MULTI-FIDELITY
-
Multi-fidelity robust aerodynamic design optimization under mixed uncertainty
PublicationThe objective of this paper is to present a robust optimization algorithm for computationally efficient airfoil design under mixed (inherent and epistemic) uncertainty using a multi-fidelity approach. This algorithm exploits stochastic expansions derived from the Non-Intrusive Polynomial Chaos (NIPC) technique to create surrogate models utilized in the optimization process. A combined NIPC expansion approach is used, where both...
-
Efficient Multi-Fidelity Design Optimization of Microwave Filters Using Adjoint Sensitivity
PublicationA simple and robust algorithm for computationally efficient design optimiza-tion of microwave filters is presented. Our approach exploits a trust-region (TR)-based algorithm that utilizes linear approximation of the filter response obtained using adjoint sensitivity. The algorithm is sequentially executed on a family of electromagnetic (EM)-simulated models of different fidelities, starting from a coarse-discretization one, and...
-
Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublicationIn this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional...
-
A Multi-Fidelity Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Optimization Problems
PublicationIntegrating data-driven surrogate models and simulation models of different accuracies (or fideli-ties) in a single algorithm to address computationally expensive global optimization problems has recently attracted considerable attention. However, handling discrepancies between simulation models with multiple fidelities in global optimization is a major challenge. To address it, the two major contributions of this paper include:...
-
Multi-Fidelity Local Surrogate Model for Computationally Efficient Microwave Component Design Optimization
PublicationIn order to minimize the number of evaluations of high-fidelity (“fine”) model in the optimization process, to increase the optimization speed, and to improve optimal solution accuracy, a robust and computational-efficient multi-fidelity local surrogate-model optimization method is proposed. Based on the principle of response surface approximation, the proposed method exploits the multi-fidelity coarse models and polynomial interpolation...
-
Improved-Efficacy EM-Based Antenna Miniaturization by Multi-Fidelity Simulations and Objective Function Adaptation
PublicationThe growing demands for integration of surface mount design (SMD) antennas into miniatur-ized electronic devices have been continuously imposing limitations on the structure dimen-sions. Examples include embedded antennas in applications such as on-board devices, picosatel-lites, 5G communications, or implantable and wearable devices. The demands for size reduction while ensuring a satisfactory level of the electrical and field...
-
Cost-Efficient EM-Driven Size Reduction of Antenna Structures by Multi-Fidelity Simulation Models
PublicationDesign of antenna systems for emerging application areas such as the Internet of Things (IoT), fifth generation wireless communications (5G), or remote sensing, is a challenging endeavor. In addition to meeting stringent performance specifications concerning electrical and field properties, the structure has to maintain small physical dimensions. The latter normally requires searching for trade-off solutions because miniaturization...
-
Multi-fidelity aerodynamic design trade-off exploration using point-by-point Pareto set identification
PublicationAerodynamic design is inherently a multi-objective optimization (MOO) problem. Determining the best possible trade-offs between conflicting aerodynamic objectives can be computationally challenging when carried out directly at the level of high-fidelity computational fluid dynamics simulations. This paper presents a computationally cheap methodology for exploration of aerodynamic design trade-offs. In particular, point-by-point...
-
Low-Cost Design Optimization of Microwave Passives Using Multi-Fidelity EM Simulations and Selective Broyden Updates
PublicationGeometry parameters of contemporary microwave passives have to be carefully tuned in the final stages of their design process to ensure the best possible performance. For reliability reasons, the tuning has to be to be carried out at the level of full-wave electromagnetic (EM) simulations. This is because traditional modeling methods are incapable of quantifying certain phenomena that may affect operation and performance of these...
-
Efficient Surrogate Modeling and Design Optimization of Compact Integrated On-Chip Inductors Based on Multi-Fidelity EM Simulation Models
PublicationHigh-performance and small-size on-chip inductors play a critical role in contemporary radio-frequency integrated circuits. This work presents a reliable surrogate modeling technique combining low-fidelity EM simulation models, response surface approximations based on kriging interpolation, and space mapping technology. The reported method is useful for the development of broadband and highly accurate data-driven models of integrated...
-
Accelerated Gradient-Based Optimization of Antenna Structures Using Multi-Fidelity Simulations and Convergence-Based Model Management Scheme
PublicationThe importance of numerical optimization has been steadily growing in the design of contemporary antenna structures. The primary reason is the increasing complexity of antenna topologies, [ a typically large number of adjustable parameters that have to be simultaneously tuned. Design closure is no longer possible using traditional methods, including theoretical models or supervised parameter sweeping. To ensure reliability, optimization...
-
Expedited Machine-Learning-Based Global Design Optimization of Antenna Systems Using Response Features and Multi-Fidelity EM Analysis
PublicationThe design of antenna systems poses a significant challenge due to stringent per-formance requirements dictated by contemporary applications and the high com-putational costs associated with models, particularly full-wave electromagnetic (EM) analysis. Presently, EM simulation plays a crucial role in all design phases, encompassing topology development, parametric studies, and the final adjustment of antenna dimensions. The latter...
-
Fast Multi-Objective Antenna Design Through Variable-Fidelity EM Simulations
PublicationA technique for fast multi-objective antenna optimization is introduced. A kriging interpolation surrogate constructed from sampled coarse-mesh EM simulations is utilized by multi-objective evolutionary algorithm (MOEA) to obtain the initial Pareto front approximation. The surrogate is defined in a subset of the original design space, determined by means of independently optimized individual objectives. Response correction techniques...
-
Variable-fidelity CFD models and co-Kriging for expedited multi-objective aerodynamic design optimization
PublicationPurpose – Strategies for accelerated multi-objective optimization of aerodynamic surfaces are investigated, including the possibility of exploiting surrogate modeling techniques for computational fluid dynamic (CFD)-driven design speedup of such surfaces. The purpose of this paper is to reduce the overall optimization time. Design/methodology/approach – An algorithmic framework is described that is composed of: a search space reduction,...
-
Fast Multi-Objective Antenna Optimization Using Sequential Patching and Variable-Fidelity EM Models
PublicationIn this work, a technique for fast multi-objective design optimization of antenna structures is presented. In our approach, the initial approximation of the Pareto set representing the best possible trade-offs between conflicting design objectives is obtained by means of sequential patching of the design space. The latter is a stencil-based search that aims at creating a path that connects the extreme Pareto-optimal designs (obtained...
-
Scalability of surrogate-assisted multi-objective optimization of antenna structures exploiting variable-fidelity electromagnetic simulation models
PublicationMulti-objective optimization of antenna structures is a challenging task due to high-computational cost of evaluating the design objectives as well as large number of adjustable parameters. Design speedup can be achieved by means of surrogate-based optimization techniques. In particular, a combination of variable-fidelity electromagnetic (EM) simulations, design space reduction techniques, response surface approximation (RSA) models,...
-
Rapid multi-objective optimization of antennas using nested kriging surrogates and single-fidelity EM simulation models
PublicationEver increasing performance requirements make the design of contemporary antenna systems a complex and multi-stage process. One of the challenges, pertinent to the emerging application areas but also some of the recent trends (miniaturization, demands for multi-functionality, etc.), is the necessity of handling several performance figures such as impedance matching, gain, or axial ratio, often over multiple frequency bands. The...
-
Cost‐efficient performance‐driven modelling of multi‐band antennas by variable‐fidelity electromagnetic simulations and customized space mapping
PublicationElectromagnetic (EM) simulations have become an indispensable tool in the design of contemporary antennas. EM‐driven tasks, for example, parametric optimization, entail considerable computational efforts, which may be reduced by employing surrogate models. Yet, data‐driven modelling of antenna characteristics is largely hindered by the curse of dimensionality. This may be addressed using the recently reported domain‐confinement...
-
Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublicationA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
-
Efficient Multi-Objective Simulation-Driven Antenna Design Using Co-Kriging
PublicationA methodology for fast multi-objective antenna optimization is presented. Our approach is based on response surface approximation (RSA) modeling and variable-fidelity electromagnetic (EM) simulations. In the design process, a computationally cheap RSA surrogate model constructed from sampled coarse-discretization EM antenna simulations is optimized using a multi-objective evolutionary algorithm. The initially determined Pareto...
-
Low-Cost EM-Simulation-Driven Multi-Objective Optimization of Antennas
PublicationA surrogate-based method for efficient multi-objective antenna optimization is presented. Our technique exploits response surface approximation (RSA) model constructed from sampled low-fidelity antenna model (here, obtained through coarse-discretization EM simulation). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. A low-cost RSA model construction is possible through...
-
Design Space Reduction for Expedited Multi-Objective Design Optimization of Antennas in Highly-Dimensional Spaces
PublicationA surrogate-based technique for efficient multi-objective antenna optimization is discussed. Our approach exploits response surface approximation (RSA) model constructed from low-fidelity antenna model data (here, obtained through coarse-discretization electromagnetic simulations). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. The cost of RSA model construction for multi-parameter...
-
Cost-efficient multi-objective design optimization of antennas in highly-dimensional parameter spaces
PublicationMulti-objective optimization of antenna structures in highly-dimensional parameter spaces is investigated. For expedited design, variable-fidelity EM simulations and domain patching algorithm are utilized. The results obtained for a monopole antenna with 13 geometry parameters are compared with surrogate-assisted optimization involving response surface approximation modeling.
-
Aerodynamic shape optimization by variable-fidelity computational fluid dynamics models: a review of recent progress
PublicationA brief review of some recent variable-fidelity aerodynamic shape optimization methods is presented.We discuss three techniques that—by exploiting information embedded in low-fidelity computationalfluid dynamics (CFD) models—are able to yield a satisfactory design at a low computational cost, usu-ally corresponding to a few evaluations of the original, high-fidelity CFD model to be optimized. Thespecific techniques considered here...
-
Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublicationIn this paper, computationally efficient multi-objective optimization of antenna structures is discussed. As a design case, we consider a multi-parameter planar Yagi-Uda antenna structure, featuring a driven element, three directors, and a feeding structure. Direct optimization of the high-fidelity electromagnetic (EM) antenna model is prohibitive in computational terms. Instead, our design methodology exploits response surface...
-
Multi-Objective Design Optimization of Compact Quasi-Isotropic Dielectric Resonator Antenna
PublicationMulti-objective optimization of a quasi-isotropic dielectric resonator antenna (DRA) is presented. Utilization of variable-fidelity electromagnetic (EM) DRA models, response surface approximations, and response correction techniques, allows us to obtain—at a low computational cost—a set of alternative antenna designs representing the best possible trade-offs between three conflicting objectives: antenna size, its reflection response,...
-
Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublicationIn the paper, computationally efficient constrained multi-objective design optimization of transonic airfoil profiles is considered. Our methodology focuses on fixed-lift design aimed at finding the best possible trade-offs between the two objectives: minimization of the drag coefficient and maximization of the pitching moment. The algorithm presented here exploits the surrogate-based optimization principle, variable-fidelity computational...
-
Design space reduction and variable-fidelity EM simulations for feasible Pareto optimization of antennas
PublicationA computationally efficient procedure for multi-objective optimization of antenna structures is presented. In our approach, a response surface approximation (RSA) model created from sampled coarse-discretization EM antenna simulations is utilized to yield an initial set of Pareto-optimal designs using a multi-objective evolutionary algorithm. The final Pareto front representation for the high-fidelity model is obtained using surrogate-based...
-
On deterministic procedures for low-cost multi-objective design optimization of miniaturized impedance matching transformers
PublicationPurpose This paper aims to investigate deterministic strategies for low-cost multi-objective design optimization of compact microwave structures, specifically, impedance matching transformers. The considered methods involve surrogate modeling techniques and variable-fidelity electromagnetic (EM) simulations. In contrary to majority of conventional approaches, they do not rely on population-based metaheuristics, which permit lowering...
-
Multi-objective optimization of expensive electromagnetic simulation models
PublicationVast majority of practical engineering design problems require simultaneous handling of several criteria. For the sake of simplicity and through a priori preference articulation one can turn many design tasks into single-objective problems that can be handled using conventional numerical optimization routines. However, in some situations, acquiring comprehensive knowledge about the system at hand, in particular, about possible...
-
Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management
PublicationParameter adjustment through numerical optimization has become a commonplace of contemporary microwave engineering. Although circuit theory methods are ubiquitous in the development of microwave components, the initial designs obtained with such tools have to be further tuned to improve the system performance. This is particularly pertinent to miniaturized structures, where the cross-coupling effects cannot be adequately accounted...
-
Rapid multi-objective simulation-driven design of compact microwave circuits
PublicationA methodology for rapid multi-objective design of compact microwave circuits is proposed. Our approach exploits point-by-point Pareto set identification using surrogate-based optimization techniques, auxiliary equivalent circuit models, and space mapping as the major model correction method. The proposed technique is illustrated and validated through the design of a compact rat-race coupler. A set of ten designs being trade-offs...
-
Nested Kriging Surrogates for Rapid Multi-Objective Optimization of Compact Microwave Components
PublicationA procedure for rapid EM-based multi-objective optimization of compact microwave components is presented. Our methodology employs a recently developed nested kriging modelling to identify the search space region containing the Pareto-optimal designs, and to construct a fast surrogate model. The latter permits determination of the initial Pareto set, further refined using a separate surrogate-assisted process. As an illustration,...
-
Reduced-cost optimization-based miniaturization of microwave passives by multi-resolution EM simulations for internet of things and space-limited applications
PublicationStringent performance specifications along with constraints imposed on physical dimensions, make the design of contemporary microwave components a truly onerous task. In recent years, the latter demand has been growing in importance, with the innovative application areas such as Internet of Things coming into play. The need to employ full-wave electromagnetic (EM) simu-lations for response evaluation, reliable yet CPU heavy, only...
-
Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
-
Low-cost multi-objective design of compact microwave structures using domain patching
PublicationA good compromise between size and electrical performance is an important design consideration for compact microwave structures. Comprehensive information about size/performance trade-offs can be obtained through multi-objective optimization. Due to considerable electromagnetic (EM) cross-couplings in highly compressed layouts, the design process has to be conducted at the level of high-fidelity EM analysis which is computationally...
-
Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublicationIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
-
Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublicationThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
-
Comprehensive dimension scaling of multi-band antennas for operating frequencies and substrate parameters
PublicationIn this paper, low-cost and comprehensive redesign of multi-band antennas with respect to the operating frequencies and material parameters of the substrate is presented. Our approach exploits an inverse surrogate model identified based on a set of reference designs optimized at the level of coarse-discretization EM simulations of the antenna at hand. An iterative correction procedure is also implemented to account for the initial...
-
Low-cost multi-objective optimization and experimental validation of UWB MIMO antenna
PublicationPurpose–The purpose of this paper is to validate methodologies for expedited multi-objective designoptimization of complex antenna structures both numerically and experimentally.Design/methodology/approach–The task of identifying the best possible trade-offs between theantenna size and its electrical performance is formulated as multi-objective optimization problem.Algorithmic frameworks are described for finding Pareto-optimal...
-
Pareto Ranking Bisection Algorithm for EM-Driven Multi-Objective Design of Antennas in Highly-Dimensional Parameter Spaces
PublicationA deterministic technique for fast surrogate-assisted multi-objective design optimization of antennas in highly-dimensional parameters spaces has been discussed. In this two-stage approach, the initial approximation of the Pareto set representing the best compromise between conflicting objectives is obtained using a bisection algorithm which finds new Pareto-optimal designs by dividing the line segments interconnecting previously...
-
Multi-objective optimization of microwave couplers using corrected domain patching
PublicationPractical design of microwave components and circuits is a compromise between various, often conflicting objectives. In case of compact structures, the trade-offs are typically concerned with the circuit size and its electrical performance. Comprehensive information about the best possible trade-offs can be obtained by means of multi-objective optimization. In this paper, we propose a computationally efficient technique for identifying...
-
Fast Multi-Objective Optimization of Narrow-Band Antennas Using RSA Models and Design Space Reduction
PublicationComputationally efficient technique for multi-objective design optimization of narrow-band antennas is presented. In our approach, the corrected low-fidelity antenna model (obtained through coarse-discretization EM simulations) is enhanced using frequency scaling and response correction, sampled, and utilized to obtain a fast response surface approximation (RSA) antenna surrogate. The RSA model is constructed in the reduced design space....
-
Low-cost EM-Simulation-based Multi-objective Design Optimization of Miniaturized Microwave Structures
PublicationIn this work, a simple yet reliable technique for fast multi-objective design optimization of miniaturized microwave structures is discussed. The proposed methodology is based on point-by-point identification of a Pareto-optimal set of designs representing the best possible trade-offs between conflicting objectives such as electrical performance parameters as well as the size of the structure of interest. For the sake of computational...
-
Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublicationThe primary objective of this study is investigation of the possibilities of accelerating nature-inspired optimization of antenna structures using multi-fidelity EM simulation models. The primary methodology developed to achieve acceleration is a model management scheme which the level of EM simulation fidelity using two criteria: the convergence status of the optimization algorithm, and relative quality of the individual designs...
-
Multi-objective design optimization of antenna structures using sequential domain patching with automated patch size deter-mination
PublicationIn this paper, a simple yet efficient and reliable technique for fully automated multi-objective design optimization of antenna structures using sequential domain patching (SDP) is discussed. The optimization procedure according to SDP is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between considered conflicting objectives, and (ii) Pareto set refinement...
-
Strategies for computationally feasible multi-objective simulation-driven design of compact RF/microwave components
PublicationMulti-objective optimization is indispensable when possible trade-offs between various (and usually conflicting) design objectives are to be found. Identification of such design alternatives becomes very challenging when performance evaluation of the structure/system at hand is computationally expensive. Compact RF and microwave components are representative examples of such a situation: due to highly compressed layouts and considerable...
-
Fast Multi-Objective Aerodynamic Optimization Using Sequential Domain Patching and Multifidelity Models
PublicationExploration of design tradeoffs for aerodynamic surfaces requires solving of multi-objective optimization (MOO) problems. The major bottleneck here is the time-consuming evaluations of the computational fluid dynamics (CFD) model used to capture the nonlinear physics involved in designing aerodynamic surfaces. This, in conjunction with a large number of simulations necessary to yield a set of designs representing the best possible...
-
Low-Cost Multi-Objective Optimization of Antennas By Means Of Generalized Pareto Ranking Bisection Algorithm
PublicationThis paper introduces a generalized Pareto ranking bisection algorithm for low-cost multi-objective design optimization of antenna structures. The algorithm allows for identifying a set of Pareto optimal sets of parameters (that represent the best trade-offs between considered objectives) by iterative partitioning of the intervals connecting previously found designs and executing a Pareto-ranking-based poll search. The initial...
-
Comprehensive comparison of compact UWB antenna performance by means of multi-objective optimization
PublicationAn optimization-based procedure for comprehensive performance comparison of alternative compact UWB antenna topologies is discussed. The assessment of the antenna performance is conducted with respect to the structure size and its reflection response. More specifically, the best possible tradeoffs between these two figures of merit are identified through multiobjective optimization at the level...