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Fast EM-Driven Nature-Inspired Optimization of Antenna Input Characteristics Using Response Features and Variable-Resolution Simulation Models
PublicationUtilization of optimization technique is a must in the design of contemporary antenna systems. Often, global search methods are necessary, which are associated with high computational costs when conducted at the level of full-wave electromagnetic (EM) models. In this study, we introduce an innovative method for globally optimizing reflection responses of multi-band antennas. Our approach uses surrogates constructed based on response...
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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...
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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...
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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...
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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...
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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...
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Fast multi-objective design optimization of microwave and antenna structures using data-driven surrogates and domain segmentation
PublicationPurpose Strategies and algorithms for expedited design optimization of microwave and antenna structures in multi-objective setup are investigated. Design/methodology/approach Formulation of the multi-objective design problem oriented towards execution of the population-based metaheuristic algorithm within the segmented search space is investigated. Described algorithmic framework exploit variable fidelity modeling, physics- and...
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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...
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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...
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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...
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Reduced-cost constrained miniaturization of wideband antennas using improved trust-region gradient search with repair step
PublicationIn the letter, an improved algorithm for electromagnetic (EM)-driven size reduction of wideband antennas is proposed. Our methodology utilizes variable-fidelity EM simulation models, auxiliary polynomial regression surrogates, as well as multi-point response correction. The constraint handling is implicit, using penalty functions. The core optimization algorithm is a trust-region gradient search with a repair step added in order...
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Rapid simulation-driven design of miniaturised dual-band microwave couplers by means of adaptive response scaling
PublicationOne of the major challenges in the design of compact microwave structures is the necessity of simultaneous handling of several objectives and the fact that expensive electromagnetic (EM) analysis is required for their reliable evaluation. Design of multi-band circuits where performance requirements are to be satisfied for several frequencies at the same time is even more difficult. In this work, a computationally efficient design...
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Adrian Bekasiewicz dr hab. inż.
PeopleAdrian Bekasiewicz received the MSc, PhD, and DSc degrees in electronic engineering from Gdansk University of Technology, Poland, in 2011, 2016, and 2020, respectively. In 2014, he joined Engineering Optimization & Modeling Center where he held a Research Associate and a Postdoctoral Fellow positions, respectively. Currently, he is an Associate Professor with Gdansk University of Technology, Poland. His research interests include...
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Fast Low-fidelity Wing Aerodynamics Model for Surrogate-Based Shape Optimization
PublicationVariable-fidelity optimization (VFO) can be efficient in terms of the computational cost when compared with traditional approaches, such as gradient-based methods with adjoint sensitivity information. In variable-fidelity methods, the directoptimization of the expensive high-fidelity model is replaced by iterative re-optimization of a physics-based surrogate model, which is constructed from a corrected low-fidelity model. The success...
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Variable-fidelity shape optimization of dual-rotor wind turbines
PublicationPurpose Dual-rotor wind turbines (DRWTs) are a novel type of wind turbines that can capture more power than their single-rotor counterparts. Because their surrounding flow fields are complex, evaluating a DRWT design requires accurate predictive simulations, which incur high computational costs. Currently, there does not exist a design optimization framework for DRWTs. Since the design optimization of DRWTs requires numerous model...
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Local response surface approximations and variable-fidelity electromagnetic simulations for computationally efficient microwave design optimisation
PublicationIn this study, the authors propose a robust and computationally efficient algorithm for simulation-driven design optimisation of microwave structures. Our technique exploits variable-fidelity electromagnetic models of the structure under consideration. The low-fidelity model is optimised using its local response surface approximation surrogates. The high-fidelity model is refined by space mapping with polynomial interpolation of...
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Variable-fidelity response feature surrogates for accelerated statistical analysis and yield estimation of compact microwave components
PublicationAccounting for manufacturing tolerances is an essential part of a reliable microwave design process. Yet, quantification of geometry and/or material parameter uncertainties is challenging at the level of full-wave electromagnetic (EM) simulation models. This is due to inherently high cost of EM analysis and massive simulations necessary to conduct the statistical analysis. Here, a low-cost and accurate yield estimation procedure...
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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...
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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...
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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...
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Fast tolerance-aware design optimization of miniaturized microstrip couplers using variable-fidelity EM simulations and re-sponse features
PublicationManufacturing tolerances and other types of uncertainties may considerably affect operation and performance of microwave components and systems. Quantification of these effects is therefore an important part of the design process. It is even more important to obtain designs whose sensitivity to parameter deviations is reduced as much as possible. All of these require statistical analysis carried out at the level of electromagnetic...
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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.
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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...
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Surrogate modeling of impedance matching transformers by means of variable‐fidelity electromagnetic simulations and nested cokriging
PublicationAccurate performance evaluation of microwave components can be carried out using full‐wave electromagnetic (EM) simulation tools, routinely employed for circuit verification but also in the design process itself. Unfortunately, the computational cost of EM‐driven design may be high. This is especially pertinent to tasks entailing considerable number of simulations (eg, parametric optimization, statistical analysis). A possible...
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Reliable Microwave Modeling By Means of Variable-Fidelity Response Features
PublicationIn this work, methodologies for low-cost and reliable microwave modeling are presented using variable-fidelity response features. The two key components of our approach are: (i) a realization of the modeling process at the level of suitably selected feature points of the responses (e.g., S-parameters vs. frequency) of the structure at hand, and (ii) the exploitation of variable-fidelity EM simulation data, also for the response...
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Implicit Space Mapping for Variable-Fidelity EM-Driven Design of Compact Circuits
PublicationSpace mapping (SM) belongs to the most successful surrogate-based optimization (SBO) methods in microwave engineering. Among available SM variations, implicit SM (ISM) is particularly attractive due to its simplicity and separation of extractable surrogate model parameters and design variables of the circuit/system at hand. Unlike other SM approaches, ISM exploits a set of preassigned parameters to align the surrogate with the...
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Antenna Modeling Using Variable-Fidelity EM Simulations and Constrained Co-Kriging
PublicationUtilization of fast surrogate models has become a viable alternative to direct handling of fullwave electromagnetic (EM) simulations in EM-driven design. Their purpose is to alleviate the difficulties related to high computational cost of multiple simulations required by the common numerical procedures such as parametric optimization or uncertainty quantification. Yet, conventional data-driven (or approximation) modeling techniques...
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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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Trawl-Door Shape Optimization with 3D CFD Models and Local Surrogates
PublicationDesign and optimization of trawl-doors are key factors in minimizing the fuel consumption of fishing vessels. This paper discusses optimization of the trawl-door shapes using high-fidelity 3D computational fluid dynamic (CFD) models. The accurate 3D CFD models are computationally expensive and, therefore, the direct use of traditional optimization algorithms, which often require a large number of evaluations, may be prohibitive....
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Fundamentals of Physics-Based Surrogate Modeling
PublicationChapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses,...
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Low-fidelity model considerations for simulation-based optimisation of miniaturised wideband antennas
PublicationHere, variable-fidelity electromagnetic (EM)-based design optimisation of miniaturised antennas is discussed. The authors focus on an appropriate selection of discretisation density of the low-fidelity EM model, which results in good performance of the optimisation algorithm in terms of its computational complexity and reliability. Trust-region gradient search with low-fidelity model corrected by means of non-linear frequency scaling...
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Objective selection of minimum acceptable mesh refinement for EMC simulations
PublicationOptimization of computational electromagnetics (CEM) simulation models can be costly in both time and computing resources. Mesh refinement is a key parameter in determining the number of unknowns to be processed. In turn, this controls the time and memory required for a simulation. Hence, it is important to use only a mesh that is good enough for the objectives of the simulation, whether for direct handling of high-fidelity EM...
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Efficient knowledge-based optimization of expensive computational models using adaptive response correction
PublicationComputer simulation has become an indispensable tool in engineering design as they allow an accurate evaluation of the system performance. This is critical in order to carry out the design process in a reliable manner without costly prototyping and physical measurements. However, high-fidelity computer simulations are computationally expensive. This turns to be a fundamental bottleneck when it comes to design automation using numerical...
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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...
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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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...
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublicationNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Expedited Design Closure of Antennas By Means Of Trust-Region-Based Adaptive Response Scaling
PublicationIn the letter, a reliable procedure for expedited design optimization of antenna structures by means of trust-region adaptive response scaling (TR-ARS) is proposed. The presented approach exploits two-level electromagnetic (EM) simulation models. A predicted high-fidelity model response is obtained by applying nonlinear frequency and amplitude correction to the low-fidelity model. The surrogate created this way is iteratively rebuilt...
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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...
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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,...
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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...
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Rapid Microwave Design Optimization in Frequency Domain Using Adaptive Response Scaling
PublicationIn this paper, a novel methodology for cost-efficient microwave design optimization in the frequency domain is proposed. Our technique, referred to as adaptive response scaling (ARS), has been developed for constructing a fast replacement model (surrogate) of the high-fidelity electromagnetic-simulated model of the microwave structure under design using its equivalent circuit (low-fidelity model). The basic principle of ARS is...
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Two-Stage Variable-Fidelity Modeling of Antennas with Domain Confinement
PublicationSurrogate modeling has become the method of choice in solving an increasing number of antenna design tasks, especially those involving expensive full-wave electromagnetic (EM) simulations. Notwithstanding, the curse of dimensionality considerably affects conventional metamodeling methods, and their capability to efficiently handle nonlinear antenna characteristics over broad ranges of the system parameters is limited. Performance-driven...
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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...
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Using Isolation Forest and Alternative Data Products to Overcome Ground Truth Data Scarcity for Improved Deep Learning-based Agricultural Land Use Classification Models
PublicationHigh-quality labelled datasets represent a cornerstone in the development of deep learning models for land use classification. The high cost of data collection, the inherent errors introduced during data mapping efforts, the lack of local knowledge, and the spatial variability of the data hinder the development of accurate and spatially-transferable deep learning models in the context of agriculture. In this paper, we investigate...
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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...
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Simulation-Based Design of Microstrip Linear Antenna Arrays Using Fast Radiation Response Surrogates
PublicationFast yet accurate technique for simulation-based design of linear arrays of microstrip patch antennas is presented. Our technique includes: (i) optimization of the corrected array factor of the antenna array under design for a phase excitation taper resulting in reduced side lobes; (ii) simulation-driven optimization of the array element for element dimensions resulting in matching at and about operational frequency, and (iii)...
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Cost-efficient design optimization of compact patch antennas with improved bandwidth
PublicationIn this letter, a surrogate-assisted optimization procedure for fast design of compact patch antennas with enhanced bandwidth is presented. The procedure aims at addressing a fundamental challenge of the design of antenna structures with complex topologies, which is simultaneous adjustment of numerous geometry parameters. The latter is necessary in order to find a truly optimum design and cannot be executed-at the level of high-fidelity...
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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...
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Novel structure and EM-driven design of miniaturized microstrip rat-race coupler
PublicationIn this paper, a novel structure and design procedure of a miniaturized microstrip rat-race coupler (RRC) is described. Small size of the RRC is achieved by folding the transmission lines of the conventional circuit into its interior, as well as by implementation of the structure on three layers. The final size of the coupler realized for the operating frequency of 1 GHz is only 220 mm2, which gives over 95% footprint reduction...