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Wyniki wyszukiwania dla: HIGH-FREQUENCY DESIGN, ELECTROMAGNETIC SIMULATION, SURROGATE MODELING, PERFORMANCE-DRIVEN MODELING
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Variable-fidelity response feature surrogates for accelerated statistical analysis and yield estimation of compact microwave components
PublikacjaAccounting 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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Improved-Efficacy Optimization of Compact Microwave Passives by Means of Frequency-Related Regularization
PublikacjaElectromagnetic (EM)-driven optimization is an important part of microwave design, especially for miniaturized components where the cross-coupling effects in tightly arranged layouts make traditional (e.g., equivalent network) representations grossly inaccurate. Efficient parameter tuning requires reasonably good initial designs, which are difficult to be rendered for newly developed structures or when re-design for different operating...
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Knowledge-Based Expedited Parameter Tuning of Microwave Passives by Means of Design Requirement Management and Variable-Resolution EM Simulations
PublikacjaThe importance of numerical optimization techniques has been continually growing in the design of microwave components over the recent years. Although reasonable initial designs can be obtained using circuit theory tools, precise parameter tuning is still necessary to account for effects such as electromagnetic (EM) cross coupling or radiation losses. EM-driven design closure is most often realized using gradient-based procedures,...
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Rapid design of miniaturised branch-line couplers through concurrent cell optimisation and surrogate-assisted fine-tuning
PublikacjaIn this study, the authors introduce a methodology for low-cost simulation-driven design optimisation of highly miniaturised branch-line couplers (BLCs). The first stage of their design approach exploits fast concurrent optimisation of geometrically dependent, but electromagnetically isolated cells that constitute a BLC. The cross-coupling effects between the cells are taken into account in the second stage, where a surrogate-assisted...
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Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics
PublikacjaElectromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure...
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Optimization-Based Robustness Enhancement of Compact Microwave Component Designs with Response Feature Regression Surrogates
PublikacjaThe ability to evaluate the effects of fabrication tolerances and other types of uncertainties is a critical part of microwave design process. Improving the immunity of the device to parameter deviations is equally important, especially when the performance specifications are stringent and can barely be met even assuming a perfect manufacturing process. In the case of modern miniaturized microwave components of complex topologies,...
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Accelerated multi-objective design of miniaturized microwave components by means of nested kriging surrogates
PublikacjaDesign of microwave components is an inherently multiobjective task. Often, the objectives are at least partially conflicting and the designer has to work out a suitable compromise. In practice, generating the best possible trade‐off designs requires multiobjective optimization, which is a computationally demanding task. If the structure of interest is evaluated through full‐wave electromagnetic (EM) analysis, the employment of...
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Fast EM-Driven Nature-Inspired Optimization of Antenna Input Characteristics Using Response Features and Variable-Resolution Simulation Models
PublikacjaUtilization 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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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublikacjaIn this work, a computationally efficient method based on data driven surrogate models is pro-posed for the design optimization procedure of a Frequency Selective Surface (FSS)-based filtering antenna (Filtenna). A Filtenna acts as a as module that simultaneously pre-filters unwanted sig-nals, and enhances the desired signals at the operating frequency. However, due to a typically large number of design variables of FSS unit elements,...
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Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
PublikacjaDesign of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters...
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Computationally Efficient Multi-Objective Optimization of and Experimental Validation of Yagi-Uda Antenna
PublikacjaIn 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...
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Rapid multi-objective antenna design using point-by-point Pareto set identification and local surrogate models
PublikacjaAntenna design is inherently a multicriterial problem.Determination of the best possible tradeoffs between conflicting objectives (a so-called Pareto front), such as reflection response, gain, and antenna size, is indispensable from the designer’s point of view, yet challenging when high-fidelity electromagnetic (EM) simulations are utilized for performance evaluation. Here, a novel and computationally...
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Explicit Size-Reduction of Circularly Polarized Antennas through Constrained Optimization with Penalty Factor Adjustment
PublikacjaModern communication systems of high data capacity incorporate circular polarization (CP) as the preferred antenna radiation field configuration. In many applications, integration of the system circuitry with antennas imposes size limitations on CP radiators, which makes their development process a challenging endeavor. This can be mitigated by means of simulation-driven design, specifically, constrained numerical optimization....
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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublikacjaDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublikacjaDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...
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Reliable EM-driven size reduction of antenna structures by means of adaptive penalty factors
PublikacjaMiniaturization has become of paramount importance in the design of modern antenna systems. In particular, compact size is essential for emerging application areas such as internet of things, wearable and implantable devices, 5G technology, or medical imaging. On the other hand, reduction of physical dimensions generally has a detrimental effect on antenna performance. From the perspective of numerical optimization, miniaturization...
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublikacjaIn 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...
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EM‐driven constrained miniaturization of antennas using adaptive in‐band reflection acceptance threshold
PublikacjaNumerical optimization of geometry parameters is a critical stage of the design process of compact antennas. It is also challenging because size reduction is constrained by the necessity of fulfilling imposed electrical performance requirements. Furthermore, full‐wave electromagnetic (EM) analysis needs to be used for reliable performance evaluation of the antenna structure, which is computationally expensive. In this paper, an...
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Supervised-learning-based development of multi-bit RCS-reduced coding metasurfaces
PublikacjaCoding metasurfaces have been introduced as efficient tools allowing meticulous control over the electromagnetic (EM) scattering. One of their relevant application areas is radar cross section (RCS) reduction, which principally relies on the diffusion of impinging EM waves. Despite its significance, careful control of the scattering properties poses a serious challenge at the level of practical realization. This article is concerned...
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Design Space Reduction for Expedited Multi-Objective Design Optimization of Antennas in Highly-Dimensional Spaces
PublikacjaA 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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Rapid Multi-Criterial Antenna Optimization by Means of Pareto Front Triangulation and Interpolative Design Predictors
PublikacjaModern antenna systems are designed to meet stringent performance requirements pertinent to both their electrical and field properties. The objectives typically stay in conflict with each other. As the simultaneous improvement of all performance parameters is rarely possible, compromise solutions have to be sought. The most comprehensive information about available design trade-offs can be obtained through multi-objective optimization...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublikacjaAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Rapid design closure of linear microstrip antenna array apertures using response features
PublikacjaA simple yet reliable approach to a rapid design closure of linear antenna array apertures at the electromagnetic (EM)-simulation level is proposed. Our methodology exploits an underlying array factor (AF) model suitably corrected by means of characteristic points (angles and levels) of the radiation pattern of the EM model of the antenna array aperture. This conveniently allows for controlling both the side lobe levels...
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Rapid tolerance‐aware design of miniaturized microwave passives by means of confined‐domain surrogates
PublikacjaThe effects of uncertainties, primarily manufacturing tolerances but also incomplete information about operating conditions or material parameters, can be detrimental to the performance of microwave components. Quantification of such effects is essential to ensure a meaningful evaluation of the structure, in particular, its reliability under imperfect fabrication procedures. The improvement of the circuit robustness can be achieved...
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A structure and design optimization of novel compact microscrip dual-band rat-race coupler with enhanced bandwidth
PublikacjaIn the letter, a topology of a novel compact wideband dual-band rat-race coupler has been presented along with its computationally efficient design optimization procedure. Reduction of the circuit size has been achieved by meandering transmission lines of the conventional circuit. At the same time, the number of independent geometry parameters has been increased so as to secure sufficient flexibility of the circuit, necessary in...
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Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublikacjaIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
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A new approach to a fast and accurate design of microwave circuits with complex topologies
PublikacjaA robust simulation-driven design methodology of microwave circuits with complex topologies has been presented. The general method elaborated is suitable for a wide class of N-port unconventional microwave circuits constructed as a deviation from classic design solutions. The key idea of the approach proposed lies in an iterative redesign of a conventional circuit by a sequential modification and optimisation of its atomic building...
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Design-oriented computationally-efficient feature-based surrogate modelling of multi-band antennas with nested kriging
PublikacjaDesign of modern antenna structures heavily depends on electromagnetic (EM) simulation tools. EM analysis provides reliable evaluation of increasingly complex designs but tends to be CPU intensive. When multiple simulations are needed (e.g., for parameters tuning), the aggregated simulation cost may become a serious bottleneck. As one possible way of mitigating the issue, the recent literature fosters utilization of faster representations,...
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Surrogate-Assisted Design of Checkerboard Metasurface for Broadband Radar Cross-Section Reduction
PublikacjaMetasurfaces have been extensively exploited in stealth applications to reduce radar cross section (RCS). They rely on the manipulation of backward scattering of electromagnetic (EM) waves into various oblique angles. However, arbitrary control of the scattering properties poses a significant challenge as a design task. Yet it is a principal requirement for making RCS reduction possible. This article introduces a surrogate-based...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublikacjaThis 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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Expedited constrained multi-objective aerodynamic shape optimization by means of physics-based surrogates
PublikacjaIn 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...
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Inverse Modeling and Optimization of CSRR-based Microwave Sensors for Industrial Applications
PublikacjaDesign optimization of multivariable resonators is a challenging topic in the area of microwave sensors for industrial applications. This paper proposes a novel methodology for rapid re-design and parameter tuning of complementary split-ring resonators (CSRRs). Our approach involves inverse surrogate models established using pre-optimized resonator data as well as analytical correction techniques to enable rapid adjustment of geometry...
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Rapid Re-Design and Bandwidth/Size Trade-Offs for Compact Wideband Circular Polarization Antennas Using Inverse Surrogates and Fast EM-Based Parameter Tuning
PublikacjaDesign of compact wideband circularly polarized (CP) antennas is challenging due to the necessity of simultaneous handling of several characteristics (reflection, axial ratio, gain) while maintaining a small size of the structure. Antenna re-design for various operating bands is clearly more difficult yet practically important because intentional reduction of the bandwidth (e.g., by moving the lower edge of the operating band up...
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Local-Global Space Mapping for Rapid EM-Driven Design of Compact RF Structures
PublikacjaIn this work, we introduce a robust and efficient technique for rapid design of compact RF circuits. Our approach exploits two-level space mapping (SM) correction of an equivalent circuit model of the structure under design. The first SM layer (local correction) is utilized to ensure good matching between the equivalent circuit and the electromagnetic model at the component level. On the other hand, the global correction allows...
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Reduced-Cost Microwave Design Closure by Multi-Resolution EM Simulations and Knowledge-Based Model Management
PublikacjaParameter 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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Multi-objective design optimization of antennas for reflection, size, and gain variability using kriging surrogates and generalized domain segmentation
PublikacjaCost-efficient multi-objective design optimization of antennas is presented. The framework exploits auxiliary data-driven surrogates, a multi-objective evolutionary algorithm for initial Pareto front identification, response correction techniques for design refinement, as well as generalized domain segmentation. The purpose of this last mechanism is to reduce the volume of the design space region that needs to be sampled in order...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublikacjaThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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Objective relaxation algorithm for reliable simulation-driven size reduction of antenna structure
PublikacjaThis letter investigates reliable size reduction of antennas through electromagnetic-driven optimization. It is demonstrated that conventional formulation of the design task by direct footprint miniaturization with imposing constraints on electrical performance parameters may not lead to optimum results. The reason is that—in a typical antenna structure—only a few geometry parameters explicitly determine the antenna footprint,...
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Rapid redesign of multiband antennas with respect to operating conditions and material parameters of substrate
PublikacjaThis work addresses geometry parameter scaling of multi-band antennas for Internet of Things applications. The presented approach is comprehensive and permits re-design of the structure with respect to both the operating frequencies and material parameters of the dielectric substrate. A two-step procedure is developed with the initial design obtained from an inverse surrogate model constructed using a set of appropriately prepared...
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Computer modeling and design of materials 2022/2023
Kursy OnlineComputer modeling and design of materials, kierunek: Nanotechnologia, specjalność: Mathematics for new materials design, II stopień, semestr 3
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On Decomposition-Based Surrogate-Assisted Optimization of Leaky Wave Antenna Input Characteristics for Beam Scanning Applications
PublikacjaRecent years have witnessed a growing interest in reconfigurable antenna systems. Travelling wave antennas (TWAs) and leaky wave antennas (LWAs) are representative examples of structures featuring a great level of flexibility (e.g., straightforward implementation of beam scanning), relatively simple geometrical structure, low profile, and low fabrication cost. Notwithstanding, the design process of TWAs/LWAs is a challenging endeavor...
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Quasi-Global Optimization of Antenna Structures Using Principal Components and Affine Subspace-Spanned Surrogates
PublikacjaParametric optimization is a mandatory step in the design of contemporary antenna structures. Conceptual development can only provide rough initial designs that have to be further tuned, often extensively. Given the topological complexity of modern antennas, the design closure necessarily involves full-wave electromagnetic (EM) simulations and—in many cases—global search procedures. Both factors make antenna optimization a computationally...
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Accelerated design optimization of miniaturized microwave passives by design reusing and Kriging interpolation surrogates
PublikacjaElectromagnetic (EM) analysis has become ubiquitous in the design of microwave components and systems. One of the reasons is the increasing topological complexity of the circuits. Their reliable evaluation—at least at the design closure stage—can no longer be carried out using analytical or equivalent network representations. This is especially pertinent to miniaturized structures, where considerable EM cross-coupling effects occurring...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Inverse surrogate modeling for low-cost geometry scaling of microwave and antenna structures
PublikacjaPurpose–The purpose of this paper is to investigate strategies for expedited dimension scaling ofelectromagnetic (EM)-simulated microwave and antenna structures, exploiting the concept of variable-fidelity inverse surrogate modeling.Design/methodology/approach–A fast inverse surrogate modeling technique is described fordimension scaling of microwave and antenna structures. The model is established using referencedesigns obtained...
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Reduced-cost surrogate modeling of input characteristics and design optimization of dual-band antennas using response features
PublikacjaIn this article, a procedure for low-cost surrogate modeling of input characteristics of dual-band antennas has been discussed. The number of training data required for construction of an accurate model has been reduced by representing the antenna reflection response to the level of suitably defined feature points. The points are allocated to capture the critical features of the reflection characteristic, such as the frequencies...
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A bisection‐based heuristic for rapid EM‐driven multiobjective design of compact impedance transformers
PublikacjaDesign of microwave structures is a multiobjective task where several conflicting requirements have to be considered at the same time. For contemporary circuits characterized by complex geometries, multiobjective optimization cannot be performed using standard population‐based algorithms due to high cost of electromagnetic (EM) evaluations. In this work, we propose a deterministic approach for fast EM‐driven multiobjective design...
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Grand Challenges on the Theory of Modeling and Simulation
PublikacjaModeling & Simulation (M&S) is used in many different fields and has made many significant contributions. As a field in its own right, there have been many advances in methodologies and technologies. In 2002 a workshop was held in Dagstuhl, Germany, to reflect on the grand challenges facing M&S. Ten years on, a series of M& S Grand Challenge activities are marking a decade of progress and are providing an opportunity to reflect...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublikacjaThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Modeling in Machine Design
Kursy OnlineThe course is meant to show the students how to build calculation models in machine design