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Search results for: KRIGING
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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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...
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Low-Cost Data-Driven Surrogate Modeling of Antenna Structures by Constrained Sampling
PublicationFull-wave electromagnetic (EM) analysis has become one of the major design tools for contemporary antenna structures. Although reliable, it is computationally expensive which makes automated simulation-driven antenna design (e.g., parametric optimization) difficult. This difficulty can be alleviated by utilization of fast and accurate replacement models (surrogates). Unfortunately, conventional data-driven modeling of antennas...
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Book review: Simulation-Driven Design Optimisation and Modelling for Microwave Engineering
PublicationCelem książki jest przedstawienie aktualnego stanu badań dotyczących projektowania układów mikrofalowych poprzez modelowanie i optymalizacje wspomagane symulacjami elektromagnetycznymi. Grupa międzynarodowych ekspertów zajmujących się rożnymi aspektami komputerowo wspomaganego projektowania układów mikrofalowych, podsumowuje i dokonuje przeglądu ostatnich osiągnięć w tej dziedzinie oraz przedstawia szereg praktycznych zastosowań....
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Statistical analysis and robust design of circularly polarized antennas using sequential approximate optimization
PublicationIn the paper, reliable yield estimation and tolerance-aware design optimization of circular polarization (CP) antennas is discussed. We exploit auxiliary kriging interpolation models established in the vicinity of the nominal design in order to speed up the process of statistical analysis of the antenna structure at hand. Sequential approximate optimization is then applied to carry out robust design of the antenna, here, oriented...
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Multiobjective Aerodynamic Optimization by Variable-Fidelity Models and Response Surface Surrogates
PublicationA computationally efficient procedure for multiobjective design optimization with variable-fidelity models and response surface surrogates is presented. The proposed approach uses the multiobjective evolutionary algorithm that works with a fast surrogate model, obtained with kriging interpolation of the low-fidelity model data enhanced by space-mapping correction exploiting a few high-fidelity training points. The initial Pareto...
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Reduced-cost surrogate modeling of input characteristics and design optimization of dual-band antennas using response features
PublicationIn 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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Performance-Driven Inverse/Forward Modeling of Antennas in Variable-Thickness Domains
PublicationDesign of contemporary antenna systems is a challenging endeavor. The difficulties are partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities, but also constraints imposed upon the physical size of the radiators. Furthermore, conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise dictated by reliability,...
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Zero-Pole Approach in Microwave Passive Circuit Design
PublicationIn this thesis, optimization strategies for design of microwave passive structures including filters, couplers, antenna and impedance transformer and construction of various surroogate models utilized to fasten the design proces have been discussed. Direct and hybrid optimization methodologies including space mapping and multilevel algorithms combined with various surrogate models at different levels of fidelity have been utilized...
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Quasi-Global Optimization of Antenna Structures Using Principal Components and Affine Subspace-Spanned Surrogates
PublicationParametric 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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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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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...
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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...
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Expedited Globalized Antenna Optimization by Principal Components and Variable-Fidelity EM Simulations: Application to Microstrip Antenna Design
PublicationParameter optimization, also referred to as design closure, is imperative in the development of modern antennas. Theoretical considerations along with rough dimension adjustment through supervised parameter sweeping can only yield initial designs that need to be further tuned to boost the antenna performance. The major challenges include handling of multi-dimensional parameter spaces while accounting for several objectives and...
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Expedite EM-driven generation of Pareto-optimal trade-off curves for variable-turn on-chip inductors
PublicationThis work presents a novel approach to computationally efficient Pareto front identification for variable-turn on-chip inductors. The final outcome is a set of solutions that correspond to the best trade-offs between conflicting design objectives. Here, we consider minimising inductor area and, simultaneously, maximising its quality factor, while maintaining a specified inductance value at a given operating frequency. As opposed...
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Fundamentals of Data-Driven Surrogate Modeling
PublicationThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Expedited Variable-Resolution Surrogate Modeling of Miniaturized Microwave Passives in Confined Domains
PublicationDesign of miniaturized microwave components is largely based on computational models, primarily, full-wave electromagnetic (EM) simulations. EM analysis is capable of giving an accurate account for cross-coupling effects, substrate and radiation losses, or interactions with environmental components (e.g., connectors). Unfortunately, direct execution of EM-based design tasks such as parametric optimization or uncertainty quantification,...
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Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
PublicationAir quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung...
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Variable Resolution Machine Learning Optimization of Antennas Using Global Sensitivity Analysis
PublicationThe significance of rigorous optimization techniques in antenna engineering has grown significantly in recent years. For many design tasks, parameter tuning must be conducted globally, presenting a challenge due to associated computational costs. The popular bio-inspired routines often necessitate thousands of merit function calls to converge, generating prohibitive expenses whenever the design process relies on electromagnetic...
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Antenna Optimization Using Machine Learning with Reduced-Dimensionality Surrogates
PublicationIn modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where parameters must be meticulously adjusted to achieve peak performance. Often, global adjustments to geometry are necessary for optimal results. However, direct manipulation of antenna responses evaluated with full-wave electromagnetic (EM)...
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Fast Machine-Learning-Enabled Size Reduction of Microwave Components Using Response Features
PublicationAchieving compact size has emerged as a key consideration in modern microwave design. While structural miniaturization can be accomplished through judicious circuit architecture selection, precise parameter tuning is equally vital to minimize physical dimensions while meeting stringent performance requirements for electrical characteristics. Due to the intricate nature of compact structures, global optimization is recommended,...
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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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Recent Advances in Accelerated Multi-Objective Design of High-Frequency Structures using Knowledge-Based Constrained Modeling Approach
PublicationDesign automation, including reliable optimization of engineering systems, is of paramount importance for both academia and industry. This includes the design of high-frequency structures (antennas, microwave circuits, integrated photonic components), where the appropriate adjustment of geometry and material parameters is crucial to meet stringent performance requirements dictated by practical applications. Realistic design has...
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RANS-based design optimization of dual-rotor wind turbines
PublicationPurpose An improvement in the energy efficiency of wind turbines can be achieved using dual rotors. Because of complex flow physics, the design of dual-rotor wind turbines (DRWTs) requires repetitive evaluations of computationally expensive partial differential equation (PDE) simulation models. Approaches for solving design optimization of DRWTs constrained by PDE simulations are investigated. The purpose of this study is to determine...
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Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
PublicationAir pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its...
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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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Design of High-Performance Scattering Metasurfaces through Optimization-Based Explicit RCS Reduction
PublicationThe recent advances in the development of coding metasurfaces created new opportunities in realization of radar cross section (RCS) reduction. Metasurfaces, composed of optimized geometries of meta-atoms arranged as periodic lattices, are devised to obtain desired electromagnetic (EM) scattering characteristics. Despite potential benefits, their rigorous design methodologies are still lacking, especially in the context of controlling...
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Expedited EM-driven multi-objective antenna design in highly-dimensional parameter spaces
PublicationA technique for low-cost multi-objective optimization of antennas in highly-dimensional parameter spaces is presented. The optimization procedure is expedited by exploiting fast surrogate models, including coarse-discretization EM antenna simulations and response surface approximations (RSA). The latter is utilized to yield an initial set of Pareto non-dominated designs which are further refined using response correction methods....
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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublicationAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...