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Search results for: LOW-FIDELITY MODELING
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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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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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On low-fidelity models for variable-fidelity simulation-driven design optimization of compact wideband antennas
PublicationThe paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband...
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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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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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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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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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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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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 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...
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Surrogate-assisted EM-driven miniaturization of wideband microwave couplers by means of co-simulation low-fidelity models
PublicationThis article proposes a methodology for rapid design optimization of miniaturized wideband couplers. More specifically, a class of circuits is considered, in which conventional transmission lines are replaced by their abbreviated counterparts referred to as slow-wave compact cells. Our focus is on explicit reduction of the structure size as well as on reducing the CPU cost of the design process. For the sake of computational feasibility,...
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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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Low-cost multiband compact branch-line coupler design using response features and automated EM model fidelity adjustment
PublicationDesign closure of compact microwave components is a challenging problem because of significant electromagnetic (EM) cross-couplings in densely arranged layouts. A separate issue is a large number of designable parameters resulting from replacement of conventional transmission line sections by compact microstrip resonant cells. This increases complexity of the design optimization problem and requires employment of expensive high-fidelity...
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Inverse surrogate modeling for low-cost geometry scaling of microwave and antenna structures
PublicationPurpose–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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Low-Cost Behavioral Modeling of Antennas by Dimensionality Reduction and Domain Confinement
PublicationBehavioral modeling has been rising in importance in modern antenna design. It is primarily employed to diminish the computational cost of procedures involving massive full-wave electromagnetic (EM) simulations. Cheaper alternative offer surrogate models, yet, setting up data-driven surrogates is impeded by, among others, the curse of dimensionality. This article introduces a novel approach to reduced-cost surrogate modeling of...
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Achieving Efficient and Stable Deammonification at Low Temperatures—Experimental and Modeling Studies
PublicationThe short-term effects of temperature on deammonification sludge were evaluated in a laboratory-scale sequencing batch reactor (SBR). Mathematical modeling was used for further evaluations of different intermittent aeration strategies for achieving high and stable deammonification performance at decreasing temperatures. As for the biomass cultivated at high temperatures (e.g., 30 C), a higher temperature dependency (the adjusted...
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Low-Cost Flight Simulator with Possibility of Modeling of Flight Controls Failures
PublicationThe goal of this paper is to present a development of a low cost flight simulator, that allows to simulate flight controls failures. Cessna 172 has been chosen as an example of a general aviation aircraft and the flight model has been implemented in Simulink. The model allows for easy integration of an experimental autopilot, using various strategies. Aerodynamic coefficients have been calculated using software called DATCOM. Such...
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Noise modeling of static CMOS gates for low-noise circuit synthesis
PublicationW artykule przedstawiono efektywną metodę modelowania widma szumu napięcia zasilającego generowanego przez statyczne bramki cyfrowe CMOS. Metoda modelowania uwzględnia krótkie impulsy prądowe powstające w czasie przełączania bramek i pozwala oszacować górne limity widma szumu napięcia zasilającego co umożliwia niskoszumową syntezę układów cyfrowych.
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Low-Cost Surrogate Modeling of Miniaturized Microwave Components Using Nested Kriging
PublicationIn the paper, a recently reported nested kriging methodology is employed for modeling of miniaturized microwave components. The approach is based on identifying the parameter space region that contains high-quality designs, and, subsequently, rendering the surrogate in this subset. The results obtained for a miniaturized unequal-power-split rat-race coupler and a compact three-section impedance transformer demonstrate reliability...
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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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Uniform sampling in constrained domains for low-cost surrogate modeling of antenna input characteristics
PublicationIn this letter, a design of experiments technique that permits uniform sampling in constrained domains is proposed. The discussed method is applied to generate training data for construction of fast replacement models (surrogates) of antenna input characteristics. The modeling process is design-oriented with the surrogate domain spanned by a set of reference designs optimized with respect to the performance figures and/or operating...
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Modeling of low calorific gas burning in a deficient oxygen environment and high-temperature oxidizer
PublicationThe experimental research will be performed using the experimental facility with a combustion chamber. The oxygen concentration in combustion oxidizers will be varied from 21% by volume (normal) air to 2%. The test combustion chamber will be fed with propane or methane as the reference fuel, then with low calorific fuels as test gases obtained by mixing various combustible components, e.g. H2, CH4, CO, and neutral gases, e.g. N2,...
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An Example of Using Low-Cost LiDAR Technology for 3D Modeling and Assessment of Degradation of Heritage Structures and Buildings
PublicationThis article examines the potential of low-cost LiDAR technology for 3D modeling and assessment of the degradation of historic buildings, using a section of the Koszalin city walls in Poland as a case study. Traditional terrestrial laser scanning (TLS) offers high accuracy but is expensive. The study assessed whether more accessible LiDAR options, such as those integrated with mobile devices such as the Apple iPad Pro, can serve...
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Low-Cost Modeling of Microwave Components by Means of Two-Stage Inverse/Forward Surrogates and Domain Confinement
PublicationFull-wave electromagnetic (EM) analysis is one of the most important tools in the design of modern microwave components and systems. EM simulation permits reliable evaluation of circuits at the presence of cross-coupling effects or substrate anisotropy, as well as for accounting for interactions with the immediate environment. However, repetitive analyses required by EM-driven procedures, such as parametric optimization or statistical...
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H2O˙+ and OH+ reactivity versus furan: experimental low energy absolute cross sections for modeling radiation damage
PublicationRadiotherapy is one of the most widespread and efficient strategies to fight malignant tumors. Despite its broad application, the mechanisms of radiation-DNA interaction are still under investigation. Theoretical models to predict the effects of a particular delivered dose are still in their infancy due to the difficulty of simulating a real cell environment, as well as the inclusion of a large variety of secondary processes. This...
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Reliable low-cost surrogate modeling and design optimisation of antennas using implicit space mapping with substrate segmentation
PublicationAbstract: In this work, a reliable methodology for fast simulation-driven design optimisation of antenna structures is proposed. The authors’ approach exploits implicit space mapping (ISM) technology. To adopt it for handling antenna structures, they introduce substrate segmentation with separate dielectric permittivity value assigned for each segment as ISM preassigned parameters. At the same time, the coarse model for space mapping...
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Maximizing the output power of magnetically geared generator in low-speed applications using subdomain modeling and particle swarm optimization
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Low-Cost and Highly-Accurate Behavioral Modeling of Antenna Structures by Means of Knowledge-Based Domain-Constrained Deep Learning Surrogates
PublicationThe awareness and practical benefits of behavioral modeling methods have been steadily growing in the antenna engineering community over the last decade or so. Undoubtedly, the most important advantage thereof is a possibility of a dramatic reduction of computational expenses associated with computer-aided design procedures, especially those relying on full-wave electromagnetic (EM) simulations. In particular, the employment of...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublicationMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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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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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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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...
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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...
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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...
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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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Expedited Geometry Scaling of Compact Microwave Passives by Means of Inverse Surrogate Modeling
PublicationIn this paper, the problem of geometry scaling of compact microwave structures is investigated. As opposed to conventional structures (i.e., constructed using uniform transmission lines), re-design of miniaturized circuits (e.g., implemented with artificial transmission lines, ATSs) for different operating frequencies is far from being straightforward due to considerable cross-couplings between the circuit components. Here, we...
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Rapid Yield Optimization of Miniaturized Microwave Passives by Response Features and Variable-Fidelity EM Simulations
PublicationThe operation of high-frequency devices, including microwave passive components, can be impaired by fabrication tolerances but also incomplete knowledge concerning operating conditions (temperature, input power levels) and material parameters (e.g., substrate permittivity). Although the accuracy of manufacturing processes is always limited, the effects of parameter deviations can be accounted for in advance at the design phase...
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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...
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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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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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Fast EM-driven optimization using variable-fidelity EM models and adjoint sensitivities
PublicationA robust and computationally efficient technique for microwave design optimization is presented. Our approach exploits variable-fidelity electromagnetic (EM) simulation models and adjoint sensitivities. The low-fidelity EM model correction is realized by means of space mapping (SM). In the optimization process, the SM parameters are optimized together with the design itself, which allows us to keep the number...
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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...
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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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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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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...
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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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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,...
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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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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...
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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:...