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Search results for: computational models
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What matters most to patients? On the Core Determinants of Patient Experience from Free Text Feedback
PublicationFree-text feedback from patients is increasingly used for improving the quality of healthcare services and systems. A major reason for the growing interest in harnessing free-text feedback is the belief that it provides richer information about what patients want and care about. The use of computational approaches such as structural topic modelling for analysing large unstructured textual data such as free-text feedback from patients...
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Expedited Design Closure of Antenna Input Characteristics by Trust Region Gradient Search and Principal Component Analysis
PublicationOptimization-based parameter tuning has become an inherent part of contemporary antenna design process. For the sake of reliability, it is typically conducted at the level of full-wave electromagnetic (EM) simulation models. This may incur considerable computational expenses depending on the cost of an individual EM analysis, the number of adjustable variables, the type of task (local, global, single-/multi-objective optimization),...
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Three-dimensional modeling and automatic analysis of the human nasal cavity and paranasal sinuses using the computational fluid dynamics method
PublicationPurpose The goal of this study was to develop a complete workflow allowing for conducting computational fluid dynam- ics (CFD) simulation of airflow through the upper airways based on computed tomography (CT) and cone-beam computed tomography (CBCT) studies of individual adult patients. Methods This study is based on CT images of 16 patients. Image processing and model generation of the human nasal cavity and paranasal sinuses...
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A structure and design of a novel compact UWB MIMO antenna
PublicationIn the paper, a concept and design procedure of a novel compact MIMO slot antenna is presented. In order to achieve a better filling of available space, individual antennas are constrained to a triangular shape and optimized for a reduced size. The MIMO structure is then assembled using the two of previously designed antennas in orthogonal arrangement. Surrogate-assisted numerical optimization involving variable-fidelity electromagnetic...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Modeling lubricant flow between thrust-bearing pads
PublicationInlet temperature is one of the main inputs in all models for the analysis of fluid film bearing performance. At the same time, inlettemperature distribution and also oil velocity distribution at the inlet are the result of flow phenomena in the gap between the bearingpads. These phenomena are complex and in many cases further affected by any special arrangements of forced oil supply to the gapbetween pads. The reason for such...
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Electromagnetic Simulation with 3D FEM for Design Automation in 5G Era
PublicationElectromagnetic simulation and electronic design automation (EDA) play an important role in the design of 5G antennas and radio chips. The simulation challenges include electromagnetic effects and long simulation time and this paper focuses on simulation software based on finite-element method (FEM). The state-of-the-art EDA software using novel computational techniques based on FEM can not only accelerate numerical analysis, but...
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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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On Computationally-Efficient Reference Design Acquisition for Reduced-Cost Constrained Modeling and Re-Design of Compact Microwave Passives
PublicationFull-wave electromagnetic (EM) analysis has been playing a major role in the design of microwave components for the last few decades. In particular, EM tools allow for accurate evaluation of electrical performance of miniaturized structures where strong cross-coupling effects cannot be adequately quantified using equivalent network models. However, EM-based design procedures (parametric optimization, statistical analysis) generate...
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Expedited Metaheuristic-Based Antenna Optimization Using EM Model Resolution Management
PublicationDesign of modern antenna systems heavily relies on numerical opti-mization methods. Their primary purpose is performance improvement by tun-ing of geometry and material parameters of the antenna under study. For relia-bility, the process has to be conducted using full-wave electromagnetic (EM) simulation models, which are associated with sizable computational expendi-tures. The problem is aggravated in the case of global optimization,...
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Patch size setup and performance/cost trade-offs in multi-objective EM-driven antenna optimization using sequential domain patching
PublicationPurpose This paper aims to assess control parameter setup and its effect on computational cost and performance of deterministic procedures for multi-objective design optimization of expensive simulation models of antenna structures. Design/methodology/approach A deterministic algorithm for cost-efficient multi-objective optimization of antenna structures has been assessed. The algorithm constructs a patch connecting extreme Pareto-optimal...
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Microbe Cultivation Guidelines to Optimize Rhamnolipid Applications
PublicationIn the growing landscape of interest in natural surfactants, selecting the appropriate one for specific applications remains challenging. The extensive, yet often unsystematized, knowledge of microbial surfactants, predominantly represented by rhamnolipids (RLs), typically does not translate beyond the conditions presented in scientific publications. This limitation stems from the numerous variables and their interdependencies...
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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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Efficient Multi-Fidelity Design Optimization of Microwave Filters Using Adjoint Sensitivity
PublicationA simple and robust algorithm for computationally efficient design optimiza-tion of microwave filters is presented. Our approach exploits a trust-region (TR)-based algorithm that utilizes linear approximation of the filter response obtained using adjoint sensitivity. The algorithm is sequentially executed on a family of electromagnetic (EM)-simulated models of different fidelities, starting from a coarse-discretization one, and...
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Low-Cost Multi-Objective Optimization Yagi-Uda Antenna in Multi-Dimensional Parameter Space
PublicationA surrogate-based technique for fast multi-objective optimization of a multi-parameter planar Yagi-Uda antenna structure is presented. The proposed method utilizes response surface approximation (RSA) models constructed using training samples obtained from evaluation of the low-fidelity antenna model. Utilization of the RSA models allowsfor fast determination of the best possible trade-offs between conflicting objectives in multi-objective...
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Impact of trajectory simplification methods on modeling carbon dioxide emissions from ships
PublicationModels of ship fuel consumption and emissions play an essential role in estimating global shipping’s greenhouse gas emissions. They are also widely used for verification of reported CO2 emissions for systems like EU MRV (Monitoring, Reporting and Verification) or IMO DCS (Data Collection System). Such models achieve high accuracy using historical spatiotemporal information about each ship from AIS data. However, this approach requires substantial...
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Reduced-cost surrogate modelling of compact microwave components by two-level kriging interpolation
PublicationFull-wave electromagnetic (EM) analysis is a versatile tool for evaluating the performance of high-frequency components. Its potential drawback is its high computational cost, inhibiting the execution of EM-driven tasks requiring massive simulations. The applicability of equivalent network models is limited owing to the topological complexity of compact microstrip components because of EM cross-coupling effects. Development of...
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A general isogeometric finite element formulation for rotation‐free shells with in‐plane bending of embedded fibers
PublicationThis article presents a general, nonlinear isogeometric finite element formulation for rotation-free shells with embedded fibers that captures anisotropy in stretching, shearing, twisting, and bending - both in-plane and out-of-plane. These capabilities allow for the simulation of large sheets of heterogeneous and fibrous materials either with or without matrix, such as textiles, composites, and pantographic structures. The work...
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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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Polynomial Chaos Expansion in Bio-and Structural Mechanics
PublicationThis monograph presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the...
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Polynomial Chaos Expansion in Bio- and Structural Mechanics
PublicationThis thesis presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the repair...
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Reduced-order models in the finite element analysis
PublicationA novel technique of incorporating macromodels into finite element electromagnetic analysis of waveguide components is presented. Macromodels are generated by using a model order reduction algorithm (ENOR), which results in significant decrease of the number of variables, that describe the computational region. Proposed technique allows for using a few independent macromodels as well as to duplicating one macromodel in many subregions...
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Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublicationIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
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On optimal tracking of rapidly varying telecommunication channels
PublicationWhen parameters of mobile telecommunication channels change rapidly, classical adaptive filters, such as exponentially weighted least squares algorithms or gradient algorithms, fail to estimate them with sufficient accuracy. In cases like this, one can use identification methods based on explicit models of parameter changes such as the method of basis functions (BF). When prior knowledge about parameter changes is available the...
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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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A design framework and a digital toolset supporting the early-stage explorations of responsive kinetic building skin concepts
PublicationIn this paper we present the first phase of our research on the development of a framework for early-stage responsive kinetic building skin design. The aims of this study were: to formulate a methodological and instrumental basis for the construction of the framework, to conduct an initial pre-assessment of its features, and finally to provide the first example of how the framework could be applied in practice. Importantly, at...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Comparison and Analysis of Service Selection Algorithms
PublicationIn Service Oriented Architecture, applications are developed by integration of existing services in order to reduce development cost and time. The approach, however, requires algorithms that select appropriate services out of available, alternative ones. The selection process may consider both optimalization requirements, such as maximalization of performance, and constraint requirements, such minimal security or maximum development...
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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method
PublicationElectrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric...
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Young’s modulus distribution in the FEM models of bone tissue
PublicationThis paper presents how differences of Young’s modulus in adjacent finite elements typical for organic materials such as bone tissue, influence stress calculating. Emphasizing high computational cost of variable Young’s modulus in parts of the model, where the number of finite elements has been raised, the authors wants to prove that new model of finite element which has variable Young’s modulus in its volume needs to be created....
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Size Reduction of Microwave Couplers by EM-Driven Optimization
PublicationThis work addresses simulation-driven design optimization of compact microwave couplers that explicitly aims at circuit footprint area reduction. The penalty function approach allows us to minimize the area of the circuit while ensuring a proper power division between the output ports and providing a sufficient bandwidth with respect to return loss and isolation around the operating frequency. Computational cost of the optimization...
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A simplified channel estimation procedure for NB-IoT downlink
PublicationThis paper presents a low-complexity channel estimation procedure which is suitable for use in energy-efficient NB-IoT user equipment devices. The procedure is based on the well-established least squares scheme, followed by linear interpolation in the time domain and averaging in the frequency domain. The quality of channel estimation vs. signal-to-noise ratio is evaluated for two channel models and compared with the performance...
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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...
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Structural, functional, and stability change predictions in human telomerase upon specific point mutations,
PublicationOverexpression of telomerase is one of the hallmarks of human cancer. Telomerase is important for maintaining the integrity of the ends of chromosomes, which are called telomeres. A growing number of human disease syndromes are associated with organ failure caused by mutations in telomerase (hTERT or hTR). Mutations in telomerase lead to telomere shortening by decreasing the stability of the telomerase complex, reducing its accumulation,...
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Numerical Analysis of Turbulent Flow over a Backward-facing Step in an Open Channel
PublicationComputational examinations of the flow field in an open channel having a single Backward--Facing Step (BFS) with a constant water depth of 1.5 m were performed. The effects of the expansion ratio, and the flow velocity along the reattachment length, were investigated by employing two different expansion ratios of 1.5 and 2, and eight various flow velocities of 0.5, 1, 2, 3, 4, 5, 7.5 and 10 m/sec in the Computational Fluid Dynamic...
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Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
PublicationDesigning microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublicationDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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Expedited Acquisition of Database Designs for Reduced-Cost Performance-Driven Modeling and Rapid Dimension Scaling of Antenna Structures
PublicationFast replacement models have been playing an increasing role in high-frequency electronics, including the design of antenna structures. Their role is to improve computational efficiency of the procedures that normally entail large numbers of expensive full-wave electromagnetic (EM) simulations, e.g., parametric optimization or uncertainty quantification. Recently introduced performance-driven modeling methods, such as the nested...
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Optimization-based stacked machine-learning method for seismic probability and risk assessment of reinforced concrete shear walls
PublicationEfficient seismic risk assessment aids decision-makers in formulating citywide risk mitigation plans, providing insights into building performance and retrofitting costs. The complexity of modeling, analysis, and post-processing of the results makes it hard to fast-track the seismic probabilities, and there is a need to optimize the computational time. This research addresses seismic probability and risk assessment of reinforced...
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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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Lessons learned from developing an Industry 4.0 mobile process management system supported by Artificial Intelligence
PublicationResearch, development and innovation (RDI) projects are undertaken in order to improve existing, or develop new, more efficient products and services. Moreover, the goal of innovation is to produce new knowledge through research, and disseminating it through education and training. In this line of thinking, this paper reports and discusses the lessons learned from the undertaken project, regarding three areas: machine learning...
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Deformable model of a butterfly in motion on the example of Attacus atlas
PublicationInsect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. High-speed videogrammetry was used to capture the wing kinematics and deformations. The movements of...
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Recent Advances in Performance-Driven Surrogate Modeling of High-Frequency Structures
PublicationDesign of high‐frequency structures, including microwave and antenna components, heavily relies on full‐wave electromagnetic (EM) simulation models. Their reliability comes at a price of a considerable computational cost. This may lead to practical issues whenever numerous EM analyses are to be executed, e.g., in the case of parametric optimization. The difficulties entailed by massive simulations may be mitigated by the use 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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Domain segmentation for low-cost surrogate-assisted multi-objective design optimisation of antennas
PublicationAbstract: Information regarding the best possible design trade-offs of an antenna structure can be obtained through multiobjective optimisation (MO). Unfortunately, MO is extremely challenging if full-wave electromagnetic (EM) simulation models are used for performance evaluation. Yet, for the majority of contemporary antennas, EM analysis is the only tool that ensures reliability. This study introduces a procedure for accelerated...
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Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
PublicationThe phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based...
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Simulation-Driven Antenna Modeling by Means of Response Features and Confined Domains of Reduced Dimensionality
PublicationIn recent years, the employment of full-wave electromagnetic (EM) simulation tools has become imperative in the antenna design mainly for reliability reasons. While the CPU cost of a single simulation is rarely an issue, the computational overhead associated with EM-driven tasks that require massive EM analyses may become a serious bottleneck. A widely used approach to lessen this cost is the employment of surrogate models, especially...
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Multi-fidelity aerodynamic design trade-off exploration using point-by-point Pareto set identification
PublicationAerodynamic design is inherently a multi-objective optimization (MOO) problem. Determining the best possible trade-offs between conflicting aerodynamic objectives can be computationally challenging when carried out directly at the level of high-fidelity computational fluid dynamics simulations. This paper presents a computationally cheap methodology for exploration of aerodynamic design trade-offs. In particular, point-by-point...
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Data-Driven Surrogate-Assisted Optimization of Metamaterial-Based Filtenna Using Deep Learning
PublicationIn 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,...