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Rapid simulation-driven Multiobjective Design optimization of Decomposable Compact Microwave Passives

IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES 2016年第8期64卷 2454-2461页

作者： Koziel, Slawomir Bekasiewicz, Adrian Reykjavik Univ Sch Sci & Engn IS-101 Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Informat PL-80233 Gdansk Poland

In this paper, a methodology for fast multiobjective optimization of the miniaturized microwave passives has been presented. Our approach is applicable to circuits that can be decomposed into individual cells [e.g., compact microstrip resonant cells (CMRCs)]. The structures are individually modeled using their corresponding equivalent circuits and aligned with their accurate, EM simulated representations, by means of implicit space mapping (ISM). The ISM-corrected cells are then assembled into the entire structures and their Pareto-optimal solutions (here, representing the best possible tradeoffs between the structure size and electrical performance) are obtained using evolutionary methods. The refinement is then carried out for the selected structure realizations using, again, SM. The latter stage is necessary, because the cell-based equivalent circuit models do not account for EM cross-couplings between the cells. The proposed methodology allows for rapid identification of compromise geometries concerning size-performance tradeoffs and, more importantly, permits quality comparison of particular CMRC realizations from the point of view of their suitability for a given compact circuit implementation. Our approach is demonstrated using several variations of the three-section wideband impedance matching transformers consisting of two types of CMRC structures. Numerical validation of the results is provided.

关键词： Compact circuits computer-aided design decomposable circuits impedance transformers multiobjective optimization surrogate-based optimization variable-fidelity simulations

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Fast Design optimization of UWB Antennas Using Response Features 21

Fast Design Optimization of UWB Antennas Using Response Feat...

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21st International conference on Microwave, Radar and Wireless Communications (MIKON)

作者： Koziel, Slawomir Bekasiewicz, Adrian Reykjavik Univ Sch Sci & Engn Reykjavik Iceland

ISBN: (纸本)9781509022144

A computationally efficient technique for design optimization of UWB antennas has been presented. Our approach adopts feature-based optimization (FBO) concept where the computational speedup is achieved by reformulating the design specifications in terms of suitably defined response features. Because the dependence of the feature point coordinates on geometry parameters of the antenna is much less nonlinear than for the original characteristics (e.g., S-parameters versus frequency), the optimization algorithm converges faster. Moreover, variable-fidelity electromagnetic (EM) simulation models are utilized to further reduce the optimization cost. In case of UWB antennas, the feature points are defined, among others, as local maxima of the reflection characteristic within the UWB frequency band, as well as the frequency location of the point corresponding to acceptable reflection level in the vicinity of the lower edge of the band (3.1 GHz). The issue related to possible change of the number of the feature points during the optimization run has been also addressed. Operation and performance of our technique is demonstrated using an example monopole antenna. It is also compared to conventional optimization using pattern search.

关键词： Antenna design UWB antennas design optimization simulation-driven design response features feature-based optimization surrogate modeling

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Data-driven Machine Learning for Wind Plant Flow modeling

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Journal of Physics: conference Series 2018年第7期1037卷

作者： R. N. King C. Adcock J. Annoni K. Dykes National Renewable Energy Laboratory Golden CO USA Massachusetts Institute of Technology Cambridge MA USA

In this paper, we introduce a data-driven machine learning framework for improving the accuracy of wind plant flow models by learning turbulence model corrections based on data from higher-fidelity simulations. First, a high-dimensional PDE-constrained optimization problem is solved using gradient-based optimization with adjoints to determine optimal eddy viscosity fields that improve the agreement of a medium-fidelity Reynolds-Averaged Navier Stokes (RANS) model with large eddy simulations (LES). A supervised learning problem is then constructed to find general, predictive representations of the optimal turbulence closure. A machine learning technique using Gaussian process regression is trained to predict the eddy viscosity field based on local RANS flow field information like velocities, pressures, and their gradients. The Gaussian process is trained on LES simulations of a single turbine and implemented in a wind plant simulation with 36 turbines. We show improvement over the baseline RANS model with the machine learning correction, and demonstrate the ability to provide accurate confidence levels for the corrections that enable future uncertainty quantification studies.

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Numerical Aspects of Model Order Reduction for Gas Transportation Networks 1

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conference on simulation-driven modeling and optimization

作者： Grundel, Sara Hornung, Nils Roggendorf, Sarah Max Planck Inst Magdeburg Magdeburg Germany Fraunhofer SCAI St Augustin Germany

ISBN: (数字)9783319275178

ISBN: (纸本)9783319275178;9783319275154

The chapter focuses on the numerical solution of parametrized unsteady Eulerian flow of compressible real gas in pipeline distribution networks. Such problems can lead to large systems of nonlinear equations that are computationally expensive to solve by themselves, more so if parameter studies are conducted and the system has to be solved repeatedly. The stiffness of the problem adds even more complexity to the solution of these systems. Therefore, we discuss the application of model order reduction methods in order to reduce the computational costs. In particular, we apply two-sided projection via proper orthogonal decomposition with the discrete empirical interpolation method to exemplary realistic gas networks of different size. Boundary conditions are represented as inflow and outflow elements, where either pressure or mass flux is given. On the other hand, neither thermal effects nor more involved network components such as valves or regulators are considered. The numerical condition of the reduced system and the accuracy of its solutions are compared to the full-size formulation for a variety of inflow and outflow transients and parameter realizations.

关键词： Gas network simulation Model order reduction Proper orthogonal decomposition Discrete empirical interpolation method Stiff initial-value problems

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POTENTIAL OF DATA-driven simulation-BASED optimization FOR ADAPTIVE SCHEDULING AND CONTROL OF DYNAMIC MANUFACTURING SYSTEMS

POTENTIAL OF DATA-DRIVEN SIMULATION-BASED OPTIMIZATION FOR A...

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Winter simulation conference (WSC)

作者： Kueck, Mirko Ehm, Jens Hildebrandt, Torsten Freitag, Michael Frazzon, Enzo M. Univ Bremen BIBA Bremer Inst Prod & Logist GmbH Fac Prod Engn Hochschulring 20Badgasteiner Str 1 D-28359 Bremen Germany Univ Fed Santa Catarina Ind & Syst Engn Dept Campus UFSC BR-88040970 Florianopolis SC Brazil

ISBN: (纸本)9781509044863

The increasing customization of products, which leads to greater variances and smaller lot sizes, requires highly flexible manufacturing systems. These systems are subject to dynamic influences and demand increasing effort for the generation of feasible production schedules and process control. This paper presents an approach for dealing with these challenges. First, production scheduling is executed by coupling an optimization heuristic with a simulation model. Second, real-time system state data, to be provided by forthcoming cyber-physical systems, is fed back, so that the simulation model is continuously updated and the optimization heuristic can either adjust an existing schedule or generate a new one. The potential of the approach was tested by means of a use case embracing a semiconductor manufacturing facility, in which the simulation results were employed to support the selection of better dispatching rules, improving flexible manufacturing systems performance regarding the average production cycle time.

关键词： Real time systems

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Ontology-driven data input for optimization

Ontology-driven data input for optimization

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49th Annual simulation Symposium, ANSS 2016, Part of the 2016 Spring simulation Multi-conference, SpringSim 2016

作者： Brandmeier, Markus Schafer, Franziska Franke, Jorg Institute for Factory Automation and Production Systems Friedrich-Alexander-Universitat Erlangen-Niirnberg Egerlandstr. 7-9 ErlangenD-91058 Germany

ISBN: (纸本)9781510824256

A major challenge when optimizing production facilities, whether in planning processes or with running facilities, is to describe the machines' initial state and to identify relevant optimization parameters. These factors have crucial influences on the optimization results. For conducting a simulation, relevant input data, representing starting conditions and influencing factors, have to be identified and acquired likewise. However, with growing complexity of systems, data collection is increasingly demanding and time-consuming. This task necessitates both knowledge about the process and the targets of improvement as well as a profound understanding of the system to be optimized. Actually, experts mostly have a thorough knowledge about either the optimization methodology or the production system. This leads to inefficiency when setting up the optimization or simulation base. In this paper, we present the approach of ontology-driven data collection for optimization tasks. Using a meta-ontology of a production facility, the user is guided through the process of data gathering. Depending on the improvement task, the ontology provides relevant parameters that have to be inquired. Thereby we provide a methodology to identify the entirety of input data for the simulation. The process is also applicable to facilities being planned. Thus the knowledge base can be used to support improvement tasks within the digital factory. © 2016 Society for modeling & simulation International (SCS).

关键词： Data acquisition

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Design Method of FCM Representation with optimization Algorithm 16th

Design Method of FCM Representation with Optimization Algori...

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Joint conference of the 16th Asia simulation conference / SCS International Autumn simulation Multi-conference (AsiaSim/SCS AutumnSim)

作者： Yuan, Haibin Wu, QiCai Beihang Univ Beijing Peoples R China Beijing Inst Space Launch Technol Beijing Peoples R China

ISBN: (纸本)9789811026720;9789811026713

A design method of Fuzzy Cognitive Map (FCM) model is simulated and verified with both PSO algorithm and SA algorithm based on computational intelligence. The aim is to develop the design method of FCM effectively and concentrate on the algorithmic way of forming the FCM model while overcome the involvement of subjective factors from the manual or user-driven interference in the case of real world application. simulation experiment of information granules representation for time series analysis is carried out to evaluate the behavior of the proposed method and algorithm performance. With data sample is given, connection matrix is generalized using supervised training process in a reasonable way. The parameters of node number and transmission function are introduced and discussed to assess performance and quality of candidate FCM configuration for further analysis and representation. The proposed approach is alternative way for FCM model based application.

关键词： Fuzzy cognitive map simulation optimization Time series Fuzzy systems Prediction

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SIGSIM-PADS 2016 - Proceedings of the 2016 Annual ACM conference on Principles of Advanced Discrete simulation

SIGSIM-PADS 2016 - Proceedings of the 2016 Annual ACM Confer...

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2016 Annual ACM conference on Principles of Advanced Discrete simulation, SIGSIM-PADS 2016

ISBN: (纸本)9781450337427

The proceedings contain 27 papers. The topics discussed include: an adaptive road traffic regulation with simulation and Internet of things;data-driven vehicle trajectory prediction;GraphPool: a high performance data management for 3D simulations;knowledge discovery for Pareto based multiobjective optimization in simulation;coupling simulation with machine learning: a hybrid approach for elderly discharge planning [applied to hip fracture care in Ireland];granular time warp objects;online data extraction for large-scale agent-based simulations;a simulator for distributed cache management in friend-to-friend networks;agent-based simulation modeling of low fertility trap hypothesis;a role-dependent data-driven approach for high density crowd behavior modeling;automatic generation of reversible C++ code and its performance in a scalable kinetic Monte-Carlo application;and development and experimentation of PDES-based analytic simulation.

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Multi-Objective Antenna Design Using Sequential Domain Patching with Automated Determination of Patch Size 10

Multi-Objective Antenna Design Using Sequential Domain Patch...

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10th European conference on Antennas and Propagation (EuCAP)

作者： Koziel, Slawomir Bekasiewicz, Adrian Gdansk Univ Technol Fac Elect Telecommun & Informat PL-80233 Gdansk Poland Reykjavik Univ Engn Optimizat & Modeling Ctr IS-101 Reykjavik Iceland

ISBN: (纸本)9788890701863

In this paper, a simple yet efficient technique for automated multi-objective design optimization of antennas using design space patching is discussed. The optimization procedure is a two-step process: (i) obtaining the initial set of Pareto-optimal designs representing the best possible trade-offs between conflicting objectives, and (ii) Pareto set refinement for yielding the optimal designs at the high-fidelity electromagnetic (EM) simulation model level. The first step is realized at the level of low-fidelity (coarse-discretization) EM model by sequential construction and relocation of small design space segments (patches) in order to create a path connecting the extreme Pareto front designs obtained beforehand. An automated procedure for determining the patch dimensions is introduced. Pareto set refinement is realized using surrogate-based optimization techniques. Our approach is demonstrated using a UWB monopole antenna with 12 independent geometry parameters.

关键词： Antenna design multi-objective optimization EM-driven design domain patching variable-fidelity simulations surrogate modeling

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16th Asia simulation conference on simulation Multi-conference, AsiaSim/SCS AutumnSim 2016

16th Asia Simulation Conference on Simulation Multi-Conferen...

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16th Asia simulation conference and SCS Autumn simulation Multi-conference, AsiaSim/SCS AutumnSim 2016

ISBN: (纸本)9789811026652

The proceedings contain 70 papers. The special focus in this conference is on Robot simulations, Military simulation, Visualization and Virtual Reality. The topics include: Model-free adaptive iterative learning control based on data-driven for noncircular turning tool feed system;vibration characteristic analysis and optimization of heavy load high voltage circuit breaker contact;self-balancing robot design and implementation based on machine vision;reliability analysis of multi-state system from time response;a hybrid particle swarm optimization algorithm for solving job shop scheduling problems;a chaotic differential evolution algorithm for flexible job shop scheduling;modeling and simulation for super large twin-propeller twin-rudder ship and its course ADRC;precise geometrical alignment of assembly design from tolerance simulation perspective;decision-making modeling of close-in air-combat based on type-2 fuzzy logic system;an external rendering algorithm for IR imaging simulation of complex infrared scene;an improved genetic algorithm in shipboard power network planning;modeling and simulation of four-point source decoying system;the optimized design on the tails of a miniature guided rocket projectile;research on image stitching algorithm for UAV Ground station terminal;cooperative task assignation for R/S UAVs Based on binary wolf pack algorithm;a filtering method of laser radar imaging based on classification of curvature;the database architecture design of the satellite simulation platform;matching suitability of geomagnetic aided navigation based on spectral moment characteristics;approach for intelligent rival-air-plane threats evading;the development of complex and large system based on simulation prototype.

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