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检索条件"任意字段=Conference on Simulation-Driven Modeling and Optimization"

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Assessment of Inverse and Direct Methods for Airfoil andWing Design 1

引用

conference on simulation-driven modeling and optimization

作者： Zhang, Mengmeng Rizzi, Arthur William Royal Inst Technol KTH S-10044 Stockholm Sweden

ISBN: (数字)9783319275178

ISBN: (纸本)9783319275178;9783319275154

The goal of aerodynamic design for airfoils and wings is to improve the performance of the lifting surfaces, e.g., by minimizing the drag. We consider here two approaches, the classical inverse design approach that finds the surface which produces desired pressure distributions, and the direct mathematical optimization based on local parameter searches, that is usually enabled by fast gradient computation, for example, by the adjoint method. The hybrid approach is to combine both of them. Each approach has its own pros and cons. In this chapter the approaches are assessed by application to the design of transonic RAE2822 airfoil and ONERA M6 wing.

关键词： Inverse design Gradient-based optimization Parametrization Drag reduction Wing surface curvature Adjoint solver

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A Surrogate-Model-Assisted Evolutionary Algorithm for Computationally Expensive Design optimization Problems with Inequality Constraints 1

引用

conference on simulation-driven modeling and optimization

作者： Liu, Bo Zhang, Qingfu Gielen, Georges Glyndwr Univ Dept Comp Wrexham Wales City Univ Hong Kong Kowloon Hong Kong Peoples R China Katholieke Univ Leuven ESAT MICAS Leuven Belgium

ISBN: (数字)9783319275178

ISBN: (纸本)9783319275178;9783319275154

The surrogate model-aware evolutionary search (SMAS) framework is a newly emerged model management method for surrogate-model-assisted evolutionary algorithms (SAEAs), which shows clear advantages on necessary number of exact evaluations. However, SMAS aims to solve unconstrained or bound constrained computationally expensive optimization problems. In this chapter, an SMAS-based efficient constrained optimization method is presented. Its major components include: (1) an SMAS-based SAEA framework for handling inequality constraints, (2) a ranking and diversity maintenance method for addressing complicated constraints, and (3) an adaptive surrogate model updating (ASU) method to address many constraints, which considerably reduces the computational overhead of surrogate modeling. Empirical studies on complex benchmark problems and a real-world mm-wave integrated circuit design optimization problem are reported in this chapter. The results show that to obtain comparable results, the presented method only needs 1-10% of the exact function evaluations typically used by the standard evolutionary algorithms with popular constraint handling techniques.

关键词： Surrogate model assisted evolutionary computation Constrained optimization Constraint handling Expensive optimization Gaussian Process Surrogate modeling mm-wave IC synthesis

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Expedited simulation-driven Multi-Objective Design optimization of Quasi-Isotropic Dielectric Resonator Antenna 1

引用

conference on simulation-driven modeling and optimization

作者： Bekasiewicz, Adrian Koziel, Slawomir Zieniutycz, Wlodzimierz Leifsson, Leifur Reykjavik Univ Sch Sci & Engn Engn Optimizat & Modeling Ctr Menntavegur 1 IS-101 Reykjavik Iceland Gdansk Univ Technol Fac Elect Telecommun & Informat PL-80233 Gdansk Poland Iowa State Univ Dept Aerosp Engn Ames IA 50011 USA

ISBN: (数字)9783319275178

ISBN: (纸本)9783319275178;9783319275154

Majority of practical engineering design problems require simultaneous handling of several criteria. Although many of design tasks can be turned into single-objective problems using sufficient formulations, in some situations, acquiring comprehensive knowledge about possible trade-offs between conflicting objectives may be necessary. This calls formulti-objective optimization that aims at identifying a set of alternative, Pareto-optimal designs. The most popular solution approaches to genuine multi-objective optimization include population-based metaheuristics. Unfortunately, such methods are not practical for problems involving expensive computational models, particularly for antenna engineering, where reliable design requires CPU-intensive electromagnetic (EM) analysis. In this work, we discuss two methodologies for expedited multi-objective design optimization of a six-parameter dielectric resonator antenna (DRA) with respect to three design criteria. The considered solution approaches rely on surrogate-based optimization (SBO) paradigm, where the design speedup is obtained by shifting the optimization burden into a cheap replacement model referred to as a surrogate. The latter is utilized for generating the initial approximation of the Pareto front representation as well as further refinement of the initially obtained Pareto-optimal solutions.

关键词： Computer-aided design (CAD) Multi-objective optimization Antenna design Evolutionary algorithm Response surface approximation Kriging interpolation Design space reduction Dielectric resonator antenna

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A case study of the generation, description, modeling and assessment of technology system of systems

A case study of the generation, description, modeling and as...

引用

International conference on Intelligent System and Knowledge Engineering, ISKE

作者： Leilei Chang Tianjun Liao Jiang Jiang Xi'an High-tech Institute Xi'an China State Key Laboratory of Complex System Simulation Beijing Institute of System Engineering Beijing China National University of Defense Technology Changsha China

In pushing the social and military developments towards its new frontiers and boundaries are the technologies. As a collection of multiple technologies driven by capability/system requirements, the concept of the Technology System of Systems (TSoS) is proposed. This study further investigates the generation, description, modeling and assessment of TSoS. Specifically, the generation of TSoS is based on the hierarchy hypothesis of TSoS. The description of TSoS is based on concept of views with each to describe a part of TSoS. The readiness assessment of TSoS is to assess the comprehensive readiness of a technology group while the satisfaction assessment of TSoS is to obtain a comprehensive and quantitative result on how much a technology (group) can meet the TSoS requirement. A TSoS with 60 technologies is derived from the 2017 US physical year budget estimates and it is further studied to verify the efficiency of the proposed TSoS generation, description, modeling and assessment methodology.

关键词： Synthetic aperture radar Correlation Aircraft System of systems Weapons optimization

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Cost-Efficient simulation-driven Design of Compact Impedance Matching Transformers 21

Cost-Efficient Simulation-Driven Design of Compact Impedance...

引用

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

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

ISBN: (纸本)9781509022144

In this paper, an algorithmic framework for cost-efficient design optimization of miniaturized impedance matching transformers has been presented. Our approach exploits a bottom-up design that involves translating the overall design specifications for the circuit at hand to its elementary building blocks (here, compact microstrip resonant cells, CMRCs), as well as fast surrogate-assisted optimization of the cells followed by simulation-based tuning of the entire transformer structure. The last stage involves local response surface approximation models and space mapping for model correction. The proposed technique is illustrated using two wideband transformers, a three-and a four-section one. In both cases, the optimization cost corresponds to just a few dozen of full-wave simulations of the respective structures despite a relatively large number of geometry parameters to be adjusted.

关键词： Compact microwave circuits impedance matching transformers simulation-driven design surrogate modeling surrogate-based optimization design tuning

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Optimal Design of Photonic Crystal Nanostructures 1

引用

conference on simulation-driven modeling and optimization

作者： Hassan, Abdel-Karim S. O. Rafat, Nadia H. Mohamed, Ahmed S. A. Cairo Univ Fac Engn Engn Math & Phys Dept Giza 12613 Egypt

ISBN: (数字)9783319275178

ISBN: (纸本)9783319275178;9783319275154

Simulated-driven optimization plays a vital role in the optimal design of engineering systems. The presented work in this chapter considers approaches for obtaining the optimal design of some photonic crystal (PC) nanostructures. PCs are periodic dielectric/dielectric or dielectric/metallic nanostructures manipulating the flow of light. They are one of the most emerging physical systems that have attracted the attention of engineers and scientists, in the last few decades, for their promising applications in many areas. Two optimization approaches are used for achieving the optimal design of one-dimensional (1D) PC nanostructures. The first approach is based on minimax optimization criterion that best fits the design specifications, while the second one is based on design centering criterion, to maximize the probability of satisfying design specifications. The proposed approaches allow considering problems of higher dimensions, in addition, optimizing over the PC layers' thickness and/or its material type. Two practical examples are given to demonstrate the flexibility and efficiency of these approaches. The first is a 1D PC-based optical filter operating in the visible range. The second example is a 1D PC-based spectral control filter, working in the infrared range, and enhances the efficiency of thermophotovoltaic systems.

关键词： Photonic filters design Photonic crystals Simulated-driven optimization Optimal system design Design centering

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Stochastic Decision-Making in Waste Management Using a Firefly Algorithm-driven simulation-optimization Approach for Generating Alternatives 1

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conference on simulation-driven modeling and optimization

作者： Imanirad, Raha Yang, Xin-She Yeomans, Julian Scott Harvard Univ Sch Business Technol & Operat Management Boston MA 02163 USA Middlesex Univ Sch Sci & Technol Dept Design Engn & Math Hendon Campus London NW4 4BT England York Univ Schulich Sch Business OMIS Area Toronto ON M3J 1P3 Canada

ISBN: (数字)9783319275178

ISBN: (纸本)9783319275178;9783319275154

In solving municipal solid waste (MSW) planning problems, it is generally preferable to formulate several quantifiably good alternatives that provide multiple, disparate perspectives. This is because MSW decision-making typically involves complex problems that are riddled with incompatible performance objectives and possess competing design requirements which are very difficult-if not impossible-to quantify and capture at the time when supporting decision models must be constructed. By generating a set of maximally different solutions, it is hoped that some of the dissimilar alternatives can provide very different perspectives that may serve to satisfy the unmodelled objectives. This maximally different solution creation approach is referred to as modelling-to-generate-alternatives (MGA). Furthermore, many MSW decision-making problems contain considerable elements of stochastic uncertainty. This chapter provides a firefly algorithm-driven simulation-optimization approach for MGA that can efficiently create multiple solution alternatives to problems containing significant stochastic uncertainties that satisfy required system performance criteria and yet are maximally different in their decision spaces. It is shown that this new computationally efficient algorithmic approach can simultaneously produce the desired number of maximally different solution alternatives in a single computational run of the procedure. The efficacy of this stochastic MGA approach for "real world," environmental policy formulation is demonstrated using an MSW case study.

关键词： Modelling-to-generate-alternatives Firefly algorithm Municipal solid waste

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Online energy flow control for residential microgrids with URGs: An event-driven approach

Online energy flow control for residential microgrids with U...

引用

Annual conference of Industrial Electronics Society

作者： Xiaodong Yang Hangfei Wu Youbing Zhang Haibo He College of Information Engineering Zhejiang University of Technology Hangzhou China Department of Electrical Computer and Biomedical Engineering University of Rhode Island Kingston RI USA

Energy flow control (EFC) of residential microgrids (RMGs) equipped with renewable generations (RGs) is an essential component for the future smart grid that contributes to enhance renewable energy consumption and reduce cost. Different from most existing papers that devote to offline EFC to against the uncertainties caused by RGs and local load demand in RMGs, this paper focuses on online EFC framework for achieving optimal operations of a RMG. This framework is based on an event-driven approach that maximizes RGs utilization and maintains supply-demand balance considering the schedulable ability of active loads and the uncertainties of RMG. An event-driven EFC architecture for RMG is developed, and the events analysis are presented. Based on this architecture, the state machine is adopted to trigger the execution of the online EFC. Furthermore, an online algorithm is designed for communal energy server platform to determine scheduling plans for active loads. Finally, the performance analysis of the online algorithm is evaluated. simulation results illustrate the basic characteristics and the advantages of the proposed approach.

关键词： Home appliances Uncertainty Microgrids Load modeling State of charge optimization Real-time systems

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Design and simulation of a Thermal Flow Sensor for Gravity-driven Microfluidic Applications 11

Design and Simulation of a Thermal Flow Sensor for Gravity-D...

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11th IEEE Annual International conference on Nano/Micro Engineered and Molecular Systems (NEMS)

作者： Maki, Antti-Juhana Kontunen, Anton Ryynanen, Tomi Verho, Jarmo Kreutzer, Joose Lekkala, Jukka Kallio, Pasi Tampere Univ Technol BioMediTech Dept Automat Sci & Engn Korkeakoulunkatu 3 Tampere 33720 Finland

ISBN: (纸本)9781509019472

Gravity-driven flow is an attractive approach to develop simpler microfluidic systems. Because clogged microchannels could easily lead to fatal operational failures, it is crucial to monitor flow rate in these systems. Therefore, we propose here for the first time a numerical model that combines a calorimetric flow sensor and a gravity-driven system. With the validated model, we studied the flow behavior in a gravity-driven system. Furthermore, we were able to improve the sensitivity of the measurement based on simulation results. This demonstrates, how the model could be used as an effective optimization tool in the gravity-driven system including calorimetric flow measurement.

关键词： calorimetric flow sensor gravity-driven flow modeling numerical simulation

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Lean NOx trap regeneration control: A data-driven MPC approach

Lean NOx trap regeneration control: A data-driven MPC approa...

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IEEE Annual conference on Decision and Control

作者： Milad Karimshoushtari Carlo Novara Politecnico di Torino Italy

Lean NO_x Trap (LNT) is one of the most effective after-treatment technologies used to reduce NO_x emissions of diesel engines. One relevant problem in this context is LNT regeneration timing control. This problem is indeed difficult due to the fact that LNTs are highly nonlinear systems, involving complex physical/chemical processes, that are hard to model. In this paper, a novel approach for regeneration timing of LNTs is proposed, allowing us to overcome these issues. This approach, named data-driven model predictive control (D~2 - MPC), does not require a physical model of the engine/trap system but is based on low-complexity polynomial prediction models, directly identified from data. The regeneration timing is computed through an optimization algorithm, which uses the identified models to predict the LNT behavior. Two D~2 - MPC strategies are proposed, and tested in a co-simulation study, where the plant is represented by a detailed LNT model, built using the well-known commercial tool AMEsim, and the controller is implemented in Matlab/Simulink.

关键词： Mathematical model Predictive models Engines Fuels Timing Computational modeling Data models

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