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

共 1171 条记录，以下是541-550 订阅

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Expedited Frequency Scaling of Circular Polarization Antennas by Inverse and Forward Surrogates

Expedited Frequency Scaling of Circular Polarization Antenna...

引用

IEEE MTT-S International conference on Numerical Electromagnetic and Multiphysics modeling and optimization (NEMO)

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

ISBN: (纸本)9781538652046

The paper demonstrates utilization of inverse and forward surrogate models for accelerated dimension scaling of circular polarization antennas. The problem at hand is to find optimum dimensions of the antenna re-designed for a particular operating frequency, which includes maximization of the realized gain in the broadside direction as well as ensuring acceptable matching and axial ratio bandwidths. According to the proposed methodology, the initial design is found using a fast inverse surrogate model established using several reference designs optimized for selected operating frequencies. Subsequently, design correction is realized using a forward surrogate of the antenna response Jacobians. Overall, the dimension scaling process is achieved at a very low cost of a few full-wave electromagnetic (EM) analyses of the structure at hand. Our technique is demonstrated using a two-point-input circularly polarized patch antenna excited through a hybrid coupler. The antenna is redesigned within the operating frequency range of 4.5 GHz to 6.5 GHz.

关键词： Circular polarization antennas antenna design dimension scaling simulation-driven design inverse surrogates

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GENERALIZATION OF EF-BASED ASSIGNMENT STRATEGIES FOR CYCLE TIME optimization AT COMPLEX WET STATIONS 18

GENERALIZATION OF EF-BASED ASSIGNMENT STRATEGIES FOR CYCLE T...

引用

Winter simulation conference (WSC)

作者： Rotondo, Anna Geraghty, John Young, Paul Irish Mfg Res Aerodrome Business Pk Rathcoole D24 WC04 Ireland Dublin City Univ Enterprise Res Ctr Dublin D09 W6Y4 Ireland

ISBN: (纸本)9781538665725

When solution approaches are developed to facilitate decision processes in real manufacturing systems, fundamental information constraints may apply. The data required by theoretically efficient decision support tools may not be available or accessible;as a consequence, the possibility of implementing the solutions developed is compromised. In this paper, assignment strategies subjected to information constraints and previously developed for a particular wet station are generalized to wet stations characterized by different tool configurations and production recipes. These strategies have been designed to be integrated with data management systems and make use of real time data to minimize the stations' average cycle time. The experiments run aim at supporting the hypothesis that progressive incorporation of details on the system status in assignment strategies enhances the strategies' performance. The relevance of data-driven simulation-based decision support is demonstrated with reference to wet stations operating in a real semiconductor manufacturing facility.

关键词： Tools Chemicals optimization Job shop scheduling Robots Real-time systems

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Data-driven Machine Learning for Wind Plant Flow modeling 7

Data-Driven Machine Learning for Wind Plant Flow Modeling

引用

7th conference on Science of Making Torque from Wind (TORQUE)

作者： King, R. N. Adcock, C. Annoni, J. Dykes, K. Natl Renewable Energy Lab Golden CO 80401 USA MIT 77 Massachusetts Ave Cambridge MA 02139 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.

关键词： Turbulence models

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Fuzzy modeling by Data-Extracted Fuzzy Rules of Cement Rotary Kiln Based on WM Method 10

Fuzzy Modeling by Data-Extracted Fuzzy Rules of Cement Rotar...

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10th International conference on Modelling, Identification and Control (ICMIC)

作者： Chen, Mingyun Guo, Feng Chen, Mengqi Shen, Zheng She, Jianshu Northeastern Univ Qinghuangdao Dept Elect Engn & Automat Qinhuangdao Hebei Peoples R China

ISBN: (纸本)9781538654163

This research applys a fuzzy modeling method based on sampling data to the modeling of cement rotary kiln. By analyzing the sampling data in the actual production process, the mathematical model of the cement rotary kiln calcining system is established using the WM fuzzy modeling algorithm. The modeling method realizes the identification and optimization of the fuzzy rules. The simulation analysis is carried out through the Matlab software. The results show that this method has a high precision. It provides a reference to establish the system's mathematical models.

关键词： Cement rotary kiln WM method fuzzy modeling intelligent control data-driven

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Optimized Routing Technique for Adaptive Data Transmission in Industrial IoT

Optimized Routing Technique for Adaptive Data Transmission i...

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Information Processing (ICINPRO), International conference on

作者： J. Shreyas B. Kavitha P.K. Udayaprasad Dilip Kumar S.M. Dept. of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore India

ISBN: (数字)9781728138077

ISBN: (纸本)9781728138084

In recent years, industrial internet of things (IIoT) has become an important research topic among industry and academia. In IIoT there is a huge demand for data exchange among different smart devices with different delay flows. However, there is a less amount of research has been carried out in this field. In order to address the limitations of the traditional routing method, The proposed work gives a numerical modeling applicable to perform adaptive transmission optimization with a set of the programmable module structure and ensure cost-effective route establishment. The proposed work utilizes bio inspired swarm intelligence based data-driven cluster head (CH) selection with energy optimized route formation to obtain an optimal route. The extensive simulation outcome shows that particle swarm optimization (PSO) based clustering attain better delay, path difference degree and packet delivery ratio as compared to other conventional methods.

关键词： Routing Data communication Particle swarm optimization Adaptation models Internet of Things Delays Numerical models

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Health-aware optimization-based Control Design: Application to Autonomous Racing based State of Charge

Health-aware Optimization-based Control Design: Application ...

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conference on Control and Fault-Tolerant Systems (SysTol)

作者： Fatemeh Karimi Pour Didier Theilliol Vicenç Puig Gabriela Cembrano Universite de Lorraine UMR 7039 Vandoeuvre-les-Nancy Cedex France

In this paper, an innovative health-aware control approach is presented for autonomous racing vehicles. Based on a dynamical model of the vehicle, a controller is computed with the general objective is maximize progress on the track subject to win racing and save energy. The main contribution of the paper consists in preserving the state of charge (SoC) and optimizing a lap time to achieve the best path of a racing vehicle. The control design is divided into two parts, path planner and controller. The first optimization problem is related to the path planner where the objective is to optimize the lap time and maximize the SoC to obtain the best trajectory under the constraints of the circuit. The proposed approach is solved by LMI based Model Predictive Control (MPC) driven from Lyapunov stability. The second part is focused on a controller gain synthesis solved by LMI formulation with integral action for tracking the trajectory obtained by the planner. The proposed approach is evaluated in simulation and results show the effectiveness of the proposed planner for optimizing the lap time and especially for maximizing the SoC of the battery.

关键词： Batteries Trajectory optimization State of charge Kinematics Predictive control Integrated circuit modeling

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Geometry-based Direct simulation for Multi-Material Soft Robots

Geometry-based Direct Simulation for Multi-Material Soft Rob...

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IEEE International conference on Robotics and Automation (ICRA)

作者： Fang, Guoxin Matte, Christopher-Denny Kwok, Tsz-Ho Wang, Charlie C. L. Delft Univ Technol Dept Design Engn Delft Netherlands Delft Univ Technol Robot Inst Delft Netherlands Concordia Univ Dept Mech Ind & Aerosp Engn Montreal PQ Canada

ISBN: (纸本)9781538630815

Robots fabricated by soft materials can provide higher flexibility and thus better safety while interacting with natural objects with low stiffness such as food and human beings. However, as many more degrees of freedom are introduced, the motion simulation of a soft robot becomes cumbersome, especially when large deformations are presented. Moreover, when the actuation is defined by geometry variation, it is not easy to obtain the exact loads and material properties to be used in the conventional methods of deformation simulation. In this paper, we present a direct approach to take the geometric actuation as input and compute the deformed shape of soft robots by numerical optimization using a geometry-based algorithm. By a simple calibration, the properties of multiple materials can be modeled geometrically in the framework. Numerical and experimental tests have been conducted to demonstrate the performance of our approach on both cable-driven and pneumatic actuators in soft robotics.

关键词： Shape Soft robotics Strain Computational modeling optimization Numerical models Deformable models"

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Destination driven Computation Offloading in Internet of Things

Destination Driven Computation Offloading in Internet of Thi...

引用

2019 IEEE Global Communications conference (GLOBECOM)

作者： Yunkai Wei Jie Zhang Ning Yang Supeng Leng School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Computation offloading can be widely used in Internet of Things (IoT), since most IoT devices do not have enough resource for complex computing. According to the target of computing results, computation offloading can be divided into source driven pattern and destination driven pattern. Currently, most studies focus on the former, where the results should be returned to the task source after computing. Another widely existing pattern, i.e., destination driven computation offloading, where the results should be transmitted to some other node instead of the task source, is rarely noticed. In this paper we propose a scheme of Destination driven Step-by-step Computation Offloading along the Route (DDSCOR), which optimizes the delay from the source node releasing the task to the results arriving the destination node. Specifically, the proposed scheme combines the data transmission and computation offloading together, dividing the computing task into several procedures and offloading them to appropriate nodes along the data transmission route. simulation results show that the proposed scheme can approximately achieve the optimal offloading- transmission combined route, and tremendously reduce the overall latency in resource limited IoT.

关键词： Task analysis Servers Delays optimization Security Computational modeling Internet of Things

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An Improvement on Extended Impedance Method towards Efficient Steady-State Analysis of High-Frequency Class-E Resonant Inverters 8

An Improvement on Extended Impedance Method towards Efficien...

引用

8th International Power Electronics conference (IPEC-Niigata) / Energy Conversion Congress and Exposition (ECCE Asia)

作者： Liang, Junrui ShanghaiTech Univ Sch Informat Sci & Technol Shanghai 201210 Peoples R China

ISBN: (纸本)9784886864055

The extended impedance method (EIM) is an efficient and intuitive tool for the design and analysis of power switching circuits with active components, nonlinear parasitic components, etc., under high-frequency operation. In this paper, we propose an improvement to the EIM by simplifying the constitutive circuit equations in the iterative calculation, such that to speed up the steady-state searching process. Taking the class-E resonant inverter, which is driven by a practical MOSFET switch, as the testbed, we comparatively evaluate the computational efforts of this improved EIM, the conventional EIM, and PSpice simulation, under the same circuit conditions. The result shows that the proposed method can greatly reduce the simulation time. Therefore, the improved EIM can be used as an efficient tool for the analysis, design, and optimization of high-frequency power electronics.

关键词： MOSFET Mathematical model Integrated circuit modeling Capacitance Switching circuits Power electronics optimization

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Towards OntoUML for Software Engineering: Optimizing Kinds and Subkinds Transformed into Relational Databases 14th

Towards OntoUML for Software Engineering: Optimizing Kinds a...

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14th International Workshop on Enterprise and Organizational modeling and simulation (EOMAS) Held at conference on Advanced Information Systems Engineering (CAiSE)

作者： Rybola, Zdenek Pergl, Robert Czech Tech Univ Fac Informat Technol Prague Czech Republic

ISBN: (纸本)9783030007874;9783030007867

Model-driven development approach to software engineering requires precise models defining as much of the system as possible. OntoUML is a conceptual modelling language based on UFO, which provides constructs to create ontologically well-founded and precise conceptual models. In the approach we utilize, OntoUML is used for making conceptual models of software application data. Such a model is then transformed into its proper realization in a relational database, preserving all the implicit constraints defined by various types of universals and relations in the original OntoUML model. In this paper, we discuss possible optimizations of the transformation of Kinds and Subkinds - rigid sortal universal types, a backbone of OntoUML models.

关键词： MDD OntoUML optimization Relational database Transformation

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