• Title/Summary/Keyword: process optimization algorithm and system

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Optimization of Valve Gates Locations Using Automated Runner System Modeling and Metamodels (유동 안내부 모델링 자동화 및 근사모델을 이용한 자동차용 도어트림의 밸브 게이트 위치 최적화)

  • Joe, Yong-Su;Park, Chang-Hyun;Pyo, Byung-Gi;Rhee, Byung-Ohk;Choi, Dong-Hoon
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.2
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    • pp.115-122
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    • 2014
  • Injection pressure is one of factors that influence part quality. In this paper, injection pressure was minimized by optimizing valve gate locations. In order to perform design optimization, MAPS-3DTM (Mold Analysis and Plastic Solution-3D) was used for injection mold analysis and PIAnOTM (Process Integration, Automation and Optimization) was used as process integration and design optimization. Also we adapted meta models based on design of experiments for efficiency. By using introduced methodology, we were able to obtain a result so that maximum injection pressure reduced by 28% compared to the initial design. And the validity of the proposed method could also be demonstrated.

Energy-Aware System Lifetime Maximization Algorithm in Multi-Hop Sensor Network (멀티홉 센서 네트워크에서 에너지 상황을 고려한 시스템 수명 최대화 알고리즘)

  • Kim, Tae-Rim;Kim, Bum-Su;Park, Hwa-Kyu
    • IEMEK Journal of Embedded Systems and Applications
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    • v.8 no.6
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    • pp.339-345
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    • 2013
  • This paper addresses the system lifetime maximization algorithm in multi-hop sensor network system. A multi-hop sensor network consists of many battery-driven sensor nodes that collaborate with each other to gather, process, and communicate information using wireless communications. As sensor-driven applications become increasingly integrated into our lives, we propose a energy-aware scheme where each sensor node transmits informative data with adaptive data rate to minimize system energy consumption. We show the optimal data rate to maximize the system lifetime in terms of remaining system energy. Furthermore, the proposed algorithm experimentally shows longer system lifetime in comparison with greedy algorithm.

An Optimum Design of a Steering Column to Minimize the Injury of a Passenger (승객 상해의 감소를 위한 승용차 조향주의 최적설계)

  • Park, Y.S;Lee, J.Y.;Park, G.J.
    • Transactions of the Korean Society of Automotive Engineers
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    • v.3 no.1
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    • pp.33-44
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    • 1995
  • As the occupant safety receives more attention from automobile industries. protection systems have been developed quite well. Developed protection systems must be evaluated through real tests in crash environment Since the real tests are extremely expensive. computer simulations are replaced for some prediction of the real test In the computer simulation. it is very crucial to express the real environment precisely in the modeling precess. The energy absorbing(EA) steering system has a very important rote in vehicle crashes because the occupant can hit the system directly. In this study. the EA steering system is modeled precisely. analyzed for the safely and designed by an optimization technology. First. the EA steering system is disassembled by parts and modeled by segments and joints. The segments are modeled by rigid bodies in motion and they have resistances in contact. Spring-damper elements and force-deflection curves are utilized to represent the joints. The body block test is cal lied out to validate. the modeling. When the test results are not enough for the detailed modeling. the differences between tests and simulations are minimized to calculate unknown parameters using optimization. The established model is applied to a crash simulation of a full-car model and tuned again. After the modeling is finished. components of the steering system are designed by an optimization algorithm. In the optimization process. the compound injury of a driver is defined and minimized to determine the chracteristics of the components. The second. order approximation algorithm has been adopted for the optimization.

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Identification of Fuzzy Inference Systems Using a Multi-objective Space Search Algorithm and Information Granulation

  • Huang, Wei;Oh, Sung-Kwun;Ding, Lixin;Kim, Hyun-Ki;Joo, Su-Chong
    • Journal of Electrical Engineering and Technology
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    • v.6 no.6
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    • pp.853-866
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    • 2011
  • We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-objective strategy. In the identification of the fuzzy inference system, the MSSA is exploited to carry out parametric optimization of the fuzzy model and to achieve its structural optimization. The granulation of information is attained using the C-Means clustering algorithm. The overall optimization of fuzzy inference systems comes in the form of two identification mechanisms: structure identification (such as the number of input variables to be used, a specific subset of input variables, the number of membership functions, and the polynomial type) and parameter identification (viz. the apexes of membership function). The structure identification is developed by the MSSA and C-Means, whereas the parameter identification is realized via the MSSA and least squares method. The evaluation of the performance of the proposed model was conducted using three representative numerical examples such as gas furnace, NOx emission process data, and Mackey-Glass time series. The proposed model was also compared with the quality of some "conventional" fuzzy models encountered in the literature.

Optimal design of a wind turbine supporting system accounting for soil-structure interaction

  • Ali I. Karakas;Ayse T. Daloglua
    • Structural Engineering and Mechanics
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    • v.88 no.3
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    • pp.273-285
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    • 2023
  • This study examines how the interaction between soil and a wind turbine's supporting system affects the optimal design. The supporting system resting on an elastic soil foundation consists of a steel conical tower and a concrete circular raft foundation, and it is subjected to wind loads. The material cost of the supporting system is aimed to be minimized employing various metaheuristic optimization algorithms including teaching-learning based optimization (TLBO). To include the influence of the soil in the optimization process, modified Vlasov and Gazetas elastic soil models are integrated into the optimization algorithms using the application programing interface (API) feature of the structural analysis program providing two-way data flow. As far as the optimal designs are considered, the best minimum cost design is achieved for the TLBO algorithm, and the modified Vlasov model makes the design economical compared with the simple Gazetas and infinitely rigid soil models. Especially, the optimum design dimensions of the raft foundation extremely reduce when the Vlasov realistic soil reactions are included in the optimum analysis. Additionally, as the designated design wind speed is decreased, the beneficial impact of soil interaction on the optimum material cost diminishes.

QoE-aware Energy Efficiency Maximization Based Joint User Access Selection and Power Allocation for Heterogeneous Network

  • Ji, Shiyu;Tang, Liangrui;Xu, Chen;Du, Shimo;Zhu, Jiajia;Hu, Hailin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4680-4697
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    • 2017
  • In future, since the user experience plays a more and more important role in the development of today's communication systems, quality of experience (QoE) becomes a widely used metric, which reflects the subjective experience of end users for wireless service. In addition, the energy efficiency is an increasingly important problem with the explosive growth in the amount of wireless terminals and nodes. Hence, a QoE-aware energy efficiency maximization based joint user access selection and power allocation approach is proposed to solve the problem. We transform the joint allocation process to an optimization of energy efficiency by establishing an energy efficiency model, and then the optimization problem is solved by chaotic clone immune algorithm (CCIA). Numerical simulation results indicate that the proposed algorithm can efficiently and reliably improve the QoE and ensure high energy efficiency of networks.

Seismic behavior enhancement of frame structure considering parameter sensitivity of self-centering braces

  • Xu, Longhe;Xie, Xingsi;Yan, Xintong;Li, Zhongxian
    • Structural Engineering and Mechanics
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    • v.71 no.1
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    • pp.45-56
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    • 2019
  • A modified mechanical model of pre-pressed spring self-centering energy dissipation (PS-SCED) brace is proposed, and the hysteresis band is distinguished by the indication of relevant state variables. The MDOF frame system equipped with the braces is formulated in an incremental form of linear acceleration method. A multi-objective genetic algorithm (GA) based brace parameter optimization method is developed to obtain an optimal solution from the primary design scheme. Parameter sensitivities derived by the direct differentiation method are used to modify the change rate of parameters in the GA operator. A case study is conducted on a steel braced frame to illustrate the effect of brace parameters on node displacements, and validate the feasibility of the modified mechanical model. The optimization results and computational process information are compared among three cases of different strategies of parameter change as well. The accuracy is also verified by the calculation results of finite element model. This work can help the applications of PS-SCED brace optimization related to parameter sensitivity, and fulfill the systematic design procedure of PS-SCED brace-structure system with completed and prospective consequences.

Optimum Design of the Power Yacht Based on Micro-Genetic Algorithm

  • Park, Joo-Shin;Kim, Yun-Young
    • Journal of Navigation and Port Research
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    • v.33 no.9
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    • pp.635-644
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    • 2009
  • The optimum design of power yacht belongs to the nonlinear constrained optimization problems. The determination of scantlings for the bow structure is a very important issue with in the whole structural design process. The derived design results are obtained by the use of real-coded micro-genetic algorithm including evaluation from Lloyd's Register small craft guideline, so that the nominal limiting stress requirement can be satisfied. In this study, the minimum volume design of bow structure on the power yacht was carried out based on the finite element analysis. The target model for optimum design and local structural analysis is the bow structure of a power yacht. The volume of bow structure and the main dimensions of structural members are chosen as an objective function and design variable, respectively. During optimization procedure, finite element analysis was performed to determine the constraint parameters at each iteration step of the optimization loop. optimization results were compared with a pre-existing design and it was possible to reduce approximately 19 percents of the total steel volume of bow structure from the previous design for the power yacht.

Fitness Sharing Particle Swarm Optimization Approach to FACTS Installation for Transmission System Loadability Enhancement

  • Chang, Ya-Chin
    • Journal of Electrical Engineering and Technology
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    • v.8 no.1
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    • pp.31-39
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    • 2013
  • Proper installation of Flexible AC Transmission Systems (FACTS) devices in existing transmission networks can enable power systems to accommodate more power transfer with less network expansion cost. The problem to maximize transmission system loadability by determining optimal locations and settings for installations of two types of FACTS devices, namely static var compensator (SVC) and thyristor controlled series compensator (TCSC), is formulated as a mixed discrete-continuous nonlinear optimization problem (MDCP). For solving the MDCP, in the paper, the proposed method with fitness sharing technique involved in the updating process of the particle swarm optimization (PSO) algorithm, can diversify the particles over the search regions as much as possible, making it possible to achieve the optimal solution with a big probability. The modified IEEE-14 bus network and a practical power system are used to validate the proposed method.

Form Finding of a Single-layered Pneumatic Membrane Structures by Using Nonlinear Force Method (비선형 내력법을 이용한 단일 공기막의 형상 탐색)

  • Shon, Sudeok;Ha, Junhong;Lee, Seungjae
    • Journal of Korean Association for Spatial Structures
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    • v.21 no.4
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    • pp.49-56
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    • 2021
  • This study aims to develop a form-finding algorithm for a single-layered pneumatic membrane. The initial shape of this pneumatic membrane, which is an air-supported type pneumatic membrane, is to find a state in which a given initial tension and internal pneumatic pressure are in equilibrium. The algorithm developed to satisfy these conditions is that a nonlinear optimization problem based on the force method considering the deformed shape is formulated, and, it's able to find the shape by iteratively repeating the process of obtaining a solution of the governing equations. An computational technique based on the Gauss-Newton method was used as a method for obtaining solutions of nonlinear equations. In order to verify the validity of the proposed form-finding algorithm, a single-curvature pneumatic membrane example and a double-curvature air pneumatic membrane example were adopted, respectively. In the results of these examples, it was possible to well observe the step-by-step convergence process of the shape of the pneumatic membrane, and it was also possible to confirm the change in shape according to the air pressure. In addition, the calculation results of the shape and internal force after deformation due to initial tension, air pressure, and self-weight were obtained.