• Title/Summary/Keyword: An Model

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A Hybrid Turbulence Model for Prediction of Buoyancy-Driven Turbulent Thermal Convection Flow (부력에 의한 난류 열대류의 혼성 난류모델)

  • 김태규;성형진
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.8
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    • pp.2069-2078
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    • 1993
  • The buoyancy-driven turbulent thermal convection is predicted using an anisotropic hybrid turbulence model, which is incorporated with a low Reynolds k-.epsilon. turbulence model and an anisotropic buoyant part of algebraic stress model(ASM). The numerical predictions are compared with the Davidson's model,(1) the full ASM and the experimental results of Cheesewright et al.(2) All the models are shown to predict good agreements with the experiments for the averaged turbulence quantities. It is found that the effect of an anisotropic part on the Reynolds stress and the turbulent heat fluxes is substantial. In this study, the present hybrid model gives a fairly reasonable prediction in terms of the computational accuracy, convergence and stability. The contribution of an anisotropic buoyant part to turbulent heat fluxes are also scrutinized over the range of Rayleigh numbers $(4.79{\times}10^{10}{\le}Ra{\le}7.46{\times}10^{10}).$

Balancing and Sequencing in Mixed Model Assembly Lines Using an Endosymbiotic Evolutionary Algorithm (내공생 진화알고리듬을 이용한 혼합모델 조립라인의 작업할당과 투입순서 결정)

  • 김여근;손성호
    • Journal of the Korean Operations Research and Management Science Society
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    • v.26 no.4
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    • pp.109-124
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    • 2001
  • This paper presents a new method that can efficiently solve the integrated problem of line balancing and model sequencing in mixed model assembly lines (MMALs). Line balancing and model sequencing are important for an efficient use of MMALs. The two problems of balancing and sequencing MMALs are tightly related with each other. However, In almost all the existing researches on mixed-model production lines, the two problems have been considered separately. In this research, an endosymbiotic evolutionary a1gorithm, which is a kind of coevolutionary a1gorithm, is adopted as a methodology in order to solve the two problems simultaneously. This paper shows how to apply an endosymbiotic evolutionary a1gorithm to solving the integrated problem. Some evolutionary schemes are used In the a1gorithm to promote population diversity and search efficiency. The proposed a1gorithm is compared with the existing evolutionary algorithms in terms of solution quality and convergence speed. The experimental results confirm the effectiveness of our approach.

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Model Synthesis and Performance analysis of an Engine Mount Using Electro-Rheological Fluids (전기유동유체를 이용한 엔진마운트의 모델구성과 성능해석)

  • 최영태;김기선;최승복;정재천;전영식
    • Transactions of the Korean Society of Automotive Engineers
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    • v.2 no.3
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    • pp.62-74
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    • 1994
  • This paper addresses on the model synthesis and performance analysis of an engine mount featuring electro-rheological(ER) fluids which undergo a phase change when subjected to electric fields. A novel type of ER fluid-filled engine mount is devised and its hydraulic model is constructed. An equivalent mechanical model is subsequently obtained from the governing equation of the hydraulic model. The model parameters associated with the ER fluids are distilled from experimental investigations on the Bingham properties of the fluids. The distilled data are then incorporated into the governing model to undertake feasible work through computer simulations,. It is shown that the proposed engine mount has an inherent capability of controlling both the damping force and the resonance frequency. Other superior performance characteristics accrued from the proposed methodology are also evaluated.

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Identification of Interval Model for Parametric Uncertain Systems (파라미터 불확실성 시스템의 구간모델 식별)

  • 김동형;우영태;김영철
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.8
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    • pp.462-470
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    • 2003
  • This paper presents an algorithm of identifying parametric uncertainty by way of an interval model. For a given set of frequency response data from an uncertain linear SISO system of which the upper and the lower bounds of both magnitude and phase responses are represented, the proposed algorithm consists of two main parts: first, the nominal model is identified by using Least Square Estimation (LSE), and then an interval model is constructed by expanding the extremal properties of interval systems, so that tightly enclose the given envelopes within those of interval model. Two numerical examples are given to demonstrate and verify the developed algorithm. The identified interval model can be used for evaluating the worst case performance and stability margins against parametric uncertainty by using some extremal properties on interval systems.

A constitutive model for confined concrete in composite structures

  • Shi, Qing X.;Rong, Chong;Zhang, Ting
    • Steel and Composite Structures
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    • v.24 no.6
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    • pp.689-695
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    • 2017
  • The constitutive relation is an important factor in analysis of confined concrete in composite structures. In order to propose a constitutive model for nonlinear analysis of confined concrete, lateral restraint mechanism of confined concrete is firstly analyze to study the generalities. As the foundation of the constitutive model, peak stress and peak strain is the first step in research. According to the generalities and the Twin Shear Unified Strength Theory, a novel unified equation for peak stress and peak strain are established. It is well coincident with experimental results. Based on the general constitutive relations and the unified equation for peak stress and peak strain, we propose a unified and convenient constitutive model for confined concrete with fewer material parameters. Two examples involved with steel tube confined concrete and hoop-confined concrete are considered. The proposed constitutive model coincides well with the experimental results. This constitutive model can also be extended for nonlinear analysis to other types of confined concrete.

Description Capability of a Simple Phenomenological Constitutive Model for High-Strain-Rate Plasticity Data (간단한 현상학적 구성방정식의 고속 유동응력 기술 능력)

  • Shin, Hyun-Ho;Kim, Jong-Bong
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2009.10a
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    • pp.190-193
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    • 2009
  • A recently reported simple phenomenological constitutive model (SK) demonstrated comparable or better data description capability to/than one of the rigorous and physics-based models, the PTW model. The simple SK model is believed to be an efficient model for practical applications where an extensive computation is needed, and can serve as a rigorous comparison standard for the development of a physics-based model.

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An Evaluation on Pilot Informatization Projects : A View of User Satisfaction (사용자 만족도 관점에서의 정보화 시범사업평가)

  • 양경식;김현수
    • Journal of Information Technology Applications and Management
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    • v.9 no.3
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    • pp.31-46
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    • 2002
  • The objective of this paper is to develop an evaluation model for pilot informatization projects. There are relatively many researches on evaluation models for information systems. These previous researches, however, lack of comprehensive view of informatization Projects and pilot systems. We apply and test a hybrid evaluation model for to measure the success of pilot informatization projects. A user satisfaction model has been used and hypotheses are developed to find relationships of evaluation factors. The hypotheses have been tested with 51 user surveys. The result of this research can give an insight for the evaluation of pilot informatization projects.

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Evolution of the Behavioral Knowledge for a Virtual Robot

  • Hwang Su-Chul;Cho Kyung-Dal
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.5 no.4
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    • pp.302-309
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    • 2005
  • We have studied a model and application that evolves the behavioral knowledge of a virtual robot. The knowledge is represented in classification rules and a neural network, and is learned by a genetic algorithm. The model consists of a virtual robot with behavior knowledge, an environment that it moves in, and an evolution performer that includes a genetic algorithm. We have also applied our model to an environment where the robots gather food into a nest. When comparing our model with the conventional method on various test cases, our model showed superior overall learning.

PSO based neural network to predict torsional strength of FRP strengthened RC beams

  • Narayana, Harish;Janardhan, Prashanth
    • Computers and Concrete
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    • v.28 no.6
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    • pp.635-642
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    • 2021
  • In this paper, soft learning techniques are used to predict the ultimate torsional capacity of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. Soft computing techniques, namely Artificial Neural Network, trained by various back propagation algorithms, and Particle Swarm Optimization (PSO) algorithm, have been used to model and predict the torsional strength of Reinforced Concrete beams strengthened with Fiber Reinforced Polymer. The performance of each model has been evaluated by using statistical parameters such as coefficient of determination (R2), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The hybrid PSO NN model resulted in an R2 of 0.9292 with an RMSE of 5.35 for training and an R2 of 0.9328 with an RMSE of 4.57 for testing. Another model, ANN BP, produced an R2 of 0.9125 with an RMSE of 6.17 for training and an R2 of 0.8951 with an RMSE of 5.79 for testing. The results of the PSO NN model were in close agreement with the experimental values. Thus, the PSO NN model can be used to predict the ultimate torsional capacity of RC beams strengthened with FRP with greater acceptable accuracy.