• 제목/요약/키워드: model optimization

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모델을 이용한 증류공정의 최적화 방안 (A model based scheme of on-line optimization in distillation process)

  • 김흥식;이광순
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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    • pp.240-245
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    • 1990
  • A on-line optimization scheme based on model in a binary distillation process is proposed. A reduced-order model utilized the concept of collocation is used as a process model and the recursive prediction error method is employed to identify the reduced-order model. The concentrations of end products are controlled by nonlinear adaptive predictive control algorithm. The objective function is constructed to find optimum operate condition for saving utility cost. The proposed optimization is scheme is tested through simulation studies in 13-staged water-methanol distillation column.

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Model Development for Lactic Acid Fermentation and Parameter Optimization Using Genetic Algorithm

  • LIN , JIAN-QIANG;LEE, SANG-MOK;KOO, YOON-MO
    • Journal of Microbiology and Biotechnology
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    • 제14권6호
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    • pp.1163-1169
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    • 2004
  • An unstructured mathematical model is presented for lactic acid fermentation based on the energy balance. The proposed model reflects the energy metabolic state and then predicts the cell growth, lactic acid production, and glucose consumption rates by relating the above rates with the energy metabolic rate. Fermentation experiments were conducted under various initial lactic acid concentrations of 0, 30, 50, 70, and 90 g/l. Also, a genetic algorithm was used for further optimization of the model parameters and included the operations of coding, initialization, hybridization, mutation, decoding, fitness calculation, selection, and reproduction exerted on individuals (or chromosomes) in a population. The simulation results showed a good fit between the model prediction and the experimental data. The genetic algorithm proved to be useful for model parameter optimization, suggesting wider applications in the field of biological engineering.

THE GLOBAL OPTIMAL SOLUTION TO THE THREE-DIMENSIONAL LAYOUT OPTIMIZATION MODEL WITH BEHAVIORAL CONSTRAINTS

  • Jun, Tie;Feng, Enmin
    • Journal of applied mathematics & informatics
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    • 제15권1_2호
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    • pp.313-321
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    • 2004
  • In this paper we study the problem of three-dimensional layout optimization on the simplified rotating vessel of satellite. The layout optimization model with behavioral constraints is established and some effective and convenient conditions of performance optimization are presented. Moreover, we prove that the performance objective function is locally Lipschitz continuous and the results on the relations between the local optimal solution and the global optimal solution are derived.

등각사상법과 유한요소법을 이용한 2단계 최적설계법 (A Novel Optimization Procedure Utilizing the Conformal Transformation Method)

  • 임지원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 학술대회 논문집 전문대학교육위원
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    • pp.7-12
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    • 2001
  • A large number of methods for the design optimization have been proposed in recent years. However, it is not easy to apply these methods to practical use because of many iterations. So, in the design optimization, physical and engineering investigation of the given model are very important, which results in an overall increase in the optimization speed. This paper describes a novel optimization procedure utilizing the conformal transformation method. This approach consists of two phases and has the advantage of grasping the physical phenomena of the model easily. Some numerical results that demonstrate the validity of the proposed method are also presented.

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혼합모델을 이용한 차체 단면의 최적화 방법에 관한 연구 (Optimization of Body Section usign Hybrid Model)

  • 고병식
    • 소음진동
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    • 제10권3호
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    • pp.437-443
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    • 2000
  • The optimal design problem for increasing dynamic stiffness using hybrid model which composed of original detailed BIW(body in white) and impinged beam elements is investigated. Using the characteristics of the beam elements and design sensitivity analysis this approach utilizes an optimization technique to determine the optimal section properties of beam elements. The constraint is to increase the first natural frequency by five percent compared with original one. The results show that the first torsion and bending natural frequencies are increased by five percent using hybrid model and optimization. These results indicate that this optimization method can be employed to enhance the dynamic stiffness of vehicle body structure in design concept stage.

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구조 최적화를 위한 특징형상 재설계 알고리즘 (A Feature-based Reconstruction Algorithm for Structural Optimization)

  • 박상근
    • 융복합기술연구소 논문집
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    • 제4권2호
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    • pp.1-9
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    • 2014
  • This paper examines feature-based reconstruction algorithm using feature-based modeling and based on topology optimization technology, which aims to achieve a minimal volume weight and to satisfy user-defined constraints such as stress, deformation related conditions. The finite element model after topology optimization allows us to remove some region of a solid model for predefined volume requirement. The stress or deformation distribution resulted from finite element analysis enables us to add some material to the solid model for a robust structure. For this purpose, we propose a feature-based redesign algorithm which inserts negative features to the solid model for material removal and positive features for material addition, and we introduce a bisection method which searches an optimal structure by iteratively applying the feature-based redesign algorithm. Several examples are considered to illustrate the proposed algorithms and to demonstrate the effectiveness of the present approach.

모의수술용 뇌모형 제작시스템 개발을 위한 연구 (Study for Development of the Fabrication System of Brain Model for Surgery Emulation)

  • 염상원;방재철;엄태준;주영철;김승우;공용해;천인국;김범태
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.298-298
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    • 2000
  • This paper presents the optimization technique to analyze the effect of the design parameters of rapid prototyping system for human brain model fabrication. The optimization method considers the functional relationships among the design parameters such as thickness gap, shrink rate, and laser speed that govern the operation of fabrication system. This paper applies a discrete optimization technique as the optimization method to determine the dominant parameter values. Additional study includes manner of complement surface image of ellipse which approximates the brain model using the adaptive slicing and the offset contour. According to the parameters tuning and interaction of effect, more suitable parameter values can be obtained by enhanced 3D brain model fabrication.

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fmGA를 이용한 하수관거정비 최적화 모델 (Optimization Model for Sewer Rehabilitation Using Fast Messy Genetic Algorithm)

  • 류재나;기범준;박규홍;이차돈
    • 상하수도학회지
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    • 제18권2호
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    • pp.145-154
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    • 2004
  • A long-term sewer rehabilitation project consuming an enormous budget needs to be conducted systematically using an optimization skill. The optimal budgeting and ordering of priority for sewer rehabilitation projects are very important with respect to the effectiveness of investment. In this study, the sewer rehabilitation optimization model using fast-messy genetic algorithm is developed to suggest a schedule for optimal sewer rehabilitation in a subcatchment area by modifying the existing GOOSER$^{(R)}$ model having been developed using simple genetic algorithm. The sewer rehabilitation optimization model using fast-messy genetic algorithm can improve the speed converging to the optimal solution relative to GOOSER$^{(R)}$, suggesting that it is more advantageous to the sewer rehabilitation in a larger-scale subcatchment area than GOOSER.

UNDX연산자를 이용한 계층적 공정 경쟁 유전자 알고리즘을 이용한 퍼지집합 퍼지 모델의 최적화 (Optimization of Fuzzy Set Fuzzy Model by Means of Hierarchical Fair Competition-based Genetic Algorithm using UNDX operator)

  • 김길성;최정내;오성권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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    • pp.204-206
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    • 2007
  • In this study, we introduce the optimization method of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation, The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods. Particularly, in parameter identification, we use the UNDX operator which uses multiple parents and generate offsprings around the geographic center off mass of these parents.

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Surrogate Model Based Approximate Optimization of Passive Type Deck Support Frame for Offshore Plant Float-over Installation

  • Lee, Dong Jun;Song, Chang Yong;Lee, Kangsu
    • 한국해양공학회지
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    • 제35권2호
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    • pp.131-140
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    • 2021
  • The paper deals with comparative study of various surrogate models based approximate optimization in the structural design of the passive type deck support frame under design load conditions. The passive type deck support frame was devised to facilitate both transportation and installation of 20,000 ton class topside. Structural analysis was performed using the finite element method to evaluate the strength performance of the passive type deck support frame in its initial design stage. In the structural analysis, the strength performances were evaluated for various design load conditions. The optimum design problem based on surrogate model was formulated such that thickness sizing variables of main structure members were determined by minimizing the weight of the passive type deck support frame subject to the strength performance constraints. The surrogate models used in the approximate optimization were response surface method, Kriging model, and Chebyshev orthogonal polynomials. In the context of numerical performances, the solution results from approximate optimization were compared to actual non-approximate optimization. The response surface method among the surrogate models used in the approximate optimization showed the most appropriate optimum design results for the structure design of the passive type deck support frame.