• 제목/요약/키워드: optimization modeling

검색결과 1,203건 처리시간 0.028초

Parametric optimization of FPSO hull dimensions for Brazil field using sophisticated stability and hydrodynamic calculations

  • Lee, Jonghun;Kim, Byung Chul;Ruy, Won-Sun;Han, Ik Seung
    • International Journal of Naval Architecture and Ocean Engineering
    • /
    • 제13권1호
    • /
    • pp.478-492
    • /
    • 2021
  • In this study, hull dimensions of an FPSO were optimized to maximize its operability at Brazil field. In contrast with the previous works which have used simplified models to evaluate some indicators related to stability and hydrodynamic performances of FPSOs for its own optimal design, we developed a generic hull and compartment modeler and sophisticated stability and hydrodynamic calculation modules. With the aid of the developed tools, the hull optimization was performed with initial dimensions of an FPSO originally designed for west Africa field. The optimization results indicated the relative importance of hydrodynamic performances compared with stability performances for the FPSO hull dimensioning by showing that there were 3 active constraints related to them, which were the natural periods of heave and roll and the maximum pitch angle under 1-year return period waves at full load condition. To the author's knowledge, this study is the first attempt to combine altogether the hull and compartment modeling and full set of stability and hydrodynamic calculations precisely to optimize an FPSO's hull dimensions within 30 min. Also, it is worthwhile to mention that the developed methods are generic enough to be applied to all types of ship-shaped offshore platforms.

계층적 크리깅 모델을 이용한 설계 최적화 기법의 유용성 검증 (Feasibility Study of Hierarchical Kriging Model in the Design Optimization Process)

  • 하홍근;오세종;이관중
    • 한국항공우주학회지
    • /
    • 제42권2호
    • /
    • pp.108-118
    • /
    • 2014
  • 근사모델을 이용한 최적설계 문제에서는 설계변수의 수가 증가함에 따라 근사모델의 정확도를 확보하기 위한 계산 횟수가 급격히 증가한다. 이를 해결하기 위해 저정확도 모델을 바탕으로 고정확도 모델로 보정하는 Variable-Fidelity Modeling을 이용하였다. 본 논문에서 Variable-Fidelity Model로는 계층적 크리깅 모델을 이용하였으며, 다목적 유전자 알고리즘과 결합하여 최적화 프레임워크를 제안하였다. 이 방법의 유용성을 검증하기 위하여 천음속 영역에 대한 익형 최적 설계를 하였다. 설계변수로는 PARSEC의 파라메터를 이용하였으며, 서로 다른 격자수를 가지는 경우 그리고 서로 다른 정확도를 가지는 해석자를 이용한 경우에 관하여 해석을 수행하였다. 검증을 위해 단일 정확도 모델에 대한 최적화 결과와 비교하였다. 모든 경우에 관하여 파레토 라인이 유사하게 나오는 것을 확인 할 수 있었으며, 계산시간은 계층적 크리깅 모델을 이용한 Variable-Fidelity Model이 단일 정확도 모델에 비하여 훨씬 줄어들었다. 이를 바탕으로 본 논문의 방법이 단일 정확도를 가지는 모델에 대한 최적화 방법과 유사한 정확도를 가지며 더욱 효율적임을 확인 할 수 있다.

Modeling and Parameter Optimization of Agile Beam Radar Tracking in Cluttered Environments

  • Hong, Sun-Mog;Jung, Young-Hun
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 2001년도 ICCAS
    • /
    • pp.99.6-99
    • /
    • 2001
  • The parameter optimization for agile beam radar tracking is addressed to minimize the radar resources that are required to maintain a target under track. The parameters to be optimized include the track-revisit interval and the sequence of pairs of target signal strengths and detection thresholds associated with repeated illumination attempts in each track-revisit. The optimization problem is solved numerically for typical examples.

  • PDF

Modern vistas of process control

  • Georgakis, Christos
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
    • /
    • pp.18-18
    • /
    • 1996
  • This paper reviews some of the most prominent and promising areas of chemical process control both in relations to batch and continuous processes. These areas include the modeling, optimization, control and monitoring of chemical processes and entire plants. Most of these areas explicitly utilize a model of the process. For this purpose the types of models used are examined in some detail. These types of models are categorized in knowledge-driven and datadriven classes. In the areas of modeling and optimization, attention is paid to batch reactors using the Tendency Modeling approach. These Tendency models consist of data- and knowledge-driven components and are often called Gray or Hybrid models. In the case of continuous processes, emphasis is placed in the closed-loop identification of a state space model and their use in Model Predictive Control nonlinear processes, such as the Fluidized Catalytic Cracking process. The effective monitoring of multivariate process is examined through the use of statistical charts obtained by the use of Principal Component Analysis (PMC). Static and dynamic charts account for the cross and auto-correlation of the substantial number of variables measured on-line. Centralized and de-centralized chart also aim in isolating the source of process disturbances so that they can be eliminated. Even though significant progress has been made during the last decade, the challenges for the next ten years are substantial. Present progress is strongly influenced by the economical benefits industry is deriving from the use of these advanced techniques. Future progress will be further catalyzed from the harmonious collaboration of University and Industrial researchers.

  • PDF

System Level Architecture Evaluation and Optimization: an Industrial Case Study with AMBA3 AXI

  • Lee, Jong-Eun;Kwon, Woo-Cheol;Kim, Tae-Hun;Chung, Eui-Young;Choi, Kyu-Myung;Kong, Jeong-Taek;Eo, Soo-Kwan;Gwilt, David
    • JSTS:Journal of Semiconductor Technology and Science
    • /
    • 제5권4호
    • /
    • pp.229-236
    • /
    • 2005
  • This paper presents a system level architecture evaluation technique that leverages transaction level modeling but also significantly extends it to the realm of system level performance evaluation. A major issue lies with the modeling effort. To reduce the modeling effort the proposed technique develops the concept of worst case scenarios. Since the memory controller is often found to be an important component that critically affects the system performance and thus needs optimization, the paper further addresses how to evaluate and optimize the memory controllers, focusing on the test environment and the methodology. The paper also presents an industrial case study using a real state-of-the-art design. In the case study, it is reported that the proposed technique has helped successfully find the performance bottleneck and provide appropriate feedback on time.

Evolutionary computational approaches for data-driven modeling of multi-dimensional memory-dependent systems

  • Bolourchi, Ali;Masri, Sami F.
    • Smart Structures and Systems
    • /
    • 제15권3호
    • /
    • pp.897-911
    • /
    • 2015
  • This study presents a novel approach based on advancements in Evolutionary Computation for data-driven modeling of complex multi-dimensional memory-dependent systems. The investigated example is a benchmark coupled three-dimensional system that incorporates 6 Bouc-Wen elements, and is subjected to external excitations at three points. The proposed technique of this research adapts Genetic Programming for discovering the optimum structure of the differential equation of an auxiliary variable associated with every specific degree-of-freedom of this system that integrates the imposed effect of vibrations at all other degrees-of-freedom. After the termination of the first phase of the optimization process, a system of differential equations is formed that represent the multi-dimensional hysteretic system. Then, the parameters of this system of differential equations are optimized in the second phase using Genetic Algorithms to yield accurate response estimates globally, because the separately obtained differential equations are coupled essentially, and their true performance can be assessed only when the entire system of coupled differential equations is solved. The resultant model after the second phase of optimization is a low-order low-complexity surrogate computational model that represents the investigated three-dimensional memory-dependent system. Hence, this research presents a promising data-driven modeling technique for obtaining optimized representative models for multi-dimensional hysteretic systems that yield reasonably accurate results, and can be generalized to many problems, in various fields, ranging from engineering to economics as well as biology.

신경망과 유전 알고리즘을 이용한 광소자용 ZnO 박막 특성 공정 모델링 및 최적화 (Process Modeling and Optimization for Characteristics of ZnO Thin Films using Neural Networks and Genetic Algorithms)

  • 고영돈;강홍성;정민창;이상렬;명재민;윤일구
    • 한국전기전자재료학회:학술대회논문집
    • /
    • 한국전기전자재료학회 2004년도 하계학술대회 논문집 Vol.5 No.1
    • /
    • pp.33-36
    • /
    • 2004
  • The process modeling for the growth rate in pulsed laser deposition(PLD)-grown ZnO thin films is investigated using neural networks(NNets) and the process recipes is optimized via genetic algorithms(GAs). D-optimal design is carried out and the growth rate is characterized by NNets based on the back-propagation(BP) algorithm. GAs is then used to search the desired recipes for the desired growth rate. The statistical analysis is used to verify the fitness of the nonlinear process model. This process modeling and optimization algorithms can explain the characteristics of the desired responses varying with process conditions.

  • PDF

휴대폰용 카메라 렌즈 시스템의 공차최적설계 (Tolerance Analysis and Optimization for a Lens System of a Mobile Phone Camera)

  • 정상진;최동훈;최병렬;김주호
    • 한국CDE학회논문집
    • /
    • 제16권6호
    • /
    • pp.397-406
    • /
    • 2011
  • Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

삼차원 적층복합재 구멍의 형상 최적화 (Shape Optimization of Three-Dimensional Cutouts in Laminated Composite Plates)

  • 한석영;마영준
    • 한국공작기계학회:학술대회논문집
    • /
    • 한국공작기계학회 2004년도 춘계학술대회 논문집
    • /
    • pp.275-280
    • /
    • 2004
  • Shape optimization was performed to obtain the precise shape of cutouts including the internal shape of cutouts in laminated composite plates by three dimensional modeling using solid element. The volume control of the growth-strain method was implemented and the distributed parameter chosen as Tsai-Hill fracture index for shape optimization. The volume control of the growth-strain method makes Tsai-Hill failure index at each element uniform in laminated composites under the initial volume. Then shapes optimized by Tsai-Hill failure index were compared with those of the initial shapes for the various load conditions and cutouts. The following conclusions were obtained in this study. (1) It was found that growth-strain method was applied efficiently to shape optimization of three dimensional cutouts in a laminate composite, (2) The optimal shapes of the various load conditions and cutouts were obtained, (3) The maximum Tsal-Hill failure index was reduced up to 67% when shape optimization was peformed under the initial volume by volume control of growth-strain method.

  • PDF