• Title/Summary/Keyword: sequential design

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Implementation of interlock in Process Control System Described by Sequential Function Chart Graphical Language (Sequential Function Chart 그래픽 언어로 記述된 공정제어 시스템에서 인터록의 실현)

  • 유정봉;우광준;허경무
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.12 no.2
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    • pp.54-61
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    • 1998
  • Ladder Diagram(LD) is the most extensively used among Programmable Logic Controller(PLC) standard languages for the design of process control system with PLC. But LD has the disadvantages for data processing and maintenance. On the other hand, there is full support for describing sequences so that complete sequential behavior can be easily broken down using a concise graphical language called Sequential Function Chart(SFC). Inspite of those characteristics, SFC is not suitable for describing interlock logic. In this paper, we propose the method for implementing interlock logic by using conventional SFC compiler and verify the effectiveness by applying proposed scheme to the In-Line Spin Coater.Coater.

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Approximate Shape Optimization Technique by Sequential Design Domain (순차설계영역을 이용한 근사 형상최적에 관한 연구)

  • 김우현;임오강
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.17 no.1
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    • pp.31-38
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    • 2004
  • Mechanical design process is generally accomplished by design, analysis, and test. Designers use programs fitting purpose, and obtain repeatedly a response of a simulation program, a sub-program for optimization. In this paper, shape optimization using approximate optimization technique is carried out with sequential design domain(SDD). In addition, algorithm executing Pro/Engineer and ANSYS automatically are adopted in the approximate optimization program by SDD. It is difficult for design problem to be approximated accurately for the whole range of design space. However, more or less accurate approximation is constructed if SDD is applied to that case. SDD starts with a certain range which is off-seted from midpoint of an initial design domain and then SDD of the next step is determined by a move limited. Convergence criterion is defined such that optimal point must be located within SDD during the two steps. Also, the PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information and the active set strategy, in order to seek the direction of design variables.

Sensitivity Approach of Sequential Sampling Using Adaptive Distance Criterion (적응거리 조건을 이용한 순차적 실험계획의 민감도법)

  • Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9 s.240
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    • pp.1217-1224
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    • 2005
  • To improve the accuracy of a metamodel, additional sample points can be selected by using a specified criterion, which is often called sequential sampling approach. Sequential sampling approach requires small computational cost compared to one-stage optimal sampling. It is also capable of monitoring the process of metamodeling by means of identifying an important design region for approximation and further refining the fidelity in the region. However, the existing critertia such as mean squared error, entropy and maximin distance essentially depend on the distance between previous selected sample points. Therefore, although sufficient sample points are selected, these sequential sampling strategies cannot guarantee the accuracy of metamodel in the nearby optimum points. This is because criteria of the existing sequential sampling approaches are inefficient to approximate extremum and inflection points of original model. In this research, new sequential sampling approach using the sensitivity of metamodel is proposed to reflect the response. Various functions that can represent a variety of features of engineering problems are used to validate the sensitivity approach. In addition to both root mean squared error and maximum error, the error of metamodel at optimum points is tested to access the superiority of the proposed approach. That is, optimum solutions to minimization of metamodel obtained from the proposed approach are compared with those of true functions. For comparison, both mean squared error approach and maximin distance approach are also examined.

Corrective Control of Composite Asynchronous Sequential Machines in Parallel Connection (병렬 결합된 비동기 순차 머신을 위한 교정 제어)

  • Yang, Jung-Min
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.8
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    • pp.139-147
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    • 2014
  • We address the problem of corrective control for two asynchronous sequential machines in parallel connection. Each asynchronous machine receives the same external input and shows independent state transition characteristics. We propose a novel control scheme in which only one corrective controller is employed so as to make the closed-loop system of each machine match the behavior of the corresponding reference model. Compared with the former method utilizing two corrective controllers, our scheme can reduce the controller size and computational load in controller design. We present the existence condition and design procedure for a state-feedback corrective controller under the assumption that the controlled machines are of input/state type. The design procedure for the proposed controller is described in an illustrative example.

Optimal Supersonic Air-Launching Rocket Design Using Multidisciplinary System Optimization Approach (다분야 최적화 기법을 이용한 공중발사로켓 최적설계)

  • Choi Young Chang;Lee Jae-Woo;Byun Yung-Hwan
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • v.y2005m4
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    • pp.11-15
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    • 2005
  • Compared with the conventional ground rocket launching, air-launching has many advantages. However, comprehensive and integrated system design approach is required because the physical geometry of air launch vehicle is quite dependent on the installation limitation of the mother plane. The system design has been performed using two different approaches: the sequential optimization and the multidisciplinary feasible(MDF) optimization method. Analysis modules include mission analysis, staging, propulsion analysis, configuration, weight analysis, aerodynamics analysis and trajectory analysis. MDF optimization shows better result than sequential optimization. As a result of system optimization, a supersonic air launching rocket with total mass of 1244.91 kg, total length of 6.18 m, outer diameter of 0.60 m and the payload mass of 7.5 kg has been successfully designed.

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Optimal Supersonic Air-Launching Rocket Design Using Multidisciplinary System Optimization Approach (다분야 최적화 기법을 이용한 공중발사 로켓 최적설계)

  • Choi, Young-Chang;Lee, Jae-Woo;ByUn, Yung-Hwan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.12
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    • pp.26-32
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    • 2005
  • Compared with the conventional ground rocket launching, air-launching has many advantages. However, a comprehensive and integrated system design approach is required because the physical geometry of air launch vehicle is quite dependent on the installation limitation of the mother plane. The system design has been performed using two different approaches: the sequential optimization and the multidisciplinary feasible(MDF) optimization method. Analysis modules include mission analysis, staging, propulsion analysis, configuration, weight analysis, aerodynamics analysis and trajectory analysis. MDF optimization shows better results than the sequential optimization. As a result of system optimization, a supersonic air launching rocket with total mass of 1244.91kg, total length of 6.36m, outer diameter of 0.60m and the payload mass of 7.5kg has been successfully designed.

Optimum Design Based on Sequential Design of Experiments and Artificial Neural Network for Enhancing Occupant Head Protection in B-Pillar Trim (센터 필라트림의 FMH 충격성능 향상을 위한 순차적 실험계획법과 인공신경망 기반의 최적설계)

  • Lee, Jung Hwan;Suh, Myung Won
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.11
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    • pp.1397-1405
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    • 2013
  • The optimal rib pattern design of B-pillar trim considering occupant head protection can be determined by two methods. One is the conventional approximate optimization method that uses the statistical design of experiments (DOE) and response surface method (RSM). Generally, approximated optimum results are obtained through the iterative process by trial-and-error. The quality of results strongly depends on the factors and levels assigned by a designer. The other is a methodology derived from previous work by the authors, called the sequential design of experiments (SDOE), to reduce the trial-and-error procedure and to find an appropriate condition for using artificial neural network (ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently.

Candidate Points and Representative Cross-Validation Approach for Sequential Sampling (후보점과 대표점 교차검증에 의한 순차적 실험계획)

  • Kim, Seung-Won;Jung, Jae-Jun;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.31 no.1 s.256
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    • pp.55-61
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    • 2007
  • Recently simulation model becomes an essential tool for analysis and design of a system but it is often expensive and time consuming as it becomes complicate to achieve reliable results. Therefore, high-fidelity simulation model needs to be replaced by an approximate model, the so-called metamodel. Metamodeling techniques include 3 components of sampling, metamodel and validation. Cross-validation approach has been proposed to provide sequnatially new sample point based on cross-validation error but it is very expensive because cross-validation must be evaluated at each stage. To enhance the cross-validation of metamodel, sequential sampling method using candidate points and representative cross-validation is proposed in this paper. The candidate and representative cross-validation approach of sequential sampling is illustrated for two-dimensional domain. To verify the performance of the suggested sampling technique, we compare the accuracy of the metamodels for various mathematical functions with that obtained by conventional sequential sampling strategies such as maximum distance, mean squared error, and maximum entropy sequential samplings. Through this research we team that the proposed approach is computationally inexpensive and provides good prediction performance.

Sequential prediction of TBM penetration rate using a gradient boosted regression tree during tunneling

  • Lee, Hang-Lo;Song, Ki-Il;Qi, Chongchong;Kim, Kyoung-Yul
    • Geomechanics and Engineering
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    • v.29 no.5
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    • pp.523-533
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    • 2022
  • Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R2≥0.79; whereas, a one-step prediction is R2≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R2 and UPD is proposed. When UPD increases R2 decreases exponentially; In particular, UPD at R2=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R2 value targeted by an operator. Therefore, a calculation process for the equation between the R2 and UPD is addressed.

Sensitivity Validation Technique for Sequential Kriging Metamodel (순차적 크리깅 메타모델의 민감도 검증법)

  • Huh, Seung-Kyun;Lee, Jin-Min;Lee, Tae-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.8
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    • pp.873-879
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    • 2012
  • Metamodels have been developed with a variety of design optimization techniques in the field of structural engineering over the last decade because they are efficient, show excellent prediction performance, and provide easy interconnections into design frameworks. To construct a metamodel, a sequential procedure involving steps such as the design of experiments, metamodeling techniques, and validation techniques is performed. Because validation techniques can measure the accuracy of the metamodel, the number of presampled points for an accurate kriging metamodel is decided by the validation technique in the sequential kriging metamodel. Because the interpolation model such as the kriging metamodel based on computer experiments passes through responses at presampled points, additional analyses or reconstructions of the metamodels are required to measure the accuracy of the metamodel if existing validation techniques are applied. In this study, we suggest a sensitivity validation that does not require additional analyses or reconstructions of the metamodels. Fourteen two-dimensional mathematical problems and an engineering problem are illustrated to show the feasibility of the suggested method.