• 제목/요약/키워드: performance-based engineering method

검색결과 8,162건 처리시간 0.043초

Handling dependencies among performance shaping factors in SPARH through DEMATEL method

  • Zhihui Xu;Shuwen Shang;Xiaoyan Su;Hong Qian;Xiaolei Pan
    • Nuclear Engineering and Technology
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    • 제55권8호
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    • pp.2897-2904
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    • 2023
  • The Standardized Plant Analysis Risk-Human Reliability Analysis (SPAR-H) method is a widely used method in human reliability analysis (HRA). Performance shaping factors (PSFs) refer to the factors that may influence human performance and are used to adjust nominal human error probabilities (HEPs) in SPAR-H. However, the PSFs are assumed to be independent, which is unrealistic and can lead to unreasonable estimation of HEPs. In this paper, a new method is proposed to handle the dependencies among PSFs in SPAR-H to obtain more reasonable results. Firstly, the dependencies among PSFs are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Then, PSFs are assigned different weights according to their dependent relationships. Finally, multipliers of PSFs are modified based on the relative weights of PSFs. A case study is illustrated that the proposed method is effective in handling the dependent PSFs in SPAR-H, where the duplicate calculations of the dependent part can be reduced. The proposed method can deal with a more general situation that PSFs are dependent, and can provide more reasonable results.

지하주차장 성능위주설계의 피난안전성 평가 개선에 관한 연구 (A Study on Improvement of Evacuation Safety Evaluation for Performance Based Design in Underground Parking Lot)

  • 송영주;공일천;김학중
    • 한국화재소방학회논문지
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    • 제33권2호
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    • pp.85-97
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    • 2019
  • 오늘날 인간의 삶의 질 향상과 다양한 욕구를 충족시키기 위한 건축물은 대형화, 고층화, 심층화, 복합화 되는 추세이며, 이에 따른 비정형화된 공간이 새롭게 창출되면서 성능위주설계대상도 증가하고 있다. 성능위주설계의 피난안전성 평가는 ASET과 RSET를 산정 비교하여 RSET이 ASET를 초과하지 않도록 하여야 한다. 그러나 지하 주차장과 같이 구획된 공간의 면적이 넓고 피난경로가 다양한 경우 현재 시행되고 있는 성능위주설계 평가 방법만으로 모든 피난경로에서 안전성을 확보하기 어려운 문제가 있다. 따라서 본 논문에서는 이러한 문제점을 극복하기 위해 현재 사용되고 있는 성능위주설계의 시뮬레이션 설정방법에 대해 먼저 고찰한 다음 지하 주차장을 대상으로 화재시뮬레이션 2가지와 피난시뮬레이션 3가지 경우를 각각 수행하여 6가지 경우에 대한 피난안전성 평가를 실시하고 비교 평가하여 문제점을 살펴보고 개선된 성능위주설계의 피난안전성 평가 방안을 제시한다.

A New Dynamic HRA Method and Its Application

  • Jae, Moosung
    • International Journal of Reliability and Applications
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    • 제2권1호
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    • pp.37-48
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    • 2001
  • This paper presents a new dynamic human reliability analysis method and its application for quantifying the human error probabilities in implementing management action. For comparisons of current HRA methods with the new method, the characteristics of THERP, HCR, and SLIM-MAUD, which are most frequency used method in PSAs, are discussed. The action associated with implementation of the cavity flooding during a station blackout sequence is considered for its application. This method is based on the concepts of the quantified correlation between the performance requirement and performance achievement. The MAAP 3.0B code and Latin Hypercube sampling technique are used to determine the uncertainty of the performance achievement parameter. Meanwhile, the value of the performance requirement parameter is obtained from interviews. Based on these stochastic obtained, human error probabilities are calculated with respect to the various means and variances of the things. It is shown that this method is very flexible in that it can be applied to any kind of the operator actions, including the actions associated with the implementation of accident management strategies.

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시차의 신뢰도를 이용한 플렌옵틱 영상의 초고해상도 복원 방법 (Super-resolution Reconstruction Method for Plenoptic Images based on Reliability of Disparity)

  • 정민창;김송란;강현수
    • 한국정보통신학회논문지
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    • 제22권3호
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    • pp.425-433
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    • 2018
  • 본 논문에서는 시차의 신뢰도를 기반으로 플렌옵틱 영상의 초고해상도 복원 알고리즘을 제안한다. 그리고 플렌옵틱 카메라 영상으로부터 생성한 서브어퍼처(sub-aperture) 이미지는 TV_L1알고리즘에 기반한 시차 추정과 초고해상도 영상 복원에 활용된다. 특히 제안된 알고리즘은 시차가 부정확하게 나타날 수 있는 경계 역역에서 향상된 성능을 보인다. 시차 벡터의 신뢰도는 서브어퍼처 이미지의 상하좌우 각 위치별 영역에 따른 분산을 고려하여 판단한다. 신뢰도가 낮은 시차벡터는 초고해상도 영상 복원시 제외된다. 제안된 방법은 바이큐빅 보간 방법과 기존의 시차기반방법 그리고 사전기반 방법과 비교하여 평가되었다. 성능 평가에서 초고해상도 영상복원의 결과는 PSNR, SSIM 관점에서 성능을 비교하여 최상의 성능을 보여준다.

에너지 소산능력을 고려한 전단벽의 내진설계 (Earthquake Design Method for Structural Walls Based on Energy Dissipation Capacity)

  • 박홍근;엄태성
    • 한국지진공학회논문집
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    • 제7권6호
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    • pp.25-34
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    • 2003
  • 최근 능력스펙트럼법, 직접변위기초설계법 등과 같은 성능에 기초한 내진 평가/설계법이 개발되어 사용되고 있다. 이들 방법은 구조물의 비선형 주기거동에 의한 에너지 소산능력을 고려함에 있어 부정확한 경험식에 의존하는 한계를 보이고 있다. 한편, 최근 연구에서 휨지배 철근콘크리트 부재에 대하여 여러 설계변수의 영향을 고려하여 주기거동에 의한 에너지 소산능력을 정확히 평가할 수 있는 방법이 개발되었다. 본 연구에서는 에너지 소산능력을 고려한 내진설계법에 대한 기초적인 연구로서, 최근 연구에서 개발된 에너지 소산능력 산정법을 이용한 철근콘크리트 전단벽 구조의 내진설계법을 개발하여, 기존의 내진설계법과 비교하였다. 제안된 설계법에서는 단면의 크기 및 형상, 축력, 철근비, 배근형태, 연성도 등과 같은 다양한 설계변수에 따른 에너지 소산능력의 변화를 정확히 고려하여 설계할 수 있다.

A Matrix-Based Genetic Algorithm for Structure Learning of Bayesian Networks

  • Ko, Song;Kim, Dae-Won;Kang, Bo-Yeong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제11권3호
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    • pp.135-142
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    • 2011
  • Unlike using the sequence-based representation for a chromosome in previous genetic algorithms for Bayesian structure learning, we proposed a matrix representation-based genetic algorithm. Since a good chromosome representation helps us to develop efficient genetic operators that maintain a functional link between parents and their offspring, we represent a chromosome as a matrix that is a general and intuitive data structure for a directed acyclic graph(DAG), Bayesian network structure. This matrix-based genetic algorithm enables us to develop genetic operators more efficient for structuring Bayesian network: a probability matrix and a transpose-based mutation operator to inherit a structure with the correct edge direction and enhance the diversity of the offspring. To show the outstanding performance of the proposed method, we analyzed the performance between two well-known genetic algorithms and the proposed method using two Bayesian network scoring measures.

Localization of ripe tomato bunch using deep neural networks and class activation mapping

  • Seung-Woo Kang;Soo-Hyun Cho;Dae-Hyun Lee;Kyung-Chul Kim
    • 농업과학연구
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    • 제50권3호
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    • pp.357-364
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    • 2023
  • In this study, we propose a ripe tomato bunch localization method based on convolutional neural networks, to be applied in robotic harvesting systems. Tomato images were obtained from a smart greenhouse at the Rural Development Administration (RDA). The sample images for training were extracted based on tomato maturity and resized to 128 × 128 pixels for use in the classification model. The model was constructed based on four-layer convolutional neural networks, and the classes were determined based on stage of maturity, using a Softmax classifier. The localization of the ripe tomato bunch region was indicated on a class activation map. The class activation map could show the approximate location of the tomato bunch but tends to present a local part or a large part of the ripe tomato bunch region, which could lead to poor performance. Therefore, we suggest a recursive method to improve the performance of the model. The classification results indicated that the accuracy, precision, recall, and F1-score were 0.98, 0.87, 0.98, and 0.92, respectively. The localization performance was 0.52, estimated by the Intersection over Union (IoU), and through input recursion, the IoU was improved by 13%. Based on the results, the proposed localization of the ripe tomato bunch area can be incorporated in robotic harvesting systems to establish the optimal harvesting paths.

Interactive Semantic Image Retrieval

  • Patil, Pushpa B.;Kokare, Manesh B.
    • Journal of Information Processing Systems
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    • 제9권3호
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    • pp.349-364
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    • 2013
  • The big challenge in current content-based image retrieval systems is to reduce the semantic gap between the low level-features and high-level concepts. In this paper, we have proposed a novel framework for efficient image retrieval to improve the retrieval results significantly as a means to addressing this problem. In our proposed method, we first extracted a strong set of image features by using the dual-tree rotated complex wavelet filters (DT-RCWF) and dual tree-complex wavelet transform (DT-CWT) jointly, which obtains features in 12 different directions. Second, we presented a relevance feedback (RF) framework for efficient image retrieval by employing a support vector machine (SVM), which learns the semantic relationship among images using the knowledge, based on the user interaction. Extensive experiments show that there is a significant improvement in retrieval performance with the proposed method using SVMRF compared with the retrieval performance without RF. The proposed method improves retrieval performance from 78.5% to 92.29% on the texture database in terms of retrieval accuracy and from 57.20% to 94.2% on the Corel image database, in terms of precision in a much lower number of iterations.

Design of Speed Controller for an Induction Motor with Inertia Variation

  • Sin E. C.;Kong B. G.;Kim J. S.;Yoo J. Y.;Park T. S.;Lee J. H.
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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    • pp.374-379
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    • 2001
  • In this paper, a novel design algorithm of speed controller for an Induction motor with the inertia variation is proposed. The main contribution of our work is a very robust, reliable and stable procedure for setting of the PI gains against the specified range of the inertia variation of an induction motor using Kharitonovs robust control theory. Therefore, the basic segment of controller design, the variation of induction motor inertia is estimated by the RLS (Recursive least square) method. PI based speed controller is widely used in industrial application for its simple structure and reliable performance. In addition the Kharitonov robust control theory is used for verification stability of closed-loop transfer function. The performance of this proposed design method is proved by digital simulation and experimentation with high performance DSP based induction motor driving system.

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Experimental and numerical structural damage detection using a combined modal strain energy and flexibility method

  • Seyed Milad Hosseini;Mohamad Mohamadi Dehcheshmeh;Gholamreza Ghodrati Amiri
    • Structural Engineering and Mechanics
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    • 제87권6호
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    • pp.555-574
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    • 2023
  • An efficient optimization algorithm and damage-sensitive objective function are two main components in optimization-based Finite Element Model Updating (FEMU). A suitable combination of these components can considerably affect damage detection accuracy. In this study, a new hybrid damage-sensitive objective function is proposed based on combining two different objection functions to detect the location and extent of damage in structures. The first one is based on Generalized Pseudo Modal Strain Energy (GPMSE), and the second is based on the element's Generalized Flexibility Matrix (GFM). Four well-known population-based metaheuristic algorithms are used to solve the problem and report the optimal solution as damage detection results. These algorithms consist of Cuckoo Search (CS), Teaching-Learning-Based Optimization (TLBO), Moth Flame Optimization (MFO), and Jaya. Three numerical examples and one experimental study are studied to illustrate the capability of the proposed method. The performance of the considered metaheuristics is also compared with each other to choose the most suitable optimizer in structural damage detection. The numerical examinations on truss and frame structures with considering the effects of measurement noise and availability of only the first few vibrating modes reveal the good performance of the proposed technique in identifying damage locations and their severities. Experimental examinations on a six-story shear building structure tested on a shake table also indicate that this method can be considered as a suitable technique for damage assessment of shear building structures.