• 제목/요약/키워드: Design tree

검색결과 1,049건 처리시간 0.026초

Bayesian-based seismic margin assessment approach: Application to research reactor

  • Kwag, Shinyoung;Oh, Jinho;Lee, Jong-Min;Ryu, Jeong-Soo
    • Earthquakes and Structures
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    • 제12권6호
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    • pp.653-663
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    • 2017
  • A seismic margin assessment evaluates how much margin exists for the system under beyond design basis earthquake events. Specifically, the seismic margin for the entire system is evaluated by utilizing a systems analysis based on the sub-system and component seismic fragility data. Each seismic fragility curve is obtained by using empirical, experimental, and/or numerical simulation data. The systems analysis is generally performed by employing a fault tree analysis. However, the current practice has clear limitations in that it cannot deal with the uncertainties of basic components and accommodate the newly observed data. Therefore, in this paper, we present a Bayesian-based seismic margin assessment that is conducted using seismic fragility data and fault tree analysis including Bayesian inference. This proposed approach is first applied to the pooltype nuclear research reactor system for the quantitative evaluation of the seismic margin. The results show that the applied approach can allow updating by considering the newly available data/information at any level of the fault tree, and can identify critical scenarios modified due to new information. Also, given the seismic hazard information, this approach is further extended to the real-time risk evaluation. Thus, the proposed approach can finally be expected to solve the fundamental restrictions of the current method.

쉴드 TBM 터널에 적용 가능한 리스크 관리: I. 리스크 요인 분석 (Risk management applicable to shield TBM tunnel: I. Risk factor analysis)

  • 현기창;민상윤;문준배;정경환;이인모
    • 한국터널지하공간학회 논문집
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    • 제14권6호
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    • pp.667-681
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    • 2012
  • 일반적으로 리스크 관리는 리스크 확인, 리스크 분석, 리스크 평가, 리스크 대책, 리스크 재평가를 포함하는 일련의 과정으로 구성된다. 본 논문에서는 쉴드 TBM 터널에서 발생 가능한 리스크 요인들을 여러 문헌 자료와 워크샵을 바탕으로 조사하였다. 리스크 요인들은 지질 요인, 설계 요인, 시공 관리 요인으로 구분되었다. Fault Tree도는 리스크들을 커터, 기계 구속, 배토(굴진), 세그먼트과 관련된 4그룹으로 분류하여 작성되었다. FT도로부터 12가지 리스크 아이템을 확인하고 각각의 발생확률을 구하였다.

교통신호등 제어를 통한 교통망 최적화 알고리즘 (A Algorithm on Optimizing Traffic Network by the Control of Traffic Signal Timing)

  • 안영필;김동춘;나승권
    • 한국항행학회논문지
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    • 제21권5호
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    • pp.472-478
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    • 2017
  • 본 논문에서는 네트워크 토폴로지 설계방법들(minimum spanning tree와 Dijkstra algorithm)을 사용하여 교통 격자 가로망을 최적화 하는 방안을 다루며, 최소신장트리(minimum spanning tree)에서 직진 교통신호등간의 연동들을 통해 출발지와 목적지간의 지연시간을 최소화 하는 것으로 교통격자 가로망을 최적화한다. 또한 컴퓨터 네트워크에서 사용되어지는 Dijkstra algorithm을 통해 구해진 경로에 따라 차량 운전자들이 그 경로를 준수한다고 가정한다면 격자망에서 교통신호등의 연동을 통해 최적화할 수 있음을 보여준다. 격자 가로망에서의 모의실험결과는 직진 교통신호등의 연동을 통해 망을 가로지는 지연시간을 최소화함을 보여준다.

An Optimized Random Tree and Particle Swarm Algorithm For Distribution Environments

  • Feng, Zhou;Lee, Un-Kon
    • 유통과학연구
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    • 제13권6호
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    • pp.11-15
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    • 2015
  • Purpose - Robot path planning, a constrained optimization problem, has been an active research area with many methods developed to tackle it. This study proposes the use of a Rapidly-exploring Random Tree and Particle Swarm Optimizer algorithm for path planning. Research design, data, and methodology - The grid method is built to describe the working space of the mobile robot, then the Rapidly-exploring Random Tree algorithm is applied to obtain the global navigation path and the Particle Swarm Optimizer algorithm is adopted to obtain the best path. Results - Computer experiment results demonstrate that this novel algorithm can rapidly plan an optimal path in a cluttered environment. Successful obstacle avoidance is achieved, the model is robust, and performs reliably. The effectiveness and efficiency of the proposed algorithm is demonstrated through simulation studies. Conclusions - The findings could provide insights to the validity and practicability of the method. This method makes it is easy to build a model and meet real-time demand for mobile robot navigation with a simple algorithm, which results in a certain practical value for distribution environments.

자생 수목 그루터기를 이용한 자연식생복원 녹화공법 연구(I) (A Study on Revegetation Measures with Recycling Root-stock of Native Tree(I))

  • 오구균;권태호;배중남;박석곤
    • 한국환경복원기술학회지
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    • 제6권5호
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    • pp.28-39
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    • 2003
  • This study was carried out to elucidate effective restoration measures for natural forest with recycling native tree un site from November 2001 to October 2002 to obtain a basic information for revegetation measure, eight experimental treatment was done and the length of stump, root-ball size of stump, antisepsis treatment of trunk cut, Planting season and contents of organic matter in soil were effective on regrowth of root-stock. Thirteen tree species including Quercus acutissima among twenty tree species showed outstanding sprout and survival rate(over 90 percent), Planting in November and combinated planting with 5 trees and 9 shrubs of root-stock per 100$m^2$ plot showed a good growth. And 10 percent of organic matter plot showed a good crown coverage.

A New Connected Coherence Tree Algorithm For Image Segmentation

  • Zhou, Jingbo;Gao, Shangbing;Jin, Zhong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제6권4호
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    • pp.1188-1202
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    • 2012
  • In this paper, we propose a new multi-scale connected coherence tree algorithm (MCCTA) by improving the connected coherence tree algorithm (CCTA). In contrast to many multi-scale image processing algorithms, MCCTA works on multiple scales space of an image and can adaptively change the parameters to capture the coarse and fine level details. Furthermore, we design a Multi-scale Connected Coherence Tree algorithm plus Spectral graph partitioning (MCCTSGP) by combining MCCTA and Spectral graph partitioning in to a new framework. Specifically, the graph nodes are the regions produced by CCTA and the image pixels, and the weights are the affinities between nodes. Then we run a spectral graph partitioning algorithm to partition on the graph which can consider the information both from pixels and regions to improve the quality of segments for providing image segmentation. The experimental results on Berkeley image database demonstrate the accuracy of our algorithm as compared to existing popular methods.

차량인터넷을 포함한 V2X 환경에서 안전한 차량 통신 서비스 제공을 위한 해시 트리 기반 통신 프로토콜 (Hash Tree based Communication Protocol in V2X Environments Including Internet of Vehicles for Providing Secure Vehicular Communication Services)

  • 진병욱;차시호
    • 디지털산업정보학회논문지
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    • 제14권1호
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    • pp.27-34
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    • 2018
  • Various messages generated in vehicles are transmitted based on the wireless telecommunication which is a core technology of vehicle to everything (V2X). However, the hackers attack them upon penetration to the system and network to cause the generation of users' inconveniences for vehicular communication. Moreover, huge damage could be occurred in terms of physical and materialistic areas if the users in the vehicles were attacked in the communication environment. Therefore, this study was to design the safe communication protocol using hash tree technique in the V2X environments. Using hash tree technique, processes of issuing certificate and registration and communication protocol were designed, and safety analysis was performed on the attacking technique which is occurred in the existing vehicles. Approximately 62% of decrease in the capacity analysis was found upon comparative analysis of telecommunication processes with the system to issue the certificate which is used in the existing vehicles.

건설공사의 확률적 위험도분석평가 (Probabilistic Risk Assessment for Construction Projects)

  • 조효남;임종권;김광섭
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1997년도 가을 학술발표회 논문집
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    • pp.24-31
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    • 1997
  • Recently, in Korea, demand for establishment of systematic risk assessment techniques for construction projects has increased, especially after the large construction failures occurred during construction such as New Haengju Bridge construction projects, subway construction projects, gas explosion accidents etc. Most of existing risk analysis modeling techniques such as Event Tree Analysis and Fault Tree Analysis may not be available for realistic risk assessment of construction projects because it is very complex and difficult to estimate occurrence frequency and failure probability precisely due to a lack of data related to the various risks inherent in construction projects like natural disasters, financial and economic risks, political risks, environmental risks as well as design and construction-related risks. Therefor the main objective of this paper is to suggest systematic probabilistic risk assessment model and demonstrate an approach for probabilistic risk assessment using advanced Event Tree Analysis introducing Fuzzy set theory concepts. It may be stated that the Fuzzy Event Tree AnaIysis may be very usefu1 for the systematic and rational risk assessment for real constructions problems because the approach is able to effectively deal with all the related construction risks in terms of the linguistic variables that incorporate systematically expert's experiences and subjective judgement.

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GOOD 2.0 : 공간 인덱스를 사용한 지리 데이타 관리기 (GOOD 2.0 : a Geographical Data Manager using Spatial indices)

  • 오병우;한기준
    • 대한공간정보학회지
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    • 제3권2호
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    • pp.137-149
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    • 1995
  • 점차 중요성이 증가하고 있는 지리 정보 시스템의 효율적인 검색을 위해서는 공간 인덱스가 필요하다. 이를 위하여 본 논문에서는 기존에 개발한 지리 정보 시스템을 위한 데이타 관리기인GOOD 1.0에 공간 인덱스를 처리할 수 있는 공간 인덱스 처리 모듈을 추가하여 GOOD 2.0을 설계 및 구현한다. 즉, 공간 인덱스로는 R tree 및 R* tree를 지원하여 효율적인 검색이 가능하도록 한다. 그리고, 효율성의 향상 정도를 측정하기 위해 성능 평가를 길시하고 결과를 분석한다. 성능 평가 시에는 다양한 환경 요소들을 고려하여 지리 정보 시스템 관리자가 해당 도메인에 적합한 공간 인덱스를 선택하는데 기초 자료로서 사용될 수 있도록 한다.

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냉연 표면 흠 분류를 위한 특징선정 및 이진 트리 분류기의 설계에 관한 연구 (A Study on The Feature Selection and Design of a Binary Decision Tree for Recognition of The Defect Patterns of Cold Mill Strip)

  • 이병진;류경;박귀태;김경민
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1998년도 하계학술대회 논문집 G
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    • pp.2330-2332
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    • 1998
  • This paper suggests a method to recognize the various defect patterns of cold mill strip using binary decision tree automatically constructed by genetic algorithm. The genetic algorithm and K-means algorithm were used to select a subset of the suitable features at each node in binary decision tree. The feature subset with maximum fitness is chosen and the patterns are classified into two classes by a linear decision boundary. This process was repeated at each node until all the patterns are classified into individual classes. The final recognizer is accomplished by neural network learning of a set of standard patterns at each node. Binary decision tree classifier was applied to the recognition of the defect patterns of cold mill strip and the experimental results were given to demonstrate the usefulness of the proposed scheme.

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