• Title/Summary/Keyword: probabilistic decision analysis

Search Result 112, Processing Time 0.024 seconds

A financial feasibility analysis of architectural development projects that use probabilistic simulation analysis method (확률론적 시뮬레이션 분석방법을 적용한 건축개발사업의 재무적 타당성 분석)

  • Lee, Seong-Soo;Choi, Hee-Bok;Kang, Kyung-In
    • Korean Journal of Construction Engineering and Management
    • /
    • v.8 no.3
    • /
    • pp.76-86
    • /
    • 2007
  • Construction development work invents profit as those finalize object, and a make or break success of project depends on correct analysis and forecast business feasibility at project early. Business feasibility study would be decision-making under precarious situation because is connoting uncertainty that is future. estimate at present visual point essentially. Under uncertainty, a decision-making method is based on probability theory of statistics, but business feasibility study had applied with not feasibility study by probabilistic decision method but it by determinism derision method so far. Therefore in this study doing decision-making by a probability theory method for successful project at early business feasibility study, it present a probabilistic study method that use simulation that can supply a little more correct and reliable data to decision-maker As result, a probabilistic study method is more suitable than deterministic study method as technique for a financial feasibility study of construction development work. Making good use of this probabilistic study method at important business or careful decision-making, because efficient Judgment that is based accuracy and authoritativeness may become available.

Methodology to Decide Optimum Replacement Term for Components of Nuclear Power Plants (원전 기기의 최적교체시기 결정방법)

  • 문호림;장창희;박준현;정일석
    • Proceedings of the Korean Reliability Society Conference
    • /
    • 2000.11a
    • /
    • pp.257-267
    • /
    • 2000
  • Mostly, the economic analyses for replacement of major components of nuclear power Plants(NPPs) have been performed in deterministic ways. However, the analysis results are more or less affected by the uncertainties associated with input variables. Therefore, it is desirable to use a probabilistic economic analysis method to properly consider uncertainty of real problem. In this paper, the probabilistic economic analysis method and decision analysis technique are briefly described. The probabilistic economy analysis method using decision analysis will provide efficient and accurate way of economic analysis for the repair and/or replace mai or components of NPPs.

  • PDF

Closed-form fragility analysis of the steel moment resisting frames

  • Kia, M.;Banazadeh, M.
    • Steel and Composite Structures
    • /
    • v.21 no.1
    • /
    • pp.93-107
    • /
    • 2016
  • Seismic fragility analysis is a probabilistic decision-making framework which is widely implemented for evaluating vulnerability of a building under earthquake loading. It requires ingredient named probabilistic model and commonly developed using statistics requiring collecting data in large quantities. Preparation of such a data-base is often costly and time-consuming. Therefore, in this paper, by developing generic seismic drift demand model for regular-multi-story steel moment resisting frames is tried to present a novel application of the probabilistic decision-making analysis to practical purposes. To this end, a demand model which is a linear function of intensity measure in logarithmic space is developed to predict overall maximum inter-story drift. Next, the model is coupled with a set of regression-based equations which are capable of directly estimating unknown statistical characteristics of the model parameters.To explicitly address uncertainties arise from randomness and lack of knowledge, the Bayesian regression inference is employed, when these relations are developed. The developed demand model is then employed in a Seismic Fragility Analysis (SFA) for two designed building. The accuracy of the results is also assessed by comparison with the results directly obtained from Incremental Dynamic analysis.

A Probabilistic Reasoning in Incomplete Knowledge for Theorem Proving (불완전한 지식에서 정리증명을 위한 확률추론)

  • Kim, Jin-Sang;Shin, Yang-Kyu
    • Journal of the Korean Data and Information Science Society
    • /
    • v.12 no.1
    • /
    • pp.61-69
    • /
    • 2001
  • We present a probabilistic reasoning method for inferring knowledge about mathematical truth before an automated theorem prover completes a proof. We use a Bayesian analysis to update beleif in truth, given theorem-proving progress, and show how decision-theoretic methods can be used to determine the value of continuing to deliberate versus taking immediate action in time-critical situations.

  • PDF

Probabilistic Safety Assessment of Gas Plant Using Fault Tree-based Bayesian Network (고장수목 기반 베이지안 네트워크를 이용한 가스 플랜트 시스템의 확률론적 안전성 평가)

  • Se-Hyeok Lee;Changuk Mun;Sangki Park;Jeong-Rae Cho;Junho Song
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.36 no.4
    • /
    • pp.273-282
    • /
    • 2023
  • Probabilistic safety assessment (PSA) has been widely used to evaluate the seismic risk of nuclear power plants (NPPs). However, studies on seismic PSA for process plants, such as gas plants, oil refineries, and chemical plants, have been scarce. This is because the major disasters to which these process plants are vulnerable include explosions, fires, and release (or dispersion) of toxic chemicals. However, seismic PSA is essential for the plants located in regions with significant earthquake risks. Seismic PSA entails probabilistic seismic hazard analysis (PSHA), event tree analysis (ETA), fault tree analysis (FTA), and fragility analysis for the structures and essential equipment items. Among those analyses, ETA can depict the accident sequence for core damage, which is the worst disaster and top event concerning NPPs. However, there is no general top event with regard to process plants. Therefore, PSA cannot be directly applied to process plants. Moreover, there is a paucity of studies on developing fragility curves for various equipment. This paper introduces PSA for gas plants based on FTA, which is then transformed into Bayesian network, that is, a probabilistic graph model that can aid risk-informed decision-making. Finally, the proposed method is applied to a gas plant, and several decision-making cases are demonstrated.

Development of a regulatory framework for risk-informed decision making

  • Jang, Dong Ju;Shim, Hyung Jin
    • Nuclear Engineering and Technology
    • /
    • v.52 no.1
    • /
    • pp.69-77
    • /
    • 2020
  • After the Fukushima Daiichi accidents, public concerns on nuclear safety and the corresponding burden of nuclear power plant licensees are increasing. In order to secure public trust and enhance the rationality of current safety regulation, we develop a risk-informed decision making (RIDM) framework for the Korean regulatory body. By analyzing all the regulatory activities for nuclear power plants in Korea, eight action items are selected for RIDM implementation, with appropriate procedures developed for each. For two items in particular - the accident sequence precursor analysis (ASPA) and the significance determination process (SDP) - two customized risk evaluation software has been developed for field inspectors and probabilistic safety assessment experts, respectively. The effectiveness of the proposed RIDM framework is demonstrated by applying the ASPA procedure to 35 unplanned scrams and the SDP to 24 findings from periodic inspections.

Influence Diagram Approach for Strategic Decision Structuring Process

  • Kim, Gi-Hyo;Kim, Soung-Hie
    • Journal of the Korean Operations Research and Management Science Society
    • /
    • v.10 no.1
    • /
    • pp.41-53
    • /
    • 1985
  • The influence diagram is a new conceptual tool that can be used for structuring a strategic decision problem in decision analysis. It has a graphical representation of probabilistic dependence among variables in the decision problem. In this formal procedures for constructuring the influence diagram and for translating it into the corresponding decision tree are studied. An example that shows the power of the infuence diagram is shown.

  • PDF

A Comparative Study between the Deterministic and Probabilistic Approach Analysis on Buckling Stability of CWR Tracks (CWR 궤도의 좌굴 안정성에 대한 결정론적 해석과 확률론적 해석 비교)

  • Bae, Hyun-Ung;Choi, Jin-Yu;Shin, Jeong-Sang;Kim, Jong-Jung;Lim, Nam-Hyoung
    • Proceedings of the KSR Conference
    • /
    • 2011.05a
    • /
    • pp.988-992
    • /
    • 2011
  • The buckling characteristics of the continuous welded rail track(CWR) is uncertainly varied by many influence factors, such as rail temperature, operating conditions of a train and maintenance of the track etc. Therefore, applying the probabilistic approach method is essential to rationally consider uncertainty and randomness of the various parameters that affect the track buckling. In this study, the probabilistic approach analysis was carried out and the results were compared with the deterministic approach using the buckling probability evaluation system of CWR tracks developed by our research team. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of the CWR tracks based on failure probability and can be used as a tool for decision making in track design, maintenance and operating etc.

  • PDF

Application of Probabilistic Health Risk Analysis in Life Cycle Assessment -Part I : A General Framework for Uncertainty and Variability Analysis of Health Risk in Life Cycle Assessment (전과정평가에 있어 확률론적 건강영향분석기법 적용 -Part I : 전과정평가에 있어 확률론적 위해도 분석기법 적용방안에 관한 연구)

  • Choi, Kwang-Soo;Park, Jae-Sung
    • Journal of Environmental Impact Assessment
    • /
    • v.9 no.3
    • /
    • pp.185-202
    • /
    • 2000
  • Uncertainty and variability in Life Cycle Assessment(LCA) have been significant key issues in LCA methodology with techniques in other research area such as social and political science. Variability is understood as stemming from inherent variations in the real world, while uncertainty comes from inaccurate measurements, lack of data, model assumptions, etc. Related articles in this issues were reviewed for classification, distinguish and elaboration of probabilistic/stochastic health risk analysis application in LCA. Concept of focal zone, streamlining technique, scenario modelling and Monte Carlo/Latin Hypercube risk analysis were applied to the uncertainty/variability analysis of health risk in LCA. These results show that this general framework of multi-disciplinary methodology between probabilistic health risk assessment and LCA was of benefit to decision making process by suppling information about input/output data sensitivity, health effect priority and health risk distribution. There should be further research needs for case study using this methodology.

  • PDF