• Title/Summary/Keyword: probabilistic assessment

Search Result 722, Processing Time 0.024 seconds

Probabilistic Remaining Life Assessment Program for Creep Crack Growth (크리프 균열성장 모델에 대한 확률론적 수명예측 프로그램)

  • Kim, Kun-Young;Shoji, Tetsuo;Kang, Myung-Soo
    • Journal of the Korean Society for Precision Engineering
    • /
    • v.16 no.6
    • /
    • pp.100-107
    • /
    • 1999
  • This paper describes a probabilistic remaining life assessment program for the creep crack growth. The probabilistic life assessment program is developed to increase the reliability of life assessment. The probabilistic life assessment involves some uncertainties, such as, initial crack size, material properties, and loading condition, and a triangle distribution function is used for random variable generation. The resulting information provides the engineer with an assessment of the probability of structural failure as a function of operating time given the uncertainties in the input data. This study forms basis of the probabilistic life assessment technique and will be extended to other damage mechanisms.

  • PDF

Differences by Selection Method for Exposure Factor Input Distribution for Use in Probabilistic Consumer Exposure Assessment

  • Kang, Sohyun;Kim, Jinho;Lim, Miyoung;Lee, Kiyoung
    • Journal of Environmental Health Sciences
    • /
    • v.48 no.5
    • /
    • pp.266-271
    • /
    • 2022
  • Background: The selection of distributions of input parameters is an important component in probabilistic exposure assessment. Goodness-of-fit (GOF) methods are used to determine the distribution of exposure factors. However, there are no clear guidelines for choosing an appropriate GOF method. Objectives: The outcomes of probabilistic consumer exposure assessment were compared by using five different GOF methods for the selection of input distributions: chi-squared test, Kolmogorov-Smirnov test (K-S), Anderson-Darling test (A-D), Akaike information criterion (AIC) and Bayesian information criterion (BIC). Methods: Individual exposures were estimated based on product usage factor combinations from 10,000 respondents. The distribution of individual exposure was considered as the true value of population exposures. Results: Among the five GOF methods, probabilistic exposure distributions using the A-D and K-S methods were similar to individual exposure estimations. Comparing the 95th percentiles of the probabilistic distributions and the individual estimations for 10 CPs, there were 0.73 to 1.92 times differences for the A-D method, and 0.73 to 1.60 times differences (excluding tire-shine spray) for the K-S method. Conclusions: There were significant differences in exposure assessment results among the selection of the GOF methods. Therefore, the GOF methods for probabilistic consumer exposure assessment should be carefully selected.

Systems Engineering Process Approach to the Probabilistic Safety Assessment for a Spent Fuel Pool of a Nuclear Power Plant (사용후핵연료저장조의 확률론적안전성평가 수행을 위한 시스템엔지니어링 프로세스 적용 연구)

  • Choi, Jin Tae;Cha, Woo Chang
    • Journal of the Korean Society of Systems Engineering
    • /
    • v.17 no.2
    • /
    • pp.82-90
    • /
    • 2021
  • The spent fuel pool (SFP) of a nuclear power plant functions to store the spent fuel. The spent fuel pool is designed to properly remove the decay heat generated from the spent fuel. If the cooling function is lost and proper operator action is not taken, the spent fuel in the storage pool can be damaged. Probabilistic safety assessment (PSA) is a safety evaluation method that can evaluate the risk of a large and complex system. So far, the probabilistic safety assessment of nuclear power plants has been mainly performed on the reactor. This study defined the requirements and the functional architecture for the probabilistic safety assessment of the spent fuel pool (SFP-PSA) by applying the systems engineering process. And, a systematic and efficient methodology was defined according to the architecture.

Probabilistic Damage Mechanics Assessment of Wall-Thinned Nuclear Piping Using Reliability Method and Monte-Carlo Simulation (신뢰도지수 및 몬데카를로 시뮬레이션을 이용한 원전 감육배관의 확률론적 손상역학 평가)

  • Lee Sang-Min;Yun Kang-Ok;Chang Yoon-Suk;Choi Jae-Boong;Kim Young-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.29 no.8 s.239
    • /
    • pp.1102-1108
    • /
    • 2005
  • The integrity of nuclear piping systems has to be maintained sufficiently all the times during operation. In order to maintain the integrity, reliable assessment procedures including fracture mechanics analysis, etc, are required. Up to now, the integrity assessment has been performed using conventional deterministic approach even though there are lots of uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for piping system evaluation. The objectives of this paper are to develop a probabilistic assessment program using reliability index and simulation technique and to estimate the damage probability of wall-thinned pipes in secondary systems. The probabilistic assessment program consists of three evaluation modules which are first order reliability method, second order reliability method and Monte Carlo simulation method. The developed program has been applied to evaluate damage probabilities of wall-thinned pipes subjected to internal pressure, global bending moment and combined loading. The sensitivity analysis results as well as prototypal evaluation results showed a promising applicability of the probabilistic integrity assessment program.

Probabilistic optimal safety valuation based on stochastic finite element analysis of steel cable-stayed bridges

  • Han, Sung-Ho;Bang, Myung-Seok
    • Smart Structures and Systems
    • /
    • v.10 no.2
    • /
    • pp.89-110
    • /
    • 2012
  • This study was intended to efficiently perform the probabilistic optimal safety assessment of steel cable-stayed bridges (SCS bridges) using stochastic finite element analysis (SFEA) and expected life-cycle cost (LCC) concept. To that end, advanced probabilistic finite element algorithm (APFEA) which enables to execute the static and dynamic SFEA considering aleatory uncertainties contained in random variable was developed. APFEA is the useful analytical means enabling to conduct the reliability assessment (RA) in a systematic way by considering the result of SFEA based on linearity and nonlinearity of before or after introducing initial tensile force. The appropriateness of APFEA was verified in such a way of comparing the result of SFEA and that of Monte Carlo Simulation (MCS). The probabilistic method was set taking into account of analytical parameters. The dynamic response characteristic by probabilistic method was evaluated using ASFEA, and RA was carried out using analysis results, thereby quantitatively calculating the probabilistic safety. The optimal design was determined based on the expected LCC according to the results of SFEA and RA of alternative designs. Moreover, given the potential epistemic uncertainty contained in safety index, failure probability and minimum LCC, the sensitivity analysis was conducted and as a result, a critical distribution phase was illustrated using a cumulative-percentile.

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

Multi-unit Level 1 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site

  • Kim, Dong-San;Han, Sang Hoon;Park, Jin Hee;Lim, Ho-Gon;Kim, Jung Han
    • Nuclear Engineering and Technology
    • /
    • v.50 no.8
    • /
    • pp.1217-1233
    • /
    • 2018
  • Following a surge of interest in multi-unit risk in the last few years, many recent studies have suggested methods for multi-unit probabilistic safety assessment (MUPSA) and addressed several related aspects. Most of the existing studies though focused on two-unit nuclear power plant (NPP) sites or used rather simplified probabilistic safety assessment (PSA) models to demonstrate the proposed approaches. When considering an NPP site with three or more units, some approaches are inapplicable or yield very conservative results. Since the number of such sites is increasing, there is a strong need to develop and validate practical approaches to the related MUPSA. This article provides several detailed approaches that are applicable to multi-unit Level 1 PSA for sites with up to six or more reactor units. To validate the approaches, a multi-unit Level 1 PSA model is developed and the site core damage frequency is estimated for each of four representative multi-unit initiators, as well as for the case of a simultaneous occurrence of independent single-unit initiators in multiple units. For this purpose, an NPP site with six identical OPR-1000 units is considered, with full-scale Level 1 PSA models for a specific OPR-1000 plant used as the base single-unit models.

Influence Analysis of Seismic Risk due to the Failure Correlation in Seismic Probabilistic Safety Assessment (다중기기 손상 상관성에 의한 지진리스크 영향 분석)

  • Eem, Seung-Hyun;Choi, In-Kil
    • Journal of the Earthquake Engineering Society of Korea
    • /
    • v.23 no.2
    • /
    • pp.101-108
    • /
    • 2019
  • The seismic safety of nuclear power plants has always been emphasized by the effects of accidents. In general, the seismic safety evaluation of nuclear power plants carries out a seismic probabilistic safety assessment. The current probabilistic safety assessment assumes that damage to the structure, system, and components (SSCs) occurs independently to each other or perfect dependently to each other. In case of earthquake events, the failure event occurs with the correlation due to the correlation between the seismic response of the SSCs and the seismic performance of the SSCs. In this study, the EEMS (External Event Mensuration System) code is developed which can perform the seismic probabilistic safety assessment considering correlation. The developed code is verified by comparing with the multiplier n, which is for calculating the joint probability of failure, which is proposed by Mankamo. It is analyzed the changes in seismic fragility curves and seismic risks with correlation. As a result, it was confirmed that the seismic fragility curves and seismic risk change according to the failure correlation coefficient. This means that it is important to select an appropriate failure correlation coefficient in order to perform a seismic probabilistic safety assessment. And also, it was confirmed that carrying out the seismic probabilistic safety assessment in consideration of the seismic correlation provides more realistic results, rather than providing conservative or non-conservative results comparing with that damage to the SSCs occurs independently.

Failure Probability Evaluation of Pressure Tube using the Probabilistic Fracture Mechanics (확률론적 파괴역학 기법을 이용한 압력관의 파손확률 평가)

  • Son, Jong-Dong;Oh, Dong-Joon
    • Journal of the Korean Society of Safety
    • /
    • v.22 no.4
    • /
    • pp.7-12
    • /
    • 2007
  • In order to evaluate the integrity of Zr-2.5Nb pressure tubes, probabilistic fracture mechanics(PFM) approach was employed. Failure assessment diagram(FAD), plastic collapses, and critical crack lengths(CCL) were used for evaluating the failure probability as failure criteria. The Kr-FAD as failure assessment diagram was used because fracture of pressure tubes occurred in brittle manner due to hydrogen embrittlement of material by deuterium fluence. The probabilistic integrity evaluation observed AECL procedures and used fracture toughness parameters of EPRI and recently announced theory. In conclusion, the probabilistic approach using the Kr-FAD made it possible to determine major failure criterion in the pressure tube integrity evaluation.

DOProC-based reliability analysis of structures

  • Janas, Petr;Krejsa, Martin;Sejnoha, Jiri;Krejsa, Vlastimil
    • Structural Engineering and Mechanics
    • /
    • v.64 no.4
    • /
    • pp.413-426
    • /
    • 2017
  • Probabilistic methods are used in engineering where a computational model contains random variables. The proposed method under development: Direct Optimized Probabilistic Calculation (DOProC) is highly efficient in terms of computation time and solution accuracy and is mostly faster than in case of other standard probabilistic methods. The novelty of the DOProC lies in an optimized numerical integration that easily handles both correlated and statistically independent random variables and does not require any simulation or approximation technique. DOProC is demonstrated by a collection of deliberately selected simple examples (i) to illustrate the efficiency of individual optimization levels and (ii) to verify it against other highly regarded probabilistic methods (e.g., Monte Carlo). Efficiency and other benefits of the proposed method are grounded on a comparative case study carried out using both the DOProC and MC techniques. The algorithm has been implemented in mentioned software applications, and has been used effectively several times in solving probabilistic tasks and in probabilistic reliability assessment of structures. The article summarizes the principles of this method and demonstrates its basic possibilities on simple examples. The paper presents unpublished details of probabilistic computations based on this method, including a reliability assessment, which provides the user with the probability of failure affected by statistically dependent input random variables. The study also mentions the potential of the optimization procedures under development, including an analysis of their effectiveness on the example of the reliability assessment of a slender column.