• Journal of the Korean Society for Precision Engineering
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• v.16 no.6
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• pp.100-107
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• 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.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.185-202
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• 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.

• Journal of Environmental Impact Assessment
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• v.9 no.3
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• pp.203-214
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• 2000

Health risk assessment is applied to streamlining LCA(Life Cycle Assessment) using Monte carlo simulation for probabilistic/stochastic exposure and risk distribution analysis caused by data variability and uncertainty. A case study was carried out to find benefits of this application. BTC(Benzene, Trichloroethylene, Carbon tetrachloride mixture alias) personal exposure cases were assumed as production worker(in workplace), manager(in office) and business man(outdoor). These cases were different from occupational retention time and exposure concentration for BTC consumption pattern. The result of cancer risk in these 3 scenario cases were estimated as $1.72E-4{\pm}1.2E+0$(production worker; case A), $9.62E-5{\pm}1.44E-5$(manger; case B), $6.90E-5{\pm}1.16E+0$(business man; case C), respectively. Portions of over acceptable risk 1.00E-4(assumed standard) were 99.85%, 38.89% and 0.61%, respectively. Estimated BTC risk was log-normal pattern, but some of distributions did not have any formal patterns. Except first impact factor(BTC emission quantity), sensitivity analysis showed that main effective factor was retention time in their occupational exposure sites. This case study is a good example to cover that LCA with probabilistic risk analysis tool can supply various significant information such as statistical distribution including personal/environmental exposure level, daily time activity pattern and individual susceptibility. Further research is needed for investigating real data of these input variables and personal exposure concentration and application of this study methodology.

• Computers and Concrete
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• v.18 no.1
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• pp.69-97
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• 2016

Performance-based remaining life assessment of reinforced concrete bridge girders, subject to chloride-induced corrosion of reinforcement, is addressed in this paper. Towards this, a methodology that takes into consideration the human judgmental aspects in expert decision making regarding condition state assessment is proposed. The condition of the bridge girder is specified by the assignment of a condition state from a set of predefined condition states, considering both serviceability- and ultimate- limit states, and, the performance of the bridge girder is described using performability measure. A non-homogeneous Markov chain is used for modelling the stochastic evolution of condition state of the bridge girder with time. The thinking process of the expert in condition state assessment is modelled within a probabilistic framework using Brunswikian theory and probabilistic mental models. The remaining life is determined as the time over which the performance of the girder is above the required performance level. The usefulness of the methodology is illustrated through the remaining life assessment of a reinforced concrete T-beam bridge girder.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.234-239
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• 2004

A study on the probabilistic methodology for the estimation of the remaining life of Pressurized pipelines containing active corrosion defects is presented. This reliability assessment is earned out using extream value distribution of the corroded defects instead of already published failure perssure moded like NG18 or ASME B31G. The failure probability of pipelines depends on the number of corroded defects. and it could be calculated directly as the area exceeded a defined L V(Limited Value of corrosion depth). The remaining life of pressurized pipelines can also be estimated by the PDF of extream value distribution as calculating the exceeded area with a defined failure probability.

• Smart Structures and Systems
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• v.10 no.2
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• pp.89-110
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• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.11 s.254
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• pp.1417-1424
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• 2006

In order to evaluate variation of fatigue life of mechanical components including engineering plastics, it is important to estimate probabilistic strain-life curves to accurately define the variation of fatigue characteristics. This paper intends to provide new assessment of P-$\varepsilon$-N (probabilistic strain-life curves) for considering the variation of fatigue characteristics in polyacetal. The fatigue strain controlled tests were conducted under constant 50% humidity and room temperature condition by a universal testing machine at strain ratio, R=0. A practical procedure is introduced to evaluate probabilistic strain-life curves. Three probabilistic distributions were used for generating P-$\varepsilon$-N curves such as normal, 2-parameter and 3-parameter Weibull. In this study, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue characteristic were examined using chi-square and Kolmogorov-Smirnov test. The more appropriate P-$\varepsilon$-N curves for these materials are generated by the proposed method considering 3-parameter Weibull distribution.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.8
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• pp.619-624
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• 2013

To predict the probabilistic service life, statistical factors should be included to consider the uncertainty of parameters. Generally the probabilistic analysis is one of the common methods to account the uncertainty of parameters on the structural failure. In order to apply probabilistic analysis on the deterministic life analysis, it would be necessary to introduce Probability of Failure(PoF) and conduct risk assessment. In this work, we have studied probabilistic risk assessment of aircraft structures by using PoF approach. To achieve this goal, the Bayesian method was utilized to model PoF estimation since this method is known as the proper method to express the uncertainty of parameters. A series of proof tests were also conducted in order to verify the result of PoF estimation. The results from this efforts showed that the PoF estimation model can calculate quantitatively the value of PoF. Furthermore effectiveness of risk assessment approach for the aircraft structures was also demonstrated.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.48-55
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• 2016

The assessment and prediction of service life of a structure are usually under uncertainty so that rational probabilistic concepts and methods have to be applied. Based on these rational assessment and prediction, optimum maintenance strategies to minimize the life-cycle cost and/or maximize the structural safety can be established. The service life assessment and prediction considering maintenance actions generally includes effects of maintenance types and times of the structural components on the service life extensions of structural system. Existing researches on the service life management have revealed the appropriate system modeling considering the correlation among the components is required for system reliability analysis and probabilistic service life estimation. However, the study on correlation among the maintenance actions is still required. This paper deals with such a study for more effective and efficient service life management. In this paper, both the preventive and essential maintenances are considered for the extended service life estimation and management.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.109-118
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• 2004

Life cycle assessment (LCA) usually involves some uncertainty. These uncertainties are generally divided in two categories such lack of data and data inaccuracy in life cycle inventory (LCI). This paper explo.es a methodology on dealing with uncertainty due to lack of data in LCI. In order to treat uncertainty of LCI data, a model for data uncertainty is proposed. The model works with probabilistic curves as inputs and with Monte Carlo Simulation techniques to propagate uncertainty. The probabilistic curves were derived from the results of survey in expert network and Monte Carlo Simulation was performed using the derived probabilistic curves. The results of Monte Carlo Simulation were verified by statistical test. The proposed approach should serve as a guide to improve data quality and deal with uncertainty of LCI data in LCA projects.