• Proceedings of the KSME Conference
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• 2004.04a
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• pp.54-59
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• 2004

In this paper probabilistic fracture mechanics(PFM) approach is employed to evaluate the integrity of CANDU Zr-2.5Nb pressure tubes. Modified failure assessment diagram(Jr-FAD), plastic collapse, and critical crack length(CCL) approach are used for evaluating failure probability of the tubes. Jr-FAD was extended from the Kr-FAD because fracture of pressure tubes occurs in brittle manner due to hydrogen embrittlement of material by deuterium fluence. For developing the probabilistic integrity evaluation module, AECL procedures and fracture toughness parameters of EPRI were used.

• 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.

• Geomechanics and Engineering
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• v.38 no.1
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• pp.93-106
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• 2024

The present paper investigates the spatial variability effect of soil property on the three-dimensional probabilistic characteristics of the bearing capacity factor (i.e., mean and coefficient of variation) of a circular footing resting on clayey soil where both mean and standard deviation of undrained shear strength increases with depth, keeping the coefficient of variation constant. The mean trend of undrained shear strength is defined by introducing the dimensionless strength gradient parameter. The finite difference method along with the random field and Monte Carlo simulation technique, is used to execute the numerical analyses. The lognormal distribution is chosen to generate random fields of the undrained shear strength. In the study, the potential failure of the structure is represented through the failure probability. The influences of different vertical scales of fluctuation, dimensionless strength gradient parameters, and coefficient of variation of undrained shear strength on the probabilistic characteristics of the bearing capacity factor and failure probability of the footing, along with the probability and cumulative density functions, are explored in this study. The variations of failure probability for different factors of safety corresponding to different parameters are also illustrated. The results are presented in non-dimensional form as they might be helpful to the practicing engineers dealing with this type of problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.667-670
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• 2001

For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PEM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. For the verification of this analysis, a comparison study of th PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.987-996
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• 2003

The structural integrity of the reactor vessel with the approaching end of life must be assured for pressurized thermal shock. The regulation specifies the screening criteria for this and requires that specific analysis be performed for the reactor vessel which is anticipated to exceed the screening criteria at the end of plant life. In case the screening criteria is exceeded by the deterministic analysis, probabilistic analysis must be performed to show that failure probability Is within the limit. In this study, probabilistic fracture mechanics analysis of the reactor vessel for pressurized thermal shock is performed and the effects of residual stress and master curve on the failure probability are investigated.

• Proceedings of the KSME Conference
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• 2001.06a
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• pp.459-464
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• 2001

For major nuclear power plant components periodic inspections and integrity assessments are needed for the safety. But many flaws are undetectable due to sampling inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties, applied load and undetectable flaws. This paper describes a Probabilistic Fracture Mechanics(PFM) analysis based on Monte Carlo(MC) algorithms. Taking important parameters as probabilistic variables such as fracture toughness, crack growth rate and flaw shape, failure probability of major nuclear power plant components is archived as a results of MC simulation. For the verification of these analysis, a comparison study of the PFM analysis using other commercial code, mathematical method is carried out and a good agreement was observed between those results.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.3
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• pp.24-29
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• 2006

Pressurized gas pipelines are subject to harmful effects from both the surrounding environment and the materials passing through them. Reliable assessment procedures, including fracture mechanics analyses, are required to maintain their integrity. Currently, integrity assessments are performed using conventional deterministic approaches, even though there are many uncertainties to hinder rational evaluations. Therefore, in this study, a probabilistic approach was considered for gas pipeline evaluations. The objectives were to estimate the failure probability of a corroded pipeline in the gas and oil industries and to propose limited operating conditions for different types of loadings. To achieve these objectives, a probabilistic assessment program was developed using a reliability index and simulation techniques, and applied to evaluate the failure probabilities of a corroded API-5L-X52 gas pipeline subjected to internal pressures, bending moments, and combined loadings. The results demonstrated the potential of the probabilistic integrity assessment program.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.158-166
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• 2005

Pressurized gas pipeline is subject to harmful effects both of the surrounding environment and of the materials transmitted in them. In order to maintain the integrity, reliable assessment procedures including tincture mechanics analysis etc are required. Up to now, the integrity assessment has been performed using conventional deterministic approaches even though there are many uncertainties to hinder a rational evaluation. In this respect, probabilistic approach is considered as an appropriate method for gas pipeline evaluation. The objectives of this paper are to estimate the failure probability of corroded pipeline in gas and oil plants and to propose limited operating conditions under different types of leadings. To do this, a probabilistic assessment program using reliability index and simulation techniques was developed and applied to evaluate failure probabilities of corroded API-5L-X52/X60 gas pipelines subjected to internal pressure, bending moment and combined loading. The evaluation results showed a promising applicability of the probabilistic integrity assessment program.

• Nuclear Engineering and Technology
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• v.44 no.5
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• pp.471-482
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• 2012

To assess the risk of nuclear power plant operation and to determine the risk impact of digital systems, there is a need to quantitatively assess the reliability of the digital systems in a justifiable manner. The Probabilistic Risk Analysis (PRA) is a tool which can reveal shortcomings of the NPP design in general and PRA analysts have not had sufficient guiding principles in modelling particular digital components malfunctions. Currently digital I&C systems are mostly analyzed simply and conventionally in PRA, based on failure mode and effects analysis and fault tree modelling. More dynamic approaches are still in the trial stage and can be difficult to apply in full scale PRA-models. As basic events CPU failures, application software failures and common cause failures (CCF) between identical components are modelled.The primary goal is to model dependencies. However, it is not clear which failure modes or system parts CCF:s should be postulated for. A clear distinction can be made between the treatment of protection and control systems. There is a general consensus that protection systems shall be included in PRA, while control systems can be treated in a limited manner. OECD/NEA CSNI Working Group on Risk Assessment (WGRisk) has set up a task group, called DIGREL, to develop taxonomy of failure modes of digital components for the purposes of PRA. The taxonomy is aimed to be the basis of future modelling and quantification efforts. It will also help to define a structure for data collection and to review PRA studies.

• Structural Engineering and Mechanics
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• v.64 no.4
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• pp.413-426
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• 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.