Reliability Analysis for the Feeder Subject to Wall Loss

2012 ◽  
Author(s):  
Min Wang ◽  
Xianxun Yuan ◽  
Xinjian Duan ◽  
Michael J. Kozluk
Keyword(s):  
Reliability Analysis ◽  
Wall Thickness ◽  
Structural Reliability ◽  
Structural Integrity ◽  
Degradation Mechanism ◽  
Linear Regression Analysis ◽  
Probabilistic Methods ◽  
Piping System ◽  
Wall Thinning ◽  
Reliability Method

Wall thinning is one of the most common degradation mechanisms experienced in piping system. Gradual wall thinning can cause the pipe to leak or in the worst scenario, to rupture. Wall thinning due to FAC of feeder pipe in CANDU® reactors has been identified as an active degradation mechanism, and local thinning has been observed in various locations such as elbows/bends and Grayloc. The assessment of structural integrity is important for the fitness-for-service of those feeders whose wall thickness is predicted to be lower than the required minimum wall thickness before their design life and therefore subject to costly repair or replacement. Among various probabilistic methods, the first-order reliability method (FORM) is adopted in this paper to evaluate the structural reliability of feeders subject to wall thinning, while the wall thickness, one of the key parameters in the reliability analysis, is modeled by three methods based on the wall thickness measurements. They are linear regression analysis, random thinning rate analysis and gamma process modeling. The difference and limitation of the methods for reliability analysis are addressed.

scholarly journals Time-Dependent Reliability Analysis of Reinforced Concrete Beams Subjected to Uniform and Pitting Corrosion and Brittle Fracture

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 1820
Author(s):  
Mohamed El Amine Ben Seghier ◽  
Behrooz Keshtegar ◽  
Hussam Mahmoud
Keyword(s):  
Reinforced Concrete ◽  
Brittle Fracture ◽  
Reliability Analysis ◽  
Pitting Corrosion ◽  
Structural Reliability ◽  
Time Dependent ◽  
State Function ◽  
Rc Beams ◽  
Highly Nonlinear ◽  
Reliability Method

Reinforced concrete (RC) beams are basic elements used in the construction of various structures and infrastructural systems. When exposed to harsh environmental conditions, the integrity of RC beams could be compromised as a result of various deterioration mechanisms. One of the most common deterioration mechanisms is the formation of different types of corrosion in the steel reinforcements of the beams, which could impact the overall reliability of the beam. Existing classical reliability analysis methods have shown unstable results when used for the assessment of highly nonlinear problems, such as corroded RC beams. To that end, the main purpose of this paper is to explore the use of a structural reliability method for the multi-state assessment of corroded RC beams. To do so, an improved reliability method, namely the three-term conjugate map (TCM) based on the first order reliability method (FORM), is used. The application of the TCM method to identify the multi-state failure of RC beams is validated against various well-known structural reliability-based FORM formulations. The limit state function (LSF) for corroded RC beams is formulated in accordance with two corrosion types, namely uniform and pitting corrosion, and with consideration of brittle fracture due to the pit-to-crack transition probability. The time-dependent reliability analyses conducted in this study are also used to assess the influence of various parameters on the resulting failure probability of the corroded beams. The results show that the nominal bar diameter, corrosion initiation rate, and the external loads have an important influence on the safety of these structures. In addition, the proposed method is shown to outperform other reliability-based FORM formulations in predicting the level of reliability in RC beams.

scholarly journals Dynamic Reliability Analysis of Corroded Pipeline Using Bayesian Network

2018 ◽  
Vol 7 (4.35) ◽  
pp. 210
Author(s):  
Nurul Sa’aadah Sulaiman ◽  
Henry Tan
Keyword(s):  
Bayesian Network ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Dynamic Bayesian Network ◽  
Operating Pressure ◽  
Dynamic Reliability ◽  
Time Dynamic ◽  
Remaining Service Life ◽  
Reliability Method ◽  
Deterioration Process

Maintenance and integrity management of hydrocarbons pipelines face the challenges from uncertainties in the data available. This paper demonstrates a way for pipeline remaining service life prediction that integrates structural reliability analysis, accumulated corrosion knowledge, and inspection data on a sound mathematical foundation. Pipeline defects depth grows with time according to an empirical corrosion power law, and this is checked for leakage and rupture probability. The pipeline operating pressure is checked with the degraded failure pressure given by ASME B31G code for rupture likelihood. As corrosion process evolves with time, Dynamic Bayesian Network (DBN) is employed to model the stochastic corrosion deterioration process. From the results obtained, the proposed DBN model for pipeline reliability is advanced compared with other traditional structural reliability method whereby the updating ability brings in more accurate prediction results of structural reliability. The comparisons show that the DBN model can achieve a realistic result similar to the conventional method, Monte Carlo Simulation with very minor discrepancy.

Fracture mechanics in design and service: ‘living with defects’ - Statistical aspects of design: risk assessment and structural integrity

1981 ◽  
Vol 299 (1446) ◽  
pp. 111-130 ◽  
Keyword(s):  
Fracture Mechanics ◽  
Structural Reliability ◽  
Structural Integrity ◽  
Product Liability ◽  
Probabilistic Methods ◽  
Statistical Variations ◽  
Engineering Designs ◽  
Recent Developments ◽  
Quantitative Basis ◽  
And Control

Statistical variations in input parameters that affect structural reliability have historically been incorporated approximately in engineering designs by application of safety factors. Increased concerns over the injury potential and costs of licensing, insurance, field repairs or recalls, and product liability claims now demand more quantitative evaluation of possible flaws or unusual usage conditions that might result from statistical variations or uncertainties. This paper describes the basic concepts of probabilistic fracture mechanics that are used to assess and control risk. Recent developments in combined analysis methods are presented that utilize field experience data with probabilistic analysis to improve the accuracy of the structural integrity predictions. Several specific examples are described that illustrate how these probabilistic methods are used to assess risk and to provide a quantitative basis for establishing design, operation or maintenance allowables. These procedures, which realistically model the actual statistical variations that exist, can eliminate unnecessarily conservative approximations and often achieve improved reliability at reduced cost.

Reliability Analysis of Ultimate Strength of a Capesize Bulk Carrier in Hogging and Alternate Hold Loading Condition

2010 ◽  
Author(s):  
Zhi Shu ◽  
Torgeir Moan
Keyword(s):  
Reliability Analysis ◽  
Ultimate Strength ◽  
Loading Condition ◽  
Structural Reliability ◽  
Bulk Carrier ◽  
Local Loads ◽  
Reliability Method ◽  
Bulk Carriers ◽  
Bending Capacity ◽  
Global And Local

This paper deals with the structural reliability analysis (SRA) of ultimate strength of a Capesize bulk carrier in hogging and alternate hold loading condition (AHL). The ultimate strength in hogging and AHL condition is very important for the safety of bulk carriers since the local loads due to internal cargo loads and external sea pressure can reduce the ultimate bending capacity. In the present paper, the characteristic ultimate bending capacity of the subject bulk carrier is investigated by nonlinear finite element (FE) analysis and the characteristic value of the global and local loads are determined in accordance with the Common Structural Rules for bulk carriers (CSR-BC). The uncertainties associated with the loading capacity and load effects are appropriately modelled. The First Order Reliability Method (FORM) is adopted to calculate the annual probability of failure of this bulk carrier in hogging and AHL condition. The effect of heavy weather avoidance on the global and local loads is also evaluated in the SRA. The results show that the local loads have a significant impact on the failure probability of such vessels in the hogging and AHL condition.

First-Order Reliability Method for Structural Reliability Analysis in the Presence of Random and Interval Variables

2015 ◽  
Vol 1 (4) ◽  
Author(s):  
Umberto Alibrandi ◽  
C. G. Koh
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Computational Cost ◽  
Computational Effort ◽  
Stochastic Dynamic ◽  
First Order Reliability Method ◽  
First Order ◽  
Structural Reliability Analysis ◽  
Reliability Method

This paper presents a novel procedure based on first-order reliability method (FORM) for structural reliability analysis in the presence of random parameters and interval uncertain parameters. In the proposed formulation, the hybrid problem is reduced to standard reliability problems, where the limit state functions are defined only in terms of the random variables. Monte Carlo simulation (MCS) for hybrid reliability analysis (HRA) is presented, and it is shown that it requires a tremendous computational effort; FORM for HRA is more efficient but still demanding. The computational cost is significantly reduced through a simplified procedure, which gives good approximations of the design points, by requiring only three classical FORMs and one interval analysis (IA), developed herein through an optimization procedure. FORM for HRA and its simplified formulation achieve a much improved efficiency than MCS by several orders of magnitude, and it can thus be applied to real-world engineering problems. Representative examples of stochastic dynamic analysis and performance-based engineering are presented.

A Vine-Copula-Based Reliability Analysis Method for Structures With Multidimensional Correlation

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
C. Jiang ◽  
W. Zhang ◽  
X. Han ◽  
B. Y. Ni ◽  
L. J. Song
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Computational Method ◽  
Joint Probability Distribution ◽  
Analysis Method ◽  
Analysis Model ◽  
Copula Functions ◽  
Solution Algorithms ◽  
Reliability Method ◽  
Vine Copula

This paper proposed a vine-copula-based structural reliability analysis method which is an effective approach for performing a reliability analysis on complex multidimensional correlation problems. A joint probability distribution function (PDF) among multidimensional random variables was established using a vine copula function, based on which a reliability analysis model was constructed. Two solution algorithms were proposed to solve this reliability analysis model: one was based on Monte Carlo simulation (MCS) and another one was based on the first-order reliability method (FORM). The former method provides a generalized computational method for a reliability analysis based on vine copula functions and can provide so-called “precise solutions”; the latter method has high computational efficiency and can be used to solve actual complex engineering problems. Finally, three numerical examples were provided to verify the effectiveness of the method.

scholarly journals An improved approach by introducing copula functions for structural reliability analysis under hybrid uncertainties

2018 ◽  
Vol 10 (7) ◽  
pp. 168781401878583 ◽  
Author(s):  
Zheng Liu ◽  
Xin Liu
Keyword(s):  
Probability Theory ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Field Tests ◽  
Copula Function ◽  
Working Environment ◽  
Imprecise Probability ◽  
Copula Functions ◽  
Structural Reliability Analysis ◽  
Reliability Method

The structural composition of the oil platform is very complicated, and its working environment is harsh, thus conducting a large number of reliability tests is not feasible, and the field tests are also hard to accomplish. So the reliability of the oil platform cannot be analyzed and calculated by the traditional reliability method which needs a lot of test data, and new methods should be studied. In recent years, imprecise probability theory has attracted more and more attention because when unified, it can quantify hybrid uncertainty. Structural reliability analysis on the basis of imprecise probability theory has made remarkable achievements in theoretical aspects, but it is scarcely used in practical engineering domains due to the complexity in the developed methods and the unavailability of suitable or specific modeling steps for applications. In this regard, we propose a unified quantification method for statistical data, fuzzy data, incomplete information, and the like, which can handle the issue of hybrid uncertainties, and then, we construct an improved imprecise structural reliability model aiming at the practical problems by introducing copula function. To verify the existing methodology, we also consider a cantilever beam widely applied in the oil platform here for the structural reliability analysis.

Supplementary Technical Basis for ASME Section XI Code Case N-597

2005 ◽  
Author(s):  
Doug Scarth
Keyword(s):  
Wall Thickness ◽  
Structural Integrity ◽  
Computer Code ◽  
Nuclear Regulatory Commission ◽  
Original Design ◽  
Acceptance Criteria ◽  
Accelerated Corrosion ◽  
Wall Thinning ◽  
Technical Basis ◽  
Flow Accelerated Corrosion

Efforts to develop clear and conservative methods to measure and evaluate wall thinning in nuclear piping have been underway since the late 1980’s. The Electric Power Research Institute (EPRI) carried out a successful campaign to address programmatic issues, such as locating and predicting flow-accelerated corrosion (FAC) degradation. This included developing a computer code (CHECWORKS), a users group (CHUG), and a comprehensive program guideline document for the effective prediction, identification and trending of flow-accelerated corrosion degradation. U.S. Nuclear Regulatory Commission (NRC) guidelines are provided in the NRC Inspection Manual Inspection Procedure 49001. At the same time, committees under Section XI of the ASME Boiler and Pressure Vessel Code have addressed evaluation of structural integrity of piping subjected to wall thinning. Code Case N-480 of Section XI provided acceptance criteria that focused on primary piping stresses, with evaluation based on a uniform wall thinning assumption for evaluating the minimum wall thickness of the piping. However, when applying this methodology to low pressure piping systems, Code Case N-480 was very conservative. Code Case N-597 was first published in 1998, and supercedes Code Case N-480. The current version is N-597-2. Code Case N-597-2 provides acceptance criteria and evaluation procedures for piping items, including fittings, subjected to a wall thinning mechanism, such as flow-accelerated corrosion. Code Case N-597-2 is a significant improvement over N-480, containing distinct elements to be satisfied in allowing the licensee to operate with piping degraded by wall thinning. The Code Case considers separately wall thickness requirements and piping stresses, and maintains original design intent margins. The Code Case does not provide requirements for locations of inspection, inspection frequency or method of prediction of rate of wall thinning. As described in the original technical basis document published at the 1999 ASME PVP Conference, the piping stress evaluation follows very closely the Construction Codes for piping. Five conditions related to industry use of Code Case N-597-1 have been published by the NRC in Regulatory Guide 1.147, Revision 13. A number of these issues are related to a need for additional explanation of the technical basis for the Code Case, such as the procedures for evaluation of wall thickness less than the ASME Code Design Pressure-based minimum allowable wall thickness. This presentation addresses these NRC conditions by providing additional description of the technical basis for the Code Case.

Risk-Informed Structural Integrity Management: Development of SMR-Centric Piping Reliability Models

2014 ◽  
Author(s):  
Bengt Lydell
Keyword(s):  
Stainless Steel ◽  
Austenitic Stainless Steel ◽  
Structural Integrity ◽  
Degradation Mechanism ◽  
Management Strategies ◽  
Mitigation Strategies ◽  
Parameter Estimates ◽  
Piping System ◽  
Reliability Models ◽  
Integrity Management

In the context of risk-informed applications, this paper addresses the progress with piping reliability analysis methods and techniques and their role in supporting development of risk-informed structural integrity programs for small modular reactors (SMRs). The structural integrity of a pressure boundary is determined by multiple and interrelated reliability attributes and influence factors. Depending on the conjoint requirements for damage and degradation, certain combinations of material, operating environment, loading conditions together with applicable design codes and standards, certain passive components are substantially more resistant to damage and degradation than others. As an example, for stabilized austenitic stainless steel pressure boundary components, there are no recorded events involving active, through-wall leakage. By contrast, for unstabilized austenitic stainless steel, multiple events involving through-wall leakage have been recorded, albeit with relative minor leak rates. The field experience with safety- and non-safety related piping in commercial GenI through GenIII nuclear power reactors is quite extensive. Equally extensive is the experience gained from the implementation of different degradation mechanism mitigation strategies. By applying advanced piping reliability models, this body engineering data and integrity management insights can be used to assess the projected structural integrity of new piping system designs, including those of SMRs. The paper presents an overview of recent methodological advances and insights from the application of statistical piping reliability models to advanced reactor designs. Examples are provided on how piping reliability parameter estimates are affected by different integrity management strategies as well as by advanced, degradation mechanism (DM) resistant materials. The technical basis for the work that is presented in this paper has evolved over a period of 20+ years of focused and sustained R&D in the area of statistical models of piping reliability.

The Impact of Probabilistic Modeling in Life-Cycle Management of Nuclear Piping Systems

2010 ◽  
Vol 133 (1) ◽  
Author(s):  
M. D. Pandey ◽  
D. Lu ◽  
D. Komljenovic
Keyword(s):  
Life Cycle ◽  
End Of Life ◽  
Wall Thickness ◽  
Probabilistic Models ◽  
Structural Integrity ◽  
Life Cycle Management ◽  
Limiting Factor ◽  
Piping System ◽  
Practical Case ◽  
The Impact

Flow accelerated corrosion (FAC) is a serious form of degradation in primary heat transport piping system (PHTS) of the nuclear reactor. Pipes transporting hot coolant from the reactor to steam generators are particularly vulnerable to FAC degradation, such as tight radius pipe bends with high flow velocity. FAC is a life limiting factor, as excessive degradation can result in the loss of structural integrity of the pipe. To prevent this, engineering codes and regulations have specified minimum wall thickness requirements to ensure fitness for service of the piping system. Nuclear utilities have implemented periodic wall thickness inspection programs and carried out replacement of pipes prior to reaching an unsafe state. To optimize the life-cycle management of PHTS, accurate prediction of time of replacement or “end of life” of pipe sections is important. Since FAC is a time-dependent process of uncertain nature, this paper presents two probabilistic models for predicting the end of life. This paper illustrates that the modeling assumptions have a significant impact on the predicted number of replacements and life-cycle management of the nuclear piping system. A practical case study is presented using wall thickness inspection data collected from Canadian nuclear plants.

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