A New Approach for the Evaluation of Structural Failure by Credibility Distribution

2020 ◽  
Vol 14 (1) ◽  
pp. 217-227
Author(s):  
Palash Dutta ◽  
Nisha Gohain
Keyword(s):  
Structural Reliability ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Present Approach ◽  
Structural Failure ◽  
New Approach ◽  
Failure Assessment ◽  
Probabilistic Nature ◽  
Assessment Problems ◽  
Failure Evaluation

Aim: To devise an effective structural failure analysis approach under uncertainty. Background: In reliability evaluation, plenty of factors are uncertain, or sometimes, spontaneously represented via linguistic expressions, and as a consequence, the traditionalist appraisal methods cannot capably handle the ambiguity and vagueness that occurs in reliability assessment components. Subsequently, this leads to the problem of tremendous computationally multifaceted and scanty correctness. Objective: To overcome the limitations and to develop efficiency as well as accuracy in structural failure evaluation techniques, an attempt has been made to devise a novel structural reliability assessment method via credibility distribution. Methods: To get rid of the problems of massive computationally difficult and inadequate precision, an algorithm has been devised using credibility sampling. To exhibit the novelty, validity, and applicability of the present approach, some structural failure assessment problems are solved along with a comparison with the existing approach. Results: The proposed method was verified by four examples and applied in structural analysis. It was observed that the present approach is technically sound and efficient; it can overcome all the drawbacks of the existing approach. Moreover, the approach can be executed in any uncertain situation. Conclusion: After evaluation of failure assessment, it is experienced that the increase in the number of simulations leads to better precision. Furthermore, it is encountered that when hybridization problems i.e., representation of imprecise components in the problem of structural failure, are both fuzzy and probabilistic nature, then the failure assessment is attained to be maximum.

scholarly journals A Practical Nonprobabilistic Reliability Assessment Method on Key Strata Shear Failure in Longwall Mining

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hebing Luan ◽  
Jiachen Wang ◽  
Guowei Ma ◽  
Ke Zhang
Keyword(s):  
Structural Reliability ◽  
Shear Failure ◽  
Longwall Mining ◽  
Reliability Assessment ◽  
Friction Angle ◽  
Assessment Method ◽  
Mechanical Tests ◽  
Potential Hazard ◽  
Support Design ◽  
Key Strata

Roof cutting has long been a potential hazard factor in longwall panels in some diggings in China. Meanwhile, the key strata structural reliability, which provides an assessment on the stability of overlying roof strata, may be a significant reference for support design in underground coal mines. This paper aims to investigate a practical nonprobabilistic reliability assessment method on key strata. The mechanical tests and the hollow inclusion triaxial strain tests were conducted to measure relevant mechanical parameters and in situ stress. Furthermore, against the typical failure features in Datong Diggings, China, a shear failure mechanical model of key strata is proposed. Then, an allowable-safety-factor based nonprobabilistic stability probability assessment method is given. The sensitivity of geometrical dimensions and uncertainty levels of friction angle and cohesion are further studied. It is found that thickness and span of key strata have more dominative effect on key strata’s stability compared with the other factor and the increase of uncertainty levels results in decrease of stability probability.

Efficient Reliability Assessment With the Conditional Probability Method

2018 ◽  
Vol 140 (8) ◽  
Author(s):  
Rami Mansour ◽  
Mårten Olsson
Keyword(s):  
Conditional Probability ◽  
Structural Reliability ◽  
A Priori ◽  
Reliability Assessment ◽  
Probability Of Failure ◽  
Assessment Method ◽  
Probability Method ◽  
Probability Of Survival ◽  
Design Variables ◽  
Reliability Method

Reliability assessment is an important procedure in engineering design in which the probability of failure or equivalently the probability of survival is computed based on appropriate design criteria and model behavior. In this paper, a new approximate and efficient reliability assessment method is proposed: the conditional probability method (CPM). Focus is set on computational efficiency and the proposed method is applied to classical load-strength structural reliability problems. The core of the approach is in the computation of the probability of failure starting from the conditional probability of failure given the load. The number of function evaluations to compute the probability of failure is a priori known to be 3n + 2 in CPM, where n is the number of stochastic design variables excluding the strength. The necessary number of function evaluations for the reliability assessment, which may correspond to expensive computations, is therefore substantially lower in CPM than in the existing structural reliability methods such as the widely used first-order reliability method (FORM).

A New Reliability Assessment Method for Complex Nuclear Power Equipment Based on Goal Oriented Methodology

2017 ◽  
Author(s):  
Yi Xiao-jian ◽  
Lu Ming-chao ◽  
Mu Hui-na ◽  
Shi Jian ◽  
Hou Peng
Keyword(s):  
Nuclear Power ◽  
System Analysis ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Power Equipment ◽  
Test Unit ◽  
New Approach ◽  
Electronic Control System ◽  
Go Model ◽  
Mean Time

This paper presents a new reliability assessment method for complex nuclear power equipment based on Goal Oriented (GO) method to evaluate Mean Time To Failures (MTTF). First, the new reliability assessment method is expounded in detail. And its process is formulated. Then, the electronic control system of hoisting mechanism in nuclear power plant is taken as an example to evaluate its MTTF by the new method. The reliability assessment processes are mainly as follows: (i) Conducting system analysis, (ii) Developing GO model, (iii) Selecting test unit by qualitative analysis of GO method, (iv) Collecting test data, (v) Estimating the failure rate of test unit, (vi) Evaluating system MTTF. In order to verify the advantages and rationality of the new reliability assessment method, the results are compared with the results by Monte Carlo method. All in all, this reliability assessment method not only improves the theory of GO method, which is only used to conduct reliability analysis before; but also provides a new approach for reliability assessment of complex nuclear power equipment, so than it can reduces costs, and improve estimating efficiency and accuracy.

scholarly journals Structural Reliability Assessment by Integrating Sensitivity Analysis and Support Vector Machine

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Shao-Fei Jiang ◽  
Da-Bao Fu ◽  
Si-Yao Wu
Keyword(s):  
Sensitivity Analysis ◽  
Support Vector Machine ◽  
Structural Reliability ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Reliability Theory ◽  
Performance Comparison ◽  
Support Vector ◽  
Performance Function ◽  
Small Influence

To reduce the runtime and ensure enough computation accuracy, this paper proposes a structural reliability assessment method by the use of sensitivity analysis (SA) and support vector machine (SVM). The sensitivity analysis is firstly applied to assess the effect of random variables on the values of performance function, while the small-influence variables are rejected as input vectors of SVM. Then, the trained SVM is used to classify the input vectors, which are produced by sampling the residual variables based on their distributions. Finally, the reliability assessment is implemented with the aid of reliability theory. A 10-bar planar truss is used to validate the feasibility and efficiency of the proposed method, and a performance comparison is made with other existing methods. The results show that the proposed method can largely save the runtime with less reduction of the accuracy; furthermore, the accuracy using the proposed method is the highest among the methods employed.

Structural Reliability Assessment of Offshore Platforms Under Hurricane Events

2007 ◽  
Author(s):  
Liangsheng Wang ◽  
Kaisheng Chen ◽  
Justin Bucknell
Keyword(s):  
Structural Reliability ◽  
Structural Integrity ◽  
Limit State ◽  
Reliability Assessment ◽  
Assessment Method ◽  
Environmental Data ◽  
State Function ◽  
Offshore Platforms ◽  
Wave Load ◽  
Reliability Method

This paper presents a structural reliability assessment method to quantify the probability of platform failure for Trinidad offshore platforms subjected to hurricane events. Platforms are modeled as a series system composed of the topsides and jacket including foundation. The platform failure limit state function is defined in terms of environmental load and platform capacity. The platform capacity is evaluated by non-linear pushover analysis using USFOS program. A parametric relationship of wave load as a function of wave height is derived based on the offshore extreme environmental data. The first order reliability method (FORM) is used to estimate the annual failure probability. The relationship between the probability of platform failure and the reserve strength ratio (RSR) of platforms is investigated. The assessment results could be used to evaluate the level of risk associated with hurricane hazards and may be incorporated into the risk-based underwater inspection (RBUI) program as part of the structural integrity management (SIM) process.

A new approach to reliability assessment of dental caries examinations

2012 ◽  
Vol 41 (4) ◽  
pp. 309-316 ◽  
Author(s):  
Yacoub Altarakemah ◽  
Mona Al-Sane ◽  
Sungwoo Lim ◽  
Albert Kingman ◽  
Amid I. Ismail
Keyword(s):  
Dental Caries ◽  
Reliability Assessment ◽  
New Approach

GENERALIZED UNCERTAINTY IN STRUCTURAL RELIABILITY ASSESSMENT

1994 ◽  
Vol 11 (2) ◽  
pp. 81-110 ◽  
Author(s):  
KWAN-LING LAI Research Assistant ◽  
BILAL M. AYYUB Member, ASCE
Keyword(s):  
Structural Reliability ◽  
Reliability Assessment
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