Structural reliability and risk models

2013 ◽  
pp. 533-533
Keyword(s):  
Structural Reliability ◽  
Risk Models

Functional and operational risk as a criterion for assessing the durability of an autonomous energy system

2019 ◽  
Vol 12 (1) ◽  
pp. 56-62 ◽  
Author(s):  
A. O. Nedosekin ◽  
A. V. Smirnov ◽  
D. P. Makarenko ◽  
Z. I. Abdoulaeva
Keyword(s):  
Service Life ◽  
Structural Reliability ◽  
Residual Life ◽  
Fuzzy Random Variable ◽  
Operational Risk ◽  
Energy System ◽  
Technical System ◽  
Residual Service Life ◽  
Technological Parameters ◽  
Residual Service

The article presents new models and methods for estimating the residual service life of an autonomous energy system, using the functional operational risk criterion (FOR). The purpose of the article is to demonstrate a new method of durability evaluation using the fuzzy logic and soft computing framework. Durability in the article is understood as a complex property directly adjacent to the complex property of system resilience, as understood in the Western practice of assessing and ensuring the reliability of technical systems. Due to the lack of reliable homogeneous statistics on system equipment failures and recoveries, triangular fuzzy estimates of failure and recovery intensities are used as fuzzy functions of time based on incomplete data and expert estimates. The FOR in the model is the possibility for the system availability ratio to be below the standard level. An example of the evaluation of the FOR and the residual service life of a redundant cold supply system of a special facility is considered. The transition from the paradigm of structural reliability to the paradigm of functional reliability based on the continuous degradation of the technological parameters of an autonomous energy system is considered. In this case, the FOR can no longer be evaluated by the criterion of a sudden failure, nor is it possible to build a Markov’s chain on discrete states of the technical system. Assuming this, it is appropriate to predict the defi ning functional parameters of a technical system as fuzzy functions of a general form and to estimate the residual service life of the technical system as a fuzzy random variable. Then the FOR is estimated as the possibility for the residual life of the technical system to be below its warranty period, as determined by the supplier of the equipment.

A Comparison of Divorce Risk Models in China and the United States

2011 ◽  
Vol 42 (2) ◽  
pp. 289-295
Author(s):  
Anqi Xu ◽  
Yuanting Zhang ◽  
Paul R Amato
Keyword(s):  
United States ◽  
The United States ◽  
Risk Models ◽  
Divorce Risk

STRUCTURAL RELIABILITY ANALYSIS BASED ON P-BOXES

2020 ◽  
Vol 92 (6) ◽  
pp. 51-58
Author(s):  
S.A. SOLOVYEV ◽  
Keyword(s):  
Probability Distribution ◽  
Reliability Analysis ◽  
Structural Reliability ◽  
Epistemic Uncertainty ◽  
Random Variable ◽  
Strength Criterion ◽  
Structural Elements ◽  
Structural Element ◽  
Limit States ◽  
Distribution Shape

The article describes a method for reliability (probability of non-failure) analysis of structural elements based on p-boxes. An algorithm for constructing two p-blocks is shown. First p-box is used in the absence of information about the probability distribution shape of a random variable. Second p-box is used for a certain probability distribution function but with inaccurate (interval) function parameters. The algorithm for reliability analysis is presented on a numerical example of the reliability analysis for a flexural wooden beam by wood strength criterion. The result of the reliability analysis is an interval of the non-failure probability boundaries. Recommendations are given for narrowing the reliability boundaries which can reduce epistemic uncertainty. On the basis of the proposed approach, particular methods for reliability analysis for any structural elements can be developed. Design equations are given for a comprehensive assessment of the structural element reliability as a system taking into account all the criteria of limit states.

Structural Reliability of Brittle Materials at High Temperatures.

1984 ◽  
Author(s):  
S. M. Wiederhorn ◽  
N. J. Tighe ◽  
T. J. Chuang ◽  
K. A. Hardman-Rhyne ◽  
B. J. Hockey
Keyword(s):  
High Temperatures ◽  
Structural Reliability ◽  
Brittle Materials

Integrating multi-market risk models

2007 ◽  
Vol 10 (2) ◽  
pp. 25-45
Author(s):  
Peter Shepard
Keyword(s):  
Market Risk ◽  
Risk Models
Sign in / Sign up

Export Citation Format

Share Document