A method of assigning a limit probability of failure

2013 ◽  
Vol 42 (1) ◽  
pp. 41-44 ◽  
Author(s):  
A. O. Chernyavskii ◽  
M. M. Shatov
Keyword(s):  
Probability Of Failure ◽  
Limit Probability

STOCHASTIC CALCULATION OF LIFETIME PREDICTION FOR COMPONENTS IN METAL STRUCTURES DUE TO THE GROWTH OF MICRODEFECTS

2020 ◽  
Vol 4 (97) ◽  
pp. 69-76
Author(s):  
IGOR N. SILVERSTOV
Keyword(s):  
Fatigue Strength ◽  
Fracture Mechanics ◽  
Stochastic Approach ◽  
Fatigue Curve ◽  
Probability Of Failure ◽  
Lifetime Prediction ◽  
Statistical Distributions ◽  
Metal Structures

A stochastic approach has been developed to evaluate fatigue strength using elements of the fracture mechanics. The article presents a method for determining the initial parameters of statistical distributions. It also considers the method for constructing a fatigue curve for a component of any size and configuration with any given probability of failure.

Vulnerability-Based Design of Sliding Concave Bearings for the Seismic Isolation of Steel Storage Tanks

2016 ◽  
Author(s):  
Hoang Nam Phan ◽  
Fabrizio Paolacci ◽  
Silvia Alessandri ◽  
Phuong Hoa Hoang
Keyword(s):  
Liquid Steel ◽  
Seismic Isolation ◽  
Failure Modes ◽  
Fragility Curves ◽  
Time History ◽  
Probability Of Failure ◽  
Design Parameters ◽  
Economic Losses ◽  
Storage Tanks ◽  
Isolation System

Liquid steel storage tanks are strategic structures for industrial facilities and have been widely used both in nuclear and non-nuclear power plants. Typical damage to tanks occurred during past earthquakes such as cracking at the bottom plate, elastic or elastoplastic buckling of the tank wall, failure of the ground anchorage system, and sloshing damage around the roof, etc. Due to their potential and substantial economic losses as well as environmental hazards, implementations of seismic isolation and energy dissipation systems have been recently extended to liquid storage tanks. Although the benefits of seismic isolation systems have been well known in reducing seismic demands of tanks; however, these benefits have been rarely investigated in literature in terms of reduction in the probability of failure. In this paper, A vulnerability-based design approach of a sliding concave bearing system for an existing elevated liquid steel storage tank is presented by evaluating the probability of exceeding specific limit states. Firstly, nonlinear time history analyses of a three-dimensional stick model for the examined case study are performed using a set of ground motion records. Fragility curves of different failure modes of the tank are then obtained by the well-known cloud method. In the following, a seismic isolation system based on concave sliding bearings is proposed. The effectiveness of the isolation system in mitigating the seismic response of the tank is investigated by means of fragility curves. Finally, an optimization of design parameters for sliding concave bearings is determined based on the reduction of the tank vulnerability or the probability of failure.

A Review of Crack Detection In-Line Inspection Case Studies

2010 ◽  
Author(s):  
Neil Bates ◽  
David Lee ◽  
Clifford Maier
Keyword(s):  
Crack Growth ◽  
Case Studies ◽  
Crack Detection ◽  
Growth Parameters ◽  
Probability Distributions ◽  
Low Frequency ◽  
Probability Of Failure ◽  
Probability Of Detection ◽  
Inspection Data

This paper describes case studies involving crack detection in-line inspections and fitness for service assessments that were performed based on the inspection data. The assessments were used to evaluate the immediate integrity of the pipeline based on the reported features and the long-term integrity of the pipeline based on excavation data and probabilistic SCC and fatigue crack growth simulations. Two different case studies are analyzed, which illustrate how the data from an ultrasonic crack tool inspection was used to assess threats such as low frequency electrical resistance weld seam defects and stress corrosion cracking. Specific issues, such as probability of detection/identification and the length/depth accuracy of the tool, were evaluated to determine the suitability of the tool to accurately classify and size different types of defects. The long term assessment is based on the Monte Carlo method [1], where the material properties, pipeline details, crack growth parameters, and feature dimensions are randomly selected from certain specified probability distributions to determine the probability of failure versus time for the pipeline segment. The distributions of unreported crack-related features from the excavation program are used to distribute unreported features along the pipeline. Simulated crack growth by fatigue, SCC, or a combination of the two is performed until failure by either leak or rupture is predicted. The probability of failure calculation is performed through a number of crack growth simulations for each of the reported and unreported features and tallying their respective remaining lives. The results of the probabilistic analysis were used to determine the most effective and economical means of remediation by identifying areas or crack mechanisms that contribute most to the probability of failure.

scholarly journals Evaluation of Bearing Capacity of Strip Footing Using Random Layers Concept

2015 ◽  
Vol 37 (3) ◽  
pp. 31-39 ◽  
Author(s):  
Marek Kawa ◽  
Dariusz Łydżba
Keyword(s):  
Monte Carlo ◽  
Bearing Capacity ◽  
Failure Mechanism ◽  
Design Theory ◽  
Cohesive Soil ◽  
Probability Of Failure ◽  
Mean Value ◽  
Strip Footing ◽  
Random Field Theory ◽  
The Mean

Abstract The paper deals with evaluation of bearing capacity of strip foundation on random purely cohesive soil. The approach proposed combines random field theory in the form of random layers with classical limit analysis and Monte Carlo simulation. For given realization of random the bearing capacity of strip footing is evaluated by employing the kinematic approach of yield design theory. The results in the form of histograms for both bearing capacity of footing as well as optimal depth of failure mechanism are obtained for different thickness of random layers. For zero and infinite thickness of random layer the values of depth of failure mechanism as well as bearing capacity assessment are derived in a closed form. Finally based on a sequence of Monte Carlo simulations the bearing capacity of strip footing corresponding to a certain probability of failure is estimated. While the mean value of the foundation bearing capacity increases with the thickness of the random layers, the ultimate load corresponding to a certain probability of failure appears to be a decreasing function of random layers thickness.

Sign in / Sign up

Export Citation Format

Share Document