A Reliability Model Validation Method for Mitigating the Effects of Measurement Uncertainty

2019 ◽  
Author(s):  
Mohammadkazem Sadoughi ◽  
Meng Li ◽  
Joseph Beck ◽  
Chao Hu
Keyword(s):  
Measurement Uncertainty ◽  
Model Validation ◽  
Experimental Measurement ◽  
Limit State ◽  
Reliability Estimation ◽  
State Function ◽  
Reliability Model ◽  
Estimation Model ◽  
Validation Method ◽  
Failure Data

Abstract With the increasing role of numerical modeling in engineering design and development processes, improved techniques are needed for validating computational results against experimental measurements. Most existing validation methods suffer from two main limitations: (i) they are often highly sensitive to the experimental measurement uncertainty, and (ii) extending these methods for reliability model validation requires large quantities of failure data that may be very time-consuming or costly to obtain. In order to overcome the aforementioned limitations, this study proposes an indirect reliability model validation method. First, a new procedure for computing a validation metric is developed based on Richardson extrapolation (RE) to reduce the sensitivity of the metric to the experimental measurement uncertainty. Second, a new validation metric is defined based on the limit state function (LSF) approximation to extend numerical model validation to reliability model validation. The proposed method is illustrated by validating a reliability estimation model for a cantilever beam under a vertical load.

scholarly journals Reliability Estimation for Highway Bridges

2020 ◽  
Author(s):  
Nafiseh Kiani
Keyword(s):  
Reliability Index ◽  
Structural Reliability ◽  
Limit State ◽  
Highway Bridges ◽  
Reliability Estimation ◽  
State Function ◽  
Limit States ◽  
Resistance Factors ◽  
Load And Resistance Factors ◽  
Reliability Methods

Structural reliability analysis is necessary to predict the uncertainties which may endanger the safety of structures during their lifetime. Structural uncertainties are associated with design, construction and operation stages. In design of structures, different limit states or failure functions are suggested to be considered by design specifications. Load and resistance factors are two essential parameters which have significant impact on evaluating the uncertainties. These load and resistance factors are commonly determined using structural reliability methods. The purpose of this study is to determine the reliability index for a typical highway bridge by considering the maximum moment generated by vehicle live loads on the bridge as a random variable. The limit state function was formulated and reliability index was determined using the First Order Reliability Methods (FORM) method.

scholarly journals A Non-Parametric Approach for Survival Analysis of Component-Based Software

2020 ◽  
Vol 5 (2) ◽  
pp. 309-318
Author(s):  
Sandeep Chopra ◽  
Lata Nautiyal ◽  
Preeti Malik ◽  
Mangey Ram ◽  
Mahesh K. Sharma
Keyword(s):  
Survival Analysis ◽  
Failure Rate ◽  
Growth Models ◽  
Reliability Estimation ◽  
Parametric Models ◽  
Model Parameters ◽  
Parametric Approach ◽  
Estimation Model ◽  
Failure Data ◽  
Non Parametric

Reliability of a software or system is the probability of system to perform its functions adequately for the stated time period under specific environment conditions. In case of component-based software development reliability estimation is a crucial factor. Existing reliability estimation model falls into two broad categories parametric and non-parametric models. Parametric models approximate the model parameters based on the assumptions of fundamental distributions. Non-parametric models enable parameter estimation of the software reliability growth models without any assumptions. We have proposed a novel non-parametric approach for survival analysis of components. Failure data is collected based on which we have calculated failure rate and reliability of the software. Failure rate increases with the time whereas reliability decreases with the time.

A Methodology for Model-Based Reliability Estimation

2014 ◽  
pp. 450-472
Author(s):  
Mohd Adham Isa ◽  
Dayang Norhayati Abang Jawawi
Keyword(s):  
Reliability Analysis ◽  
Reliability Assessment ◽  
Reliability Estimation ◽  
Reliability Model ◽  
Estimation Model ◽  
Domain Experts ◽  
Reliability Models ◽  
Model Based ◽  
Reliability Parameters ◽  
Estimate Reliability

In recent years, reliability assessment is an essential process in system quality assessments. However, the best practice of software engineering for reliability analysis is not yet of its matured stage. The existing works are only capable to explicitly apply a small portion of reliability analysis in a standard software development process. In addition, an existing reliability assessment is based on an assumption provided by domain experts. This assumption is often exposed to errors. An effective reliability assessment should be based on reliability requirements that could be quantitatively estimated using metrics. The reliability requirements can be visualized using reliability model. However, existing reliability models are not expressive enough and do not provide consistence-modeling mechanism to allow developers to estimate reliability parameter values. Consequently, the reliability estimation using those parameters is usually oversimplified. With this situation, the inconsistency problem could happen between different estimation stages. In this chapter, a new Model-Based Reliability Estimation (MBRE) methodology is developed. The methodology consists of reliability model and reliability estimation model. The methodology provides a systematic way to estimate system reliability, emphasizing the reliability model for producing reliability parameters which will be used by the reliability estimation model. These models are built upon the timing properties, which is the primary input value for reliability assessment.

Effect of Boundary Conditions of Failure Pressure Models on Reliability Estimation of Buried Pipelines

2004 ◽  
Vol 261-263 ◽  
pp. 803-808
Author(s):  
Ouk Sub Lee ◽  
Jang Sik Pyun ◽  
Si Won Hwang ◽  
Kyoo Sung Cho
Keyword(s):  
Boundary Conditions ◽  
Failure Probability ◽  
Probability Model ◽  
Limit State ◽  
Fluid Pressure ◽  
Taylor Series Expansion ◽  
Reliability Estimation ◽  
State Function ◽  
Buried Pipelines ◽  
Failure Pressure

This paper presents the effect of boundary conditions of various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the help of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure periods with unit of years. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

Efficient Assessment of Structural Reliability in Presence of Random and Fuzzy Uncertainties

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
A. S. Balu ◽  
B. N. Rao
Keyword(s):  
Function Approximation ◽  
Structural Reliability ◽  
Limit State ◽  
Reliability Estimation ◽  
High Dimensional Model Representation ◽  
State Function ◽  
Convolution Integral ◽  
Possibility Distribution ◽  
Fuzzy Variables ◽  
Uncertain Variables

This paper presents an efficient uncertainty analysis for estimating the possibility distribution of structural reliability in presence of mixed uncertain variables. The proposed method involves high dimensional model representation for the limit state function approximation, transformation technique to obtain the contribution of the fuzzy variables to the convolution integral and fast Fourier transform for solving the convolution integral. In this methodology, efforts are required in evaluating conditional responses at a selected input determined by sample points, as compared to full scale simulation methods, thus the computational efficiency is accomplished. The proposed method is applicable for structural reliability estimation involving any number of fuzzy and random variables with any kind of distribution.

Reliability Estimation of Solder Joint Utilizing Thermal Fatigue Models

2005 ◽  
Vol 297-300 ◽  
pp. 1816-1821
Author(s):  
Ouk Sub Lee ◽  
No Hoon Myoung ◽  
Dong Hyeok Kim
Keyword(s):  
Solder Joint ◽  
Thermal Fatigue ◽  
Failure Probability ◽  
Coefficient Of Thermal Expansion ◽  
Probability Model ◽  
Limit State ◽  
Reliability Estimation ◽  
State Function ◽  
First Order ◽  
Reliability Method

The differences of coefficient of thermal expansion (CTE) of component and FR-4 board connected by solder joint generally cause the dissimilarity in shear strain and failure in solder joint when they are heated. The first order Taylor series expansion of the limit state function (LSF) incorporating with thermal fatigue models is used in order to estimate the failure probability of solder joints under heated condition. Various thermal fatigue models, classified into five categories: categories four such as plastic strain-based, creep strain-based, energy-based, and damage-based except stress-based, are utilized in this study. The effects of random variables such as CTE, distance of the solder joint from neutral point (DNP), temperature variation and height of solder on the failure probability of the solder joint are systematically investigated by using a failure probability model with the first order reliability method (FORM) and thermal fatigue models.

Effects of Various Types of Distribution on Probabilistic Method and FAD

2007 ◽  
Vol 353-358 ◽  
pp. 2561-2564
Author(s):  
Ouk Sub Lee ◽  
Dong Hyeok Kim
Keyword(s):  
Failure Probability ◽  
Probabilistic Method ◽  
Limit State ◽  
Random Variables ◽  
Reliability Estimation ◽  
Probabilistic Methods ◽  
State Function ◽  
Operating Pressure ◽  
Lognormal Distributions ◽  
Reliability Method

The reliability estimation of pipeline is performed in accordance with the probabilistic methods such as the FORM (first order reliability method) and the SORM (second order reliability method). A limit state function has been formulated with help of the FAD (failure assessment diagram). Various types of distribution of random variables are assumed to investigate its effect on the failure probability. It is noted that the failure probability increases with the increase of the dent depth, the operating pressure and the outside radius, and the decrease of the wall thickness. Furthermore it is found that the failure probability for the random variables having the Weibull distribution is larger than those of the normal and the lognormal distributions.

Guided tail modelling for efficient and accurate reliability estimation of highly safe mechanical systems

2011 ◽  
Vol 225 (5) ◽  
pp. 1237-1251 ◽  
Author(s):  
E Acar
Keyword(s):  
Limit State ◽  
Mathematical Problem ◽  
Generalized Pareto Distribution ◽  
Monte Carlo Sampling ◽  
Reliability Estimation ◽  
State Function ◽  
Distribution Fitting ◽  
Tail Region ◽  
Tail Part ◽  
State Approximation

Classical tail modelling is based on performing a relatively small number of limit-state calculations through Monte Carlo sampling, and then fitting a generalized Pareto distribution to the tail part of the data. The limit-state calculations that do not belong to the tail part are discarded. To reduce the amount of discarded data, this article proposes an efficient tail modelling procedure based on guiding the limit-state evaluations towards the sampling points that have high chances of yielding limit-state values falling into the tail region. The guidance of the limit-state evaluations is achieved through a procedure that utilizes limit-state approximation and distribution fitting. The accuracy of the proposed method is tested through a mathematical problem and four structural mechanics problems, and it is found that the accuracy of reliability estimations can be significantly increased compared to classical tail modelling techniques for the same number of limit-state function evaluations. In addition, it is also found that the improvement in accuracy can be traded off for reducing the number of limit-state evaluations.

scholarly journals Uncertainty propagation in structural reliability with implicit limit state functions under aleatory and epistemic uncertainties

2021 ◽  
Vol 23 (2) ◽  
pp. 231-241
Author(s):  
Shuang Zhou ◽  
Jianguo Zhang ◽  
Lingfei You ◽  
Qingyuan Zhang
Keyword(s):  
Structural Reliability ◽  
Least Squares Method ◽  
Limit State ◽  
Uniform Design ◽  
Uncertainty Propagation ◽  
Reliability Estimation ◽  
Estimation Methods ◽  
State Function ◽  
Chance Theory ◽  
Theory Uncertainty

Uncertainty propagation plays a pivotal role in structural reliability assessment. This paper introduces a novel uncertainty propagation method for structural reliability under different knowledge stages based on probability theory, uncertainty theory and chance theory. Firstly, a surrogate model combining the uniform design and least-squares method is presented to simulate the implicit limit state function with random and uncertain variables. Then, a novel quantification method based on chance theory is derived herein, to calculate the structural reliability under mixed aleatory and epistemic uncertainties. The concepts of chance reliability and chance reliability index (CRI) are defined to show the reliable degree of structure. Besides, the selection principles of uncertainty propagation types and the corresponding reliability estimation methods are given according to the different knowledge stages. The proposed methods are finally applied in a practical structural reliability problem, which illustrates the effectiveness and advantages of the techniques presented in this work.

Effect of Boundary Conditions of Failure Pressure Models on Reliability Estimation of Buried Pipelines

2003 ◽  
Author(s):  
Ouk Sub Lee ◽  
Jang Sik Pyun ◽  
Dong Hyeok Kim
Keyword(s):  
Boundary Conditions ◽  
Failure Probability ◽  
Probability Model ◽  
Limit State ◽  
Fluid Pressure ◽  
Random Variables ◽  
Reliability Estimation ◽  
State Function ◽  
Buried Pipelines ◽  
Failure Pressure

This paper presents the effect of boundary conditions of various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the help of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

Sign in / Sign up

Export Citation Format

Share Document