scholarly journals The Evaluation Of Algorithms For Determination Of The Reliability Index

2015 ◽  
Vol 61 (3) ◽  
pp. 133-147 ◽  
Author(s):  
A. Dudzik ◽  
U. Radoń
Keyword(s):  
Reliability Index ◽  
Limit State ◽  
Probabilistic Approach ◽  
Random Variables ◽  
Numerical Procedure ◽  
Vertical Displacement ◽  
Design Parameters ◽  
State Function ◽  
Structural Failure

AbstractThe study deals with stability and dynamic problems in bar structures using a probabilistic approach. Structural design parameters are defined as deterministic values and also as random variables, which are not correlated. The criterion of structural failure is expressed by the condition of non-exceeding the admissible load multiplier and condition of non-exceeding the admissible vertical displacement. The Hasofer-Lind index was used as a reliability measure. The primary research tool is the FORM method. In order to verify the correctness of the calculations Monte Carlo and Importance Sampling methods were used. The sensitivity of the reliability index to the random variables was defined. The limit state function is not an explicit function of random variables. This dependence was determined using a numerical procedure, e.g. the finite element methods. The paper aims to present the communication between the STAND reliability analysis program and the KRATA and MES3D external FE programs.

The Comparison of Methods of Assessing the Reliability of the Steel Frame

2015 ◽  
Vol 797 ◽  
pp. 11-18
Author(s):  
Agnieszka Dudzik ◽  
Urszula Radoń
Keyword(s):  
Reliability Index ◽  
Limit State ◽  
Probabilistic Approach ◽  
Random Variables ◽  
Random Variable ◽  
Design Parameters ◽  
Variable Sensitivity ◽  
Index Sensitivity ◽  
The Impact ◽  
The Mathematical Model

The study presents a probabilistic approach to the problems of static analysis of a steel building. Structural design parameters were defined as deterministic values and random variables. The latter were not correlated. The criterion of structural failure is expressed by limit functions related to the ultimate and serviceability limit state. The description of limit functions by the Mathematica program was generated. The Hasofer-Lind index was used as a reliability measure. In the description of random variables were used the normal distribution and, for comparison, different types of probability distribution appropriate to the nature of the variable. Sensitivity of reliability index to the random variables was defined. If the reliability index sensitivity due to the random variable Xi is low when compared with other variables, it can be stated that the impact of this variable on failure probability is small. Therefore, in successive computations it can be treated as a deterministic parameter. Sensitivity analysis leads to simplify the description of the mathematical model, determine the new limit functions and values of the Hasofer-Lind reliability index. The primary research method is the FORM method. In order to verify the correctness of the calculation SORM, Monte Carlo and Importance Sampling methods were used. In the examples of reliability analysis the STAND program was used.

scholarly journals The proposal of explicit account of the random character of design process parameters

2013 ◽  
Vol 12 (1) ◽  
pp. 219-226
Author(s):  
Agnieszka Dudzik ◽  
Urszula Radoń
Keyword(s):  
Structural Design ◽  
Reliability Index ◽  
Research Method ◽  
Sampling Methods ◽  
Limit State ◽  
Random Variables ◽  
Design Parameters ◽  
Structural Failure ◽  
Primary Research ◽  
Random Character

The study concerns the static analysis of rods structures in terms of probabilism. Structural design parameters are defined as the deterministic values and random variables. Random variables are not correlated. The criterion for structural failure is expressed the limits of functions referring to the ultimate and serviceability limit state. The Cornell and Hasofer-Lind index is used as a reliability measure. The primary research method is the FORM method. In order to verify the correctness of the calculation SORM, Monte Carlo and Importance Sampling methods are used. The sensitivity of reliability index to the random variables is defined. The STAND program is used to present the examples of reliability analysis.

Inversion analysis to determine design parameters for reliability assessment in pavement structures

2014 ◽  
Vol 41 (10) ◽  
pp. 845-855 ◽  
Author(s):  
Sungho Mun
Keyword(s):  
Reliability Index ◽  
Limit State ◽  
Reliability Assessment ◽  
Pavement Performance ◽  
Design Parameters ◽  
State Function ◽  
Limit State Function ◽  
Performance Function ◽  
Pavement Structures ◽  
Inversion Analysis

Reliability assessment has been used to evaluate the performance of pavement structures. However, probabilistic inversion analysis of pavement structure design has not yet been tested to determine the design parameters of the pavement performance function, given a specified reliability index. In this study, a limit state function numerical calculation and the inversion technique of the Nelder–Mead simplex algorithm were used to determine the design parameters for the pavement performance function. The method of moments was used to develop the forward limit state function, which was then compared to Monte Carlo simulations; the comparison indicated good agreement between the two methods. Additionally, several cases were studied to determine the design parameters of the pavement performance function for the reliability index specified in this study. The case studies indicated that the structure number significantly affected the pavement performance function.

Reliability Methods for Bimodal Distribution With First-Order Approximation1

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Zhangli Hu ◽  
Xiaoping Du
Keyword(s):  
Probability Density ◽  
Order Approximation ◽  
Limit State ◽  
Random Variables ◽  
Random Variable ◽  
State Function ◽  
First Order ◽  
Reliability Method ◽  
Reliability Methods ◽  
Basic Random Variable

In traditional reliability problems, the distribution of a basic random variable is usually unimodal; in other words, the probability density of the basic random variable has only one peak. In real applications, some basic random variables may follow bimodal distributions with two peaks in their probability density. When binomial variables are involved, traditional reliability methods, such as the first-order second moment (FOSM) method and the first-order reliability method (FORM), will not be accurate. This study investigates the accuracy of using the saddlepoint approximation (SPA) for bimodal variables and then employs SPA-based reliability methods with first-order approximation to predict the reliability. A limit-state function is at first approximated with the first-order Taylor expansion so that it becomes a linear combination of the basic random variables, some of which are bimodally distributed. The SPA is then applied to estimate the reliability. Examples show that the SPA-based reliability methods are more accurate than FOSM and FORM.

Reliability Analysis of Lead-Free Solders in Electronic Packaging Using a Novel Surrogate Model and Kriging Concept

2018 ◽  
Vol 140 (4) ◽  
Author(s):  
Hamoon Azizsoltani ◽  
Achintya Haldar
Keyword(s):  
Response Surface ◽  
Electronic Packaging ◽  
Limit State ◽  
Experimental Studies ◽  
Lead Free ◽  
Evaluation Procedure ◽  
Design Parameters ◽  
State Function ◽  
Thermomechanical Loading ◽  
Lead Free Solders

A novel reliability evaluation procedure of lead-free solders used in electronic packaging (EP) subjected to thermomechanical loading is proposed. A solder ball is represented by finite elements (FEs). Major sources of nonlinearities are incorporated as realistically as practicable. Uncertainties in all design variables are quantified using available information. The thermomechanical loading is represented by five design parameters and uncertainties associated with them are incorporated. Since the performance or limit state function (LSF) of such complicated problem is implicit in nature, it is approximately generated explicitly in the failure region with the help of a completely improved response surface method (RSM)-based approach and the universal Kriging method (KM). The response surface (RS) is generated by conducting as few deterministic nonlinear finite element analyses as possible by integrating several advanced factorial mathematical concepts producing compounding beneficial effect. The accuracy, efficiency, and application potential of the procedure are established with the help of Monte Carlo simulation (MCS) and the results from laboratory investigation reported in the literature. The study conclusively verified the proposed method. Similar studies can be conducted to fill the knowledge gap for cases where the available analytical and experimental studies are limited or extend the information to cases where reliability information is unavailable. The study showcased how reliability information can be extracted with the help of multiple deterministic analyses. The authors believe that they proposed an alternative to the classical MCS technique.

Uncertainty Quantification of Time-Dependent Reliability Analysis in the Presence of Parametric Uncertainty

2016 ◽  
Vol 2 (3) ◽  
Author(s):  
Zhen Hu ◽  
Sankaran Mahadevan ◽  
Xiaoping Du
Keyword(s):  
Uncertainty Quantification ◽  
Reliability Analysis ◽  
Surrogate Model ◽  
Reliability Index ◽  
Integration Method ◽  
Epistemic Uncertainty ◽  
Random Variables ◽  
Time Dependent ◽  
Data Uncertainty ◽  
State Function

Limited data of stochastic load processes and system random variables result in uncertainty in the results of time-dependent reliability analysis. An uncertainty quantification (UQ) framework is developed in this paper for time-dependent reliability analysis in the presence of data uncertainty. The Bayesian approach is employed to model the epistemic uncertainty sources in random variables and stochastic processes. A straightforward formulation of UQ in time-dependent reliability analysis results in a double-loop implementation procedure, which is computationally expensive. This paper proposes an efficient method for the UQ of time-dependent reliability analysis by integrating the fast integration method and surrogate model method with time-dependent reliability analysis. A surrogate model is built first for the time-instantaneous conditional reliability index as a function of variables with imprecise parameters. For different realizations of the epistemic uncertainty, the associated time-instantaneous most probable points (MPPs) are then identified using the fast integration method based on the conditional reliability index surrogate without evaluating the original limit-state function. With the obtained time-instantaneous MPPs, uncertainty in the time-dependent reliability analysis is quantified. The effectiveness of the proposed method is demonstrated using a mathematical example and an engineering application example.

Assessment of Fatigue Safety Factors for Deep-Water Risers in Relation to VIV

2005 ◽  
Vol 127 (4) ◽  
pp. 353-358 ◽  
Author(s):  
Bernt J. Leira ◽  
Trond Stokka Meling ◽  
Carl M. Larsen ◽  
Vidar Berntsen ◽  
Bernie Stahl ◽  
...  
Keyword(s):  
Fatigue Damage ◽  
Limit State ◽  
Random Variables ◽  
Response Surfaces ◽  
State Function ◽  
Safety Factors ◽  
Parameter Variations ◽  
Input Parameters ◽  
Steel Catenary Risers ◽  
Analytical Expressions

Safety factors required to control fatigue damage of deepwater metallic risers caused by vortex-induced vibration (VIV) are considered. Four different riser configurations are studied: Cases I and II: Vertical tensioned 12in. risers suspended from a spar buoy at water depths of 500 and 1500m. Cases III and IV: Steel catenary risers suspended from a spar buoy, both at 1000m. For Case III, the riser diameter is 12in., while for Case IV it is 33in. For each riser configuration, relevant design and analysis parameters which are subject to uncertainty are identified. For these quantities, random variables are established also representing model uncertainties. Subsequently, repeated analyses of fatigue damage are performed by varying the input parameters within representative intervals. The results are applied to fit analytical expressions (i.e., so-called response surfaces) utilized to describe the limit state function and to develop the probabilistic model for reliability analysis of the risers. By combining the random variables for the input parameters with the results from the parameter variations, a relationship between the fatigue safety factor and the failure probability is established for each riser configuration.

scholarly journals Reliability Evaluation of Bridges Based on Nonprobabilistic Response Surface Limit Method

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Xuyong Chen ◽  
Qian Chen ◽  
Xiaoya Bian ◽  
Jianping Fan
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Reliability Index ◽  
Limit State ◽  
Iteration Process ◽  
Evaluation Process ◽  
Reliability Evaluation ◽  
State Function ◽  
Interval Model ◽  
Surface Method

Due to many uncertainties in nonprobabilistic reliability assessment of bridges, the limit state function is generally unknown. The traditional nonprobabilistic response surface method is a lengthy and oscillating iteration process and leads to difficultly solving the nonprobabilistic reliability index. This article proposes a nonprobabilistic response surface limit method based on the interval model. The intention of this method is to solve the upper and lower limits of the nonprobabilistic reliability index and to narrow the range of the nonprobabilistic reliability index. If the range of the reliability index reduces to an acceptable accuracy, the solution will be considered convergent, and the nonprobabilistic reliability index will be obtained. The case study indicates that using the proposed method can avoid oscillating iteration process, make iteration process stable and convergent, reduce iteration steps significantly, and improve computational efficiency and precision significantly compared with the traditional nonprobabilistic response surface method. Finally, the nonprobabilistic reliability evaluation process of bridge will be built through evaluating the reliability of one PC continuous rigid frame bridge with three spans using the proposed method, which appears to be more simple and reliable when lack of samples and parameters in the bridge nonprobabilistic reliability evaluation is present.

Reliability Analysis of Foundation Pit by Improved Response Surface Method

2011 ◽  
Vol 147 ◽  
pp. 197-202 ◽  
Author(s):  
Jiang Zhou ◽  
Jing Cao ◽  
Yu He ◽  
Jie Song
Keyword(s):  
Reliability Analysis ◽  
Response Surface ◽  
Structural Reliability ◽  
Lateral Displacement ◽  
Limit State ◽  
Uniform Design ◽  
Design Parameters ◽  
State Function ◽  
Foundation Pit ◽  
Improved Response Surface Method

Lacking of explicit limit state function (LSF) will result large quantities of computational efforts for a FEAM based structural reliability analysis. An improved response surface (RS) method is proposed to analyze the failure probability of foundation pit through combining uniform design (UD) and non-parametric regression (NPR). Deferent levels of design parameters are first delicately selected according to UD and then FEAM is used to analysis corresponding pit response parameters including maximum lateral displacement of wall, settlement of ground, safety factor of overall stability, safety factors of against overturning, heave and piping. The RS relationship is then established through NPR based on inputs and responses. At last, a direct Mont Carlo Simulation is carried out to obtain the probability density function of response parameters.

Reliability-Based Topology Optimization Using Mean-Value Second-Order Saddlepoint Approximation

2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Dimitrios I. Papadimitriou ◽  
Zissimos P. Mourelatos
Keyword(s):  
Topology Optimization ◽  
Limit State ◽  
Random Variables ◽  
Saddlepoint Approximation ◽  
Probability Of Failure ◽  
Mean Value ◽  
Second Order ◽  
State Function ◽  
Sensitivity Derivatives ◽  
Reliability Method

A reliability-based topology optimization (RBTO) approach is presented using a new mean-value second-order saddlepoint approximation (MVSOSA) method to calculate the probability of failure. The topology optimizer uses a discrete adjoint formulation. MVSOSA is based on a second-order Taylor expansion of the limit state function at the mean values of the random variables. The first- and second-order sensitivity derivatives of the limit state cumulant generating function (CGF), with respect to the random variables in MVSOSA, are computed using direct-differentiation of the structural equations. Third-order sensitivity derivatives, including the sensitivities of the saddlepoint, are calculated using the adjoint approach. The accuracy of the proposed MVSOSA reliability method is demonstrated using a nonlinear mathematical example. Comparison with Monte Carlo simulation (MCS) shows that MVSOSA is more accurate than mean-value first-order saddlepoint approximation (MVFOSA) and more accurate than mean-value second-order second-moment (MVSOSM) method. Finally, the proposed RBTO-MVSOSA method for minimizing a compliance-based probability of failure is demonstrated using two two-dimensional beam structures under random loading. The density-based topology optimization based on the solid isotropic material with penalization (SIMP) method is utilized.

Sign in / Sign up

Export Citation Format

Share Document