scholarly journals Reliability Analysis via an Optimal Covariance Matrix Adaptation Evolution Strategy: Emphasis on Applications in Civil Engineering

2020 ◽  
Author(s):  
Ali Kaveh ◽  
Seyed Mohammad Javadi ◽  
Roya Mahdipour Moghanni
Keyword(s):  
Reliability Index ◽  
Civil Engineering ◽  
Limit State ◽  
Normal Space ◽  
State Function ◽  
Optimization Approach ◽  
Covariance Matrix Adaptation ◽  
Highly Nonlinear ◽  
Standard Normal ◽  
Reliability Based Optimization

In this paper, a reliability-based optimization approach is applied using a recently proposed CMA-ES with optimal covariance update and storage complexity. Cholesky-CMA-ES gives a significant increase in optimization speed and reduces the runtime complexity of the standard CMA-ES. The reliability index is the shortest distance between the surface of Limit-State Function (LSF) and the origin of the standard normal space. Hence, finding the reliability index can be expressed as a constrained optimization problem. To verify the concept and test the feasibility of this algorithm, several numerical examples consisting of mathematical and highly nonlinear civil engineering problems are investigated. The reliability indexes obtained agree reasonably well with reported values from some existing approximation methods and Monte Carlo simulation.

Optimal Calculation of Non-Probabilistic Structure Reliability Index

2014 ◽  
Vol 1048 ◽  
pp. 560-566
Author(s):  
Jia Zhao ◽  
Chang Hua Li ◽  
Jun Lian
Keyword(s):  
Reliability Index ◽  
Present Method ◽  
Minimum Distance ◽  
Limit State ◽  
Normal Space ◽  
Numerical Examples ◽  
Structure Reliability ◽  
Standard Normal ◽  
Probabilistic Structure ◽  
Optimal Calculation

The optimal calculaion of non-probabilistic structure reliability index is researched, where the minimum distance from the origin to the limit-state surface in the standard normal space is required. From the viewpoints of the global nolinear and local linear, it build the global approximate variational inequality. The primal coupled potential function is used to decide direction and step of searching. It is more effective in convergence and polynomials than the other methods in the related references. After a brief review, the method are compared through two numerical examples. It shows that the present method is effective and feasibility.

Most-Probable-Point-Locus Reliability Method in Standard Normal Space

1991 ◽  
Author(s):  
M. R. Khalessi ◽  
Y.-T. Wu ◽  
T. Y. Torng
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Search Algorithm ◽  
Limit State ◽  
Iteration Procedure ◽  
Normal Space ◽  
State Function ◽  
Most Probable Point ◽  
Reliability Method ◽  
Standard Normal

Abstract This paper describes a new structural reliability analysis iteration procedure based on the concept of most probable point locus (MPPL). Using a new quadratic search algorithm, the proposed procedure examines the global behavior of the limit-state function, g, along the MPPL in the standard normal space in search of the most probable point (MPP) on the g = o surface, and identifies unusual conditions such as multiple MPPs. During the iteration procedure, the generated information is updated after each sensitivity analysis. This action helps the analyst to minimize the number of computer runs and determine the next step. By adopting two efficient convergence criteria, the proposed procedure is demonstrated to be significantly more efficient than the commonly used reliability analysis procedures, and is suitable to be integrated with existing general-purpose finite element computer programs for nondeterministic structural analysis.

A Comprehensive Investigation of Ensembles of Gaussian-Based and Gradient-Based Transformed Reliability Analyses: When and How to Use Them

2016 ◽  
Author(s):  
Po Ting Lin ◽  
Wei-Hao Lu ◽  
Shu-Ping Lin
Keyword(s):  
Design Optimization ◽  
Design Space ◽  
Optimization Problems ◽  
Nonlinear Problems ◽  
Kernel Functions ◽  
Sensitivity Analyses ◽  
Normal Space ◽  
Highly Nonlinear ◽  
Standard Normal ◽  
Gradient Based

In the past few years, researchers have begun to investigate the existence of arbitrary uncertainties in the design optimization problems. Most traditional reliability-based design optimization (RBDO) methods transform the design space to the standard normal space for reliability analysis but may not work well when the random variables are arbitrarily distributed. It is because that the transformation to the standard normal space cannot be determined or the distribution type is unknown. The methods of Ensemble of Gaussian-based Reliability Analyses (EoGRA) and Ensemble of Gradient-based Transformed Reliability Analyses (EGTRA) have been developed to estimate the joint probability density function using the ensemble of kernel functions. EoGRA performs a series of Gaussian-based kernel reliability analyses and merged them together to compute the reliability of the design point. EGTRA transforms the design space to the single-variate design space toward the constraint gradient, where the kernel reliability analyses become much less costly. In this paper, a series of comprehensive investigations were performed to study the similarities and differences between EoGRA and EGTRA. The results showed that EGTRA performs accurate and effective reliability analyses for both linear and nonlinear problems. When the constraints are highly nonlinear, EGTRA may have little problem but still can be effective in terms of starting from deterministic optimal points. On the other hands, the sensitivity analyses of EoGRA may be ineffective when the random distribution is completely inside the feasible space or infeasible space. However, EoGRA can find acceptable design points when starting from deterministic optimal points. Moreover, EoGRA is capable of delivering estimated failure probability of each constraint during the optimization processes, which may be convenient for some applications.

Response surface method strategies coupled with NLFEA for structural reliability analysis of prestressed bridges

2021 ◽  
Author(s):  
Silvia J. Sarmiento Nova ◽  
Jaime Gonzalez-Libreros ◽  
Gabriel Sas ◽  
Rafael A. Sanabria Díaz ◽  
Maria C. A. Texeira da Silva ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Structural Reliability ◽  
Limit State ◽  
Material Behavior ◽  
Nonlinear Material ◽  
State Function ◽  
Surface Method ◽  
Highly Nonlinear

<p>The Response Surface Method (RSM) has become an essential tool to solve structural reliability problems due to its accuracy, efficacy, and facility for coupling with Nonlinear Finite Element Analysis (NLFEA). In this paper, some strategies to improve the RSM efficacy without compromising its accuracy are tested. Initially, each strategy is implemented to assess the safety level of a highly nonlinear explicit limit state function. The strategy with the best results is then identified and used to carry out a reliability analysis of a prestressed concrete bridge, considering the nonlinear material behavior through NLFEA simulation. The calculated value of &#120573; is compared with the target value established in Eurocode for ULS. The results showed how RSM can be a practical methodology and how the improvements presented can reduce the computational cost of a traditional RSM giving a good alternative to simulation methods such as Monte Carlo.</p>

Reliability Based Optimization of Steel Monopod Offshore-Towers

2008 ◽  
Author(s):  
H. Karadeniz ◽  
V. Togan ◽  
T. Vrouwenvelder
Keyword(s):  
Natural Frequency ◽  
Cross Section ◽  
Sequential Quadratic Programming ◽  
Limit State ◽  
State Function ◽  
Wave Loading ◽  
Extreme Wave ◽  
Design Variables ◽  
Reliability Based Optimization ◽  
Numerical Strategy

In this work, the implementation of reliability-based optimization (RBO) of a circular steel monopod-offshore-tower with constant and variable diameters (represented by segmentations) and thicknesses is presented. The tower is subjected to the extreme wave loading. For this purpose, the deterministic optimization of the tower is performed with constraints including stress, buckling, and the lowest natural frequency firstly. Then, a reliability-based optimization of the tower is performed. The reliability index is calculated from FORM using a limit state function based on the lowest natural frequency. The mass of the tower is considered as being the objective function; the thickness and diameter of the cross-section of the tower are taken as being design variables of the optimization. The numerical strategy employed for performing the optimization uses the IMSL-Libraries routine that is based on the Sequential Quadratic Programming (SQP). In addition, to check the results obtained from aforementioned procedure, the RBO of the tower is also performed using the genetic algorithms (GA) tool of the MATLAB. Finally, a demonstration of an example monopod tower is presented.

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.

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.

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.

Reliability Analyses of Clay-Embedded Offshore Pipelines Under Vertical Buckling Considering Lower-Bound Pipe-Soil Capacity

2012 ◽  
Author(s):  
Celestino Valle-Molina ◽  
Jorge Alamilla-López ◽  
Shadi S. Najjar ◽  
Francisco Silva-González
Keyword(s):  
Lower Bound ◽  
Reliability Index ◽  
Clayey Soil ◽  
Limit State ◽  
State Function ◽  
Soil System ◽  
Upheaval Buckling ◽  
Vertical Loading ◽  
Reliability Assessments ◽  
The Impact

This paper presents the reliability formulation and analyses for studying and quantifying probabilistically the impact of the main parameters involved in the upheaval buckling of offshore buried pipes due to high pressure high temperature conditions (HPHT) on the reliability of the pipeline. Pipelines are considered installed in a clayey trench and naturally covered. The limit state function is established in terms of the vertical pipe-soil capacity and vertical loading. A lower-bound capacity of the pipe-clayey soil system is included in the reliability analysis in order to represent more realistic conditions with regards to the uncertainty in the capacity. The lower-bound capacity is the smallest possible physical limit of the pipe-soil capacity. Reliability assessments using the main parameters that control the vertical buckling in terms of loading and capacity were performed. Consequently, the variations of the reliability index (β) with the vertical imperfection (δ) and the ratio of the cover height (depth of pipe embedment) to the pipe diameter (H/D) were quantified. The reliability index was evaluated by means of Monte Carlo simulations. The inclusion of the lower-bound capacity by means of a left-censored lognormal distribution was found to increase in some cases the values of β.

Study of Computation for Structural Reliability Index Based on Penalty Function Method

2014 ◽  
Vol 635-637 ◽  
pp. 443-446 ◽  
Author(s):  
Hai Tao Lu ◽  
Yu Ge Dong ◽  
Fang Ying Wu
Keyword(s):  
Unconstrained Optimization ◽  
Penalty Function ◽  
Reliability Index ◽  
Function Method ◽  
Structural Reliability ◽  
Limit State ◽  
State Function ◽  
Penalty Function Method ◽  
Design Point ◽  
Reliability Method

According to the geometric meaning of the structural reliability index, an unconstrained optimization model with structural reliability index and design point is obtained by exterior penalty function method. The Powell method, golden section method and extrapolation method are used to solve the unconstrained optimization problem. The proposed method not has to deal with the any derivative of the limited state function, and can been used to obtain structural reliability index and design point of the strong nonlinear limit state function, which first-order reliability method (FORM) may fail to converge. Three examples are given to compare penalty function method with the difference methods. The results show that the given method is simply, effective and precise enough.

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