scholarly journals Hybrid Approach to the First Order Reliability Method in the Reliability Analysis of a Spatial Structure

2021 ◽  
Vol 11 (2) ◽  
pp. 648
Author(s):  
Agnieszka Dudzik ◽  
Beata Potrzeszcz-Sut
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Limit State ◽  
Hybrid Approach ◽  
Reference Method ◽  
Transformation Method ◽  
State Function ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method

The objective of the article involves presenting two approaches to the structure reliability analysis. The primary research method was the First Order Reliability Method (FORM). The Hasofer–Lind reliability index β in conjunction with transformation method in the FORM was adopted as the measure of reliability. The first proposal was combining NUMPRESS software with the non-commercial KRATA program. In this case, the implicit form of the random variables function was created. Limit state function was symbolically given in the standard math notation as a function of the basic random and external variables. The second analysis proposed a hybrid approach enabling the introduction of explicit forms of limit state functions to the reliability program. To create the descriptions of this formula, the neural networks were used and our own original FEM module. The combination of conventional and neural computing can be seen as a hybrid system. The explicit functions were implemented into NUMPRESS software. The values of the reliability index for different descriptions of the mathematical model of the structure were determined. The proposed hybrid approach allowed us to obtain similar results to the results from the reference method.

First-Order Reliability Method for Structural Reliability Analysis in the Presence of Random and Interval Variables

2015 ◽  
Vol 1 (4) ◽  
Author(s):  
Umberto Alibrandi ◽  
C. G. Koh
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Limit State ◽  
Computational Cost ◽  
Computational Effort ◽  
Stochastic Dynamic ◽  
First Order Reliability Method ◽  
First Order ◽  
Structural Reliability Analysis ◽  
Reliability Method

This paper presents a novel procedure based on first-order reliability method (FORM) for structural reliability analysis in the presence of random parameters and interval uncertain parameters. In the proposed formulation, the hybrid problem is reduced to standard reliability problems, where the limit state functions are defined only in terms of the random variables. Monte Carlo simulation (MCS) for hybrid reliability analysis (HRA) is presented, and it is shown that it requires a tremendous computational effort; FORM for HRA is more efficient but still demanding. The computational cost is significantly reduced through a simplified procedure, which gives good approximations of the design points, by requiring only three classical FORMs and one interval analysis (IA), developed herein through an optimization procedure. FORM for HRA and its simplified formulation achieve a much improved efficiency than MCS by several orders of magnitude, and it can thus be applied to real-world engineering problems. Representative examples of stochastic dynamic analysis and performance-based engineering are presented.

Neural network approach to model the limit state surface for reliability analysis

2003 ◽  
Vol 40 (6) ◽  
pp. 1235-1244 ◽  
Author(s):  
Anthony TC Goh ◽  
Fred H Kulhawy
Keyword(s):  
Neural Network ◽  
Reliability Index ◽  
Structural Reliability ◽  
Limit State ◽  
Random Variables ◽  
First Order Reliability Method ◽  
First Order ◽  
The Neural Network ◽  
Reliability Method ◽  
Geotechnical Structures

Structural reliability methods are often used to evaluate the failure performance of geotechnical structures. A common approach is to use the first-order reliability method. Its popularity results from the mathematical simplicity of the method, since only second moment information (mean and coefficient of variation) on the random variables is required. The probability of failure is then assessed by an index known commonly as the reliability index. One critical aspect in determining the reliability index is the explicit definition of the limit state surface of the system. In a problem involving multi-dimensional random variables, the limit state surface is the boundary separating the safe domain from the "failure" (or lack of serviceability) domain. In many complicated and nonlinear problems where the analyses involve the use of numerical procedures such as the finite element method, this surface may be difficult to determine explicitly in terms of the random variables, and therefore the limit state can only be expressed implicitly rather than in a closed-form solution. It is proposed in this paper to use an artificial intelligence technique known as the back-propagation neural network algorithm to model the limit state surface. First, the failure domain is found through repeated point-by-point numerical analyses with different input values. The neural network is then trained on this set of data. Using the optimal weights of the neural network connections, it is possible to develop a mathematical expression relating the input and output variables that approximates the limit state surface. Some examples are given to illustrate the application and accuracy of the proposed approach.Key words: first-order reliability method, geotechnical structures, limit state surface, neural networks, reliability.

Reliability and Sensitivity Analysis of Laminate Using Different Methods

2014 ◽  
Vol 945-949 ◽  
pp. 1159-1162
Author(s):  
Wei Tao Zhao ◽  
Xiao Li ◽  
Feng Guo
Keyword(s):  
Good Accuracy ◽  
Limit State ◽  
Nonlinear Function ◽  
State Function ◽  
Laminate Structure ◽  
First Order Reliability Method ◽  
First Order ◽  
Fiber Properties ◽  
Surface Method ◽  
Reliability Method

Reliability of laminate structure is deeply influenced by uncertainties such as fiber properties, loads and design sizes. It is very difficult to evaluate the reliability and sensitivity of laminate structure because that laminate structure is anisotropic and the limit state function (LSF) is a high nonlinear function. In this paper, reliability and sensitivity are evaluated by using first order reliability method (FORM), response surface method (RSM) and Monte Carlo simulation (MCS). The study aims to find a numerical method to evaluate the reliability and sensitivity of laminate structures efficiently and accurately. An example of laminate with a large number of variables is analyzed. The results obtained by using different methods are compared in terms of efficiency and accuracy. It is shown that FORM is not accuracy, and RSM has a very good accuracy and efficient in terms of reliability, but the accuracy of sensitivity obtained by using RSM is not good enough.

scholarly journals High Dimension Model Representation-Based Response Surface for Reliability Analysis of Tunnel

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Hongbo Zhao
Keyword(s):  
Reliability Analysis ◽  
Response Surface ◽  
Reliability Index ◽  
Limit State ◽  
State Function ◽  
Limit State Function ◽  
Implicit Function ◽  
Surface Method ◽  
Reliability Method ◽  
Rock Tunnel

Uncertainty is an important prosperity to rock tunnel. Reliability analysis is widely used to deal with the uncertainty. But it is difficult to be adopted in rock tunnel using the traditional reliability method because the limit state function is an implicit function. High dimension model representation (HDMR) can approximate the high dimensional, nonlinear, and implicit function using the low dimensional function. In this study, the HDMR method was adapted to approximate the limit state function through combining with response surface method (RSM). A new reliability analysis approach of HDMR-based response surface method, combined with the first-order reliability method (FORM), is developed to calculate the reliability index of tunnel, and implementation of the method is explained briefly. A circular tunnel with analytical solution and horseshoe tunnel with numerical solution are used to demonstrate the proposed method. The obtained reliability index is in excellent agreement with Low and Tang’s (2007) method and traditional RSM. It shows that HDMR-based response surface can approximate well the limit state function, and the proposed method is an efficient and effective approach for reliability analysis in tunnel engineering. It is very useful for reliability analysis of practical large-scale rock engineering.

scholarly journals Reliability Analysis of Reinforced Concrete Frame by Finite Element Method with Implicit Limit State Functions

Buildings ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 119 ◽  
Author(s):  
Marin Grubišić ◽  
Jelena Ivošević ◽  
Ante Grubišić
Keyword(s):  
Finite Element Method ◽  
Finite Element ◽  
Reinforced Concrete ◽  
Reliability Analysis ◽  
Numerical Models ◽  
Limit State ◽  
First Order Reliability Method ◽  
First Order ◽  
Knowledge Based ◽  
Reliability Method

Since the prediction of the seismic response of structures is highly uncertain, the need for the probabilistic approach is clear, especially for the estimation of critical seismic response parameters. Considering the uncertainties present in the material and geometric form of reinforced concrete (RC) structures, reliability analyses using the Finite Element Method (FEM) were performed in the context of Performance-Based Earthquake Engineering (PBEE). This study presented and compared the possibilities of nonlinear modelling of the reinforced concrete (RC) planar frame and its reliability analysis using different numerical methods, Mean-Value First-Order Second-Moment (MVFOSM), First-Order Reliability Method (FORM), Second-Order Reliability Method (SORM) and Monte Carlo simulation (MCS). The calibrated numerical models used were based on the previous experimental test of a planar RC frame subjected to cyclic horizontal load. Numerical models were upgraded by random variable (RV) parameters for reliability analysis purposes and, using implicit limit state function (LSF), pushover analyses were performed by controlling the horizontal inter-storey drift ratio (IDR). Reliability results were found to be sensitive to the reliability analysis method. The results of reliability analysis reveal that, in a nonlinear region, after exceeding the yield strength of the longitudinal reinforcement, the cross-sectional geometry parameters were of greater importance compared to the parameters of the material characteristics. The results also show that epistemic (knowledge-based) uncertainties significantly affected dispersion and on the median estimate parameter response. The MCS sampling method is recommended, but the First-Order Reliability Method (FORM) applied on a response model can be used with good accuracy. Reliability analysis using the FEM proved to be suitable for the direct implementation of geometric and material nonlinearities to cover epistemic (knowledge-based) uncertainties.

scholarly journals A simplified approach to reliability evaluation of deep rock tunnel deformation using First-Order Reliability Method and Monte Carlo simulations

2022 ◽  
Vol 15 (1) ◽  
Author(s):  
Caio Cesar Cardoso da Silva ◽  
Mauro de Vasconcellos Real ◽  
Samir Maghous
Keyword(s):  
Monte Carlo ◽  
Reliability Analysis ◽  
Numerical Models ◽  
Limit State ◽  
Random Variables ◽  
Support Pressure ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method ◽  
Shotcrete Lining

abstract: The Monte Carlo simulation (MCS) and First-Order Reliability Method (FORM) provide a reliability analysis in axisymmetric deep tunnels driven in elastoplastic rocks. The Convergence-Confinement method (CV-CF) and Mohr-Coulomb (M-C) criterion are used to model the mechanical interaction between the shotcrete lining and ground through deterministic parameters and random variables. Numerical models synchronize tunnel analytical models and reliability methods, whereas the limit state functions control the failure probability in both ground plastic zone and shotcrete lining. The results showed that a low dispersion of random variables affects the plastic zone's reliability analysis in unsupported tunnels. Moreover, the support pressure generates a significant reduction in the plastic zone's failure, whereas the increase of shotcrete thickness results in great reduction of the lining collapse probability.

An improved first order reliability method based on modified Armijo rule and interpolation-based backtracking scheme

2020 ◽  
pp. 1748006X2095989
Author(s):  
Sheng-Tong Zhou ◽  
Di Wang ◽  
Qian Xiao ◽  
Jian-min Zhou ◽  
Hong-Guang Li ◽  
...  
Keyword(s):  
Structural Reliability ◽  
Limit State ◽  
Initial Step ◽  
State Function ◽  
Computationally Efficient ◽  
Step Size ◽  
First Order Reliability Method ◽  
First Order ◽  
Reliability Method ◽  
Initial Step Size

Hasofer-Lind and Rackwtiz-Fiessler (HLRF) method is an efficient iterative algorithm for locating the most probable failure point and calculating the first order reliability index in structural reliability analysis. However, this method may encounter numerical instability problems for high nonlinear limit state function (LSF). In this paper, an improved HLRF-based first order reliability method is developed based on a modified Armijo line search rule and an interpolation-based step size backtracking scheme to improve the robustness and efficiency of the original HLRF method. Compared with other improved HLRF-based methods, the proposed method can not only guarantee the global convergence but also adaptively estimate some sensitive algorithm parameters, such as initial step size, step-size reduction coefficient, using the current known iterative information. Ten selected examples with high nonlinear LSFs are used to compare the robustness and efficiency of the proposed method with the original HLRF method and the improved HLRF (iHLRF) method. Results indicate that the proposed method is not only more computationally efficient but also less sensitive to the remaining user-defined algorithm parameters than the iHLRF method.

scholarly journals Reliability analysis of a prestressed bridge beam designed in serviceability limit state as recommended by NBR 6118 and 7188

2020 ◽  
Vol 13 (2) ◽  
pp. 380-397
Author(s):  
P. H. C. DE LYRA ◽  
A. T. BECK ◽  
F. R. STUCCHI
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Limit State ◽  
Economic Losses ◽  
Allowable Stress ◽  
State Equations ◽  
First Order ◽  
Serviceability Limit State ◽  
Reliability Method ◽  
Brazilian Standard

Abstract Nowadays it is known that it is important to study the safety of structures to avoid tragic accidents or economic losses. The most widely used method in the world to evaluate the safety of structures is structural reliability. The reliability index of prestressed precast beams of bridges designed using Brazilian standards (NBR6118 and NBR7188) is not known. This work evaluates the annual reliability indexes of a prestressed precast beam bridge at the serviceability limit state (SLS) projected using the Brazilian standard and compares it with results from the literature. The studied bridge has 33.5 meters of span, is simply supported, constituted by five precast concrete beams with U section. The reliability analysis was carried out using two methods for the four limit state equations: First Order Mean Value (FOMV) and First Order Reliability Method (FORM). Sensitivity analyzes were performed to consider both the relative contribution of these variables and the effect of their distributions on the annual reliability indexes for SLS. It was verified that the effect of load trains and the allowable stress significantly reduce the reliability index obtained for Brazilian standard. The service limit state equations are particularly sensitive to load trains, allowable stress and prestress losses, as well as their respective distributions.

Some Important Issues on First-Order Reliability Analysis With Nonprobabilistic Convex Models

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
C. Jiang ◽  
G. Y. Lu ◽  
X. Han ◽  
R. G. Bi
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Probability Model ◽  
Mean Value ◽  
Convex Model ◽  
First Order ◽  
Reliability Method ◽  
Complex Engineering ◽  
Mean Value Method ◽  
Form Type

Compared with the probability model, the convex model approach only requires the bound information on the uncertainty, and can make it possible to conduct the reliability analysis for many complex engineering problems with limited samples. Presently, by introducing the well-established techniques in probability-based reliability analysis, some methods have been successfully developed for convex model reliability. This paper aims to reveal some different phenomena and furthermore some severe paradoxes when extending the widely used first-order reliability method (FORM) into the convex model problems, and whereby provide some useful suggestions and guidelines for convex-model-based reliability analysis. Two FORM-type approximations, namely, the mean-value method and the design-point method, are formulated to efficiently compute the nonprobabilistic reliability index. A comparison is then conducted between these two methods, and some important phenomena different from the traditional FORMs are summarized. The nonprobabilistic reliability index is also extended to treat the system reliability, and some unexpected paradoxes are found through two numerical examples.

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