Reliability Analysis for Structures With Multiple Temporal and Spatial Parameters Based on the Effective First-Crossing Point

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Yan Shi ◽  
Zhenzhou Lu ◽  
Kaichao Zhang ◽  
Yuhao Wei
Keyword(s):  
Failure Probability ◽  
Limit State ◽  
Function Technique ◽  
State Function ◽  
Fourth Moment ◽  
Dynamic Failure ◽  
Dynamic Reliability ◽  
Spatial Parameters ◽  
Temporal And Spatial ◽  
Crossing Point

For efficiently estimating the dynamic failure probability of the structure with the multiple temporal and spatial parameters, a transferred limit state function technique is first proposed in this paper. By finding the effective first-crossing point which controls the failure of the structural system, the transferred technique is constructed to transform the dynamic reliability problem into a static one. For determining the effective first-crossing point, the parameter domain is first divided into different dominant domain corresponding to every parameter. Based on the parameter dominant domain, the first-crossing point about each parameter is obtained by comparing the difference value between the point on the failure boundary and the corresponding parameter upper bound. Finally, the effective first-crossing point is determined by finding the point which controls the structure failure. With the transferred technique, two strategies (including the sparse grid integration based on fourth-moment method and the maximum entropy based on dimensional reduction method) are proposed to efficiently estimate the dynamic failure probability. Several examples are employed to illustrate the significance and effectiveness of the transferred technique and the proposed methods for solving the multiple temporal and spatial parameters dynamic reliability. The results show that the proposed methods can estimate the multiple temporal and spatial parameters dynamic failure probability efficiently and accurately.

Dynamic reliability analysis for structure with temporal and spatial multi-parameter

2019 ◽  
Vol 233 (6) ◽  
pp. 1002-1013
Author(s):  
Yan Shi ◽  
Zhenzhou Lu
Keyword(s):  
Random Field ◽  
Failure Probability ◽  
Gaussian Random Field ◽  
Simulation Method ◽  
Dynamic Failure ◽  
Performance Function ◽  
Dynamic Reliability ◽  
Field Transformation ◽  
Real Performance ◽  
Temporal And Spatial

For efficiently estimating the dynamic failure probability of the structure with random variables, stochastic processes and temporal and spatial multi-parameter, an estimation strategy is presented based on the random field transformation. The random field transformation focusing on the dynamic reliability with only one time parameter is further investigated, and it is extended to temporal and spatial multi-parameter issue, which simulates the output as multi-dimensional Gaussian random field. Also, the active learning Kriging method is used to construct the surrogate models for the mean function and auto-covariance function of performance function. After that, the temporal and spatial dynamic failure probability can be obtained by the simulation method. Although it doesn’t need to call the real performance function during the process of simulation method, it is time computationally expensive. To address this issue, the optimization algorithm procedure is established to estimate the dynamic failure probability. Several examples including an aero engine turbine disk and a cylindrical pressure vessel are introduced to illustrate the significance and effectiveness of the proposed methods for analyzing the temporal and spatial multi-parameter dynamic failure probability.

Reliability and reliability-based sensitivity analysis of self-centering buckling restrained braces using meta-models

2021 ◽  
pp. 1045389X2110263
Author(s):  
Seyede Vahide Hashemi ◽  
Mahmoud Miri ◽  
Mohsen Rashki ◽  
Sadegh Etedali
Keyword(s):  
Failure Probability ◽  
Limit State ◽  
Computational Cost ◽  
Sensitivity Analyses ◽  
State Function ◽  
Reliability Indices ◽  
Buckling Restrained Brace ◽  
Polynomial Response Surface ◽  
Nonlinear Dynamic Analyses ◽  
High Computational Cost

This paper aims to carry out sensitivity analyses to study how the effect of each design variable on the performance of self-centering buckling restrained brace (SC-BRB) and the corresponding buckling restrained brace (BRB) without shape memory alloy (SMA) rods. Furthermore, the reliability analyses of BRB and SC-BRB are performed in this study. Considering the high computational cost of the simulation methods, three Meta-models including the Kriging, radial basis function (RBF), and polynomial response surface (PRSM) are utilized to construct the surrogate models. For this aim, the nonlinear dynamic analyses are conducted on both BRB and SC-BRB by using OpenSees software. The results showed that the SMA area, SMA length ratio, and BRB core area have the most effect on the failure probability of SC-BRB. It is concluded that Kriging-based Monte Carlo Simulation (MCS) gives the best performance to estimate the limit state function (LSF) of BRB and SC-BRB in the reliability analysis procedures. Considering the effects of changing the maximum cyclic loading on the failure probability computation and comparison of the failure probability for different LSFs, it is also found that the reliability indices of SC-BRB were always higher than the corresponding reliability indices determined for BRB which confirms the performance superiority of SC-BRB than BRB.

scholarly journals Gaussian Process-Based Response Surface Method for Slope Reliability Analysis

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Bin Hu ◽  
Guo-shao Su ◽  
Jianqing Jiang ◽  
Yilong Xiao
Keyword(s):  
Gaussian Process ◽  
Reliability Analysis ◽  
Response Surface ◽  
Response Surface Method ◽  
Failure Probability ◽  
Limit State ◽  
State Function ◽  
Limit State Function ◽  
Surface Method ◽  
Gp Model

A new response surface method (RSM) for slope reliability analysis was proposed based on Gaussian process (GP) machine learning technology. The method involves the approximation of limit state function by the trained GP model and estimation of failure probability using the first-order reliability method (FORM). A small amount of training samples were firstly built by the limited equilibrium method for training the GP model. Then, the implicit limit state function of slope was approximated by the trained GP model. Thus, the implicit limit state function and its derivatives for slope stability analysis were approximated by the GP model with the explicit formulation. Furthermore, an iterative algorithm was presented to improve the precision of approximation of the limit state function at the region near the design point which contributes significantly to the failure probability. Results of four case studies including one nonslope and three slope problems indicate that the proposed method is more efficient to achieve reasonable accuracy for slope reliability analysis than the traditional RSM.

Improved Line Sampling Reliability Analysis Method and its Application

2007 ◽  
Vol 353-358 ◽  
pp. 1001-1004 ◽  
Author(s):  
Shu Fang Song ◽  
Zhen Zhou Lu
Keyword(s):  
Markov Chain ◽  
Reliability Analysis ◽  
Failure Probability ◽  
Low Cycle Fatigue ◽  
Limit State ◽  
Computational Cost ◽  
State Function ◽  
Line Sampling ◽  
Failure Region ◽  
Important Direction

For reliability analysis of implicit limit state function, an improved line sampling method is presented on the basis of sample simulation in failure region. In the presented method, Markov Chain is employed to simulate the samples located at failure region, and the important direction of line sampling is obtained from these simulated samples. Simultaneously, the simulated samples can be used as the samples for line sampling to evaluate the failure probability. Since the Markov Chain samples are recycled for both determination of the important direction and calculation of the failure probability, the computational cost of the line sampling is reduced greatly. The practical application in reliability analysis for low cycle fatigue life of an aeronautical engine turbine disc structure under 0-takeoff-0 cycle load shows that the presented method is rational and feasible.

Plastic hinges mechano-reliability analysis in the beams of RC frames structures

2020 ◽  
Vol 17 (5) ◽  
pp. 719-732
Author(s):  
Leyla Bouzid ◽  
Mohand Hamizi ◽  
Naceur-Eddine Hannachi ◽  
Aghiles Nekmouche ◽  
Karim Akkouche
Keyword(s):  
Compressive Strength ◽  
Yield Stress ◽  
Failure Probability ◽  
Limit State ◽  
State Function ◽  
Concrete Compressive Strength ◽  
Plastic Hinges ◽  
Content Type ◽  
Steel Bars ◽  
The Impact

Purpose The purpose of this study is to establish a relationship between causes and effects, the respect of materials characteristics values [concrete compressive strength (fc) and steel yield stress (fy)] and the norms of the construction dispositions value (covers). This study is motivated by the post-seismic damages related to the plastification of the reinforced concrete (RC)/beams sections, named plastic hinges. The results are given by fragility curves representing the failure probability (Pf) of the plastic hinges versus covers value. Design/methodology/approach A mechanical-reliability coupling methodology is proposed and performed on three frames (three, six and nine storey). For each frame, seven covers the value of reinforcement steel bars has been taken into account in the beams. After definition of the limit state function G(x), a process of idea to twin-track; deterministic and probabilistic, is considered. Thus, numerical simulations are carried out under ETABS© software, to extract a soliciting moments Ms(x). Then, ultimate moments Mu(x), the result of reliability approach are calculated using Monte Carlo Simulations. In this step, two random variables; concrete compressive strength in 28 days of age (fc) and steel yield stress (fy), have been studied. Findings In the mechanical study, the results show that, the first plastic hinge appears at the beams for all frames. In the reliability study, the (fy) variation shows that all plastic hinges are in failure domain, nevertheless, the (fc) variation leads to have all sections in the safety domain, except A7 and B7 models. The failure probability (Pf) calculation according to (fc) and (fy) shows that an absolute error of 0.5 cm in the steel bars covers can switch the frame from the safety domain to the failure domain. Originality/value The plastic hinges reliability of the RC/ frame structures is independent on the high of the structure. The (fc) random variable according to the used distribution law does not affect the reliability (safety or failure). However, the impact of the steel yield stress variation (fy) is not negligible. The errors in covers affect considerably the strength of the elements.

Reliability evaluation of reinforced concrete columns designed by Eurocode for wind-dominated combination considering random loads eccentricity

2019 ◽  
Vol 23 (1) ◽  
pp. 146-159 ◽  
Author(s):  
Youbao Jiang ◽  
Suixiang Peng ◽  
Michael Beer ◽  
Lei Wang ◽  
Jianren Zhang
Keyword(s):  
Reinforced Concrete ◽  
Failure Probability ◽  
Limit State ◽  
Concrete Columns ◽  
State Function ◽  
Reinforced Concrete Columns ◽  
Compression Failure ◽  
Random Loads ◽  
Standard Design ◽  
Total Failure

With the capacity models in the 2004 edition of the European Committee for Standardization’s Standard Design of Concrete Structures, a more realistic limit state function is obtained for reinforced concrete columns with random loads eccentricity. Using this function, the applicability of the code-based design factors is discussed. Taking the wind-dominated combination as an example, the probabilistic distribution of loads eccentricity and the statistics of column resistance are analyzed for representative cases. The analysis indicates that the possible loads eccentricity is scattered over a large range, and the probabilistic model of column resistance varies from case to case, which is largely different from the resistance model assumed in previous reliability calibration. With Monte Carlo simulation, the column reliability and the contributions of both tension failure and compression failure to the total failure probability are calculated and obtained for different cases. The results show that the fixed loads eccentricity criterion underestimates differences in the reliability of columns for different loads eccentricity cases and overestimates the column reliability in some tension failure cases. Furthermore, it is found that the tension failure mode contributes most to the total failure probability for not only some columns designed to fail in tension failure but also for some columns designed to fail in compression failure. To attain a robust design, a group of optimum wind load factors varying with cases is recommended. The new calibration results prove that the recommended wind local factors can achieve a better goal.

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.

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.

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.

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