scholarly journals Kriging Model for Reliability Analysis of the Offshore Steel Trestle Subjected to Wave and Current Loads

2021 ◽  
Vol 10 (1) ◽  
pp. 25
Author(s):  
Pengfei Liu ◽  
Daimeng Shang ◽  
Qiang Liu ◽  
Zhihong Yi ◽  
Kai Wei
Keyword(s):  
Reliability Analysis ◽  
Failure Probability ◽  
Reliability Index ◽  
Prediction Accuracy ◽  
Limit State ◽  
Kriging Model ◽  
Structural Safety ◽  
Unbiased Estimation ◽  
Sample Number ◽  
Current Loading

Offshore steel trestles (OSTs) are exposed to severe marine environments with stochastic wave and current loads, making structural safety assessment challenging and difficult. Reliability analysis is a suitable way to consider both wave and current loading intensity uncertainties, but the implicit and complex limit state functions of the reliability analysis usually imply huge computational costs. This paper proposes an efficient reliability analysis framework for OST using the kriging model of optimal linear unbiased estimation. The surrogate model is built with stochastic waves, current parameters, and the corresponding load factors. The framework is then used to evaluate the reliability of an example OST subjected to wave and current loads at three limit states of OST, including first yield (FY), full plastic (FP), and collapse initiation (CI). Three different distributions are used for comparison of the results of failure probability and reliability index. The results and the computational cost by the proposed framework are compared with that from the Monte Carlo sampling (MCS) and Latin hypercube sampling (LHS) method. The influences of sample number on the prediction accuracy and reliability index are investigated. The influence of marine growth on the reliability analysis of the OST is discussed using MCS and the kriging model. The results show that the reliability analysis based on the kriging model can obtain the reliability index for the OST efficiently with less calculation time but similar results compared with MCS and LHS. With the increase of the number of samples, the prediction accuracy of the kriging model increases, and the corresponding failure probability fluctuates greatly at first and then tends to be stable. The reliability of the example OST is reduced with the increase of marine growth, regardless of the limit state.

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.

scholarly journals Reliability Analysis of St. Barbara’s Church in Otovice

2020 ◽  
Vol 868 ◽  
pp. 166-172
Author(s):  
Chandrashekhar Mahato ◽  
Pavel Kuklík
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Probabilistic Approach ◽  
Probability Of Failure ◽  
Structural Safety ◽  
Site Condition ◽  
Baroque Architecture ◽  
Material Parameters ◽  
Safety And Stability ◽  
Present Site

The Churches of the Broumov region are well known for their unique baroque architecture, distinct shapes, sizes, and constitutes an integral part of the Czech cultural heritage. The St. Barbara’s Church that has been studied in this article, is in the Otovice village of Broumov. It was built in the year 1726 by Bavarian architects Christoph Dientzenhofer and Kilian Ignaz and is significant because of its religious, artistic and historic values. The main objective of this study is to evaluate the structural safety and stability of St. Barbara’s Church based on a probabilistic approach. A deterministic assessment of the structure is carried out and the results are assessed concerning the present site condition. Depending upon the observed damages, a condition for failure is defined for the structure. The uncertainties in the material parameters are considered and reliability analysis is performed to determine the reliability index, probability of failure and influence of different material parameters in the structural stability.

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.

scholarly journals Reliability Analysis of Anchored Geotechnical Structures for the Design Limit States

2020 ◽  
Vol 8 (2) ◽  
pp. 35-47
Author(s):  
Sohaib K Al-Mamoori ◽  
Laheab A. Al-Maliki ◽  
Khaled El-Tawel
Keyword(s):  
Reliability Analysis ◽  
Reliability Index ◽  
Failure Modes ◽  
Limit State ◽  
Tensile Failure ◽  
Limit States ◽  
Geotechnical Parameters ◽  
Retaining Structure ◽  
Geotechnical Structures ◽  
Bending Failure

Reliability has been considered of magnificent importance in engineering design specially in geotechnical engineering due to the unpredictable conditions of soil layers. It is essential to establish well- designed failure modes that could guarantee safety and durability of the proposed structure. This study aims to suggest a reliability analyses procedure for retaining walls by the mean of a reliability index β using the specifications of AASHTO Bridge Design 2002, Eurocode 7, and DIN EN 1993-5 norms. Two failure modes; Tensile failure of tendon (G1) and Failure by bending (G2) were studied and compared by using equation of the Design Limit State (DLS) and by taking some basic geotechnical parameters as Random Variables RV. The analyses demonstrated that the reliability index β and probability of failure Pf are the most important parameter in the reliability analysis. Also, the suitable height (H) for the retaining structure (for all angles ϴ) equals to 6 m and the most critical angle is ϴ= 45º to prevent the failure by tensile of tendon. While the bending failure reliability analysis shows that all heights of retaining structure are suitable. After comparing the two cases it was found that (G1) is more dangerous than (G2).

RCA-PCK: A new structural reliability analysis method based on PC-Kriging and radial centralized adaptive sampling strategy

2020 ◽  
pp. 095440622095771
Author(s):  
Zhenliang Yu ◽  
Zhili Sun ◽  
Runan Cao ◽  
Jian Wang ◽  
Yutao Yan
Keyword(s):  
Reliability Analysis ◽  
Failure Probability ◽  
Adaptive Sampling ◽  
Structural Reliability ◽  
Sampling Strategy ◽  
Kriging Model ◽  
Strong Nonlinearity ◽  
Analysis Method ◽  
Structural Reliability Analysis ◽  
Training Samples

To improve the efficiency and accuracy of reliability assessment for structures with small failure probability and time-consuming simulation, a new structural reliability analysis method (RCA-PCK) is proposed, which combines PC-Kriging model and radial centralized adaptive sampling strategy. Firstly, the PC-Kriging model is constructed by improving the basis function of Kriging model with sparse polynomials. Then, the sampling region which contributes a great impact on the failure probability is constructed by combining the radial concentration and important sampling technology. Subsequently, the k-means++ clustering technology and learning function LIF are adopted to select new training samples from each subdomains in each iteration. To avoid the sampling distance in one subdomain or the distance between the new training samples in two subdomains being too small, we construct a screening mechanism to ensure that the selected new training samples are evenly distributed in the limit state. In addition, a new convergence criterion is derived based on the relative error estimation of failure probability. Four benchmark examples are given to illustrate the convergence process, accuracy and stability of the proposed method. Finally, the transmission error reliability analysis of thermal-elastic coupled gears is carried out to prove the applicability of the proposed method RCA-PCK to the structures with strong nonlinearity and time-consuming simulation.

STRUCTURAL RELIABILITY ANALYSIS OF STEEL TRUSS ELEMENTS ON BUCKLING USING PBOX APPROACH

2021 ◽  
pp. 45-53
Author(s):  
A.A. Solovyova ◽  
◽  
S.A. Solovyov ◽  
Keyword(s):  
Reliability Analysis ◽  
Structural Reliability ◽  
Statistical Data ◽  
Limit State ◽  
Random Variables ◽  
Distribution Functions ◽  
Structural Safety ◽  
Random Load ◽  
Load Models ◽  
Steel Trusses

Abstract. The reliability of load-bearing structural elements is one of the indicators of structural safety. The article presents methods for steel trusses bars reliability analysis according to the buckling criterion using p-boxes. A p-box consists of two boundary probability distribution functions that form the area of possible distribution functions. Such model used for modeling random variables in conditions of incomplete statistical data by quantity or quality. An algorithm for summing p-boxes of random load models is demonstrated on the example of a probabilistic estimate of the force in the truss bar. The result of reliability analysis using p-boxes is presented in interval form. The use of p-boxes makes it possible to obtain a more cautious assessment of reliability in case of incomplete statistical data. To increase the informativity of the reliability analysis result, it is necessary to obtain more statistical data about random variables in design mathematical models of limit state, which will allow forming p-boxes with narrower boundary distribution functions.

Line Sampling Reliability Analysis for Low Cycle Fatigue Life of Aeronautical Engine Disc Structure

2006 ◽  
Vol 324-325 ◽  
pp. 875-878
Author(s):  
Shu Fang Song ◽  
Zhen Zhou Lu
Keyword(s):  
Markov Chain ◽  
Fatigue Life ◽  
Reliability Analysis ◽  
Failure Probability ◽  
High Efficiency ◽  
Low Cycle Fatigue ◽  
Limit State ◽  
Cycle Fatigue ◽  
Line Sampling ◽  
Important Direction

In engineering reliability analysis, the limit state equation is generally implicit and nonlinear, and large number basic random variables and small failure probability are associated. For this kind of reliability analysis, a novel numerical simulation is presented based on the combination of Markov Chain Simulation and line sampling. In the presented method, Markov Chain Simulation is used to draw samples in the failure domain rapidly, and important direction for the line sampling is determined by these samples. Then the line sampling technique is employed to take samples according to the important direction, and failure probability can be evaluated by line sampling with high efficiency. Comparing to the finite differential method for obtaining the important direction, higher accuracy and higher robustness of the important direction are obtained by the presented method. The application in the reliability analysis of low cycle fatigue life of aeronautical engine turbine disc structure, which is applied by multiple cyclic loads, shows that the presented line sampling combining with the Markov Chain Simulation is efficient and feasible.

Reliability Analysis of Mooring Lines of Floating Structures Under Corrosion and Material Degradation

2020 ◽  
Author(s):  
Ricardo Soares Gomes Junior ◽  
Paulo Mauricio Videiro ◽  
Paulo de Tarso Themistocles Esperança ◽  
Luis Volnei Sudati Sagrilo
Keyword(s):  
Reliability Analysis ◽  
Failure Probability ◽  
Limit State ◽  
Gas Production ◽  
Ultimate Limit State ◽  
Offshore Structure ◽  
Material Degradation ◽  
Mooring Lines ◽  
Piecewise Constant Model ◽  
Over Time

Abstract This paper presents a procedure for reliability analysis of mooring lines of floating units for oil and gas production considering corrosion and material degradation over time. The proposed procedure is limited to the ultimate limit state (ULS) and considers mooring lines made up of chain and polyester rope segments, although the same methodology can be applied to cases with steel wire segments. The proposed procedure can also be applied for mooring lines connected to any other type of floating offshore structure. For reliability assessments, it is necessary to consider the distributions and the probabilistic aspects of the random variables involved in the process. The weakest link system is used to model the strength of a mooring line segment. Simplified time-dependent probabilistic models for chain corrosion and polyester degradation are adopted to predict the strength degradation over time. The annual failure probability for different years is estimated by approximating the degraded strength by a piecewise constant model in order to perform a time variant reliability analysis. Monte Carlo simulations are used to determine the failure probability. A study case is also presented, where annual extreme top tension is obtained from long-term statistics considering Brazilian offshore environmental conditions acting on a turret moored floating, production, storage and offloading unit (FPSO).

Dynamic Reliability Analysis on Arch Dam by Considering Random Elastic Modulus

2012 ◽  
Vol 226-228 ◽  
pp. 931-936
Author(s):  
Hong Jie Chen ◽  
Qing Xi Wu ◽  
Hong Feng Zhen
Keyword(s):  
Elastic Modulus ◽  
Reliability Analysis ◽  
Reliability Index ◽  
Response Spectrum ◽  
Limit State ◽  
Complex Structure ◽  
Optimization Method ◽  
Arch Dam ◽  
Rock Foundation ◽  
Dynamic Reliability

Due to the massive volume of body and complex structure, the dynamic reliability analysis on arch dam under earthquake action draws more attention. In this paper calculated seismic dynamic action on arch dam by applying mode superposition response spectrum method. By taking the elastic modulus of the dam concrete and the rock foundation beneath the dam, and concrete tensile and compressive strength as random variables, adapting response surface method to establish limit state equation. The reliability index of each element in the dam was calculated via gradient optimization method, as a result to obtain the variation law of reliability index of dam body. The calculation of real case shows that the tensile index is comparatively low at some region of dam heel and abutment upstream, which requires the measure for aseismic measures, while the reliability index for tensile and compressive stress on other part of dam generally meets requirement.

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