Multiple Failure Modes of Compressor Station Incorporated into Risk Evaluation of Electricity-gas Integrated Energy Systems

Multiple failure modes of gas compressor stations have not been modeled into risk evaluation of electricity-gas integrated energy system(EGIES).This paper presents a method to incorporate multiple failure modes of compressor stations with bypass systems in the EGIES risk evaluation.Three outage models representing multi-states and multi-failure-modes of com-pressor stations and a bi-level Monte Carlo sampling algorithm for the models are developed.A novel network model of EGIES considering compressor stations with multiple failure modes is presented.An EGIES with a modified RBTS and an 11-node gas system is used to demonstrate the effectiveness of the proposed method and models.Results indicate that compressor stations have both positive and negative significant impacts on the risk of EGIES.Bypass systems for compressor stations can effectively offset the negative impacts.Ignoring compressor stations and their station failures in the risk evaluation of EGIES may result in an inaccurate estimation of the system risk levels and even lead to a misleading conclusion in system planning.Index Terms-Compressor station,electricity-gas integrated energy system,multiple failure modes,risk evaluation.

Reliability-based robust geotechnical design of braced excavations considering multiple failure modes

Reliability design of braced excavation is still a challenge for geotechnical community.Optimization design is a normal method to control the safety and cost of braced excavations.This study presents an advanced reliability-based robust geotechnical design method,which can consider multiple failures and uncertainty of statistical information.A universal design sample was conducted to verify the necessity of considering the uncertainty of statistical information.Ultimate limit state and serviceability limit state of braced excavations were defined,and point estimating method was used to evaluate the standard deviation of failure probabilities.Two-objective and three-objective optimization models were developed to illustrate the application of proposed methods in detail.In addition,the performance of optimization algorithms and further application of multiple-objective models were discussed.The results from this study indicate that the proposed method has a good performance in determining the optimal design with reasonable robustness and cost.New algorithms have higher efficiency in solving nonlinear and multiple-objective optimization problems than the 2nd Non-dominated sorting genetic algo-rithm.This study can guide the design of retaining systems of braced excavations in clay.

Reliability Sensitivity Algorithm Based on Stratified Importance Sampling Method for Multiple Failure Modes Systems

Combining the advantages of the stratified sampling and the importance sampling, a stratified importance sampling method （SISM） is presented to analyze the reliability sensitivity for structure with multiple failure modes. In the presented method, the variable space is divided into several disjoint subspace by n-dimensional coordinate planes at the mean point of the random vec- tor, and the importance sampling functions in the subspaces are constructed by keeping the sampling center at the mean point and augmenting the standard deviation by a factor of 2. The sample size generated from the importance sampling function in each subspace is determined by the contribution of the subspace to the reliability sensitivity, which can be estimated by iterative simulation in the sampling process. The formulae of the reliability sensitivity estimation, the variance and the coefficient of variation are derived for the presented SISM. Comparing with the Monte Carlo method, the stratified sampling method and the importance sampling method, the presented SISM has wider applicability and higher calculation efficiency, which is demonstrated by numerical examples. Finally, the reliability sensitivity analysis of flap structure is illustrated that the SISM can be applied to engineering structure.

System Reliability Analysis for Truss Structures Based on Automatic Updated Model

Multiple failure modes tend to be identified in the reliability analysis of a redundant truss structure.This identification process involves updating the model for identifying the next potential failure members.Herein we intend to update the finite element model automatically in the identification process of failure modes and further perform the system reliability analysis efficiently.This study presents a framework that is implemented through the joint simulation of MATLAB and APDL and consists of three parts:reliability index of a single member,identification of dominant failure modes,and system-level reliability analysis for system reliability analysis of truss structures.Firstly,RSM(response surface method)combines with a constrained optimization model to calculate the reliability indices ofmembers.Then theβ-unzipping method is adopted to identify the dominant failuremodes,and the system function in MATLAB,as well as the EKILL command in APDL,is used to facilitate the automatic update of the finite element model and realize load-redistribution.Besides,the differential equivalence recursion algorithmis performed to approximate the reliability indices of failuremodes efficiently and accurately.Eventually,the PNET(probabilistic network evaluation technique)is used to calculate the joint failure probability as well as the system reliability index.Two illustrative examples demonstrate the accuracy and efficiency of the proposed system reliability analysis framework through comparison with corresponding references.

Fuzzy Reliability and Availability of System under a Calendar-based Inspection Involving Multiple Failures and Its Application to Wind Turbine System

Uncertainty is an important factor that needs to be considered while analyzing the performance of any engineering system.In order to quantify uncertainty,fuzzy set theory is frequently used by most of researchers,including energy system experts.According to the classical reliability theory,component lifetimes have crisp parameters,but due to uncertainty and inaccuracy in data,it is sometimes very difficult to determine the exact values of these parameters in real-world systems.To overcome this difficulty in the current research,failure and repair rates were taken as triangular fuzzy numbers to determine the fuzzy availability of a system undergoing calendar-based periodic inspection subject to multiple failure modes(FMs).It was assumed that each component in the system had an exponential failure rate and repair rate with fuzzy parameters.System FMs were explicitly taken into account when a functional state of the system was considered.Each FM had a random failure time.On the occurrence of any failure,a random time was selected for the relevant corrective repair work.The proposed research was studied for one of the major sources of green energy,namely a wind turbine system wherein all the derived propositions have been implemented on it.

Modelling Upgrading Maintenance Policy in the One-Dimensional Renewing Warranty Period

In the one-dimensional renewing warranty period,the quality of the spares for product is likely to be improved during the warranty period.Therefore,upgrading maintenance becomes more and more common.Then the manufacturers(customers) may have to decide whether or not to provide(buy) the warranty considering upgrading maintenance.This paper presents a mathematical model considering upgrading maintenance for products with multiple failure modes.Upgrading maintenance is taken into account with the assumption that the warranted item is upgraded one time during the warranty cycle.The upgrading maintenance is carried out,when the corrective maintenance is taken place.After upgrading maintenance,the high-quality spares are used to replace the failed item.In the numerical example,the results of the models are calculated.Monte Carlo simulation results are compared with the analytical results to demonstrate the correctness and efficiency of the proposed models considering upgrading maintenance.

用于具有多失效模式和带相关不确定性结构可靠性分析的基于有限数据的非概率凸多面体模型

本文提出了一种新的非概率可靠性模型,关注不确定性条件下结构可靠性评估,称为凸多面体可靠性模型.与现有的概率和非概率区间模型不同,凸多面体模型考虑用多维凸多面体描述不确定变量空间.与区间模型相比,凸多面体模型更紧凑,反映了基于有限信息的不确定变量之间的相关性.在所提出的准则中,面积/体积比被视作可靠性指标.然后,利用基于最可能失效点的线性化方法和分段线性化方法对非线性极限状态函数的情况进行了讨论和处理.在此基础上,研究了基于非概率凸多面体可靠性模型的多失效模式结构系统可靠性分析的有效方法.最后,通过三个实例验证了该方法的有效性和适用性.通过与现有可靠性模型的比较,结果表明,概率可靠性模型和非概率可靠性模型评估的可靠性是相容的.