Probabilistic Engineering Mechanics最新文献_第7页

A novel self-adaptive step size first-order method for structural reliability analysis based on modified Sigmoid function and Armijo rule 基于修正Sigmoid函数和Armijo规则的一阶结构可靠度分析方法

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2024.103721

Yu Xia, Yiying Hu, Yingye Yu

{"title":"A novel self-adaptive step size first-order method for structural reliability analysis based on modified Sigmoid function and Armijo rule","authors":"Yu Xia, Yiying Hu, Yingye Yu","doi":"10.1016/j.probengmech.2024.103721","DOIUrl":"10.1016/j.probengmech.2024.103721","url":null,"abstract":"<div><div>Among the first-order reliability methods (FORM), the Hasofer-Lind and Rackwitz-Fiessler method (HL-RF), and the chaos control method (CC) rely on a fixed step size and cannot generate an adaptive one, making it difficult to achieve a satisfactory trade-off between efficiency and robustness when dealing with highly nonlinear problems. To address these drawbacks, this paper proposes two innovative first-order reliability methods: the Sigmoid-based self-adaptive step size adjustment method (SSA) and the hybrid Sigmoid-based self-adaptive step size adjustment method (HSSA). The iterative rotation angle is first determined for both proposed methods. In the SSA method, a modified Sigmoid function is employed to enable nonlinear adaptive adjustments of the step size based on changes in the iterative turning angles, allowing for rapid convergence. Subsequently, the HSSA method incorporates the Armijo rule to further explore a more effective solution. Both proposed methods demonstrate strong computational merits, favorable performance, and user-friendly procedures, providing self-adaptive step sizes suitable for engineering problems, thus offering a broad range of applications. The paper introduces eight examples to showcase the remarkable performance of the two proposed methods. The results indicate that both methods exhibit significantly superior efficiency and robustness compared to other comparative analytical FORM methods when addressing highly nonlinear engineering challenges. Finally, a discussion is presented.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103721"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The influence of slope geometric parameters on the reliability of slope reinforced by micro-piles in spatially variable soils 空间变土中边坡几何参数对微桩加固边坡可靠度的影响

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2024.103719

Yuke Wang , Haiwei Shang , Yukuai Wan , Yuyuan Chen

{"title":"The influence of slope geometric parameters on the reliability of slope reinforced by micro-piles in spatially variable soils","authors":"Yuke Wang , Haiwei Shang , Yukuai Wan , Yuyuan Chen","doi":"10.1016/j.probengmech.2024.103719","DOIUrl":"10.1016/j.probengmech.2024.103719","url":null,"abstract":"<div><div>Currently, the combined effects of soil spatial variability and slope geometric parameters on the reliability of micro-pile reinforced slopes remain unclear. To evaluate the influence of slope geometric parameters on the reliability of micro-pile reinforced slope, a reliability calculation program considering the spatial variability of soil strength parameters was proposed in this study. By combining the effective micro-pile side pressure formula with the simplified Bishop method, the limit equilibrium calculation method for micro-pile reinforced slope was obtained. The Karhunen–Loève (K-L) expansion method was employed to generate random fields. The failure probability and reliability index of the slope were calculated by Monte Carlo Simulation (MCS). The effects of different reinforcement parameters and random parameters on the mean safety factor and reliability of micro-pile reinforced slope were studied, and the influence of slope geometric parameters on the reliability of micro-pile reinforced slope was analyzed. The results indicate that the stability of the slope is effectively improved by micro-pile reinforcement. After reinforcement, the reliability index is less affected by the change of slope geometric parameters. Compared to reducing the slope height, decreasing the slope ratio can more effectively ensure the enhancement of the slope's reliability. The reinforcement efficiency is the highest when the micro-pile is set near the foot of the slope. With the increase of slope ratio, the influence of the change of pile length on the reliability index increases. The influence of each random parameter on the reliability of the slope is different, and the influence of <em>L</em><sub><em>v</em></sub> is more significant. The influence of random parameters on the reliability index and safety factor of micro-pile reinforced slopes is essentially consistent across different geometric parameters.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103719"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reliability analysis method for multiple failure modes with overlapping failure domains 具有重叠失效域的多失效模式可靠性分析方法

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2025.103741

Aoyang Zhang , Zhenzhong Chen , Qianghua Pan , Xiaoke Li , Pei Feng , Xuehui Gan , Ge Chen , Liang Gao

{"title":"Reliability analysis method for multiple failure modes with overlapping failure domains","authors":"Aoyang Zhang , Zhenzhong Chen , Qianghua Pan , Xiaoke Li , Pei Feng , Xuehui Gan , Ge Chen , Liang Gao","doi":"10.1016/j.probengmech.2025.103741","DOIUrl":"10.1016/j.probengmech.2025.103741","url":null,"abstract":"<div><div>In reliability analysis, the problem of multiple failure modes with overlapping failure domains has long attracted significant attention. Traditional methods, such as direct integral methods and approximate analytical methods, cannot deal with this issue effectively. Typically, simulation techniques, such as Monte Carlo simulation and kriging, are employed. However, these methods require extensive sampling and computation, resulting in lower efficiency. Therefore, this paper proposes a new reliability analysis method for multiple failure modes with overlapping failure domains and multiple design points. The method combines a simplified formula for the hyperspherical cap area, applicable to both odd and even integer values, with the curved surface integral method, significantly simplifying the failure probability calculation process. Furthermore, by incorporating the hypersphere cap intersection region area, structures or systems with multiple failure modes can be efficiently handled. Five examples demonstrate that the proposed method outperforms traditional methods in both computational efficiency and accuracy.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103741"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An efficient strategy for information reuse in probability density evolution method considering large shift of distributions with multiple random variables 考虑多随机变量分布大位移的概率密度演化方法中信息复用的有效策略

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2024.103728

Jia-Shu Yang , Zhiqiang Wan , Hector Jensen

{"title":"An efficient strategy for information reuse in probability density evolution method considering large shift of distributions with multiple random variables","authors":"Jia-Shu Yang , Zhiqiang Wan , Hector Jensen","doi":"10.1016/j.probengmech.2024.103728","DOIUrl":"10.1016/j.probengmech.2024.103728","url":null,"abstract":"<div><div>The probability density evolution method (PDEM) is a versatile approach for analyzing stochastic dynamical systems. When combined with the change of probability measure (COM), it provides a tool to efficiently deal with the aleatory and epistemic uncertainties, where shifts of probability distributions are frequently encountered. However, when the shifts of distributions are too large, the PDEM-COM method can lead to increasing numerical errors. This paper aims to propose an extension of the PDEM-COM that can address the large shifts of distributions involving multiple random variables. In the proposed method, the concepts of the multi-dimensional augmented support and the augmented probability density function (PDF) are introduced based on the differences between the original and updated distributions. Then, an efficient numerical procedure is established for selecting a small set of additional representative points based on the augmented PDF. These additional representative points serve as a complement to the representative point set selected according to the original distributions. By incorporating the augmented representative point set and solving the generalized probability density evolution equation (GDEE), the stochastic response of the system considering the updated distributions can be evaluated. Numerical examples are presented to demonstrate the capability and effectiveness of the proposed approach. The results demonstrate that the proposed approach offers improved accuracy compared to the PDEM-COM method, particularly for large distribution shifts, while maintaining a relatively lower computational cost.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103728"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Stochastic stabilization of quasi integrable and non-resonant Hamiltonian systems under combined Gaussian and Poisson white noise excitation 高斯和泊松白噪声联合激励下拟可积非谐振哈密顿系统的随机镇定

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2025.103733

Weiyan Liu, Xunru Yin, Zhongjin Guo, Shan Jiang

{"title":"Stochastic stabilization of quasi integrable and non-resonant Hamiltonian systems under combined Gaussian and Poisson white noise excitation","authors":"Weiyan Liu, Xunru Yin, Zhongjin Guo, Shan Jiang","doi":"10.1016/j.probengmech.2025.103733","DOIUrl":"10.1016/j.probengmech.2025.103733","url":null,"abstract":"<div><div>A stochastic stabilization control strategy is proposed for multi-degree-of-freedom (MDOF) quasi integrable and non-resonant Hamiltonian systems under combined Gaussian and Poisson white noise excitation. At first, the averaged Itô stochastic differential equations (SDEs) for controlled first integrals are derived from the system motion equations by using the stochastic averaging method. Second, the dynamical programming equation of the averaged system with undetermined cost function is established based on the dynamical programming principle. The optimal control law is given through solving the dynamical programming equation. Third, the asymptotic Lyapunov stability with probability one of the controlled system is analyzed approximately by evaluating the largest Lyapunov exponent of the averaged system. Finally, the cost function and optimal control forces are determined based on the requirement of stabilizing the system. An example is delivered to illustrate the application and effectiveness of the proposed stochastic stabilization control strategy.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103733"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of train-induced ground-borne vibration transmission considering parametric uncertainties 考虑参数不确定性的列车引起的地面振动传递预测

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2025.103731

Ziyu Tao , Duo Zhang , Desi Tu , Lingshan He , Chao Zou

{"title":"Prediction of train-induced ground-borne vibration transmission considering parametric uncertainties","authors":"Ziyu Tao , Duo Zhang , Desi Tu , Lingshan He , Chao Zou","doi":"10.1016/j.probengmech.2025.103731","DOIUrl":"10.1016/j.probengmech.2025.103731","url":null,"abstract":"<div><div>Train-induced vibrations are of increasing concern as railway tracks and buildings are located closer to each other. In this study, a field measurement campaign was carried out where train-induced accelerations were monitored at the ground surface. Despite the uniformity of the train and track, field measurements unveil discrepancies in train-induced ground-borne vibrations at the given observation point. It underscores the need for a probabilistic evaluation of train-induced environmental vibrations. This study quantifies the uncertainties in train-induced ground-borne vibration transmissions and achieves a probabilistic assessment of the amplification phenomenon during ground-borne vibration transmissions. A transfer function-based model accounting for the train-induced ground-borne vibration transmission is developed and applied to the case study to justify its validity. Based on the validated prediction model, Monte Carlo method is subsequently adopted for quantifying uncertainties in train-induced ground-borne vibration transmissions caused by the spatially varied soil properties and by the variation in train speed, separately. Variations in soil properties are simulated using log-normally distributed random fields, while the train speed is simulated using a uniformly distributed random variable. The amplitude ratio between a pair of observation points is used to characterize ground-borne vibration transmissions. Burr distribution fitting is applied to the calculated samples of amplitude ratios, and during this process, the null hypothesis test is not rejected at the 5% significance level. The proposed methodology enables the determination of the amplification probability during train-induced ground-borne vibration transmissions. In addition, it aids reliability analysis and site screening in assessing building serviceability.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103731"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

B-splines chaos and Kalman Filters for solving a stochastic differential equation 解随机微分方程的b样条混沌和卡尔曼滤波

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2025.103734

Luis Sánchez , Andrew J. Simpkin , Norma Bargary

引用次数: 0

Global sensitivity analysis of design variables for porous hydrostatic gas bearings considering uncertainty 考虑不确定性的多孔静压气体轴承设计变量全局敏感性分析

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2024.103722

Yihua Wu , Lixiong Cao , Jiachang Tang , Mingqi Tian

{"title":"Global sensitivity analysis of design variables for porous hydrostatic gas bearings considering uncertainty","authors":"Yihua Wu , Lixiong Cao , Jiachang Tang , Mingqi Tian","doi":"10.1016/j.probengmech.2024.103722","DOIUrl":"10.1016/j.probengmech.2024.103722","url":null,"abstract":"<div><div>Porous hydrostatic gas bearing (PHGB) utilizes porous materials as restrictors and is widely recognized in mechanical equipment and scientific instruments due to their exceptional stability and load capacity. At present, the design of PHGB relies on deterministic models to calculate bearing capacity and stiffness, and the adjustment of parameters such as air supply pressure and bearing clearance mainly depends on experience. However, uncertainties related to compressor performance, material properties, and manufacturing errors are inevitably introduced in the practical applications, which can significantly affect the design performance of PHGBs. To address these challenges, this paper presents a global sensitivity analysis to identify the sensitive factors causing variations in the mechanical properties of PHGBs. First, a PHGB model is developed based on the Darcy and continuity equations, and its predictive accuracy for bearing characteristics is validated. Subsequently, a global sensitivity analysis method employing sparse polynomial chaos expansion is introduced to quantitatively assess the impact of uncertainties such as supply pressure, bearing length, diameter, clearance, and eccentricity on load capacity and mass flow rate. This analysis identifies the most critical uncertain parameters influencing the mechanical performance of PHGBs. The insights gained from this study will enable designers to comprehensively understand the mechanical performance of bearings under uncertainty while reducing computational costs, thus providing a valuable theoretical foundation for PHGB analysis and design.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103722"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advances in dimension-reduction methods for simulating univariate and multivariate non-stationary stochastic processes via spectral representation 用谱表示模拟单变量和多变量非平稳随机过程的降维方法研究进展

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2024.103720

Zixin Liu , Zhangjun Liu , Xinxin Ruan , Bohang Xu

{"title":"Advances in dimension-reduction methods for simulating univariate and multivariate non-stationary stochastic processes via spectral representation","authors":"Zixin Liu , Zhangjun Liu , Xinxin Ruan , Bohang Xu","doi":"10.1016/j.probengmech.2024.103720","DOIUrl":"10.1016/j.probengmech.2024.103720","url":null,"abstract":"<div><div>The novel dimension-reduction methods based on spectral representation for simulating both univariate and multivariate non-stationary stochastic processes are addressed. Initially, the original spectral (decomposition) representation of univariate (multivariate) non-stationary stochastic processes is derived. A unified expression for the original spectral decomposition integrating Cholesky decomposition and eigen decomposition is presented. Further, two typical random orthogonal functions associated with the standard orthogonal random variables in the original spectral (decomposition) representation are defined, resulting in the conventional Monte Carlo methods, namely the random amplitude method and the random phase method, are readily obtained. Meanwhile, two updated random orthogonal functions are introduced, enabling the dimension-reduction methods based on the random amplitude and the random phase respectively. The analysis above establishes that the original spectral (decomposition) representation forms the unified theoretical foundation for both the conventional Monte Carlo and the developed dimension-reduction methods. Essentially, both approaches are specific cases of the original spectral form. However, they share the same necessary conditions for simulation, though their sufficient conditions differ. Consequently, the dimension-reduction methods just require merely one to three elementary random variables for simulating univariate and multivariate non-stationary stochastic processes, significantly reducing the randomness of simulation from the level of thousands to an extremely low degree. Finally, numerical examples including the comparisons of simulation accuracy and efficiency between the conventional Monte Carlo methods and the dimension-reduction methods thoroughly substantiate the effectiveness and superiority of the latter.</div></div>","PeriodicalId":54583,"journal":{"name":"Probabilistic Engineering Mechanics","volume":"79 ","pages":"Article 103720"},"PeriodicalIF":3.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quadratic point estimate method for probabilistic moments computation 概率矩计算的二次点估计方法

IF 3 3区工程技术

Probabilistic Engineering Mechanics Pub Date : 2025-01-01 DOI: 10.1016/j.probengmech.2024.103705

Minhyeok Ko, Konstantinos G. Papakonstantinou

引用次数: 0