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An imprecise multiscale uncertainty quantification framework for fiber reinforced composites 纤维增强复合材料的不精确多尺度不确定性量化框架
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-09-20 DOI: 10.1016/j.probengmech.2024.103686
Haodong Zhao, Changcong Zhou
The study focuses on the reliability and global sensitivity analysis of fiber-reinforced composite radome structures, considering uncertainty from a multiscale perspective. Macroparameters are estimated based on microparameters using the multiscale analysis method for composites, and a reliability analysis model of the composite structure at the macrolevel is constructed. The material performance mechanism is explored in depth, both "from bottom to top" and "from top to bottom", to reveal its inherent laws. Due to insufficient variable distribution information, an imprecise probabilistic model is introduced to characterize the uncertainty effect in multiscale composite analysis. A nested optimization calculation method is applied to obtain reliability and sensitivity results. To ensure both calculation accuracy and efficiency, the regression and classification problems encountered in the proposed framework are addressed using two support vector machine models. The reliability and sensitivity analysis under the imprecise probabilistic framework can help engineers identify significant influential factors, thereby guiding the design of composite radome structures.
研究重点是纤维增强复合材料雷达罩结构的可靠性和全局敏感性分析,从多尺度角度考虑不确定性。使用复合材料多尺度分析方法,根据微观参数估计宏观参数,并在宏观层面构建复合材料结构的可靠性分析模型。从 "自下而上 "和 "自上而下 "两个方面深入探讨材料的性能机理,揭示其内在规律。由于变量分布信息不足,在多尺度复合材料分析中引入了一个不精确的概率模型来描述不确定性效应。应用嵌套优化计算方法获得可靠性和灵敏度结果。为了确保计算的准确性和效率,我们使用两个支持向量机模型来解决所提出的框架中遇到的回归和分类问题。不精确概率框架下的可靠性和灵敏度分析可以帮助工程师识别重要的影响因素,从而指导复合材料雷达罩结构的设计。
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引用次数: 0
Hybrid Bayesian-Copula-based damage probability estimation for steel-concrete composite tall buildings under concurrent seismic and wind loads 基于贝叶斯-Copula 的钢-混凝土复合高层建筑在地震和风荷载同时作用下的损坏概率估计混合方法
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-09-20 DOI: 10.1016/j.probengmech.2024.103693
Xiao-Wei Zheng , Jie Cheng , Ling-Xin Zhang , Xian-Xin Xie
Tall buildings with long service periods inevitably face multiple hazards, and the uncertainty associated with various factors has a considerable impact on life-cycle structural safety estimation. This study presents a hybrid Bayesian-Copula-based methodology for evaluating the damage risk e of tall buildings under concurrent seismic and strong wind excitations that incorporate various uncertainties. The main contributions of this study to the field of probabilistic multi-hazard risk assessment include the following: (1) The Bayes statistic method is employed to develop posterior probability distributions of the unknown parameters in the marginal probability models of an individual earthquake and strong wind as well as parameters involved in the multi-hazard demand model for fragility estimation. (2) The Bayesian-based method is applied to update the existing joint probabilistic model of earthquakes and strong winds. (3) A new method is presented to estimate the muti-hazard fragility bounds. The damage risk assessment quantifies the epistemic uncertainties of the unknown demand model parameters by calculating the total probability in the domain of the definition of the model parameters. A representative composite building with 42 floors is selected to perform this multi-hazard damage risk assessment method. The application of this study highlights the considerable impact of epistemic uncertainties and loading directions on damage risk. This presented Bayesian-Copula-based method is beneficial for decision-making involving tall buildings subjected to multiple hazards.
使用期较长的高层建筑不可避免地会面临多种危害,而各种因素的不确定性会对全寿命周期结构安全评估产生相当大的影响。本研究提出了一种基于贝叶斯-Copula 的混合方法,用于评估高层建筑在地震和强风同时激励下的损坏风险 e,其中包含各种不确定性。本研究在概率多灾害风险评估领域的主要贡献包括以下几点:(1) 采用贝叶斯统计方法建立了单个地震和强风边际概率模型中未知参数的后验概率分布,以及用于脆性估计的多灾害需求模型中的参数。(2) 运用基于贝叶斯的方法更新现有的地震和强风联合概率模型。(3) 提出了一种估算多灾害脆弱性边界的新方法。损害风险评估通过计算模型参数定义域内的总概率来量化未知需求模型参数的认识不确定性。本研究选取了一栋具有代表性的 42 层复合式建筑来执行这种多灾害损害风险评估方法。这项研究的应用凸显了认识上的不确定性和加载方向对损害风险的巨大影响。所提出的这种基于贝叶斯-Copula 的方法有利于涉及受多种灾害影响的高层建筑的决策。
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引用次数: 0
Numerical investigation of turbulence effect on flight trajectory of spherical windborne debris: A multi-layered approach 湍流对球形风载碎片飞行轨迹影响的数值研究:多层次方法
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103661
Shaopeng Li , Kurtis Gurley , Yanlin Guo , John van de Lindt

Accurate modeling of the turbulent wind field is a crucial component of risk analysis for structures to windborne debris damage. Existing studies typically simplify the complexities of wind turbulence, and the potential influence on the accuracy of debris flight modeling has not been systematically demonstrated. This study takes a multi-layered approach to numerically simulate the flight trajectory of spherical debris in a turbulent wind field. Complexities are incrementally added to the simulated wind field to systematically investigate the influence of spatial correlation and non-Gaussian features of turbulence on debris flight behavior. The sensitivity of debris flight behavior to turbulent wind features will inform the design of debris flight tracking wind tunnel tests and building façade debris vulnerability modeling efforts.

湍流风场的精确建模是结构物遭受风载碎片破坏风险分析的关键组成部分。现有研究通常会简化风湍流的复杂性,而其对碎片飞行建模准确性的潜在影响尚未得到系统论证。本研究采用多层方法对球形碎片在湍流风场中的飞行轨迹进行数值模拟。在模拟风场中逐步增加复杂性,以系统地研究湍流的空间相关性和非高斯特征对碎片飞行行为的影响。碎片飞行行为对湍流风特征的敏感性将为设计碎片飞行跟踪风洞试验和建筑外墙碎片易损性建模工作提供参考。
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引用次数: 0
Uncertainties quantification for damage localization in concrete based on Bayesian method 基于贝叶斯方法的混凝土损伤定位不确定性量化
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103660
Minghui Zhang, Deyuan Zhou, Xia Yang, Xiangtao Sun, Qingzhao Kong

The presence of defects in concrete can diminish load-bearing capacity of structures, giving rise to potential concerns regarding safety and durability. Thus, a method that enhances the sensitivity, resolution and robustness of damage localization is critically necessary to assess the condition of concrete structures. This research presents a damage localization method based on Bayesian probabilistic fusion, and uncertainties from measurement and identification process are considered and quantified. The likelihood function is constructed based on the hyperbola-based damage localization method, and the posterior distributions of unknown parameters are calculated via Bayesian theorem combined with measurement data. Furthermore, a meso-level finite element model is established, wherein the concrete medium is considered as a three-phase composite material consisting of polygonal aggregates, mortar matrix and interface transition zones. Owing to the meso-level modeling, the propagation behavior of stress waves within concrete and complicated interactions between stress waves and concrete internal structures can be better characterized. Finally, the damage information, time-difference-of arrival, is extracted from the response signals and the efficiency of the proposed method is verified numerically. The numerical results demonstrate that the proposed probabilistic fusion method outperforms the conventional hyperbola-based method in terms of achieving high spatial resolution and resilience in damage localization.

混凝土中存在的缺陷会降低结构的承载能力,从而引发安全和耐久性方面的潜在问题。因此,一种能提高损伤定位灵敏度、分辨率和稳健性的方法对于评估混凝土结构的状况至关重要。本研究提出了一种基于贝叶斯概率融合的损伤定位方法,考虑并量化了测量和识别过程中的不确定性。基于双曲线的损伤定位方法构建了似然函数,并通过贝叶斯定理结合测量数据计算了未知参数的后验分布。此外,还建立了中层有限元模型,将混凝土介质视为由多边形集料、砂浆基质和界面过渡区组成的三相复合材料。由于采用了中层模型,应力波在混凝土内部的传播行为以及应力波与混凝土内部结构之间复杂的相互作用可以得到更好的描述。最后,从响应信号中提取了损伤信息(到达时间差),并通过数值验证了所提方法的效率。数值结果表明,所提出的概率融合方法在实现高空间分辨率和损伤定位弹性方面优于传统的基于双曲线的方法。
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引用次数: 0
Performance-based target reliability analysis of offshore wind turbine mooring lines subjected to the wind and wave 对受风浪影响的海上风力涡轮机系泊缆线进行基于性能的目标可靠性分析
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103673
Mohammad Safari , Seyed Hooman Ghasemi , Andrzej S. Nowak

Reliability assessment is a crucial aspect of the design and operation of structures, particularly in balancing safety and cost considerations. This paper introduces a novel method for evaluating the performance-based target reliability of floating wind turbine platforms in offshore environments. The method focuses on the platform's motion modes and wave frequencies, which significantly influence the system's structural integrity and performance. An improved limit state function is proposed to enhance the accuracy of reliability calculations, specifically for steady-state conditions. The platform's six degrees of freedom motions are carefully analyzed to investigate their dependence on wave frequencies. By considering the time response of these motions and accounting for uncertainties in wave characteristics, wave impact directions, and wind effects, a comprehensive reliability analysis is conducted to assess the stability modes of the platform. This paper introduces the term 'Reliability Performance-Based' (RPB) analysis as a new concept to evaluate the system's reliability at a given performance level. Furthermore, an optimal target reliability index is defined to address the economic aspect of the design process. The proposed methodology's PEB analysis focuses on capturing uncertainties in wave characteristics and wind effects on floating wind turbine platforms. This includes a detailed examination of wave and wind-induced loads and their propagation through the system concerning its performance level. Statistical models were integrated to quantify these uncertainties, applying Monte Carlo simulations to assess their effects on the platform's reliability. This approach allows for a nuanced understanding of the interactions between environmental factors and structural responses, enhancing the precision of our reliability assessments. It enables the consideration of economic efficiency alongside safety, ensuring a balanced approach to the design and operation of the floating wind turbine platform. By providing a comprehensive reliability assessment framework, it aids in the optimization of design and decision-making processes for floating wind turbine platforms.

可靠性评估是结构设计和运行的一个重要方面,尤其是在平衡安全和成本方面。本文介绍了一种新方法,用于评估海上浮动风力涡轮机平台基于性能的目标可靠性。该方法侧重于平台的运动模式和波频,因为它们对系统的结构完整性和性能有重大影响。为提高可靠性计算的准确性,特别是稳态条件下的可靠性计算,提出了一种改进的极限状态函数。对平台的六个自由度运动进行了仔细分析,以研究它们对波频的依赖性。通过考虑这些运动的时间响应,并考虑波浪特性、波浪冲击方向和风效应的不确定性,进行了全面的可靠性分析,以评估平台的稳定模式。本文引入了 "基于可靠性能"(RPB)分析这一全新概念,用于评估给定性能水平下的系统可靠性。此外,本文还定义了最佳目标可靠性指数,以解决设计过程中的经济问题。拟议方法的 PEB 分析侧重于捕捉浮动风力涡轮机平台上波浪特性和风效应的不确定性。这包括详细检查波浪和风引起的负载及其在系统中的传播,从而影响系统的性能水平。统计模型用于量化这些不确定性,并应用蒙特卡罗模拟来评估它们对平台可靠性的影响。通过这种方法,我们可以深入了解环境因素与结构反应之间的相互作用,从而提高可靠性评估的精确度。在考虑安全性的同时,还能考虑经济效益,确保浮动风力涡轮机平台的设计和运行达到平衡。通过提供全面的可靠性评估框架,它有助于优化浮动风力涡轮机平台的设计和决策过程。
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引用次数: 0
Modal–based uncertainty quantification for deterministically estimated structural parameters in low-fidelity model updating of complex connections 复杂连接低保真模型更新中确定性估算结构参数的基于模态的不确定性量化
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103671
Milad Mehrkash, Erin Santini-Bell

Modeling complex joints in structures entails significant time and effort, necessitating simplifications. Epistemic uncertainties arising from low-fidelity modeling can be quantified through probabilistic model updating. However, finding a surrogate physical model to represent simplified joint configurations poses challenges. Additionally, establishing a Bayesian formulation capable of incorporating structural parameters of connections is necessary. This study employs a validated simplifying parameterization approach for surrogate modeling of complex semi-rigid connections in a benchmark laboratory steel grid. It proposes a modal probabilistic Bayesian methodology to quantify uncertainties in the structure's joints. Three modal-based objective functions are utilized for finite element model updating. The modal properties of the structure are extracted by experimental modal analysis during an impact test, which will be utilized in the model updating process. Deterministic and probabilistic structural parameter estimations are integrated to enhance the robustness of the Bayesian technique. Furthermore, a guideline for selecting optimal hyperparameters is provided. Results demonstrate that utilizing deterministically estimated parameters as prior knowledge can facilitate and improve modal probabilistic model updating for structures with complex joints. Also, it is found that despite significant simplifications of joints, structural parameter tolerance around the maximum a posteriori estimate in surrogate models remains low.

结构中复杂关节的建模需要花费大量的时间和精力,因此必须进行简化。低保真建模产生的认识不确定性可通过概率模型更新进行量化。然而,寻找一个替代物理模型来表示简化的关节配置是一项挑战。此外,还需要建立一个能够纳入连接结构参数的贝叶斯公式。本研究采用了一种经过验证的简化参数化方法,用于在基准实验室钢网格中对复杂的半刚性连接进行代理建模。它提出了一种模态概率贝叶斯方法来量化结构连接中的不确定性。利用三个基于模态的目标函数进行有限元模型更新。结构的模态属性是在冲击试验中通过实验模态分析提取的,将在模型更新过程中加以利用。确定性和概率性结构参数估计相结合,增强了贝叶斯技术的稳健性。此外,还提供了选择最佳超参数的指南。结果表明,利用确定性估计参数作为先验知识,可以促进和改进具有复杂接头的结构的模态概率模型更新。此外,研究还发现,尽管对关节进行了大量简化,代用模型中最大后验估计值附近的结构参数容差仍然很低。
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引用次数: 0
An improved interval prediction method for recurrence period wind speed 重现期风速的改进区间预测法
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103675
Weihu Chen , Yuji Tian , Yiyi Tian , Haiwei Guan

Based on the improved interval operation theory, an improved expression of the return period wind speed interval prediction is constructed by using an approximate first-order Taylor series expansion. According to the measured wind speed data in Beijing, Jinan, Nanjing, Wuxi, Shanghai and Shenzhen, the improved method and the traditional method are respectively used to predict the interval of the return period wind speed. Furthermore, the interval results predicted by the improved method and the traditional method are compared and analyzed under the same confidence level. Results show that the improved method has good applicability for different parameter estimation methods under the condition of certain extreme value distribution model, and the interval prediction results of the return period wind speed are basically stable. Compared with the interval results predicted by the traditional method, the interval predicted by the improved method is more likely to be close to or contain the exact solution of the return period wind speed, which has higher prediction accuracy. In addition, the calculation process of the improved method is relatively simple and can realize the simplified calculation of interval prediction.

基于改进的区间运行理论,利用近似一阶泰勒级数展开,构建了改进的回归期风速区间预测表达式。根据北京、济南、南京、无锡、上海和深圳的实测风速数据,分别采用改进方法和传统方法预测了回归期风速的区间。此外,在相同置信水平下,对改进方法和传统方法预测的区间结果进行了比较和分析。结果表明,在一定的极值分布模型条件下,改进方法对不同的参数估计方法具有良好的适用性,重现期风速的区间预测结果基本稳定。与传统方法预测的区间结果相比,改进方法预测的区间更容易接近或包含回归期风速的精确解,预测精度更高。此外,改进方法的计算过程相对简单,可以实现区间预测的简化计算。
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引用次数: 0
Statistical model calibration of correlated unknown model variables through identifiability improvement 通过可识别性改进对相关未知模型变量进行统计模型校准
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103670
Jeonghwan Choo , Yongsu Jung , Hwisang Jo , Ikjin Lee

A statistical model calibration problem is known to have unstable or non-unique optimal solutions due to its ill-posed inverse nature, which is further complicated by limited test data availability due to time and cost constraints. To overcome these challenges and improve the identifiability of calibration parameters, this study proposes a novel statistical model calibration framework. The proposed method integrates input test data for unknown model variables and output test data for a system response, employing a bivariate form of copula function to model the probability distribution while accounting for the correlations between unknown model variables. Furthermore, a sample-averaged log-likelihood is used as a calibration metric, assuming conditional independence to reflect input and output test data evenly in a single metric. Optimization-based model calibration (OBMC) is performed to identify the probability models that maximize the calibration metric for a given set of input and output test data, among candidates of marginal probability distributions and copula functions. Consequently, this proposed method enhances the identifiability of calibration parameters and overcomes insufficient data issues by taking observations of unknown model variables into account in the statistical model calibration procedure. The proposed framework is validated using numerical examples.

众所周知,统计模型校准问题具有不稳定或非唯一的最优解,这是因为它的反问题性质,而由于时间和成本的限制,测试数据的可用性有限,使得问题变得更加复杂。为了克服这些挑战并提高校准参数的可识别性,本研究提出了一种新型统计模型校准框架。该方法整合了未知模型变量的输入测试数据和系统响应的输出测试数据,采用双变量形式的 copula 函数来模拟概率分布,同时考虑未知模型变量之间的相关性。此外,使用样本平均对数似然作为校准指标,假定条件独立,以单一指标均匀反映输入和输出测试数据。通过基于优化的模型校准(OBMC),可从边际概率分布和共轭函数的候选模型中,找出能使给定输入和输出测试数据集的校准指标最大化的概率模型。因此,通过在统计模型校准过程中考虑对未知模型变量的观测,该方法提高了校准参数的可识别性,并克服了数据不足的问题。所提出的框架通过数值示例进行了验证。
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引用次数: 0
Inference on the high-reliability lifetime estimation based on the three-parameter Weibull distribution 基于三参数威布尔分布的高可靠性寿命估计推论
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103665
Xiaoyu Yang , Liyang Xie , Bowen Wang , Jianpeng Chen , Bingfeng Zhao

The high-reliability lifetime estimation of the lifting lug is of significant importance, as it is the most crucial component of the aerial bomb. This paper focuses on the high-reliability lifetime of the three-parameter Weibull distribution for lifting lug fatigue data. A novel method is developed to generate estimates of reliability lifetime according to the generalized fiducial inference, whose prior is calculated by the failure data. A posterior distribution is obtained based on Bayesian theory to compute the point estimate and the confidence interval of the generalized fiducial inference for reliability lifetime using the Monte Carlo Markov chain method. Subsequently, it is compared with the non-informative prior Bayesian inference. A Monte Carlo simulation demonstrates that the proposed method outperforms the non-informative prior Bayesian inference. The lower confidence limit of the generalized fiducial inference for the reliability lifetime exhibis satisfactory coverage probabilities. Finally, fatigue tests are performed on 18 lifting lugs under variable loads. The point estimate and the lower confidence limit of the high-reliability lifetime are estimated, which can illustrate the applicability of the proposed method.

吊耳是航空炸弹最关键的部件,因此对吊耳的高可靠性寿命进行估算具有重要意义。本文重点研究了吊耳疲劳数据的三参数 Weibull 分布的高可靠性寿命。本文开发了一种新方法,可根据广义似然推理生成可靠性寿命估计值,而似然推理的先验值由失效数据计算得出。根据贝叶斯理论获得后验分布,利用蒙特卡洛马尔科夫链方法计算出可靠性寿命广义信标推断的点估计和置信区间。随后,将其与非信息先验贝叶斯推断进行比较。蒙特卡罗模拟证明,所提出的方法优于非信息先验贝叶斯推断法。可靠性寿命的广义先验推断的置信度下限显示出令人满意的覆盖概率。最后,对 18 个起重吊耳进行了不同载荷下的疲劳试验。估算出了高可靠性寿命的点估计值和置信下限,从而说明了所提方法的适用性。
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引用次数: 0
Probability density of the solution to nonlinear systems driven by Gaussian and Poisson white noises 高斯和泊松白噪声驱动的非线性系统解的概率密度
IF 3 3区 工程技术 Q2 ENGINEERING, MECHANICAL Pub Date : 2024-07-01 DOI: 10.1016/j.probengmech.2024.103658
Wantao Jia , Zhe Jiao , Wanrong Zan , Weiqiu Zhu

A new method is proposed to compute the probability density of the multi-dimensional nonlinear dynamical system perturbed by a combined excitation of Gaussian and Poisson white noises. We first deduce a probability-density solver from the Euler–Maruyama scheme of the stochastic system and the corresponding Chapman–Kolmogorov equation. This solver actually is an explicit numerical formula of the probability density of the solution to this stochastic system. To compute the probability density, we propose an efficient algorithm for this solver, which actually is the implementation of a numerical integration. Furthermore, we prove this solver is an approximated solution of the corresponding forward Kolmogorov equation. Numerical examples are conducted to illustrate our probability-density solver.

本文提出了一种新方法,用于计算受到高斯白噪声和泊松白噪声联合激励扰动的多维非线性动力系统的概率密度。我们首先从随机系统的 Euler-Maruyama 方案和相应的 Chapman-Kolmogorov 方程推导出概率密度求解器。这个求解器实际上是该随机系统解的概率密度的显式数值公式。为了计算概率密度,我们为这个求解器提出了一种高效算法,实际上就是数值积分的实现。此外,我们还证明了这种求解器是相应的正向科尔莫哥罗夫方程的近似解。我们通过数值示例来说明我们的概率密度求解器。
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引用次数: 0
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Probabilistic Engineering Mechanics
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