论文标题
离散结构响应的概率建模，并应用于复合板穿透模型
Probabilistic modeling of discrete structural response with application to composite plate penetration models
论文作者
论文摘要
结构的离散响应通常是关键的概率量。例如，一个人可能需要确定二进制事件的概率，例如结构是否包裹。在这项研究中，一种基于自适应域的分解和分类方法，结合稀疏的网格采样，用于为此类离散输出开发有效的分类替代模型算法。基于问题的物理学，输出相对于所有模型参数的单调行为的假设有助于减少模型评估的数量，并使算法更有效。作为一个应用问题，本文介绍了一个计算框架的开发，用于在弹道冲击下生成S-2玻璃/SC-15环氧复合板的概率渗透反应。这使概率速度响应（PVR）曲线的计算可行生成或$ V_0-V_ {100} $曲线是冲击速度的函数，以及弹道极限速度预测作为模型参数的函数。 PVR曲线结合了模型输入参数的可变性，并描述了板渗透是冲击速度的函数的概率。
Discrete response of structures is often a key probabilistic quantity of interest. For example, one may need to identify the probability of a binary event, such as, whether a structure has buckled or not. In this study, an adaptive domain-based decomposition and classification method, combined with sparse grid sampling, is used to develop an efficient classification surrogate modeling algorithm for such discrete outputs. An assumption of monotonic behaviour of the output with respect to all model parameters, based on the physics of the problem, helps to reduce the number of model evaluations and makes the algorithm more efficient. As an application problem, this paper deals with the development of a computational framework for generation of probabilistic penetration response of S-2 glass/SC-15 epoxy composite plates under ballistic impact. This enables the computationally feasible generation of the probabilistic velocity response (PVR) curve or the $V_0-V_{100}$ curve as a function of the impact velocity, and the ballistic limit velocity prediction as a function of the model parameters. The PVR curve incorporates the variability of the model input parameters and describes the probability of penetration of the plate as a function of impact velocity.
