When dealing with timber structures, the characteristic strength and stiffness of the material are made highly variable and uncertain by the unavoidable, yet hardly predictable, presence of knots and other defects. In this work we apply the sparse grids stochastic collocation method to perform uncertainty quantification for structural engineering in the scenario described above. Sparse grids have been developed by the mathematical community in the last decades and their theoretical background has been rigorously and extensively studied. The document proposes a brief practice-oriented introduction with minimal theoretical background, provides detailed instructions for the use of the already implemented Sparse Grid Matlab kit (freely available on-line) and discusses two numerical examples inspired from timber engineering problems that highlight how sparse grids exhibit superior performances compared to the plain Monte Carlo method. The Sparse Grid Matlab kit requires only a few lines of code to be interfaced with any numerical solver for mechanical problems (in this work we used an isogeometric collocation method) and provides outputs that can be easily interpreted and used in the engineering practice.
翻译:在与木材结构打交道时,由于不可避免、但难以预测的结节和其他缺陷的存在,材料的特性强度和坚硬性因不可避免、但又难以预测而变化很大和不确定。在这项工作中,我们采用稀疏的网格混搭方法,对上述假设情景中的结构工程进行不确定的量化。数学界在过去几十年中开发了粗糙的网格,对它们的理论背景进行了严格和广泛的研究。文件提出了一个简短的面向实践的介绍,其理论背景极小,为使用已经安装的Sparse Grid Matlab包(可免费在线查阅)提供了详细的指导,并讨论了来自木材工程问题的两个数字例子,这些例子突出了稀疏网格与平坦的蒙特卡洛方法相比,表现如何优异。Sparse Grap Matlab包只需要几行代码才能与机械问题的任何数字求解器相连接(在这项工作中,我们使用的是等分解方法),并提供了在工程实践中容易解释和使用的产出。