Department of Physics, North Carolina State University, Raleigh, NC 27695;
Department of Mathematics, University of California, Los Angeles, CA 90095.
Proc Natl Acad Sci U S A. 2019 Aug 20;116(34):16742-16749. doi: 10.1073/pnas.1900272116. Epub 2019 Aug 2.
Forecasting fracture locations in a progressively failing disordered structure is of paramount importance when considering structural materials. We explore this issue for gradual deterioration via beam breakage of 2-dimensional (2D) disordered lattices, which we represent as networks, for various values of mean degree. We study experimental samples with geometric structures that we construct based on observed contact networks in 2D granular media. We calculate geodesic edge betweenness centrality, which helps quantify which edges are on many shortest paths in a network, to forecast the failure locations. We demonstrate for the tested samples that, for a variety of failure behaviors, failures occur predominantly at locations that have larger geodesic edge betweenness values than the mean one in the structure. Because only a small fraction of edges have values above the mean, this is a relevant diagnostic to assess failure locations. Our results demonstrate that one can consider only specific parts of a system as likely failure locations and that, with reasonable success, one can assess possible failure locations of a structure without needing to study its detailed energetic states.
当考虑结构材料时,预测逐渐失效的无序结构中的断裂位置至关重要。我们通过二维(2D)无序晶格的梁断裂来探索这种渐进劣化的问题,我们将其表示为网络,对于不同的平均度数。我们研究了具有基于在二维颗粒介质中观察到的接触网络构建的几何结构的实验样本。我们计算了测地边介数中心性,这有助于量化网络中哪些边在许多最短路径上,以预测失效位置。我们为测试样本证明,对于各种失效行为,失效主要发生在具有比结构中平均值更大的测地边介数值的位置。因为只有一小部分边缘的值高于平均值,所以这是评估失效位置的一个相关诊断方法。我们的结果表明,可以仅将系统的特定部分视为可能的失效位置,并且可以合理地成功评估结构的可能失效位置,而无需研究其详细的能量状态。