The application of rail buckling models is often limited by uncertain information with respect to track properties, and many conventional are poorly suited network-wide or even regional application. Here, a methodology using fuzzy sets presented that, when trained data can use inputs properties predict the minimum temperature increase for particular track. An investigation impact size training ...

We extend the model-free Data-Driven computing paradigm to solids and structures that are stochastic due intrinsic randomness in material behavior. The behavior of such materials is characterized by a likelihood measure instead constitutive relation. specifically assume known only through an empirical point-data set or phase space. state solid structure additionally subject compatibility equili...