  Numerous theories of failure have been postulated and implemented in various
commercial programs for composite materials. Even the best theories have had
limited success in predicting damage and failure in validation exercises. In
view of this background, many researchers have started exploring the use of
multiscale modeling to improve the fidelity of the modeling and simulation of
various structural and materials systems. In this paper, a multi-scale modeling
scheme is used to illustrate how a combination of virtual and laboratory
testing programs can be used to generate a point cloud of failure surface data
that can then be queried during finite element analysis at the continuum scale
to ascertain if the onset of failure has occurred. The k-nearest neighbor
(k-NN) classification concept is used to obtain the answer to the query. A
linear, elastic, static finite element example using a unidirectional composite
shows that the framework can be generated and used effectively and efficiently
with the possibility to extend the approach for all types of composite
architectures and behaviors.
