An ontological framework for integrated computational materials engineering

Abstract

ICME is expected to significantly reduce the dependence on trial and error based experimentation cycles for materials development and deployment in products. However, modeling and simulation is a knowledge intensive activity. In an integrated design, choosing right models for different phenomena, at right scales, with right parameters, and ensuring integration across these models is a non-trivial task. The gaps in modeling and simulation need to be filled with tacit knowledge and co-engineered with product knowledge. Therefore, an IT platform having capabilities such as, (a) a repository of building-block models, templates and workflows with an intelligent means to choose and compose right workflows for a given problem, (b) a knowledge engineering framework for knowledge management, (c) a simulation services framework for simulation tool integration and simulation execution, (d) tools for decision support, optimization, robust design etc., is essential for scaling up ICME for industrial applicability. This requires a unifying semantic foundation. Ontologies can provide the common substrate for integration of different models, the common language for information exchange, and the means for capturing and organizing knowledge. However, ontology engineering is a challenge when we consider the diversity of the material systems, products, processes and mechanisms involved in ICME. This calls for a flexible ontological framework that provides a means for modeling the generic structure of a subject area (e.g. materials) and a means for instantiating subject specific ontologies from this generic structure. We describe a model driven framework and how it has been used for developing an enabling platform for ICME.