Computer-Aided Design 45 (2013) 4–25 Contents lists available at SciVerse ScienceDirect Computer-Aided Design journal homepage: www.elsevier.com/locate/cad Key computational modeling issues in Integrated Computational Materials Engineering Jitesh H. Panchal a , Surya R. Kalidindi b , David L. McDowell c,∗ a School of Mechanical and Materials Engineering, Washington State University, Pullman, WA 99164-2920, USA b Department of Materials Science and Engineering, Department of Mechanical Engineering and Mechanics, Drexel University, Philadelphia, PA 19104, USA c School of Materials Science and Engineering, Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0405, USA article info Keywords: Materials design Multiscale modeling ICME Databases Uncertainty abstract Designing materials for targeted performance requirements as required in Integrated Computational Materials Engineering (ICME) demands a combined strategy of bottom–up and top–down modeling and simulation which treats various levels of hierarchical material structure as a mathematical representation, with infusion of systems engineering and informatics to deal with differing model degrees of freedom and uncertainty. Moreover, with time, the classical materials selection approach is becoming generalized to address concurrent design of microstructure or mesostructure to satisfy product-level performance requirements. Computational materials science and multiscale mechanics models play key roles in evaluating performance metrics necessary to support materials design. The interplay of systems-based design of materials with multiscale modeling methodologies is at the core of materials design. In high performance alloys and composite materials, maximum performance is often achieved within a relatively narrow window of process path and resulting microstructures. Much of the attention to ICME in the materials community has focused on the role of generating and representing data, including methods for characterization and digital representation of microstructure, as well as databases and model integration. On the other hand, the computational mechanics of materials and multidisciplinary design optimization communities are grappling with many fundamental issues related to stochasticity of processes and uncertainty of data, models, and multiscale modeling chains in decision- based design. This paper explores computational and information aspects of design of materials with hierarchical microstructures and identifies key underdeveloped elements essential to supporting ICME. One of the messages of this overview paper is that ICME is not simply an assemblage of existing tools, for such tools do not have natural interfaces to material structure nor are they framed in a way that quantifies sources of uncertainty and manages uncertainty in representing physical phenomena to support decision- based design. © 2012 Elsevier Ltd. All rights reserved. 1. The path to Integrated Computational Materials Engineering (ICME) Within the past decade, several prominent streams of research and development have emerged regarding integrated design of materials and products. One involves selection of materials, em- phasizing population of databases and efficient search algorithms for properties or responses that best suit a set of specified perfor- mance indices [1], often using combinatorial search methods [2], pattern recognition, and so on. In such materials informatics ap- proaches, attention is focused on data mining, visualization, and providing convenient and powerful interfaces for the designer to ∗ Corresponding author. Tel.: +1 404 894 5128; fax: +1 404 894 0186. E-mail address: david.mcdowell@me.gatech.edu (D.L. McDowell). support materials selection. Another class of approaches advocates simulation-based design to exploit computational materials sci- ence and physics in accelerating the discovery of new materials, computing structure and properties using a bottom–up approach. This can be combined with materials informatics. For example, the vision for Materials Cyber-Models for Engineering is a compu- tational materials physics and chemistry perspective [3] on using quantum and molecular modeling tools to explore for new ma- terials and compounds, making the link to properties. Examples include the computational estimate of stable structure and prop- erties of multicomponent phases using first principles approaches (e.g., Refs. [4–6]). These approaches have been developed and pop- ularized largely within the context of the materials chemistry, physics and science communities. A third approach, involving more the integration of databases with tools for modeling and simulation, as well as design 0010-4485/$ – see front matter © 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.cad.2012.06.006