Bridging the Material Modeling Gap Between Research and Design

John Moore | 18-FS-003


The goal of this brief study was to investigate the feasibility of creating a materials modeling research and design software framework for better understanding and control of modern materials, as well as optimizing device-specific materials for high performance. If successful, the framework would enable reduction in design iterations in the context of energy and national security applications, which rely on tailored, advanced materials. Software development was initiated with partial success.

Background and Research Objectives

Modern materials (i.e., functionally graded and additively manufactured materials, or materials with properties not found in nature) can have material properties that vary inside a single part. This is detrimental to designers whose material models generally lack the ability to capture this heterogeneity and its effect on property variations. To address this deficiency, researchers build microscale material models that often take days to simulate what a designer must simulate in seconds. Though material models are a crucial tool for engineering analysis and design, at the fidelity currently used by designers, they often fail to account for microscale features (microstructures) that affect mechanical material properties. We proposed to fill the gap between research and design by determining the feasibility of decomposing a material's mechanical response into three categories, investigating these categories on the microscale, and transferring the results to a software model inexpensive enough for design.

The goal of the initial software development stage was to create a material model in an arbitrary Lagrangian-Eulerian three-dimensional (ALE3D) multi-physics code that was to calculate the plastic deformation of a material using criteria based on the work of Karafillis & Boyce (1993) and Moore (2018). Since the principal investigator had previous implementations of an anisotropic yield criteria, as well as a degradation function, the first task was to convert that code to ALE3D format and combine the anisotropic and degradation functions into one yield criteria. Early technical complications presented a roadblock that consumed most of the time allotted for this study, so the balance of the research remains to be done.

Impact on Mission

This study supported the NNSA goal of strengthening the competencies that are the foundation of its mission. Specifically, it was a step in helping to facilitate translation of materials research to design, thus supporting the Laboratory's core competency in advanced materials and manufacturing. Also, by exploring a tool that would allow for better materials optimization based on high-performance computing simulations, this study enhanced the Laboratory's core competency in high-performance computing, simulation, and data science.


During the initial phase of the study (combining existing codes), various technical issues arose. Though these issues were resolved, further effort would be needed to debug the code.


Karafillis, A. P. and M. C. Boyce. 1993. "A General Anisotropic Yield Criterion Using Bounds and a Transformation Weighting Tensor." Journal of the Mechanics and Physics of Solids, 41(12):1859–1886.

Moore, J. A. 2018. "A Degradation Function Consistent with Cocks–Ashby Porosity Kinetics." International Journal of Fracture, 209:231–234.