PRISMS: An Integrated, Open-Source Framework for Accelerating Predictive Structural Materials Science

Abstract

The Center for Predictive Integrated Structural Materials Science (PRISMS Center) is creating a unique framework for accelerated predictive materials science and rapid insertion of the latest scientific knowledge into next-generation ICME tools. There are three key elements of this framework. The first is a suite of high-performance, open-source integrated multi-scale computational tools for predicting microstructural evolution and mechanical behavior of structural metals. Specific modules include statistical mechanics, phase field, crystal plasticity simulation and real-space DFT codes. The second is the Materials Commons, a collaboration platform and information repository for the materials community. The third element of the PRISMS framework is a set of integrated scientific ''Use Cases'' in which these computational methods are linked with experiments to demonstrate the ability for improving our predictive understanding of magnesium alloys, in particular, the influence of microstructure on monotonic and cyclic mechanical behavior. This paper reviews progress toward these goals and future plans.

PRISMS-PF: A general framework for phase-field modeling with a matrix-free finite element method

“…PRISMS-PF has already been applied toward advancing the understanding of lightweight structural components, the primary testbed for the PRISMS integrated software framework 25 , to simulate the evolution of precipitates in magnesium-rare earth alloys 31 . Simulations of isolated precipitates were shown to be largely consistent with experimental observations.…”

“…In this article, we introduce PRISMS-PF, a new open-source community framework for phase-field modeling, which is a key component of the open-source multiscale materials modeling framework developed by the PRISMS Center 25 . PRISMS-PF was created upon four principles:…”

Towards a scientific data framework to support scientific model development

“…All these fields are characterized by the mathematical, physical and computational modeling of complex systems and behaviors, and the validation of such models against experimental data which typically come from research articles. Indeed, similar challenges have been discussed recently in these fields, particularly those related to data integration, interpretation and large-scale analysis [1,6,21,35,47], highlighting several shared open issues. The framework investigated in this paper has been currently tested and optimized only for the scenario described in Section 2, but most of the design choices were taken trying to generalize its applicability.…”

“…Therefore, the solutions discussed in this paper have a general validity beyond the domain of combustion kinetics. Indeed, recent literature has highlighted "cases where datasets are reused in combination with other data, whether to make comparisons, build new models, or explore new questions altogether" [39], in fields such as computational biology [6], gene expression analysis [47], biomedical research [35], cell biology [21] or predictive structural materials science [1]. All these fields are characterized by the mathematical, physical and computational modeling of complex systems and behaviors, and the validation of such models against experimental data which typically come from research articles.…”

“…Large-scale validation of models with respect to experimental data is an emerging topic and other integrated systems have been proposed very recently in different domains. PRISMS [1] is an integrated framework for accelerating predictive structural materials science. It includes computational modules to predict microstructural evolution and the mechanical behavior of structural metals and a set of integrated scientific "use cases" where they are linked to experiments.…”