ITR: Computational Tools for Multicomponent Materials Design

该奖项是在信息技术研究倡议下获得的，由材料研究部和高级计算基础设施研究部联合资助。这项合作研究项目涉及两名材料科学家、一名计算机科学家、一名数学家和两名来自学术界、工业界和国家实验室的物理学家。该项目是一项协同努力，利用了研究人员在可扩展并行科学计算、第一性原理和原子计算、计算热力学、中尺度微观结构演化和宏观力学特性建模领域的重叠和互补专业知识。该提案的主要目标是开发一套集成的计算工具，以预测多组分材料的化学，微观结构和机械性能之间的关系，使用技术上重要的铝基合金作为模型材料。将开发一种支持网格的原型软件，用于多组分材料设计，并在设计阶段之间进行有效的信息交换。每个设计阶段将结合有效的算法和并行计算方案。将集成四个计算组件，它们是：(1)第一性原理计算，以确定一元，二元和三元化合物的热力学性质，晶格参数和动力学数据；(2) CALPHAD数据优化计算，结合第一性原理计算结果和实验数据提取多组分体系的热力学性质、晶格参数和动力学数据；(3)多组分相场建模生成微观结构；(4)有限元分析，从模拟的微观结构中获得力学响应。该研究涉及信息技术的并行工作，主要包括两个部分：(1)先进的离散化和并行算法；(2)分布式计算系统的软件体系结构。第一个组成部分包括：(a)谱和有限元近似的耦合，(b)局部自适应和多尺度分辨率，(c)时间方案中的高阶稳定半隐式，(d)通过域分解的并行化，以及(e)可扩展的稀疏系统求解器。第二个组成部分涉及用于整个设计过程的计算网格支持软件；该软件体系结构支持使用地理分布的高性能并行计算资源，以减少应用程序的周转时间，同时提供灵活的客户机-服务器接口，允许进行多个设计周期。该研究项目将通过学生和pi参与宾夕法尼亚州立大学高性能计算研究所提供的“高性能计算研究生辅修课程”，与计算科学和工程广泛领域的研究生教育和培训相结合。宾夕法尼亚州立大学现有的项目将用于整合本科生到该项目中。该奖项是在信息技术研究倡议下获得的，由材料研究部和高级计算基础设施研究部联合资助。这项合作研究项目涉及两名材料科学家、一名计算机科学家、一名数学家和两名来自学术界、工业界和国家实验室的物理学家。该项目是一项协同努力，利用了研究人员在可扩展并行科学计算、第一性原理和原子计算、计算热力学、中尺度微观结构演化和宏观力学特性建模领域的重叠和互补专业知识。该提案的主要目标是开发一套综合计算工具，以预测多组分材料的化学，微观结构和力学性能之间的关系，使用技术上重要的铝基合金作为模型材料。原型网格支持软件将开发用于多组分材料设计。有效的算法和并行计算方案将被纳入设计。支持网格的软件允许利用地理分布的高性能并行计算资源，为给定的问题带来更大的计算能力，并使这些计算工具的实际应用成为可能。原型软件在多组分材料设计方面具有改进的预测能力，可以使科学家开发具有独特性能的新材料，并使现有材料具有更好的性能。该研究项目将通过学生和pi参与宾夕法尼亚州立大学高性能计算研究所提供的“高性能计算研究生辅修课程”，与计算科学和工程广泛领域的研究生教育和培训相结合。宾夕法尼亚州立大学现有的项目将用于整合本科生到该项目中

This award is made under the Information Technology Research initiative and is funded jointly by the Division of Materials Research and the Advanced Computational Infrastructure Research Division.This collaborative research project involves two materials scientists, a computerscientist, a mathematician, and two physicists from academia, industry and a national laboratory. The project is a synergistic effort that leverages the overlapping and complimentary expertise of the researchers in the areas of scalable parallel scientific computing, first-principles and atomistic calculations, computational thermodynamics, mesoscale microstructure evolution, and macroscopic mechanical property modeling. The main objective of the proposal is to develop a set of integrated computational tools to predict the relationships among the chemical, microstructural, and mechanical properties of multicomponent materials using technologically important aluminum-based alloys as model materials. A prototype GRID-enabled software will be developed for multicomponent materials design with efficient information exchange between design stages. Each design stage will incorporate effective algorithms and parallel computing schemes. Four computational components will be integrated, these are: (1) first-principles calculations to determine thermodynamic properties, lattice parameters, and kinetic data of unary, binary and ternary compounds; (2) CALPHAD data optimization computation to extract thermodynamic properties, lattice parameters, and kinetic data of multicomponent systems combining results from first-principles calculations and experimental data; (3) multicomponent phase-field modeling to produce microstructure; and (4) finite element analysis to obtain the mechanical response from the simulated microstructure. The research involves a parallel effort in information technology with two main components: (1) advanced discretization and parallel algorithms, and (2) a software architecture for distributed computing system. The first component includes: (a) a coupling of spectral and finite element approximations, (b) local adaptivity and multi-scale resolution, (c) high order stable semi-implicit in time schemes, (d) parallelization through domain decomposition, and (e) scalable sparse system solvers. The second component involves computational GRID-enabled software for the overall design process; this software architecture enables the use of geographically distributed high performance parallel computing resources to reduce application turnaround time while providing a flexible client-server interface that allows multiple design cycles to proceed.The research project will be integrated with education and training of graduate students in the broad area of computational science and engineering through the participation of students and the PIs in the "High Performance Computing Graduate Minor" offered through the Institute of High Performance Computing at The Pennsylvania State University. Existing programs at Penn State will be used to integrate undergraduates into the project.%%%This award is made under the Information Technology Research initiative and is funded jointly by the Division of Materials Research and the Advanced Computational Infrastructure Research Division.This collaborative research project involves two materials scientists, a computerscientist, a mathematician, and two physicists from academia, industry and a national laboratory. The project is a synergistic effort that leverages the overlapping and complimentary expertise of the researchers in the areas of scalable parallel scientific computing, first-principles and atomistic calculations, computational thermodynamics, mesoscale microstructure evolution, and macroscopic mechanical property modeling. The main objective of the proposal is to develop a set of integrated computational tools to predict the relationships among the chemical, microstructural and mechanical properties of multicomponent materials using technologically important aluminum-based alloys as model materials. Prototype GRID-enabled software will be developed for multicomponent materials design. Effective algorithms and parallel computing schemes will be incorporated into the design. The GRID-enabled software allows geographically distributed high performance parallel computing resources to be harnessed bringing greater computational power to bear on a given problem and enabling practical application of these computational tools. The prototype software, with improved predictive power in multicomponent materials design, may enable scientists to develop new materials with unique properties and to tailor existing materials for better performance.The research project will be integrated with education and training of graduate students in the broad area of computational science and engineering through the participation of students and the PIs in the "High Performance Computing Graduate Minor" offered through the Institute of High Performance Computing at The Pennsylvania State University. Existing programs at Penn State will be used to integrate undergraduates into the project.***