ITR: Computational Tools for Multicomponent Materials Design

ITR：多组分材料设计的计算工具

• 批准号: 0205232
• 负责人: Zi-Kui Liu
• 金额: $ 290万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0205232&HistoricalAwards=false
• 关键词: ITR; Computational; Tools; Multicomponent; Materials

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.***

该奖项是根据信息技术研究计划颁发的，由材料研究部和先进的计算基础设施研究部共同资助。该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Academia，Academia，工业和国家实验室的物理学家。该项目是一种协同的努力，它利用了研究人员在可扩展的平行科学计算，第一原理和原子计算，计算热力学，中尺度微观结构演化和巨镜机械性能建模领域的重叠和免费专业知识。该提案的主要目的是开发一组集成的计算工具，以使用基于技术重要的铝合金作为模型材料来预测多组分材料的化学，微结构和机械性能之间的关系。将开发具有原型网格的软件，用于多组分材料设计，并在设计阶段之间具有有效的信息交换。每个设计阶段将结合有效的算法和并行计算方案。将集成四个计算成分，这些组件是：（1）确定一部分，二元和三元化合物的热力学特性，晶格参数以及动力学数据的第一原理计算； （2）calphad数据优化计算，以提取多组分系统的热力学特性，晶格参数和动力学数据，结合了第一原理计算和实验数据的结果； （3）多组分相位场建模以产生微观结构； （4）有限元分析以从模拟微结构中获得机械响应。该研究涉及在信息技术方面的平行努力，其中有两个主要组成部分：（1）高级离散化和并行算法，以及（2）用于分布式计算系统的软件体系结构。第一个组件包括：（a）光谱和有限元近似值的耦合，（b）局部适应性和多尺度分辨率，（c）时间方案中的高阶稳定半无用，（d）通过域分解以及（e）可扩展的稀疏系统求解器并行化。第二个组件涉及为总体设计过程提供的计算网格软件。该软件体系结构能够使用地理分布的高性能平行计算资源来减少应用周转时间，同时提供允许多个设计周期进行的灵活的客户服务器接口。研究项目将与在计算机科学和工程中的广泛的学生和工程的培训相结合，并通过“高度培训”计算机来培训计算机科学和工程的培训。 大学。宾夕法尼亚州立大学的现有计划将用于将本科生整合到该项目中。%%;该奖项是在信息技术研究计划下颁发的，并由材料研究部和先进的计算基础设施研究部共同资助。该协作研究项目涉及两名材料科学家，计算机科学家，一项计算机科学家，一位数学家和两个物理学家。该项目是一种协同的努力，它利用了研究人员在可扩展的平行科学计算，第一原理和原子计算，计算热力学，中尺度微观结构演化和巨镜机械性能建模领域的重叠和免费专业知识。该提案的主要目的是开发一组集成的计算工具，以使用具有技术重要的基于铝的合金作为模型材料来预测多组分材料的化学，微结构和机械性能之间的关系。将为多组分材料设计开发基于网格的原型软件。有效的算法和并行计算方案将纳入设计。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，从而在给定的问题上实现更大的计算能力，并实现这些计算工具的实际应用。 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.宾夕法尼亚州的现有计划将用于将大学生纳入项目。***