CDS&E: Optimal control of material microstructure evolution via massively parallel computing

CDS

基本信息

批准号：
1802867
负责人：
Michael Demkowicz
金额：
$ 91.42万
依托单位：
Texas A&M Engineering Experiment Station
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-01 至 2022-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1802867&HistoricalAwards=false
关键词：
CDS&amp Optimal control material microstructure

项目摘要

NONTECHNICAL SUMMARYThis award supports interdisciplinary computational research and education aimed to advance understanding and control of the microstructure of materials. Some important properties of materials, such as mechanical strength or corrosion susceptibility, are largely a function of microstructure: the sizes, shapes, and arrangement of material constituents, for example grains in polycrystals, over distances of micrometers. Despite the importance of microstructure, techniques for synthesizing and processing materials to obtain desired microstructures, and therefore desired materials properties, remain limited. Understanding how microstructure evolves in time as a material is made remains a fundamental challenge and the susceptibility of microstructure evolution to external control is nearly unexplored. This project investigates the fundamental physical characteristics that make microstructure evolution amenable to external control and explores novel pathways for creating designer microstructures through incorporation of materials modeling, real-time feedback, and control into material processing. This work will close a deep knowledge gap concerning the fundamental limits of microstructure controllability, thereby laying the foundation for the systematic control of microstructure evolution. "Controllability" itself will be a fundamental physical property emerging from the mechanisms that govern microstructure evolution. The computational tools and fundamental insights provided by this project will guide future development of microstructure controllers to be used in specific materials processing applications. The computational aspects of this project are extremely demanding and will require the full power of exascale computers: ones that perform 1 billion billion floating point operations per second. A major part of this project is therefore to efficiently parallelize nearly every stage of computation.TECHNICAL SUMMARYThis award supports interdisciplinary computational research and education aimed to advance understanding and control of the microstructure of materials. While much effort has been invested into the design, discovery, and optimization of new materials, optimal control of materials processing is relatively less well understood. In particular, the fundamental physical characteristics of an evolving microstructure that determine the degree of susceptibility to external control remain unexplored. This project will lay the foundations for material microstructure control by: a) designing microstructure-sensitive feedback controllers, b) developing computational tools for efficient implementation of feedback control, and c) systematically exploring feedback controller performance with respect to metrics such as objective fidelity, energy-efficiency, and cost-optimality. This work lies at the intersection of control theory, materials modeling, and high-performance computing. Ultimately, the researchers aim to create optimal controllers for the synthesis of designer materials by exploiting massively parallel, high performance computing architectures to explore fundamental questions of controllability in materials processing, such as: How does one optimally control materials processing parameters to make designer microstructures? What are the limits to the types of microstructures that may be made using a given processing method? What are the minimal requirements for a processing method to be able to synthesize a given type of microstructure?This work will explore the fundamental limits of materials microstructure controllability using the tools of control theory: the branch of engineering that creates optimal algorithms for the autonomous operation of vehicles, aircraft, and robots. To enable rapid investigation of this new field, the project will use computational materials models as surrogates for physical materials. The goal is to develop model-agnostic control tools that are transferrable between different models. However, effort will initially focus on one specific model problem, namely: phase field models of microstructure evolution as governed by the Allen-Cahn equation. Since the control methods to be developed will be sufficiently general that they can be used with other materials models.This award is jointly supported by the Condensed Matter and Materials Theory Program in the Division of Materials Research in the Directorate for Mathematical and Physical Sciences, the Civil, Mechanical and Manufacturing Innovation Division in the Engineering Directorate, and the Software and Hardware Foundations Program in the Division of Computing and Communications Foundations in the Directorate for Computer and Information Science and Engineering.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

非技术摘要这一奖项支持跨学科的计算研究和教育，旨在提高对材料微观结构的理解和控制。材料的一些重要特性，例如机械强度或腐蚀敏感性，主要是微观结构的函数：材料成分的尺寸，形状和排列，例如多晶的晶粒，超过微米的距离。尽管微观结构很重要，但对于获得所需的微观结构并因此所需的材料特性的合成和加工材料的技术仍然有限。了解微观结构如何随着材料的及时发展仍然是一个基本挑战，并且几乎没有探索微观结构演变对外部控制的敏感性。该项目调查了使微观结构演变适合外部控制的基本物理特征，并探索了通过融合材料建模，实时反馈和控制材料处理的新型途径来创建设计师微观结构。这项工作将缩小有关微观结构可控性的基本限制的深刻知识差距，从而为微观结构演化的系统控制奠定了基础。 “可控性”本身将是控制微观结构演变的机制的基本物理特性。该项目提供的计算工具和基本见解将指导用于特定材料处理应用程序中的微观结构控制器的未来开发。该项目的计算方面非常苛刻，将需要Exascale计算机的全部功能：每秒执行10亿亿卢比的浮点操作。因此，该项目的主要部分是有效地平行几乎每个计算阶段。尽管已经将大量精力投入到新材料的设计，发现和优化中，但对材料处理的最佳控制却相对较少。特别是，确定外部控制易感程度的不断发展的微观结构的基本物理特征仍未得到探索。该项目将通过以下方式为材料微结构控制奠定基础：a）设计对微观结构敏感的反馈控制器，b）开发用于有效实施反馈控制的计算工具，以及c）系统地探索反馈控制器在客观的忠诚，能量效率，能量效率和成本上的衡量指标中的性能。这项工作在于控制理论，材料建模和高性能计算的交集。最终，研究人员旨在通过利用大规模平行，高性能计算体系结构来探讨材料处理中可控性的基本问题，例如：如何最佳控制材料处理参数以使设计人员的微结构？使用给定处理方法可以制造的微观结构类型的限制是什么？处理方法可以使用控制理论的工具：工程学的分支，为车辆，飞机和机器人的自主操作创造了最佳的工程算法，这项工作将使处理方法合成给定类型的微观结构的最小要求？为了迅速研究这个新领域，该项目将使用计算材料模型作为物理材料的替代物。目标是开发可在不同模型之间转移的模型 - 不足控制工具。但是，努力最初将集中在一个特定的模型问题上，即：由Allen-Cahn方程控制的微观结构演化的相位场模型。由于要开发的控制方法将足够笼统地与其他材料模型一起使用。该奖项由在数学和物理科学局材料研究局的凝结物质和材料理论计划共同支持，民用，机械和制造创新局在工程局中，以及计算机和硬件基础，在计算机和硬件基础中，该计划在计算机上以及计算机的基础，并在计算机上进行了范围，并在计算机和硬件基础中进行了研究。反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准来评估值得支持。