题目：材料的多尺度建模:高性能计算、数据科学和不确定性量化

Multiscale modelling of materials: computing, data science, and uncertainty quantification

时间：2022年03月25日周五16：00－17：00

地点：腾讯会议 ID：93382698531

腾讯直播间：https://meeting.tencent.com/l/hA1SrLFrwFwl

报告人：刘布日格德（剑桥大学 工程系）

欢迎广大师生参加！

                                      土木与交通学院

                                                                                                                    2022年3月23日

报告人简介：

刘布日格德目前是剑桥大学工程学院Granta Design冠名助理教授。刘教授于2019年获得剑桥大学工程学博士学位，之后到瑞士苏黎世联邦理工学院机械与制造工程系(2019)和加州理工学院机械与土木工程系(2019-2021)进行博士后研究工作。刘博士的研究领域包括基于数据驱动的力学、材料不确定性量化、金属、复合材料和力学超材料的微观力学研究，以及函数空间学习方法。

Burgiede Liu is Granta Design Assistant Professor at the University of Cambridge. He received his Ph.D. in Engineering at University of Cambridge in 2019. He was a postdoc in Department of Mechanical and Process Engineering at ETH Zruch (2019) and a postdoctoral fellow in Mechanical and Civil Engineering at California Institute of Technology (2019-2021). Dr Liu's research interest includes data-driven mechanics; uncertainty quantification of materials; micro-mechanics of metals, composites and mechanical meta-materials as well as function space learning method.

报告摘要：

近几十年来，大量研究者热衷于开发针对特定应用场景的新材料结构。具体应用所需的性能取决于特定的材料系统，该系统能够通过加工其基础微观结构来优化性能。通过对材料特征详细地描述，并在系统层级下使用该特征以及基本物理原理进行模拟与优化，设计出具有定制化属性的结构。材料的多尺度建模、高通量实验、大型材料数据库、拓扑优化和其他方法推动了这类研究。尽管如此，大变形、高应变率和高温等极端应用场景下开发材料仍然是一项挑战。本次讲座将回顾一些能够加速设计特定应用材料的方法。

The recent decades have seen various attempts at accelerating the process of developing materials/structures targeted towards specific applications. The performance required for a particular application leads to the choice of a particular material system whose properties are optimized by manipulating its underlying microstructure through processing. The specific configuration of the structure is then designed by characterizing the material in detail, and using this characterization along with physical principles in system level simulations and optimization. These have been advanced by multiscale modelling of materials, high-throughput experimentations, materials data-bases, topology optimization and other ideas. Still, developing materials for extreme applications involving large deformation, high strain rates and high temperatures remains a challenge. This talk reviews a number of recent methods that advance the goal of designing materials targeted by specific applications.