Computational Multiresolution Mechanics of Solids and Structures

在不久的将来，一个集成的多尺度分析系统是设计可靠的工程结构以在预定寿命内维持恶劣环境条件的理想选择。为设计高强度、高韧性、长疲劳寿命和低重量材料，将发展一种克服传统方法局限性的多分辨率力学理论。该框架的主要特点有两个方面：可以根据关键的微观结构设计参数直接预测宏观尺度的性能和性能；并提供了微结构材料设计与产品设计制造之间的数学联系。社会效益：在材料工程中，与其随机发现材料并利用其性能，不如全面了解微观结构-性能关系。提出的多分辨率理论可以推动一系列先进的复合材料，包括多层材料和纳米纤维基复合材料。通过智能设计材料微观结构，可以设计和优化能源相关、工业和医疗应用的超轻、超强度、低磨损材料等新材料。可以为研究生和本科生以及公众提供关于材料设计和制造的良好教育机会。希望本科生对研究感兴趣，并鼓励他们继续攻读研究生课程。此外，预计这种新兴的方法将有效地转移到工业和政府实验室。

Computational Multiresolution Mechanics of Solids and Structures In the not too distant future, an integrated multiscale analysis system is desirable for the design of a reliable engineering structure to sustain harsh environmental conditions within a predetermined lifetime. A multiresolution mechanics theory that may overcome the limitations of conventional approaches will be developed for design of higher strength, toughness, extended fatigue life and lower weight materials. The key features of the proposed framework are two-fold: macroscale properties and performance could be predicted directly in terms of the key microstructure design parameters; and a mathematical link between microstructure materials design and product design and manufacture will be provided. Societal Benefits: In materials engineering, rather than randomly discovering materials and exploiting their properties, a comprehensive understanding of microstructure-property relationship is desirable. The proposed multiresolution theory could advance a range of advanced composite materials, including multilayer materials and nanofiber-matrix composites. By designing material microstructure intelligently, new materials such as super-lightweight, ultra-strength, low-wear materials for energy related, industrial, and medical applications alike could be designed and optimized. Wonderful opportunities of educating graduate and undergraduate students and the public about materials design and manufacturing could be created. It is hoped that the undergraduate students would be interested in research and they are encouraged to continue for postgraduate studies. In addition, it is expected that this emerging methodology will be effectively transfer to industry and government laboratories.