气候变化领域集成服务门户(CCPortal): Knowledge extraction and transfer in data-driven fracture mechanics

CCPortal

DOI	10.1073/pnas.2104765118
	Knowledge extraction and transfer in data-driven fracture mechanics
	Liu X.; Athanasiou C.E.; Padture N.P.; Sheldon B.W.; Gao H.
发表日期	2021
ISSN	0027-8424
卷号	118 期号:23
英文摘要	Data-driven approaches promise to usher in a new phase of development in fracture mechanics, but very little is currently known about how data-driven knowledge extraction and transfer can be accomplished in this field. As in many other fields, data scarcity presents a major challenge for knowledge extraction, and knowledge transfer among different fracture problems remains largely unexplored. Here, a data-driven framework for knowledge extraction with rigorous metrics for accuracy assessments is proposed and demonstrated through a nontrivial linear elastic fracture mechanics problem encountered in small-scale toughness measurements. It is shown that a tailored active learning method enables accurate knowledge extraction even in a data-limited regime. The viability of knowledge transfer is demonstrated through mining the hidden connection between the selected three-dimensional benchmark problem and a well-established auxiliary two-dimensional problem. The combination of data-driven knowledge extraction and transfer is expected to have transformative impact in this field over the coming decades. © 2021 National Academy of Sciences. All rights reserved.
英文关键词	Fracture mechanics; Fracture toughness; Machine learning; Transfer learning
语种	英语
来源期刊	Proceedings of the National Academy of Sciences of the United States of America
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/238535
作者单位	School of Engineering, Brown University, Providence, RI 02912, United States; School of Mechanical and Aerospace Engineering, College of Engineering, Nanyang Technological University, Singapore, 639798, Singapore; Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore, 138632, Singapore
推荐引用方式 GB/T 7714	Liu X.,Athanasiou C.E.,Padture N.P.,et al. Knowledge extraction and transfer in data-driven fracture mechanics[J],2021,118(23).
APA	Liu X.,Athanasiou C.E.,Padture N.P.,Sheldon B.W.,&Gao H..(2021).Knowledge extraction and transfer in data-driven fracture mechanics.Proceedings of the National Academy of Sciences of the United States of America,118(23).
MLA	Liu X.,et al."Knowledge extraction and transfer in data-driven fracture mechanics".Proceedings of the National Academy of Sciences of the United States of America 118.23(2021).