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清华大学材料科学与工程研究院《材料科学论坛》:Adaptive Nanophotonics by Novel...
报告题目:
A big data-based statistical nanoindentation technique for extracting shale’s mechanical genes and beyond
 报告人:
Dr. Guoping Zhang
Dr. Guoping Zhang, Associate Professor
University of Massachusetts Amherst, USA.
报告时间:
2017-06-23 14:30
报告地点:
李兆基科技大楼A260会议室
主办单位:
热能系
  简介:
讲演者简介:
Dr. Guoping Zhang(张国平) was graduated at the Department of Hydraulic Engineering of Tsinghua University, and got the Bachelor degree and Master degree in 1991 and 1994. He got PH.D. degree majoring in Geotechnical & Geoenvironmental Engineering from Massachusetts Institute of Technology in 2002. He once was an associate professor in Louisiana State University, USA. From 2013, he is an associate professor in University of Massachusetts Amherst, USA.
 
报告摘要:
Shales represent one of the most complex composites found in nature, and the safe and economical recovery of oil and gas from shale formations requires thorough understanding of the mechanical, geophysical, and hydraulic properties of shales. This seminar presents the latest state-of-the-art nanomechanical testing technique for characterization of shales. Grid nanoindentation testing with Continuous Stiffness Measurement (CSM) method was employed to obtain massive data sets (i.e., big data) on the load-depth response of shales to indentation depths of up to 8000 nm. The depth-dependent data were then analyzed statistically at specified depths to extract the Young’s modulus and hardness at pertinent depths. A new data analytics method was then developed to process the data by considering the finite-sized indents and the surrounding effects, given that shales are multi-phase, multi-scale composites consisting of solid particles with sizes ranging from tens of nanometers to hundreds of micrometers as well as voids and organic. With the new data analytics, a series of physical and mechanical properties of shales was obtained, including: (1) the number of phases in the parent shale; (2) the volumetric fraction of each phase; (3) the mechanical properties (e.g., Young’s modulus and hardness) of each phase; and (4) the mechanical properties of the bulk shale as a composite. Moreover, data can also provide viable guidance for selecting appropriate indentation test parameters (e.g., indentation depth) for the determination of mechanical properties of certain individual phases (e.g., clay matrix, bulk shale). At the end, future applications of this big data-based nanoindentation technique to other composite materials (e.g., cement, concrete) as well as shale softening and hydraulic fracturing are discussed.
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