Big Data Nanoindentation (BDNi) of Rocks: Concept, Theory, Data Analytics, and Applications

Date(s) - 12/06/2021
11:00 AM - 12:00 PM


Zoom Link:

Meeting ID: 972 8836 7341

Big Data Nanoindentation (BDNi) of Rocks: Concept, Theory, Data
Analytics, and Applications

Guoping Zhang
Department of Civil and Environmental Engineering
University of Massachusetts Amherst
Originally developed as a non-destructive experimental technique for probing the mechanical
properties (e.g., Young’s modulus, hardness, creep, and fracture toughness) of low-dimensional,
homogeneous, monolithic materials, nanoindentation, coupled with statistical analysis, has
recently evolved under a strong momentum into characterizing heterogeneous, multiphase,
multiscale composites such as rocks, cements, and concretes. After a brief introduction to the
fundamental concepts of nanoindentation and pertinent underlying mechanics, the seminar
highlights the new advancements of a big data nanoindentation (BDNi) approach involving
acquiring massive depth- and size-dependent data via continuous stiffness measurement (CSM)
mode, followed by data analytics for processing massive, chaotic, highly scattered data (e.g.,
~2,000 Young’s modulus/hardness vs. depth curves) involving data segmentation, statistical
deconvolution, data re-integration, indentation surround effect, result extraction, and upscaling
modeling. As a result, the cross-scale characterization of the mechanical properties of multiphase,
multiscale composites, including the individual constituents at the nano/micro-scale and bulk
composite at the meso/macro-scale, is achieved via a single testing mode on a single, usually small
specimen. A few example applications of the BDNi are showcased at the end, including shale
softening, screening of hydrofracking fluid additives, and role of elastomers in oil well cementing.

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