Depth-sensing instrumented indentation with dual sharp indenters

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On the uniqueness of measuring elastoplastic properties from indentation: The indistinguishable mystical materials (2007, methodology): “Other variants of a are also commonly used in the indentation analyses (Futakawa et al., 2001; Bucaille et al., 2003; Chollacoop et al., 2003; DiCarlo et al., 2003; Cao and Lu, 2004a; Ogasawara et al., 2005), such as a 1⁄4 60 (Rockwell tip), a 1⁄4 63:14 (the cross-sectional area is half of that of t”
On the uniqueness and sensitivity of indentation testing of isotropic materials (2013, methodology): “Closely related to uniqueness is sensitivity to experimental er rors (Chollacoop et al., 2003; Lan and Venkatesh, 2007; Le, 2008; Hyun et al., 2011; Cao and Lu, 2004a,b; Swaddiwudhipong et al., 2005).”
Extraction of mechanical properties of materials through deep learning from instrumented indentation (2020, background): “The high sensitivity of traditional brute force calculations to solve the inverse indentation problem and the uncertainty inherent in such calculations in uniquely extracting elastoplastic properties from indentation responses are known to arise from functional nonlinearity (5, 6, 9).”