New procedure to determine steel mechanical parameters from the spherical indentation technique

Nayebi, A.; Abdi, R. El; Bartier, Olivier; Mauvoisin, Gérard

doi:10.1016/s0167-6636(02)00113-8

Cited by 106 publications

(49 citation statements)

References 17 publications

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“…Presently, there are several proposed methods [177][178][179][180][181][182][183][184][185][186][187][188][189][190][191][192] for estimating stress-strain relationships from spherical indentation load-displacement curves using such optimization and statistical techniques as response surfaces, Kalman filters, and neural networks. Using these methods, a set of values of E, Y, n; and n may be identified so that the calculated load-displacement curves match that of experimentally measured ones.…”

Section: Probing Stress-strain Relationshipsmentioning

confidence: 99%

Scaling, dimensional analysis, and indentation measurements

Cheng

2004

Materials Science and Engineering: R: Reports

943

512

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We provide an overview of the basic concepts of scaling and dimensional analysis, followed by a review of some of the recent work on applying these concepts to modeling instrumented indentation measurements. Specifically, we examine conical and pyramidal indentation in elastic-plastic solids with power-law workhardening, in power-law creep solids, and in linear viscoelastic materials. We show that the scaling approach to indentation modeling provides new insights into several basic questions in instrumented indentation, including, what information is contained in the indentation load-displacement curves? How does hardness depend on the mechanical properties and indenter geometry? What are the factors determining piling-up and sinking-in of surface profiles around indents? Can stress-strain relationships be obtained from indentation load-displacement curves? How to measure time dependent mechanical properties from indentation? How to detect or confirm indentation size effects? The scaling approach also helps organize knowledge and provides a framework for bridging micro-and macroscales. We hope that this review will accomplish two purposes: (1) introducing the basic concepts of scaling and dimensional analysis to materials scientists and engineers, and (2) providing a better understanding of instrumented indentation measurements. # 2004 Published by Elsevier B.V.

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Section: Probing Stress-strain Relationshipsmentioning

confidence: 99%

Scaling, dimensional analysis, and indentation measurements

Cheng

2004

Materials Science and Engineering: R: Reports

943

512

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“…Researchers have used the slope of the P-h curve during loading process to estimate plastic flow properties and deduced the Young Modulus from the unloading slope [4,5].…”

Section: Introductionmentioning

confidence: 99%

An Alternative Approach to Determine Material Characteristics Using Spherical Indentation and Neural Networks for Bulk Metals

Mahmoudi

Nourbakhsh

Amali

2012

Journal of Testing and Evaluation

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Material characteristics such as Young modulus, yield, and ultimate stresses are often considered as fundamental material parameters. Determination of material characteristics using the instrumented indentation test has gained interest among many researchers. The output of a spherical indentation test is usually the load-penetration (P-h) curve which is used to determine the Hollomon’s equation coefficients. Ideally, the elastic deformation of the sphere is to be excluded from the total displacement. However, the available techniques to omit the elastic deformation of the sphere are difficult-to-use and time consuming. In the present work, a noticeably simplified method is proposed to determine the load-displacement curve, preserving the required accuracy. The coefficients of Hollomon’s equation are then determined using the spherical indentation. The proposed method has also the ability to specify the unloading curve at each point of interest, even if the experimental data of the unloading procedure at that point is not available. Finally, by training a neural network and extracting the weights of its layers, an equation governing the network is presented explicitly. This expression makes the neural network easy to use. Furthermore, the proposed method is verified using the experimental results and method and experiment are shown to be in good agreement.

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“…Recently, it has been shown that, with a spherical indenter, plastic properties can be determined from a single loading curve. 18,19,23 By reviewing the spherical indentation methods that have been developed, [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] the five models selected for this study were those of Field and Swain, 14 Cao and Lu, 18 Zhao et al, 19 Lee, 11 and Jiang et al 23 Although there have certainly been many more studies performed on this topic, these five were selected for three reasons. First, they can be simply reproduced step by step according to only the procedures provided by the original literature; second, they offer a means of identifying the plastic properties solely by analyzing the load-depth data (that is, they do not rely on the physical measurement of residual impression); third, they are easy to implement experimentally (no difficulty is caused by repetitive loading and unloading, and only a small number of empirical parameters are used).…”

Section: Introductionmentioning

confidence: 99%

Numerical verification for instrumented spherical indentation techniques in determining the plastic properties of materials

et al. 2009

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Instrumented indentation tests have been widely adopted for elastic modulus determination. Recently, a number of indentation-based methods for plastic properties characterization have been proposed, and rigorous verification is absolutely necessary for their wide application. In view of the advantages of spherical indentation compared with conical indentation in determining plastic properties, this study mainly concerns verification of spherical indentation methods. Five convenient and simple models were selected for this purpose, and numerical experiments for a wide range of materials are carried out to identify their accuracy and sensitivity characteristics. The verification results show that four of these five methods can give relatively accurate and stable results within a certain material domain, which is defined as their validity range and has been summarized for each method.

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New procedure to determine steel mechanical parameters from the spherical indentation technique

Cited by 106 publications

References 17 publications

Scaling, dimensional analysis, and indentation measurements

Scaling, dimensional analysis, and indentation measurements

An Alternative Approach to Determine Material Characteristics Using Spherical Indentation and Neural Networks for Bulk Metals

Numerical verification for instrumented spherical indentation techniques in determining the plastic properties of materials

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