Determination of plastic material properties by analysis of residual imprint geometry of indentation

Schmaling, B.; Hartmaier, Alexander

doi:10.1557/jmr.2012.212

Cited by 21 publications

(11 citation statements)

References 19 publications

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“…Another advantage of this choice is that no inplane rotation operation must be performed to align numerical and experimental data. The topology evaluation method of the present study is a further development of Schmaling and Hartmaier (2012). We noted, that the topology error was dominated by the correct match of the indentation depth, which could be enhanced by a weighting of positive and negative displacements in the error determination or by a limitation to positive displacement information.…”

Section: Discussionmentioning

confidence: 79%

Parameterization of a Non-local Crystal Plasticity Model for Tempered Lath Martensite Using Nanoindentation and Inverse Method

2019

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Section: Discussionmentioning

confidence: 79%

Parameterization of a Non-local Crystal Plasticity Model for Tempered Lath Martensite Using Nanoindentation and Inverse Method

2019

Self Cite

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“…This approach is similar to a previous study [54], in which FEA and AFM were combined in study of Rockwell indentation profiles on metal surfaces to infer material properties, in particular yield stress and work-hardening rate. As noted above, these inferred quantities need to be interpreted with some care, they are only representative in that they are consistent with the measured profiles, but the combined FEA-AFM approach clearly provides a method for determining material properties.…”

Section: Discussionmentioning

confidence: 87%

Assessing strain mapping by electron backscatter diffraction and confocal Raman microscopy using wedge-indented Si

et al. 2016

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The accuracy of electron backscatter diffraction (EBSD) and confocal Raman microscopy (CRM) for small-scale strain mapping are assessed using the multi-axial strain field surrounding a wedge indentation in Si as a test vehicle. The strain field is modeled using finite element analysis (FEA) that is adapted to the near-indentation surface profile measured by atomic force microscopy (AFM). The assessment consists of (1) direct experimental comparisons of strain and deformation and (2) comparisons in which the modeled strain field is used as an intermediate step. Direct experimental methods (1) consist of comparisons of surface elevation and gradient measured by AFM and EBSD and of Raman shifts measured and predicted by CRM and EBSD, respectively. Comparisons that utilize the combined FEA-AFM model (2) consist of predictions of distortion, strain, and rotation for comparison with EBSD measurements and predictions of Raman shift for comparison with CRM measurements. For both EBSD and CRM, convolution of measurements in depth-varying strain fields is considered. The interconnected comparisons suggest that EBSD was able to provide an accurate assessment of the wedge indentation deformation field to within the precision of the measurements, approximately 2 × 10−4 in strain. CRM was similarly precise, but was limited in accuracy to several times this value.

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“…Consequently, researchers used local measures, i.e. atom force microscopy (AFM) when using nanoindentation experiments (Zambaldi et al 2012;Schmaling and Hartmaier 2012). Other researchers have used local texture measures to verify crystal plasticity simulations (Pinna et al 2015).…”

Section: General Discussion Of the Frameworkmentioning

confidence: 99%

A framework for material calibration and deformation predictions applied to additive manufacturing of metals

Brinckmann

2019

Int J Fract

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Additive manufacturing of metals offers the possibility of net-shape production of topologies that are infeasible by conventional subtractive methods, e.g. milling. However, additive manufacturing of metals posses a high defect density, which necessitates accounting for the larger statistical material variation than in conventional metals. To prevent timeconsuming experimental component testing, computational methods are required that account for the topology and metal as well as that precisely predict component failure even for metals with statistically varying properties. Predictions require an automatic and modular evaluation of the possibly large set of material properties and their scatter by employing calibration experiments. In addition, a module for failure and deformation prediction as well as a module for the aggregation of experimental data are required. In this contribution, such a modular framework is presented and the encapsulated and non-structured storage of statistically varying material properties is highlighted. In addition, the framework includes multiple FEM solvers and a multitude of optimizers, which are compared and the objective function is addressed. The approach is employed for the third Sandia Fracture Challenge for which two configurations (homogeneous and heterogeneous material properties) are studied and discussed. The blind-predictions of the verification geom

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Determination of plastic material properties by analysis of residual imprint geometry of indentation

Abstract: Abstract

Cited by 21 publications

References 19 publications

Parameterization of a Non-local Crystal Plasticity Model for Tempered Lath Martensite Using Nanoindentation and Inverse Method

Parameterization of a Non-local Crystal Plasticity Model for Tempered Lath Martensite Using Nanoindentation and Inverse Method

Assessing strain mapping by electron backscatter diffraction and confocal Raman microscopy using wedge-indented Si

A framework for material calibration and deformation predictions applied to additive manufacturing of metals

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