Abstract
The spherical indentation test has been successfully applied to inversely derive the tensile properties of small regions in a non-destructive way. Current inverse methods mainly rely on extensive iterative calculations, which yield a considerable computational costs. In this paper, a database method is proposed to determine tensile flow properties from a single indentation force-depth curves to avoid iterative simulations. Firstly, a database that contain numerous indentation force-depth curves is established by inputting varied Ludwic material parameters into the indentation finite elements model. Secondly, for a given experimental indentation curve, a mean square error (MSE) is designated to evaluate the deviation between the experimental curve and each curve in the database. Finally, the true stresses at a series of plastic strain can be acquired by analyzing these deviations. To validate this new method, three different steels, i.e. A508, 2.25Cr1Mo and 316L are selected. Both simulated indentation curves and experimental indentation curves are used as inputs of the database to inversely acquire the flow properties. The result indicates that the proposed approach provides impressive accuracy when simulated indentation curves are used, but is less accurate when experimental curves are used. This new method can derive tensile properties in a much higher efficiency compared with traditional inverse method and are therefore more adaptive to engineering application.
Highlights
Indentation technique is generally take as a non-destructive method with the advantage of local characterization
The results show that the simulated F-h curves, in general, agreed well with the corresponding experimental curves
5 Conclusions In the present study, a new approach was suggested for extraction of material uniaxial flow curves by employing a single spherical indentation test incorporated with the database
Summary
Indentation technique is generally take as a non-destructive method with the advantage of local characterization. Huang et al [19] employed the least-square difference between the experimental and simulated force-depth curve as the objective, and identified the materials parameters with a modified particle swarm algorithm (PSO) which increases the ability to obtain a global optimal solution. Note that these approaches have been widely reported, there are still several limitations. Extensive iterative simulations for each parameter identification are required and yield a considerable time and computational cost Another efficient inverse tool that are widely used is artificial neural networks (ANN) [24,25,26]. The true stress-plastic strain curves are structure-independent for the indentation and uniaxial tensile test
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