Design and theoretical analysis of dynamic indentation experimental device

The article is devoted to modification of the impact devices of Leeb hardness testers for the implementation of the dynamic instrumented indentation method. The results obtained made it possible to construct a load–displacement curve using primary EMF signals and made it possible to determine the values of the dissipated and elastic impact body energy, the maximal load of indentation, the maximal and residual penetration depth and the geometric parameters of the indentation region, namely the contact area of the indenter with the surface and the volume of the displaced material. The listed parameters of the indentation process allow us to measure the contact and volume hardness, the elastic modulus and the yield strength of test objects with portable hardness testers.

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“…Research into and development of devices and methods of dynamic indentation were carried out by the authors of other works [22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Modification of the Leeb Impact Device for Measuring Hardness by the Dynamic Instrumented Indentation Method

et al. 2022

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“…Majzoobi and Pourolajal 1 proposed a new approach based on indentation test, simulation of indentation and optimization to predict the constants of Johnson-Cook model. Shenzhen et al 21 captured the load-displacement diagram from dynamic penetration test. In this research, the nano-scale penetration test was conducted using a split Hopkinson bar.…”

Section: Introductionmentioning

confidence: 99%

Determination of the parameters of material models using dynamic indentation test and artificial neural network

Pourolajal

Majzoobi

2022

The Journal of Strain Analysis for Engineering Design

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Stress-strain curves of materials normally change with strain rate and temperature and are normally defined by material models. In this study, a new technique was developed for determining the constants of material models. This technique was based on dynamic indentation test, numerical simulation using Ls-dyna code and artificial neural network. An indenter of tapered shape was shot against the materials as the target by a gas gun. The experiments were carried out for four strain rates and four temperatures. The target was made of pure copper. The penetration depth-time and load-time histories were captured by a LVDT and a piezoelectric load-cell, respectively and the load-penetration depth curve (P-h) was obtained. This curve is characterized by five parameters which are determined for each indentation test. On the other hand, the indentation test was simulated using Ls-dyna hydrocode. From the simulations, the P-h curves were obtained using Johnson-Cook (J-C) and Zerilli-Armstrong (Z-A) material models and the characterizing parameters of the numerical P-h curves were also identified. Finally, an artificial neural network (ANN) was trained by the numerical P-h curves parameters as the input and the constants of J-C and Z-A models as the output. The trained neural network was then tested by the experimental p-h curves parameters as the input and the constants of J-C and Z-A models as the output. Moreover, a number of dynamic compression tests were performed using the well-known Split Hopkinson Bar at the same strain rates and temperatures used for indentation tests and the stress-strain curves of material were obtained. A reasonable agreement was observed between the stress-strain curves predicted by neural network and the Split Hopkinson Bar. The proposed method does not need sophisticated instrumentation and in fact, the load-time and indentation depth-time histories are directly converted to stress-strain of material using an artificial neural network.

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Effect of strain rate on mechanical behavior of Sn0.3Ag0.7Cu solder at macro- and micro-scales

Niu

Geng

et al. 2020

J Mater Sci: Mater Electron

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Design and theoretical analysis of dynamic indentation experimental device

Cited by 3 publications

References 27 publications

Modification of the Leeb Impact Device for Measuring Hardness by the Dynamic Instrumented Indentation Method

Modification of the Leeb Impact Device for Measuring Hardness by the Dynamic Instrumented Indentation Method

Determination of the parameters of material models using dynamic indentation test and artificial neural network

Effect of strain rate on mechanical behavior of Sn0.3Ag0.7Cu solder at macro- and micro-scales

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