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- W2890813293 abstract "This work presents a methodology to calibrate a strength model for ductile metals, based on dynamic tension tests of relatively long Dog-Bone specimens conducted on a Split Hopkinson Tension Bar (SHTB). We address the main difficulties involved in conducting and interpreting such tests, namely the duration of the loading pulse needed to deform long specimens and the non-uniform stress and strain distributions along the specimen due to neck formation. The first issue is addressed by using the waves‘ reflections within the output bar, as explained below. When the first loading (tension) wave does not cause failure of the specimen, a reflected compression wave travels from the specimen‘s bar end to the free bar‘s end. Upon reaching the free end this latter compression wave is reflected again as a second tension wave, which travels back along the bar until it reaches the specimen and loads it the second time. This enables further deformation of the specimen, practically doubling the loading pulse duration without changing the striker‘s length. The second issue is addresses by using full numerical simulations of the experimental setup, including the striker, the bars and the specimen. This way, the full dynamic behaviour of the specimen is taken into account, eliminating the need to consider specimen equilibrium and taking into account the current strain rate in the specimen as it deforms. Hence, model calibration can be done from the very start of plastic deformation and without the need to keep the strain rate constant during deformation. As a result, it is possible to reliably calibrate the strength model considering necking and neck location, as well as plastic heating which is a significant factor in the plastic deformation of ductile metals." @default.
- W2890813293 created "2018-09-27" @default.
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- W2890813293 date "2018-01-01" @default.
- W2890813293 modified "2023-10-14" @default.
- W2890813293 title "Improving data interpretation from SHTB tests on ductile metals" @default.
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- W2890813293 doi "https://doi.org/10.1051/epjconf/201818301006" @default.
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