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In situ measurement of damage evolution in shocked magnesium as a function of microstructure.

Brianna MacNiderDavid JonesJesse CallananMatt BeasonGeorge T GrayDana M DattelbaumNicholas BoechlerSaryu Fensin
Published in: Science advances (2023)
Accurate modeling and prediction of damage induced by dynamic loading in materials have long proved to be a difficult task. Examination of postmortem recovered samples cannot capture the time-dependent evolution of void nucleation and growth, and attempts at analytical models are hindered by the necessity to make simplifying assumptions, because of the lack of high-resolution, in situ, time-resolved experimental data. We use absorption contrast imaging to directly image the time evolution of spall damage in metals at ∼1.6-μm spatial resolution. We observe a dependence of void distribution and size on time and microstructure. The insights gained from these data can be used to validate and improve dynamic damage prediction models, which have the potential to lead to the design of superior damage-resistant materials.
Keyphrases
  • high resolution
  • oxidative stress
  • electronic health record
  • white matter
  • magnetic resonance
  • big data
  • magnetic resonance imaging
  • machine learning
  • deep learning
  • human health
  • drinking water
  • liquid chromatography