Probing the properties and mechanisms of failure waves in soda-lime glass

Abstract

Soda-lime glass (SLG) and other silica glasses exhibit the failure wave phenomenon under shock compression. The mechanism responsible for this peculiar behavior of glasses is still unresolved. In this study, a series of plate impact experiments was performed at three different impact stresses of 6.4, 8.3, and 10.8 GPa to better understand the mechanisms underlying the failure wave phenomenon. Specifically, spall experiments were conducted to probe the speed and existence of failure waves at different stresses in SLG. A layered glass target was used to probe the possibility of a “renucleation” of the wave at the SLG–SLG interface. When it existed, the failure wave was inferred to propagate at a speed of 1.3 km/s. However, it was observed that the failure wave phenomenon ceases to exist for impact stresses higher than 10 GPa. In experiments with a 6.4 GPa impact stress, the peak free surface velocity was significantly less than what is predicted by stress-Hugoniot calculations. This velocity deficit and other important features of the measured free surface velocity profiles were simulated using finite element analysis by incorporating an abrupt densification of SLG at a critical stress in the equation of state. This densification feature is similar to what would be expected of a phase transition. Although unable to unambiguously reveal the mechanism causing the failure wave phenomenon, the results of the present work clearly indicate that the failure wave causes a secondary compression and densification in SLG.

Document Details

Document Type
Pub Defense Publication
Publication Date
May 11, 2021
Source ID
10.1063/5.0047950

Entities

People

  • Akshay Joshi
  • G. Ravichandran
  • Suraj Ravindran
  • Vatsa Gandhi

Organizations

  • California Institute of Technology
  • National Nuclear Security Administration
  • Office of Naval Research

Tags

Readers

  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Mechanical Engineering/Mechanics of Materials.
  • Surface Coatings Technology.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference