Physics based Prediction of Unexploded Ordnance Penetration in Granular Materials
Abstract
The present research report contains a combined analytical, numerical, and experimental methodology for the quantification of the maximum penetration depth of unexploded ordnance (UXO) into dry granular media at thermodynamic equilibrium under gravitational lithostatic stress states. Penetration into in-situ granular media is considered to be an unsteady state boundary-value problem that may refer to transient phenomena at a number of interrelated scales. These scales spanacross apparent contact areas of sub-microscopic and microscopic surface roughness, corresponding intragrain heterogeneous deformation and interparticle friction at grain scales, grain-scale damping and inertia in formation of force chains and corresponding particle rearrangement at continuum scales, and collective intergranular motion through semi-infinite domains.The research findings are presented for the proof-of-concept of proposed physics-based predictive methodology on highvelocityimpact and penetration of granular media at prototype scales, in relation to variational thermodynamic states at underlying scales, where mass densities (i.e., packing densities) under lithostatic stress states may vary with respect tocontrolled, gravitational packing processes. The results obtained from physical laboratory testing at various scales, including nano-indentation, measurement of surface energy, scanning electron and probe microscopies, grain-to-grain force-deformationin loading and unloading cycles, tri-axial compression, and prototype projectiles penetration into a granular material in ageotechnical centrifuge, are presented alongside a series of corresponding analytical and numerical models that have been implemented in a new soft-particle contact algorithm for the combined Finite-Discrete Element Method. The test data measured at the interrelated scales are used to benchmark corresponding grain-, continuum-, and system-scale discrete and finite element analysis models.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 2017
- Accession Number
- AD1036286
Entities
People
- A. Patil
- Adam Taylor
- Amirata Taghavi
- Jae H. Chung
- Kapya Ilay
- Michael Faraone
- Michael Stone
- Michael T. Davidson
- Nikhil Mishra
- Theodor Krauthammer
- Yu Zhang
Organizations
- University of Florida