Grain Scale Interactions with Subterranean Structures: Material Removal Algorithms

Abstract

The primary objective of the project is to utilize XRCT and LS-DEM to investigate and understand grain scale interactions with subterranean structures and use the enhanced understanding and data to develop biologically inspired excavation algorithms. There are three major goals to achieve the primary objective: 1. Image ant tunnel networks before, during, and after construction with 3D XRCT 2. Utilize the XRCT images to gather force and position data on all grains with LS-DEM. 3. Develop excavation algorithms utilizing neural networks with the collected data.

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 06, 2018
Source ID
W911NF1710212

Entities

People

  • José E Andrade

Organizations

  • Army Contracting Command
  • California Institute of Technology
  • United States Army

Tags

Readers

  • Geotechnical Engineering.
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks