Optimizing 3D-Printable Hierarchical Materials for Shock and Projectile Impact Mitigation
Abstract
The goal of this two-year NEPTUNE project is to develop a new simulation-based optimization framework (i.e., algorithms and software) that allows hierarchical materials to be designed rationally for shock and projectile impact mitigation. Recent advances in three-dimensional (3D) printing have enabled the fabrication of a new class of polymeric and metallic materials with hierarchical structures, some of which (e.g., auxetics, brick-and-mortar, origami) have high potentials for impact mitigation. While the advantage of these materials can be roughly attributed to the cooperative deformation of repeated cells, the detailed structure-property relationship is complicated by the large number of variables that characterize the material#s structure and the highly nonlinear impact physics. Without closed-form design formulas, hierarchical materials are currently designed mainly by intuition (e.g., biomimicry), which hinders their adoption by the defense and commercial sectors. This project aims to enable goal-oriented, rational design of hierarchical materials through a combination of predictive impact simulation, numerical optimization, and machine learning. In this way, theexpensive laboratory and field impact tests required to populate the high-dimensional design space are replaced by physics-based simulations performed on supercomputers. The FIVER (FInite Volume method with Exact multi-material Riemann solvers) method developed by the PI and collaborators through previous ONR grants will be used to simulate the dynamic response (e.g., stress, deformation, andfailure) of hierarchical materials to impact loads from both underwater explosions and high-speed projectiles. A key advantage of FIVER is that it couples compressible fluid dynamics with nonlinear structural dynamics using an embedded boundary method, which allows it to resolve complex cell geometries and simulate both impact scenarios mentioned above. This project focuses on achieving the following three research and demonstration objectives.(1)Develop a simulation-based optimization framework by coupling the FIVER method implemented in the PI#s open-source research codes (M2C and Aero-S, in C++) with the genetic optimization algorithms implemented in Sandia#s open-source Dakota toolkit.(2)Calibrate and validate the simulation model by conducting impact and puncture experiments using an Instron 9450 drop tower (impact energy up to 1500J).(3)Demonstrate and assess the optimization framework by optimizing auxetic materials for Navy-specific impact mitigation, using the Tinkercliffs computer cluster at Virginia Tech (42,000 CPU cores).This project is at the intersection of two Critical Technology Areas identified in the 2023 DoD National Defense Science and Technology Strategy, namely Advanced Materials and Advanced Computing & Software. The delivery of the optimization framework to the defense sector will be facilitated by the PI#s collaborations with NUWC and NRL, and the entrepreneurial support from VT#s Link+Licence+Launch group. The transfer of technology to the commercial sector can be facilitated by a recent project with DynaSafe LLC (USA) that aimed to improve the design of explosion containment chambers. Up to five military and veteran students will be trained in impact physics,high-performance computing, and 3D printing, leveraging the large bodies of cadets at Virginia Tech (~1200) and in the Department of Aerospace and Ocean Engineering (~60).Approved for Public Release
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 08, 2024
- Source ID
- N000142412509
Entities
People
- Kevin G. Wang
Organizations
- Office of Naval Research
- United States Navy
- Virginia Tech