An Efficient Computational Platform for Simulations of Parachute and Other Deformable Structures in Turbulent Flow
Abstract
We propose an efficient and optimized computational platform for the simulation of parachute delivery system and other systems involving fluid and deformable surfaces. Our method is based on the dual-stiffness spring-mass model which we developed during the previous phase of the project funded by the ARO-BAA core grant W91INF-14-1-0428: "Robust and High Order Computational Methods for Parachute Air Delivery and MAV Systems". This model incorporates both the tensile stiffness and angular stiffness and conforms with the material s Young modulus and Poisson ratio; In this proposal for the next phase of the project, we propose the design, implementation and testing of several new algorithms to enhance the efficiency, robustness and parallelization of the computational platform established in the previous phase of the project. We propose an enhanced second order scheme for the spring-mass model through the least square method, a library of numerical procedures to perform fast and high quality folding of fabric surfaces, and optimizing the software so that it can compute efficiently on DOD s high performance supercomputers. In collaboration with Army scientists, we propose a verification and validation study of the parachute code, and to carry out predictive simulations of parachute inflation. We also propose to add bending energy to the current model to simulate the elastic foil and insect wings which will have potential applications to the Micro Air Vehicle (MAV) system. In comparison with the LS-DYNA code, our method is on a structured grid (except the surface) and easy to modularize and parallelize. The mathematical and numerical methods, and the computational geometry functions we develop in this proposed work will shed light on applications of other interface and moving boundary problems such as fluid interlace instabilities, phase transition problems, and other fluid-structure interaction problems.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 14, 2019
- Source ID
- W911NF1810346
Entities
People
- Xiaolin Li
Organizations
- Army Contracting Command
- Research Foundation for the State University of New York
- United States Army