My Project
Machine Learning and Computational Modeling for Predicting the Deformation of Natural Fiber-Reinforced Polymer Composites in Bulletproof Material Prototyping
What happened here?
This research project was conducted in collaboration with my partner, Henry Galino, under the supervision of the Computer Vision and Machine Intelligence Laboratory at the UP Department of Computer Science, in partnership with the UP Department of Mining, Metallurgical, and Materials Engineering's AeroComp Project.
The objective was to explore the feasibility of using locally sourced natural fibers as alternatives or supplements to synthetic materials like Kevlar in ballistic armor. Our role involved utilizing data from both live-fire experiments and simulated impact tests to develop a machine learning model that could support the design and prototyping process . This model aims to significantly reduce the cost and time required for testing by enabling rapid digital evaluation of proposed ballistic plate designs before progressing to more detailed simulations and live-fire validation.produced data from live-fire tests together with simulated impact simulations to create a machine learning model to aid in the prototyping of these ballistic plates. Wherein using the ML model would allow for cheaper and most importantly quicker digital testing of proposed ballistic armor before moving on to higher fidelity simulation and finally live-fire testing.
Our resulting paper was presented at the Material Research Society of Japan's MRM-2023 in Kyoto, Japan
What did I use?
