Prediction of Deformation of Hexagonal Honeycomb Blast Structure Under Explosive Loading Using Deep Learning
Year: 2024
Type: article
Abstract: Honeycomb composites are widely used in blast structure under explosive loading because of mechanical properties. The simulation of high-pressure explosion is time consuming in order to simulate an important number of scenarios. New deep learning neural models might approximate results with low computational resources outputting the result very fast. The purpose of this study is to propose using deep learning model using a relative low amount of training fata to approximate deformation in honeycomb structures subjected to a blast load. This study employed variation of hexagonal honeycomb dimensions to determine the deformation using deep learning model.
Authors: Mihaela MARIN, Florin-Bogdan MARIN
Institution: "Dunarea de Jos" University of Galati
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4407548991