Use of Artificial Neural Networks to Optimize Stacking Sequence in UHMWPE Protections.

Jairo Peinado,Liu Jiao-Wang,Álvaro Olmedo,Carlos Santiuste

doi:10.3390/polym13071012

Jairo Peinado, Liu Jiao-Wang + Show 2 more

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https://doi.org/10.3390/polym13071012

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Journal: Polymers	Publication Date: Mar 25, 2021
Citations: 4	License type: CC BY 4.0

Affiliation: Carlos III University of Madrid

Abstract

The aim of the present work is to provide a methodology to evaluate the influence of stacking sequence on the ballistic performance of ultra-high molecular weight polyethylene (UHMWPE) protections. The proposed methodology is based on the combination of experimental tests, numerical modelling, and Artificial Neural Networks (ANN). High-velocity impact experimental tests were conducted to validate the numerical model. The validated Finite Element Method (FEM) model was used to provide data to train and to validate the ANN. Finally, the ANN was used to find the best stacking sequence combining layers of three UHMWPE materials with different qualities. The results showed that the three UHMWPE materials can be properly combined to provide a solution with a better ballistic performance than using only the material with highest quality. These results imply that costs can be reduced increasing the ballistic limit of the UHMWPE protections. When the weight ratios of the three materials remain constant, the optimal results occur when the highest-performance material is placed in the back face. Furthermore, ANN simulation showed that the optimal results occur when the weight ratio of the highest-performance material is 79.2%.

Highlights

In the global industry, ultra-high molecular weight polyethylene (UHMWPE) fibers are the leading high-performance fibers and widely used in armor applications
The maximum ballistic limit is 513.1 m/s and the minimum 463.3 m/s, differences of 10.7% can be found in laminates with the sam12e omf a2t0erials and the proper stacking sequence can significantly improve the ballistic performance of the UHMWPE panel
A methodology that combines experimental tests, Finite Element Method (FEM) modelling and Artificial Neural Networks (ANN) simulation, is validated to evaluate the ballistic performance of 361 stacking sequences formed by three different UHMWPE materials

Summary

Introduction

Ultra-high molecular weight polyethylene (UHMWPE) fibers are the leading high-performance fibers and widely used in armor applications. These fibers show great resistance against impact or blast loads being a promising alternative for aramids in armor products [1,2,3,4,5,6,7]. Czechowski et al [8] compared aramid with UHMWPE (Dyneema) composites conducting a rigorously study including tensile, hardness, bending and delamination test. The prediction of ballistic limit and back face signature under high velocity impacts are the main goals of FEM models when they are used to model UHMWPE protections [14,15,16]. The number of configurations that can be analyzed with FEM models is limited due to the computational cost

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