Integrated manufacturing of REciclable multi-material COmposites for the TRANSport sector
Predictive modeling of jute?polyester composite tubes for impact performance: A comprehensive finite element analysis approach
The research paper focuses on the development of accurate modeling techniques using LS?DYNA/Explicit to predict the force–displacement behaviors and failures of jute?polyester composite tubes under both static and dynamic loading conditions. Experimental tests validate the model's accuracy, with the Gross Correlation Index (GCI) ranging from 0.83 to 0.97, demonstrating strong agreement and confirming the reliability of the finite element model. These validated modeling procedures provide valuable insights for optimizing the design and performance of jute?polyester composites, offering sustainable material solutions for automotive interior trim applications.This paper examines the feasibility of utilizing jute?polyester composites as a substitute for glass fiber composites in demanding automotive impact protection. Further, the study focuses on developing accurate modeling procedures using LS?DYNA explicit finite element analysis to predict the load–displacement responses and failures of jute?polyester (JP) composite tubes under static and dynamic loading. Experimental tests validate the model, comparing numerical and experimental results using the Gross Correlation Index (GCI). The GCI ranged from a minimum of 0.83 to a maximum of 0.97. Strong agreement is observed, confirming the reliability of the developed finite element (FE) model. The validated modeling procedures offer insights for optimizing the design and performance of jute?polyester composites, promoting sustainable materials in the automotive sector, particularly for applications related to vehicle interior trims.HighlightsJP composite tubes studied under axial and transverse impact loadsDeveloped accurate modeling procedure using LS?DYNAFE model validated through experimental test resultsGCI used to compare numerical and experimental resultsSuccessful prediction of failure modes and impact parameters
» Publication Date: 08/11/2023
This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement Nº 768737
