Impact Resistance And Damage Identification Of Hybrid Fiber Reinforced Composites

The Hybrid Fiber Reinforced Polymer(HFRP)has the advantages of different fibers to achieve a unique hybrid effect.In addition to the characteristics of single fiber components,it can improve the defects of the component materials and reduce the overall costs.HFRP is commonly used in aerospace,automotive,and construction industries as it outperforms single fiber materials due to its blend of different fiber advantages.Carbon fiber,being a high-strength and lightweight material,is prone to brittle fractures and damage under impact loads,resulting in a sharp decline in strength.The Hybrid Fiber Reinforcement method seeks to improve the impact resistance of composite material by mixing more resilient fibers into the carbon fiber matrix.This method helps to prevent the occurrence of overall catastrophic failure in structures,which could otherwise arise from the failure of a single fiber material.The use of hybrid composites,featuring several reinforcement fibers in the same matrix,results in a progressive,rather than sudden,damage and failure.Nevertheless,given that the elastic modulus of different reinforcement fibers in the HFRP material varies,this may lead to different failure modes and different modulus layers,which may contribute to delamination.Therefore,this paper aims to study the impact resistance of carbon and aromatic fiber hybrid fiber composite materials,to analyze the impact response and damage modes of HFRP,and subsequently investigate the influence of HFRP’s internal damage on the structure’s vibration properties by examining how changes in vibration characteristics,such as natural frequency,could aid in damage identification for HFRP structures.This work will provide relevant theoretical and practical bases and references for the evolution of damage and non-destructive evaluation of HFRP structures.This paper examines Carbon-Aramid Hybrid Fiber Reinforced Polymer(C/AHFRP),a hybrid composite formed by blending T1000 ultra-high-strength carbon fibers and heterocyclic Aramid III fibers.Firstly,this paper investigates the tensile,impact and residual compression performance of carbon-aromatic fiber hybrid composites by analyzing external deformation and internal damage and failure modes using digital image correlation testing system(DIC)and ultrasonic C-scan technology,thereby examining the damage pattern and failure mechanism of layered hybrid composites in the impact process.Secondly,this paper conducts modal experiments to analyze the vibration characteristics of HFRP structures before and after the occurrence of delamination damage,creating and validating finite element simulation models to investigate the influence of different damage parameters on the frequency changes of HFRP structures.Finally,we construct an artificial neural network(ANN)and genetic algorithm(GA)with a surrogate model to identify the typical impact damage types of hybrid fiber composite structures – delamination(interface,location,and size)-based on the changes in vibrational frequency.Furthermore,numerical and experimental validations of two inverse intelligent algorithms ANN and SAGA were conducted to prove and compare their damage identification accuracy and efficiency.Low-velocity impact tests show that hybrid structures containing Aramid fibers demonstrate excellent impact resistance,and the blend of Aramid fibers increases the damage resistance of carbon fiber composites.The carbon-Aramid hybrid fibers also exhibit a beneficial hybrid effect under impact loading.Ultrasonic non-destructive testing reveals that delamination is the main form of impact damage in carbon-Aramid hybrid fiber composite materials.Modal analysis results show that when the delamination is located closer to the midplane of structures or the delamination is larger,the frequencies are lower,indicating that the influence of internal delamination is greater on the structure’s stiffness..The experimental modal results and simulation findings are in good agreement.The numerical and experimental verification results suggest that,compared with the damage location,both ANN and the GA with a surrogate model have greater accuracy in predicting damage size.The SAGA prediction error is within 1.68%,higher than the ANN prediction error of 2.17%,with an overlap rate of predicted damage and real damage exceeding 88%.The comparison of the ANN and SAGA prediction results through experimental validation indicates that SAGA has higher prediction accuracy than ANN,with a prediction error of 3.84% compared to3.92% for ANN.Therefore,GA should be the primary choice for damage prediction in the damage identification of HFRP beams,to achieve the best identification effect and prediction accuracy.