Coupled thermal-electrical–mechanical characteristics of lightning damage in woven composite honeycomb sandwich structures

• A sequentially coupled electrical-thermal–mechanical model incorporating dielectric breakdown of materials is developed to simulate the lightning-induced ablation damages, mechanical damages and delamination on W-CHSPs. • The ablation damage process and impact damage process of W-CHSP subjected to lightning strikes are simulated by the electrical-thermal–mechanical coupling model, respectively. • The proposed thermal-electrical–mechanical model shows improved predictive accuracy for assessing lightning damage compared to the thermal-electrical coupling model. • The thicker the honeycomb, the lesser the extent of lightning damage to the honeycomb core, while the damage to the upper and lower panels remains almost unaffected by the honeycomb thickness. In this study, lightning strike damage of woven carbon fibre-reinforced polymer laminates (W-CFRPs) and woven composite honeycomb sandwich panels (W-CHSPs) are simulated using the proposed sequential thermal-electrical–mechanical finite element (FE) coupling model incorporating dielectric breakdown of materials. Surface current with an amplitude of 200 kA and corresponding lightning shockwave overpressure were applied on each composite. The FE model coupled with LaRC05 criterion was used to study the failure behaviours of intralaminar damage and interlaminar delamination of the W-CFRPs and W-CHSPs. A series of lightning strike tests were performed to validate the FE model. Detailed lightning damage assessments and mechanisms were characterized by a combination of visual inspection, image processing, ultrasonic scanning and micro computed tomography (Micro-CT) and showed good agreements with the FE-predicted results. It can be concluded that shockwave overpressure significantly impacts lightning-induced damages, thereby supporting the effectiveness of the newly proposed sequential thermal-electrical–mechanical coupling model, which demonstrates improved predictive accuracy.