To predict the force-displacement responses of Carbon Fiber Reinforced Plastic (CFRP) thin-walled C-columns in the aircraft sub-cargo area under quasi-static axial crushing, an intelligent prediction model (WOA-BP-LSTM autoencoder model) integrating the Whale Optimization Algorithm (WOA), Back Propagation (BP) neural network, and Long Short-Term Memory (LSTM) autoencoder was proposed. The reliability of the finite element model of CFRP thin-walled C-columns was validated through quasi-static axial crushing tests, with axial crushing response evaluation indicators showing errors within 10%. A dataset comprising 700 force-displacement response samples with variable cross-sectional geometric parameters was constructed based on the model. The LSTM autoencoder was employed for dimensionality reduction and reconstruction of the force-displacement responses. Subsequently, the BP neural network was used for force-displacement responses prediction, with WOA optimizing the neural network parameters. The results show that the LSTM autoencoder achieved high-precision reconstruction of force-displacement responses, where the errors for initial peak crushing force and energy absorption in the test set were both less than 3%, and 80% of the samples had errors within 1%. The optimized prediction model significantly improved prediction accuracy, reducing the test set's Mean Absolute Error (MAE) by 17.55%, Mean Squared Error (MSE) by 31.77%, and Root Mean Squared Error (RMSE) by 17.47%. Prediction errors for the initial peak crushing force and energy absorption were both less than 8%, with 80% of samples showing errors within 5%. This model enables rapid and accurate prediction of axial crushing responses for variable cross-section CFRP thin-walled C-columns while reducing computational costs, providing an efficient parameter-performance mapping tool for the study of its axial crushing response.

To analyze the dynamic response of fuselage section and occupant injury under crash scenarios, the vertical drop test of typical fuselage section of large aircraft (including two sets of triple seats and four dummies) at 6.02 m/s was conducted. The crash response data of fuselage section and occupants were obtained, and the crash damage of fuselage section and occupant injury were analyzed, and the evaluation of aircraft crashworthiness was conducted through considering survivable volume, retention strength, occupant injury and emergency evacuation. The drop test results show that the sub-cabin floor structures suffer the serious deformation and damage, and three plastic hinges are generated in the sub-cargo middle supporting columns area and the connection areas between the both sides cabin supporting columns and fuselage frames. The cabin area is remained basically intact, and the survivable volume is maintained. The connections between the seats and the cabin floor guide rail are maintained in good condition, and the occupant seat belts are kept in place. The maximum value of head injury criterion is 31.47, and the maximum compressive load of occupant lumbar spine is 3 997.2 N. The dummies lean towards the aisle, and the occupant egress paths are maintained. The risk of occupant injury is relatively low at the vertical velocity of 6.02 m/s through conducting the aircraft crashworthiness evaluation.