Landing load is important reference factor affecting the structural design and safety boundary of carrier-based aircraft. In the initial stage of design, the landing load is predicted by dynamic simulation, However, the simulation results cannot be verified by other methods. This paper analyzes the main factors affecting the landing load of carrier-based aircraft from the perspective of multi-body dynamics, Integrate the aircraft drop test data, a highly nonlinear prediction model based on radial basis neural network is established. The neural network model is trained by using the test data of multiple conditions and batches, And validate the model using data that has not participated in training, The results indicate that the interpolation prediction accuracy of the model on the test set is not less than 1%. This provides an effective method for predicting and analyzing the landing load of carrier based aircraft. It can be applied in load prediction of similar scenarios.


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    Title :

    Research and Application of Landing Load Prediction Method for Carrier-Based Aircraft


    Additional title:

    Lect.Notes Mechanical Engineering


    Contributors:
    Hou, Qiaoqiao (author) / Zeng, Jie (author) / Wang, Gang (author) / Yin, Wei (author)

    Conference:

    China Aeronautical Science and Technology Conference ; 2024 ; Chengdu, China September 19, 2024 - September 21, 2024



    Publication date :

    2025-03-23


    Size :

    10 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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