Machine Learning based Prediction of Ditching Loads

arXiv:2402.10724v1 Announce Type: new
Abstract: We present approaches to predict dynamic ditching loads on aircraft fuselages using machine learning. The employed learning procedure is structured into two parts, the reconstruction of the spatial loads using a convolutional autoencoder (CAE) and the transient evolution of these loads in a subsequent part. Different CAE strategies are assessed and combined with either long short-term memory (LSTM) networks or Koopman-operator based methods to predict the transient behaviour. The training data is compiled by an …

abstract aircraft arxiv autoencoder cae cs.lg dynamic evolution machine machine learning part prediction spatial strategies type