Machine Learning Prediction of Lightning Damage to Aircraft

Lightning can cause physical damage to the aircraft structure, including the wings, nose cone, and other components. This damage can compromise the structural integrity of the aircraft and pose a serious risk to passenger safety. In addition, it can cause electromagnetic interference that can disrupt communications, navigation, and other essential systems that are critical for safe flight.  To better understand the impact of lightning strikes on aircraft, a dataset of more than 300 such events has been collected and analysed. The dataset mainly covers Scandinavia and North Europe in the period from 2021 to 2024. The lightning data come from the regional lightning detection networks operated by the Norwegian, Finish, and Danish Meteorologic Institutes.  The dataset has been used to train a Machine Learning model for lightning damage assessment in close cooperation with Scandinavian Airlines. The model shows high prediction accuracy for all known types of lightning strikes to airplanes. The dataset will be available for interested researchers.  Overall, this research advances understanding of the phenomenon and can aid in developing strategies to mitigate the risk of lightning strikes and ensure safe air transportation.