en Rolling Stock Rolling Stock پژوهشي Research <div style="text-align: justify;"><span style="font-size:11pt"><span style="text-justify:kashida"><span style="text-kashida:0%"><span style="line-height:normal"><span style="font-family:Calibri,sans-serif"><span style="font-size:10.0pt"><span new="" roman="" style="font-family:" times="">Given the significant role of the railway sector in transportation, railway managers and operators place great importance on traffic and maintenance costs. While existing track wayside monitoring systems can detect geometric defects in train wheels, like flats, they do not provide a severity assessment. To address this limitation, the WAY4SafeRail project aims to enhance rail safety by assessing the condition of train wheels. As an initial step in employing Artificial Intelligence Techniques, this paper presents a portion of the research conducted within the WAY4SafeRail project, specifically focusing on numerical simulations of wheel defects, in particular wheel flats. The proposed methodology has demonstrated its reliability and cost-effectiveness in identifying wheel defects.</span></span></span></span></span></span></span></div> &nbsp; Artificial intelligence, damage detection, wheel flat, train-track dynamic interaction, wayside condition monitoring 9 18 http://ijrare.iust.ac.ir/browse.php?a_code=A-10-280-1&slc_lang=en&sid=1 Araliya Mosleh amosleh@fe.up.pt 180031947532846002766 180031947532846002766 Yes CONSTRUCT – LESE, Faculty of Engineering, University of Porto, Porto, Portugal Mohammadreza Mohammadi mohammadreza.mohammadi.sm@gmail.com 180031947532846002767 180031947532846002767 No CONSTRUCT – LESE, Faculty of Engineering, University of Porto, Porto, Portugal Cecília Vale cvale@fe.up.pt 180031947532846002768 180031947532846002768 No CONSTRUCT – LESE, Faculty of Engineering, University of Porto, Porto, Portugal Diogo Ribeiro drr@isep.ipp.pt 180031947532846002769 180031947532846002769 No CONSTRUCT – LESE, School of Engineering, Polytechnic of Porto, Porto, Portugal Pedro Montenegro paires@fe.up.pt 180031947532846002770 180031947532846002770 No CONSTRUCT – LESE, Faculty of Engineering, University of Porto, Porto, Portugal Andreia Meixedo ameixedo@fe.up.pt 180031947532846002771 180031947532846002771 No CONSTRUCT – LESE, Faculty of Engineering, University of Porto, Porto, Portugal