Data‐driven machine learning regression methods to predict the residual strength in FRP composites subjected to fatigue

Documents similaires

• Fast prediction of curing residual stress in polymer‐matrix composites by a deep learning method
  par: Fan Zhang, et autres
  Publié: (2025)
• Development of machine learning models for the prediction of erosion wear of hybrid composites
  par: Sourav Kumar Mahapatra, et autres
  Publié: (2024)
• A novel framework to predict transversal and shear parameters of unidirectional composites by combining experimental, numerical and machine learning methods
  par: Siqi Cheng, et autres
  Publié: (2025)
• Integrating machine learning and digital twin for strength prediction of CFRP/aluminum adhesive joints under hygrothermal conditions
  par: Noor Hadi Aysa, et autres
  Publié: (2025)
• Image driven deep learning method with FFT solver for predicting the microscale full field stress of stochastic boundary composites
  par: Yong Liao, et autres
  Publié: (2024)