Image driven deep learning method with FFT solver for predicting the microscale full field stress of stochastic boundary composites

Documenti analoghi

• Fast prediction of curing residual stress in polymer‐matrix composites by a deep learning method
  di: Fan Zhang, et al.
  Pubblicazione: (2025)
• Data‐driven machine learning regression methods to predict the residual strength in FRP composites subjected to fatigue
  di: Anand Gaurav
  Pubblicazione: (2025)
• Effect of boundary conditions on the low‐velocity impact damage mechanism of fiber metal laminate
  di: Huadong Wang, et al.
  Pubblicazione: (2024)
• Temperature field and curing degree prediction of large composite blades based on coupled finite element analysis and machine learning
  di: Yue Wu, et al.
  Pubblicazione: (2025)
• A novel framework to predict transversal and shear parameters of unidirectional composites by combining experimental, numerical and machine learning methods
  di: Siqi Cheng, et al.
  Pubblicazione: (2025)