75 citations · 156 across the 16 of their papers we have counts for
5 papers · 1 filter
I-FENN with DeepONets: accelerating simulations in coupled multiphysics problems
Fouad M. Amin, Diab W. Abueidda, Panos Pantidis +1
Coupled multiphysics simulations for high-dimensional, large-scale problems can be prohibitively expensive due to their computational demands. This article presents a novel framewo…
Time Resolution Independent Operator Learning
Diab W. Abueidda, Mbebo Nonna, Panos Pantidis +1
Accurately learning solution operators for time-dependent partial differential equations (PDEs) from sparse and irregular data remains a challenging task. Recurrent DeepONet extens…
Modified non-local damage model: resolving spurious damage evolution
Roshan Philip Saji, Panos Pantidis, Mostafa E. Mobasher
Accurate prediction of damage and fracture evolution is critical for the safety design and preventive maintenance of engineering structures, however existing computational methods…
Integrated Finite Element Neural Network (IFENN) for Phase-Field Fracture with Minimal Input and Generalized Geometry-Load Handling
Panos Pantidis, Lampros Svolos, Diab Abueidda +1
We present a novel formulation for modeling phase-field fracture propagation based on the Integrated Finite Element Neural Network (IFENN) framework. IFENN is a hybrid solver schem…
Physics-informed Multiple-Input Operators for efficient dynamic response prediction of structures
Bilal Ahmed, Yuqing Qiu, Diab W. Abueidda +3
Finite element (FE) modeling is essential for structural analysis but remains computationally intensive, especially under dynamic loading. While operator learning models have shown…