7 papers · 1 filter
A hybrid IFENN solver for generalizable modeling of phase-field fracture initiation and propagation
Panos Pantidis, Fouad Amin, Diab Abueidda +1
In this paper we demonstrate how the Integrated Finite Element Neural Network (IFENN) framework can effectively model the entire evolution of phase-field fracture, including the in…
A comprehensive comparison of neural operators for 3D industry-scale engineering designs
Weiheng Zhong, Qibang Liu, Diab Abueidda +2
Neural operators have emerged as powerful tools for learning nonlinear mappings between function spaces, enabling real-time prediction of complex dynamics in diverse scientific and…
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…
Bridging Sequential Deep Operator Network and Video Diffusion: Residual Refinement of Spatio-Temporal PDE Solutions
Jaewan Park, Farid Ahmed, Kazuma Kobayashi +4
Video-diffusion models have recently set the standard in video generation, inpainting, and domain translation thanks to their training stability and high perceptual fidelity. Build…
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…
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…