activity
20232026
most citedI-FENN with Temporal Convolutional Networks: expediting the load-history analysis of non-local gradient damage propagation

15 citations · 22 across the 8 of their papers we have counts for

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cs.CE2026

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…

cs.CE2025

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…

cs.CE2025

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…

cs.CE2025

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…

cs.CE2024

Image-based adaptive domain decomposition for continuum damage models

Panos Pantidis, Cornelius Otchere, Mostafa E. Mobasher

We present a novel image-based adaptive domain decomposition FEM framework to accelerate the solution of continuum damage mechanics problems. The key idea is to use image-processin…

cs.CE2024

DeepOKAN: Deep Operator Network Based on Kolmogorov Arnold Networks for Mechanics Problems

Diab W. Abueidda, Panos Pantidis, Mostafa E. Mobasher

The modern digital engineering design often requires costly repeated simulations for different scenarios. The prediction capability of neural networks (NNs) makes them suitable sur…