Diab W. Abueidda

Orcid: 0000-0003-3594-2455

According to our database1, Diab W. Abueidda authored at least 22 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Sequential Deep Operator Networks (S-DeepONet) for predicting full-field solutions under time-dependent loads.
Eng. Appl. Artif. Intell., January, 2024

Advanced Deep Operator Networks to Predict Multiphysics Solution Fields in Materials Processing and Additive Manufacturing.
CoRR, 2024

Geom-DeepONet: A Point-cloud-based Deep Operator Network for Field Predictions on 3D Parameterized Geometries.
CoRR, 2024

I-FENN with Temporal Convolutional Networks: expediting the load-history analysis of non-local gradient damage propagation.
CoRR, 2024

Material-Response-Informed DeepONet and its Application to Polycrystal Stress-strain Prediction in Crystal Plasticity.
CoRR, 2024

2023
Multi-component Predictions of Transient Solution Fields with Sequential Deep Operator Network.
CoRR, 2023

Effect of the cross-section architecture on the impact resistance of bio-inspired low-porosity structures using neural networks.
CoRR, 2023

Sequential Deep Learning Operator Network (S-DeepONet) for Time-Dependent Loads.
CoRR, 2023

Novel DeepONet architecture to predict stresses in elastoplastic structures with variable complex geometries and loads.
CoRR, 2023

I-FENN for thermoelasticity based on physics-informed temporal convolutional network (PI-TCN).
CoRR, 2023

Gyroid-like metamaterials: Topology optimization and Deep Learning.
CoRR, 2023

2022
A deep learning energy-based method for classical elastoplasticity.
CoRR, 2022

On the use of graph neural networks and shape-function-based gradient computation in the deep energy method.
CoRR, 2022

Deep energy method in topology optimization applications.
CoRR, 2022

LatticeOPT: A heuristic topology optimization framework for thin-walled, 2D extruded lattices.
CoRR, 2022

Enhanced physics-informed neural networks for hyperelasticity.
CoRR, 2022

Exploring the structure-property relations of thin-walled, 2D extruded lattices using neural networks.
CoRR, 2022

Surrogate Neural Network Model for Sensitivity Analysis and Uncertainty Quantification of the Mechanical Behavior in the Optical Lens-Barrel Assembly.
CoRR, 2022

A deep learning energy method for hyperelasticity and viscoelasticity.
CoRR, 2022

2020
Deep learning collocation method for solid mechanics: Linear elasticity, hyperelasticity, and plasticity as examples.
CoRR, 2020

Machine learning accelerated topology optimization of nonlinear structures.
CoRR, 2020

2019
Prediction and optimization of mechanical properties of composites using convolutional neural networks.
CoRR, 2019


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