activity
20232026
most citedA machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture content

25 citations · 30 across the 6 of their papers we have counts for

collaborators

6 papers

physics.comp-ph2026

PI-GINOT: Data-free geometry-informed neural operator learning for finite-strain hyperelasticity on parametric DogBone specimens

Aamir Dean, Betim Bahtiri

Parametric nonlinear solid-mechanics simulations are widely used in virtual testing, optimisation, and uncertainty analysis, but repeated finite-element simulations become costly w…

physics.comp-ph2026

A multiphysics deep energy method for fourth-order phase-field fracture with piezoresistive self-sensing

Aamir Dean, Betim Bahtiri

Piezoresistive materials can act as self-sensing media because deformation and cracking modify their electrical resistance. This paper presents a fracture-informed multiphysics fra…

physics.comp-ph2025★ 5 cited

A hybrid electromechanical phase-field and deep learning framework for predicting fracture in dielectric nanocomposites

Aamir Dean, Jaykumar Mavani, Betim Bahtiri +2

The accurate and efficient prediction of crack propagation in dielectric materials is a critical challenge in structural health monitoring and the design of smart systems. This wor…

cs.LG2024

A thermodynamically consistent physics-informed deep learning material model for short fiber/polymer nanocomposites

Betim Bahtiri, Behrouz Arash, Sven Scheffler +2

This work proposes a physics-informed deep learning (PIDL)-based constitutive model for investigating the viscoelastic-viscoplastic behavior of short fiber-reinforced nanoparticle-…

cs.CE2024

Cyclic viscoelastic-viscoplastic behavior of epoxy nanocomposites under hygrothermal conditions: A phase-field fracture model

Behrouz Arash, Shadab Zakavati, Betim Bahtiri +2

In this study, a finite deformation phase-field formulation is developed to investigate the effect of hygrothermal conditions on the viscoelastic-viscoplastic fracture behavior of…

cs.LG2023★ 25 cited

A machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture content

Betim Bahtiri, Behrouz Arash, Sven Scheffler +2

In this work, we propose a deep learning (DL)-based constitutive model for investigating the cyclic viscoelastic-viscoplastic-damage behavior of nanoparticle/epoxy nanocomposites w…