Cover Image

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

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Dean, Aamir, Mavani, Jaykumar, Bahtiri, Betim, Arash, Behrouz, Rolfes, Raimund
Format:	Preprint
Published:	2025
Subjects:	Computational Physics
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Cyclic viscoelastic-viscoplastic behavior of epoxy nanocomposites under hygrothermal conditions: A phase-field fracture model
by: Arash, Behrouz, et al.
Published: (2024)

A multiphysics deep energy method for fourth-order phase-field fracture with piezoresistive self-sensing
by: Dean, Aamir, et al.
Published: (2026)

A thermodynamically consistent physics-informed deep learning material model for short fiber/polymer nanocomposites
by: Bahtiri, Betim, et al.
Published: (2024)

A machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture content
by: Bahtiri, Betim, et al.
Published: (2023)

A phase-field framework for anisotropic viscoelastic-viscoplastic fracture in short fiber-reinforced polymers in hygrothermal environments
by: Arash, Behrouz, et al.
Published: (2026)

A COMSOL framework for predicting hydrogen embrittlement -- Part II: phase field fracture
by: Díaz, A., et al.
Published: (2025)

Physics‐Informed Deep Learning Constitutive Model for Anisotropic and Pressure‐Dependent Behavior of Short Fiber‐Reinforced Polymers
by: Aamir Dean, et al.
Published: (2025)

A multi-phase-field model for fiber-reinforced composite laminates based on puck failure theory
by: Kumar, Pavan Kumar Asur Vijaya, et al.
Published: (2026)

Deep learning-based phase-field modelling of brittle fracture in anisotropic media
by: Plungė, N., et al.
Published: (2026)

Single replica spin-glass phase detection using field variation and machine learning
by: Talebi, Ali, et al.
Published: (2024)

A unified variational framework for phase-field fracture and third-medium contact in finite deformation hyperelasticity
by: Kim, Jaemin, et al.
Published: (2026)

A phase field model for hydraulic fracture: Drucker-Prager driving force and a hybrid coupling strategy
by: Navidtehrani, Y., et al.
Published: (2025)

A pseudo-dynamic phase-field model for brittle fracture
by: Sargado, Juan Michael, et al.
Published: (2025)

A generalised framework for phase field-based modelling of coupled problems: application to thermo-mechanical fracture, hydraulic fracture, hydrogen embrittlement and corrosion
by: Navidtehrani, Y., et al.
Published: (2025)

A predictive machine learning force field framework for liquid electrolyte development
by: Gong, Sheng, et al.
Published: (2024)

Assessment of unsteady flow predictions using hybrid deep learning based reduced order models
by: Bukka, Sandeep Reddy, et al.
Published: (2020)

A fluxonium qubit-based hybrid electromechanical system
by: Nongthombam, Roson, et al.
Published: (2025)

A perspective on hybrid quantum opto- and electromechanical systems
by: Chu, Yiwen, et al.
Published: (2020)

Digital twin model of colon electromechanics for manometry prediction of laser tissue soldering
by: Djoumessi, René Thierry, et al.
Published: (2024)

Meta-GGA dielectric-dependent and range-separated screened hybrid functional for reliable prediction of material properties
by: Jana, Subrata, et al.
Published: (2025)

A self-contact electromechanical framework for intestinal motility
by: Djoumessi, René Thierry, et al.
Published: (2025)

A joint voxel flow - phase field framework for ultra-long microstructure evolution prediction with physical regularization
by: Zhou, Ao, et al.
Published: (2026)

A complete phase-field fracture model for brittle materials subjected to thermal shocks
by: Zeng, Bo, et al.
Published: (2026)

Damage Mechanics Challenge: Predictions based on the phase field fracture model
by: Navidtehrani, Y., et al.
Published: (2024)

Long-range machine-learning potentials with environment-dependent charges enable predicting LO-TO splitting and dielectric constants
by: Korogod, Dmitry, et al.
Published: (2026)

A unified sharp-diffusive phase-field model for bulk and interfacial cohesive fracture
by: Qin, Ye-Hang, et al.
Published: (2026)

Classical variational phase-field models cannot predict fracture nucleation
by: Lopez-Pamies, Oscar, et al.
Published: (2024)

Enhancing nuclear cross-section predictions with deep learning: the DINo algorithm
by: Gesson, Levana, et al.
Published: (2025)

Tunneling phase diagram: A machine-learning framework for multidimensional kinetic isotope effects
by: Yang, Xinrui, et al.
Published: (2026)

A Navier-Stokes-Peridynamics hybrid algorithm for the coupling of compressible flows and fracturing materials
by: Han, Mingshuo, et al.
Published: (2025)

Wakefield-induced THz wave generation in a hybrid dielectric-plasma cylindrical waveguide
by: Choobini, A. A. Molavi, et al.
Published: (2025)

Phase-field models for ductile fatigue fracture
by: Kalina, Martha, et al.
Published: (2024)

TeD-Q: a tensor network enhanced distributed hybrid quantum machine learning framework
by: Chen, Yaocheng, et al.
Published: (2023)

A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: efficient mapping of concrete microstructures to its fracture properties
by: Koopas, Rasoul Najafi, et al.
Published: (2024)

A hybrid quantum-classical framework for computational fluid dynamics
by: Ye, Chuang-Chao, et al.
Published: (2024)

Optimizing the Charging of Open Quantum Batteries using Long Short-Term Memory-Driven Reinforcement Learning
by: Zakavati, Shadab, et al.
Published: (2025)

Phonon-induced band gap renormalization by dielectric dependent global hybrid density functional tight-binding
by: van der Heide, Tammo, et al.
Published: (2024)

Emergent Wigner phases in moiré superlattice from deep learning
by: Li, Xiang, et al.
Published: (2024)

Adaptive deep learning framework for robust unsupervised underwater image enhancement
by: Saleh, Alzayat, et al.
Published: (2022)

Enhanced fringe-to-phase framework using deep learning
by: Kim, Won-Hoe, et al.
Published: (2024)