activity
20192025
most citedA Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning

132 citations · 211 across the 7 of their papers we have counts for

collaborators

7 papers

cond-mat.soft2025

Invariant fractocohesive length in thermally aged elastomers

Aimane Najmeddine, Santiago Marin, Zhen Xu +3

The fractocohesive length - the ratio between fracture toughness and work-to-fracture - provides a material-specific length scale that characterizes the size-dependent fracture beh…

cs.LG2025

Predicting Stress and Damage in Carbon Fiber-Reinforced Composites Deformation Process using Composite U-Net Surrogate Model

Zeping Chen, Marwa Yacouti, Maryam Shakiba +3

Carbon fiber-reinforced composites (CFRC) are pivotal in advanced engineering applications due to their exceptional mechanical properties. A deep understanding of CFRC behavior und…

cond-mat.mtrl-sci2022★ 26 cited

Physics and chemistry-based constitutive framework for thermo-chemically aged elastomer using phase-field approach

Aimane Najmeddine, Maryam Shakiba

We propose a physics and chemistry-based constitutive framework to predict the stress responses of thermo-chemically aged elastomers and capture their brittle failure using the pha…

cond-mat.mtrl-sci2021★ 26 cited

Physics-based Constitutive Modeling of Photo-oxidative Aging in Semi-Crystalline Polymers based on Chemical Characterization Techniques

Aimane Najmeddine, Zhen Xu, Guoliang Liu +2

This paper proposes a physio-chemically-based constitutive framework to simulate and predict the response of semi-crystalline low-density polyethylene (LDPE) to severe photo-oxidat…

cond-mat.mtrl-sci2021★ 4 cited

Physics-based Constitutive Equation for Thermo-Chemical Aging in Elastomers based on Crosslink Density Evolution

Maryam Shakiba, Aimane Najmeddine

This paper presents a physics-based constitutive equation to predict the thermo-chemical aging in elastomers. High-temperature oxidation in elastomers is a complex phenomenon. The…

cs.LG2021★ 132 cited

A Data-Driven Approach to Full-Field Damage and Failure Pattern Prediction in Microstructure-Dependent Composites using Deep Learning

Reza Sepasdar, Anuj Karpatne, Maryam Shakiba

An image-based deep learning framework is developed in this paper to predict damage and failure in microstructure-dependent composite materials. The work is motivated by the comple…

physics.comp-ph2019★ 23 cited

Overcoming the Convergence Difficulty of Cohesive Zone Models through a Newton-Raphson Modification Technique

Reza Sepasdar, Maryam Shakiba

This paper studies the convergence difficulty of cohesive zone models in static analysis. It is shown that an inappropriate starting point of iterations in the Newton-Raphson metho…