arXiv subjects

Aditya Konale

Publications and source records attributed to Aditya Konale.

4 recordsLinked to original sources

arXiv2026

Modeling damage and fracture in additively manufactured polymeric triply periodic minimal surface lattices

Architected triply periodic minimal surface (TPMS) lattices offer superior specific energy absorption, toughness, fatigue strength, and tunability. While recent advancements have established rate-dependent viscoplastic constitutive models to capture the complex nonlinear deformation response of additively manufactured polymeric TPMS structures, predicting fracture and the resulting structural failure remains a significant challenge. We address this by performing systematic experiments on unit cells and lattices of various sizes under tension, compression, and non-monotonic loading. The experiments inform the development of a new constitutive model that captures the damage and fracture behavior of polymeric TPMS lattices. We first implement a high-fidelity viscoplastic deformation constitutive model from Ma et al. (2026) into finite element software Abaqus/Explicit via a user material subroutine. We then propose a damage initiation criterion for amorphous polymers based on stored elastic energy and equivalent plastic strain. The damage model is implemented in Abaqus using gradient-damage framework following Konale and Srivastava(2025). The damage model and numerical simulation capability are quantitatively and qualitatively validated using experimental results for a unit cell under non-monotonic loading and lattices under tension. The proposed damage model and simulation capability enable in silico design of architected polymer structures.

cond-mat.soft↗

arXiv2025

A physics-informed neural network for modeling fracture without gradient damage: formulation, application, and assessment

Accurate computational modeling of damage and fracture remains a central challenge in solid mechanics. The finite element method (FEM) is widely used for numerical modeling of fracture problems; however, classical damage models without gradient regularization yield mesh-dependent and usually inaccurate predictions. The use of gradient damage with FEM improves numerical robustness but introduces significant mathematical and numerical implementation complexities. Physics-informed neural networks (PINNs) can encode the governing partial differential equations, boundary conditions, and constitutive models into the loss functions, offering a new method for fracture modeling. Prior applications of PINNs have been limited to small-strain problems and have incorporated gradient damage formulation without a critical evaluation of its necessity. Since PINNs in their basic form are meshless, this work presents a PINN framework for modeling fracture in elastomers undergoing large deformation without the gradient damage formulation. The PINN implementation here does not require training data and utilizes the collocation method to formulate physics-informed loss functions. We have validated the PINN's predictions for various defect configurations using benchmark solutions obtained from FEM with gradient damage formulation. The crack paths obtained using the PINN are approximately insensitive to the collocation point distribution. This study offers new insights into the feasibility of using PINNs without gradient damage and suggests a simplified and efficient computational modeling strategy for fracture problems. The PINN's performance has been evaluated through systematic variations in key neural network parameters to provide an assessment and guidance for future applications. The results motivate the extension of PINN-based approaches to a broader class of materials and damage models in mechanics.

cond-mat.soft↗

arXiv2024

On modeling fracture of soft polymers

Soft polymers are ubiquitous materials in nature and as engineering materials with properties varying from rate-independent to rate-dependent. Current fracture toughness measures are non-unique for rate-dependent soft materials for varying loading profiles and specimen geometries. Works on modeling fracture in rate-dependent soft polymers are limited to specific pre-cracked geometries. There is no generally agreed-upon model for the fracture of soft polymers. We propose and show that a critical value of stress work can be used as a measure of fracture resistance for a certain class of soft polymers. We develop a damage model to predict fracture in soft polymers. In the model, the energetic part of the critical stress work is proposed as a damage initiation criterion that has the ability to capture failure surfaces. The damage growth is modeled through a generalized gradient-damage framework. The fracture model is validated for both elastomers and viscous soft polymers by comparing model predictions against experimental results for different materials (ethylene propylene diene monomer - EPDM, EPS25 vitrimer, styrene butadiene rubber - SBR, natural rubber - NR, and polyborosiloxane - PBS), a variety of specimen geometries, and loading conditions. The model can predict key physical phenomena such as brittle and ductile responses and different fracture profiles. The microstructural quantities, such as subchain dissociation energy during the fracture of polymers, can be predicted from the macroscopic model parameters.

cond-mat.soft↗

arXiv2023

A large deformation model for quasi-static to high strain rate response of a rate-stiffening soft polymer

Polyborosiloxane (PBS) is an important rate-stiffening soft polymer with dynamic, reversible crosslinks used in applications ranging from self-healing sensing and actuation to body and structural protection. Its highly rate-dependent response, especially for impact-mitigating structures, is important. However, the large strain response of PBS has not been characterized over quasi-static to high strain rates. Currently, there are no constitutive models that can predict the strongly rate-dependent large-deformation elastic-viscoplastic response of PBS. To address this gap, we have developed a microstructural physics motivated constitutive model for PBS and similar soft polymers and polymer gels with dynamic crosslinks to predict their large strain, non-linear loading-unloading, and significantly rate-dependent response. We have conducted compression experiments on PBS up to true strains of $\sim$125$\%$ over a wide strain rate range of 10$^{-3}$ s$^{-1}$ to 10$^{3}$ s$^{-1}$. The model reasonably accurately captures the response of PBS over six decades of strain rates. We propose boron-oxygen coordinate-bond dynamic crosslinks with macroscopic relaxation timescale $τ\approx 3$ s and temporary entanglement lockups at high strain rates acting as crosslinks with $τ\approx 0.0005$ s as the two types of crosslink mechanisms in PBS. We have outlined a numerical update procedure to evaluate the convolution-like time integrals arising from dynamic crosslink kinetics. Experiments involving three-dimensional inhomogeneous deformations were used to verify the predictive capabilities of our model and its finite element implementation. The modeling framework can be adopted for other dynamically crosslinked rate-stiffening soft polymers and polymer gels that are microstructurally similar to PBS.

cond-mat.soft↗