Maryam Shakiba

This study introduces the Interface-Aware Deep Energy Method (IDEM), a physics-informed neural network framework for predicting the mechanical linear response of tapered composite laminates. The proposed methodology incorporates an interface property-averaging scheme within a deep energy minimization framework to improve the representation of stress discontinuities across different material interfaces. The proposed formulation embeds governing physics directly into the learning process, enabling accurate prediction of displacement and stress fields without requiring any training data.The proposed method is evaluated on tapered composite laminate configurations with varying stacking sequences and taper angles. IDEM's predicted full-field displacement and stress distributions within the tapered laminate cross sections are validated against high-fidelity finite element simulations. Results demonstrate that the proposed IDEM framework accurately captures both displacement and stress fields with high accuracy. IDEM achieves high correlation with finite element results ($R^2 \geq 0.99$) for displacement predictions and significantly reduces stress prediction errors compared to a baseline Deep Energy Method, with mean absolute error reductions of over 50\%. Therefore, the proposed interface-aware formulation extends the applicability of Deep Energy Methods to composite laminates with material discontinuities and complex geometries. By accurately resolving localized stress concentrations, the framework provides a robust physics-informed approach for the analysis and design of tapered composite structures.

Thermal aging can strongly embrittle elastomers, degrading both their bulk mechanical response and their resistance to crack growth. Yet, despite substantial progress in constitutive modeling of aging-driven changes in stress-strain behavior, there is currently no reliable numerical framework to predict how fracture toughness evolves with aging without performing dedicated fracture tests at each aging state. Here we address this gap by identifying an aging-invariant material length scale for elastomers, defined by the ratio of fracture toughness to work-of-fracture. Through experiments on styrene-butadiene rubber (SBR) and silicone rubber (SR) aged at multiple temperatures for up to eight weeks, we show that thermal aging substantially decreases both the work-of-fracture (from unnotched specimens) and the fracture toughness (from notched specimens), but their ratio remains constant. This invariance provides the missing bridge between bulk aging models and fracture predictions: once the length scale is calibrated for the pristine material, the fracture toughness at any aging state can be computed directly from the work-of-fracture predicted by constitutive models. We further show that this invariant length governs flaw sensitivity by connecting it to the internal length in an AT1 phase-field formulation and demonstrating, via large-deformation phase-field simulations, that the critical flaw size separating flaw-insensitive and flaw-sensitive rupture is unchanged between aged and unaged specimens. The proposed framework enables stand-alone, computationally tractable toughness evolution and fracture simulation of thermally aged elastomeric components without exhaustive fracture testing across aging conditions.

This paper presents a novel and efficient micromechanical framework for finite element simulation of damage and failure in 3-D printed aligned discontinuous fiber-reinforced composites. The framework can predict the initiation and propagation of different types of damage in the composite under tensile loading along the fibers’ axis. The micromechanical framework includes the microstructural representation of the composite with explicit fibers and matrix in addition to linear expansions at the ends. Accurate constitutive equations are utilized for fibers, matrix, and fiber/matrix interfaces in the microstructural representation. Fibers’ locations and lengths are generated randomly; based on a target distribution for the fibers’ aspect ratios measured experimentally; within the microstructural representation. Optimal microstructural representative dimensions for reliable investigation of the mechanical response are computed by conducting sensitivity analyses. The accuracy of the micromechanical framework is validated versus the experimental results of a 3-D printed aligned discontinuous fiber-reinforced composite as the composite of interest. It is shown that the proposed framework can simulate various aspects of the mechanical response, including the failure pattern and stress-strain behavior. Subsequently, the sensitivity of the mechanical response of the composite to a few constitutive equation-related parameters, including the strength and fracture toughness of the fiber/matrix interfaces and the matrix strength, is investigated. The correlation between the studied parameters and the composite’s strength and failure pattern is also analyzed and discussed. This paper delivers valuable guidance on the mechanical response of printed aligned discontinuous fiber-reinforced composites, eventually resulting in the paradigm-shifting design, manufacturing, and analysis of such advanced composites.