There are numerous factors that can have an impact on the degradation behavior of
batteries, such as the number of recharge cycles or the charge rate. Here, we investigate the …

This work presents the application of Physics Informed Deep Learning models for both
surrogate modelling and segmentation of composite materials. The segmentation is …

A quantitative link between crack evolution in lithium-ion positive electrodes and the
degrading performance on cells is not yet well established nor is any single technique …

Porosity severely reduces the mechanical performance of composite laminates and methods
for automatic segmentation of void phases are growing. This study investigates porosity in …

Combinations of X-ray Computed Tomography (XCT) scan times, from 30 s to 60 min, and
voxel sizes, from 6 to 50 µm, were investigated for their effect on the porosity measurements …

Modeling realistic textile composite structures remains a challenging task due to their
complex geometry. In this paper, a novel method for reconstructing yarn paths based on …

High-fidelity models are essential for accurate finite element (FE) simulations of composite
material behavior. This paper proposes an efficient meshing methodology based on micro …

Analyzing computed tomography (CT) scans is challenging and time-consuming due to their
high complexity. Machine learning, particularly in the form of segmentation techniques, has …

This study demonstrated substantial agreement between groups of experts and non-experts
in labelling image regions required for semantic segmentation of X-ray micrographs of …

Identifying different features and phases within the biaxial warp-knitted composites enables
accurate characterization of the internal changes of the composites under complex loading …