PSI - Issue 77

Muhammad Jahanzeb Zia et al. / Procedia Structural Integrity 77 (2026) 111–118

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Muhammad Jahanzeb Zia et al. / Structural Integrity Procedia 00 (2026) 000–000

Nomenclature SHM

Structural health monitoring Finite element analysis Support Vector Machine Pseudo Wigner-Ville Distribution Benzeghagh-Kenane model Acoustic emission

FEA SVM

AE

PWVD BK 1 2 , 3 1 , 2 , 3 12 , 13 , 23 11 22 , 12

Longitudinal modulus Transverse moduli Poisson’s ratios Shear moduli Longitudinal stress Transverse stresses Ultimate tensile strength Longitudinal strength Compressive strength

τ a τ

Allowable longitudinal tensile strength

,

Mixed-mode critical energy release rate Fracture toughness in Mode I and II Energy release rate in Mode I and II

,

Empirical material parameter for shear contribution

1. Introduction The rapid advancement of aerospace, automotive, renewable energy, and marine industries has intensified the demand for lightweight, high-strength structural materials. Among candidate materials, epoxy–glass fibre composites have gained wide industrial adoption due to their cost-effectiveness relative to carbon fibre reinforced polymers while retaining excellent mechanical performance. Despite these advantages, robust real-time Structural Health Monitoring (SHM) strategies remain a critical challenge, particularly in detecting the initiation, propagation, and progression of damage in these structures. As highlighted by Farrar and Worden (2013) and Staszewski et al. (2004), large-scale applications such as wind turbine blades, aircraft components, and marine vessels necessitate continuous monitoring to prevent catastrophic failures and optimize maintenance strategies. The complexity of these systems reinforces the importance of advanced SHM approaches. E-glass fibres, as described by Rana and Fanguiero (2016), offer excellent specific stiffness at low cost. Their mechanical performance depends on fibre architecture, ranging from chopped and woven to unidirectional forms, each exhibiting distinct responses under load. Characterizing damage in such composites has been widely investigated through acoustic emission (AE), which enables real-time monitoring of evolving failure mechanisms (see, e.g., Schnabel et al., 2017; Osa-uwagboe et al., 2023). On the computational side, finite element (FE) modelling of E-glass composites remains challenging due to complex multiscale interactions between fibre breakage, matrix cracking, and fibre–matrix debonding (Zhuang and Talreja, 2016). Representative Volume Element approaches by Liu et al. (2016) have proven effective in capturing local stress concentrations, but reliable identification of failure modes continues to be a bottleneck. Prior studies by Qiao et al. (2022), Zhou et al. (2018), and Zhao et al. (2019) consistently identified matrix cracking, fibre breakage, and delamination as the dominant mechanisms. Computational–experimental correlations further support predictive modelling. For example, Kimyong et al. (2012) observed strong agreement between FE-predicted AE events and experiments, while Barbero et al. (2013) demonstrated that integrating the Hashin failure criteria with progressive damage analysis in Abaqus successfully replicated fibre and matrix cracking under loading. Solver choice is also influential; Leckey et al. (2018) and Chiappa et al. (2018) demonstrated that ABAQUS/Explicit provided superior agreement with guided wave experiments compared to NASTRAN, ANSYS, and COMSOL.