Analysis of Acoustic Wave Propagation in Defective Concrete: Evolutionary Modeling, Energetic Coercivity, and Defect Classification
Source abstract
Abstract
This study introduces a theoretical and computational framework for modeling acoustic wave propagation in defective concrete, with applications to non-destructive testing and structural health monitoring. The formulation is based on a coupled system of evolutionary hyperbolic equations, where internal defects are explicitly represented as localized energetic sources or sinks. A key contribution is the definition of a coercivity coefficient, which quantifies the energetic effect of defects and enables their classification as stabilizing, neutral, or dissipative. The model establishes a rigorous relationship between defect morphology, spatial distribution, and the global energetic stability of the material. Numerical simulations performed with an explicit finite-difference time-domain scheme confirm the theoretical predictions: the normalized total energy remains above 95% for stabilizing defects (μi>0), decreases by about 10% for quasi-neutral cases (μi≈0), and drops below 50% within 200μs for dissipative defects (μi<0). The proposed approach reproduces the attenuation and phase behavior of classical Biot-type and Kelvin–Voigt models with deviations below 5% while providing a richer energetic interpretation of local defect dynamics. Although primarily theoretical, this study establishes a physically consistent and quantitatively validated framework that supports the development of predictive ultrasonic indicators for the energetic classification of defects in concrete structures.
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Affiliations
DICEAM Department, Mediterranea University, Via Zehender (ex Via Graziella Feo di Vito), I-89122 Reggio Calabria, Italy
Department of Health Science, Magna Graecia University, Viale Europa, I-88100 Catanzaro, Italy
DIIES Department, Mediterranea University, Via Zehender (ex Via Graziella Feo di Vito), I-89122 Reggio Calabria, Italy
Funding
Integration of Artificial Intelligence and Ultrasonic Techniques for Monitoring Control and Self Repair of Civil Concrete Structures · Future Artificial Intelligence Research · NextGenerationEU
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