Microstructure-driven wave energy control in temperature-dependent fiber-reinforced composites: A unified micropolar thermoelastic model and data-driven design

• First unified model for wave reflection in temperature-dependent fiber-reinforced micropolar composites. • Quantified parameter hierarchy: stiffness constant (47%) and thermal lag (43%) dominate wave energy. • Machine learning provides robust validation of the analytical model (R2 > 0.999). • Optimal 55°±5° incidence angle identified for ultrasonic non-destructive evaluation. • Practical design guidelines for tailoring composites for vibration damping and wave control Predicting and controlling wave energy distribution in fiber-reinforced composites remains a fundamental challenge due to their complex microstructure. This paper presents a unified microstructure-aware model for incompressible, temperature-dependent composites, integrating micropolar theory, nonlocal elasticity, and three-phase-lag heat conduction. We derive a complete analytical solution for wave reflection and perform a normalized sensitivity analysis, revealing a definitive hierarchy of parameter influence. The empirical stiffness constant ( α * , 47 % ) and thermal displacement lag ( τ v , 43 % ) dominate wave energy distribution by governing anisotropic stress transfer and thermo-micropolar resonance. Our model predicts that an incidence angle of ( 55 o ± 5 o ) is optimal for non-destructive evaluation and provides specific parameter thresholds (e.g., α * > 2 × 10 13 G P a · n m − 1 ) for maximizing microrotational damping. Furthermore, we develop highly accurate machine learning surrogates ( L S T M R 2 > 0.999 ) for rapid design exploration. This work bridges advanced continuum mechanics with practical composite engineering, providing a validated framework and actionable design guidelines for tailoring wave management in next-generation composite structures.