Environmentally friendly lead-free piezoelectric ceramics as pavement sensing element: A multi-scale finite element perspective

Potassium sodium niobate (KNN), a lead-free piezoelectric ceramic, demonstrates its significant potential as an environmentally friendly element for energy harvesting and sensing due to its relatively high piezoelectricity and cost-effectiveness. Although the properties of KNN have been proven promising as a piezoelectric element in some electronic devices, the application in pavement engineering as a sensing element remains challenging due to the knowledge gap of static mechanical-piezoelectric correlations along with dynamic multi-axial loads and cross-scale coupling effects. Most importantly, due to the shortage of basic information about the properties of bulk KNN ceramics, it is even infeasible to implement numerical simulations. To tackle this challenge, we developed a KNN-based multi-scale dynamic evaluation finite element framework by using real properties obtained from lab-prepared KNN ceramics as pivotal parameters. To assess the feasibility of KNN as a sensing element in pavements, traffic flow-related factors (horizontal offset, camber, axle load, speed, deceleration, and friction coefficient) and sensor position factors (buried depth, phase angle, and arrangement spacing) were involved in this model. The simulation results indicate that KNN sensors exhibit superior applicability in asphalt pavement compared with concrete pavement under dynamic traffic conditions. The optimal open-circuit voltage output for asphalt pavements occurs at a depth of 2 cm, a phase angle of 15°, and an arrangement spacing of 15 cm, whereas in concrete pavements, the optimal configuration is a depth of 2 cm, a phase angle of 0°, and an arrangement spacing of 15 cm. This work establishes a multi-scale coupling theory and scalable optimization framework for dynamically adaptive lead-free piezoelectric sensors in smart transportation systems. • The multi-scale FE models of tire-pavement-KNN sensor systems are developed. • The mechanical response of pavement with embedded KNN sensors are studied in a large-scale model. • The mechanical and piezoelectric responses of the KNN sensor are studied in a small-scale model. • Simulations show KNN sensors in asphalt are more stable than in concrete due to stiffness and piezoelectric reliability. • Multiscale theory guides lead-free ceramics via cross-scale frameworks and parametric optimization.