DYNAMIC ANALYSIS OF PAVEMENT-SOIL SYSTEM WITH PIEZO-SENSORS

Abstract

The dynamic performance of pavement–soil systems under moving vehicular loads is a complex interaction of load-induced stresses, material damping, and subgrade behavior. Despite significant theoretical progress, practical implementations remain limited due to the lack of integrated modeling frameworks and sensing mechanisms that can capture in situ dynamic responses. This thesis presents a comprehensive investigation that combines finite element-based numerical simulation, experimental validation, and piezoelectric sensing to develop a generalised dynamic framework for pavement–soil systems. A finite element model incorporating viscoelastic pavement layers over an elastoplastic subgrade was developed using Lagrangian mechanics and multi-degree-of-freedom discretization. The model introduces a Generalised Dissipation Mechanism (GDM) defined by dissipation parameters (α, β, γ) and empirical coefficients (η, ϑ) to quantify damping and amplification characteristics under moving loads. Simulations revealed a 70% increase in load and a 46% increase in displacement compared to static conditions, establishing realistic velocity-dependent amplification zones. The Vibrational Compounded Stress Transfer Mechanism (V-CSTM) was formulated to explain the nonlinear amplification and post-elastic flow behavior of geomaterials, bridging cyclic strength and fatigue responses under high-velocity traffic loads. Experimental investigations employed flexible PVDF and PVDF–MoS2 piezoelectric films embedded within confined geomaterials to capture electromechanical responses under vibration. The inclusion of MoS2 nanoflakes enhanced the electroactive β-phase from 54% to 76%, producing a four-fold increase in voltage output (up to 16.2 V) and viii confirming superior energy-harvesting efficiency. Correlations between frequency, stress, deflection, and voltage established the films’ suitability for vibration sensing and renewable energy generation. The integrated numerical–experimental framework enables quantification of damping, stress transfer, and energy dissipation across multi-layered pavement systems. The developed piezo-sensors demonstrate strong potential for self-powered monitoring, while the coupled model offers predictive capability for deformation and damage evolution. Overall, this research advances the understanding of dynamic pavement–soil interaction and contributes to the development of smart, sustainable, and energyefficient infrastructure systems. The work supports Sustainable Development Goals 9 and 11 by promoting intelligent transport networks capable of real-time monitoring, reduced maintenance, and green energy harvesting.