Over recent decades, advances in concrete design codes have left many existing bridges with outdated detailing and reduced nominal capacity, while traffic loads and intensities have continued to increase. Since many of these structures are now nearing the end of their service life, reducing uncertainty in their residual capacity has become critical. Structural Health Monitoring (SHM) offers a means to achieve this. This thesis investigates the applicability of Smart Aggregates (SA), a novel type of piezoelectric acoustoelastic sensor, for SHM of concrete slab bridges. A framework is proposed for SA data to decouple temperature related effects and an approach to signal data-processing challenges, in order to isolate stresses related to mechanical loading, enabling more reliable data interpretations of proof loadings and long-term monitoring. The approach is demonstrated on the Balladelaan Bridge in Amersfoort, a vintage structure with uncertain composite action between its original deck and a concrete topping layer. Signal processing was carried out using the stretching technique, which estimates relative velocity changes and cross-correlation between signals. A systematic window configuration strategy is proposed, based on wave interferometry of early-arrivals or fully diffused coda waves. A key data-processing challenge—sub-sample misalignment in the SA triggering mechanism—was identified and corrected using a confidence interval derived from reference data at the Zeeland Bridge. Temperature effects were decoupled by combining experiments and Finite Element Modeling (FEM). A negative linear relationship between temperature and wave velocity change in concrete is quantified, with velocity decreasing as temperature increases. The effect is found to be relatively more pronounced in the later coda waves compared to early-arrivals. Sub-zero temperatures indicated a non-linear temperature-velocity change relationship for freeze-thaw, important for passive monitoring applications. Simplified temperature-induced stresses, including mean temperature and linearized gradients, are evaluated using both (1) literature-based relations and (2) a parametric 2.5D finite element (FE) model, which should yield a similar result. For mean temperature changes, the literature-based approach overestimated temperature-induced stress effects compared to FE approach by an order of 10 when analyzing early-arrivals. This was caused mainly by unrepresentative assumed higher order constants relating wave velocity to stress change for the literature-based approach, and limitations of the finite element model to represent the stresses at the Balladelaan bridge. Linearized gradients showed unexpected behavior for sensor pairs at the interface between the original deck and the concrete topping layer, suggesting a complex stress state due to possible partial composite action. This is further reaffirmed by significant drops in correlation-coefficient for sensor pairs at the supports where the effect of sliding is expected. The proposed framework demonstrates how Smart Aggregates can support SHM of slab bridges, reducing uncertainty in safety assessments and extending service life through predictive maintenance and digital twin applications.

As materials degrade over time and traffic loads increase, monitoring the structural health of concrete infrastructures has become crucial. Structural health monitoring (SHM) and non-destructive evaluation (NDE) techniques are gaining attention for their role in maintaining the functionality and safety of these structures. One of the most effective methods is tracking stress changes in concrete, as it allows engineers to detect potential weaknesses and address them proactively, thus preventing catastrophic failures and improving safety. To monitor these changes, bulk wave-based acoustoelasticity is chosen for its promise in long-term monitoring and tracking of internal stress distributions.

However, applying bulk wave-based acoustoelasticity to concrete presents significant challenges. These challenges arise from three main areas: data processing techniques, acoustoelastic theory, and heterogeneity of concrete. First, there is limited research on data processing techniques for extracting bulk wave properties specific to concrete, resulting in a gap in understanding how these techniques apply to this material. Second, the existing acoustoelastic theory is primarily developed for scenarios where bulk waves propagate parallel or orthogonal to the principal deformation directions. This focus limits its applicability to concrete, where the principal deformation directions often vary under different loading conditions. Third, the meso-scale heterogeneity of concrete causes strong interactions between bulk waves, at frequencies of around a hundred kilohertz, and heterogeneities within the concrete. These interactions, known as scattering, significantly impact the propagation and spatial distribution of bulk waves, making interpretation challenging. This dissertation explores solutions to these challenges and offers a theoretical framework for engineers and researchers to monitor stress and strain changes in concrete using acoustoelasticity.

Our investigation into data processing techniques focuses on retrieving two categories of bulk wave properties from experiments: travel time changes and diffusive properties. We use wave interferometry techniques to measure travel time changes resulting from stress changes, comparing the wavelet cross-spectrum (WCS) technique and the stretching technique. The results show consistency in the velocity changes retrieved by both techniques. For diffusive properties like diffusivity and dissipation, we fit these proper-ties through the diffusion equation. Adjustments are made to account for boundary effects by incorporating reflected energy from so-called image sources.

We further revisit the current acoustoelastic theory to address bulk waves propagating at angles to the principal deformation directions. Our findings reveal that while shear strains have a minimal impact on longitudinal wave velocities, they significantly affect transverse wave velocities. Based on this, we propose a simplified acoustoelastic ex-pression for inclined propagating ballistic waves, primarily longitudinal, in a plane stress state, and validate it experimentally.

Understanding acoustoelastic theory alone is insufficient for interpreting travel time changes of diffuse waves in concrete; the energy ratio between longitudinal and trans-verse waves is also crucial. To address this, we propose a bulk wave energy transport model to estimate this energy ratio based on the angular frequency of bulk waves, the volume fraction of coarse aggregates, and the characteristic radius of these aggregates. The validity of the proposed model is confirmed by comparing theoretical diffusivities with experimental values, which are fitted from the diffusion equation while accounting for boundary reflections.

To investigate travel time changes of diffuse bulk waves, we integrate the previously discussed acoustoelastic theory with the bulk wave energy transport model. The energy transport model estimates the energy ratio between longitudinal and transverse waves and the time required for this ratio to equilibrate. Using Monte Carlo simulations in conjunction with acoustoelastic theory, we estimate the travel time changes for diffuse longitudinal and transverse waves. These estimates are then weighted by the energy ratio to predict travel time changes, which are compared with experimental observations retrieved using the WCS techniques.

This dissertation provides a theoretical foundation for applying bulk wave-based acoustoelasticity to concrete. Additionally, the revisited acoustoelastic theory may be applicable to other compressible, statistically isotropic solids, such as metals. The scattering theory-based model also offers a valuable tool for investigating scatterer proper-ties in concrete.