Julia Irene Real

This study presents a Digital Twin-based Structural Health Monitoring framework for the assessment of existing concrete gravity dams. The proposed methodology integrates distributed sensing, automated signal processing, finite element modelling, model calibration and validation, degradation sensitivity analysis, and digital visualization within a unified monitoring framework. A network of inertial sensors is deployed along the dam to characterize its dynamic and quasi-static response. Hourly monitoring records are processed to identify natural frequencies using Fast Fourier Transform, Power Spectral Density, and Peak Picking techniques, while acceleration measurements are also used to derive displacement and inclination indicators. A 3D finite element model developed in ANSYS Mechanical APDL (2026 R1) is calibrated by iteratively updating the effective Young’s modulus and density until the relative error between numerical and experimentally identified modal frequencies is below 5%. Independent validation using inclination measurements resulted in relative differences between 0.74% and 4.92%. The calibrated Digital Twin is subsequently used to simulate progressive stiffness degradation and establish relationships between degradation, modal properties, and structural deformation. The resulting model-informed thresholds are integrated into a digital monitoring platform for automated condition assessment and anomaly detection. The framework provides a physically interpretable approach for complementing conventional dam safety inspections with long-term quantitative structural health information.

This study develops a comprehensive Structural Health Monitoring (SHM) strategy applied to the Spyckstraße Bridge, a three-span composite slab-girder structure constructed in 1976, with the objective of evaluating its structural performance under current design standards and increased traffic loads. A short-term monitoring campaign based on non-destructive techniques was carried out to record dynamic responses, including vibrations, displacements, and modal properties. The collected data served to calibrate and validate a Digital Twin model through an iterative optimization process using a genetic algorithm, achieving a deviation below 3 % between experimental and numerical eigenfrequencies. Once validated, the Digital Twin was used to assess the structural response under code-compliant load combinations and to determine utilisation levels for all critical sections. The analysis showed that none of the structural components reached their ultimate limit state, although the maximum tensile utilisation (97.3 %) was identified in the external girder of the central span under combined extreme traffic and thermal loading conditions. Furthermore, a parametric study addressing tendon corrosion effects indicated notable variations in modal characteristics and a decrease in load-bearing capacity. These findings highlight the effectiveness of integrating short-term SHM data with calibrated numerical models as a reliable framework for structural assessment, enabling early damage detection, informed maintenance strategies, and enhanced lifecycle management of existing bridge assets.

Structural Health Monitoring (SHM) of large-span bridges requires dense sensor networks to accurately capture dynamic and kinematic behaviors. Traditional commercial systems rely on complex wiring or wireless protocols that frequently suffer from data loss, high power consumption, and synchronization phase errors, which are detrimental to Operational Modal Analysis (OMA). To address these limitations, this study presents the design, development, and field validation of a custom, offline-synchronized multi-sensor Data Acquisition (DAQ) system. Two specialized sensor nodes were developed: (i) an inertial node integrating a low-noise triaxial MEMS accelerometer (ADXL355); and (ii) a displacement node featuring a 24-bit Analog-to-Digital Converter (ADS1220) for displacement sensors. Both nodes share an ultra-low-power microcontroller (STM32L431) and utilize a local microSD storage strategy with an intermediate pseudo-SRAM buffer. To ensure precise temporal alignment without wireless communication overhead, each node incorporates a temperature-compensated Real-Time Clock (DS3231) for offline timestamp synchronization. The system was validated during a field campaign on the Spyckstraße bridge (Germany), deploying a hardware pool of 53 physical DAQ nodes to monitor 118 distinct geometric measurement points (106 inertial, 12 displacement) through a hybrid strategy of fixed and roving setups. The proposed system achieved reliable, low-noise measurements and enabled accurate extraction of operational mode shapes, demonstrating its viability as a robust, cost-effective solution for large-scale infrastructure monitoring.

Transmission of train-induced vibrations to buildings located in the vicinity of the track is one of the main negative externalities of railway transport, since both human comfort and the adequate functioning of sensitive equipment may be compromised. In this paper, a 3D FEM model is presented and validated with data from a real track stretch near Barcelona, Spain. Furthermore, a case study is analyzed as an application of the model, in order to evaluate the propagation and transmission of vibrations induced by the passage of a suburban train to a nearby 3-storey building. As a main outcome, vertical vibrations in the foundation slab are found to be maximum in the corners, while horizontal vibrations keep constant along the edges. The propagation within the building structure is also studied, concluding that vibrations invariably increase in their propagation upwards the building. Moreover, the mitigation capacity of a wave barrier acting as a source isolation is assessed by comparing vibration levels registered in several points of the building structure with and without the barrier. In this regard, the wave barrier is found to effectively reduce vibration in both the soil and the structure.

Important track degradation occurs in structure-embankment transitions, in which an abrupt change in track vertical stiffness arises, leading to a reduction in passengers comfort and safety. Although granular wedges are suggested by different railroad administrations as a solution to avoid these problems, they present some disadvantages which may affect track long-term performance. In this paper, a new solution designed with prefabricated reinforced concrete slabs is proposed. The aim of this solution is to guarantee a continuous and gradual track vertical stiffness transition in the vicinity of structures, overcoming granular wedges disadvantages. The aim of this study is to assess the performance of the novel wedge design by means of a 3-D FEM model and to compare it with the current solution.