Offshore wind turbines are prone to structural damage over time due to environmental factors, which increases operational costs and the risk of accidents. Early detection of structural damage through monitoring systems can help reduce maintenance costs. However, under complex external conditions and varying structural parameters, existing methods struggle to accurately and quickly detect damage. Understanding the factors that influence structural health is critical for effective long-term monitoring, as these factors directly affect the accuracy and timeliness of damage identification. This study comprehensively analyzed 5 MW offshore wind turbine measurement data, including constructing a digital twin model, establishing a surrogate model, and performing a sensitivity analysis. For monopile-based turbines, sensors in x and y directions were installed at four heights on the pile foundation and tower. Via Bayesian optimization, the finite element model's structural parameters were updated to align its modal parameters with sensor data analysis results. The update efficiencies of different objective functions and the impacts of neural network hyperparameters on the surrogate model were examined. The sensitivity of the turbine's structural parameters to modal parameters was studied. The results showed that the modal flexibility matrix is more effective in iteration. A 128-neuron, double-hidden-layer neural network balanced computational efficiency and accuracy well in the surrogate model for modal analysis. Flange damage and soil degradation near the pile mainly impacted the turbine's health.

Based on a prototype of the Beijing subway tunnel, this research conducts large-scale model experiments to systematically investigate the vibration response patterns of tunnels with different damage levels under the influence of measured train loads. Initially, the polynomial fitting modal identification method (Levy) and the model test preparation process are introduced. Then, using time-domain peak acceleration, frequency response function, frequency-domain modal frequency, and modal shape indicators, a detailed analysis of the tunnel's dynamic response is conducted. The results indicate that damage significantly amplifies vibration acceleration, with the amplification increasing with the severity of the damage. When the crack lengths are 2 cm, 4 cm, and 6 cm, the peak acceleration increases by 25.12%, 36.35%, and 50.29%, respectively, while adjacent segments show increases of 13%, 29%, and 45%. Damage decreases the tunnel structure's modal frequency, with the first two modal frequencies showing the most significant reductions of 9.87% and 7.34%, respectively. The adjacent segments show reductions of 7.7% and 4.2%. As the severity of the damage increases, the amplitude of the modal shape at the damaged location also increases, with the first modal shape rising by 43.37% for 4 cm damage compared to 2 cm damage and by 72.21% for 6 cm damage. The second modal shape increases by 9.04% and 26.51%, respectively. Additionally, the effectiveness of the polynomial fitting modal identification method (Levy) for tunnel structural damage detection was validated. Finally, based on the methods outlined above, the tunnel responses measured on-site in the Beijing metro were also analyzed. The findings of this study provide important theoretical support for the assessment and routine maintenance of metro tunnels.

Distributed acoustic sensing (DAS) technology applied to telecommunication optical fiber networks offers new possibilities for structural health monitoring. The dynamic responses of five bridges are extracted along a 24-km long optical fiber crossing the Lyon metropolitan area in France. From their characteristics signals, three physical parameters informing on the health of structures have been determined: vibration frequencies, damping and modal shapes. The fiber measurements are in agreement with velocimetric data serving as reference. The telecom optical fiber records the dynamic response of bridges in several directions and thus allows the reconstruction of 3D deformation modes using their orthogonality properties. Time tracking of frequencies, commonly used to assess structural integrity, shows that the average values of natural frequencies vary cyclically between day and night. The increase in frequencies during the night does not exceed 2% and probably reflects an overall stiffening of the structures due to the drop in temperature. The telecom fiber allows to obtain deformation and damping identity of structures, highlighting soil-structure coupling between the bridge and underlying soil. This study shows that it is possible to assess the spatial and temporal variability of bridge dynamic response from DAS data using existing fiber networks.

Seismic isolation aims to prevent the direct transmission of seismic wave energy to the main resistant structure. Typically, this is achieved by using a flexible support system that isolates the base of the structural system from the ground, absorbing the relative deformation at the soil-structure interface. Meanwhile, the main structure tends to move as a rigid body on this flexible support. This article proposes an alternative approach for the dynamic characterization of shredded rubber, which is used in geotechnical seismic isolation (GSI). Traditional testing methods are expensive and require specialized equipment, making them less practical for routine determination. The article details the most important parameters needed to evaluate the applicability and effectiveness of the material in the context of GSI. The parameter of interest, i.e. the transverse elasticity module GR, was calibrated numerically from an experimental model of a column of shredded rubber subjected to free vibrations tests. The results were consistent with those obtained from resonant column and hollow cylinder tests. In this way, it is shown that the presented approach is capable of providing valid estimations of the transverse modulus of elasticity of shredded rubber.

The assessment of pipeline free-spans may involve non-linearities, including those arising from the mechanical behaviour of the pipeline, soil properties and hydrodynamic loading; as well as the interaction between these factors. Failure to properly quantify and account for these factors may lead to inadequate design outcomes, which can lead to failure (if unconservative) or result in costly remediation when unnecessary (if conservative). This paper is part of an ongoing study into the vibration response of free spanning subsea pipelines, including the development of a numerical model that highlights the value of modal and full fatigue analyses as tools for understanding span behaviour. For quality control and enhancing the reliability of assessment methodologies, the model has been benchmarked against published data in terms of modal analysis, and against industrial fatigue assessment packages in terms of fatigue analysis - and shows excellent agreement with both. Since verification, the model was used to conduct a sensitivity study on a single free span, to explore how pipeline response and fatigue damage is affected by the value of dynamic soil stiffness and damping.

Aleppo, one of the oldest inhabited world heritage cities in the world, was struck by a destructive earthquake on February 06, 2023. Its iconic citadel built on a historical hill and surrounded by a protective moat, was severely damaged. However, the main entrance tower and the massive arched masonry bridge composed of an inclined deck and a series of unequal pillars height, constructed over the moat, survived the earthquake with minor apparent damages. In the light of a damage identification purpose, characterization of dynamic properties, and a health monitoring plan, an experimental dynamic identification campaignwas conducted on the historic structure, and sonic testingwas undertaken on the bridge pillars. The in-plan and out-of-plan mode shapes were clearly identified under ambient vibrations, in addition to the monument's natural frequencies. The dynamic parameters were estimated via the commercial software ARTeMIS using the EFDD method. Knowing that no data was available on the foundations and the soil conditions, the in-plane deformation modes provided qualitative information about the soil stiffness under the main pillars. Additionally, it was possible to correlate the damage state of the tower to a certain number of bending and torsional modes. The experimental results allowed the calibration of a numerical modal analysis elaborated on a 3D FE model, for a better assessment of the seismic capacity of the monument. The obtained dynamic parameters are to be compared to the monument response during and after a future structural rehabilitation for efficient monitoring of the structural intervention.