Search Results (929)

The Garisenda Tower, along with the neighboring Asinelli Tower, is arguably the symbol of the city of Bologna. They are the sole remnants of about one hundred towers that formed the city’s skyline in medieval times. As such, the monitoring of their state of health has been of great interest to the scientific community for more than a century—one example being the studies of Prof. Cavani in the early 1900s. The Garisenda Tower, famous for its impressive lean, is the object of Structural Health Monitoring (SHM) involving a multitude of devices. Some examples are a 30 m long pendulum installed on the inside of the tower to measure the planar displacement of the tower’s top; Fiber-Optical Strings (FOSs) installed in the walls of the basement to measure their vertical deformation; and piezoelectric acoustic emission (AE) sensors, also installed on the walls of the tower’s basement to detect elastic waves generated by micro-cracking. This rich experimental setup allows for the investigation of the tower’s stability and damage assessment. In this work, attention is focused on two analyses: The first is a Principal Component Analysis (PCA) study that investigates the correlation between AE data and other SHM data, such as in situ temperature, pendulum displacement, and AE rate. The second analysis corresponds with numerical finite element (FE) studies that assess damage in the base of the tower. Initially, the Smeared Cracking material model is used to understand which zones of the tower are more damaged. Moreover, a possible critical scenario due to increasing tower tilt is investigated. Finally, a viscoelastic formulation of the materials at the base of the tower is used to account for creep to understand the possible viscous effects at the base of the tower. Full article

The excavation of deep shafts using Vertical Shaft Sinking Machine (VSM) technology in stratified soft soils involves complex soil-structure interaction (SSI) mechanisms that are often oversimplified by conventional numerical approaches. This study develops a robust three-dimensional numerical framework to investigate ground deformation induced by VSM operations, explicitly incorporating the phased construction sequence, segmental lining installation, and site-specific stratigraphy. The model is calibrated and validated against high-resolution field monitoring data, employing a prediction envelope approach and statistical performance metrics (RMSE and R2). The results suggest that ground response during VSM excavation is predominantly stiffness-controlled under the investigated conditions. Mobilized shear stresses remain significantly below the available soil capacity, indicating that deformation under serviceability conditions is driven by progressive strain accumulation. Horizontal displacement profiles suggest a relatively stable depth of influence, indicating that the excavation process amplifies deformations within a pre-established domain without significant deep-seated propagation. Sensitivity analyses indicate soil stiffness modules (E50,Eoed,Eur) and the SSI interface factor (Rinter) as the primary drivers of deformation magnitude. Furthermore, stratigraphic contrasts specifically clay-sand sequences, act as a mechanical filter, concentrating strains in soft layers while limiting vertical propagation through stiffer strata. The proposed framework provides a mechanically coherent basis for serviceability-oriented design, deformation prediction, and risk-mitigation strategies for mechanized shafts in saturated soft ground. Full article

Deformation monitoring of bridges is essential to ensure the structural integrity and serviceability of these critical civil infrastructures. In this context, geodetic measurements using total stations and 3D terrestrial laser scanning (TLS) surveys can provide accurate and reliable data. Multitemporal geodetic observations from total stations enable the tracking of displacements at discrete points, whereas TLS surveys allow for the extension of deformation analysis to entire surfaces. Both techniques can achieve comparable millimeter-level precision. These methods were applied to monitor the deformation of the Ponte della Costituzione (PdC), the most recent pedestrian arch bridge spanning the Grand Canal in Venice (Italy). A total station was used to measure the displacements of six control points installed on structurally significant locations of the bridge. Between 3 October 2023 and 2 February 2026, 28 multitemporal measurement campaigns were conducted. In addition, four TLS surveys, using two different laser scanners, were carried out on 1 August 2025 and 2 February 2026, in order to capture conditions corresponding to maximum annual thermal deformation. The results derived from geodetic measurements reveal a strong correlation among: (i) variations in the distance between the abutments (on the order of 6–7 mm); (ii) vertical displacements of the central upper points of the arch (ranging from 9 to 12 cm); and (iii) fluctuations in ambient temperature. TLS data highlighted a spatially homogeneous deformation pattern extending from the crown of the arch to the abutments, demonstrating that longitudinal displacements affect the entire lateral structure. Mid-term deformation analysis over the two-year period from 6 February 2024 to 2 February 2026 indicates displacement rates of approximately 1.4 mm/year for increasing separation between the abutments and 16.2 mm/year for the decrease in elevation of the central arch point. However, these trends are significantly influenced by environmental temperature variations, as evidenced by an estimated temperature change rate of −3.5 °C/year over the same period. Therefore, continued deformation monitoring of the PdC bridge is recommended in the coming years, particularly in light of ongoing climate change and the associated increase in temperature variability. Full article

Land subsidence is an important challenge faced by coastal cities under rapid urban development. This study focuses on the Haikou–Laocheng area and conducts time-series monitoring of land subsidence using PS-InSAR and SBAS-InSAR based on 42 Sentinel-1 SAR scenes acquired from April 2023 to April 2025, thereby deriving the spatial distribution of cumulative subsidence rates and the evolution patterns of multi-temporal cumulative subsidence. Because only ascending-orbit Sentinel-1 data were used, the reported deformation values are vertical-projected estimates converted from line-of-sight (LOS) displacement under the assumption that horizontal motion is negligible. The reliability of the monitoring results is evaluated through cross-validation between the two methods, assessing their inter-method consistency. The results indicate that the study area is dominated by slight subsidence, with vertical-projected subsidence rates mainly ranging from −6 to 3.7 mm/y, while a few uplift points are locally observed, forming an overall “stable with localized anomalies” deformation pattern. PS-InSAR and SBAS-InSAR show good consistency in overall trends, and both identify a pronounced subsidence bowl in the southwestern part of the study area, where the peak vertical-projected subsidence rates reach −25.1 mm/y and −35.1 mm/y, respectively, with outward banded attenuation. The results suggest that land subsidence in the study area is influenced by both natural factors and human activities. Specifically, rainfall shows a non-synchronous, stage-wise modulation relationship with subsidence evolution, and most high-subsidence zones are distributed in impervious surfaces such as built-up land and transportation corridors, or in low-elevation areas such as farmland. In terms of geological factors, thick, highly compressible soft soils are the primary geological control on the continued development of subsidence. These findings can provide scientific references for the prevention and control of abnormal subsidence and for urban planning and development in the Haikou–Laocheng area. The strengthened discussion clarifies the research gap, planning significance, and limitations of applying dual time-series InSAR in a data-scarce tropical coastal soft-soil setting. Full article

With the increased extraction thickness in fully mechanized top-coal caving faces in extra-thick coal seams, the caved gangue in the goaf is unable to effectively support the roof, resulting in aggravated deformation of the pre-driven withdrawal channel. Taking the No. 221304 working face in the No. 13 coal seam of Xiaojiawa Coal Mine as the engineering background, this study combined theoretical analysis, numerical simulation, and field measurement to investigate the effects of the top-coal caving stopping position, suspended roof length, and presplitting roof cutting on the stress and deformation of the rock surrounding the withdrawal channel. The results indicate that the convergence of the roof and floor and that of the two ribs of the withdrawal channel decrease in a staged manner with the increase in the top-coal caving stopping distance, but increase nonlinearly with the increase in the suspended roof length. With the increase in the presplitting roof-cutting height, the surrounding rock deformation first decreases significantly and then tends to level off. When the roof-cutting height is 30.5 m, the reductions in roof displacement and rib convergence reach 33.46% and 37.76%, respectively. When the roof-cutting height is further increased to 35.0 m, the improvement becomes insignificant. Therefore, the reasonable roof-cutting height for the No. 13 coal seam is determined to be 30.5 m. Field monitoring results show that the convergence of the roof and floor and that of the two ribs of the withdrawal channel are reduced by 41.2% and 36.8%, respectively, and the distance between the stopping line and the terminal mining line is shortened by 15 m. The research results provide a useful reference for determining the top-coal caving stopping position and roof-cutting height, and for improving the stability of the surrounding rock of the support withdrawal channel during the final mining stage of fully mechanized top-coal caving faces with thick and hard roofs in extra-thick coal seams. Full article

This study is conducted to investigate the deformation evolution and collapse mechanism of the Rongxing gypsum mine by integrating multi-source monitoring data, including synthetic aperture radar (SAR), global navigation satellite system (GNSS), and microseismic observations. Long-term surface deformation from 2015 to 2025 is retrieved using small baseline subset interferometric synthetic aperture radar (SBAS-InSAR), while GNSS data (2021–2022) are used to capture rapid ground displacement during the collapse event. Microseismic monitoring provides insights into the evolution of subsurface fracturing processes. The results show that the pre-collapse stage is characterized by continuous and spatially heterogeneous subsidence. Prior to the collapse, microseismic activity is observed to exhibit clear precursory signals, including an increase in event number, a decrease in b-value, and accelerated cumulative energy release, suggesting that the transition from distributed microcrack development to large-scale fracture coalescence is occurring. The b-value, derived from the Gutenberg–Richter frequency–magnitude relationship, describes the relative proportion of small to large seismic events and reflects variations in the statistical distribution of event magnitudes. During the collapse stage, abrupt, large-magnitude subsidence is observed by GNSS. After the collapse, the deformation is found to enter a long-term adjustment phase characterized by the coexistence of subsidence and uplift, indicating that stress redistribution within the overburden is occurring. Based on these observations, a conceptual model is proposed to describe the progressive failure mechanism of the goaf, with four stages: slow subsidence, accelerated deformation, collapse, and post-collapse adjustment. This study demonstrates the effectiveness of integrating SBAS-InSAR, GNSS, and microseismic monitoring for understanding the full lifecycle of goaf collapse. It provides valuable insights for early warning of mining-induced geohazards. Full article

This study investigates vertical surface displacements in an area previously impacted by extensive underground hard coal extraction, specifically focusing on the closed “Kazimierz-Juliusz” mine in the Upper Silesian Coal Basin (Poland). The cessation of mining operations and formal decommissioning do not necessarily signify the termination of ground instability; rather, the discontinuation of mine water pumping triggers a progressive groundwater rebound within the rock mass. This hydrogeological shift leads to a redistribution of stresses in the geological structure, inducing deformation processes that manifest as surface uplift. This research aims to characterize the temporal evolution and magnitude of post-closure surface elevation changes by integrating satellite radar interferometry with conventional geodetic surveys. The analysis, spanning a 28-month observation period, utilizes both Persistent Scatterer Interferometry (PSInSAR) and European Ground Motion Service (EGMS) data, complemented by precise geometric leveling. The results reveal a low-magnitude deformation process, with detected uplift rates reaching approximately 1 cm/year. The synergistic integration of InSAR-based monitoring and classical geodesy allowed for robust cross-validation, significantly enhancing the reliability of the findings both qualitatively and quantitatively. Full article

Rockfall events are significant natural hazards on fractured rock cliffs, often driven by environmental forcing, including thermal variations that induce stress and fatigue in rocks. This study presents the first application of Ground-Based Interferometric Synthetic Aperture Radar (GB-InSAR) for high-resolution monitoring of sub-millimeter thermally induced displacements on a rock slope. An eight-day pilot experiment conducted at the La Cornalle molasse cliff (Vaud, Switzerland) revealed cyclic displacement signals with a clear 24 h periodicity, identified through Fourier and wavelet analyses, with a mean amplitude of 5 × 10⁻⁴ m. Simultaneously, infrared thermography (IRT) and a weather station recorded rock surface and air temperature variations, allowing a first estimation of the time lag between thermal forcing and mechanical response, with delays of 1–8 h relative to air temperature and 1–6 h relative to solar radiation. An analytical deformation model based on thermal diffusion predicts a daily displacement amplitude of 4.2 × 10⁻⁵ m, highlighting a significant difference with GB-InSAR observations and emphasizing the influence of structural complexity and thermo-hydro-mechanical processes in rock slopes. These results demonstrate the capability of combined high-resolution remote sensing techniques to quantify thermo-mechanical behavior in rock masses and provide a methodological framework for future investigations of rockfall-prone slopes. Full article

The mechanical behavior of laminated elastomeric bearings in service is highly sensitive to ambient temperature, whereas conventional monitoring approaches often fail to accurately capture their temperature-dependent load response. To address this issue, this study proposes a multi-temperature framework for identification and load monitoring of bridge elastomeric bearings. Using a high-precision laser displacement measurement system, six temperature levels were defined from −20 to 30 °C at 10 °C intervals. Room-temperature load–displacement calibration tests, compressive elastic modulus tests under different temperature conditions, and monitoring accuracy validation tests were then systematically conducted. Based on these experiments, the effects of temperature on the mechanical properties and compressive deformation response of the bearing were quantified, and an inverse load-identification model was developed. The results show that the compressive elastic modulus increases markedly with decreasing temperature, reaching a 32.11% increase at −20 °C relative to that at 30 °C. Under the same applied load, the vertical compressive deformation decreases significantly as temperature decreases, with a 27.76% reduction at −20 °C compared with that at 30 °C, indicating a pronounced low-temperature stiffening effect. The proposed inverse load-identification model achieves a maximum relative error of 4.83% over the full temperature range, demonstrating good accuracy and applicability. The proposed methodology provides a practical basis for mechanical-performance evaluation and high-precision monitoring of bridge bearings under complex thermal environments. Full article

To investigate the deformation law of adjacent metro tunnels under the coupling effect of servo supports and deep foundation pit excavation, this study takes an ultra-deep foundation pit adjacent to Hangzhou Metro Line 2 as the research object. A servo support system was adopted for synchronous active loading during excavation, and field monitoring was conducted to analyze the deformation response of existing operating tunnels before and after servo loading. The results indicate that servo loading significantly reduces the rate of increase in tunnel vertical displacement, horizontal displacement, and horizontal relative convergence. It is found that the servo support closest to the tunnel (i.e., the third servo support in the case) exhibits the most prominent control effect—after loading, the vertical displacement rate of the down-line tunnel decreases from −0.04 mm/d to 0 mm/d, and the horizontal displacement rate is reduced by approximately 70%. Moreover, seven days after loading, the horizontal relative convergence rate of the up-line tunnel tends to be 0 mm/d. Servo supports effectively weaken the tunnel’s deformation development during critical stages of ultra-deep foundation pit construction, enabling active and precise control of adjacent operating metro tunnels. Full article

Early-stage landslides and rockfalls are often characterized by very small internal accelerations associated with creep and progressive deformation, which are difficult to capture using conventional surface-based displacement monitoring techniques. To address this, the study presents the design and laboratory validation of a prototype in-mass inertial monitoring device, referred to as a Smart Rock, intended for embedded monitoring of rock mass motion. The developed device integrates low-noise inertial measurements with on-board processing to enable real-time characterization of motion signatures within a moving mass. Two sensing configurations, including a low-noise accelerometer-only configuration and a full inertial measurement unit (IMU) configuration, were implemented to evaluate their relative performance for in-mass motion monitoring. Embedded signal processing approaches suitable for landslide motions were developed to identify quasi-static, step-change, and impact-related motion regimes. Laboratory experiments using a controlled robotic testbed generated repeatable motion scenarios representative of creep-like movement, abrupt displacement changes, and impact events. Results showed that Smart Rock resolved very low-magnitude acceleration signatures on the order of 10⁻⁵ g and distinguished these from higher-energy motion and impact events, with improved signal stability observed for IMU-based configurations. These findings demonstrated the feasibility of in-mass inertial devices for characterizing landslide and rockfall motion in geotechnical applications. These results should be interpreted as proof-of-concept laboratory validation under controlled conditions. Full article

Concrete structures frequently experience sustained loading during service, which may lead to crack propagation and eventual failure. In this study, three-point bending beams with heights of 200 mm and 300 mm were subjected to sustained load levels of 0.82, 0.84, and 0.86 of the peak load. The crack propagation process was monitored using the Digital Image Correlation (DIC) technique to capture full-field displacement and strain distributions. Analysis of the crack opening displacement (COD) and the fracture process zone (FPZ) revealed that concrete exhibits brittle fracture behavior under sustained loading, with the FPZ not fully developed at creep failure. The crack propagation process was further characterized into three stages. In the initial stage, crack development is mainly governed by viscoelastic deformation. In the intermediate stage, both viscoelasticity and the gradual decay of cohesive stresses within the FPZ contribute to crack growth. In the final unstable acceleration stage, crack propagation is dominated by cohesive stress degradation. Importantly, the crack length at creep failure closely matches the corresponding crack length on the descending branch of quasi-static loading, indicating a direct link between time-dependent creep fracture and quasi-static post-peak behavior. These results provide new insights into the time-dependent fracture mechanics of concrete, revealing the evolution of damage under long-term loading. The study emphasizes material behavior, including FPZ development and stage-wise crack propagation, offering a mechanistic understanding of creep fracture beyond the evaluation of measurement techniques. Full article

Interferometric Synthetic Aperture Radar (InSAR) is crucial for monitoring ground displacement, particularly in Pakistan’s capital area, where urban expansion and active geotectonics converge. This study introduces the Consecutive Interferogram Stacking Approach (CISA), a processing framework optimized for near-real-time deformation monitoring using full-resolution Sentinel-1 data from adjacent acquisition pairs. Unlike conventional InSAR techniques that rely on spatial multilooking to suppress phase noise—which sacrifices spatial resolution for computational efficiency—CISA preserves native resolution through sequential interferogram stacking, accepting that short-interval interferograms retain geophysical phase instabilities (including fading signals) inherent to scatterer decorrelation. By minimizing temporal decorrelation through consecutive pairing, CISA enhances interferogram coherence (6–14% improvement) and reduces Root Mean Square Error (RMSE) by approximately 25% compared to conventional multilooked time series, while enabling the computational efficiency critical for operational applications. The framework’s incremental architecture allows velocity updates within hours of new image acquisition—requiring only single interferogram addition rather than complete network reprocessing—making it suitable for rapid-response hazard assessment where latency constraints outweigh the need for long-baseline phase filtering. CISA reveals spatiotemporal subsidence patterns potentially reflecting the influence of fault zone geometry, groundwater fluctuation, and urbanization, with full-resolution analysis delineating linear deformation patterns spatially consistent with blind fault traces through multi-directional displacement modeling. These findings demonstrate that operational monitoring of geohazards can be achieved through strategic trade-offs between processing latency and geophysical noise suppression, providing actionable intelligence for infrastructure risk management in tectonically active urban environments. Full article

Giant cantilevered tree-shaped steel structures are highly susceptible to cumulative deformation and geometric deviation during staged construction due to their complex spatial configuration, long cantilever characteristics, and nonlinear load transfer mechanisms. To address these challenges, this study investigates deformation monitoring and control of such structures based on 3D laser scanning, taking the “Tree of Life” project as a representative case. A high-precision full-field monitoring system is established to acquire multi-stage point cloud data throughout the construction process. The collected data are registered with the BIM model to quantify spatial deviations and track the deformation evolution of key structural components. Meanwhile, a staged preloading–unloading strategy is implemented to simulate operational loads, reconstruct load transfer paths, and regulate structural deformation during construction. Based on continuous field measurements, the deformation characteristics of different structural regions, including ring beams, rotating platforms, and trunk–branch systems, are systematically analyzed. The results indicate that the structure exhibits a pronounced global torsional deformation pattern. The displacement of ring beams ranges from 40.35 mm to 80.15 mm, while the maximum local displacement reaches 131.37 mm in geometrically complex regions, primarily attributed to the coupling effects of complex geometry, long cantilever action, stiffness discontinuity, and load concentration. Furthermore, deformation exhibits a progressive and stage-dependent accumulation pattern under sequential loading–unloading processes. The proposed monitoring and control approach achieves millimeter-level accuracy and enables effective feedback for construction adjustment and deviation mitigation. The integration of 3D laser scanning with staged load regulation provides a reliable technical framework for deformation monitoring and control of complex cantilevered steel structures. While the findings are based on a single complex project, further validation on additional cases is required to fully establish the general applicability of the proposed framework, although its integration of 3D monitoring, BIM registration, and staged load regulation suggests potential transferability to other large-scale cantilevered steel structures with similar geometric complexity. Full article

Subgrade collapse threatens coastal infrastructure under harsh environments, where deterioration accelerates deformation and failure risk. Accurate prediction is essential, yet traditional monitoring suffers from low informatization and delayed response. Thus, this paper presents a Micro-Electro-Mechanical Systems (MEMS)-based intelligent perception-driven method for subgrade collapse deformation prediction to improve the level of intelligence in subgrade collapse monitoring and prediction. Firstly, a hierarchical prediction framework is established based on subgrade deformation monitoring scenarios, consisting of an intelligent perception layer, a collapse deformation prediction layer, and a functional application layer, with the functions of each layer systematically defined. Secondly, two key technologies involved in the proposed framework, including MEMS data cleaning and time-series feature extraction, as well as the deformation prediction model, are identified and corresponding solutions are developed. Finally, a linear sliding rail experiment and a subgrade collapse model test are conducted to validate the feasibility and effectiveness of the proposed method. The results indicated that effective MEMS data cleaning was achieved through Leave-One-Out Encoding (LOOE) encoding, missing value imputation, and normalization. Accurate time-series feature representation was obtained by combining seismic parameter extraction with a sliding window strategy. The improved the improved Long Short-Term Memory–Back Propagation (LSTM-BP) model model achieved accurate prediction of collapse displacement, with an accuracy of 95.56%. The proposed MEMS-based intelligent perception method accurately captured the evolution trend and spatial heterogeneity of subgrade collapse deformation, and the results can be used to support and guide early warning of subgrade collapse, providing technical support for the safety and durability management of coastal and offshore infrastructure under harsh environmental conditions. Full article