Field Monitoring Data Research Articles

Research PIV-based model on subsidence caused by coal mining

The subsidence caused by coal mining could cause the destruction of roads and houses, and even the failure of infrastructures. Understanding of the mechanism of coal mining subsidence may provide early protecting to infrastructures on coming failure, but dynamic analysis of subsidence due to coal mining is currently needed. In this study we apply particle image velocimetry (PIV) method to reveal strata movement and subsidence according to the prototype and indoor physical model similarity experiment of Henan. Our result shows magnitude of the subsidence of overlying strata during the coal mining at different excavation thickness, that more coal mining thickness may produce more subsidence, and that shallower coal may cause more significant subsidence. Our result suggests that further PIV test combined with field monitoring data may be an effective measure to study subsidence mechanism and pattern helping to predict disaster caused by subsidence.

Deep learning-based approach for identifying vortex-induced vibrations in stay cables

Due to variations in wind speed profiles along the length of bridge stay cables, vortex-induced vibrations (VIV) exhibit multimodal characteristics, presenting challenges for VIV identification. Currently, the VIV identification is concentrated on the stable stage of VIV, lacking an available early warning system for detecting the initial developing stage of VIV. In this study, a deep learning-based approach that integrates energy distribution ratio features derived from frequency band wavelet packet decomposition to recognize VIV of stay cable was proposed. Firstly, vibration characteristics induced by vortices in cable-stayed bridges were analyzed based on field monitoring data from the bridge health monitoring system, aiming to propose suitable feature indicators for VIV identification. Secondly, using root mean square as label classification, a deep learning model was constructed, incorporating convolutional neural networks, long short-term memory networks, and attention mechanisms. Finally, four different stages in the evolution of stay cables VIV were identified utilizing field monitoring datasets to analyze the optimal parameter. Meanwhile, effective early warning recognition was achieved through the classification and recognition of confusion matrix. This study provides technical support for early warning systems and structural condition assessment concerning bridge stay cable VIV.

Field observation and cause investigation of low-frequency cable vibrations in a cable-stayed bridge

Considerable levels of stay cable vibration in cable-supported bridges pose significant challenges for safety, operation, and maintenance. An accurate understanding of the specific causes and types of vibration is essential for effectively addressing this problem with an optimal design for mitigation measures. This study aims to investigate the cause of an extraordinary low-frequency vibration that occurred at a stay cable by employing comprehensive methodologies. The modal properties and vibrational characteristics of cable vibrations were first obtained through finite element modeling, operational modal analysis, and vision-based displacement measurements. Subsequently, the primary cause of low-frequency vibrations was investigated using field observations and wind tunnel tests. Field-monitoring data revealed that stay cables were excited by small deck vibrations. The critical wind speeds at which deck vibrations occurred in a wind tunnel experiment were aligned with the ranges of wind speeds that produce low-frequency cable vibrations, which confirmed that these two phenomena are manifested under similar wind conditions. A calculated support excitation amplitude, determined via the use of an empirical equation, exhibited consistency with vision-based measured displacement obtained in field experiments. These findings underscore the potential risk of support excitation between minor deck vibrations and cables, which provides valuable insights that could mitigate cable vibrations.

Probabilistic back analysis of reservoir landslide considering hydro-mechanical coupled observations

Precisely assessing statistical parameters to characterize spatial soil variability presents a significant challenge in probabilistic slope stability analysis, primarily due to inherent soil uncertainties and limited field-specific data. Probabilistic back analysis, recognized as an effective and reliable technique, offers a rational method for utilizing observational data to invert parameters. Nevertheless, previous investigations into parameter inversion for slope stability analysis have seldom considered the coupling of hydro-mechanical characteristics in reservoir landslides. This study proposes a novel integrated Bayesian framework to perform back analysis of reservoir landslides, incorporating the spatial variability of hydro-mechanical parameters. Within this framework, a hypoplastic constitutive model is developed to characterize the step-like deformation of the reservoir slope. The posterior knowledge of the saturated permeability coefficient and shear strength parameters is obtained by collecting field monitoring data of the underground water level and ground displacement. The Maliulin landslide, located in the Three Gorges Reservoir area of China, is used as an illustrative example to validate the proposed framework through back analysis of spatially variable soil parameters and probabilistic stability analysis. The results demonstrate that the proposed Bayesian updating framework significantly reduces the uncertainties associated with statistical values of soil parameters, providing more accurate and reasonable updated soil parameters for probabilistic slope stability analysis.

Custom integration of a magnetic-field monitoring system into a 32-channel MRI head coil.

Customizing a Siemens 32-channel coil for use in a Philips 3T MRI system with incorporated magnetic field probes for collecting high-quality MRI and magnetic-field monitoring data concurrently. The development process of the custom coil involved several (iterative) phases. Standard temporal SNR and B1 + data were collected with the 32-channel Siemens and for reference the 32-channel/8-channel Philips head coils before and afterthe custom coil was made compatible with the 3T Philips Achieva system, and magnetic field probes were installed into it along with ancillary electronics around it. Quality assurance tests were conducted in each of the build phases to ensure that the modifications did not affect MRI or field-monitoring data negatively. To test the finished custom coil, we collected high angular resolution diffusion imaging (HARDI) datasets on a spherical silicon oil phantom both with and without concurrent field monitoring and a 32-channel Philips coil without concurrent field monitoring, where the latter two served as reference scans to assess the improved performance of the custom coil with field monitoring. Similar HARDI-MRI data were also collected in vivo with the finished custom coil together with field monitoring data. The custom coil provided excellent temporal SNR especially at the edges where cortical gray matter is expected. When using concurrent field monitoring in HARDI acquisitions, the custom coil alleviated ghosting artifacts in phantom data and provided in vivo images with 1.4-mm isotropic resolution. The custom MRI coil with integrated magnetic-field monitoring probes provided improved imaging performance.

Insights into the shallow landslide mechanism of expansive soil slope induced by freeze-thaw cycles and snowmelt infiltration

For rigorous understanding the shallow landslide mechanisms and deformation characteristics of expansive soil slopes, a comprehensive in-situ monitoring platform is established. Triaxial creep tests and microstructure analysis with scanning electron microscopy (SEM) are also conducted on expansive soil samples obtained from Binxi station. Field monitoring data indicates that freeze-thaw (F-T) cycle and snowmelt infiltration significantly increase the creep deformation of expansive soil slope during spring melting period. Due to the influence of F-T cycle and snowmelt infiltration, more soil grains are involved in the shear deformation contributing to a large, localized shearing. Additionally, the microstructural analysis shows that F-T cycle influence the relationship between expansive soil grains that gradually change from face-face contact to point-face contact or edge-edge contact form. The shallow landslide mechanisms of expansive soil slope are revealed from creep deformation and microstructure characteristics of soils after the F-T cycle and snowmelt infiltration, which can be summarized into two stages, namely, the snowfall accumulation state and snow melt-shallow infiltration stage. These results can serve as a good reference for the prevention of expansive soil slopes in seasonally frozen regions.

Vibration response of piles at different distances induced by shield tunneling in hard rock strata

Excavation of subway tunnels in hard rock generates strong vibration waves that pose potential risks to the stability of surrounding structures. In this study, the discrete element method-finite difference method (DEM-FDM) coupling was adopted to build the model of tunnel structure-rock-pile, which was validated by field monitoring data. Then, the vibration response of piles under various pile-tunnel spacings was analyzed, revealing the occurrence of vibration peak rebound phenomena within certain distance ranges. The range of vibration effects was categorized. Furthermore, in shield tunneling construction, the energy induced by vibrations was mainly concentrated within the 50 Hz range. Low-frequency vibrations result in a wider effect range. The study also demonstrated that within a 1d (tunnel diameter) range of the pile-tunnel spacing, the vibration induced by shield tunneling construction had a more significant effect. As the pile-tunnel spacing increased, the piles transitioned from being subjected to bending forces to experiencing bending-shear forces. Finally, the vibration effects on the existing piles were evaluated under field working conditions. It also provided suggestions for construction based on the effects and laws of the pile dynamic response.

A diffusion model of explosion gas under airflow diversion during ventilation of a bifurcated tunnel

In this paper, the bifurcation tunnel in the Yue Long Men Tunnel (Chengdu-Lanzhou Railway, Sichuan Province, China) is used as the research object. Based on the field monitoring data, CFD is used to simulate the explosive gas diffusion process of explosive airflow during the bifurcation tunnel ventilation diversion process, and the effects of different bifurcation angles θ and cross-sectional area ratios s on the diversion flow field are compared. The results show that: (1) Under the control of a single factor, θ and s affect the flow field characteristics after shunt by changing the position of the eddy current in the main tunnel. Varying the bifurcation angle and cross-sectional area ratio increases the ventilation efficiency by up to 9.1% and 14.9%, respectively. (2) The locations of vortices are influenced by θ and s to different extents, and the more forward the locations of vortices in the bifurcated structure, the weaker the influences on explosive gas diffusion in the rear space; (3) Some airflows deflect after diversion and their velocity is influenced by s. An appropriate decrease of s is conducive to the discharge of explosive gas from the transverse tunnel. The research content can provide a basis for tunnel blasting and excavation ventilation schemes.

Optimizing Grouting Parameters to Control Ground Deformation in the Shield Tunneling

In urban shield tunneling, reducing the disturbance of underground construction to the surrounding environment is important for both tunnel engineers and researchers. Among other factors, the quality of synchronous grouting is one of the crucial factors affecting the safe construction of shields. In order to determine a reasonable grouting pressure and grout amount during shield construction, the relationships among synchronous grouting pressure, grout amount and shield chamber pressure are analyzed using field monitoring data. Based on the tunnel face pressure and the ultimate yield conditions of the soil at the gap edge, a method for calculating the grouting pressure considering the overburdening load of the tunnel was proposed. Then, by linking the grout amount and the grouting pressure, an accurate calculation method for the simultaneous grout amount in shield construction was proposed. These methods were then used in the construction of the Jurong shield tunnel. The results show that the adopted grouting pressure and grout amount calculated by the proposed method, which considered the change of the overburdening load of the tunnel, can well control the ground deformation caused by the shield construction and significantly reduce the uneven settlement of the surface buildings. The proposed methods in this paper may provide a reference for other shield construction projects.

ANN-Based Bridge Support Fixity Quantification Using Thermal Response Data from Real-Time Wireless Sensing.

Bridges are critical infrastructures that support our economic activities and daily lives. Aging bridges have been a major issue for decades, prompting researchers to improve resilience and performance through structural health monitoring. While most research focuses on superstructure damage, the majority of bridge failures are associated with support or joint damages, indicating the importance of bridge support. Indeed, bridge support affects the performance of both the substructure and superstructure by maintaining the load path and allowing certain movements to mitigate thermal and other stresses. The support deterioration leads to a change in fixity in the superstructure, compromising the bridge's integrity and safety. Hence, a reliable method to determine support fixity level is essential to detecting bearing health and enhancing the accuracy of the bridge health monitoring system. However, such research is lacking because of its complexity. In this study, we developed a support fixity quantification method based on thermal responses using an Artificial Neural Network (ANN) model. A finite element (FE) model of a representative highway bridge is used to derive thermal displacement data under different bearing stiffnesses, superstructure damage, and thermal loading. The thermal displacement behavior of the bridge under different support fixity conditions is presented, and the model is trained on the simulated response. The performance of the developed FE model and ANN was validated with field monitoring data collected from two in-service bridges in Connecticut using a real-time Wireless Sensor Network (WSN). Finally, the support stiffnesses of both bridges were predicted using the ANN model for validation.

Over 25-year monitoring of the Tsing Ma suspension bridge in Hong Kong

AbstractBridges in service are subjected to environmental and load actions, but their status and conditions are typically unknown. Health monitoring systems have been installed on long-span bridges to monitor their loads and the associated responses in real time. Since 1997, the Tsing Ma suspension bridge in Hong Kong has been the world’s first of the type equipped with a long-term health monitoring system. For the first time, this study reports the first-hand field monitoring data of the bridge from 1997 to 2022. The 26-year data provide an invaluable and rare opportunity to examine the long-term characteristics of the loads, bridge responses, and their relationships, thereby enabling the assessment of the bridge’s load evolution and structural condition over time. Results show that traffic loads have remained stable after 2007, highway vehicles kept increasing until the COVID-19 pandemic in 2020, the annual maximum deck temperature continued to increase at a rate of 0.51 °C/decade, typhoon durations increased by 2.5 h/year, and monsoon speeds decreased and became dispersed and variable. For the bridge responses, deck displacement is governed by the varying temperature. Natural frequencies in the past 26 years were almost unchanged. The overall condition of the bridge is very satisfactory. Current status and recent update of the health monitoring system are also reported. Lastly, prospects of bridge health monitoring are discussed. This study is the first to report the over one-quarter century status of a structural health monitoring system and the behavior of a long-span suspension bridge. This research provides a benchmark for many other bridge monitoring systems worldwide.

Monitoring data motivated health condition assessment of cement concrete pavements in field based on FBG sensing technology

Health condition of cement concrete pavements in field is difficult to characterize due to the random action of traffic loads and environmental variations. It is also difficult to accurately get the deformation merely based on theoretical or simulation analysis, for the heterogeneous material and complicated interfacial bonding properties of multilayered concrete pavements. Therefore, in situ health monitoring is particularly significant for structural condition assessment. To contribute this topic, improved fiber Bragg grating sensors have been designed and embedded in the two-layered pavement to measure the strain, deformation, and temperature. Deformation information of the cement concrete pavement under environmental action in about 3 years has been analyzed. Data analysis indicates that the longitudinal and transverse deformations of the pavement have behaved in nonuniform distribution, and local points suffered from the large tensile strains. The vertical measurement data declared that local interfacial micro void defects existed in the soil base and kept stable during the following 3 years. The temperature variation inside the pavement was highly correlated with the environmental temperature, and the variation amplitude was relatively smaller than the environmental temperatures, with the maximum amplitude smaller than 4°C. The load and temperature transfer principles in different layers have also been checked. Generally, the monitoring data in field from the year 2020 to year 2023 have declared that the concrete pavement has good performance to resist the combined action of traffic loads and environmental temperatures. The study can help to understand the actual structural performance of cement concrete pavements in field based on the optical fiber sensing system.

Research on the technology of uniformly injecting nitrogen into the porous long pipes in the gob of the gob-side entry retaining mining mode with roof cutting and pressure relief

The implementation of the Gob-Side Entry Retaining Mining Mode with Roof Cutting and Pressure Relief (GERRCPR) results in the gob connecting to the retaining roadway, creating an open space that causes significant air leakage and increases the risk of spontaneous combustion. A study was conducted during the implementation of the GERRCPR in the Xiaonan Coal Mine N1-1502 working face to investigate spontaneous combustion characteristics, along with fire prevention and extinguishing measures. To analyze gob airflow, Computational Fluid Dynamics (CFD) was employed to collect data on airflow conditions, O2 concentration, and temperature. Based on this, this study focuses on exploring the effects of nitrogen injection treatment under various rates and positions to optimize parameters for buried pipe nitrogen injection. Results indicated that within the GERRCPR, air leakage in the gob increased, leading to an increase in O2 concentration, expansion of the oxidation zone, and an elevated risk of spontaneous combustion. Air leakage primarily occurred from the retaining roadway and the working face near the intake-air roadway, peaking at a retaining roadway length of 500 m, with a flow rate of 226 m3/min. Following nitrogen injection treatment, the oxidation zone was significantly reduced, with optimal treatment achieved at a nitrogen injection depth of 70 m and a rate of 600 m3/h. Field monitoring data showed that the inertization measure of using porous long pipes, a nitrogen injection spacing of 30 m, and a nitrogen injection rate of 600 m3/h significantly decreased the O2 concentration within the gob. This reduction meets safety production requirements and outperforms the effectiveness of traditional buried-pipe nitrogen injection methods, thereby validating the simulation accuracy. Understanding the laws governing spontaneous coal combustion in the GERRCPR and enacting preventive measures for nitrogen injection can improve safety standards in mining operations. This proactive approach can effectively prevent spontaneous coal combustion accidents, resulting in substantial social benefits.

On the multi‐parameters identification of concrete dams: A novel stochastic inverse approach

AbstractThis paper introduces a novel stochastic inverse method that utilizes perturbation theory and advanced intelligence techniques to solve the multi‐parameter identification problem of concrete dams using displacement field monitoring data. The proposed method considers the uncertainties associated with the dam displacement monitoring data, which are comprised of two distinct sources: the first is related to stochastic mechanical properties of the dam, and the second is due to observation errors. The displacements at different measuring points generated by dam mechanical properties exhibit spatial correlation, while the observation errors at different points can be considered statistically random. In this context, the inversion formulas are derived for unknown stochastic parameters of the dam by combining perturbation equations and Taylor expansion methods. An improved meta‐heuristic optimization method is employed to identify the mean of stochastic parameters, while mathematical and statistical methods are used to determine the variance of stochastic parameters. The feasibility of the proposed method is verified through numerical examples of a typical dam section under different conditions. Additionally, the paper discusses and demonstrates the applicability of this method in a practical dam project. Results indicate that this method can effectively capture the uncertainty of dam's mechanical properties and separates them from observation errors.

A Prediction Method for the Average Winding Temperature of a Transformer Based on the Fully Connected Neural Network

The average winding temperature of a transformer (AWTT), serving as a key indicator for assessing the running state of the transformer, is of utmost importance in determining a transformer’s electrical properties and the insulation longevity of the transformer. An accurate prediction of AWTT is essential for ensuring the safe operation of the transformer. A novel method for predicting AWTT is introduced based on the analysis of field monitoring data. Firstly, the thermal characteristics and operational mechanisms of oil-immersed transformers are examined. Secondly, a factor analysis model is developed to streamline the network structure, accounting for the strong correlations among ambient temperature, load current, and top oil temperature. Thirdly, the independent temperature factor and load factor are extracted as pivotal features, and then input into the fully connected neural network to predict AWTT. Through a case study involving a 110 kV/10 kV oil-immersed transformer, the results show that the proposed method reduces redundant correlation information compared to traditional methods and improves the prediction accuracy of AWTT, establishing a foundation for further transformer state assessments.

Variation of segment joint opening of underwater shield tunnel during long operational period

Segment joint is the main water leakage channel in underwater shield tunnels, and joint deformation influences tunnel waterproof capacity greatly. Real-time structure health monitoring is a great way to investigate the joint opening and to offer early warnings for abnormality, such as data outlier and joint properties degradation. This study investigated the variation of joint opening, provided early warning indexes and evaluated the joint mechanical properties degradation using the field monitoring data of an underwater shield tunnel over 10 years, which is rarely seen in the literature. Study results show that: (1) Field monitoring data reveals that the distribution of joint opening increments obeys a heavy-tailed distribution rather than the normal distribution. The exponential distribution model and the log normal distribution model can fit the longitudinal joint increments and circumferential joint increments much better. (2) The early warning index is determined based on the statistic theory and 0.999 quantile is set as the warning value. The obtained warning values of the studied underwater tunnel are 0.005 mm and 0.08 mm for the longitudinal and circumferential joint respectively. The small warning value means that small abnormality can be identified and the early warning would be more efficient. (3) A mechanical model is proposed to evaluate the joint mechanical properties degradation based on monitoring data. Results show that normal stiffness of circumferential joint decreases from 18.3 GPa/m to 14.7 GPa/m. Results of this study provides valuable reference for early-warning and joint degradation evaluation of under water shield tunnel.

Excavation Method Comparison and Optimization for a Super Large Cross-Section Tunnel

Characterized by long spans, low aspect ratios, and intricate construction sequences, super-large cross-section tunnels present substantial construction risks. Therefore, the selection of the optimal excavation method and construction sequence is crucial for ensuring the safety of tunnel construction and minimizing project costs. This paper takes a super large transverse-section highway tunnel as a case study, employing field monitoring data combined with ABAQUS software to analyze the stress and deformation of surrounding rock and support structures under different excavation methods. The findings reveal that the deformation of surrounding rock and support structures excavated by the Double-Side Drift Method is smaller than those caused by the three-benching seven-step method and the CRD excavation method. Nevertheless, the significant stresses of surrounding rock and support structures are released by the Double-Side Drift Method, leading to potential stress concentrations. Thus, it is necessary to ensure the rapid completion of early support and quick sealing of the tunnel. Furthermore, the sixth process achieves smaller deformation (including arch displacement and surface settlement) of the tunnel, a shorter construction period, and lower economic costs when compared to other construction processes. Consequently, it can obviously be concluded that both the Double-Side Drift Method and the sixth construction process stand out as the most appropriate choices for excavating super large cross-section tunnels. The insights obtained from this study provide theoretical guidance for the design and construction of similar tunnel projects.

Study on Deformation Control of Road-Deep Foundation Pit Passing under Elevated Subway Bridge

This paper focuses on the application of pile foundation underpinning technology in a deep foundation pit of a subway Viaduct Project in Beijing. The study aims to address the engineering characteristics of the project, including a large number of new piles, a wide span of underpinning abutment, a long length of deep foundation pit, and a wide range of influences. This research utilizes field monitoring and numerical simulation methods to investigate the pile foundation underpinnings. The impact and management of road-deep foundation pit construction are considered, as well as their combined effect on subway viaducts and track structures. The primary accomplishments are as follows: (1) By analyzing the data from on-site deformation monitoring, it is evident that the pier exhibits maximum vertical deformation and maximum transverse deformation at the same location. The measuring locations are specifically situated on Pier 7# at the pile foundation underpinning. The maximum vertical and transverse deformations of the track are directly proportional to the maximum deformation of the pier. (2) By comparing the numerical simulation results with the field monitoring data, it is observed that although there is some discrepancy between the two, the deformation trend is largely consistent. This suggests that the numerical simulation analysis method is effective in reflecting the deformation of the bridge and track. (3) Through the numerical model and changing the values of the retaining structure parameters, the sensitivity of the pier deformation near the road foundation pit to the retaining structure parameters is systematically analyzed. The sensitivity of the pier deformation to the foundation pit parameters is as follows: the embedded depth insertion ratio of the retaining pile > the diameter of the retaining pile > the pile spacing.

Simulation research on blasting of an open pit mine slope considering elevation conditions and slope shape factors

This study established a numerical model that considers elevation conditions and slope shape factors by the modified Sadovsky formula to analyze the vibration attenuation law of open-pit slopes under blasting vibration conditions. The blasting excavation of a slope in a certain open-pit mine in Yunfu, Guangdong, is selected as an example. Using a numerical model that considers elevation conditions and slope shape factors by the modified Sadovsky formula, a triangular pulse load was utilized to approximate the time-history characteristics of explosion vibration with FLAC3D software. The simulation results showed the radiation range of the blasting vibration seismic wave. By comparison with field monitoring data, the numerical model that considers the slope shape factor had a relative error of ∼10%, while the numerical model that disregards the slope shape factor had a relative error of ∼15%. The relative accuracy of the calculation results of the new numerical model is higher and closer to the actual attenuation law of blasting particle vibration speed, providing more reliable results for slope stability assessment. The peak particle velocities obtained from the numerical simulation results were generally higher than the field monitoring data. These discrepancies might be attributed to the use of simplified models that disregard the discontinuous structural planes within the rock mass. This study provides an important reference for the stability assessment of open-pit slopes under blasting vibration conditions, offering guidance for improving slope stability assessment and related engineering practices.

Dynamic response of a permafrost railway subgrade with 3D train-track-subgrade-ground model simulations

Studying train-induced response characteristics is essential for safely operating permafrost railway subgrades. A three-dimensional thermal-mechanical coupling nonlinear dynamic model of train-track-subgrade-ground relationships was established to analyse the train-induced dynamic stress, acceleration and stress path characteristics of a permafrost railway subgrade, and field monitoring data were used to verify this model. The differences between the 2D and 3D models are also discussed, along with the seasonal changes, train speed, axle load, and train type affecting permafrost subgrades. The main results are as follows. First, the vibration load significantly impacts the subgrade 6 m below the sleeper, producing distinct vertical dynamic stress waves due to the wheels and bogies. Dynamic compression stress dominates the subgrade and is influenced by the train structure, speed, and sleeper spacing. While the 2D model tends to underestimate the dynamic stress in shallower layers, it concurs with the 3D model in deeper subgrade dynamics within a 10% margin of error. Then, the principal stress axis of the subgrade soil rotates synchronously with train movements, exhibiting regular stress paths in the YZ plane (longitudinal section) with depth-dependent variations in the stress cycles and deviatoric stress. Finally, predominantly originating from sleeper-induced vibrations, the subgrade vibration acceleration varies with the train speed, sleeper spacing, and season and is most pronounced in the vertical direction. This study provides theoretical guidance for the vibration response of permafrost subgrades on the Qinghai-Tibet Railway (QTR).