Subsidence Monitoring Research Articles

Settlement prediction of immersed tunnel considering time-dependent foundation modulus

The focus of immersed tunnel research has primarily revolved around settlement monitoring or prediction. However, there has been a lack of discussion regarding the time-dependent effects on settlement prediction, which could lead to obvious misjudgments in subsequent maintenance work. This paper addresses this issue by applying the physics-informed machine learning (PIML) algorithm to conduct an inverse analysis of the foundation modulus of the Hong Kong-Zhuhai-Macau Bridge (HZMB) tunnel, thereby identifying its variation tendency with time. The proposed time-dependent expression of foundation modulus demonstrates that the time-dependent effect is related to both post-construction settlement and the accumulation of back silting, which is significant and could persist throughout the entire service life of the HZMB tunnel. In further studies on settlement prediction for the HZMB tunnel, the results show that errors in prediction can exceed 30 mm at certain monitoring points. This error can be mitigated by considering the time-dependent effect, thereby significantly enhancing the reliability of predictions.

High-precision FBG-based sensor for soil settlement monitoring: A comparative study with magnetic settlement gauges and PIV technique

The primary objective of layered settlement monitoring is to detect subsidence issues in soil or foundational structures, in order to implement appropriate measures for ensuring the safety and stability of engineering projects. Conventional monitoring techniques have problems such as errors in manual readings, high costs, susceptibility to interference, and low levels of automation. A layered soil settlement sensor based on fiber Bragg grating (FBG) technology is proposed in this study. This sensor utilizes an equal-strength beam as an "intermediate bridge" to make the FBG sensor respond. The sensor is prepared by the laboratory's 3D fused deposition modelling (FDM) and calibrated by applying displacement loads through a fine-tuning platform. The sensitivity coefficient is 0.068 nm/mm, and the correlation coefficient exceeds 0.99. Finally, the sensor exhibited high precision when compared to measurements obtained from magnetic settlement gauges and particle image velocimetry (PIV). The discrepancies between the measurement outcomes of the sensor and the actual values of soil settlement does not exceed 3.33%.

Sensitivity of granular pile dimension parameters to deformation response of soft ground under building load

Granular pile is one of the proven soil improvement mechanisms applied especially for reinforcement of compressible soils supporting light structures. The improvement performance of granular piles is influenced by various factors including the dimension parameters (length, spacing and diameter of the piles). The influence of these three dimension parameters on deformation response of reinforced weak soil has widely been reported. However, the most influential parameter affecting deformation of the weak soil has not been clearly identified. Apparently, these dimension parameters do not equally influence the performance of stone columns in lessening soil deformation. Hence, comparative analysis was carried out in the current study to find out the dimension parameter to which deformation of stone column reinforced weak ground is most sensitive. Finite element based parametric numerical analysis was conducted to simulate the weak ground reinforced with a group of granular piles supporting light weight building. For the parametric study, five dimensions for each parameter (diameter, spacing and length) were considered. The dimensions were purposely varied by uniform percentage increase. Field settlement monitoring data was used to track deformation response of the site and validate the finite element results. The numerical analysis reveals that the simulation results have good agreement with the field settlement monitoring data. From sensitivity view point, column spacing was found to be the most controlling and influential parameter affecting deformation of the reinforced weak soil. Similarly, column length is the dimension parameter to which ground deformation is least sensitive.

An Evaluation of Treatment Effectiveness for Reclaimed Coral Sand Foundation in the South China Sea

Mega land reclamation projects have been carried out on the coral reefs in the South China Sea. Coral sand was used as a backfill material through hydraulic filling, with fill heights ranging from 6 to 10 m. To enhance foundation stability, vibro-flotation and impact rolling have been employed. However, the uneven distribution of coral sand, irregular particle shape, lower single-particle strength, and paucity of engineering cases for reference have posed challenges in evaluating the effectiveness of these foundation treatments. In this study, the effectiveness of vibro-flotation and impact rolling on the densification and bearing capacity of coral sand foundations has been investigated. In situ tests, including the plate load test, California Bearing Ratio (CBR) test, density measurements, dynamic penetration test (DPT), and settlement monitoring, were conducted at four distinct zones: an untreated zone, a vibro-flotation zone at a 5 m depth, a vibro-flotation zone at a 10 m depth, and an impact rolling zone. The findings suggest that coral sand exhibits promising characteristics for foundation construction. Seepage and self-weight consolidation following land reclamation formation significantly enhance the compaction degree of the coral sand foundation, thereby meeting the requirements for areas with lower bearing capacity demands. Both vibro-flotation and impact rolling techniques could significantly enhance the foundation-bearing capacity, with marginal differences between them. Since the machinery is simple and construction speed is quick, the impact rolling method is considered to be the most efficient for the treatment of coral sand foundation. The DPT results suggest that the reinforcement effect of both vibro-flotation and impact rolling on the deep foundation is not as substantial as the surface layers. This study provides valuable insights into optimizing foundation treatments for land reclamation projects on the coral reefs.

Evaluating the Safety and Control Scheme of Coastal Railway Using Land Subsidence Coupling Model

Uneven settlement caused by excessive exploitation of groundwater will seriously affect the smooth operation of high-speed railways. This study takes the Jinwei high-speed railway as an example to explore the development characteristics and distribution of groundwater and land subsidence along the railway under the influence of groundwater exploitation. Based on the comprehensive analysis of hydrogeological conditions and soil characteristics, a three-dimensional coupling model of groundwater seepage and land subsidence was established. The groundwater flow field and land subsidence along the railway under different mining schemes were quantified, and the prevention and control scheme to ensure the smooth operation of the high-speed railway was determined. The results show that the coupling model verified by groundwater and subsidence monitoring data can better simulate the development process of land subsidence. The subsidence center along the railway line is located between DK315 ∼ DK327, with a predicted maximum subsidence rate of 16.36 mm/a. The second most serious area is located between DK295 ∼ DK309, with a maximum subsidence rate of 12.21 mm/a. The maximum ban on mining along the railway is extended to 350 m at the section DK295 ∼ DK309, and to 450 m at the section DK315 ∼ DK325, which can minimize the impact of land subsidence on the high-speed railway.

Vertical Displacement Measurement in a Slow-Moving Sinkhole Using BOTDA

The effectiveness of monitoring and early-warning systems for ground deformation phenomena, such as sinkholes, depends on their ability to accurately resolve the ongoing ground displacement and detect the subtle deformation preceding catastrophic failures. Sagging sinkholes with a slow subsidence rate and diffuse edges pose a significant challenge for subsidence monitoring due to the low deformation rates and limited lateral strain gradients. In this work, we satisfactorily illustrate the practicality of the Brillouin optical time domain analysis (BOTDA) to measure the spatial-temporal patterns of the vertical displacement in such challenging slow-moving sagging sinkholes. To assess the performance of the approach, we compare the strain recorded by the distributed optical fiber sensor with the vertical displacement measured by high-precision leveling. The results show a good spatial correlation with the ability to identify the maximum subsidence point. There is also a good temporal correlation with the detection of an acceleration phase in the subsidence associated with a flood event.

Land Subsidence Monitoring and Analysis in Heifei Based on Sentinel-1A Data

Land Subsidence Monitoring and Analysis in Heifei Based on Sentinel-1A Data

Monitoring of Subsidence in Berezniki City (Perm Krai) by SAR Interferometry. Method of Persistent Scatterers

Monitoring of Subsidence in Berezniki City (Perm Krai) by SAR Interferometry. Method of Persistent Scatterers

Monitoring and Analysis of Land Subsidence in Cangzhou Based on Small Baseline Subsets Interferometric Point Target Analysis Technology

Cangzhou is located in the northeast part of the North China Plain; here, groundwater is the main water source for production and living. Due to the serious regional land subsidence caused by long-term overexploitation of groundwater, the monitoring of land subsidence in this area is significant. In this paper, we used the Small Baseline Subsets Interferometric Point Target Analysis (SBAS-IPTA) technique to process the Envisat-ASAR, Radarsat-2, and Sentinel-1A data and obtained the land subsidence of Cangzhou from 2004 to 2020. Additionally, we obtained winter wheat distribution information in Cangzhou using the Pixel Information Expert Engine (PIE-Engine) remote sensing cloud platform. On this basis, we analyzed the relationship between ground water level, winter wheat planting area, and the response of land subsidence according to the land use type and groundwater level monitoring data near the winter wheat growing area. The results show that during 2004–2020, the average annual subsidence rate of many places in Cangzhou was higher than 30 mm/year, and the maximum subsidence rate was 115 mm/year in 2012. From 2004 to 2020, the area of the subsidence funnel showed a trend of first increasing and then decreasing. In 2020, the subsidence funnel area reached 6.9 × 103 km2. The winter wheat planting area in the urban area showed a trend of first decreasing, then increasing and then decreasing, and it accounted for a large proportion in the funnel area. At the same time, we studied the relationship between the land subsidence rate and the water level at different burial depths and the response of winter wheat planting area. The results showed that the change of confined water level had a stronger response with the other two variables.

Optimal selection of dictionary atoms for sparse dictionary learning of time-varying monitoring data in two-dimensional geotechnical problems

Geotechnical monitoring data (e.g., settlement monitoring data) are often sparsely measured at limited locations, but the corresponding geotechnical quantities of interest (e.g., ground settlement) usually vary in both temporal and spatial dimensions. The sparsely measured monitoring data can be efficiently leveraged under a sparse dictionary learning (SDL) framework, which represents a spatio-temporally varying quantity (e.g., settlement) by a weighted summation of dictionary atoms. However, selection of dictionary atoms in SDL greatly affects the SDL performance, and under-fitting or over-fitting problems are frequently encountered, particularly when dealing with limited monitoring data. To tackle these problems, a knee point-based method is proposed in this study to properly select dictionary atoms for optimizing the SDL performance. The proposed method not only automatically determines dictionary atom IDs and weights, but also strikes a balance between the under-fitting and over-fitting. The proposed approach is illustrated using a real case history of embankments constructed on soft clay in Australia. The proposed approach significantly improves the prediction of time-varying settlements that also spatially vary over a two-dimensional (2D) space (e.g., a vertical cross-section), particularly at subsequent time steps and spatial locations without monitoring data. Effects of the dictionary atom quantity on settlement predictions are also investigated.

Prediction of the Deformation of Heritage Building Communities under the Integration of Attention Mechanisms and SBAS Technology

The protection of heritage building communities is of important historical significance, the occurrence of a landslide is related to the safety and stability of the heritage building, and ground monitoring and forecasting are the key steps for the early warning and timely restoration of the heritage building. This study utilizes remote sensing technology to monitor the ground of a cultural heritage building, and employs a Long Short-Term Memory (LSTM) network for prediction. Firstly, we conducted ground subsidence monitoring within a specific time series of the study area using heritage remote sensing images and SBAS-InSAR technology. Following the subsidence monitoring, and incorporating an attention mechanism, we effectively localized and extracted features of heritage building clusters within the region. This approach efficiently addresses the challenge of feature identification resulting from the dense distribution of buildings and the similarity between various objects. The results indicate that the maximum subsidence rate in the research area reached −60 mm/year, reached a maximum uplift rate of 45 mm/year, and that the maximum cumulative subsidence reached −65 mm. Secondly, for the multi-level, multi-scale, and class-specific objects in remote sensing images, the LSTM network enables adaptive contextual information during deep and shallow feature extraction. This allows for better contextual modeling and the correlation between predicted and actual results reaches a 0.95 correlation, demonstrating the accurate predictive performance of the LSTM network. In conclusion, both LSTM and SBAS technologies play a crucial role in decision-making for heritage buildings, facilitating effective early warning and disaster mitigation.

A Review of Selected Applications of GNSS CORS and Related Experiences at the University of Palermo (Italy)

Services from the Continuously Operating Reference Stations (CORS) of the Global Navigation Satellite System (GNSS) provide data and insights to a range of research areas such as physical sciences, engineering, earth and planetary sciences, computer science, and environmental science. Even though these fields are varied, they are all linked through the GNSS operational application. GNSS CORS have historically been deployed for three-dimensional positioning but also for the establishment of local and global reference systems and the measurement of ionospheric and tropospheric errors. In addition to these studies, CORS is uncovering new, emerging scientific applications. These include real-time monitoring of land subsidence via network real-time kinematics (NRTK) or precise point positioning (PPP), structural health monitoring (SHM), earthquake and volcanology monitoring, GNSS reflectometry (GNSS-R) for mapping soil moisture content, precision farming with affordable receivers, and zenith total delay to aid hydrology and meteorology. The flexibility of CORS infrastructure and services has paved the way for new research areas. The aim of this study is to present a curated selection of scientific papers on prevalent topics such as network monitoring, reference frames, and structure monitoring (like dams), along with an evaluation of CORS performance. Concurrently, it reports on the scientific endeavours undertaken by the Geomatics Research Group at the University of Palermo in the realm of GNSS CORS over the past 15 years.

Coherence Optimization in Polarimetric Subspace of Sentinel-1 for Subsidence Monitoring

Coherence Optimization in Polarimetric Subspace of Sentinel-1 for Subsidence Monitoring

Analysis of monitoring optimization of high-rise building settlement in China

With the continuous advancement of China's economic construction, the population density is increasing, and the construction of high-rise buildings is also constantly advancing. This paper addresses settlement issues related to the construction of tall buildings. The author conducts a comprehensive analysis of the current state of tall buildings in China and explores the causes and negative impacts of settlement. To proactively mitigate settlement in high-rise buildings, the author presents two established monitoring methods based on triangulation. The first method employs fiber optic sensors, while the second utilizes a differential pressure settlement monitoring system. The authors recognize that each method has its own strengths and limitations, underscoring the significance of selecting an appropriate monitoring solution tailored to the specific project's characteristics.

Research to complete software processing settlement monitoring data of constructions in Vietnam

Currently, there are many software for processing settlement monitoring data in Vietnam. However, these softwares still lack some module to calculate the relative deflection settlement (S/L) as well as the lack of modules for building settlement model over time. This article presents the content of establishing a program to calculate relative deflection settlement and building settlement model over time. The results of the article aim to improve the current settlement monitoring software in Vietnam in order to automate the analysis and evaluation of settlement monitoring results.

The solution to improve the quality and reliability of permanent benchmark network for settlement monitoring

Benchmark is a particularly important item that determines the quality of settlement monitoring. However, building a benchmark with a stable height is a very difficult and expensive task. Most of the current benchmarks that are built to monitor the settlement of buildings are not satisfactory for stable heights, thus greatly affecting the quality of settlement monitoring as well as building stability assessment. of the project. In this paper, a new kind of benchmark is proposed that can give a relatively stable elevation but is not too expensive and is completely feasible in condition of Việt Nam.

Mechanical and microstructural evolution of solidified/stabilized heavy metal-contaminated soil under a hydro-chemical-mechanical coupling environment

The long-term effectiveness of Solidification/Stabilization (S/S) under realistic disposal scenarios is a common controversy of its application. This study sought to investigate the evolution of the mechanical properties and microstructure of Pb-Zn-Cd composite contaminated soil solidified/stabilized by cement and fly ash (CSCS) under a hydro-chemical-mechanical coupling environment (HCM). An HCM simulation system was developed to reproduce the simultaneous action of hydraulic, chemical, and stress environments on CSCS. The mechanical and microstructural evolution of CSCS under HCM was assessed using vertical settlement monitoring, unconfined compressive strength (UCS) test, computed tomography (CT), mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR). The increasing environmental acidity induces an increase in vertical displacement and a decrease in UCS. The highest final settlement was 0.96 mm at pH 3 and a pressure of 250 kPa, which was 39.13 % greater than the value at pH 5 and 7. The UCS decreased by 18.54 % after 168 h of HCM treatment at pH 7, while the value reached 45.83 % when the pH was lowered to 3. Seepage contributes to initial hydration as evidenced by an increase in the early E50 of the CSCS. Hydrodynamic scouring and chemical erosion increase the pore size and deteriorate the soil structure, whereas compaction helps to redistribute soil particles, thus improving the structural integrity and uniformity of the CSCS.

Mine Subsidence Monitoring Integrating DS-InSAR with UAV Photogrammetry Products: Case Studies on Hebei and Inner Mongolia

Frequent mining activities create a series of geological and environmental problems resulting in an immeasurable loss of life and property. Adopting effective technologies that monitor the surface subsidence of mining areas reliably and accurately is necessary. Targeting problems associated with conventional distributed scatterers interferometric synthetic aperture radar (DS-InSAR) technology, we propose a DS-InSAR technology integrating unmanned aerial vehicle (UAV) photogrammetry products divided into two key technical contents: generating an external reference digital elevation model (DEM) fused with UAV DEM and refining distributed scatterers candidates (DSCs) fused with an UAV digital orthophoto map (DOM). We selected two mining areas, one in Wu’an, Hebei, and the other in Inner Mongolia, with different surface cover types, mining depths, and topographies as the research area. We used Sentinel-1A SAR images covering a mine in Wu’an from 4 November 2018 to 4 March 2019 and a mining area in Inner Mongolia from 11 June 2018 to 21 October 2018 to compare and analyze the subsidence results. We also combined these results with data from their respective field observation stations to assess accuracy. We could apply DS-InSAR technology integrated with UAV photogrammetry products to the subsidence monitoring of two mining areas with different landforms and mining characteristics. Comparing with the leveling and total station, the experimental results show that the RMSE was reduced by about 2 mm in both mining areas, and accuracy for the Wu’an region improved to a higher degree than Inner Mongolia did. Furthermore, the refinement method of DS eliminated 965 and 2948 lower-quality DSCs in the two mining areas. These demonstrate that our proposed method can effectively improve the accuracy and reliability of subsidence results from two mining areas.

Research on reuse of shield soil dregs on synchronous grouting materials and its application

Shield tunnel construction will produce a large amount of soil dregs. Transporting soil dregs directly to landfills raises costs and CO2 emissions. In this paper, the shield tunnel of Intercity from Shenzhen to Huizhou is taken as an example, based on the special treating agent of shield soil dregs, the soil dregs were prepared as synchronous grouting material. The working performance and mechanical properties of soil dregs grouting material were studied. The optimal dosage of the treating agent was proposed, and the curing mechanism of the soil dregs synchronous grouting material was analyzed. The soil dregs grouting material was applied to practical engineering, and the application effect was verified by surface subsidence monitoring. The results showed that the setting time, bleeding rate, stone rate and compressive strength of the soil dregs grouting material were better than cement mortar grouting material. The treating agent realized the cementation of soil particles through the synergistic effect of epoxy resin and nano-SiO2, and the optimum dosage is 0.02 % of the solid component. The maximum surface settlement of the soil dregs grouting construction section was 10 mm, which is smaller than the maximum surface settlement of the cement mortar grouting section. Through the life cycle assessment (LCA) method, the CO2 emission reduction capacity of the soil dregs synchronous grouting material was analyzed. The soil dregs grouting material reduced the production and transportation of fly ash and bentonite, and reduces the outward transportation of soil dregs. The use of 1 t soil dregs synchronous grouting material can reduce 59.05 kg CO2 emission.

Multi-temporal SAR Interferometry (MTInSAR)-based study of surface subsidence and its impact on Krishna Godavari (KG) basin in India: a support vector approach.

The surface subsidence in the Krishna Godavari (KG) basin in India has increased with the discovery of crude oil and natural gas reserves since 1983. With private players coming up to bag the exploration and refining contracts, there must be timely monitoring of the surface subsidence of the region so that remedial measures for the resettlement of the populations can be taken promptly. Regular monitoring is necessary since the region is fertile and any seawater ingress results in the loss of valuable cultivable land. Multi-temporal SAR Interferometry (MTInSAR) technique has been applied successfully all over the world for the study and regular monitoring of land surface subsidence scenarios. This study utilizes data from Sentinel-1 C-band SAR sensor for MTInSAR-based surface subsidence and RADAR Vegetation Index (RVI)-based vegetation loss for the same season estimation between 2017 and 2022 for the KG basin region. It is inferred from the study that the region has shown surface subsidence of 80mm/year between April 2020 and June 2022. This study uses support vector regressor (SVR) to predict the loss in forest cover in terms of RVI using MTInSAR-based surface subsidence, VH, and VV backscatter as parameters. It is observed that the SVR gave R2-statistics of 0.89 and 0.873 in the training and testing phases with a mean absolute error (MAE) and root mean squared error (RMSE) of 0.08 and 0.02, respectively. It is also observed that the region showed a loss of 3.21 km2 of cultivable land between 2020 and 2022.