To explore an effective method for deformation monitoring and behavior prediction of expansive soil slope, field tests are conducted for a flexible slope protection scheme with soilbags that has been implemented in an expansive highway soil slope. A new monitoring system, i.e., the universal Beidou deformation monitoring system, is developed to overcome the limitations of traditional Global Navigation Satellite System (GNSS) software and hardware, simplify the hardware structure and realize the power sharing mode; furthermore, this system can create and upload a large amount of monitored data to a cloud platform to enable real-time calculation. Compared with traditional GNSS, the volume of equipment required is reduced by approximately 75%, and the cost is reduced by approximately 80%. Secondly, a multilevel safety early-warning evaluation system is constructed by integrating the monitoring results of the universal Beidou deformation monitoring system, bag damage states, rainfall conditions, and slope fissure development; additionally, a deformation early-warning mechanism of flexible support of soilbags was established. Finally, the deformation and collapse of flexible supports of soilbags can be successfully predicted in the field. This research on flexible support of soilbags provides new ideas and methods of deformation monitoring, safety evaluation, and early warning for expansive soil slopes.

The deterioration of shear resistance in rock and soil masses has resulted in numerous severe natural disasters, highlighting the significance of long-term monitoring for disaster prevention and mitigation. This study explores the use of a nondestructive method to quickly and accurately evaluate the shear properties of soil-rock mixture. The shear stress, shear strain, and resistivity of the soil-rock mixture were tested simultaneously using a combination of direct shear and resistivity tests. The test results show that the resistivity of the soil-rock mixture gradually decreases with increasing shear strain. The resistivity of all specimens ranged approximately from 60 to 130 Omega.m throughout the shear process. At the end of the shear test, the vertical failure resistivity showed an irregular W shape with increasing rock content. It exhibited a significant negative linear functional relationship with the shear strength. With reference to the determination of cohesion and internal friction angle on the shear strength envelope, the horizontal angle of the vertical failure resistivity-normal stress curve is defined as the resistivity angle, and the intercept of the curve is the resistivity at the initial moment of shear. It has been observed that the resistivity angle is negatively and linearly correlated with the internal friction angle. At the same time, there is a linear growth relationship between resistivity at the initial moment of shear and cohesion. It has been demonstrated that an increase in rock content contributes to a general escalation in both the average structure factor and average shape factor. Meanwhile, a decrease in the anisotropy coefficient has also been noted. These alterations are indicative of the extent of microstructural transformations occurring during the deformation process of the soil-rock mixture. The research results verify the feasibility of real-time deformation monitoring and characterization of shear strength parameters using resistivity.

Pipe roofs are widely used as an effective proactive support measure in the construction of tunnel entrances, shallow-buried and underground excavated tunnels, underground stations, and large- soft and weak soil structures. However, the stress variation characteristics of pipe roofs exceeding 40 m in length are not yet clear. This paper utilizes numerical simulation methods to conduct a comprehensive analysis of the deformation characteristics of three excavation methods: center cross-diaphragm method (CRD), both-side heading method, and the three-bench excavation method with super-long pipe roofs combined with temporary inverted arches. It specifically compares the deformation control effectiveness and stress variation patterns of pipe roofs of different lengths. The results indicate that the deformation control effectiveness of 40 m and 20 m long pipe roofs is inferior to that of super-long pipe roofs. Within a range of 30 m in front of the tunnel face and 20 m behind it, significant stress variations of the pipe roof are observed. The most influential range is within 10 m in front of the tunnel face and 5 m behind it. It is evident that the overall load-bearing capacity of the super-long pipe roof is higher than that of pipe roofs below 40 m. Furthermore, in this study, a novel approach is adopted by utilizing fiber optic grating testing technology to achieve comprehensive monitoring of the axial forces in super-long large pipe roofs. The measured data strongly corroborate the accuracy of the numerical calculations.

Geogrid is widely used in slope, retaining wall, embankment, and other projects as the new geosynthetic material. In order to master the deformation behavior of geogrid, this study employs advanced optical frequency domain reflectometry (OFDR) technology to capture the deformation of geogrid; the optical fiber sensor installation method is considered; the influence of colloidal layer on strain transmission is explored; the medium type around the geogrid is changed; and the deformation characteristics of geogrid during the pulling process are analyzed. The results reveal that the strain of slotted layout is larger compared with tie layout, and the deformation trends of the two layouts are the same. The colloidal layer demonstrates an excellent strain transfer efficiency, with a coefficient of 97%. The geogrid pulling test successfully measures the deformation of geogrid in both sand and air medium using OFDR technology. The strain of the geogrid in sand medium is small; it indicates that the surrounding medium effectively restrains the deformation of geogrid.

Due to the effects of global climate change, the permafrost temperature in the Qinghai-Tibet Plateau (QTP) has rapidly increased over the past decades. The development of thermokarst landforms is one distinctive indicator of permafrost degradation, while the change of the rate of permafrost degradation in recent 10 years has not been systematically investigated in QTP. In this paper, the annual average growth rate (AAGR) of ground deformation, the change of thaw slump areas, and the change of active layer thickness (ALT) of thermokarst landforms are monitored integrating SAR (synthetic aperture radar) and optical images for years 2007 to 2020 in Qilian Mountain, northern QTP. The ground deformation rate and seasonal amplitude were estimated by InSAR method, and the descending and ascending InSAR data are compared the validate the results. Based on the deformation results, AAGR was introduced to evaluate the permafrost degradation degree. Moreover, the ALT were estimated based on the seasonal deformation amplitude and Stefan model. The spatio-temporal characteristics of ground deformation and its relationship with thaw slump and temperature are explored. Experimental results show that the deformation rate increased about 150 % from 2007 to 10 to 2017-20. The maximum AAGR of deformation rate in the study area can reach 20.6 %. The thaw slump area has an obvious trend of expansion from 2009 to 2015, and its distribution agreed well with the deformation map. The ALT results ranged from 0.5 m to 2.8 m, indicating an obvious increase trend from 2007 to 2020. Based on the estimated increased ground deformation, thaw slump area, and ALT, it is inferred that frozen ground was undergoing serious degradation in the last 10 years. This study demonstrates the capability of multi-temporal InSAR in observing the accelerated permafrost thaw-freezing process and monitoring the permafrost parameters.

Real -time monitoring of foundation pits is an important part of the engineering construction. This paper proposes a method of deformation monitoring of foundation pit based on MEMS technology. The algorithm based on time-domain integration is adopted, and a fixed distance test is designed to verify the feasibility of the algorithm. Through the indoor model test of foundation pit monitoring, MEMS sensors are embedded to collect the acceleration, rotation angle and the other signals of soil movement, and then the acceleration signal is integrated to obtain displacement by algorithm calculation. Finally, the deformation characteristics of soil in the process of foundation pit are analyzed by using soil displacement and rotation angle to investigate the effectiveness of applying MEMS technology to foundation pit monitoring. The test results show that the MEMS sensor could accurately collect the acceleration, rotation angle and other signals of soil movement in model box. The monitoring method proposed in this paper lay a theoretical foundation and experimental verification for the application of MEMS technology in foundation pit monitoring.

The combined effect of climate change and accelerated economic development in Northern regions increases the threat of permafrost related surface deformation to buildings and transportation infrastructure. Satellite based InSAR provides a means for monitoring infrastructure that may be both remote and spatially extensive. However, permafrost poses challenges for InSAR monitoring due to the complex temporal deformation patterns caused by both seasonal active layer fluctuations and long-term changes in permafrost thickness. These dynamics suggest a need for increasing the temporal resolution of multi-temporal InSAR methods. To address this issue we have developed a method that combines and jointly processes two or more same side geometry InSAR stacks to provide a high-temporal resolution estimate of surface deformation. The method allows for combining stacks from more than a single SAR sensor and for a combination of frequency bands. Data for this work have been collected and analysed for an area near the community of Umiujaq, Quebec in Northern Canada and include scenes from RADARSAT-2, TerraSAR-X and COSMO-SkyMed. Multiple stack based surface deformation estimates are compared for several cases including results from the three sensors individually and for all sensors combined. The test cases show substantially similar surface deformation results which correlate well with surficial geology. The best spatial coverage of coherent targets was achieved when data from all sensors were combined. The proposed multiple stack method is demonstrated to improve the estimation of surface deformation in permafrost affected areas and shows potential for deriving InSAR based permafrost classification maps to aid in the monitoring of Northern infrastructure.