Search Results (33)

Two-dimensional viscoplastic nonlinear analyses of the 2019 Feijão Dam 1 failure are performed using the finite difference program FLAC 8.1 with the user-defined constitutive models PM4SiltR and PM4Sand to assess how a series of commonly used engineering approaches can approximate the observed failure. A brief history of Feijão Dam 1, its failure, and the findings from two previous independent failure investigations are summarized. The present study uses the site characterization from those prior studies to develop the dam cross section, obtain material index properties, and establish groundwater conditions but uses alternative techniques for characterizing undrained shear strengths. The simulations show that the dam was marginally stable against long-term consolidated, undrained conditions and that modest loading changes were sufficient to trigger failure with deformation patterns consistent with the observed failure. The simulations further show that the collapse could have been triggered by a modest wetting event, ongoing drilling activities, or a combination of both mechanisms. Result sensitivity to choices in the calibration process and the numerical solution scheme are evaluated. The implications of these results on the use of commonly used engineering approaches for system-level time-dependent analyses and on long-term slope stability assessment procedures in practice are discussed. The results of this study provide support for the use of these analysis methods and engineering procedures in practice despite their simplifications and associated limitations. Full article

The Heifangtai Loess terrace in northwest China is frequently affected by landslides due to hydrological factors, establishing it as a significant research area for loess landslides. Advanced time-series InSAR technology facilitates the retrieval of surface deformation information, thereby aiding in the monitoring of landslide deformation status. However, existing methods that analyze deformation patterns do not fully exploit the displacement time series derived from InSAR, which hampers the exploration of potentially coexisting deformation patterns within the area. This study integrates InSAR with time-series clustering methods to reveal the surface deformation patterns and their spatial distribution characteristics in Heifangtai. Initially, utilizing the Sentinel-1 ascending and descending SAR data stack from January 2020 to June 2023, we optimize the interferometric phase based on distributed scatterer characteristics to reduce noise levels and obtain higher spatial density of measurement points. Subsequently, by combining the differential interferometric datasets from both ascending and descending orbits, the multidimensional small baseline subsets technique is employed to calculate the two-dimensional deformation time series. Finally, time-series clustering methods are utilized to extract the deformation patterns present and their spatial distribution from all measurement point time series. The results indicate that the deformation of the Heifangtai is primarily distributed around the surrounding area of the platform, with subsidence deformation being more intense than horizontal deformation. The entire terrace exhibits five deformation patterns: eastward subsidence, westward subsidence, vertical subsidence, westward movement, and eastward movement. The spatial distribution of these patterns suggests that the areas beneath the platform, namely Yanguoxia Town and Dangchuan Village, may be more susceptible to landslide threats in the future. Furthermore, wavelet analysis reveals the response relationship between rainfall and various deformation patterns, further enhancing the interpretability of these patterns. These findings hold significant implications for subsequent landslide monitoring, early warning, and risk prevention. Full article

The Pamir is located on the northwestern margin of the Tibetan Plateau, which is an area of intense continental deformation and part of the famous India–Himalaya collision zone. The dominant structural deformation in the eastern Pamir is characterized by a 250 km long east–west extensional fault system, known as the Kongur Shan extensional system (KSES), which has developed a series of faults with different orientations and characteristics, resulting in highly complex structural deformation and lacking sufficient geodetic constraints. We collected Sentinel-1 SAR data from December 2016 to March 2023, obtained high-resolution ascending and descending LOS velocities and 3D deformation fields, and combined them with GPS data to constrain the current motion characteristics of the northeastern Pamirs for the first time. Based on the two-dimensional screw dislocation model and using the Bayesian Markov chain Monte Carlo (MCMC) inversion method, the kinematic parameters of the fault were calculated, revealing the fault kinematic characteristics in this region. Our results demonstrate that the present-day deformation of the KSES is dominated by nearly E–W extension, with maximum extensional motion concentrated in its central segment, reaching peak extension rates of ~7.59 mm/yr corresponding to the Kongur Shan. The right-lateral Muji fault at the northern end exhibits equivalent rates of extensional motion with a relatively shallow locking depth. The strike-slip rate along the Muji fault gradually increases from west to east, ranging approximately between 4 and 6 mm/yr, significantly influenced by the eastern normal fault. The Tahman fault (TKF) at the southernmost end of the KSES shows an extension rate of ~1.5 mm/yr accompanied by minor strike-slip motion. The Kashi anticline is approaching stability, while the Mushi anticline along the eastern Pamir frontal thrust (PFT) remains active with continuous uplift at ~2 mm/yr, indicating that deformation along the Tarim Basin–Tian Shan boundary has propagated southward from the South Tian Shan thrust (STST). Overall, this study demonstrates the effectiveness of integrated InSAR and GPS data in constraining contemporary deformation patterns along the northeastern Pamir margin, contributing to our understanding of the region’s tectonic characteristics. Full article

The Qilian Mountains, located on the northeastern edge of the Qinghai–Tibet Plateau, are characterized by unique high-altitude and cold-climate terrain, where permafrost and seasonally frozen ground are extensively distributed. In recent years, with global warming and increasing precipitation on the Qinghai–Tibet Plateau, permafrost degradation has become severe, further exacerbating the fragility of the ecological environment. Therefore, timely research on surface deformation and the freeze–thaw patterns of alpine permafrost in the Qilian Mountains is imperative. This study employs Sentinel-1A SAR data and the SBAS-InSAR technique to monitor surface deformation in the alpine permafrost regions of the Qilian Mountains from 2017 to 2023. A method for spatiotemporal interpolation of ascending and descending orbit results is proposed to calculate two-dimensional surface deformation fields further. Moreover, by constructing a dynamic periodic deformation model, the study more accurately summarizes the regular changes in permafrost freeze–thaw and the trends in seasonal deformation amplitudes. The results indicate that the surface deformation time series in both vertical and east–west directions obtained using this method show significant improvements in accuracy over the initial data, allowing for a more precise reflection of the dynamic processes of surface deformation in the study area. Subsidence is predominant in permafrost areas, while uplift mainly occurs in seasonally frozen ground areas near lakes and streams. The average vertical deformation rate is 1.56 mm/a, with seasonal amplitudes reaching 35 mm. Topographical (elevation; slope gradient; aspect) and climatic factors (temperature; soil moisture; precipitation) play key roles in deformation patterns. The deformation of permafrost follows five distinct phases: summer thawing; warm-season stability; frost heave; winter cooling; and spring thawing. This study enhances our understanding of permafrost deformation characteristics in high-latitude and high-altitude regions, providing a reference for preventing geological disasters in the Qinghai–Tibet Plateau area and offering theoretical guidance for regional ecological environmental protection and infrastructure safety. Full article

High-precision monitoring of glacier motion provides crucial information for a thorough understanding of the dynamic characteristics and development patterns of glaciers, which serves as a scientific basis for the prevention and management of glacier-related disasters. Zelongnong Glacier, located in Tibet, China, has experienced glacier surges, collapse, and hazard chains four times in the last 70 years. On 10 September 2020, a major glacier hazard chain occurred in this region. To reveal the influencing factors of the glacier motion, we monitor the Zelongnong Glacier motions with 65 scenes of TerraSAR/PAZ images from 2022 to 2023, where the Pixel Offset Multidimensional Small Baseline Subset (PO-MSBAS) method is employed for three-dimensional time series inversion. As the registration window size directly affects the matching success rate, deformation accuracy, and signal-to-noise ratio (SNR) during the offset tracking processing, we adopt a variable window-weighted cross-correlation strategy. The strategy balances the advantages of different window sizes, effectively reducing noise while preserving certain details in the offset results. The standard deviation in stable areas is also significantly lower than that obtained using smaller window sizes in conventional methods. The results reveal that the velocity of the southern glacier tributary was larger than the one in the northern tributary. Specifically, the maximum velocity in the northern tributary reached 45.07 m/year in the horizontal direction and −7.45 m/year in the vertical direction, whereas in the southern tributary, the maximum velocity was 50.15 m/year horizontally and 50.66 m/year vertically. The southern tributary underwent two bends before merging with the mainstream, leading to a more complex motion pattern. Lastly, correlation reveals that the Zelongnong Glacier was affected by the combined influence of temperature and precipitation with a common period of around 90 days. Full article

Based on domain decomposition, a semi-analytical method (SAM) is applied to analyze the free vibration of double-curved shells of revolution with a general curvature radius made from graphene nanoplatelet (GPL)-reinforced porous composites. The mechanical properties of the GPL-reinforced composition are assessed with the Halpin–Tsai model. The double-curvature shell of revolution is broken down into segments along its axis in accordance with first-order shear deformation theory (FSDT) and the multi-segment partitioning technique, to derive the shell’s functional energy. At the same time, interfacial potential is used to ensure the continuity of the contact surface between neighboring segments. By applying the least-squares weighted residual method (LWRM) and modified variational principle (MVP) to relax and achieve interface compatibility conditions, a theoretical framework for analyzing vibrations is developed. The displacements and rotations are described through Fourier series and Chebyshev polynomials, accordingly, converting a two-dimensional issue into a suite of decoupled one-dimensional problems. The obtained solutions are contrasted with those achieved using the finite element method (FEM) and other existing results, and the current formulation’s validity and precision are confirmed. Example cases are presented to demonstrate the free vibration of GPL-reinforced porous composite double-curved paraboloidal, elliptical, and hyperbolical shells of revolution. The findings demonstrate that the natural frequency of the shell is related to pore coefficients, porosity, the mass fraction of the GPLs, and the distribution patterns of the GPLs. Full article

To address the industry’s demand for sustainable oilfield development and safe production, it is crucial to enhance the scientific rigor and accuracy of monitoring ground stability and reservoir parameter inversion. For the above purposes, this paper proposes a technical solution that employs two-dimensional time-series ground deformation monitoring based on ascending and descending Interferometric Synthetic Aperture Radar (InSAR) technique first, and the composite dislocation model (CDM) is utilized to achieve high-precision reservoir parameter inversion. To validate the feasibility of this method, the Liaohe Oilfield is selected as a typical study area, and the Sentinel-1 ascending and descending Synthetic Aperture Radar (SAR) images obtained from January 2020 to December 2023 are utilized to acquire the ground deformation in various line of sight (LOS) directions based on Multitemporal Interferometric Synthetic Aperture Radar (MT-InSAR). Subsequently, by integrating the ascending and descending MT-InSAR observations, we solved for two-dimensional ground deformation, deriving a time series of vertical and east-west deformations. Furthermore, reservoir parameter inversion and modeling in the subsidence trough area were conducted using the CDM and nonlinear Bayesian inversion method. The experimental results indicate the presence of uneven subsidence troughs in the Shuguang and Huanxiling oilfields within the study area, with a continuous subsidence trend observed in recent years. Among them, the subsidence of the Shuguang oilfield is more significant and shows prominent characteristics of single-source center subsidence accompanied by centripetal horizontal displacement, the maximum vertical subsidence rate reaches 221 mm/yr, and the maximum eastward and westward deformation is more than 90 mm/yr. Supported by the two-dimensional deformation field, we conducted a comparative analysis between the Mogi, Ellipsoidal, and Okada models in terms of reservoir parameter inversion, model fitting efficacy, and residual distribution. The results confirmed that the CDM offers the best adaptability and highest accuracy in reservoir parameter inversion. The proposed technical methods and experimental results can provide valuable references for scientific planning and production safety assurance in related oilfields. Full article

Multi-track synthetic aperture radar interferometry (InSAR) provides a good approach for the monitoring of long-term multi-dimensional earthquake deformation, including pre-, co-, and post-seismic data. However, the removal of atmospheric errors in both single- and multi-track InSAR data presents significant challenges. In this paper, a method of spatio-temporal correlation analysis using independent component analysis (ICA) is proposed, which can extract multi-track deformation components for the accurate retrieval of earthquake deformation time series. Sentinel-1 data covering the double earthquakes in Turkey and Syria in 2023 are used to demonstrate the effectiveness of the proposed method. The results show that co-seismic displacement in the east–west and up–down directions ranged from −114.7 cm to 82.8 cm and from −87.0 cm to 63.9 cm, respectively. Additionally, the deformation rates during the monitoring period ranged from −137.9 cm/year to 123.3 cm/year in the east–west direction and from −51.8 cm/year to 45.7 cm/year in the up–down direction. A comparative validation experiment was conducted using three GPS stations. Compared with the results of the original MSBAS method, the proposed method provides results that are smoother and closer to those of the GPS data, and the average optimization efficiency is 43.08% higher. The experiments demonstrated that the proposed method could provide accurate two-dimensional deformation time series for studying the pre-, co-, and post-earthquake events of the 2023 Turkey–Syria Earthquakes. Full article

Surface subsidence hazards in mining areas are common geological disasters involving issues such as vegetation degradation and ground collapse during the mining process, which also raise safety concerns. To address the accuracy issues of traditional prediction models and study methods for predicting subsidence in open-pit mining areas, this study first employed 91 scenes of Sentinel-1A ascending and descending orbits images to monitor long-term deformations of a phosphate mine in Anning City, Yunnan Province, southwestern China. It obtained annual average subsidence rates and cumulative surface deformation values for the study area. Subsequently, a two-dimensional deformation decomposition was conducted using a time-series registration interpolation method to determine the distribution of vertical and east–west deformations. Finally, three prediction models were employed: Back Propagation Neural Network (BPNN), BPNN optimized by Genetic Algorithm (GA-BP), and BPNN optimized by Artificial Bee Colony Algorithm (ABC-BP). These models were used to forecast six selected time series points. The results indicate that the BPNN model had Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) within 7.6 mm, while the GA-BP model errors were within 3.5 mm, and the ABC-BP model errors were within 3.7 mm. Both optimized models demonstrated significantly improved accuracy and good predictive capabilities. Full article

Proppant transport and distribution law in hydraulic fractures has important theoretical and field guidance significance for the optimization design of hydraulic fracturing schemes and accurate production prediction. Many studies aim to understand proppant transportation in complex fracture systems. Few studies, however, have addressed the flow path mechanism between the transverse fracture and horizontal well, which is often neglected in practical design. In this paper, a series of mathematical equations, including the rock elastic deformation equation, fracturing fluid continuity equation, fracturing fluid flow equation, and proppant continuity equation for the proppant transport, were established for the transverse fracture of a horizontal well, while the finite element method was used for the solution. Moreover, the two-dimensional radial flow was considered in the proppant transport modeling. The results show that proppant breakage, embedding, and particle migration are harmful to fracture conductivity. The proppant concentration and fracture wall roughness effect can slow down the proppant settling rate, but at the same time, it can also block the horizontal transportation of the proppant and shorten the effective proppant seam length. Increasing the fracturing fluid viscosity and construction displacement, reducing the proppant density and particle size, and adopting appropriate sanding procedures can all lead to better proppant placement and, thus, better fracturing and remodeling results. This paper can serve as a reference for the future study of proppant design for horizontal wells. Full article

This article extends the application of fractional-order time derivatives to replace their integer-order counterparts within a system comprising two singular one-dimensional coupled partial differential equations. The resulting model proves invaluable in representing radially symmetric deformation and temperature distribution within a unit disk. The incorporation of fractional-order derivatives in mathematical models is shown to significantly enhance their capacity for characterizing real-life phenomena in comparison to their integer-order counterparts. To address the studied system numerically, we employ the q-homotopy analysis transform method (q-HATM). We evaluate the efficiency of this method in solving the problem through a series of illustrative examples. The convergence of the derived scheme is assessed visually, and we compare the performance of the q-HATM with that of the Laplace decomposition method (LDM). While both methods excel in resolving the majority of the presented examples, a notable divergence arises in the final example: the numerical solutions obtained using q-HATM converge, whereas those derived from LDM exhibit divergence. This discrepancy underscores the remarkable efficiency of the q-HATM in addressing this specific problem. Full article

To investigate the plastic deformation (PD) response of a liner material during the shaped-charge jet (SCJ) formation process, the state of motion of liner material and the pattern of change in its deformation environment under explosive loading were theoretically analyzed and modeled. The distribution patterns of the characteristic PD parameters (that is, strain, strain rate, temperature, and flow stress) of the jet at any given time were theoretically predicted. The distribution patterns of the characteristic PD parameters of jets formed from two materials, namely, oxygen-free high-thermal-conductivity copper (OFHC-Cu) and molybdenum (Mo), during their formation process were theoretically analyzed. A series of experimental and numerical simulation studies were conducted to examine the accuracy of the theoretical predictions. As per the results, the developed theoretical model is effective in predicting the one-dimensional distribution of the characteristic PD parameters in the direction of jet formation. At any given time, the distribution of the characteristic PD parameters varies considerably between different parts of the jet. There is no significant difference in the distribution of the strain and strain rate between the jets formed from the two materials in the presence of the same warhead structure. A theoretical analysis predicted average temperatures of 804 and 2277.8 K and average flow stresses of 193.1 and 344.3 MPa for the OFHC-Cu and Mo jets, respectively. A hardness analysis of the jet fragments revealed average strengths of 144.32 and 286.66 MPa for the OFHC-Cu and Mo jets during their formation process, respectively. These results differed by 34% and 20% from the corresponding theoretical predictions. Full article

Land subsidence caused by excessive groundwater pumping in Central Valley, California, is a major issue that has several negative impacts such as reduced aquifer storage and damaged infrastructures which, in turn, produce an economic loss due to the high reliance on crop production. This is why it is of utmost importance to routinely monitor and assess the surface deformation occurring. Two main goals that this paper attempts to accomplish are deformation characterization and deformation prediction. The first goal is realized through the use of Principal Component Analysis (PCA) applied to a series of Interferomtric Synthetic Aperture Radar (InSAR) images that produces eigenimages displaying the key characteristics of the subsidence. Water storage changes are also directly analyzed by the use of data from the Gravity Recovery and Climate Experiment (GRACE) twin satellites and the Global Land Data Assimilation System (GLDAS). The second goal is accomplished by building a Long Short-Term Memory (LSTM) model to predict short-term deformation after developing an InSAR time series using LiCSBAS, an open-source InSAR time series package. The model is applied to the city of Madera and produces better results than a baseline averaging model and a one dimensional convolutional neural network (CNN) based on a mean squared error metric showing the effectiveness of machine learning in deformation prediction as well as the potential for incorporation in hazard mitigation models. The model results can directly aid policy makers in determining the appropriate rate of groundwater withdrawal while maintaining the safety and well-being of the population as well as the aquifers’ integrity. Full article

Offset tracking technology is widely studied to evaluate glacier surface displacements. However, few studies have used a cross-platform to this end. In this study, two heterogeneous data sources, Sentinel-1 and Landsat 8, from January 2019 to January 2021, were used to estimate the offset, and then the optimal estimation of the 3D deformation rate of a Himalayan glacier was obtained based on the joint model of variance component estimation. The results show that the maximum deformation rates of the glacier in the east–west direction, north–south direction, and vertical direction are 85, 126, and 88 mm/day, respectively. The results of the joint model were compared and analyzed with the results of simultaneous optical image pixel offset tracking. The results showed that the accuracy of the joint solution model increased by 41% in the east–west direction and 36% in the south–north direction. The regional flow velocity of the moraine glacier after the joint solution was consistent with the vector boundary of the glacier cataloging data. The time-series results of the glacier displacement were calculated using more images. These results indicate that the joint solution model is feasible for calculating temporal glacier velocity. The model can improve the time resolution of the monitoring results and obtain further information on glacier characteristics. Our results show that the glacier velocity is affected by local terrain slope and temperature. However, there is no absolute positive correlation between glacier velocity and slope. This study provides a reference for the joint acquisition of large-scale three-dimensional displacement of glaciers using multi-source remote sensing data and provides support for the identification and early warning of glacier disasters. Full article

The Loess Plateau is one of the three most severely affected geological disaster areas in China. Water sensitivity is the most significant feature of the loess. Under the action of continuous heavy rainfall, rainwater infiltrates the loess, resulting in a rapid increase in soil saturation and changes in soil moisture. This affects the shear strength of the soil and induces shallow loess landslides. Therefore, it is significant to our country’s disaster prevention and mitigation efforts to effectively monitor the deformation and inducement of such landslides. At present, the global navigation satellite system (GNSS) is widely used in the field of landslide disaster monitoring as a technical means to directly obtain real-time three-dimensional vector deformation of the surface. At the same time, GNSS can also provide a steady stream of L-band microwave signals to obtain surface environmental information, such as soil moisture around the station. In past landslide disaster monitoring research, GNSS was only used to provide three-dimensional deformation information, and its ability to provide environmental information around the station was almost completely ignored. This study proposes a ground-based GNSS remote sensing comprehensive monitoring system integrating “three-dimensional deformation and soil moisture content” combined with a rainfall-type shallow loess landslide event in Linxia City. The ability of ground-based GNSS to comprehensively monitor shallow loess landslide disasters was analysed. Experiments show that GNSS can provide high-precision deformation time series characteristics and monitor the changes in soil moisture content around the station at the same time; the two have a certain response relationship, which can comprehensively evaluate the stability of shallow loess landslides. As heavy rainfall is a key factor affecting the change in soil water content, this study adds the atmospheric water vapour content calculated by ground-based GNSS refraction remote sensing in the discussion chapter and analyses the relationship between precipitable water vapour and rainfall in this area to give full play to ground-based GNSS remote sensing. In the role of landslide disaster monitoring, we hope to build a more comprehensive ground-based GNSS remote sensing monitoring system to better serve the monitoring of landslide disasters. Full article