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The long-term and extensive exploration of energy sources, such as oil and gas, has led to the large-scale surface deformation of the Songnen Plain in China. To study the impact of oil and gas exploitation on surface deformation in the Songnen Plain, we selected a typical oil exploitation area (OEA) to conduct an analysis and prediction using multimodal data, Interferometry Synthetic Aperture Radar (InSAR) technology, and Autoregressive Integrated Moving Average (ARIMA) – Back Propagation (BP) neural network model. The study revealed a subsidence trend in the OEA using Small Baseline Subset InSAR (SBAS-InSAR), indicating a deformation velocity of −2.4 mm/year throughout the monitoring period. Additionally, we analysed the factors impacting surface deformation by considering six factors: oil and gas exploitation, stratum structure, groundwater, surface water, meteorological conditions, and seismic activity. We found that oil and gas exploitation production had a significant negative correlation with surface deformation, with a distance effect of about 800 m. The stratum structure causing surface subsidence was mainly located in the silty clay layers. Groundwater, surface water, and cumulative precipitation were all negatively correlated with surface deformation, while temperature and seismic activity showed no clear relationship. Furthermore, we proposed a novel ARIMA-BP model to predict the deformation trend of OEA and found that the prediction accuracy of this model is higher than the single models. This study can provide decision support for analysing surface deformation and implementing disaster prevention measures in the OEA, thereby contributing significantly to the sustainable development of society. [ABSTRACT FROM AUTHOR]

Spatiotemporal patterns of earth surface deformation are influenced by a combination of static and dynamic environmental characteristics specific to any landscape of interest. Nowadays, these patterns can be captured for larger areas using Interferometric Synthetic-Aperture Radar (InSAR) technologies and yet, their spatial prediction has been poorly investigated so far. Here, we initially compute the InSAR-derived line-of-sight hillslope velocities (VLOS) and calculate their mean (ranging from 0 to ~ 30 mm/y) and maximum (ranging from 0 to ~ 60 mm/y) values per Slope Units (SUs). These separately constitute the response variables to be modelled through a series of deep learning routines: i) a basic neural network (Multi-Layer Perceptron), ii) a Graph Convolutional Network implemented to capture spatial dependence among neighbouring SUs, and iii) an Edge-Featured Graph Attention Network sensitive not only to the interdependence brought by the SU positions in space but also to reciprocal terrain characteristics. We assessed the model performance for both models via Mean Absolute Error (MAE), r-squared (R2), and Pearson Correlation Coefficient (PCC). The Edge-Featured Graph Attention Network model produced the best performance. The result for the first model targeting the mean VLOS are 4.75 mm/y, 0.63, and 0.79 for MAE, R2, and PCC, respectively. As for the second model, targeting the maximum VLOS, these are 19.52 mm/y, 0.55 and 0.75. We also showcased interpretable multivariate models, where the contribution of each predictor to the InSAR velocities is summarized and interpreted. This represent a clear example where InSAR-derived hillslope velocities are accurately estimated at regional scales, thus setting up the scene for further advances towards space-time regional deformation modelling. [ABSTRACT FROM AUTHOR]

Interferometric synthetic aperture radar (InSAR) technology plays a crucial role in monitoring surface deformation and has become widely used in volcanic and earthquake research. With the rapid advancement of satellite technology, InSAR now generates vast volumes of deformation data. Deep learning has revolutionized data analysis, offering exceptional capabilities for processing large datasets. Leveraging these advancements, automatic detection of volcanic and earthquake deformation from extensive InSAR datasets has emerged as a major research focus. In this paper, we first introduce several representative deep learning architectures commonly used in InSAR data analysis, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), and Transformer networks. Each architecture offers unique advantages for addressing the challenges of InSAR data. We then systematically review recent progress in the automatic detection and identification of volcanic and earthquake deformation signals from InSAR images using deep learning techniques. This review highlights two key aspects: the design of network architectures and the methodologies for constructing datasets. Finally, we discuss the challenges in automatic detection and propose potential solutions. This study aims to provide a comprehensive overview of the current applications of deep learning for extracting InSAR deformation features, with a particular focus on earthquake and volcanic monitoring. [ABSTRACT FROM AUTHOR]

Bubbles present in saline water typically exhibit a prolonged lifetime, making them attractive for various engineering processes. Herein, we unveil a transition from delayed bubble coalescence to rapid bursting within about one millisecond in salty solutions. The key aspect in understanding this transition lies in the combined influences of surface deformation and ion surface excess instead of characterizing the ions alone. Only with a sufficiently deformed region trapped between the colliding bubble and fluid surfaces can the coalescence inhibition effect be maintained to cause the bouncing behavior. Thus, we quantify a consistent upper limit of ion transfer content required for instant coalescence under different salty conditions. Furthermore, we present numerical ranges associated with different bubble behaviors in terms of Eo, Re, and We and determine the critical values to predict bubble dynamics. Our findings shed light on the bubble coalescence principle in saline water and allow access to the regulation of coalescence time based on the requirement of technological applications. [ABSTRACT FROM AUTHOR]

Introduction: Surface deformation in the Three Gorges Reservoir area poses significant threats to infrastructure and safety due to complex geological and hydrological factors. Despite existing studies, systematic exploration of long-term deformation characteristics and their driving mechanisms remains limited. This study combines SBAS-InSAR technology and machine learning to analyze and predict surface deformation in Fengjie County, Chongqing, China, between 2020 and 2022, focusing on riverside urban ground, riverside road slopes, and ancient landslides in the reservoir area. Methods: SBAS-InSAR technology was applied to 36 Sentinel-1A images to monitor surface deformation, complemented by hydrological and meteorological data. Machine learning models—Random Forest (RF), Extremely Randomized Trees (ERT), Gradient Boosting Decision Tree (GBDT), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM)—were evaluated using six metrics, including RMSE, R2, and SMAPE, to assess their predictive performance across diverse geological settings. Results: Deformation rates for riverside urban ground, road slopes, and ancient landslides were −3.48 ± 2.91 mm/yr, −5.19 ± 3.62 mm/yr, and −6.02 ± 4.55 mm/yr, respectively, with ancient landslides exhibiting the most pronounced deformation. A negative correlation was observed between reservoir water level decline and subsidence, highlighting the influence of seasonal hydrological adjustments. Urbanization and infrastructure development further exacerbated deformation processes. Among the models, LSTM demonstrated superior predictive accuracy but showed overestimation trends in ancient landslide areas. Discussion: Reservoir water level adjustments emerged as a critical driver of subsidence, with rapid water level declines leading to increased pore pressure and soil compression. Seasonal effects were particularly evident, with higher subsidence rates during and after the rainy season. Human activities, including urbanization and road construction, significantly intensified deformation, disrupting natural geological conditions. Progressive slope failure linked to road expansion underscored the long-term impacts of engineering activities. For ancient landslides, accelerated deformation patterns were linked to prolonged drought and reservoir-induced hydrological changes. While LSTM models showed high accuracy, their limitations in complex geological settings highlight the need for hybrid approaches combining machine learning with physical models. Future research should emphasize developing integrated frameworks for long-term risk assessment and mitigation strategies in reservoir environments. Conclusions: This study provides new insights into the complex surface dynamics in the Three Gorges Reservoir area, emphasizing the interplay of hydrological, geological, and anthropogenic factors. The findings highlight the need for adaptive management strategies and improved predictive models to mitigate subsidence risks. [ABSTRACT FROM AUTHOR]

Interferometric Synthetic Aperture Radar (InSAR) technology has emerged as a vital tool for monitoring surface deformation due to its high accuracy and spatial resolution. With the rapid economic development of Nanchang, extensive infrastructure development and construction activities have significantly altered the urban landscape. Underground excavation and groundwater extraction in the region are potential contributors to surface deformation. This study utilized Sentinel-1 satellite data, acquired between September 2018 and May 2023, and applied the Permanent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to monitor surface deformation in Nanchang's urban area. The findings revealed that surface deformation rates in the study area range from −10 mm/a to 6 mm/a, with the majority of regions remaining relatively stable. Approximately 99.9% of the monitored points exhibited deformation rates within −5 mm/a to 5 mm/a. However, four significant subsidence zones were identified along the Gan River and its downstream regions, with a maximum subsidence rate reaching 9.7 mm/a. Historical satellite imagery comparisons indicated that certain subsidence areas are potentially associated with construction activities. Further analysis integrating subsidence data, monthly precipitation, and groundwater depth revealed a negative correlation between surface deformation in Region A and rainfall, with subsidence trends aligning with groundwater level fluctuations. However, such a correlation was not evident in the other three regions. Additionally, water level data from the Xingzi Station of Poyang Lake showed that only Region A's subsidence trend closely corresponds with water level variations. We conducted a detailed analysis of the spatial distribution of soil types in Nanchang and found that the soil types in areas of surface deformation are primarily Semi-hydromorphic Soils and Anthropogenic Soils. These soils exhibit high compressibility, making them prone to compaction and significantly influencing surface deformation. This study concludes that localized surface deformation in Nanchang is primarily driven by urban construction activities and the compaction of artificial fill soils, while precipitation also has an impact in certain areas. [ABSTRACT FROM AUTHOR]

The 2022 Paktika earthquake (moment magnitude: 6.2) occurred on June 22, 2022, near the border between the Khost and Paktika Provinces of Afghanistan, causing heavy damage and casualties in Paktika Province. This study evaluated the crustal deformation and associated strong motions induced by the Paktika earthquake. Crustal deformations were determined using the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique and three-dimensional finite element method (3D-FEM) and the results were compared. The permanent ground displacements obtained from the DInSAR and 3D-FEM analyses were similar in terms of amplitude and areal distribution. Strong motions were estimated using the 3D-FEM with and without considering regional topography. The estimations of maximum ground acceleration, velocity, and permanent ground deformations were compared among each other as well as with those inferred from failures of some simple structures in the Spera and Gayan districts. The inferred maximum ground acceleration and velocity from the failed adobe structures were more than 300 Gal and 50 cm/s, respectively, nearly consistent with the estimates obtained using empirical methods. The empirical method yielded a maximum ground acceleration of 347 Gal, whereas the maximum ground velocity was approximately 50 cm/s. In light of these findings, some surface expressions of crustal deformations and strong ground motions, such as failures of soil and rock slopes and rockfalls, have been presented. The rock slope failures in the epicentral area were consistent with those observed during various earthquakes in Afghanistan and worldwide.

Objective To investigate the spatial-temporal variations in landslide susceptibility due to human engineering activities in resettled urban areas. Methods This study focuses on the new urban area of Yunyang County in the Three Gorges Reservoir region. Landslide susceptibility time-varying index factors were introduced to map spatial-temporal susceptibility differences and explore the spatial-temporal evolution of landslide disasters during urbanization in resettled urban areas. First, the stacking ensemble model was selected as the static susceptibility evaluation model. Then, the InSAR deformation rates and land use types over three distinct time spans (namely, January 16, 2017, to August 27, 2018 (T1), September 20, 2018, to July 30, 2021 (T2), and August 23, 2021, to November 17, 2023 (T3)) were selected as time-varying factors. Last, the time-varying factors were combined with the static evaluation results to create susceptibility difference distribution maps for the different periods. Results The study revealed that introducing time-varying factors in the analysis of spatial-temporal susceptibility differences effectively reflects the impact of urbanization on landslide disasters. When the land type in the study area changed from non-engineering land to engineering land, the landslide susceptibility level generally increased, with grid shares of 61.3% and 67.1% in the two change stages, respectively. The temporal trends of the InSAR displacement time series curves for selected typical landslides in urban areas showed high spatial-temporal correlations with land type changes, further validating the reliability of this method. Conclusion The proposed research approach provides the basis for disaster prevention, mitigation, and regional planning during the urbanization process in resettled urban areas of the Three Gorges Reservoir region.

This paper introduces a novel, ecofriendly, and cost‐effective method to create deformation patterns on vertically vibrating thin film surfaces using resonant sessile droplets. The key findings emphasize the critical role of resonant frequency and vibration velocity in the formation of these deformations. Through theoretical and experimental investigations on aluminum thin film, it is validated that the deformations are influenced by the energy distribution within the resonant droplets. Specifically, higher‐order resonant frequencies produce a more concentrated energy distribution at the droplet's center due to internal top‐down flow behaviors, resulting in various deformation states. By observing regularities in deformation width patterns, the underlying phenomena are elucidated, and derive related empirical formulas. This method demonstrates significant potential for surface microstructure fabrication. The ability to control deformation shapes by adjusting vibration parameters is crucial for optimizing microfabrication processes. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Surface deformation poses significant risks to urban infrastructure, agriculture, and the environment in many regions worldwide, including Rwanda and the neighboring areas. This study focuses on surface deformation mapping and time series analysis in Rwanda and the neighboring areas from 2 July 2016 to 8 June 2023 using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). The influence of atmospheric delay error is effectively reduced by integrating the Generic Atmospheric Correction Online Service (GACOS), which provides precise atmospheric delay maps. Then the SBAS-InSAR method is utilized to generate surface deformation maps and displacement time series across the region. The results of this study indicated that the maximum deformation rate was −0.11 m/yr (subsidence) and +0.13 m/yr (uplift). Through time series analysis, we quantified subsidence and uplift areas and identified key drivers of surface deformation. Since subsidence or uplift varies across the region, we have summarized the different deformation patterns and briefly analyzed the factors that may lead to deformation. Finally, this study underscores the importance of SBAS-InSAR for tracking surface deformation in Rwanda and the neighboring areas, which offers valuable perspectives for sustainable land utilization strategizing and risk mitigation. [ABSTRACT FROM AUTHOR]

Computational results of aircraft icing and predictions of ice shape are not only determined by the solutions of air-supercooled droplet two-phase flow and icing thermodynamic models of surface water film, but are also influenced by the growth mode of the ice layer. Two ice growth modes were established in a two-dimensional (2D) icing process simulation framework to calculate the ice thickness and ice shape, depending on whether surface deformation of the icing process was considered. Ice accretion simulations were performed with the two ice growth modes for an NACA0012 airfoil under rime ice and mixed ice conditions, and the results of ice amount, ice thickness, and ice shape were compared and analyzed. Under the same amount of ice formation, the ice thickness and ice shape obtained using different ice growth modes vary. The ice thickness and the ice shape size are relatively large without considering surface deformation, whereas the results with growth correction show a certain degree of reduction, which is more noticeable around the leading edge and the ice horns. However, the degrees of difference in ice thickness and ice shape are not the same, and the deviation in ice thickness is more obvious. Furthermore, the ice thickness and ice shape obtained using the ice growth correction mode are more consistent with experimental data and commercial software results, verifying the accuracy of the ice simulation method and the necessity of considering ice surface deformation. This paper is an essential guide for understanding the icing mechanism and accurately predicting two-dimensional ice shape. [ABSTRACT FROM AUTHOR]

Copyright of Geotechnical Engineering Technique / Yantu Gongcheng Jishu is the property of Geotechnical Engineering Technique Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The 2022 Paktika earthquake (moment magnitude: 6.2) occurred on June 22, 2022, near the border between the Khost and Paktika Provinces of Afghanistan, causing heavy damage and casualties in Paktika Province. This study evaluated the crustal deformation and associated strong motions induced by the Paktika earthquake. Crustal deformations were determined using the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique and three-dimensional finite element method (3DFEM) and the results were compared. The permanent ground displacements obtained from the DInSAR and 3D-FEM analyses were similar in terms of amplitude and areal distribution. Strong motions were estimated using the 3D-FEM with and without considering regional topography. The estimations of maximum ground acceleration, velocity, and permanent ground deformations were compared among each other as well as with those inferred from failures of some simple structures in the Spera and Gayan districts. The inferred maximum ground acceleration and velocity from the failed adobe structures were more than 300 Gal and 50 cm/s, respectively, nearly consistent with the estimates obtained using empirical methods. The empirical method yielded a maximum ground acceleration of 347 Gal, whereas the maximum ground velocity was approximately 50 cm/s. In light of these findings, some surface expressions of crustal deformations and strong ground motions, such as failures of soil and rock slopes and rockfalls, have been presented. The rock slope failures in the epicentral area were consistent with those observed during various earthquakes in Afghanistan and worldwide. [ABSTRACT FROM AUTHOR]

During the process of mining in a coal mine, the overlying rock mass above the working face undergoes deformation and transmits the deformation to the surface, leading to movement deformation. This has a significant impact on the structures above the mined-out area. In order to address the detrimental impact of surface deformation on structures, based on the engineering geological data and subsequent mining design at the Laohutai mining area, a study was conducted using numerical simulation methods. The research focused on the surface deformation and damage extent induced by multiple mining operations at the - 280 m shaft mining area during different time periods. Profiles N900 and E5800, representing the maximum changes in trend and dip, were selected for further investigation into the displacement and settlement patterns. The results indicate that, with the continuous mining in the extraction area, the overlying rock mass is influenced by the free face. Moreover, the cumulative effects exacerbate the extent and severity of rock mass failure. The maximum surface settlement and surface displacement during the overlapping extraction of multiple mining areas reached - 1. 89 m and 0. 43 m, respectively. It is evident that as mining progresses, surface movements intensify, which disrupt the initial equilibrium between structures and foundations. This disruption leads to structural deformation, and in cases of severe surface deformation, structural damage may occur. [ABSTRACT FROM AUTHOR]

Under the interference of climate warming and human engineering activities, the degradation of permafrost causes the frequent occurrence of geological disasters such as uneven foundation settlement and landslides, which brings great challenges to the construction and operational safety of road projects. In this paper, the spatial and temporal evolution of surface deformations along the Beihei Highway was investigated by combining the SBAS-InSAR technique and the surface frost number model after considering the vegetation factor with multi-source remote sensing observation data. After comprehensively considering factors such as climate change, permafrost degradation, anthropogenic disturbance, and vegetation disturbance, the surface uneven settlement and landslide processes were analyzed in conjunction with site surveys and ground data. The results show that the average deformation rate is approximately −16 mm/a over the 22 km section of the study area. The rate of surface deformation on the pavement is related to topography, and the rate of surface subsidence on the pavement is more pronounced in areas with high topographic relief and a sunny aspect. Permafrost along the roads in the study area showed an insignificant degradation trend, and at landslides with large surface deformation, permafrost showed a significant degradation trend. Meteorological monitoring data indicate that the annual minimum mean temperature in the study area is increasing rapidly at a rate of 1.266 °C/10a during the last 40 years. The occurrence of landslides is associated with precipitation and freeze–thaw cycles. There are interactions between permafrost degradation, landslides, and vegetation degradation, and permafrost and vegetation are important influences on uneven surface settlement. Focusing on the spatial and temporal evolution process of surface deformation in the permafrost zone can help to deeply understand the mechanism of climate change impact on road hazards in the permafrost zone. [ABSTRACT FROM AUTHOR]

Copyright of China Mining Magazine is the property of China Mining Magazine Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Railway Science & Engineering is the property of Journal of Railway Science & Engineering Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The accuracy of Interferometric Synthetic Aperture Radar surface deformation solutions depends on the quality of the chosen interferogram subset. We present a method to select interferogram subsets based on unwrapping errors rather than temporal baseline thresholds. Using Sentinel‐1 interferograms over the Tulare Basin, California, we show that subtle phase noise can lead to up to 31.5 mm/yr line‐of‐sight (LOS) errors in short temporal baseline subset solutions, while decorrelation leads to a systematic underestimation of LOS rates (up to 92.3 mm/yr) in long temporal baseline subset solutions. Our new workflow better mitigates these noise sources at the same time. In the Eagle Ford region, Texas, our strategy better reconstructed up to 11.9 cm of cumulative LOS deformation between 2017 and 2021 over a ∼ ${\sim} $900 km2 $\mathrm{k}{\mathrm{m}}^{\mathrm{2}}$ region. This deformation feature can be linked to the total volume of produced oil and water through a linear relationship. Plain Language Summary: Surface deformation estimates derived from spaceborne imaging radar data are often impacted by weather conditions and surface vegetation changes. While it is common to select high‐quality data based on the time separation between two image passes, we designed a new data selection strategy based on measurable phase artifacts. We applied the new method to two vegetated regions that experienced land subsidence due to agricultural groundwater pumping (Tulare Basin, California) or oil and gas production (Eagle Ford region, Texas). In both cases, we show that surface deformation estimates can vary substantially depending on the choice of data subsets. Our strategy better mitigates different InSAR measurement noise terms at the same time. We showed that the observed subsidence in the Eagle Ford region is linearly proportional to the volume of produced oil and water from unconventional oil and gas resources exploitation. Furthermore, ongoing production activities have led to an increase in human‐induced earthquakes. Based on these findings, accurate surface deformation derived from InSAR data is now achievable in densely vegetated regions and can play an important role in future induced seismicity studies. Key Points: InSAR phase coherence does not always decrease with temporal baselinesChoosing interferograms based on phase unwrapping errors rather than temporal baselines better mitigates InSAR measurement noiseThe improved InSAR analysis strategy reveals up to 11.9 cm of LOS deformation signals related to oil and gas operations over the Eagle Ford [ABSTRACT FROM AUTHOR]

• Inhomogeneous elastic properties are identified using an explicit inverse method. • High accuracy in identification can be achieved using limited surface deformation. • The explicit inverse method can reduce the relative error from 40 % to 5 %. Identifying the spatial variation of stiffness properties in soft tissues nondestructively, with limited surface measurements, poses significant challenges. In this paper, we present a novel explicit inverse approach designed to characterize the nonhomogeneous elastic property distribution of soft tissues using only surface displacement datasets. In contrast to the prevalent implicit inverse approach, which focuses on optimizing the elastic properties of individual pixels, our proposed method optimizes the geometric parameters of deformable and movable components, as well as shear moduli of each component. As a result, the proposed approach requires far fewer optimization variables, streamlining the process. Numerical tests conducted in this study demonstrate the superiority of the explicit inverse method over the implicit inverse method, providing much-improved reconstructed results. In particular for a ring structure, while the average relative error of reconstruction using the implicit inverse method can exceed 40 %, the explicit inverse method achieves a remarkable average relative error of only 5 %. Given that surface displacements are easily measurable, the integration of our proposed explicit inverse method with low-cost imaging techniques shows great potential in accurately mapping the elastic property distribution of biological tissues. [ABSTRACT FROM AUTHOR]

Dislocations are being used to tune versatile mechanical and functional properties in oxides with most current studies focusing on single crystals. For potentially wider applications, polycrystalline ceramics are of concern, provided that dislocations can be successfully introduced. However, in addition to preexisting pores and flaws, a major barrier for bulk plastic deformation of polycrystalline ceramics lies in the grain boundaries (GBs), which can lead to dislocation pile‐up and cracking at the GBs due to the lack of sufficient independent slip systems in ceramics at room temperature. Here, we use the cyclic Brinell indentation method to circumvent the bulk deformation and focus on near‐surface regions to investigate the plastic deformation of polycrystalline SrTiO3 at room temperature. Dislocation etch‐pit analysis suggests that plastic deformation can be initiated within the grains, at the GBs, and from the GB triple junction pores. The deformability of the individual grains is found to be dependent on the number of cycles, as also independently evidenced on single‐crystal SrTiO3 with representative surface orientations (001), (011), and (111). We also identify a grain‐size‐dependent plastic deformation. [ABSTRACT FROM AUTHOR]

In order to eliminate the potential safety hazard of the mining area and the society caused by the ground subsidence disaster triggered by the continuous mining of the ore body, it is extremely important to carry out effective monitoring of the surface deformation in the mining area and research on the deformation mechanism. Therefore, based on the research background of Dengganshu mine section of Jinsha Mining Industry, the surface deformation monitoring of mining area is carried out using time-series interferometric synthetic aperture radar (InSAR) technology, and a three-dimensional model is established combining with the actual site to simulate the underground excavation process and obtain the distribution law of the displacement, stress and plastic zone of the surrounding rock of the mining area through FLAC3D, so as to comprehensively explore the deformation process and mechanism of the overlying rock and surface under the action of underground mining. The results show that the study area is in the state of non-uniform deformation, and the obvious deformation area is mainly distributed along the highway slope, and its cumulative shape variable fluctuates are in the range of 80~20 mm. Under the influence of mining, the surrounding rock of the goaf is mainly shear failure, and the plastic zone expands gradually with the increase of mining depth. With the advance of mining depth, under the action of its own gravity and mining stress, the magnitude and influence range of concentrated stress increase, and the disturbance influence on the surface is superimposed. At the end of the third mining, the movement range of surrounding rock in the goaf gradually increases and penetrates to the surface, causing surface deformation. The numerical simulation is consistent with the surface subsidence and deformation results shown by InSAR monitoring, which proves the rationality and reliability of the simulation process. The results show that the combination of InSAR monitoring and numerical simulation can directly reflect the formation process and mechanism of surface deformation in the mining area. This method can provide a reference for the monitoring of surface deformation disasters in similar underground mines and the prevention of potential disasters. [ABSTRACT FROM AUTHOR]

We performed an extensive analysis of C-band SAR datasets provided by the European Space Agency (ESA) satellites ERS-1/2, Envisat ASAR, and Sentinel-1 in the period 1992–2020 aiming at reconstructing the multi-decadal spatial and temporal evolution of the surface displacements at the Brienz/Brinzauls landslide complex, located in canton Graubünden (Switzerland). To this end, we analyzed about 1000 SAR images by applying differential interferometry (InSAR), multitemporal stacking, and persistent scatterer interferometry (PSI) approaches. Moreover, we jointly considered digital image correlation (DIC) on high-resolution multi-temporal digital terrain models (DTM) generated from airborne surveys and InSAR results to compute 3-D surface deformation fields. The extensive network of GNSS stations across the Brienz landslide complex allowed us to extensively validate the deformation results obtained in our remote sensing analyses. Here, we illustrate the limitations occurring when relying on InSAR and/or PSI measurements for the analysis and interpretation of complex landslide scenarios, especially in cases of relevant spatial and temporal heterogeneities of the deformation field. The joint use of InSAR and DIC can deliver a better picture of the evolution of the deformation field, however, not for all displacement components. Since InSAR, PSI and DIC measurements are nowadays routinely used in the framework of local investigations, as well as in regional, national, and/or continental monitoring programs, our results are of major importance for users aiming at a comprehensive understanding of these datasets in landslide scenarios. [ABSTRACT FROM AUTHOR]

Differential interferometric synthetic aperture radar (InSAR) is a remote sensing technique for measuring surface displacements with precision down to millimeters, most commonly from satellites. In permafrost landscapes, InSAR measurements can provide valuable information on geomorphic processes and hazards, including thaw subsidence and frost heave, thermokarst, and permafrost creep. We first review recent progress in InSAR data availability, InSAR processing and uncertainty analysis methods relevant to permafrost studies. These technical advances have contributed to our understanding of surface deformation in flat and sloping terrain in polar and mountainous regions. We emphasize two emerging trends. First, InSAR increasingly enables insight into the mechanisms, controls, and drivers of permafrost landscape dynamics on subseasonal to decadal time scales. Second, InSAR observations in conjunction with models enable novel ways to infer subsurface parameters, such as near‐surface ground ice content and active layer thickness. We anticipate that in the coming decade, InSAR will mature into a widely used operational tool for monitoring, modeling, and planning across rapidly changing permafrost landscapes. [ABSTRACT FROM AUTHOR]

IntroductionSurface deformation in the Three Gorges Reservoir area poses significant threats to infrastructure and safety due to complex geological and hydrological factors. Despite existing studies, systematic exploration of long-term deformation characteristics and their driving mechanisms remains limited. This study combines SBAS-InSAR technology and machine learning to analyze and predict surface deformation in Fengjie County, Chongqing, China, between 2020 and 2022, focusing on riverside urban ground, riverside road slopes, and ancient landslides in the reservoir area.MethodsSBAS-InSAR technology was applied to 36 Sentinel-1A images to monitor surface deformation, complemented by hydrological and meteorological data. Machine learning models—Random Forest (RF), Extremely Randomized Trees (ERT), Gradient Boosting Decision Tree (GBDT), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM)—were evaluated using six metrics, including RMSE, R2, and SMAPE, to assess their predictive performance across diverse geological settings.ResultsDeformation rates for riverside urban ground, road slopes, and ancient landslides were −3.48 ± 2.91 mm/yr, −5.19 ± 3.62 mm/yr, and −6.02 ± 4.55 mm/yr, respectively, with ancient landslides exhibiting the most pronounced deformation. A negative correlation was observed between reservoir water level decline and subsidence, highlighting the influence of seasonal hydrological adjustments. Urbanization and infrastructure development further exacerbated deformation processes. Among the models, LSTM demonstrated superior predictive accuracy but showed overestimation trends in ancient landslide areas.DiscussionReservoir water level adjustments emerged as a critical driver of subsidence, with rapid water level declines leading to increased pore pressure and soil compression. Seasonal effects were particularly evident, with higher subsidence rates during and after the rainy season. Human activities, including urbanization and road construction, significantly intensified deformation, disrupting natural geological conditions. Progressive slope failure linked to road expansion underscored the long-term impacts of engineering activities. For ancient landslides, accelerated deformation patterns were linked to prolonged drought and reservoir-induced hydrological changes. While LSTM models showed high accuracy, their limitations in complex geological settings highlight the need for hybrid approaches combining machine learning with physical models. Future research should emphasize developing integrated frameworks for long-term risk assessment and mitigation strategies in reservoir environments.ConclusionsThis study provides new insights into the complex surface dynamics in the Three Gorges Reservoir area, emphasizing the interplay of hydrological, geological, and anthropogenic factors. The findings highlight the need for adaptive management strategies and improved predictive models to mitigate subsidence risks.

The subject of this work is the development of a nonlinear model of the interaction of an unsteady fluid flow with a structure and finding analytical solutions for the system of equations that correspond to the specified model. The convection effect of the fluid velocity field was already considered in the previous works of the authors of this paper. These studies are devoted to the water hammer without considering the "flow-structure" interaction. This work expands the possibilities of modeling and considers four equations instead of two equations of the theory of the water hammer (equations of conservation of mass and momentum), two of which relate to the motion of particles of a solid body (pipes or structures). The novelty of this work lies in the consideration of the model that describes the interaction of the flow with the structure, the convection in the velocity field, and the effect, together with the friction of the fluid against the solid wall, on the dynamics of the shock pulse propagation process both in the fluid and in the solid body. It should be noted that the solution of the nonlinear system of differential equations as a whole is carried out by an analytical method, which makes it possible to obtain an exact (rather than numerical) solution of the problem. Since the effects of various factors should be evaluated by comparison with the main components, dimensionless equations containing six parameters (dimensionless combinations) were obtained in this study. Two of these parameters were named after scientists – Darcy and Weisbach (steady friction) and Bruno (unsteady friction). Particular cases of the general (full) model were considered, and the effects of various factors on the dynamics of the interaction of the flow with the structure during the propagation of the shock pulse were determined. Research methods are purely theoretical. The concepts of a self-similar equation and a system of equations, balances of forces acting on particles of a fluid and a solid body, and a standard method of reducing a system of equations to a single equivalent equation are used. Conclusions. An extended model of the interaction between the unsteady fluid flow and the structure is proposed. The transition to a self-similar variable makes it possible to solve a nonlinear system of differential equations and obtain an analytical (exact) solution. The functions of longitudinal stress in a solid body, pressure disturbance, and velocity of motion of particles in a solid body (pipe) are linearly expressed by the velocity of shock pulse propagation in the fluid. It should also be noted that the results for the particular case of the linear model completely agree with the already known ones. The advantage of using a self-similar solution is that it is easy to obtain. The results of previous studies on the water hammer problem were qualitatively consistent. As the fluid viscosity increases, the shock pulse domain becomes more concentrative.

Bu çalışmanın amacı, Eskişehir ilinde geçmiş depremlerde sıvılaşmanın varlığını araştırmaktır. Bu kapsamda Eskibağlar, Yenibağlar, Vişnelik, Sümer ve Şarhöyük mahallelerindeki temel kazılarında inceleme yapılmıştır. Şarhöyük ve Vişnelik mahallelerindeki temel kazılarında bulunan kum mercekleri dışında belirgin kum sokulumu ve benzeri oluşumlar diğer kazılarda bulunamamıştır. Depremde oluşacak sıvılaşma nedeniyle temel kazılarında yüzey deformasyonu oluşabilirliği de araştırılmıştır. 0.33g ve 0.48g ivmelerini oluşturacak deprem senaryoları değerlendirilmiştir. 0.33g ivme ile oluşacak bir deprem senaryosunda Şarhöyük ve Sümer mallelerin temel kazılarında sıvılaşma belirlenememiştir. Yenibağlar, Eskibağlar ve Vişnelik mahallelerindeki temel kazılarında sıvılaşabilir seviyeler belirlenmiştir. 0.48g ivmeli deprem senaryosunda tüm temel kazı sahalarında sıvılaşan seviyeler belirlenmiştir. Bu seviyelerin kalınlıklarının 0.33g deprem senaryosuna göre arttığı görülmüştür. Sıvılaşma Şiddeti İndeksi-Kapak zemin Kalınlığı (m) abağına göre 0.33g deprem senaryosuna göre Yenibağlar mahallesinde deformasyon izi yüzeyde beklenmemektedir. Eskibağlar ve Vişnelik mahallelerinde ise sıvılaşma beklenmemektedir. 0.48g depremi senaryosuna göre Vişnelik ve Yenibağlar mahallelerinde yüzeyde sıvılaşma deformasyonu beklenmektedir. Şarhöyük ve Eskibağlar mahallelerinde yüzeyde sıvılaşma izi beklenmezken, Sümer mahallesinde sıvılaşma beklenmemektedir.

The connections between parameter surfaces enable the development of various geometric designs. However, these surfaces are generally connected along their boundaries in a rectangular domain. This study investigated the methods for connecting surfaces along a curve. To this end, we introduced two-variable degenerate functions and utilized their algebraic properties to characterize the form of the parameter surfaces for practical surface construction. The results were used to deform the surfaces along the curve. For application, we presented the examples of deformations using Bézier surfaces and extended them to general surfaces. [ABSTRACT FROM AUTHOR]

Mining-induced surface deformation disrupts ecological balance and impedes economic progress. This study employs SBAS-InSAR with 107-view of ascending and descending SAR data from Sentinel-1, spanning February 2017 to September 2020, to monitor surface deformation in the Fa'er Coal Mine, Guizhou Province. Analysis on the surface deformation time series reveals the relationship between underground mining and surface shifts. Considering geological conditions, mining activities, duration, and ranges, the study determines surface movement parameters for the coal mine. It asserts that mining depth significantly influences surface movement parameters in mountainous mining areas. Increasing mining depth elevates the strike movement angle on the deeper side of the burial depth by 22.84°, while decreasing by 7.74° on the shallower side. Uphill movement angles decrease by 4.06°, while downhill movement angles increase by 15.71°. This emphasizes the technology's suitability for local mining design, which lays the groundwork for resource development, disaster prevention, and ecological protection in analogous contexts. [ABSTRACT FROM AUTHOR]

Mining operations disrupt the structure of rock layers, leading to surface deformations and potential mining damage. This issue has been extensively studied since the 19th century using various analytical, geometric-integral, and stochastic methods. Since the 1990s, numerical methods have been increasingly applied to determine changes in the stress and strain states of rock masses due to mining activities. These methods account for numerous additional factors influencing surface deformation, offering significant advantages over classical approaches. However, modelling rock masses presents challenges, particularly in calibrating the mechanical parameters of rock layers, an area extensively researched with numerous publications. In this study, we determined the mechanical parameter values of rock layers at the advancing mining front using a custom Python script and Finite Element Method (FEM) numerical models. We also introduced a modification to evaluate the error of the estimated parameter values. Numerical analyses were conducted for the Piast–Ziemowit mine region in Poland, utilizing mining, geological, and surveying data. Our results demonstrate that accurate calibration of mechanical parameters is crucial for reliable predictions of surface deformations. The proposed methodology enhances the precision of numerical models, providing a more robust framework for assessing the impact of mining activities on rock layers. [ABSTRACT FROM AUTHOR]

This study aimed to map and analyze the spatial pattern of the surface deformation associated with the 2024 Noto Peninsula earthquake (Mw7.5) using structure-from-motion/multi-view-stereo (SfM–MVS), an advanced photogrammetric technique. The analysis was conducted using digital aerial photographs with a ground pixel dimension of 0.2 m (captured the day after the earthquake). Horizontal locations of GCPs were determined using pre-earthquake data to remove the wide-area horizontal crustal deformation component. The elevations of the GCPs were corrected by incorporating quasi-vertical values derived from a 2.5-dimensional analysis of synthetic aperture radar (SAR) results. In the synclinorium structure area, where no active fault had previously been identified, we observed a 5 km long uplift zone (0.1 to 0.2 km in width), along with multiple scarps that reached a maximum height of 2.2 m. The area and shape of the surface deformation suggested that the induced uplift and surrounding landslides were related to fold structures and their growth. Thus, our study shows the efficacy of SfM–MVS with respect to accurately mapping earthquake-induced deformations, providing crucial data for understanding seismic activity and informing disaster-response strategies. [ABSTRACT FROM AUTHOR]

Extensive researches have been conducted on the relationship between surface deformation and the properties of upper crust. However, the link between surface deformation and lower crustal rheology, especially in a three‐dimensional context, remains unclear. In this study, we utilize sandbox modeling to investigate the impact of lower crustal rheology on surface deformation during oblique extension. Under the same conditions, six models with different lower crustal viscosities, both with and without syn‐kinematic deposits, are conducted. The results indicate that a decrease in lower crustal viscosity may contribute to an increase in: (a) graben width, (b) graben length, (c) graben spacing, (d) the number of isolated rifts and (e) topographic relief of oblique extensional systems, while also leading to a reduction in the total number of grabens. Notably, there exists a negative linear correlation between graben spacing and lower crustal viscosity. In map view, the angle between fault strike and the direction of pre‐existing discontinuities increases as the viscosity of the lower crust decreases. Furthermore, the frequency of large rakes (>50°) decreases with decreasing lower crustal viscosity. These findings align with natural examples such as the East African Rift System, Weihe Graben and the South Tibetan Rift in terms of geomorphology, tectonics, and crustal rheology. Through a comprehensive comparison of the graben width, spacing, and the angle between fault strike and the direction of pre‐existing discontinuities, our study provides valuable insights into the rheology of the lower crust in natural settings. Key Points: Lower crustal viscosity affects width, spacing, relief, and fault strike of oblique rifts, forming regular changes in rift geomorphologyFaults show increasing strike‐slip components with decreasing lower crustal viscosityOur models can provide new insights on understanding the lower crustal viscosity from surface deformation in nature [ABSTRACT FROM AUTHOR]

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The construction of tunnels in conditions of dense urban development affects buildings, structures, and engineering communications located at the surface. In this work, through dispersion analysis, factors influencing the settlement of the earth's surface and buildings during tunneling were selected. Subsequently, a model based on statistically significant parameters that can predict deformations at the pre-design stage was created. This research was conducted using data from geotechnical monitoring obtained during the construction of underground structures, with information about the technological parameters of shield tunneling in the construction of the single-track lines of the Moscow Metro using TBM with face-support pressure and engineering–geological conditions. In the obtained model, there is a clear dependency between the additional displacement of the monitoring object located above the projected tunnel and the average face-support pressure causing the mentioned deformations. The response is also affected by the soil deformation model at the tunnel face, the depth of the tunnel, and the soil excavation for the installation of one ring. [ABSTRACT FROM AUTHOR]

The viaduct is an important infrastructure for urban sustainable development, but it will inevitably pass through a coal mining subsidence area in coal resource-based cities, which poses a threat to the construction and operation of the viaduct. However, there is a lack of research on long time-series monitoring and assessing the safety of elevated bridges above subsidence areas, both domestically and internationally. In this study, a resource-based city viaduct in Shandong, China, was selected as the research object, utilizing SBAS-InSAR technology for deformation monitoring during bridge construction and post-opening phases. The viaduct based on the goaf was analyzed by the key settlement subsection. Before completing construction (March 2019 to December 2020), research revealed that the cumulative maximum deformation in the bridge area was 44mm and the maximum uplift was 22 mm, with overall stability in the underlying subsidence area. After completion (January 2021 to July 2023), the cumulative maximum deformation value in the elevated bridge area was 10mm and the maximum uplift was 6 mm, indicating minimal fluctuations over three years, maintaining overall stability. This stable condition ensures the safety of construction and operation of regional elevated bridges. These findings not only support the safe operation of bridges in underlying subsidence areas but also provide a new approach to sustainable areas globally, especially in coal resource-based urban areas. [ABSTRACT FROM AUTHOR]

The surface topography of substrates is a crucial factor that determines the interaction with biological materials in bioengineering research. Therefore, it is important to appropriately modify the surface topography according to the research purpose. Surface topography can be fabricated in various forms, such as wrinkles, creases, and ridges using surface deformation techniques, which can contribute to the performance enhancement of cell chips, organ chips, and biosensors. This review provides a comprehensive overview of the characteristics of soft, hard, and hybrid substrates used in the bioengineering field and the surface deformation techniques applied to the substrates. Furthermore, this review summarizes the cases of cell-based research and other applications, such as biosensor research, that utilize surface deformation techniques. In cell-based research, various studies have reported optimized cell behavior and differentiation through surface deformation, while, in the biosensor and biofilm fields, performance improvement cases due to surface deformation have been reported. Through these studies, we confirm the contribution of surface deformation techniques to the advancement of the bioengineering field. In the future, it is expected that the application of surface deformation techniques to the real-time interaction analysis between biological materials and dynamically deformable substrates will increase the utilization and importance of these techniques in various fields, including cell research and biosensors. [ABSTRACT FROM AUTHOR]

Copyright of Coal Science & Technology (0253-2336) is the property of Coal Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)