Surface Deformation Research Articles

Mechanical responses and fracturing behaviors of coal under complex normal and shear stresses, Part I: Experimental results

This work presents experimental tests based on coal collected from a coal mine based underground water reservoir (CMUWR). The mechanical responses of dry and water-soaked coal samples under the complex normal and shear stresses under multi-amplitude and variable frequency is investigated. The experimental results reveal the effects of stress path, water soaking and frequency on deformation, energy dissipation, secant modulus and shear failure surface roughness. The experimental results show that when normal and shear stresses are applied simultaneously, there is a significant competitive relationship between them. On the dominant side, the strain rate will be significantly increased. The sample under a loading frequency of 0.2 Hz exhibits a longer fatigue life. During the cyclic shear test, the shear strain of the water-soaked sample is higher than that of the dry samples. The average roughness coefficient of failure surface exhibits an increasing pattern with increase in shear strength, the elevated roughness of a shear surface is advantageous in constraining shear displacements of specimens, thereby lowering the energy dissipation. This study can provide theoretical and practical implications for a long-term safety evaluation of CMUWR.

Surface Deformation Time-Series Monitoring and Stability Analysis of Elevated Bridge Sites in a Coal Resource-Based City

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.

Fiber Laser Writing of Highly Sensitive Nickel Nanoparticle-Incorporated Graphene Strain Sensors.

Unlocking new dimensions in wearable sensor technology, this research highlights ultrasensitive stretchable strain sensors fabricated with the customized laser-induced graphene (LIG) decorated with uniformly distributed nickel nanoparticles with a fiber laser writing process. The nickel nanoparticle-incorporated LIG (Ni-NPs@LIG) strain sensors fabricated by a simple all-laser-based method utilize a commercial fiber laser. The Ni-NPs@LIG sensors showcase an impressive gauge factor, reaching up to 248 for strain values below 5%, demonstrating a sensitivity increase of up to 430% compared to the pure LIG sensors. Moreover, these sensors offer adjustable strain sensitivity based on laser fluence. The key advancement of this study lies in the direct laser writing of highly porous nickel-graphene nanostructures with adjustable properties, making them applicable across a broad range of applications. As an application demonstration, the strain sensors were employed to assess the small deformation of a pouch battery or track the large deformation of a balloon surface.

Van Hove annihilation and nematic instability on a kagome lattice.

A nematic phase breaks the point-group symmetry of the crystal lattice and is known to emerge in correlated materials. Here we report the observation of an intra-unit-cell nematic order and associated Fermi surface deformation in the kagome metal ScV6Sn6. Using scanning tunnelling microscopy and scanning tunnelling spectroscopy, we reveal a stripe-like nematic order breaking the crystal rotational symmetry within the kagome lattice itself. Moreover, we identify a set of Van Hove singularities adhering to the kagome-layer electrons, which appear along one direction of the Brillouin zone and are annihilated along other high-symmetry directions, revealing rotational symmetry breaking. Via detailed spectroscopic maps, we further observe an elliptical deformation of the Fermi surface, which provides direct evidence for an electronically mediated nematic order. Our work not only bridges the gap between electronic nematicity and kagome physics but also sheds light on the potential mechanism for realizing symmetry-broken phases in correlated electron systems.

A Deep-Learning-Based Algorithm for Landslide Detection over Wide Areas Using InSAR Images Considering Topographic Features.

The joint action of human activities and environmental changes contributes to the frequent occurrence of landslide, causing major hazards. Using Interferometric Synthetic Aperture Radar (InSAR) technique enables the detailed detection of surface deformation, facilitating early landslide detection. The growing availability of SAR data and the development of artificial intelligence have spurred the integration of deep learning methods with InSAR for intelligent geological identification. However, existing studies using deep learning methods to detect landslides in InSAR deformation often rely on single InSAR data, which leads to the presence of other types of geological hazards in the identification results and limits the accuracy of landslide identification. Landslides are affected by many factors, especially topographic features. To enhance the accuracy of landslide identification, this study improves the existing geological hazard detection model and proposes a multi-source data fusion network termed MSFD-Net. MSFD-Net employs a pseudo-Siamese network without weight sharing, enabling the extraction of texture features from the wrapped deformation data and topographic features from topographic data, which are then fused in higher-level feature layers. We conducted comparative experiments on different networks and ablation experiments, and the results show that the proposed method achieved the best performance. We applied our method to the middle and upper reaches of the Yellow River in eastern Qinghai Province, China, and obtained deformation rates using Sentinel-1 SAR data from 2018 to 2020 in the region, ultimately identifying 254 landslides. Quantitative evaluations reveal that most detected landslides in the study area occurred at an elevation of 2500-3700 m with slope angles of 10-30°. The proposed landslide detection algorithm holds significant promise for quickly and accurately detecting wide-area landslides, facilitating timely preventive and control measures.

Unsteady flow of nanofluid over a sheet of variable thickness with nonlinear kinematics

The transport of heat in an unsteady flow of nanofluid has been discussed in this paper. The flow is maintained over a non-flat, variably porous, and moving sheet in the present simulation. Moreover, the sheet has both constant temperature and nanoparticle concentration at its surface. Unsteadiness in all field variables (i.e. the flow, temperature, and nanoparticles concentration) has been produced by the time-dependent quantities, specified at the surface of the sheet (i.e. kinematics of sheet). The well-known Buongiorno model of nanofluid has been undertaken in the present studies. Furthermore, the simulation includes the particular cases of uniform and linear (polynomial & algebraic functions) stretching/shrinking and injection/suction velocities. Besides that observations of the same nature have been recorded for the non-flat sheet. The boundary layer form of the governing PDEs has been utilized to evaluate the exact status of field variables in the flow domain. Appropriate conditions are imposed by considering the geometry of the flow problem. The problem at hand is simplified by introducing a new set of functions for the field variables because of boundary inputs. After this treatment, the system of boundary value ODEs, which contains several dimensionless numbers (parameters), has appeared, and the problem is solved numerically for various values of parameters, involved in it. More precisely, effects of unsteadiness, wall roughness, surface deformation parameters, Prandtl, Schmidt, thermophoretic, and Brownian motion numbers have been seen on profiles of four field variables. Besides that, the numerical results are also obtained for the skin friction coefficient, Nusselt, and Sherwood numbers. The present modelled problem and its solution are compared with classical models of that particular nature and with their solutions.

Аналіз впливу на прохідність автобронетанкової техніки конструктивних факторів та методика її збільшення шляхом автоматичного регулювання тиску повітря в шинах коліс

The purpose of the study is to analyze and determine the influence of various factors on the patency of armored vehicles (AMT) operated by the National Guard of Ukraine. Determination of the change in patency during the movement of AMT in different road and climatic conditions. Analysis of static and dynamic loads, which are characteristic of AMT movement over rough terrain, and their impact on the efficiency of the vehicle. The theoretical component of the study was carried out using mathematical modeling of the work process of regulating the air pressure in tires of AMT wheels, using the example of changes in the characteristics of adhesion coefficients with the supporting surface and rolling resistance depending on the change in pressure and load on the tires of the wheels when the AMT is moving off-road. As a result of mathematical modeling, the dependences of air pressure in tires of AMT wheels were obtained, depending on the coefficient of rolling resistance and the load on each of the wheels. Which, in turn, makes it possible to move to a sufficiently complete mathematical modeling of the movement of AMT on off-road, taking into account the reference cross-country ability. In the process of theoretical research, the structural parameters of the impact on the patency of AMT were analyzed quite completely, and a generalized comparative indicator of the patency parameters of vehicles was proposed. When analyzing it, it was found that the AMT tire and, specifically, the change in air pressure in it, have a significant impact on the bearing capacity. The authors propose to use the following evaluation criteria as criteria for assessing the efficiency of the passability when driving on deformable surfaces: a generalized comparative indicator of the parameters of the passability of vehicles. As a result of consideration of which, a significant influence on the patency parameters of the tires and directly the air pressure in them was established. Regulation and change of the air pressure in the tires of the wheels depending on the change in the coefficient of rolling resistance as well as the change in the load on each wheel, which are the ratio of the work that is spent on the traction force when overcoming different degrees of heaviness of the resistance of the supporting surfaces with the effect of deformation. And the load that falls on each of the AMT wheels allowed us to draw conclusions about the improvement of the regular tire pressure regulation system (RPRS) of the wheels.

Double Floquet-Bloch transforms and the far-field asymptotics of Green's functions tailored to periodic structures

We propose a general procedure to study double integrals arising when considering wave propagation in periodic structures. This method, based on a complex deformation of the integration surface to bypass the integrands' singularities, is particularly efficient to estimate the Green's functions of such structures in the far field. We provide several illustrative examples and explicit asymptotic formulas. Special attention is devoted to the pathological cases of degeneracies, such as Dirac conical points. Published by the American Physical Society 2024

On the Move: 2023 Observations on Real Time Graben Formation, Grindavík, Iceland

AbstractGrabens, or valleys formed during extensional tectonic events, are common but rarely observed during formation. In November 2023, inelastic surface deformation formed abruptly along Iceland's plate boundary in Grindavík. We documented graben formation in real‐time through satellite mapping (InSAR), seismicity, GNSS data, repeated lidar surveys, and field mapping. Five normal faults and ∼12 fissures ruptured the surface delineating two grabens separated by a horst, a context not present in other contemporary case studies. The graben normal faults slipped rapidly (over hours) and maximum surface motions coincided with the occurrence of turbulent seismic swarms in both space and time. Although 3 eruptions took place ∼15 km northeast of Grindavík from 2021 to 2023, attributed to magma intrusions (i.e., dikes), none of these also formed grabens. Thus, the Grindavík grabens shows evidence for tectonic origins. Real‐time monitoring of these phenomena provide insight into graben formation on Earth and potentially on other planets.

Mapping of Land Surface Deformation Using Ps-Insar for Disaster Risk Management in the Future

DKI Jakarta is experiencing land subsidence due to overexploitation of its use and the increasing population. It is feared that this decline or deformation will occur in the location of the new national capital. The research objective is "Mapping of Land Surface Deformation using PS-InSAR for Disaster Risk Management in the Future." Quantitative and qualitative research and data collection methods use secondary and primary data. Secondary data in the form of Permanent Scatterers Interferometry Synthetic Aperture Radar (PS-InSAR) Sentinel-1A images to determine soil deformation. Primary data uses a questionnaire to assess disaster risk management. Data analysis uses spatial and statistical analysis. Spatial analysis for land deformation mapping and statistical analysis for risk management. The results showed that the pattern of land deformation before the determination of the location of the capital city of Indonesia was random. On the other hand, after decision-making, it appears to be more systematic and homogeneous in adjacent areas with a decreasing range of about 5 cm per year. Other findings show that disaster risk management carried out by several agencies, especially the problem of land deformation in East Kalimantan, is still far from expectations and very minimal. The findings can be used for future disaster risk management to minimize negative impacts and reduce disaster risk.Keywords: PS-INSAR; Land Deformation; Capital City; Disaster Risk Management

Analisis Bencana Longsor akibat Gempa bumi Cianjur 2022 dengan DInSAR

Indonesia is a country with a high potential for disasters such as earthquakes, which usually cause changes in the shape/position of the earth's surface (deformation). The Cianjur area has a seismic vulnerability level value based on maximum ground acceleration, maximum intensity and earthquake return period. On Monday, November 21, 2022 at 13.21 WIB there was an earthquake with a magnitude of 5.6 M in the Cianjur area of West Java based on BMKG data, until November 22, 2022 there were 140 aftershocks with magnitudes of 1.2-4.2 and an average depth of approximately 10 km. As a result, causing subsidence, the purpose of this study is to determine the magnitude of subsidence in landslides due to the 2022 Cianjur earthquake using the DInSAR method. Vertical land subsidence (displacement data) due to the earthquake from DInSAR observations on displacement data, which ranged up to -101mm vertically with two soil types andosol and cambisol Overlay analysis of soil type and displacement data showed the highest area of displacement, found a match based on information circulating that Cugenang Sub-district is the most severely affected area (the existence of a new fault "Cugenang").

A Study on Deformation Characteristics and Stability of Soft Surrounding Rock for a Shallow-Buried Tunnel

The Heimaguan Tunnel in China serves as a case study to exemplify the variation laws related to surface settlement, deformation, and stress characteristics in a shallow-buried soft-rock tunnel, while emphasizing in the tunnel support requirements. The first stage of this study begins with monitoring the time-varying characteristics of surface settlement, vault subsidence, and the horizontal convergence of Grade V rock. In the second stage, Peck theory is used to calculate the distribution characteristics of surface settlement. The results of both stages are compared to create a vault settlement model, thus establishing the horizontal convergence based on exponential function, logarithmic function and hyperbolic function, and determining the optimal time of secondary lining construction. On this basis, the time-dependent variation laws and characteristics of vertical and horizontal displacement and principal stress of surrounding rock are studied. After this, using simulation and analysis, the proper support is recommended. The study reveals that the surface settlement, vault subsidence, and horizontal convergence of the shallow-buried soft-rock tunnel stabilize within 25–30 days. Peck theory closely aligns with predictions based on exponential functions, with only a 0.72% difference. The recommended time for secondary lining application is 26–27 days.

A novel deformation measurement method for rotating blade based on PSO-ILS image correlation matching and mismatch correction

Abstract Aiming at the problem of small measurement range and difficult measurement of traditional contact sensor method in the rotating state of aero-engine blades, this paper proposes a novel deformation measurement method for rotating blade based on image correlation matching and mismatch correction. Firstly, a Particle Swarm Optimization-Iterative Local Search image intelligent matching algorithm is proposed, which effectively balances global search and local optimization, and the image matching displacement accuracy reaches 10−3 pixel. Secondly, a mismatch point detection method based on multi-scale local Root Mean Square is proposed, and the high-precision detection of mismatch points is realized by considering the influence of local structure. Finally, through the hierarchical refinement of the sub-pixel level mismatch point correction method, the mismatch point is corrected in the two iterative stages of global search and local optimization. The corrected mismatch point response value K is reduced by 99% compared with that before correction, which further improves the accuracy of deformation field calculation. In the experiment, the deformation of the rotating blade of 4500 RPM is measured, which proves that the image intelligent matching algorithm and the deformation field calculation method proposed in this paper can provide new methods and technical support for the accurate measurement of the blade surface deformation.

Surface deformation monitoring of Raniganj coalfield, India, using advanced InSAR and DGPS

The Raniganj coalfield, which is the oldest coal mine in India, is susceptible to ground subsidence. For the purpose of detecting surface deformation, this work makes use of field surveys, interferometric synthetic aperture radar (InSAR), and Differential GPS (DGPS). The study utilised Sentinel-1 InSAR data spanning from 2017 to 2023. PS-InSAR was used for both ascending and descending datasets, while SBAS-InSAR was used for descending datasets alone. Records show a maximum subsidence rate of −21.18 mm/year. Three surface deformation maps were generated from time-series assessments of individual locations, revealing regions undergoing significant changes. Known mining collapse locations and continuing deformation zones were designated with four differential GPS stations. By analysing the DGPS data with the GAMIT/GLOBK software, we were able to measure surfaces that were undergoing rapid deformation. Using Google Earth Engine (GEE), we generated thermal maps to delve deeper into the coal fire activity. We found coal bed methane (CBM) mining causing substantial subsidence in Kataberia and the surrounding areas. Shyamsundarpur and New Kenda are impacted by mining voids and coal fire-induced subsidence, respectively. The results of this study give the Raniganj region’s decision-making procedures more credibility in terms of minimising and controlling geological dangers.

Accurate modeling of thermal-optical performance for a lightweight SiC mirror

The SiC mirror has excellent structural rigidity and thermal stability, making it widely applicable in high-power optical systems. This manuscript aims to establish a coupled analysis model of thermal-optical performance for a lightweight SiC reflector under high-power laser irradiation. First, based on the Fourier principle, the transient temperature rise of the mirror is analyzed using the finite element method, considering boundary conditions such as heat source and convective radiation. A transient thermal response model for the mirror is established. Then, the reflective surface deformation is solved based on the mirror temperature field. By processing the data of node deformation, the decrease in the mirror surface shape accuracy (RMS) value is obtained. Finally, the experimental platform is built to measure the transient temperature rise and wavefront aberration change of the mirror after high-power laser excitation. Based on the deviation between the calculated data of the analysis model and the measured data, thermodynamic parameters in the analysis model are adjusted according to the principle of minimum residual. The research findings of this manuscript can be utilized for accurately predicting the temperature rise and optical degradation of SiC mirrors under high-power laser irradiation and provide a theoretical basis for the subsequent design of actively compensating methods for thermal-induced distortions.

Asymmetric analogous hyperbola model of overburden movement and its verification

The extraction of underground coal resources induces the fracture and movement of overlying strata, leading to geological hazards such as surface deformation, cracks, and even subsidence. Utilizing the analogous hyperbola model of overlying strata movement, we conducted a mechanical analysis to examine the asymmetric fracture mechanism resulting from coal seam mining in thick loose strata. An asymmetric analogous hyperbola model was established by introducing distinct virtual half-axis lengths (b). The thickness impact of thick loose layers (H) and bedrock layer (h) on the asymmetric movement of overlying rock during mining was also discussed. Similarity model tests were conducted to research the migration characteristics and surface subsidence patterns of overburdened rock and thick loose layers at different mining stages and validate the hypothesis of asymmetric overburdened rock migration. Additionally, the discrete element numerical model for thick and loose layers mining was established by using UDEC and discussed the asymmetric analogous hyperbola behaviour of overburden movement and surface subsidence. The comparison results show that the established asymmetric hyperbolic model can effectively predict the movement law of overlying strata and surface subsidence characteristics. Therefore, the proposed model can provide valuable theoretical support for predicting the movement patterns of overburden under thick loose layers and mitigating surface subsidence disasters.

Visualization of Isometric Deformations of Helicoidal CMC Surfaces

Helicoidal surfaces of constant mean curvature were fully described by do Carmo and Dajczer. However, the obtained parameterizations are given in terms of somewhat complicated integrals, and as a consequence, not many examples of such surfaces are visualized. In this paper, by using these methods in some particular cases, we provide several interesting visualizations involving these surfaces, mostly as an isometric deformation of a rotational surface. We also give interpretations of some older results involving helicoidal surfaces, motivated by the work carried out by Malkowsky and Veličković. All of the graphics in this paper were created in Wolfram Mathematica.

DACLnet: A Dual-Attention-Mechanism CNN-LSTM Network for the Accurate Prediction of Nonlinear InSAR Deformation

Nonlinear deformation is a dynamically changing pattern of multiple surface deformations caused by groundwater overexploitation, underground coal mining, landslides, urban construction, etc., which are often accompanied by severe damage to surface structures or lead to major geological disasters; therefore, the high-precision monitoring and prediction of nonlinear surface deformation is significant. Traditional deep learning methods encounter challenges such as long-term dependencies or difficulty capturing complex spatiotemporal patterns when predicting nonlinear deformations. In this study, we developed a dual-attention-mechanism CNN-LSTM network model (DACLnet) to monitor and accurately predict nonlinear surface deformations precisely. Using advanced time series InSAR results as input, the DACLnet integrates the spatial feature extraction capability of a convolutional neural network (CNN), the advantages of the time series learning of a long short-term memory (LSTM) network, and the enhanced focusing effect of the dual-attention mechanism on crucial information, significantly improving the prediction accuracy of nonlinear surface deformations. The groundwater overexploitation area of the Turpan Basin, China, is selected to test the nonlinear deformation prediction effect of the proposed DACLnet. The results demonstrate that the DACLnet accurately captures developmental trends in historical surface deformations and effectively predicts surface deformations for the next two months in the study area. Compared to traditional LSTM and CNN-LSTM methods, the root mean square error (RMSE) of the DACLnet improved by 85.09% and 68.57%, respectively. These research results can provide crucial technical support for the early warning and prevention of geological disasters and can serve as an effective alternative tool for short-term ground subsidence prediction in areas lacking hydrogeological and other related data.

Original Insights Into Rock Slope Damage Processes Until Collapse From Passive Seismic Monitoring

AbstractWe performed a passive seismic monitoring of the La Praz ∼14,000 m3 unstable slope (French Alps) spanning over 10 years. During the last 6 months prior to collapse, we detected a clear 24% decrease in the slope's fundamental resonance frequency, f0, caused by a reduction in overall rock mass stiffness. The combined study of f0 and slope deformation suggested the alternating importance of sudden brittle failure processes versus more ductile phases with possible sliding. Seismic monitoring revealed slope damage that remained ambiguous or undetected with ground surface deformation monitoring, and highlighted critical periods with intense damage. Only some of these critical damage periods could be related to clear external forcing factors such as intense rainfall episodes. These new insights into rock slope's structural condition at depth represent an asset for future monitoring systems. Surface deformation and passive seismic stiffness tracking combined could reveal active slopes with ongoing damage processes.

Synthesis and antimicrobial activity testing of quaternary ammonium silane compounds

With increasing health awareness of the pathogenic effects of disease-causing microorganisms, interest in and use (of medical textiles, disinfectants in medical devices, etc.) of antimicrobial substances have increased in various applications, such as medical textiles and disinfectants (alcohol-based and nonalcoholic), in medical devices There are several concerns with alcohol-based disinfectants, such as surface deformation of medical devices due to high alcohol content and damage to skin tissue caused by lipid and protein denaturation of cell membranes. Quaternary ammonium compounds (quats) were preferred because they have the potential to prepare water-based disinfectants. In this study, novel (3-chloropropyl)triethoxysilane (CPTMO) and (3-chloropropyl)triethoxysilane (CPTEO) based quaternary ammonium silane compounds (silane-quats) were developed using quats with carbon chain lengths of C12, C14, C16 and C18. Titration (ASTM D2074) was used to calculate the yield of the synthesis and the structures of the products were characterised by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance spectroscopy (13C NMR, 1H NMR) and gas chromatography-mass spectrometry (GC–MS).The in vitro antimicrobial activity of the synthesized samples was evaluated against Gram-positive (Staphylococcus aureus (S. aureus), Enterococcus hirae (E. hirae)) and Gram-negative (Escherichia coli (E. coli), Pseudomonas aeruginosa (P. aeruginosa)) bacteria and fungi (Candida albicans (C. albicans), Aspergillus brasiliensis (A. brasiliensis)) using the minimum inhibitory concentration (MIC) test. According to MIC tests, the silane-quats with the highest antimicrobial effects were dimethylhexadecyl[3-(trimethoxysilyl)propyl]ammonium chloride (SQ3), which had an MIC of < 16 μg/ml (ppm) against E. coli, S. aureus, E. hirae, C. albicans, and A. brasiliensis and 32 μg/ml against P. aeruginosa. The MIC test results also showed antimicrobial activity at least 2 times greater than that of the commercially available disinfectant benzalkonium chloride (BAC). Findings suggest that SQ3 (C16) holds promise as an effective medical disinfectant, presenting a novel approach to combating microbial infections in healthcare settings.