Surface Deformation Research Articles

Slip Distribution Along the Chenghai Fault From Airborne LiDAR and Tectonic Implications for the 1515 Yongsheng Earthquake, China

AbstractThe tectonic deformation of the southeastern margin of the Tibetan Plateau underwent significant changes before and after the Miocene, which led to the change of the deformation characteristics of the Sichuan‐Yunnan block, and some local areas in the block also showed structural patterns inconsistent with the macroscopic clockwise rotation deformation. Moreover, the Chenghai fault (CF) in the Sichuan‐Yunnan block was the seismogenic fault of the M 73/4 Yongsheng earthquake in 1515. However, the dense vegetation impeded the acquisition of surface deformation characteristics and small‐scale horizontal offsets along the fault, resulting in its misty kinematic properties, roughly determined geometric distribution, and the highly controversial rupture parameters of the Yongsheng earthquake. Therefore, we used airborne light detection and ranging, which can penetrate vegetation to obtain high‐resolution surface topography, to map the CF within 120 km. Combined with satellite images and field investigations, we determined that the CF consists of a series of secondary faults with simple geometric structures. Continuous offset linear landforms were preserved along the fault. 102 offsets below 30 m were statistically analyzed and the result revealed that the CF has a characteristic displacement of ∼6 m and it may rupture as a united rupture segment in each large earthquake or its two rupture segments cascade rupture to generate large earthquakes. The magnitude of the Yongsheng earthquake in 1515 was estimated at 7.7. Finally, based on this study, the kinematic characteristics of the Dali terrane and Sichuan‐Yunnan block, where the CF is located are discussed.

Preparation and characterization of UV-curable coatings based on waterborne polyurethane acrylate/g-C3N4 co-crosslinked network for wood materials

Wood materials are often damaged due to exposure to environmental factors including humidity changes, temperature fluctuations, and ultraviolet radiation, resulting in surface aging, deformation, and cracking. Therefore, developing a new wood coating with good mechanical properties and weather resistance is conducive to improving the usability and service life of wood as an outdoor material. In this study, graphitic carbon nitride (g-C3N4) with a characteristic crystal structure was synthesized using melamine as raw material. By constructing a g-C3N4 /polyurethane acrylate co-crosslinked network, a UV-curable wood coating with excellent interfacial adhesion was prepared, which retained the natural aesthetic texture of the wood and imparted good wear resistance, anti-wetting property, and aging resistance to the wood material. Subsequently, the formation process and cross-linking reaction mechanism of the coating were revealed by XRD, FTIR and XPS measurements. Compared with untreated samples, coatings with a cross-linked network structure exhibited enhanced resistance to external environmental changes. As the content of the g-C3N4 increased (>1.0 %), the mechanical properties were significantly improved, with the mass loss rate and damaged area decreasing by 56.9 % and 60.0 %. Meanwhile, with the increased cross-link density of the coating, the water and heat resistance of the wood increased by 22.77 % and 260 %, respectively. After a seven-day UV aging resistance test, the ΔE values only changed by 10.28 %, showing good weathering resistance. This design and synthesis of wood coating provides an effective technology for the long-term use of outdoor wood material.

Aerial SfM–MVS Visualization of Surface Deformation along Folds during the 2024 Noto Peninsula Earthquake (Mw7.5)

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.

Effects of 3D Geocells on Flexible Pavement Foundations

Abstract: The current below study examines the effects of adding a Cubic Three-dimensional Geo-synthetics material known as Geo-cells to the foundation layer of flexible Bitumen pavements. In this study, the test of California bearing ratio (CBR) of 5% is used to compare the steel reinforced and unreinforced pavement made sections built on that subgrade. To comprehend the impact of Geo-cell reinforcement upon the pavement section's load-carryings mechanism under static and repetitive loading circumstances, a number of model tests were conducted. The following characteristics were examined: surface deformation profile the test sections, real rut subgrade level, load-settlement response of the pavement sections, and pressure is transmitted into the subgrade soil beneath into the Geo-cell reinforced foundation layer.

Synergistic use of SAR satellites with deep learning model interpolation for investigating of active landslides in Cuenca, Ecuador

Among the most intense geological disasters, landslides frequently occur throughout the world. These phenomena have been studied using space geodetic techniques, including Global Navigation Satellite Systems (GNSS) and Multi-Temporal Interferometric Synthetic Aperture Radars (MT-InSAR). Nevertheless, complete mapping and analysis of landslides’ surface deformation in most areas can be complicated due to a large diversity in kinematics, such as periods of quiescence and acceleration in the toe and crown. One of these landslides is the Cuenca landslides in Ecuador, where the geological investigation revealed that the toe of the landslides was located in urban areas, with more noticeable deformation effects. In contrast, its crown was located mainly in a rural and green land area. In this study, we show the potential of a synergistic use of COSMO-SkyMed (CSK) and Sentinel-1A (S1A) synthetic aperture radar (SAR) data for comprehensively monitoring the Cuenca landslides. To this aim, we have used Long-Short Term Memory (LSTM) and Convolutional Neural Networks (CNN) as two different Deep Learning Algorithms (DLAs) to integrate results in the temporal and spatial domain, respectively. A cross-comparison of the results was made with the nine GPS-derived deformations and the visual effects (i.e. crack width and pattern) on the field. This validation against GPS observation reveals that the RMSEs of the final MT-InSAR-derived velocity after applying the synergic double band SAR dataset decrease at more than 73% of nine GPS stations. Highlights Synergic MT-InSAR approach for studying landslide deformation in diverse kinematic areas. Utilized DLAs (LSTM and CNNs) for effective temporal and spatial interpolation of InSAR results. Findings emphasize the potential of multi-sensor SAR and DLAs for landslide monitoring regarding improving the RMSE at nine stations with an average of 73%.

Co-seismic landslides susceptibility evaluation of Bayesian random forest considering InSAR deformation: a case study of the Luding Ms6.8 earthquake

Strong earthquakes can frequently trigger a large number of co-seismic landslides. Obtaining an accurate susceptibility map of co-seismic landslides is crucial for post-disaster rescue and reconstruction efforts. In this study, the pre-seismic average annual surface deformation rate of the study area was obtained using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology. Furthermore, the landslide hazards prior to the earthquake in multiple locations within the study area were analyzed. Subsequently, the deformation data was combined with 11 evaluation factors, including the distance to the fault and the Peak Ground Acceleration (PGA), to model the susceptibility of landslides. We constructed four models to evaluate the susceptibility of landslides in the study area: the Bayesian optimization random forest (BO-RF) model, the random forest model (RF), the logistic regression model (LR), and the support vector machine model (SVM). The BO-RF model outperformed the other models, achieving an AUC value of 0.984, an accuracy of 0.952, a precision of 0.953, a recall of 0.952, and an F1 score of 0.953. Furthermore, incorporating pre-seismic deformation features in the evaluation of co-seismic landslide susceptibility can effectively improve the reliability of model predictions, as compared to the evaluation model results without incorporating deformation factors. The obtained research results provide valuable data support for the rescue and management of disaster-stricken areas.

Effect of liquid surface depression size on discharge characteristics and chemical distribution in the plasma-liquid anode system

Atmospheric pressure plasma-liquid interactions exist in a variety of applications, including wastewater treatment, wound sterilization, and disinfection. In practice, the phenomenon of liquid surface depression will inevitably appear. The applied gas will cause a depression on the liquid surface, which will undoubtedly affect the plasma generation and further affect the application performance. However, the effect of liquid surface deformation on the plasma is still unclear. In this work, numerical models are developed to reveal the mechanism of liquid surface depressions affecting plasma discharge characteristics and the consequential distribution of plasma species, and further study the influence of liquid surface depressions of different sizes generated by different helium flow rates on the plasma. Results show that the liquid surface deformation changes the initial spatial electric field, resulting in the rearrangement of electrons on the liquid surface. The charges deposited on the liquid surface further increase the degree of distortion of the electric field. Moreover, the electric field and electron distribution affected by the liquid surface depression significantly influence the generation and distribution of active species, which determines the practical effectiveness of the relevant applications. This work explores the phenomenon of liquid surface depression, which has been neglected in previous related work, and contributes to further understanding of plasma-liquid interactions, providing better theoretical guidance for related applications and technologies.

Rapid early afterslip characteristics of the 2010 moment magnitude (Mw) 8.8 Maule earthquake determined with sub-daily GPS solutions

Ground surface deformations can be observed during the coseismic and postseismic periods. The accurate determination of displacements is of paramount importance for the assessment of the destructive power of large earthquakes and the characterization of fault behaviors. Therefore, we employ the sub-daily Global Positioning System (GPS) solutions at 19 GPS stations to determine the coseismic and postseismic deformations of the 2010 moment magnitude (Mw) 8.8 Maule earthquake. Using sub-daily GPS data, we can accurately measure both coseismic and early postseismic deformation signals, which can precisely identify the distribution of coseismic slip and the spatiotemporal evolution of early afterslip within the first 36 h. In particular, the sub-daily solution can provide more accurate and quicker results, nearly 10% smaller than those with the daily solution. Furthermore, there is significant ground motion in the immediate postseismic period, which decreases rapidly thereafter. The largest postseismic deformation observed during the first 2 h occurred at station CONZ and amounted to 3.6 cm. During the immediate postseismic period of the 2010 Maule earthquake, afterslip is the dominant mechanism, while poroelasticity plays a negligible role within the first 36 h. Meanwhile, early aftershocks tend to occur in the boundary and the inner part of the afterslip, indicating that the afterslip has the potential to drive the occurrence of aftershocks in the initial stages of postseismic activity.

Sustained Co‐Eruptive Increase in Seismic Velocity Below Great Sitkin Volcano Due To Magma Extrusion

AbstractVolcanic eruptions carry essential information on the dynamics of volcanic systems. Studies have documented variable eruption styles and eruptive surface deformation. However, co‐eruptive subsurface structural changes remain poorly understood. Here we characterize the seismic velocity changes from July 2019 to July 2023 at Great Sitkin Volcano in the central Aleutian volcanic arc, using single‐station ambient noise interferometry at five three‐component seismic stations. Coincident with the lava effusion since late July 2021, about two months after the explosive eruption on 26 May 2021, we observe a sustained velocity increase, most prominently to the northwest of the caldera. We attribute this velocity increase to the structural changes with magma extrusion, with the spatial variation controlled by the geometry of the magma system or the property of shallow volcaniclastics. Our findings offer insights into understanding co‐eruptive structural modifications at active volcanoes.

Revealing the Ground Deformation and Its Mechanism in the Heihe River Basin by Interferometric Synthetic Aperture Radar and Optical Images.

The Heihe River Basin (HRB), located on the northeast margin of the Qilian Mountains, is China's second largest inland river basin. It is a typical oasis-type agricultural area in northwest China's arid and semiarid areas. It is important to monitor and investigate the spatiotemporal distribution characteristics and mechanisms of surface deformation in HRB for the ecology of inland river basins. In recent years, research on HRB has mainly focused on hydrology, meteorology, geology, or biology. Few studies have conducted wide-area monitoring and mechanism analysis of the surface stability of HRB. In this study, an improved interferometric point target analysis InSAR (IPTA-InSAR) technique is used to process 101 Sentinel-1 SAR images from two adjacent track frames covering the HRB from 2019 to 2020. The wide-area deformation of the HRB is obtained first for this period. The results show that most of the surface around the HRB is relatively stable. There are six areas with an extensive deformation range and magnitude in the plain oasis area. The maximum deformation rate is more than 50 mm/year. The maximum seasonal subsidence and uplift along the satellites' line-of-sight (LOS) direction can be up to -70 mm and 60 mm, respectively. Moreover, we use the Google Earth Engine platform to process the multisource optical images and analyze the deformation areas. The remote sensing indicators of the deformation areas, such as the normalized difference vegetation index (NDVI), soil moisture (SMMI), and precipitation, are obtained during the InSAR monitoring period. We combine these integrated remote sensing results with soil type and precipitation to analyze the surface deformations of the HRB. The spatiotemporal relationships between soil moisture, vegetation cover, and surface deformation of the HRB are revealed. The results will provide data support and reference for the healthy and sustainable development of the inland river basin economic zone.

Surface integrity improvement of the ground surface of Inconel 718 fabricated by forging and additive manufacturing using a robotic rotational burnishing method

Given that the surface acts as the primary interface with the surrounding environment, the surface integrity of a component significantly influences its operational effectiveness. In the aerospace industry, materials like Inconel 718 are often utilized for their high-temperature strength despite their poor thermal conductivity and machinability, resulting in inferior surface integrity during grinding procedures. This research proposes an innovative robotic rotational burnishing method that leverages self-generated heat to aid in the post-grinding burnishing process, eliminating the need for an external heat source. The surface integrity achieved through this method undergoes a comprehensive evaluation, encompassing surface topological features, microstructure, and mechanical properties, and is compared with surfaces treated by grinding and slide burnishing. The findings demonstrate that during the rotational burnishing process, the friction between the high-speed rotating burnishing tip and the workpiece surface induces circumferential flow of the surface material, thereby enhancing surface anisotropy. Additionally, this process generates significant heat, further encouraging plastic deformation of the material surface under high burnishing forces. As a result, the surface acquires a compressive residual stress exceeding 1000 MPa and develops a microhardness-strengthened layer with a thickness exceeding 500 μm. Both forging and additive manufacturing techniques for preparing Inconel 718 raw materials yield consistent outcomes. This study not only achieves a fusion of additive, subtractive, and equivalent manufacturing but also validates the applicability of the proposed robotic rotational burnishing method in enhancing surface integrity across materials manufactured by various techniques.

Research on the thermo-hydro-mechanical coupling simulation and deformation spatiotemporal evolution for the entire process of oil shale in-situ mining

The ground surface deformation (GSD) caused by oil shale in-situ mining poses a threat to land resources and human's lives and property. This study, for the first time, conducts a full stratum simulation of the Fuyu oil shale in-situ pyrolysis pilot base, analyzing the evolution characteristics of the temperature field, stress field, and deformation field of the entire stratum profile during the heating and cooling processes of convective heating mining. Considering the changes in the pore structure, thermophysical, and mechanical properties of the stratum, the environmental geological effects of rock deformation during in-situ mining were identified. Simulation results show that after heating, the temperature within 80 cm of the heating well reaches above the initial pyrolysis temperature of 350 °C for oil shale organic matter, and there is a significant stress concentration near the heat source. In the simulation, ground displacement rises in a wave-like manner during heating, quickly subsides after cooling, and finally stabilizes. Eventually, the entire stratum exhibited subsidence, with a subsidence amount of 0.59 cm. The spatiotemporal deformation trend obtained from SBAS-InSAR real-time monitoring results is similar to the simulation results. By comparing the monitoring results with the simulation results, the synergistic deformation mechanism of underground and ground surface co-deformation during in-situ mining of geochemical reactions in the study area was analyzed. The deformation rate is determined by the thermal hysteresis phenomenon and the temperature difference between the heated fluid and the rock layer. This provides scientific support for the geological effect evaluation of oil shale in-situ mining, which helps to improve mining safety and efficiency.

Landslide Hazard Prediction Based on Small Baseline Subset–Interferometric Synthetic-Aperture Radar Technology Combined with Land-Use Dynamic Change and Hydrological Conditions (Sichuan, China)

Le’an Town, located in the southwest of Qingchuan County, Guangyuan City, Sichuan Province, boasts a unique geographical position. The town’s terrain is complex, and its geological environment is fragile. Multiple phases of tectonic movements have resulted in numerous cracks and faults, making the area prone to landslides, debris flows, and other disasters. Additionally, heavy rainfall and fluctuating groundwater levels further exacerbate the instability of the mountains. Human activities, such as overdevelopment and deforestation, have significantly increased the risk of geological disasters. Currently, the methods for landslide prediction in Le’an Town are limited; traditional techniques cannot provide precise forecasts, and the study area is largely covered by tall vegetation. Therefore, this paper proposes a method that combines SBAS-InSAR technology with dynamic changes in land use and hydrological conditions. SBAS-InSAR technology is used to obtain surface deformation information, while land-use changes and hydrological condition data are incorporated to analyze the dynamic characteristics and potential influencing factors of landslide areas. The innovation of this method lies in its high-precision surface deformation monitoring capability and the integration of multi-source data, which can more comprehensively reveal the geological environmental characteristics of the study area, thereby achieving accurate predictions of landslide development. The study results indicate that the annual subsidence rate in most deformation areas of Le’an Town ranges from −10 to 0 mm, indicating slow subsidence. In some areas, the subsidence rate exceeds −50 mm per year, showing significant slope aspect differences, reflecting the combined effects of geological structures, climatic conditions, and human activities. It is evident that land-use changes and hydrological conditions have a significant impact on the occurrence and development of landslides. Therefore, by utilizing SBAS-InSAR technology and cross-verifying it with other techniques, the consistency of identified landslide deformation areas can be enhanced, thereby improving results. This method provides a scientific basis for the monitoring and early warning of landslide disasters and has important practical application value.

Study on Optimization Method for InSAR Baseline Considering Changes in Vegetation Coverage.

Time-series Interferometric Synthetic Aperture Radar (InSAR) technology, renowned for its high-precision, wide coverage, and all-weather capabilities, has become an essential tool for Earth observation. However, the quality of the interferometric baseline network significantly influences the monitoring accuracy of InSAR technology. Therefore, optimizing the interferometric baseline is crucial for enhancing InSAR's monitoring accuracy. Surface vegetation changes can disrupt the coherence between SAR images, introducing incoherent noise into interferograms and reducing InSAR's monitoring accuracy. To address this issue, we propose and validate an optimization method for the InSAR baseline that considers changes in vegetation coverage (OM-InSAR-BCCVC) in the Yuanmou dry-hot valley. Initially, based on the imaging times of SAR image pairs, we categorize all interferometric image pairs into those captured during months of high vegetation coverage and those from months of low vegetation coverage. We then remove the image pairs with coherence coefficients below the category average. Using the Small Baseline Subset InSAR (SBAS-InSAR) technique, we retrieve surface deformation information in the Yuanmou dry-hot valley. Landslide identification is subsequently verified using optical remote sensing images. The results show that significant seasonal changes in vegetation coverage in the Yuanmou dry-hot valley lead to noticeable seasonal variations in InSAR coherence, with the lowest coherence in July, August, and September, and the highest in January, February, and December. The average coherence threshold method is limited in this context, resulting in discontinuities in the interferometric baseline network. Compared with methods without baseline optimization, the interferometric map ratio improved by 17.5% overall after applying the OM-InSAR-BCCVC method, and the overall inversion error RMSE decreased by 0.5 rad. From January 2021 to May 2023, the radar line of sight (LOS) surface deformation rate in the Yuanmou dry-hot valley, obtained after atmospheric correction by GACOS, baseline optimization, and geometric distortion region masking, ranged from -73.87 mm/year to 127.35 mm/year. We identified fifteen landslides and potential landslide sites, primarily located in the northern part of the Yuanmou dry-hot valley, with maximum subsidence exceeding 100 mm at two notable points. The OM-InSAR-BCCVC method effectively reduces incoherent noise caused by vegetation coverage changes, thereby improving the monitoring accuracy of InSAR.

Prediction of Surface Subsidence in Mining Areas Based on Ascending-Descending Orbits Small Baseline Subset InSAR and Neural Network Optimization Models.

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.

Identification of force chains in wet coal dust layer and the effect of porosity on three-body contact stiffness

Aiming at the three-body contact problem of mechanical rough surface containing wet coal dust interface, the three-body contact model of rough surface containing wet coal dust interface is constructed by comprehensively considering the contact deformation of rough surface and contact characteristics of wet coal dust, and based on the crushing theory. By analysing the contact force, load-bearing particle size and adjacent contact angle thresholds of the wet coal dust layer, the force chain identification criterion is formulated. Finally, quantitative calculations of the force chain characteristics are performed to reveal the effect of different initial porosities on the three-body contact stiffness, which is verified experimentally. The results of the study show that the average contact force of the wet coal dust layer can be used as the force chain contact force threshold, the average particle size can be used as the force chain particle size threshold, and the force chain angle threshold is determined by the particle coordination number. As the initial porosity decreases, the number, length and stiffness of force chains in the wet coal dust layer increase significantly, and the stiffness reaches a maximum value of 2.007 × 108 pa/m at the moment of downward pressure to stabilisation, while the trend of force chain bending varies in the opposite direction, and its minimum bending degree decreases to 20°. The maximum relative error between the simulation and experimental results of three-body contact stiffness is 9.64%, which proves the accuracy of the force chain identification criterion and the quantitative calculation of three-body contact stiffness by force chain.

Investigation of Oil Well Blowouts Triggered by Wastewater Injection in the Permian Basin, USA

AbstractAged hydrocarbon wells, if proper care is not ensured, can crack, get corroded, and leak subsurface fluids. Permian Basin in Texas, home to thousands of such wells, has seen numerous blowouts and wastewater leaks. Our study employs surface deformation derived from satellite observations, and injection well records to investigate these events. The results reveal an over‐pressurized wastewater aquifer producing a surface uplift of 20 cm/yr, likely due to wastewater being injected tens of kilometers away. Focusing on a January 2022 blowout resulting in 3 cm subsidence in 2 weeks, our geophysical model suggests aquifer over‐pressurization as the cause. With an excess pressure of over 3 MPa in the aquifer, several more such blowouts are possible in the near future. This research highlights the urgent need to better understand the impact of subsurface fluid injection and calls for prompt action to mitigate the environmental effects of oil and gas production.

Numerical analysis of hydrogen storage in lined rock cavern under high pressure and its implications to hydrogen embrittlement

Underground hydrogen storage could provide buffer capacity to store the excess energy from renewable resources. A lined rock cavern (LRC) is one of the hydrogen geologic storage site options. It offers great flexibility because it does not rely on the existence of salt caverns, aquifer formations or depleted hydrocarbon reservoir fields. However, many important aspects have to be investigated before its full-scale implementation, among them (1) the effect of spatial variation of rock mass properties and (2) hydrogen embrittlement on the steel lining. We present a numerical study on these two aspects by simulating field tests at a pilot LRC project. For the effect of rock heterogeneity, we assign a spatial variation of elastic properties based on the Gaussian covariance model. The results show a good agreement with the field measurements. The spatial correlation length of rock mass elastic properties only has a minor impact on the cavern surface deformation. Regarding hydrogen embrittlement, our simulations predict a significant hydrogen diffusion in the low alloy steel (S355) lining after ∼2 months of operation. The fracture simulations show little fracture propagation even after 10 years of contact with hydrogen gas. However, the product loss may be too high for the low alloy steel (S355). We would recommend the use of stainless steel to inhibit the hydrogen diffusion. We show that advanced numerical models are powerful tools to ensure the safety of hydrogen storage in LRCs.

Error Correction of the RapidEye Sub-Pixel Correlation: A Case Study of the 2019 Ridgecrest Earthquake Sequence.

The optical image sub-pixel correlation (SPC) technique is an important method for monitoring large-scale surface deformation. RapidEye images, distinguished by their short revisit period and high spatial resolution, are crucial data sources for monitoring surface deformation. However, few studies have comprehensively analyzed the error sources and correction methods of the deformation field obtained from RapidEye images. We used RapidEye images without surface deformation to analyze potential errors in the offset fields. We found that the errors in RapidEye offset fields primarily consist of decorrelation noise, orbit error, and attitude jitter distortions. To mitigate decorrelation noise, the careful selection of offset pairs coupled with spatial filtering is essential. Orbit error can be effectively mitigated by the polynomial fitting method. To address attitude jitter distortions, we introduced a linear fitting approach that incorporated the coherence of attitude jitter. To demonstrate the performance of the proposed methods, we utilized RapidEye images to extract the coseismic displacement field of the 2019 Ridgecrest earthquake sequence. The two-dimensional (2D) offset field contained deformation signals extracted from two earthquakes, with a maximum offset of 2.8 m in the E-W direction and 2.4 m in the N-S direction. A comparison with GNSS observations indicates that, after error correction, the mean relative precision of the offset field improved by 92% in the E-W direction and by 89% in the N-S direction. This robust enhancement underscores the effectiveness of the proposed error correction methods for RapidEye data. This study sheds light on large-scale surface deformation monitoring using RapidEye images.

Dynamic deformation and fracture surface investigation of rolled homogenous armor steel through Charpy impact testing

The amount of energy that can be absorbed by armor steel during dynamic loadings, such as a crash, impact, or blast, is crucial. To characterize the behaviour of material deformation under such loading, rigorous testing and a suitable material model are needed. Within the scope of this research, relevant tensile tests in the dynamic range are carried out to obtain the parameters necessary for three different material models, namely, the Johnson-Cook (J-C), Rusinek and Klepaczko (R-K), and a newly proposed modified Johnson-Cook (MJ-C) model. Tensile tests are simulated using these three material models, and the results are compared with the experimental results. The Charpy impact test at five different striking velocities, viz. 3, 4, 5, 6, and 8 ms−1 are numerically simulated using these material models. Upon comparing the obtained results with the experimental data, it becomes evident that the J-C model with modification (MJ-C) exhibits the best fit in prediction with regard to the specimen energy absorption and force versus displacement. A fractography investigation is also carried out to estimate the number of voids and void size with striking velocities. It shows that at higher strain rates, the number of voids increases. Additionally, the plastic deformation is restricted at high strain rates, leading to higher stress and reduced ductility.