The fracture network of hydraulic crack is significantly influenced by the bedding plane in coalbed methane extraction. Under mode II loading, crack deflection holds a key position in hydraulic cracking, especially in hydraulic shearing. This study first analyzed the crack deflection theory of layered rock. The semi-circle bending test under asymmetric loading is performed, and the four-dimensional Lattice Spring Model (4D-LSM) is established to examine how the bedding parameters affect coal crack propagation under mode II dominant loads. The 4D-LSM results are comparable to the coal loading test results under quasi-mode II and the analytical prediction of crack deflection theory. During mode II loading, the coal crack propagation is greatly influenced by the angle, strength, and elastic modulus of the bedding plane, while the effects of thickness and spacing of bedding are insignificant. The crack of coal tends to propagate towards the bedding, following a decrease in bedding angle, a decrease in bedding strength, and an increase in elastic modulus. With higher bedding strength, spacing, and thickness, the peak load on the coal sample is higher. The influences of bedding strength, elastic modulus, spacing, and thickness on the peak load of coal samples and its anisotropy gradually decrease. It is proved that compared with the tangential stress ratio and traditional energy release ratio theories, the corrected energy release ratio criterion can more accurately predict the direction of crack deflection of coal, especially under mode II loading. The results can provide assistance in the design of initiation pressure and fracturing direction in coal seam hydraulic fracturing. (c) 2025 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).

The issue of bridge end bumps is a critical concern in the failure of bridge and bridge approaches. A series of novel centrifuge tests utilizing a ring model box were conducted to investigate settlement and its induced damages at the bridge approach. A new mitigation method, the deep-seated slab, for bridge end bumps was modeled in the test. This study analyzed the decisive role of pavement stiffness, soil modulus, and load cycles on deformation from the perspective of structure-soil interaction under standard traffic load conditions. The test results show that when deep-seated slabs are used, the deformation of the bridge approach follows an exponential decay pattern, eventually stabilizing after approximately one slab length. Furthermore, the upper and lower bridges exhibit distinct damage modes, i.e., the bridge damage by wheel collision at the upper bridge and the pavement damage by wheel impact at the lower bridge. The damage zone on the pavement is approximately 1.7 times the wheel width and the damage zone on the bridge 2.6 times. Finally, a predictive model for the deformation of bridge approaches was proposed, considering the effect of pavement stiffness, subgrade soil modulus, and load cycles. The relationship between the deformation and the three normalized variables conforms to the quadratic polynomial function.

Objective In coal mining regions, extensive coal dust is generated during mining, transportation, and storage, coupled with substantial black carbon produced resulting from incomplete coal combustion in the industry chain. Over time, these materials form absorbable substances, evolving into core- shell aerosols with inorganic salt shells. These aerosols, including sulfate, nitrate, and water, exert significant climate impacts through direct and indirect radiation effects. The environmental and radiative forcing effects are substantial. Absorbing aerosol demonstrates strong solar radiation absorption across the ultraviolet to infrared spectrum. However, past studies primarily focus on their optical properties in visible and infrared bands, overlooking ultraviolet band absorption. Current research often assumes a lognormal particle size distribution for absorbing aerosols, neglecting variations in distribution and optical properties resulting from diverse emission scenarios. Therefore, a thorough analysis of absorbing aerosol optical properties at local scales is crucial. Quantitative assessments of particle size distribution, mixing state, and spatio-temporal variations are vital for elucidating the intricate interactions with boundary layer development, radiative forcing changes, and air pollution. Methods In our study conducted in the coal mining area of Changzhi City, Shanxi Province, various datasets are collected, including surface black carbon concentration, particle size distribution, and columnar aerosol optical depth (AOD). The investigation commenced with the utilization of the variance maximization method to categorize AOD data into distinct pollution events. Subsequent analysis involved evaluating the particle size distribution corresponding to different pollution degrees through probability density functions. The uncertainty of particle size for the desorption aerosol core and shell is then determined by integrating black carbon mass concentration data and particle size distribution information. These uncertainties are then used as input parameters to run the Mie scattering model based on the core- shell structure. This process results in the inversion of the multi- band optical characteristic parameters of absorbing aerosol in the coal mining area. The computations are carried out under both the assumption of a uniform distribution and a non- uniform distribution, representing different mixing degrees of aerosols. To complete the picture, the uncertainty interval for the single scattering albedo (SSA) of absorbing aerosol was constrained through the application of absorption & Aring;ngstr & ouml;m exponent (AAE) theory. This comprehensive approach provides a nuanced understanding of the complex dynamics of absorbing aerosol in the specific context of coal mining environments. Results and Discussions In the coal mining area, absorbing aerosols are influenced by emission sources, manifesting a particle size distribution divergent from the lognormal model. Under various pollution conditions, robust peaks are discernible in smaller particle size ranges (0.28 -0.3 mu m), with weaker peaks present around 0.58 -0.65 mu m. The relative proportion between the two peaks fluctuates in tandem with the pollution severity (Fig. 3). Using the Mie scattering model, the optical characteristics of absorbing aerosol are inverted based on AOD information, black carbon mass concentration, and particle number concentration. Results indicate that under the assumption of a uniform distribution (Fig. 4), the average size of the core particles at 0.28, 0.58, and 0.7 mu m is relatively low, leading to corresponding patterns in SSA with changes in core particle size. Additionally, the average core particle size shows no significant variation with changes in wavelength in different size ranges. SSA decreases with increasing wavelength, with greater fluctuations in the smaller particle size range (0.25-0.58 mu m) and more stable changes in the larger particle size range (0.58-1.6 mu m). Under this assumption, the AAE theory is found to be inapplicable. In the case of a non- uniform distribution (Fig. 5), SSA values exhibit a slow, followed by a gradual and then rapid increase in the shortwave region, while in the longwave region, SSA first rapidly increases and then gradually levels off. For shorter wavelengths (500 nm and above), AAE theory proves effective for absorbing aerosol with smaller particle sizes. For longer wavelengths (675 nm and above), AAE theory is applicable to absorbing aerosol with moderate particle sizes. However, for larger particles such as coal dust, AAE theory is not suitable. It is noteworthy that, under both assumptions, the inversion results of SSA values in the longwave spectrum (such as 870 and 936 nm) are relatively lower compared to the shortwave spectrum (such as 440 and 500 nm). This discrepancy will lead to an underestimation of emission quantities. Conclusions We conduct on- site observations in the coal mining area of Changzhi City, Shanxi Province, aiming to capture the variation characteristics of AOD, particle concentration, and black carbon mass concentration. Utilizing the Mie scattering model based on the core- shell hypothesis, we simulate the SSA of absorbing aerosol under two different mixing states. Additionally, we calculate the optical variations of absorbing aerosol constrained by the AAE. The research findings reveal the following: 1) The particle size distribution of absorbing aerosol in the coal mining area deviates from the assumptions made in previous studies, which typically assumed single or double- peaked distributions. Influenced by emission sources, the characteristics vary under different pollution conditions. Smaller particles predominantly originate from the incomplete combustion of coal in local power plants and coking factories, producing black carbon. Larger particles stem from the aging processes of black carbon in the atmospheric environment and coal dust generated during coal transportation. 2) Comparison of the SSA variations under different mixing states simulated by the two hypotheses indicates that particle size, mixing state, and spectral range significantly impact the SSA of absorbing. In contrast to previous studies using the infrared spectrum, the present investigation reveals higher SSA values in the ultraviolet and visible light spectrum, suggesting a potential underestimation of black carbon emissions. 3) The AAE theory is applicable only to certain particle size ranges in different spectral bands. For large- sized absorbing aerosol in the coal mining area, using the AAE theory to estimate SSA introduces uncertainty, and applying the AAE assumption across all particle size ranges leads to an underestimation of emissions. These findings underscore that the distribution characteristics of SSA in absorbing aerosol do not strictly adhere to the power- law relationship of the AAE index but are collectively determined by particle size distribution, mixing state, and spectral range.

The global increase in building collapses and damage on soft-soil sites due to distant significant earthquakes poses similar challenges for sand-blowing reclamation (SBR) sites on soft-soil layers. This study was initiated to capture the vibration characteristics of the SBR sites and to provide fresh insights into their seismic responses. Initially, considering the heterogeneity and layered structure of soil at SBR sites, we developed a novel stratified shearing model box. This model box enables the simulation of the complex characteristics of soil layers at SBR sites under laboratory conditions, representing a significant innovation in this field. Subsequently, an innovative jack loading system was developed to apply active vertical pressure on the soil layer model, accelerating soil consolidation. Furthermore, a new data collection and analysis system was devised to monitor and record acceleration, pore water pressure, and displacement in real time during the experiments. To verify the model box's accuracy and innovation, and to examine the seismic response of SBR sites under varying consolidation pressures, four vibration tests were conducted across different pressure gradients to analyze the model's predominant period evolution due to consolidation pressures. The experimental results demonstrate that the model box accurately simulates the propagation of one-dimensional shear waves in soil layers under various consolidation pressures, with notable repeatability and reliability. Our experiments demonstrated that increasing consolidation pressure results in higher shear wave speeds in both sand and soft-soil layers, and shifts the site's predominant period towards shorter durations. Concurrently, we established the relationship between the site's predominant period and the input waves. This study opens new paths for further research into the dynamic response properties of SBR sites under diverse conditions through shaking-table tests.

Piles are inevitably installed on sloping coastlines or inclined seabeds to support offshore wind turbines, offshore bridges, and other structures. The objective of this paper is to develop an analytical method for investigating the lateral response of short piles near clay slopes. The soil-pile interaction is modelled by a two-spring model which is used to describe the soil resistance around the pile and the horizontal shear force at the pile base. Considering the combined effect of slope angle and near-slope distance, the ultimate soil resistance along the pile is divided into three cases based on the nearby soil flow mechanism. The soil-pile-slope surface deformation mechanism is established according to the rotational deformation characteristics of short piles. In contrast to the modification of the initial stiffness, the p-y curve around the pile is constructed by considering the deformation mechanism. The accuracy of the analytical method is verified by comparing its results with two piles on level ground and five piles near slopes. Considering the soil-pile-slope deformation mechanism, the secant stiffness of the p-y curve is automatically adjusted and reduced without the need for additional numerical simulations or pile tests to determine the reduction factor of the initial stiffness.

This paper presents an improved longitudinal beam-spring model on the Vlasov foundation for estimating the longitudinal deformation of the shield tunnel when subjected to the ground surface surcharge. This model incorporates an improved subgrade modulus and treats each segmental ring as a Timoshenko short beam, with each circumferential joint modeled by two mechanical springs. It can accurately reflect the discontinuous deformation, and capture the dislocation and opening deformation of shield tunnels. Two-stage analysis methodology is adopted to consider soil and tunnel interaction. The feasibility of this model is verified by comparing it with two well-documented field monitoring cases. The computed results are also compared with those based on other analytical models. The results show that the Timoshenko continuous beam overestimates the dislocation deformation, while underestimates the opening deformation. In addition, the settlement curve exhibits neither smooth nor differentiable features. Finally, this paper also conducted some parameter analysis to examine the impact on tunnel deformation, encompassing dimensions of ground surface surcharge, the dual-area loading, and the joint reinforcement. This approach provides valuable insights into how the deformation characteristics of shield tunnels are influenced by ground surface surcharge.

Polarimetric target decomposition algorithms have played an important role in extracting the scattering characteristics of buildings, crops, and other fields. However, there is limited research on the scattering characteristics of grasslands and a lack of volume scattering models established for grasslands. To improve the accuracy of the polarimetric target decomposition algorithm applicable to grassland environments, this paper proposes an adaptive polarimetric target decomposition algorithm (APD) based on the anisotropy degree (A). The adaptive volume scattering model is used in APD to model volume scattering in forest and grassland regions separately by adjusting the value of A. When A > 1, the particle shape becomes a disk, and the grassland canopy is approximated as a cloud layer composed of randomly oriented disk particles; when A < 1, the particle shape is a needle, simulating the scattering mechanism of forests. APD is applied to an L-band AirSAR dataset from San Francisco, a C-band AirSAR dataset from Hunshandak grassland in Inner Mongolia Autonomous Region, and an X-band COSMO-SkyMed dataset from Xiwuqi grassland in Inner Mongolia Autonomous Region to verify the effectiveness of this method. Comparison studies are carried out to test the performance of APD over several target decomposition algorithms. The experimental results show that APD outperforms the algorithms tested in terms of this study in decomposition accuracy for grasslands and forests on different bands of data.

Precisely estimating the lateral capacity of the large-diameter monopile is essential for securing the stability of the fixed wind turbine of high power generation. Conventional standards relying on p-y curves often underestimate the monopile-soil interaction due to their failure to account for pile shaft rotations and base effects, leading to overly cautious lateral capacity designs. This paper introduces the three-spring soil reaction model that comprehensively considers lateral soil resistance, shaft frictional resistance, base shear force, and base moment. The analytical expressions for three springs are established considering the self-similarity between soil stress-strain relationships and load-displacement responses. The bearing capacity calculation method of monopiles with varying rigidity is developed based on the combinations of three springs. The results reveal that the modified p-y curve for lateral capacity predictions achieves over 80% accuracy. The contributions of base effects and shaft frictional resistance to bearing capacity gradually increase with the increases in pile rigidity, and the correction of monopile ultimate lateral displacement prediction is also enhanced.