Search Results (7,645)

Hydraulic actions may compromise dam foundation stability. Helical anchors have been used in dam foundation reinforcement projects because of the advantages of large uplift and compression bearing capacity, fast installation, and convenient recovery. However, the research on the anchor plate, which plays a key role in the bearing performance of helical anchors, is insufficient at present. Based on the finite element model of helical anchor, this study reveals the failure mode and influencing factors of the anchor plate and establishes the theoretical model of deformation calculation. The results showed that the helical anchor plate had obvious bending deformation when the dam foundation reinforced with a helical anchor reached large deformation. The helical anchor plate can be simplified to a flat circular disk. The stress distribution of the closed flat disk and the open flat disk was consistent with that of the helical disk. The maximum deformation of the closed flat disk was slightly smaller than that of the helical disk (less than 6%), and the deformation of the open flat disk was consistent with that of the helical disk. The results fill the blank of the design basis of helical anchor plate and provide a reference basis for the engineering design. Full article

This study synthesizes and comparatively investigates two squaric acid-based phthalocyanine-like dyes, SNF and its long-chain alkylated derivative LNF, to systematically elucidate the influence of peripheral hydrophobic groups on their third-order nonlinear optical (NLO) properties. The NLO characteristics were comprehensively characterized using femtosecond Z-scan and I-scan techniques at both 800 nm and 900 nm. Both dyes exhibited strong saturable absorption (SA), confirming their potential as saturable absorbers. Critically, the comparative analysis revealed that SNF exhibits a significantly greater nonlinear absorption coefficient (β) compared to LNF under identical conditions. For instance, at 800 nm, the β of SNF was approximately 3–5 times larger than that of LNF. This result conclusively demonstrates that the introduction of long hydrophobic alkyl chains attenuates the NLO response. Furthermore, I-scan measurements revealed excellent SA performance, with high modulation depths (e.g., LNF: 43.0% at 900 nm) and low saturation intensities. This work not only clarifies the structure–property relationship in these D-A-D dyes but also presents a clear strategy for modulating the NLO properties of organic chromophores for applications in near-infrared pulsed lasers. Full article

The integration of large-scale wind power clusters significantly reduces the inertia level of the power system, increasing the risk of frequency instability. Accurately assessing the equivalent virtual inertia of wind farms is critical for grid stability. Addressing the dual bottlenecks in existing inertia assessment methods, where physics-based modeling requires full control transparency and data-driven approaches lack interpretability for inertia response analysis, thus failing to reconcile commercial confidentiality constraints with analytical needs, this paper proposes a symbolic regression framework for inertia evaluation in doubly fed wind farms with limited control information constraints. First, a dynamic model for the inertia response of DFIG wind farms is established, and a mathematical expression for the equivalent virtual inertia time constant under different control strategies is derived. Based on this, a nonlinear function library reflecting frequency-active power dynamic is constructed, and a symbolic regression model representing the system’s inertia response characteristics is established by correlating operational data. Then, sparse relaxation optimization is applied to identify unknown parameters, allowing for the quantification of the wind farm’s equivalent virtual inertia. Finally, the effectiveness of the proposed method is validated in an IEEE three-machine nine-bus system containing a doubly fed wind power cluster. Case studies show that the proposed method can fully utilize prior model knowledge and operational data to accurately assess the system’s inertia level with low computational complexity. Full article

Iridium, with its excellent high-temperature chemical inertness, is a preferred cladding material for radioisotope batteries. However, its inherent room-temperature brittleness severely restricts its application. In this research, pure Ir and six Ir-W solid solutions (Ir₃₁W₁ to Ir₂₆W₆) were modeled. The effects of W on the elastic properties, generalized stacking fault energy, and bonding properties of Ir solid solution alloys were investigated by first-principles simulation, aiming to find a way to overcome the intrinsic brittleness of Ir. With the W concentration increasing from 0 to 18.75 at %, the calculated Cauchy pressure (C₁₂–C₄₄) increases from −22 to 5 GPa, Pugh’s ratio (B/G) increases from 1.60 to 1.72, the intrinsic stacking fault energy reduces from 337.80 to 21.16 mJ/m², and the unstable stacking fault energy reduces from 636.90 to 547.39 mJ/m². According to these results, it is predicted that the addition of W improves the toughness of iridium alloys. The alloying of W weakens the covalency properties of the Ir-Ir bond (the ICOHP value increases from −0.8512 to −0.7923 eV). These phenomena result in a decrease in the energy barrier for grain slip. Full article

Timely and accurate monitoring of crop nitrogen (N) status is essential for precision agriculture. UAV-based hyperspectral remote sensing offers high-resolution data for estimating plant nitrogen concentration (PNC), but its cost and complexity limit large-scale application. This study compares the performance of UAV hyperspectral data (S185 sensor) with simulated multispectral data from DJI Phantom 4 Multispectral (P4M), PlanetScope (PS), and Sentinel-2A (S2) in estimating winter wheat PNC. Spectral data were collected across six growth stages over two seasons and resampled to match the spectral characteristics of the three multispectral sensors. Three variable selection strategies (one-dimensional (1D) spectral reflectance, optimized two-dimensional (2D), and three-dimensional (3D) spectral indices) were combined with Random Forest Regression (RFR), Support Vector Machine Regression (SVMR), and Partial Least Squares Regression (PLSR) to build PNC prediction models. Results showed that, while hyperspectral data yielded slightly higher accuracy, optimized multispectral indices, particularly from PS and S2, achieved comparable performance. Among models, SVM and RFR showed consistent effectiveness across strategies. These findings highlight the potential of low-cost multispectral platforms for practical crop N monitoring. Future work should validate these models using real satellite imagery and explore multi-source data fusion with advanced learning algorithms. Full article

High-strength steel has high strength and low thermal conductivity, and its thin-walled parts are very susceptible to residual stress and deformation caused by cutting heat during the drilling process, which affects the machining accuracy and quality. High-strength steel thin-walled components are widely used in aerospace and other high-end sectors; however, systematic investigations into their temperature fields during drilling remain scarce, particularly regarding the evolution characteristics of the temperature field in thin-wall drilling and the quantitative relationship between drilling parameters and these temperature variations. This paper takes the thin-walled parts of AF1410 high-strength steel as the research object, designs a special fixture, and applies infrared thermography to measure the bottom surface temperature in the thin-walled drilling process in real time; this is carried out in order to study the characteristics of the temperature field during the thin-walled drilling process of high-strength steel, as well as the influence of the drilling dosage on the temperature field of the bottom surface. The experimental findings are as follows: in the process of thin-wall drilling of high-strength steel, the temperature field of the bottom surface of the workpiece shows an obvious temperature gradient distribution; before the formation of the drill cap, the highest temperature of the bottom surface of the workpiece is distributed in the central circular area corresponding to the extrusion of the transverse edge during the drilling process, and the highest temperature of the bottom surface can be approximated as the temperature of the extrusion friction zone between the top edge of the drill and the workpiece when the top edge of the drill bit drills to a position close to the bottom surface of the workpiece and increases with the increase in the drilling speed and the feed volume; during the process of drilling, the highest temperature of the bottom surface of the workpiece is approximated as the temperature of the top edge of the drill bit and the workpiece. The maximum temperature of the bottom surface of the workpiece in the drilling process increases nearly linearly with the drilling of the drill, and the slope of the maximum temperature increases nearly linearly with the increase in the drilling speed and feed, in which the influence of the feed on the slope of the maximum temperature increases is larger than that of the drilling speed. Full article

The highly stochastic nature of rainfall presents significant challenges for the accurate prediction of its time series. To enhance the prediction performance of non-stationary rainfall time series, this study proposes a hybrid deep learning forecasting framework—VMD-IWMA-BiLSTM—that integrates Variational Mode Decomposition (VMD), Improved Whale Migration Algorithm (IWMA), and Bidirectional Long Short-Term Memory network (BiLSTM). Firstly, VMD is employed to decompose the original rainfall series into multiple modes, extracting Intrinsic Mode Functions (IMFs) with more stable frequency characteristics. Secondly, IWMA is utilized to globally optimize multiple hyperparameters of the BiLSTM model, enhancing its ability to capture complex nonlinear relationships and long-term dependencies. Finally, experimental validation is conducted using daily rainfall data from 2020 to 2024 at the Xinzheng National Meteorological Observatory. The results demonstrate that the proposed framework outperforms traditional models such as LSTM, ARIMA, SVM, and LSSVM in terms of prediction accuracy. This research provides new insights and effective technical pathways for improving rainfall time series prediction accuracy and addressing the challenges posed by high randomness. Full article

Soil respiration (Rt), consisting of heterotrophic (Rh) and autotrophic respiration (Ra), plays a vital role in terrestrial carbon cycling and is sensitive to soil temperature and moisture. In dryland agriculture, plastic film mulching (PM) is widely used to regulate soil hydrothermal conditions, but its effects on Rt components and their temperature sensitivity (Q₁₀) across regions remain unclear. A two-year field study was conducted at two rain-fed maize sites: Anding (warmer, semi-arid) and Yuzhong (colder, drier). PM significantly increased Rt, Rh, and Ra, especially Ra, due to enhanced root biomass and improved microclimate. Yield increased by 33.6–165%. Peak respiration occurred earlier in Anding, aligned with maize growth and soil temperature. PM reduced Q₁₀ of Rt and Ra in Anding, but only Ra in Yuzhong. Rh Q₁₀ remained stable, indicating microbial respiration was less sensitive to temperature changes. Structural equation modeling revealed that Rt and Ra were mainly driven by soil temperature and root biomass, while Rh was more influenced by microbial biomass carbon (MBC) and dissolved organic carbon (DOC). Despite increased CO₂ emissions, PM improved carbon emission efficiency (CEE), particularly in Yuzhong (+67%). The application of PM is recommended to enhance yield while optimizing carbon efficiency in dryland farming systems. Full article

Understanding alpine plants’ survival and reproduction is crucial for their conservation in climate change. Based on 423 valid distribution points, this study utilizes the MaxEnt model to predict the potential habitat and distribution dynamics of Leontopodium nanum under both current and future climate scenarios, while clarifying the key factors that influence its distribution. The primary ecological drivers of distribution are altitude (2886.08 m–5576.14 m) and the mean temperature of the driest quarter (−6.60–1.55 °C). Currently, the suitable habitat area is approximately 520.28 × 10⁴ km², covering about 3.5% of the global land area, concentrated mainly in the Tibetan Plateau, with smaller regions across East and South Asia. Under future climate scenarios, low-emission (SSP126), suitable areas are projected to expand during the 2050s and 2070s. High-emission (SSP585), suitable areas may decrease by 50%, with a 66.07% reduction in highly suitable areas by the 2070s. The greatest losses are expected in the south-eastern Tibetan Plateau. Regarding dynamic habitat changes, by the 2050s, newly suitable areas will account for 51.09% of the current habitat, while 68.26% of existing habitat will become unsuitable. By the 2070s, newly suitable areas will rise to 71.86% of the current total, but the loss of existing areas will exceed these gains, particularly under the high-emission scenario. The centroid of suitable habitats is expected to shift northward, with migration distances ranging from 23.94 km to 342.42 km. The most significant shift is anticipated under the SSP126 scenario by the 2070s. This study offers valuable insights into the distribution dynamics of L. nanum and other alpine species under the context of climate change. From a conservation perspective, it is recommended to prioritize the protection and restoration of vegetation in key habitat patches or potential migration corridors, restrict overgrazing and infrastructure development, and maintain genetic diversity and dispersal capacity through assisted migration and population genetic monitoring when necessary. These measures aim to provide a robust scientific foundation for the comprehensive conservation and sustainable management of the grassland ecosystem on the Qinghai–Tibet Plateau. Full article

Accelerated industrialization and surging energy demands have led to continuously rising atmospheric CO₂ concentrations. Developing sustainable methods to reduce atmospheric CO₂ levels is crucial for achieving carbon neutrality. Concurrently, the rapid development of new energy vehicles has driven a significant increase in demand for lithium-ion batteries (LIBs), which are now approaching an end-of-life peak. Efficient recycling of valuable metals from spent LIBs represents a critical challenge. This study employs conventional hydrometallurgical processing to recover valuable metals from spent LIBs. Subsequently, Ni-doped Co₃O₄ (Ni:Co₃O₄) supported on the natural mineral attapulgite (ATP) was synthesized via a sol–gel method. The incorporation of a small amount of Ni into the Co₃O₄ lattice generates oxygen vacancies, inducing a localized surface plasmon resonance (LSPR) effect, which significantly enhances charge carrier transport and separation efficiency. During the photocatalytic reduction of CO₂, the primary product CO generated by the Ni:Co₃O₄/ATP composite achieved a high production rate of 30.1 μmol·g⁻¹·h⁻¹. Furthermore, the composite maintains robust catalytic activity even after five consecutive reaction cycles. Full article

A method for configuration synthesis of a reconfigurable decoupled parallel mechanical leg is proposed. In addition, a configuration evaluation index is proposed to evaluate the synthesized configurations and select the optimal one. Kinematic analysis and performance optimization of the selected mechanism’s configuration are carried out, and the motion mode of the robot’s reconfigurable mechanical leg is selected according to the task requirements. Then, the robot’s gait in walking mode is planned. Firstly, based on bionic principles, the motion characteristics of a mechanical leg based on a mammalian model and an insect model were analyzed. The input and output characteristics of the mechanism were analyzed to obtain the reconfiguration principle of the mechanism. Using type synthesis theory for the decoupled parallel mechanism, the configuration synthesis of the chain was carried out, and the constraint mode of the mechanical leg was determined according to the constraint property of the chain and the motion characteristics of the moving platform. Secondly, an evaluation index for the complexity of the reconfigurable mechanical leg structure was developed, and the synthesized mechanism was further analyzed and evaluated to select the mechanical leg’s configuration. Thirdly, the inverse position equations were established for the mechanical leg in the two motion modes, and its Jacobian matrix was derived. The degrees of freedom of the mechanism are completely decoupled in the two motion modes. Then, the workspace and motion/force transmission performance of the mechanical leg in the two motion modes were analyzed. Based on the weighted standard deviation of the motion/force transmission performance, the global performance fluctuation index of the mechanical leg motion/force transmission is defined, and the structural size parameters of the mechanical leg are optimized with the performance index as the optimization objective function. Finally, with the reconfigurable mechanical leg in the insect mode, the robot’s gait in the walking operation mode is planned according to the static stability criterion. Full article

Hydrogen energy holds immense potential to address the global energy crisis and environmental challenges. However, its large-scale application is severely hindered by the lack of efficient hydrogen storage materials. This study systematically investigates the H₂ adsorption properties of intrinsic C₂₆ fullerene and Li-decorated C₂₆ fullerene using density functional theory (DFT) calculations. The results reveal that Li atoms preferentially bind to the H_5-5 site of C₂₆, driven by significant electron transfer (0.90 |e|) from Li to C₂₆. This electron redistribution modulates the electronic structure of C₂₆, as evidenced by projected density of states (PDOS) analysis, where the p orbitals of C atoms near the Fermi level undergo hybridization with Li orbitals, enhancing the electrostatic environment for H₂ adsorption. For Li-decorated C₂₆, the average adsorption energy and consecutive adsorption energy decrease as more H₂ molecules are adsorbed, indicating a gradual weakening of adsorption strength and signifying a saturation limit of three H₂ molecules. Charge density difference and PDOS analyses further demonstrate that H₂ adsorption induces synergistic electron transfer from both Li (0.89 |e| loss) and H₂ (0.01 |e| loss) to C₂₆ (0.90 |e| gain), with orbital hybridization between H s orbitals, C p orbitals, and Li orbitals stabilizing the adsorbed system. This study aimed to provide a comprehensive understanding of the microscopic mechanism underlying Li-enhanced H₂ adsorption on C₂₆ fullerene and offer insights into the rational design of metal-decorated fullerene-based systems for efficient hydrogen storage. Full article

The accurate identification of seismic faults, which serve as crucial fluid migration pathways in hydrocarbon reservoirs, is of paramount importance for reservoir characterization. Traditional interpretation is inefficient. It also struggles with complex geometries, failing to meet the current exploration demands. Deep learning boosts fault identification significantly but struggles with edge accuracy and noise robustness. To overcome these limitations, this research introduces SwiftSeis-AWNet, a novel lightweight and high-precision network. The network is based on an optimized MedNeXt architecture for better fault edge detection. To address the noise from simple feature fusion, a Semantics and Detail Infusion (SDI) module is integrated. Since the Hadamard product in SDI can cause information loss, we engineer an Attention-Weighted Semantics and Detail Infusion (AWSDI) module that uses dynamic multi-scale feature fusion to preserve details. Validation on field seismic datasets from the Netherlands F3 and New Zealand Kerry blocks shows that SwiftSeis-AWNet mitigates challenges like the loss of small-scale fault features and misidentification of fault intersection zones, enhancing the accuracy and geological reliability of automated fault identification. Full article

In a greenhouse experiment, we examined the behavior of biochar in arable soil to demonstrate that these supplements can boost soil carbon storage, as well as to track changes in microbial biomass and identify the microbial communities that use these biochars. In order to ascertain if biochar can consistently alter soil microbial activities, we studied the impact of biochar combination treatments on 16S rRNA gene diversity. In soil treated with biochar, there was a rise in the relative abundance of taxa belonging to the phyla Actinobacteria and Gemmatimonadetes, despite the overall diversity decreasing with biochar addition. According to all of these observations, pyrogenic carbon has a major effect on the composition of the soil microbial community and enriches keystone taxa within the parent soil microbial community. Certain species experienced increases throughout the biochar-amended incubation period, despite the total diversity declining following biochar amendments. The phyla Actinobacteria and Gemmatimonadetes increased in the relative abundance of bacteria in soil treated with biochar, according to DNA sequencing of these species. In summary, these findings show that biochar significantly impacts the constitution and composition of the soil microbial community and enriches important taxa within the parent soil microbial community. Full article

In this study, we analyzed the lithospheric seismic background of the Tianshan and adjacent areas by combining various geophysical methods (effective elastic thickness, time-varying gravity, apparent density, and InSAR), and explored the genesis mechanism of the Wushi Ms7.1 earthquake as an example, which led to the following conclusions: (1) The effective elastic thickness (Te) of the Tianshan lithosphere is low (13–28 km) and weak, while the Tarim and Junggar basins have Te > 30 km with high intensity, and the loads are all mainly from the surface (F < 0.5). Earthquakes occur mostly in areas with low values of Te. (2) Medium and strong earthquakes are prone to occur in regions with alternating positive and negative changes in the gravity field during the stage of large-scale reverse adjustment. It is expected that the risk of a moderate-to-strong earthquake occurring again in the vicinity of the survey area between 2025 and 2026 is relatively high. (3) Before the Wushi earthquake, the positive and negative boundaries of the apparent density of the crust at 12 km shifted to be approximately parallel to the seismic fault, and the earthquake was triggered after undergoing a “solidification” process. (4) The Wushi earthquake is a leptokurtic strike-slip backwash type of earthquake; coseismic deformation shows that subsidence occurs in the high-visual-density zone, and vice versa for uplift. The results of this study reveal the lithosphere-conceiving environment of the Tianshan and adjacent areas and provide a basis for regional earthquake monitoring, early warning, and post-disaster disposal. Full article