Search Results (72)

With the strict requirements of national policies on truck dimensions, axle loads, and weight limits, along with the implementation of tolls based on vehicle types, rapid and accurate identification of vehicle axle types has become essential for toll station management. To address the limitations of existing methods in distinguishing between drive and driven axles, complex equipment setup, and image evidence retention, this article proposes a panoramic image detection technology for vehicle chassis based on enhanced ORB and YOLOv11. A portable vehicle chassis image acquisition system, based on area array cameras, was developed for rapid on-site deployment within 20 min, eliminating the requirement for embedded installation. The FeatureBooster (FB) module was employed to optimize the ORB algorithm’s feature matching, and combined with keyframe technology to achieve high-quality panoramic image stitching. After fine-tuning the FB model on a domain-specific area scan dataset, the number of feature matches increased to 151 ± 18, substantially outperforming both the pre-trained FB model and the baseline ORB. Experimental results on axle type recognition using the YOLOv11 algorithm combined with ORB and FB features demonstrated that the integrated approach achieved superior performance. On the overall test set, the model attained an mAP@50 of 0.989 and an mAP@50:95 of 0.780, along with a precision (P) of 0.98 and a recall (R) of 0.99. In nighttime scenarios, it maintained an mAP@50 of 0.977 and an mAP@50:95 of 0.743, with precision and recall both consistently at 0.98 and 0.99, respectively. The field verification shows that the real-time and accuracy of the system can provide technical support for the axle type recognition of toll stations. Full article

The increasing frequency and magnitude of flood-related disasters has led to adopting advanced flood models to provide a better understanding of flood vulnerability, particularly for human lives. Human flood vulnerability assessment is a primary objective when planning and designing in urban areas. Results of a numerical model in the coastal hamlet of Solanas (Sardinia, IT), in terms of water velocity and depth, have been processed using the empirical method of the regional legislation (RAS), as suggested by the National Network for Environmental Protection. Vulnerability maps and statistical parameters were compared and benchmarked with the DEFRA method, which is largely used in the UK and is regarded as a state-of-the-art empirical approach. The main findings from the benchmark results between the DEFRA and RAS methods suggest that the applicability threshold of the RAS method can significantly underestimate the pedestrian vulnerability to urban flood in Solanas, and this paper suggests a preliminary step in improving that method could be a tentative threshold value of 0.10 m depth to assure a more realistic evaluation of human vulnerability in Solanas. Full article

Hydraulic turbine governor servomotors in wind solar hydro complementary energy systems face significant fatigue failure challenges due to high-frequency regulation. This study develops an intelligent fatigue monitoring and prediction system based on strain sensors, specifically designed for the frequent regulation requirements of complementary systems. A multi-point monitoring network was constructed using resistive strain sensors, integrated with temperature and vibration sensors for multimodal data fusion. Field validation was conducted at an 18.56 MW hydroelectric unit, covering guide vane opening ranges from 13% to 63%, with system response time <1 ms and a signal-to-noise ratio of 65 dB. A simulation model combining sensor measurements with finite element simulation was established through fine-mesh modeling to identify critical fatigue locations. The finite element analysis results show excellent agreement with experimental measurements (error < 8%), validating the simulation model approach. The fork head was identified as the critical component with a stress concentration factor of 3.4, maximum stress of 51.7 MPa, and predicted fatigue life of 1.2 × 10⁶ cycles (12–16 years). The cylindrical pin shows a maximum shear stress of 36.1 MPa, with fatigue life of 3.8 × 10⁶ cycles (16–20 years). Monte Carlo reliability analysis indicates a system reliability of 51.2% over 20 years. This work provides an effective technical solution for the predictive maintenance and digital operation of wind solar hydro complementary systems. Full article

During the installation and operation of Pelton turbines, deviations of the jet centerline from the runner pitch circle can compromise turbine stability and efficiency. Utilizing design data from a Pelton turbine on China’s Dadu River, this study employs the SST k-ω and VOF models to investigate the flow characteristics, pressure pulsations, and force on the bucket surface under varying offset conditions. The results demonstrate that radial offset causes the jet to enter the bucket later when deflected outward and earlier when deflected inward. All forms of offset exert adverse effects on turbine performance, with axial offsets causing more severe impacts than radial ones. The maximum pressure pulsation amplitude reached 24%. Afterwards, the erosion of Pelton turbines with different grain sizes was investigated by erosion modeling. It was found that the erosion of large grain size is more serious than that of small grain size. This research provides valuable theoretical insights and an important guiding role for improving the operational stability of Pelton turbines. Full article

Coseismic landslides are geological events in which slopes, either on the verge of instability or already in a fragile state, experience premature failure due to seismic shaking. On 5 September 2022, an Ms 6.8 earthquake struck Luding County, Sichuan Province, China, triggering numerous landslides that caused severe casualties and property damage. This study systematically interprets 13,717 coseismic landslides in the Luding earthquake’s epicentral area, analyzing their spatial distribution concerning various factors, including elevation, slope gradient, slope aspect, plan curvature, profile curvature, surface cutting degree, topographic relief, elevation coefficient variation, lithology, distance to faults, epicentral distance, peak ground acceleration (PGA), distance to rivers, fractional vegetation cover (FVC), and distance to roads. The analytic hierarchy process (AHP) was improved by incorporating frequency ratio (FR) to address the subjectivity inherent in expert scoring for factor weighting. The improved AHP, combined with the Pearson correlation analysis, was used to identify the dominant controlling factor and assess the landslide susceptibility. The accuracy of the model was verified using the area under the receiver operating characteristic (ROC) curve (AUC). The results reveal that 34% of the study area falls into very-high- and high-susceptibility zones, primarily along the Moxi segment of the Xianshuihe fault and both sides of the Dadu river valley. Tianwan, Caoke, Detuo, and Moxi are at particularly high risk of coseismic landslides. The elevation coefficient variation, slope aspect, and slope gradient are identified as the dominant controlling factors for landslide development. The reliability of the proposed model was evaluated by calculating the AUC, yielding a value of 0.8445, demonstrating high reliability. This study advances coseismic landslide susceptibility assessment and provides scientific support for post-earthquake reconstruction in Luding. Beyond academic insight, the findings offer practical guidance for delineating priority zones for risk mitigation, planning targeted engineering interventions, and establishing early warning and monitoring strategies to reduce the potential impacts of future seismic events. Full article

Water Resource Carrying Capacity (WRCC) serves as a critical indicator for assessing the supportive capacity of water resource systems. This study selects 28 districts and counties within the Dadu River Basin as case studies, constructs a WRCC evaluation framework based on the four-dimensional collaborative perspective of “water resources–society–economy–ecology,” proposes a combined weighting method integrating the CRITIC and entropy weight approaches to optimize index weight calculation, and applies the obstacle degree model to investigate the spatio-temporal heterogeneity of regional WRCC and its underlying driving mechanisms. The results show the following: (1) From 2011 to 2020, the WRCC in the Dadu River Basin increased by 17% as a whole. All districts and counties showed an upward trend. (2) The spatial differentiation of WRCC is significant. The downstream regions are approaching the fourth-level threshold, driven by the adoption of water-saving technologies and the agglomeration effects of economic activities. In contrast, the upstream regions face inherent constraints arising from the conflict between ecological conservation and resource exploitation, leading to a relatively slower growth rate. (3) The driving mechanism of WRCC shows the transformation characteristics of “shifting from being dominated by the social economy to the synergy of the economy and ecology”. Based on this analysis, a strategy of “zonal regulation–structural optimization–management upgrade” is proposed. Full article

Under the pressures of global climate change, the sustainable management of plant resources in alpine gorge regions faces severe challenges. P. aquilinum var. latiusculum is widely harvested and utilized by residents in the upper reaches of the Dadu River–Min River basin due to its high edible and medicinal value. This study employed ensemble models to simulate the potential distribution of P. aquilinum var. latiusculum in this region, predicting the impacts of future climate change on its distribution, the centroid migration of suitable habitats, and niche dynamics. A production dynamics model was also constructed to identify current and future potential cultivation areas by integrating ecological suitability and nutritional component synergies. The results show that current high-suitability areas and core cultivation zones of P. aquilinum var. latiusculum are predominantly distributed in patchy, fragmented patterns across the Wenchuan, Li, Mao, Luding, and Xiaojin Counties and Kangding City. Under climate change, the “mountain-top trap effect” drives a significant increase in high-suitability areas and core cultivation zones, while moderate-to-low-suitability areas and marginal cultivation zones decrease substantially. Meanwhile, suitable habitats and cultivation areas exhibit a northward migration trend toward higher latitudes. The most significant changes in suitable area and cultivation zone extent, as well as the most pronounced niche shifts, occur under high-emission climate scenarios. This research facilitates the development of suitability-based management strategies for P. aquilinum var. latiusculum in the study region and provides scientific references for the sustainable utilization of montane plant resources in the face of climate change. Full article

This study presents the first detailed analysis of a Late Pleistocene cliff-front dune in northern Mallorca (Western Mediterranean). The research is based on sedimentological fieldwork conducted in a disused coastal quarry, where stratigraphic columns were recorded and facies were described in detail. Grain size analysis was performed using image-based measurements from representative samples, and palaeowind conditions were reconstructed through the analysis of cross-bedding orientations and empirical wind transport equations. The dune, corresponding to Unit U4, exhibits three distinct evolutionary stages: initial, intermediate, and final. During the initial stage, sediment mobilisation required wind speeds of approximately 10 m/s from the south-southwest (SSW). The intermediate stage was characterised by variable wind velocities between 5 and 8 m/s from the west-southwest (WSW). In the final stage, average wind speeds reached 7 m/s from the west (W), with intermittent peaks up to 10 m/s. These findings underscore the critical influence of wind regime and topographic constraints on aeolian sedimentation processes. By reconstructing wind dynamics and analysing sedimentary architecture, this work provides key insights into the interplay between climatic drivers and geological context in the development of coastal aeolian systems. Full article

Under global climate change, sustainable management of plant resources in alpine canyon regions faces severe challenges. M. esculenta, highly valued for its edible and medicinal properties, is widely harvested for consumption by residents in the upper Dadu River–Minjiang River region. This study employs ensemble models to simulate the potential distribution of M. esculenta in this region, predicting the impacts of future climate change on its distribution, centroid migration of suitable habitats, and niche dynamics. Additionally, a production dynamics model integrating ecological suitability and nutritional components was developed to delineate current and future potential cultivation zones for M. esculenta. The results indicate that current high-suitability areas and core cultivation zones of M. esculenta are predominantly distributed in a patchy and fragmented pattern. The high-suitability habitats in the upper Dadu River–Minjiang River region have three distribution centers: the largest spans southern Danba County, southern Jinchuan County, and northeastern Kangding City, while the other two are located in northeastern Li County, southwestern Aba County, and northwestern Ma’erkang City, with sporadic distributions in Heishui County, Maoxian County, and Wenchuan County. First-level cultivation areas are primarily concentrated in Kangding City, Danba County, Ma’erkang City, Li County, and surrounding regions. Under climate change, low-suitability areas and third-level cultivation zones for M. esculenta in the region have increased significantly, while high- and medium-suitability areas, along with first- and second-level cultivation zones, have decreased notably. Concurrently, suitable habitats and cultivation zones exhibit a migration trend toward higher northern latitudes. The most pronounced changes in suitable areas and cultivation zones, as well as the largest niche migration, occur under the high-emission climate scenario. This study facilitates the formulation of suitability-based management strategies for M. esculenta in the upper Dadu River–Minjiang River region and provides a scientific reference for the sustainable utilization of mountain plant resources under climate change. Full article

Argentina anserina (Rosaceae), a perennial herb, forms enlarged tuberous roots (commonly referred to as “ginseng fruit”) exclusively in the Qinghai–Tibet Plateau, making it a unique medicinal and edible plant resource in this region. The upper reaches of the Dadu River and Minjiang River are one of its primary production areas in China. This study employs an ensemble model to simulate the potential distribution of A. anserina in this region, predicting the impacts of future climate change on its distribution, ecological niche, and centroid migration patterns. Additionally, a cultivation productivity evaluation model integrating ecological suitability and nutritional components was developed to delineate potential cultivation areas. Results indicate that high-suitability habitats span 0.37 × 10⁴ km² (7.39% of the total suitable area), exhibiting a patchy and fragmented distribution in Aba County, Rangtang County, Jiuzhi County, and Banma County. Core cultivation areas cover 3.78 × 10⁴ km², distributed across Aba County, Rangtang County, Jiuzhi County, Seda County, Banma County, Hongyuan County, and Markam City. Under future climate scenarios, the suitable distribution area of A. anserina will gradually decline with rising temperatures, migrating to higher-latitude northern regions, accompanied by increased niche migration. By the 2090s under the SSP5-8.5 scenario, the centroid demonstrates the largest migration amplitude, with high-suitability habitats showing a “collapsing” polarization pattern and near-complete niche separation from the previous period, indicating significant changes. Collectively, these results provide a theoretical basis for the sustainable utilization of A. anserina in the upper Dadu River and Minjiang River basin. Full article

Southwestern China has abundant hydropower networks, wherein neighboring cascade hydropower stations within the same river basin are typically connected to the power system in a chain-structured configuration. However, when such chain-structured cascade hydroelectric power plants (CC-HPPs) participate in automatic voltage control (AVC), problems such as reactive power interactions among stations and unreasonable voltage gradients frequently arise. To address these issues, this study proposes an optimized multi-station coordinated response control strategy based on sensitivity analysis and hierarchical AVC. Firstly, based on the topology of the chain-structured hydropower sending-end network, a reactive power–voltage sensitivity matrix is constructed. Subsequently, a regional-voltage-coordinated regulation model is developed using sensitivity analysis, followed by the establishment of a mathematical model, solution algorithm, and operational procedure for multi-station AVC-coordinated response optimization. Finally, case studies based on the actual operational data of a CC-HPP network validate the effectiveness of the proposed strategy, and simulation results demonstrate that the approach reduces the interstation reactive power pulling up to 97.76% and improves the voltage gradient rationality by 16.67%. These results substantially improve grid stability and operational efficiency while establishing a more adaptable voltage control framework for large-scale hydropower integration. Furthermore, they provide a practical foundation for future advancements in multi-scenario hydropower regulation, enhanced coordination strategies, and predictive control capabilities within clean energy systems. Full article

Landslides on reservoir slopes are one of the key geologic hazards that threaten the safe operation of hydropower plants. The aim of our study was to reduce the limitations of the existing methods of landslide risk assessment when dealing with complex nonlinear relationships and the difficulty of quantifying the uncertainty of predictions. We established a multidimensional system of landslide risk assessment that covers geological settings, meteorological conditions, and the ecological environment, and we proposed a model of landslide risk assessment that integrates Bayesian theory and a random forest algorithm. In addition, the model quantifies uncertainty through probability distributions and provides confidence intervals for the prediction results, thus significantly improving the usefulness and reliability of the assessment. In this study, we adopted the Gini index and SHAP (SHapley Additive exPlanations) value, an analytical methodology, to reveal the key factors affecting slope stability and their interaction. The empirical results obtained show that the model effectively identifies the key risk factors and also provides an accurate prediction of landslide risk, thus enhancing scientific and targeted decision making. This study offers strong support for managing landslide risk and providing a more solid guarantee of the safe operation of hydropower station sites. Full article

Civil, transportation, and hydraulic projects often result in concrete or rocky slope surfaces that have difficultly sustaining vegetation due to the lack of suitable substrate. A geosynthetic-based vegetation substrate was proposed to replace traditional soil-based vegetation substrates for vegetation restoration on steep concrete or rock surfaces. The geosynthetic vegetation substrate (GVS) provides the following four key functions for vegetation restoration: 1. Germination environment for seeds. 2. Room for root development and vegetation fixation. 3. Allowing water and nutrients to be transported and stored within the substrate. 4. Sufficient strength to support vegetation on steep or vertical surfaces. An 8-month field study revealed the following: vegetation leaf length peaked at over 400 mm by the 100th day, with annual fresh biomass reaching 2.99 kg/m² (94% from stems/leaves). The geosynthetics maintained 91.6% to 99.5% of initial tensile strength and 82.9% to 98.2% creep resistance. These findings establish GVS as a viable solution for ecological restoration on engineered slopes. Full article

With the development of a power system predominantly reliant on new energy sources, turbine generator sets are increasingly required to operate under wide load conditions, resulting in numerous unstable flow phenomena and substantial economic losses for power stations. This study employs the Shear Stress Transport (SST) k-ω turbulence model to combine numerical simulations with experimental methods. It calculates the guide vane opening at the rated head of a Francis turbine and examines the internal flow field characteristics and pressure pulsations under various operating conditions. The findings indicate that the entropy production ratio in the draft tube is the highest among all load conditions, ranging from about 72.7% to 95.9%. Energy dissipation in the vaneless zone and the runner increases with greater opening. At 45% and 100% load conditions, the draft tube is mainly influenced by dynamic and static interference, single and double frequencies induced by runner rotation, and low-frequency fluctuations of the vortex and. Under 60% load conditions, pressure fluctuations in the draft tube are primarily caused by the eccentric vortex band, characterized by higher intensity and a frequency of 0.2 f_n. Numerical results closely align with experimental observations. The findings provide essential guidance for ensuring the stable operation of power plant units. Full article

Precipitation is a key component of the water cycle. Different precipitation data sources have strengths and weaknesses. To combine these strengths and achieve accurate precipitation data, this study introduces a dual-layer neural network (D-ConvLSTM) based on a convolutional long short-term memory neural network (ConvLSTM) that integrates ground station data (1 h interval) and grid precipitation data generated by the China Meteorological Administration Multi-source merged Precipitation Analysis System (CMPAS, 1 h interval, 0.05° × 0.05°) through a two-layer network for precipitation identification and correction. To evaluate the performance of the proposed model, D-ConvLSTM, optimal interpolation (OI), and a single-layer ConvLSTM model are evaluated in the Dadu River Basin, China. The results show that D-ConvLSTM outperforms the CMPAS in all the metrics compared with the OI and ConvLSTM, with improvements of 18.9% and 19.8% in the critical success index (CSI) and Kling–Gupta efficiency (KGE), respectively. D-ConvLSTM enhances gridded precipitation under various conditions, including areas without station data, different intensities, and regions. Furthermore, this study analyzes the impact of training data distribution on the performance of the D-ConvLSTM model and enhances model performance by adjusting the training data distribution. The analysis reveals that the ratio of dry to wet data in the training set affects the model’s identification performance. The ratio of overestimation to underestimation of gridded data compared with station observations influences value correction. This study offers a new model for merging station and gridded precipitation data and provides insights for enhancing the accuracy of neural network merging. Full article