To investigate the mechanism of interaction between root-soil composites and rock interfaces in the ecological protection of rocky slopes, physical models of interfaces were established, considering different plant species, types of soil for slope protection, and degrees of rock weathering. Under natural stress conditions, direct shear tests on the root-soil-rock interfaces were conducted. The variation patterns of shear strength and shear displacement at the interfaces were revealed, and the influence mechanisms of plant root morphology, types of protective soil, and rock weathering degree on the shear strength of the interfaces were analyzed. The results indicate that plant roots, penetrating through the slope protection soil and into the bedrock fissures, significantly enhance the shear strength of the soil in the shear zone and the anti-slip capacity of the soil-rock interface, thereby improving the overall cohesion between the slope protection soil and the rock. The shear strength of the interface is positively correlated with the vertical extension of plant roots and the degree of rock weathering. Compared to scenarios without plants, the planting of vetiver grass increased the peak shear strength by 53.9%, and under highly weathered bedrock conditions, the peak strength increased by 22.4%. Compared to ordinary soil, substrate soil containing binders and aggregating agents significantly improved the shear performance of the soil, increasing the peak shear strength of the interface by 20.1%.

Considering the oscillation phenomenon of the original DWA(dynamic window approach) in path planning, an improved DWA path planning algorithm was designed, which is integrated with the artificial potential field method. Firstly, the safety constraint of the DWA algorithm is improved, and the linear obstacle distance evaluation function in the original DWA was improved to the nonlinear obstacle potential field function in the artificial potential field method. Secondly, the improved DWA was combined with the smooth A^* path of the gradient descent method to solve the problem of poor global planning of the traditional algorithm. Finally, the feasibility of the algorithm was verified by simulation experiments and physical experiments. In the simulation experiments, compared with the original algorithm, the improved algorithm in this paper reduces the path of the designed obstacle scene by 9.84%, reduces the running time by 31.71%, and improves the smoothness by 6.49%. Meanwhile, compared with the results of related literatures, the results of this paper have been improved to different degrees in different scenarios. In the physical experiments of automated guided vehicle, the path length is reduced by 10.76% and the elapsed time is reduced by 13.09%. Therefore, the improved DWA generates better path smoothness, shorter path length and shorter elapsed time.

In order to study the prediction and health management of PEMFCs(proton exchange membrane fuel cells) for vehicles, a method combining GWO(grey wolf optimizer) and RBF(radial basis function) neural network with relative power loss rate as a health indicator was proposed to predict the remaining useful life of vehicular PEMFCs. Firstly, by analyzing the polarization curve of the fuel cell at the initial moment, a calculation method based on the relative power loss rate as a health indicator was constructed, and its feasibility was verified using the grey correlation analysis method. Then, the RBF neural network optimized by GWO algorithm was applied to predict the remaining useful life of vehicular PEMFCs. Finally, the proposed method was validated using two datasets. The results show that compared with other methods, the GWO-RBF method proposed in this paper has the smallest average absolute percentage error and root mean square error, the largest coefficient of determination, and a relative error of less than 1%. It is concluded that the proposed method can be used to predict the remaining useful life of vehicular PEMFCs with fewer datasets and better accuracy.

Addressing challenges such as large memory footprint, high computational complexity, and insufficient real-time detection speed in road crack detection models for complex scenarios, a highly efficient and precise algorithm named FCG-YOLO was proposed. Lightweight modules and attention mechanisms were integrated, and traditional feature fusion pyramids were enhanced.The algorithm incorporates PConv into the residual calculation module of YOLOv8n to introduce the improved C2f_Faster structure, thereby reducing model parameters and computational complexity. To enhance detection accuracy, GAM(global attention mechanism) was introduced into the backbone, and the Feature Fusion Pyramid SPPF was improved to SPPFCSPC module, enhancing the model’s ability to represent and fuse features of road cracks.The impact of each module on algorithm performance was verified through ablation experiments, identifying a lightweight and accurate model configuration. Furthermore, the robustness and generalization of the algorithm were explored in practical application scenarios.FCG-YOLO demonstrates outstanding detection efficiency, achieving a detection accuracy of 90.3% mAP50 and 74.4% mAP50-95 on the validation set, with a detection speed of 345 frames per second. These results highlight its high detection efficiency and significant practical value.

The performance of supercritical multi-thermal fluid injection in heavy oil reservoirs is markedly superior to that of steam flooding. However, the underground seepage law of injecting supercritical multi-thermal fluid is not yet clear. Therefore, the “high-temperature and high-pressure steady-state method” was proposed to test the oil-water and oil-gas relative permeability curves at different temperatures. The viscosity of produced heavy oil and the contact angle between oil sand and water at different temperatures were tested, and finally, combined with the oil-water, oil-gas relative permeability and Stone-Ⅱ prediction model, the isoperms of oil phase relative permeability in different hot areas during three-phase seepage were obtained. The results show that after the action of supercritical water on heavy oil, the measured viscosity of produced heavy oil decreased by 31.03% at 50 ℃ compared to steam, and the contact angle between oil sand and water decreased from 139.5° to 100.9°, indicating that the wetting properties of the oil sand develop towards a water-wet direction. Compared with the relative permeability of oil phase, the relative permeability of water phase is very small, and the characteristic value of oil-water relative permeability curve changes gradually and then suddenly at supercritical temperature. The relative permeability of oil-gas increases gradually with the increase of temperature. In the isoperms of oil phase relative permeability, the area of the oil flow zone expanded as temperatures rose, and under supercritical conditions, the flow zone area grew to 54.59%, highlighting a significant enhancement in oil-phase flow capacity. The research results of this paper can provide theoretical basis for the seepage mechanism and numerical simulation of supercritical multi-thermal fluid injected in heavy oil reservoirs.

It is essential to perform equipment reliability classification in order to devote limited resources to NPP equipment management reasonably, improve equipment reliability and availability while reducing maintenance workload and cost, and enable NPP’s safe, reliable, and economical operation. In light of engineering characteristics of the demonstration fast reactor and the challenges during the construction, an attainable new method was developed to standardize the process of equipment reliability classification and complete the classification of all systems. The differences and characteristics among the methods were compared, the implementation process of the new method was proposed and demonstrated with two real systems. The application shows that the proposed method is efficient, effective and rational, hence can offer to assist other NPPs of similar reactors to implement reliability classification during NPP construction.

In recent years, important progress has been made in the lithologic trap exploration of the Lower Cretaceous Yageliemu Formation in the Yakela fault convex and its surrounding areas in the Tarim Basin, in order to clarify the sedimentary facies distribution law of the clastic rock reservoir of Yageliemu Formation in this area, and promote the efficient exploration and development of the clastic rock reservoir. Based on an integrated analysis of core samples, well logging data, and 3D seismic surveys, the sedimentary facies types and spatial distribution patterns of the Cretaceous Yageliemu Formation in the Yakela fault convex and its surrounding areas in the Tarim Basin were investigated. Furthermore, under the framework of source-to-sink system theory, the controlling effects of source area characteristics on fan delta development were systematically examined. The results show that fan delta group deposits are developed in the Yageliemu Formation in the Yakela fault convex and its surrounding areas. During the deposition period of the Yageliemu Formation, the ancient uplift in the Yakela fault convex area was obviously segmented, with a banded uplift in the NEE direction, with two bulges in the east and west, and a low terrain in the middle. Based on the analysis of source-sink system, it is clear that the sediment source of the fan delta group is from the weathered denudation area of the ancient uplift, and the multi-branch ancient gullies provide sediment transport channels for the fan delta Group. It can be seen that paleogeomorphology and gully development characteristics control the sour-sink system of Yageliemu formation in the Yakela fault convex and its surrounding areas, forming a sedimentary pattern with multiple sources supply. The western ancient uplift is mainly characterized by high uplift and large gully area,the eastern section is mainly characterized by low uplift and small gully area. The development scale of gullies in provenance area controlled the distribution scale of deltaic sediments around ancient uplift. The gentle slope fan delta sedimentary system developed in the south of the ancient uplift, and the steep slope and gentle slope fan delta sedimentary system developed in the north. The analysis of source-sink system reduces the uncertainty of sedimentary facies study of Yageliemu Formation and can provide more geological basis for oil and gas exploration.

To solve the problem of high memory and computational resource demands in obstacle detection models within autonomous driving perception domain controllers, a lightweight obstacle detection method based on improved YOLOv8 was proposed. This method reconstructs the YOLOv8 backbone network using FasterNet, which utilizes less memory access and computational resources. To mitigate the accuracy decline and the insufficient detection capabilities for small objects caused by model lightweighting, three main improvements were made to YOLOv8: SPD-Conv (space-to-depth convolution) was used to replace traditional stride convolution in the neck network to enhance small object feature extraction. IPIoU(inner powerful IoU), combining the concepts of IIoU(inner IoU) and PIoU(powerful IoU), is introduced as the bounding box regression loss to accelerate loss convergence and improve small object detection performance. SimAM (simple attention module) was incorporated to further enhance model detection accuracy. Experimental results demonstrate that, compared to the original model, the improved model achieves a reduction of 29.1% in parameters, 20.5% in computational load, and 28.8% in model size, while increasing mAP@0.5 by 1.2%. Once deployed in autonomous driving vehicle controllers, the model effectively detects obstacles on the road ahead.

In order to address a series of safety management issues involved in low-altitude economic development, the technical routes and principles of low-altitude economy as well as the operational experience of implementation plans are summarized, and four universal construction plans for low-altitude security and protection are analyzed, namely the radar and integrated perception technology fusion plan, the broadcast automatic dependent surveillance technology plan, the remote identification technology plan, and the multi-source fusion plan based on TDOA radio technology. On this basis, an evaluation index system for unmanned aerial vehicle detection technology was constructed, and a multi-attribute evaluation method based on DEMATEL and TOPSIS was established. The results show that the multi-source fusion plan based on time difference of arrival (TDOA) is an effective and universal solution for building a low-altitude security system in cities. It is concluded that the construction of a low-altitude security system is a systematic project, which requires the joint efforts of governments, enterprises and the whole society. Integration is needed at the levels of technology, data and operation to meet the future development needs of the low-altitude economy.

To accurately and comprehensively explore the entire process of physical fatigue development in rescue team members during weighted walking, a multidimensional fatigue assessment method based on eye movement characteristics, electromyographic signals, and subjective evaluation is proposed. Eight volunteers were recruited for the weight-bearing walking fatigue induction experiment. The glasses eye tracking was used to extract the eye movement data about ST (saccade time), average SS (saccade speed) and maximum SA (saccade amplitude). The correlation between the characteristics of eye movement and the degree of fatigue estimated by subjective evaluation was -0.857±0.059, -0.938±0.092, not correlated, respectively. The correlation with iEMG to judge fatigue degree was -0.782±0.090, -0.942±0.030, -0.928±0.026, respectively. Multiple linear regression analysis was performed on subjective score, iEMG value and eye movement parameters. The regression model yielded a coefficient of determination R²=0.989, with the following standardized coefficients: iEMG signals=0.27, ST=-0.16, SS=-0.513, and SA=-0.124. This study makes new explorations and attempts in the monitoring and evaluation methods of fatigue during weighted walking.