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%.

To investigate the mechanism and influencing factors of soil heating with coupled in situ thermal technology, a two-dimensional experimental setup was used to simulate the heat treatment process, and the effects of coupled steam injection on thermal conductive heating as well as the effects of steam injection rate and heating mode on the application of the thermal conductive heating and steam injection technology were investigated. The results show that coupling steam injection on the basis of thermal conductive heating treatment can accelerate heat transfer, reduce heat loss, shorten the heating time by 35.67%, and reduce energy consumption by 24.53%. The main mechanism of steam injection enhanced heating is as follows. The additional heat injection increases the temperature difference, which in turn enhances convective heat transfer in the liquid phase driven by buoyancy. The upward migration of steam under buoyancy or pressure to enhance convective heat transfer in the gas phase. In thermal conductive heating and steam injection treatment, changing the steam injection rate or heating mode had a small effect on the treatment energy consumption, increasing the steam flow rate from 0.18 to 0.54 kg/h can shorten the heating time by 22.05%, but increase the water consumption by 132.43%. Compared with the thermal conductive heating and steam injection heated at the same time, thermal conductive heating heated for 30 min and then coupled with steam injection can reduce the water consumption by 28.57%, but will extend the heating time by 3.84%. In engineering applications, suitable restoration solutions should be selected based on duration, cost, etc.

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.

Exploring the impact of various hole shapes on the acoustic emission properties of rocks and the fracture mechanisms within rock structures containing holes is of utmost importance, as it enables the detection of fracture progression in rock engineering and the prediction of instability and failure in defective rocks. The mechanical properties, acoustic emission evolution patterns, precursor characteristics of failure, and failure mechanisms of red sandstone samples with different hole shapes were investigated through uniaxial compression tests and acoustic emission systems. The results indicate that the compressive strength, elastic modulus, and strain energy of the intact specimen are approximately 1.4 times, 1.3 times, and 1.7 times greater, respectively, than those of the specimen containing holes. There is a mutation point in the evolution of the multifractal spectrum of A_E at 86%~95% of the peak stress, where the width undergoes a transition from an average low value to a sudden increase before and after the mutation point. This change is accompanied by an increase in fluctuation range, from small to large. The A_E waveform characteristics are distinguished by the presence of dual main frequency bands. As the sample approaches failure, a significant number of low-frequency and high-amplitude signals, along with high-amplitude and high-amplitude signals, are generated. These peculiar trends in acoustic emission can be used as precursors to the critical instability of red sandstone. Based on the correlation between the main frequency of the acoustic emission signal of the rupture event and the fracture mechanism of the rock, the failure mechanism of the intact and square cavity red sandstone is mainly characterized by tension-shear mixed failure, and the shear failure of circular cavity red sandstone is revealed, which effectively avoids the subjectivity of the RA-AF failure mode classification method, and the research results can provide certain guiding significance for engineering design and optimization.

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.

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.

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 order to understand the properties of char which is the main byproduct of coal pyrolysis in the reactor with internals, especially the char prepared at high temperatures, the char samples were prepared by pyrolysis of Yulin bituminous coal under vacuum condition between 1 000 ℃ and 1 500 ℃ in the fixed-bed reactor with internals. The variations of pore structure, composition, calorific value, and carbon structure of chars with pyrolysis temperature were studied. The isothermal combustion characteristic and kinetics were investigated by MFBRA(micro fluidized bed reaction analyzer). The results show that the increase in pyrolysis temperature leads to a deeper degree of pyrolysis. As the pyrolysis temperature increases, the C content and C/H molar ratio of chars gradually increase, H and O contents of chars gradually decreases, and the calorific value increases slightly. The specific surface area and pore volume of chars firstly decrease with the increase of pyrolysis temperature, and then remain essentially constant after the pyrolysis temperature exceeds 1 300 ℃, which is consistent with the trend of graphitization degree. The three-dimensional diffusion model G(x)=[1-(1-x)^1/2]² can well describe the combustion process of chars. The activation energy and pre-exponential factor increase with the increase of pyrolysis temperature, and vary in the range of 30.49~90.17 kJ/mol and 0.69~352.25 s^-1, respectively. The significant decrease in combustion reactivity of char prepared above 1400 ℃ is mainly due to the sharp increase of C/H.

The general acidification technology of horizontal wells provides a simple and important method of stimulation for carbonate gas reservoirs. The common acidization methods were divided into two major categories: matrix acidification and fracturing acidification. To determine the best stimulation method of horizontal wells between acid fracturing and matrix acidizing, it is significant to achieve the efficient exploitation of reservoirs and optimization of process program. A dimensionless gas production index formula was obtained for horizontal well acidizing in carbonate gas reservoir. Also, a carbonate-acid-stimulation coefficient model was established to optimize the general method of acidification for the horizontal wells in carbonate gas reservoirs. Then, the influence of geological and engineering factors on the acidization increase coefficient was analyzed. Finally, field verification and application were conducted. The conclusions are as follows. When the carbonate-acid-stimulation coefficient R_JH>1, the productivity of matrix acidizing wells exceeds that of fractured acidizing wells. When R_JH<1, the productivity of fractured acidizing wells is higher compared to matrix acidizing wells. A higher permeability anisotropy coefficient increases, the number of fracturing fractures and the amount of acid fluid, but reduces the carbonate-acid-stimulation coefficient. The increase in porosity and horizontal length lead, to a higher carbonate-acid-stimulation coefficient. When the porosity of the gas reservoir falls below 7.3%, the productivity of the fractured acidizing well is improved. When the length of the horizontal section is 500 m and the number of fracturing fractures exceeds 4, the carbonate-acid-stimulation coefficient R_JH<1, and the productivity of the fractured acidizing well is improved. When the total volume of acid solution injected is 600 m³, the productivity of fractured acidizing well reaches a higher level than when the acid-solution volumetric dissolving power X>0.08.As verified in the carbonate reservoirs located in the northeastern Sichuan block, the production increase effect produced by using the carbonate-acid-stimulation coefficient method is significant after process optimization. Therefore, a theoretical guidance is provided in this paper for optimizing the acidification method of horizontal wells in carbonate gas reservoirs.

A simplified lower-limb exoskeleton model was established for the prototype, and the D-H parameter method was used to perform dynamic analysis. Joint angles were measured experimentally and used as inputs for the controller. To address the robot's trajectory tracking problem, traditional PID control was employed, showing good tracking performance but slow response and parameter tuning speed. Although PSO(particle swarm optimization) accelerated the parameter tuning, issues with low convergence accuracy and local optimum traps persisted. Therefore, a PID control based on a chaotic-mapping improved PSO algorithm was designed. The results show that the randomness was enhanced, the parameter tuning speed was increased, and the tracking error was reduced. Simscape was used for visual simulation of joint angles, and the control performance was further validated through various experiments.