Reclaimed asphalt pavement (RAP) has been utilized in numerous road projects. However, considering safety and service life, further in-depth investigation is required into the road performance of high dosage RAP hot-mix/warm-mix recycled asphalt mixtures under traffic loads. To investigate this, indoor tests and mathematical analysis were employed to examine the impact of design parameters, including the waste cooking oil (WCO) content, RAP dosage, and mixing method, on the road performance of recycled asphalt mixtures. The results indicate that in most cases, the VMA of R-100RAP mixes exceeds 14%, and the VV exceeds 3%. Moreover, both the VV and VMA of asphalt mixtures with 60% RAP content, 10% WCO, and 1.0% asphalt fall within specified ranges. Additionally, the split strength ratios of the majority of R-100RAP, R-80RAP, W-80RAP, and R-60RAP mixes surpass 80%, indicating excellent resistance to water damage. The addition of WCO proves beneficial in enhancing the water damage resistance of recycled asphalt mixtures. Although the rutting resistance of the W-80RAP asphalt mixture was inferior to that of the recycled asphalt mixtures containing R-80RAP and R-60RAP, all three exhibited commendable rutting resistance. When comparing the performance of W-80RAP and R-60RAP, it is observed that W-80RAP exhibits a smaller phase angle and a larger stiffness value, indicating better aging resistance. In order to maximise performance and facilitate the effective building of high dosage RAP hot-mix/warm-mix recycled asphalt mixes, the research provides a theoretical framework.

The issue of comfort in subway stations is typically analyzed using the predicted mean vote (PMV) and the predicted percent dissatisfied (PPD) indices. Based on the PMV-PPD comfort indices calculation model, the weight proportions of different environmental parameters on comfort were studied. The PMV calculation model was improved by considering the spatiotemporal characteristics of passengers’ clothing and activity levels. The PPD calculation model was enhanced by taking into account the impact of drastic environmental temperature changes on comfort. The environmental comfort of public areas in stations was then analyzed using the improved PMV-PPD calculation model. On this basis, the feasibility of predicting environmental comfort using long short-term memory (LSTM) networks was explored. The research results indicate that the weight proportions of metabolic rate, air temperature, clothing thermal resistance, and humidity on environmental comfort are 0.558, 0.260, 0.113, and 0.069, respectively. At a given time, the maximum differences in PMV and PPD at different monitoring points on the platform are approximately 15% and 60%, respectively. The improved PMV-PPD calculation model is found to be more universally applicable compared to the traditional PMV-PPD calculation model. The neural network is shown to accurately predict PMV and PPD values, with a maximum error of 8% for PMV and 14% for PPD between the actual and predicted values.

Taking a three-level, multi product, and dual channel supply chain as an example, the inventory control problem in the supply chain under stochastic demand was explored. A dual channel supply chain simulation model was established based on the independent control, information sharing, and pre warehouse replenishment model of “single manufacturer-dual distributor-dual retailer-dual customer”. In node enterprises, the Pull/Push strategy was adopted for ordering decisions, and information entropy was used to measure the uncertainty of nodes. Finally, the whale optimization algorithm was used to adjust the inventory control parameters in the simulation model. The results show that in the case of interruption, the pre warehouse replenishment mode can increase customer satisfaction in the interrupted channel by 80%. The whale optimization algorithm can ensure customer satisfaction while controlling total costs and reducing uncertainty in the supply chain system.

The utilization of offshore floating photovoltaic has became a hotspot in major coastal countries in complex marine environment. Offshore floating photovoltaic is currently in the phase of the experimental and pilot test. In order to explore the main components and current technological status of offshore floating photovoltaic technology, and to assist in the large-scale and commercial development of offshore floating photovoltaic in China, by sorting out the main components of offshore floating photovoltaic, based on the research and application status of offshore floating photovoltaic at home and abroad, focusing on the structural types of floating platforms, and analyzing the characteristics of various types of floating platforms. The results reveal that the maturity level of zero-gap and non-zero-gap floating platform concepts is not high, and the novel body materials should be considered to reduce engineering costs. The electrical equipment that is suitable for the complex marine environment needs to be further improved. The business modes of integrating floating solar power with other marine scenarios should be actively developed. The strategy, security, and means of operation and maintenance need to be given special attention. The research aims to provide the current status and challenges of key technologies, and offer reference experience and research directions for the development and design of offshore floating photovoltaic.

The layout of the distribution path of urban logistics terminals is the key to controlling transportation costs. In order to solve the path planning problem of urban low-carbon logistics, a brainstorming-adaptive large neighborhood search algorithm (BSO_ALNS) was proposed. Firstly, a low-carbon vehicle path model with capacity and time window constraints based on vehicle fuel consumption (CVRPTW) was established with the optimization goal of minimum total vehicle transportation cost. Secondly, the brainstorming algorithm (BSO) was used to improve the quality of the initial solution, and the heuristic crossover strategy was introduced to improve the quality of the global search. Using the adaptive large neighborhood search (ALNS) local search, ten kinds of damage and repair operators were designed, and the adaptive weighting mechanism was introduced, combined with the simulated annealing criterion to avoid falling into the local optimum. The performance of the BSO_ALNS algorithm was tested by selecting C, R, CR and other types of instances of different scales in Solomon. Taking the shortest path distance as the goal, the error between the BSO_ALNS algorithm solution and the historical optimal solution is within 1.5%. With the goal of minimizing the total cost of vehicle transportation, the optimal solution is obtained BSO_ALNS compared with BSO and ALNS. It is proved that the proposed algorithm can effectively solve the problem of urban low-carbon logistics path optimization.

Most of Triassic strata in Guizhou are distributed with bedding rock landslides with weak interbeds, which are characterized by strong destructiveness, complex slip mechanism and difficult treatment. Taking the West Second Ring landslide in Guiyang City as an example, the disaster mechanism and instability evolution process were explored by means of field geological investigation, theoretical analysis and discrete element numerical simulation. The results show that the West Second Ring landslide is mainly composed of dolomitic layered cataclastic rock mass with good permeability and water retention, showing a “sponge” structure, and continuous rainfall is the direct cause of the landslide. The landslide is first cut out by the front sliding body and gradually pulled upward, and then the tensile cracks at the trailing edge of the sliding body developed further, which led to slip-tensile crack failure under the action of gravity. The simulation results are basically consistent with the actual situation. The landslide in West Second Ring Road can be divided into four stages of deformation and instability: natural dissolution and cracking, excavation and unloading expansion, saturated and weakened shear, and slow sliding and accumulation. The conclusions have certain reference significance for the disaster mechanism analysis and engineering prevention of Triassic bedding rock landslide with weak interlayer in Guizhou.

In order to enhance the overall performance of the heat sink, a novel meshed microchannel heat sink structure was introduced, and its geometric parameters were optimized by performing a multi-objective optimization. The Box-Behnken design method was utilized to conduct response surface analysis on the design variables of channel width, fin thickness, and channel depth. The resulting temperature and pressure drop functions of the spider-shaped microchannel were then fitted as objective functions. The Pareto solution set was derived by applying a multi-objective particle swarm optimization algorithm, followed by utilizing the technique for order preference by similarity to an ideal solution(TOPSIS) method for selection from the Pareto solution set. It is concluded that the Pareto solution set is the optimal choice across various conditions. The multivariate statistical coefficients R² for temperature and pressure drop functions are 0.999 6 and 0.998 4, respectively, suggesting a high level of accuracy in the fitting function. The optimized structure not only reduces the average temperature by 3 K compared with the original design, but also decreases the pressure drop by 1 514 Pa. This significant improvement in comprehensive performance demonstrates that a well-designed channel structure can further enhance the heat sink performance of the microchannel.

In order to solve the problem of automatic sorting of garbage, an intelligent sorting method for household garbage was designed based on the artificial intelligence computing platform Jetson NANO and YOLOv8 algorithm. Firstly, the lightweight YOLOv8 multi-target detection algorithm was used to classify garbage into four categories and achieve accurate recognition in the presence of occlusion. Secondly, the CoreXY coordinate transformation algorithm was used to determine the optimal angle for mechanical claw grasping and achieve precise garbage grasping. Finally, based on TensorRT optimization technology, the lightweight YOLOv8 multi-objective detection algorithm was deployed on the NANO hardware platform, completing the overall construction of the four major categories of garbage intelligent sorting system based on YOLOv8-NANO. The results show that in the self-made garbage test consisting of four major categories and a total of 13 sub categories, the sorting system can effectively achieve detection of single and multiple targets. The detection mAP0.5:0.95 value is 97.3%, and the target detection speed reaches 30.6 frames/s. The fastest garbage sorting speed could reach 6 pieces/min.

Subsidence monitoring and reservoir parameters inversion in gas field can provide important supporting information for safe production protection and mining planning. The SBAS-InSAR method was used to investigate the surface subsidence evolution characteristics of Sebei gas fields from February 2022 to September 2023. Furthermore, the InSAR monitoring results were used as the observation measurements to invert the reservoir center projection coordinates, depth, strike and other parameters of the gas fields through the Prolate spheroid source. The results show that the subsidence funnel occurs in the Tainan gas field, the Sebei No.1 gas field and the Sebei No.2 gas field, and the average annual subsidence rate is -124~-109, -275~-34, and -329~-89 mm/a, respectively. Among them, the Sebei No.1 gas field and the Sebei No.2 gas field show a more significant surface subsidence phenomenon. And the surface of all three gas fields continues to sink rapidly. Further, the reservoir parameters were obtained by inversion of InSAR monitoring results. The results show that there is little difference between the deformation derived by using the optimal parameters and the observed deformation, and the spatial distribution is consistent, which indicates that it is feasible to invert the reservoir parameters of Sebei gas fields based on SBAS-InSAR deformation results.

The occurrence characteristics and genetic models of geothermal resources is an important basis for the development of geothermal resources. Drilling data, geophysical and geochemical data was applied to analyze the thermal reservoir, cap rock, heat sources, channels and supply elements, and the genetic model of geothermal system in the southwest of Zhoukou Depression was established. The development prospect was also evaluated. The geothermal resources in study area can be divided into sedimentation basin type with low temperature. Mantle derived heat is the main heat source, and the geothermal flow in the north part is higher than that in the south part, also in the protruding area is higher than that in the depressed area, reaching over 70 mW/m². The average geothermal gradient is about 2.8 ℃/hm, dominated by heat conduction system. Isotope analysis shows that the supply source comes from atmospheric precipitation in the western low mountains and hills, which infiltrates through the exposed area and moves along permeable strata and unconformity towards the east, and is heated and warmed up. The pores of the Neogene and Paleogene sandstones, as well as the karst pores of the Cambrian-Ordovician carbonate rocks, are the main storage spaces for fluids. The silt and clay deposits developed in the upper part of the Quaternary and Neogene systems form a good waterproof and thermal insulation cover layer. The development and utilization risk of the Neogene system is the lowest, with a floor depth of 400~1 400 m, increasing towards the north. The average sand to soil ratio is 40.9%, with a water flow between 40~60 m³/h and a wellhead temperature of 43~48 ℃. The development of faults also promotes the upwelling of deep heat flow, and there is a local thermal convection warming effect. Finally, four favorable development area for porous geothermal resources and three favorable areas for karst resources were identified.