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As urbanization advances, rural construction and resource development in China encounter significant challenges, leading to the widespread adoption of standardized planning and design methods to manage increasing population pressure. These uniform approaches often prioritize economic benefits over climate adaptability and energy efficiency. This paper addresses this issue by focusing on traditional mountain villages in northern regions, particularly examining the wind and thermal environments of courtyards and street networks. This study integrates energy consumption and comfort performance analysis early in the planning and design process, utilizing Genetic and XGBoost algorithms to enhance efficiency. This study began by selecting a benchmark model based on simulations of courtyard PET (Physiological Equivalent Temperature) and MRT (mean radiant temperature). It then employed the Wallacei_X plugin, which uses the NSGA-II algorithm for multi-objective genetic optimization (MOGO) to optimize five energy consumption and comfort objectives. The resulting solutions were trained in the Scikit-learn machine learning platform. After comparing machine learning models like RandomForest and XGBoost, the highest-performing XGBoost model was selected for further training. Validation shows that the XGBoost model achieves an average accuracy of over 80% in predicting courtyard performance. In the project's validation phase, the overall street network framework of the block was first adjusted based on street performance prediction models and related design strategies. The optimized model prototype was then integrated into the planning scheme according to functional requirements. After repeated validation and adjustments, the performance prediction of the village planning scheme was conducted. The calculations indicate that the optimized planning scheme improves overall performance by 36% compared with the original baseline. In conclusion, this study aimed to integrate performance assessment and machine learning algorithms into the decision-making process for optimizing traditional village environments, offering new approaches for sustainable rural development. [ABSTRACT FROM AUTHOR]

Currently, there is no mature method for calculating the probability of human failure that occurs in multi-unit. In this study, the single-unit HRA is expanded and improved, and we have compiled a method flow suitable for human reliability analysis in multi-unit. This method considers the communication of commands between different organizations and analyzes the equipment shared by multiple units. This research demonstrates the feasibility of the THERP+HCR method to calculate the human-caused failure probability of multiple units. In this paper, the human failure probability of the fifth emergency diesel engine is investigated during a station blackout at a multi-unit site. The calculated failure probability of personnel deploying a fifth diesel-engine between two units is 0.1061, which is higher than the failure probability of a single unit, and the consequences of failure of a dual-unit invocation would be more severe. Due to the uncertainty of some conditions and parameters, the variation of the failure probability after sensitivity analysis ranges from–0.0846–0.2083. Involvement of more organizations during the accident increases the risk of the plant site. Among the most influential factors on the probability of failure are the presence of inspection clauses in the operating procedures and the level of tension of personnel. [ABSTRACT FROM AUTHOR]

Carrying out full lifecycle management of SF6 gas recovery, purification, and recycling, developing new digital control technologies, and eliminating SF6 gas emissions from the source are of great significance for achieving the “dual carbon” goal. Given the low level of digital control of SF6 gas at present, especially in the situation, the SF6 gas recovery rate, the effective volume of the gas chamber, and gas weight cannot be accurately measured at an on-site inspection surface, this paper carries out research on SF6 gas recovery rate measurement at on-site inspection surface and key technologies of gas measurement. An intelligent online monitoring device such as SF6 gas recovery rate and effective chamber volume of high voltage electrical equipment was developed, which can quickly identify SF6 gas density, recovery rate, effective chamber volume, weight, and other parameters in high voltage electrical equipment, and evaluate the detection methods such as gas recovery rate and effective chamber volume. The results show that when the recovery rate was about 96.5%, the maximum positive deviation between the recovery rate measured by the detection device and that measured by the weighing method was 0.32% and the maximum negative deviation was -0.24%, both of which are less than 0.50%. When the container to be tested was 1000 L, the maximum indication error was -1.51%, which can meet the requirements of digital control in the SF6 gas recycling and reuse process of high-voltage electrical equipment.

NASICON-type electrode materials suffer from poor intrinsic electronic conductivity, which significantly limits their capacity and rate capability for further application in sodium-ion batteries. Herein, we aim to address this issue by introducing oxygen vacancies (VO) into core–shell C@NaTi2(PO4)3-x composites to tailor the electronic structures and enhance the Na storage performance. Various characterization techniques, including Rietveld refinement of X-ray diffraction (XRD), electron paramagnetic resonance (EPR) and X-ray photoelectron spectroscopy (XPS), confirm the successful generation of VO in the core–shell C@NaTi2(PO4)3-x composites. Density functional theory calculations demonstrate that VO induce partial hole states in O 2p orbitals, localizing the electronic structures of P1 3p, Ti1 t2g, and Ti2 t2g orbitals. Simultaneously, the electronic structure of O atoms bridging these cations (Ti1, Ti2, and P1) becomes delocalized. This unique electronic modulation facilitates sodiation/desodiation and enhances fast Na+ diffusion kinetics. Among the C@NaTi2(PO4)3-x composites, the C@NaTi2(PO4)3-1.0 anode, which possesses the highest content of VO, exhibits the most stable cycling performance (retaining 108.9 mA h g−1 after 10 000 cycles at 20C) and the best rate capability. The CV and GITT tests confirm about an order of magnitude of DNa+ increase in C@NaTi2(PO4)3-1.0 composites. Furthermore, the EPR, scanning electron microscopy and transmission electron microscopy results confirm the robustness of intrinsic VO and the stable core–shell structure even after 10 000 cycles at 20C, firmly confirming their ability to enable high electrochemical activity. Overall, the engineering of oxygen vacancies provides a promising approach to address the poor electronic and ionic conductivities of NASICON-type materials for future applications of SIBs. [ABSTRACT FROM AUTHOR]