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Hydrogen refueling station (HRS) is an essential part of the infrastructure for promoting the hydrogen economy. Since hydrogen is a flammable and explosive gas, hydrogen released from high‐pressure hydrogen storage equipment in HRS will likely cause combustion or explosion accidents. Studying high‐pressure hydrogen leakage in HRS is a prerequisite for promoting hydrogen fuel cell vehicles and HRS. A computational fluid dynamics (CFD) model of an HRS in a demonstrated project in Ningbo, China, was established on the ANSYS FLUENT software platform. The CFD model for hydrogen leakage simulation was validated by comparing the simulation results with experimental data in the literature. The effects of the direction and mass flow rate of the hydrogen leakage jet, as well as the direction and speed of ambient wind, on hydrogen diffusion behavior were investigated. The spreading distances of the flammable hydrogen cloud were predicted using an artificial neural network for horizontal leakage. The results show that the jet direction strongly affected the flammable cloud flow. The greater the mass flow rate of the leak, the greater the hydrogen dispersion distance and the volume of the flammable hydrogen cloud. At a hydrogen leakage mass flow rate of 4.5589 kg/s, the volume of the hydrogen flammable cloud reached 6,140.46 m3 at 30 s of leakage. The ambient wind speed has complicated effects on spreading the flammable cloud. The wind makes the flammable cloud move in certain directions, and the higher wind speed accelerates the diffusion of the flammable gas in the air. The results of the study can be used as a reference for the study of high‐pressure hydrogen leakage in HRS and will play an important role in the safe demonstration of the studied project. [ABSTRACT FROM AUTHOR]

Liquid hydrogen storage is an important way of hydrogen storage and transportation, which greatly improves the storage and transportation efficiency due to the high energy density but at the same time brings new safety hazards. In this study, the liquid hydrogen leakage in the storage area of a hydrogen production station is numerically simulated. The effects of ambient wind direction, wind speed, leakage mass flow rate, and the mass fraction of gas phase at the leakage port on the diffusion behavior of the liquid hydrogen leakage were investigated. The results show that the ambient wind direction directly determines the direction of liquid hydrogen leakage diffusion. The wind speed significantly affects the diffusion distance. When the wind speed is 6 m/s, the diffusion distance of the flammable hydrogen cloud reaches 40.08 m, which is 2.63 times that under windless conditions. The liquid hydrogen leakage mass flow rate and the mass fraction of the gas phase have a greater effect on the volume of the flammable hydrogen cloud. As the leakage mass flow rate increased from 5.15 kg/s to 10 kg/s, the flammable hydrogen cloud volume increased from 5734.31 m3 to 10,305.5 m3. The installation of a barrier wall in front of the leakage port can limit the horizontal diffusion of the flammable hydrogen cloud, elevate the diffusion height, and effectively reduce the volume of the flammable hydrogen cloud. This study can provide theoretical support for the construction and operation of hydrogen production stations. [ABSTRACT FROM AUTHOR]

With the rapid development of hydrogen energy worldwide, the number of hydrogen energy facilities, such as hydrogen refueling stations, has grown rapidly in recent years. However, hydrogen is prone to leakage accidents during use, which could lead to hazards such as fires and explosions. Therefore, research on the safety of hydrogen energy facilities is crucial. In this paper, a study of high-pressure hydrogen jet flame accidents is conducted for a proposed integrated hydrogen production and refueling station in China. The effects of leakage direction and leakage port diameter on the jet flame characteristics are analyzed, and a risk assessment of the flame accident is conducted. The results showed that the death range perpendicular to the flame direction increased from 2.23 m to 5.5 m when the diameter of the leakage port increased from 4 mm to 10 mm. When the diameter of the leakage port is larger than 8 mm, the equipment on the scene will be within the boundaries of the damage. The consequences of fire can be effectively mitigated by a reasonable firewall setup to ensure the overall safety of the integrated station. [ABSTRACT FROM AUTHOR]

The era of Industry 4.0 is gradually transforming our society into a data-driven one, which can help us uncover valuable information from accumulated data, thereby improving the level of social governance. The detection of anomalies, is crucial for maintaining societal trust and fairness, yet it poses significant challenges due to the ubiquity of anomalies and the difficulty in identifying them accurately. This paper aims to enhance the performance of the current Graph Convolutional Network (GCN)-based Graph Anomaly Detection (GAD) algorithm on datasets with extremely low proportions of anomalous labels. This goal is achieved through modifying the GCN network structure and conducting feature extraction, thus fully utilizing three types of information in the graph: node label information, node feature information, and edge information. Firstly, we theoretically demonstrate the relationship between label propagation and feature convolution, indicating that the Label Propagation Algorithm (LPA) can serve as a regularization penalty term for GCN, aiding in training and enabling learnable edge weights, providing a basis for incorporating node label information into GCN networks. Secondly, we introduce a method to aggregate node and edge features, thereby incorporating edge information into GCN networks. Finally, we design different GCN trainable weights for node features and co-embedding features. This design allows different features to be projected into different spaces, greatly enhancing model expressiveness. Experimental results on the DGraph dataset demonstrate superior AUC performance compared to baseline models, highlighting the feasibility and efficacy of the proposed approach in addressing GAD tasks in the scene with extremely low proportions of anomalous data. [ABSTRACT FROM AUTHOR]

Pure organic persistent room‐temperature phosphorescence (p‐RTP) materials have attracted rapidly growing attention due to their unique photophysical properties and wide potential practical applications. However, most of the reported pure organic p‐RTP materials have low quantum yields and short lifetimes, and many p‐RTP compounds contain large π‐conjugated structures, which are difficult and complex to synthesize. Herein, a series of triazole derivatives with efficient p‐RTP emissions is reported. 2H‐1,2,3‐triazole‐4,5‐dicarboxylic acid (TDAc) is first found to exhibit green RTP under 312 nm excitation. Then, a series of ionized products of TDAc and their isomers with red‐shifted RTP emissions are further obtained by ionization of TDAc. Among them, the sodium 2H‐1,2,3‐triazole‐4‐carboxy‐5‐carboxylate can emit RTP with an ultra‐long phosphorescence lifetime (3.25 s) and high photoluminescence (PL) and p‐RTP quantum yields of 31.3% and 14.2%, respectively, as well as mechanorochromic behavior. Experimental results and theoretical calculations prove that strong intra‐/intermolecular interactions including hydrogen bonding and ionic bonding promote the overlap of molecular orbitals to form effective through‐space conjugation (TSC) and greatly stabilize the conformations, thus achieving efficient p‐RTP emissions. This work provides a simple and efficient strategy for designing p‐RTP compounds with high quantum yields. [ABSTRACT FROM AUTHOR]