Fujian Special Equipment Inspection Institute

Abstract The effect of the different temperatures of the skin-effect heating cables on the buried pipeline of the pressure-regulating station. Ansys Workbench was applied to numerically simulate the effect of skin-effect heating cables on buried pipelines located in the permafrost zone and the surrounding permafrost. At the same time, according to the analysis results, the best heat-tracing temperature was selected. The analysis showed that the buried pipeline around the low-temperature area of the heating cable progressively heated, and the side on which the heating cable is laid was hotter than the other side as the heat-tracing temperature increased. And buried pipeline straight pipe before the 7 m stress distribution complex. However, 7 m after the pipeline is subject to stress with the increase of the heat-tracing temperature and increasing. The displacement of the pipeline except 50 °C has obviously changed. Meanwhile, 30 °C is selected as the optimal heat-tracing temperature according to the temperature field analysis. The relevant conclusions and research methods are of great significance for the optimization of the method of laying the heating cable in the gas transmission station in the future, providing an energy-efficient and safe heating system design basis for gas transmission stations in permafrost regions, which holds significant engineering guidance value for achieving refined management and low-carbon operation.

With the increasing number of retired lithium-ion batteries from electric vehicles (EVs), effective screening and classification are necessary to enable their secondary utilization. The existing retired lithium-ion battery screening methods have limitations in accuracy and high-energy consumption. This article proposes a method based on local discharge curves and an improved CrossFormer model to reduce energy consumption and improve screening accuracy. Considering the actual conditions of retired lithium-ion batteries, features are extracted from the discharging stage. Select the segments of the capacity sequence that exhibit the most significant variation with the voltage sequence and construct a partial capacity-voltage sequence. The standard deviation (Std) and Shannon entropy (ShanEn) of the capacity sequence, as well as the variance, energy, and the maximum amplitude of the low-frequency part of the Fourier-transformed voltage sequence, are used as features. Then, the CrossFormer utilizes a flexible embedding mechanism and a hierarchical structure for handling the dependencies of the feature. The CrossFormer is improved for classification by adding a cross-attention layer at the final stage of the CrossFormer decoder, which enhances its ability to capture the dependencies between features and improves the model’s performance in battery screening classification. Finally, the validation of 252 retired batteries shows that the method achieves a classification accuracy of 94.74%, outperforming other advanced models, including the original CrossFormer, Transformer, ResNet, and multilayer perceptron (MLP) models.

In recent years, extensive attention has been paid to advanced oxidation processes (AOPs) with peracetic acid (PAA), a widely used disinfectant, using transition metal ions for the degradation of organic contaminants within water environments. Mn(II) has been widely used as an effective homogeneous transition metal catalyst for oxidant activation, but it has shown poor performances with PAA. Since the stability of manganese species can be enhanced through the addition of ligands, this study systematically investigated a novel AOP for the oxidation of carbamazepine (CBZ) using an Mn(II)/PAA system with several different ligands added. The reactive species were explored through UV-vis spectrometry, scavengers, and probe compounds. The results suggest that Mn(III)–ligand complexes and other high-valent Mn species (Mn(V)) were generated and contributed obviously toward efficient CBZ oxidation, while radicals like CH3CO2• and CH3CO3• were minor contributors. The oxidation efficiency of Mn(II)/PAA/ligands depended highly on ligand species, as ethylene diamine tetraacetic acid (EDTA) and oxalate (SO) could promote the oxidation of CBZ, while pyrophosphate (PPP) showed modest enhancement. The results obtained here might contribute to the removal of residue pharmaceuticals under manganese-rich waters and also shed light on PAA-based AOPs that could help broaden our present knowledge of manganese chemistry for decontamination in water treatment.

This study focuses on improving the operating efficiency and intelligent energy consumption control of elevator systems, and cleverly integrates the global optimization technology of simulated annealing algorithm. The core goal of this framework is to improve the elevator scheduling strategy, to effectively reduce energy consumption while ensuring efficient transportation. For the complex scenario of multi-elevator coordinated scheduling, the simulated annealing algorithm demonstrates its excellent ability in global search and solution. To rigorously verify the practicality and effectiveness of the proposed algorithm, this study constructed a detailed mathematical model of elevator operation and conducted comprehensive and in-depth experimental verification in the MATLAB simulation environment. The experimental results strongly confirm that compared with the traditional scheduling algorithm, the system designed in this study successfully achieved significant energy consumption reduction based on maintaining or even optimizing the elevator transportation efficiency. Specifically, under the set experimental conditions, compared with the traditional control system, this system achieved about 15.3% energy saving and about 12.7% transportation time optimization. Through in-depth analysis of a large amount of experimental data, people further confirmed that the simulated annealing algorithm not only performs well in solving the elevator scheduling problem, but also has good stability and convergence characteristics. The intelligent control module embedded in this system can keenly perceive the dynamic changes in floor demand and adjust the elevator operation strategy in real time, thereby achieving the effect of dynamic energy consumption optimization.