基于动态聚类分析的空袭编队判断模型

空袭编队是由担负不同作战任务的飞机组成的战术机群,其分布是防空作战指挥员分析空袭企图和定下作战决心的重要依据。空袭编队具有数量多、分布范围大,空情分析要求实时性强的特点,依据空中目标的数据特征,首先建立了基于动态聚类法对空中目标群进行分类的方法和步骤,该算法具有较好地收敛性,能够满足防空指控系统的高实时性要求。在此基础上提出了目标群内和目标群间作战参数的计算方法,并依据空袭编队数量分布及航路捷径给出了主要来袭方向和攻击企图分析模型。最后给出了一个具体算例,其运行结果与指挥员的判断基本吻合。工程实际应用表明,该模型能对空中目标进行快速聚类,可为区域防空指挥员准确掌握空情和快速决策提供量化依据。     

Iron Oxide Nanoparticle-Based Ferro-Nanofluids for Advanced Technological Applications

Iron oxide nanoparticle (ION)-based ferro-nanofluids (FNs) have been used for different technological applications owing to their excellent magneto-rheological properties. A comprehensive overview of the current advancement of FNs based on IONs for various engineering applications is unquestionably necessary. Hence, in this review article, various important advanced technological applications of ION-based FNs concerning different engineering fields are critically summarized. The chemical engineering applications are mainly focused on mass transfer processes. Similarly, the electrical and electronics engineering applications are mainly focused on magnetic field sensors, FN-based temperature sensors and tilt sensors, microelectromechanical systems (MEMS) and on-chip components, actuators, and cooling for electronic devices and photovoltaic thermal systems. On the other hand, environmental engineering applications encompass water and air purification. Moreover, mechanical engineering or magneto-rheological applications include dampers and sealings. This review article provides up-to-date information related to the technological advancements and emerging trends in ION-based FN research concerning various engineering fields, as well as discusses the challenges and future perspectives.     

用空气作绿色氧化剂合成苯并咪唑的新方法

报道了一种利用空气作为氧化剂由邻苯二胺和醛为原料合成苯并咪唑的新方法.该方法以DMF为溶剂,等物质的量的邻苯二胺和醛反应一锅合成目标产物,产率较好(64%~90%),且具有操作简单、条件温和、环境友好等优点.     

Energy Analysis of Precooling Air Compressor System

Energy saving is one of the main technique routes for net zero carbon emissions. Air compressor systems take up a large part of energy consumption in the industrial field. A pre-cooling air compressor system was proposed for energy saving by cooling the air before it flows in a compressor. The energy efficiency of the proposed system was analyzed. As additional energy consumption is required for air cooling, the feasibility of the pre-cooling method for energy saving was analyzed. As the efficiency of the pre-cooling air compressor system is mainly influenced by the environment temperature and humidity, applicability of the system in different regions and at different seasons was discussed. A pilot project was performed to verify the technical feasibility and economics of the proposed system. When the precooling temperature of the pilot system was set to 2 °C, the annual pneumatic-electrical ratio of the system can be increased by approximately 2% in several regions of China. This paper shows the pre-cooling air compressor system is feasible for energy saving.     

An Improved Temporal Fusion Transformers Model for Predicting Supply Air Temperature in High-Speed Railway Carriages

A key element for reducing energy consumption and improving thermal comfort on high-speed rail is controlling air-conditioning temperature. Accurate prediction of air supply temperature is aimed at improving control effects. Existing studies of supply air temperature prediction models are interdisciplinary, involving heat transfer science and computer science, where the problem is defined as time-series prediction. However, the model is widely accepted as a complex model that is nonlinear and dynamic. That makes it difficult for existing statistical and deep learning methods, e.g., autoregressive integrated moving average model (ARIMA), convolutional neural network (CNN), and long short-term memory network (LSTM), to fully capture the interaction between these variables and provide accurate prediction results. Recent studies have shown the potential of the Transformer to increase the prediction capacity. This paper offers an improved temporal fusion transformers (TFT) prediction model for supply air temperature in high-speed train carriages to tackle these challenges, with two improvements: (i) Double-convolutional residual encoder structure based on dilated causal convolution; (ii) Spatio-temporal double-gated structure based on Gated Linear Units. Moreover, this study designs a loss function suitable for general long sequence time-series forecast tasks for temperature forecasting. Empirical simulations using a high-speed rail air-conditioning operation dataset at a specific location in China show that the temperature prediction of the two units using the improved TFT model improves the MAPE by 21.70% and 11.73%, respectively the original model. Furthermore, experiments demonstrate that the model effectively outperforms seven popular methods on time series computing tasks, and the attention of the prediction problem in the time dimension is analyzed.     

明线会车、隧道会车及过隧道时的高速列车动力响应1)

明线会车、隧道会车和过隧道工况下的气动压力波对高速列车的动力响应和运行安全产生很大影响,本文建立了三辆编组的高速列车动力学模型,通过数值仿真得到了列车在三种工况下的车体所受的气动力,基于数值积分分析了列车的动力响应和脱轨系数。研究发现：明线会车和隧道会车工况相比,车辆的侧向运动相反。 明线会车和过隧道时,气动载荷对列车的脱轨系数影响较小,而隧道会车时,气动载荷作用对尾车的安全性影响较大。     

林芝市主城区典型生态用地空气质量评价

对林芝市主城区典型生态用地空气质量进行评价,以期为其市政规划及旅游发展提供依据.在市区选择典型生态用地,监测其空气正负离子、温湿度及大气颗粒物,采用单因素方差、多重比较及主成分分析等方法,对其空气质量指标的动态变化及综合评价进行研究.结果表明:①不同季节空气负离子含量日变化均呈"单峰"型,峰值出现在14:00左右;不同季节温湿度指数的日变化同空气负离子的日变化一致,夏季全天候均表现为舒适,冬季全天候均表现为寒冷;夏季及秋冬季节颗粒物(PM_2.5,PM₁₀,TSP)日变化分别表现为"线性递减"和"幂函数"型曲线.不同季节颗粒物含量达标率均在50%以上.②空气负离子、温湿度指数季变化从大到小均为:夏季、秋季、冬季,而颗粒物含量季变化从小到大均为:夏季、秋季、冬季;不同季节各生态用地在空气负离子、温湿度指数、颗粒物含量中大小顺序不一.③空气负离子、 PM_2.5、 PM₁₀、 TSP、温湿度指数及温度在第一主成分中的载荷系数较大(0.8以上),其对第一主成分的影响较大;绿地、水体空气质量优于湿地和对照点.绿...     

钝头机体用嵌入式大气数据传感系统的 改进三点式算法1)

针对传统的用于钝头体飞行器的嵌入式大气数据传感系统的经典三点式算法对测压孔配置约束性严格的特点,对经典三点式算法进行了改进及验证。首先,对于经典三点式算法及改进算法进行了论述;其次,针对不同测压孔配置对算法精度的影响进行了系统的评估;最后,对于传统的经典三点式算法与改进三点式算法的优劣进行了比较。结论为：(1)改进的三点式算法对于测压孔的配置敏感性变差,即对测压孔约束很宽松,可用测压孔数增加,从而使得算法的适用性更强;(2)改进的三点式算法的精度与三点式算法相当,但是需要对测压孔进行系统选取及对比验证。     

Effects of a Volatile Organic Compound Filter on Breath Profiles Measured by Secondary Electrospray High-Resolution Mass Spectrometry

Environmental volatile organic compounds (VOCs) from the ambient air potentially influence on-line breath analysis measurements by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). The aim of this study was to investigate how inhaling through a VOC filter affects the detected breath profiles and whether it is feasible to integrate such filters into routine measurements. A total of 24 adult participants performed paired breath analysis measurements with and without the use of an activated carbon filter for inspiration. Concordance correlation coefficients (CCCs) and the Bland–Altman analysis were used to assess the agreement between the two methods. Additionally, the effect on a selection of known metabolites and contaminants was analyzed. Out of all the detected features, 78.3% showed at least a moderate agreement before and after filter usage (CCC > 0.9). The decrease in agreement of the remaining m/z features was mostly associated with reduced signal intensities after filter usage. Although a moderate-to-substantial concordance was found for almost 80% of the m/z features, the filter still had an effect by decreasing signal intensities, not only for contaminants, but also for some of the studied metabolites. Operationally, the use of the filter complicated and slowed down the conductance of measurements, limiting its applicability in clinical studies.     

Anodic TiO2 Nanotube Layers for Wastewater and Air Treatments: Assessment of Performance Using Sulfamethoxazole Degradation and N2O Reduction

The preparation of anodic TiO₂ nanotube layers has been performed using electrochemical anodization of Ti foil for 4 h at different voltages (from 0 V to 80 V). In addition, a TiO₂ thin layer has been also prepared using the sol–gel method. All the photocatalysts have been characterized by XRD, SEM, and DRS to investigate the crystalline phase composition, the surface morphology, and the optical properties, respectively. The performance of the photocatalyst has been assessed in versatile photocatalytic reactions including the reduction of N₂O gas and the oxidation of aqueous sulfamethoxazole. Due to their high specific surface area and excellent charge carriers transport, anodic TiO₂ nanotube layers have exhibited the highest N₂O conversion rate (up to 10% after 22 h) and the highest degradation extent of sulfamethoxazole (about 65% after 4 h) under UVA light. The degradation mechanism of sulfamethoxazole has been investigated by analyzing its transformation products by LC-MS and the predominant role of hydroxyl radicals has been confirmed. Finally, the efficiency of the anodic TiO₂ nanotube layer has been tested in real wastewater reaching up to 45% of sulfamethoxazole degradation after 4 h.