泡沫-细水雾对变压器油池火的冷却及热辐射阻隔特性研究

泡沫-细水雾在全尺寸变压器灭火实验中展现出高效灭火性能。纯水细水雾具有冷却效果好、热辐射阻隔能力强的特点,但添加泡沫灭火剂后对其冷却及热辐射阻隔特性的影响机制尚不明确。对泡沫-细水雾和纯水细水雾的冷却与热辐射阻隔特性进行了对比实验,并基于雾特性测试结果对相应性能的差异进行了分析。发现添加泡沫灭火剂后能降低水雾的粒径,从而令泡沫-细水雾的冷却和热辐射阻隔性能优于纯水细水雾。此外,泡沫灭火剂中的阻燃物质也是加速火焰熄灭的重要因素。研究结果可为变压器灭火系统选择、泡沫-细水雾系统工况参数优化等方面提供理论指导。     

Parametric study along with selection of optimal solutions in dry wire cut machining of cemented tungsten carbide (WC-Co)

This work deals with parametric study of dry wire EDM (WEDM) process of cemented tungsten carbide. Experiments have been conducted using air as dielectric medium to investigate effects of pulse on time, pulse off time, gap set voltage, discharge current and wire tension on cutting velocity (CV) surface roughness (SR) and oversize (OS). Firstly, a series of exploratory experiments were carried out to identify appropriate gas and its pressure. Afterward, preliminary experiments were conducted to investigate effects of process parameters on dry WEDM characteristics and find appropriate ranges for each factor. Then a central composite rotatable method was employed to design experiments based on response surface methodology (RSM). Empirical models were developed to create relationships between process factors and responses by considering to analysis of variances (ANOVA). To increase the predictability of the process, intelligent models have been developed based on back-propagation neural network (BPNN) and accuracy of these models was compared with mathematical models based on root mean square error (RMSE) and prediction error percent (PEP). In order to select optimal solutions in the cases of single-objective and multi-objectives optimization problems, optimization includes two main approaches. First approach was based on mathematical model and desirability function. Also second approach was designed based on neural network and particle swarm optimization. These approaches were applied in both cases of single-objective and multi-objectives optimization problems and their results were compared with together. Results indicated that selection of air at inlet pressure of 1.5 bar is really appropriate for conducting experiments of next stages. Also, the BPNN creates more accurate prediction rather than mathematical model. Moreover, the BPNN-PSO approach was more efficient in optimization of process rather than mathematical model-desirability function in respect with validation tests.     

典型机载设备加速振动试验应用方法研究

目的为了提高加速振动试验方法在高新军用装备中工程化应用的准确性和可操作性。方法由于在合理的加速等级下,较大的振动能量可能导致试件局部振动疲劳累积损伤机理发生改变,因此在传统加速振动试验中充分评估结构试件的频率响应特性,得出一种修正的加速振动试验方法。首先结合计算机辅助分析手段对试件进行模态分析及频率响应分析,识别试件的薄弱部位。其次利用结构动力学特性测试手段,对薄弱部位的实测动态特性进行分析,并对超出加速响应限的加速度幅值进行修正。结果以典型的机载设备结构作为研究对象,将试件薄弱部位的频率响应幅值控制在合理的放大系数范围内,保证加速破坏机理的一致性,修改后加速振动试验结果与长周期正常等级振动试验结果特征一致。结论该方法符合国军标中振动试验方法的有关规定,可在装备研制过程中对设备结构部件的加速振动试验加以工程化应用。     

Challenges in characterization of nanoplastics in the environment

Plastic pollution has been a legacy environment problems and more recently, the plastic particles, especially those ultrafine or small plastics particles, are widely recognized with increasing environmental and ecological impacts. Among small plastics, microplastics are intensively studied, whereas the physicochemical properties, environmental abundance, chemical states, bioavailability and toxicity toward organisms of nanoplastics are inadequately investigated. There are substantial difficulties in separation, visualization and chemical identification of nanoplastics due to their small sizes, relatively low concentrations and interferences from co-existing substances (e.g., dyes or natural organic matters). Moreover, detection of polymers at nanoscale is largely hampered by the detection limit or sensitivity for existing spectral techniques such as Transformed Infrared Spectroscopy (FTIR) or Raman Spectroscopy. This article critically examined the current state of art techniques that are exclusively reported for nanoplastic characterization in environmental samples. Based on their operation principles, potential applications and limitations of these analytical techniques are carefully analyzed.     

Particle concentration effect in adsorption/desorption of Zn（Ⅱ） on anatase type nano TiO2

Adsorption/desorption in a new Zn(II)-TiO2 adsorption system was investigated at different particle concentrations (Cp). TEM, SEM and XRD analyses revealed that the TiO2 particles were an aggregation of nano-sized (approximately 10 nm) pure anatase-type TiO2. Adsorption experiments were carried out with particle concentrations of 100, 400 and 1000 mg/L, and their adsorption isotherms were found to decline successively, showing an obvious Cp effect. Desorption experiments indicated that adsorption in this system was irreversible, and the irreversibility increased with increasing Cp. These phenomena could be explained by the MEA (metastable equilibrium adsorption) theory and the Cp effect could be modeled well with an MEA-Freundlich-type Cp effect isotherm equation. This study may help understand environmental behavior of contaminants on ultrafine natural particles.     

Roles of SO2 oxidation in new particle formation events

The oxidation of SO₂ is commonly regarded as a major driver for new particle formation (NPF) in the atmosphere. In this study, we explored the connection between measured mixing ratio of SO₂ and observed long-term (duration > 3 hr) and short-term (duration <1.5 hr) NPF events at a semi-urban site in Toronto. Apparent NPF rates (J₃₀) showed a moderate correlation with the concentration of sulfuric acid ([H₂SO₄]) calculated from the measured mixing ratio of SO₂ in long-term NPF events and some short-term NPF events (Category I) (R² = 0.66). The exponent in the fitting line of J₃₀ ~ [H₂SO₄]ⁿ in these events was 1.6. It was also found that SO₂ mixing ratios varied a lot during long-term NPF events, leading to a significant variation of new particle counts. In the SO₂-unexplained short-term NPF events (Category II), analysis showed that new particles were formed aloft and then mixed down to the ground level. Further calculation results showed that sulfuric acid oxidized from SO₂ probably made a negligible contribution to the growth of >10 nm new particles.     

Unraveling the size distributions of surface properties for purple soil and yellow soil

Soils contain diverse colloidal particles whose properties are pertinent to ecological and human health, whereas few investigations systematically analyze the surface properties of these particles. The objective of this study was to elucidate the surface properties of particles within targeted size ranges (i.e. > 10, 1–10, 0.5–1, 0.2–0.5 and < 0.2 μm) for a purple soil (Entisol) and a yellow soil (Ultisol) using the combined determination method. The mineralogy of corresponding particle-size fractions was determined by X-ray diffraction. We found that up to 80% of the specific surface area and 85% of the surface charge of the entire soil came from colloidal-sized particles (< 1 μm), and almost half of the specific surface area and surface charge came from the smallest particles (< 0.2 μm). Vermiculite, illite, montmorillonite and mica dominated in the colloidal-sized particles, of which the smallest particles had the highest proportion of vermiculite and montmorillonite. For a given size fraction, the purple soil had a larger specific surface area, stronger electrostatic field, and higher surface charge than the yellow soil due to differences in mineralogy. Likewise, the differences in surface properties among the various particle-size fractions can also be ascribed to mineralogy. Our results indicated that soil surface properties were essentially determined by the colloidal-sized particles, and the < 0.2 μm nanoparticles made the largest contribution to soil properties. The composition of clay minerals within the diverse particle-size fractions could fully explain the size distributions of surface properties.     

Study of the explosion parameters of vapor–liquid diethyl ether/air mixtures

The knowledge of the vapor–liquid two-phase diethyl ether (DEE)/air mixtures (mist) on the explosion parameters was an important basis of accident prevention. Two sets of vapor–liquid two-phase DEE/air mixtures of various concentrations were obtained with Sauter mean diameters of 12.89 and 22.90 μm. Experiments were conducted on vapor–liquid two-phase DEE/air mixtures of various concentrations at an ignition energy of 40.32 J and at an initial room temperature and pressure of 21 °C and 0.10 MPa, respectively. The effects of the concentration and particle size of DEE on the explosion pressure, the explosion temperature, and the lower and upper flammability limits were analyzed. Finally, a series of experiments was conducted on vapor–liquid two-phase DEE/air mixtures of various concentrations at various ignition energies. The minimum ignition energies were determined, and the results were discussed. The results were also compared against our previous work on the explosion characteristics of vapor–liquid two-phase n-hexane/air mixtures.     

Pollution levels and characteristics of phthalate esters in indoor air of offices

The pollution status and characteristics of PAEs (phthalate esters) were investigated in indoor air of offices, and PAEs of both gas-phase and particulate-phase were detected in all the samples. The concentration (sum of the gas phase and the particulate phase) was 4748.24 ng/m³, ranging between 3070.09 and 6700.14 ng/m³. Diethyl phthalate, dibutyl phthalate, and di(2-ethylhexyl) phthalate were the most abundant compounds, together accounting for 70% of the ∑ 6PAEs. Dividing the particulate-phase PAEs into four size ranges (< 2.5, 2.5–5, 5–10, > 10 μm), the result indicated that PAEs in PM_2.5 were the most abundant, with the proportion of 72.64%. In addition, the PAE concentration in PM_2.5 correlated significantly with the total particulate-phase PAEs (R² = 0.85). Thus, the amount of PAEs in PM_2.5 can be estimated from the total amount of particulate-phase PAEs using this proportion. In a comparison between the offices and a newly decorated study room, it was found that pollution characteristics were similar between these two places. Thus, it is implied that the PAE concentration decreased by 50% 2 yr after decorating.     

Leak location of pipelines based on transient model and PSO-SVM

An improved and integrated approach of support vector machine and particle swarm optimization theory (PSO-SVM) is first used to detect the leak location of pipelines and overcome the problem of multiple leaks. The calibration and predictive ability of improved PSO-SVM is investigated and compared with that of other common method, back-propagation neural network (BPNN). Two conditions are evaluated. One with a leak involves a set of 20 samples, while another with two leaks has 127 samples. Both internal and external validations are performed to validate the performance of the resulting models. The results show that, for the two conditions, the values calculated by improved PSO-SVM are in good agreement with those simulated by transient model, and the performances of improved PSO-SVM models are superior to those of BPNN. This paper provides a new and effective method to inspect the multiple leak locations, and also reveals that improved PSO-SVM can be used as a powerful tool for studying the leak of pipeline.