基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析

针对呼吸道系统疾病与大气 PM2:5、 SO2 浓度序列的相关性特征, 应用多重分形消除趋势波动分析法 (MF-DCCA), 对张家界市永定区呼吸道系统疾病患病人数与大气 PM2:5、 SO2 浓度序列进行了研究。结果发现该地区 呼吸道系统疾病患病人数与大气 PM2:5、 SO2 浓度的相关性具有长期持续特征和多重分形特征。随后对它们相关性 多重分形特征的动力来源进行了分析, 通过随机重排和相位随机处理, 结果表明在不同时间尺度上的长期持续性影响 是其主要动力来源。进一步研究发现该地区呼吸道系统疾病与大气 PM2:5、 SO2 浓度序列的相关性在四个季节均具 有长期持续性的多重分形特征, 且夏季多重分形特征相对强于其他季节。     

Braking behaviours of C/C–SiC mated with iron/copper-based PM in dry,wet and salt fog conditions

C/C–SiC composites have enormous potential as a new generation of brake materials. It is worth studying the friction and wear behaviours of these materials in special environments to ensure the safe and effective braking of trains in practical applications. In this study, the braking behaviours and wear mechanisms of C/C–SiC mating with iron/copper-based PM in dry, wet and salt fog conditions are compared in detail. The results show that the coefficient of friction (COF) in the wet condition is reduced by 14.13% compared with that under the dry condition. The COF value of the first braking under salt fog condition is increased by 12.27% and 30.75% compared to the dry and wet conditions, respectively. Additionally, the tail warping phenomenon of the braking curve disappears in wet condition, which is attributed to the weak adhesion of friction interfaces and the lubrication of the water film. The main wear mechanisms of C/C–SiC mating with iron/copper-based PM under dry condition are adhesive, fatigue and oxidation wear. However, the dominant wear in wet condition is abrasive wear. The cooling and lubrication of water reduce the tendency of thermal stress, and weaken adhesive and fatigue wear. Furthermore, salt fog can accelerate the corrosion of alloy friction film, leading to the damage of friction film. Meanwhile, the third body particles formed in salt fog condition participate in the braking process. The wear mechanisms in salt fog condition are dominated by abrasive and delamination wear.     

Effect of low-pressure carburizing and plasma nitriding on mechanical properties and fatigue endurance limits of low alloy sintered steels

ABSTRACT

Thermochemical treatments like plasma nitriding or surface carburizing are commonly used to enhance surface hardness of steel components. An important difference between these treatments is the temperature at which they are carried out. In the present paper, the surface carburizing was carried out following a recently reported non-isothermal low pressure carburizing (LPC) treatment. In order to gain a comparative view of the effect of different treatments on the microstructure, microhardness, fatigue and impact properties, materials with distinct hardenability and widely used in the industrial production were evaluated. Tests were also carried out using industrially processed components aimed to an application demanding high wear resistance. The microstructural evolution during case hardening was studied by optical and electron microscopy.     

Mean-stress and oxidation effects on fatigue behaviour of CM 247 DS LC alloy

During present investigations, an attempt was made to understand the effect of mean stress and oxidation on low cycle fatigue (LCF) behaviour of CM 247 DS LC alloy at T?=?850°C. A significant reduction in fatigue life was observed during LCF tests conducted at strain ratio (R) of 0 as compared to R?=??1. Reduction in fatigue life is attributed to the synergistic effect of mean stress, oxidation and the expanding precipitates within the grain boundaries which imparts high stresses at the grain boundary leading to the intergranular cracking. Additionally, to account the effect of mean stress on fatigue life of the alloy CM 247 DS LC empirical relations developed by Smith–Watson–Topper (SWT) and Morrow were used.     

The influence of the processing route on the fragmentation of (Nb,Ti)C stringers and its role on mechanical properties and hydrogen embrittlement of nickel based alloy 718

The nickel-base superalloy 718 is a precipitation hardened alloy widely used in the nuclear fuel assembly of pressurized water reactors (PWR). However, the alloy can experience failure due to hydrogen embrittlement (HE). The processing route can influence the microstructure of the material and, therefore, the HE degree. In particular, the size and distribution of the (Nb,Ti)C particles can be affected by the processing. In this regard, the objective of this work was to analyze the influence of cold and hot deformation processing routes on the development of the microstructure, and the consequences on mechanical properties and hydrogen embrittlement. Tensile samples were hydrogenated through gaseous charging and compared to non-hydrogenated samples. Characterization was performed via scanning and transmission electron microscopies, as well as electron backscattered diffraction. The processing was effective to promote significant variations in average grain size and length fraction of special Σ3ⁿ boundaries, as well as reduction of average (Nb,Ti)C particle size, being these changes more intense for the cold-rolled route. For the mechanical properties, on one side, the cold-rolled route presented the highest increase in ductility for non-hydrogenated samples, while, on the other side, had the highest degree of embrittlement under hydrogen. This dual behavior was attributed to the interaction of hydrogen with the (Nb,Ti)C particles and stringers and its ensuing influence on the fracture processes.     

Effectiveness of portable HEPA air cleaners on reducing indoor PM2.5 and NH3 in an agricultural cohort of children with asthma: A randomized intervention trial

We conducted a randomized trial of portable HEPA air cleaners with pre-filters designed to also reduce NH₃ in non-smoking homes of children age 6-12 with asthma in Yakima Valley (Washington, USA). Participants were recruited through the Yakima Valley Farm Workers Clinic asthma education program. All participants received education on home triggers while intervention families additionally received two HEPA cleaners (child's sleeping area, main living area). Fourteen-day integrated samples of PM_2.5 and NH₃ were measured at baseline and one-year follow-up. We fit ANCOVA models to compare follow-up concentrations in HEPA vs control homes, adjusting for baseline concentrations. Seventy-one households (36 HEPA, 35 control) completed the study. Most were single-family homes, with electric heat and stove, A/C, dogs/cats, and mean (SD) 5.3 (1.8) occupants. In the sleeping area, baseline geometric mean (GSD) PM_2.5 was 10.7 (2.3) μg/m³ (HEPA) vs 11.2 (1.9) μg/m³ (control); in the living area, it was 12.5 (2.3) μg/m³ (HEPA) vs 13.6 (1.9) μg/m³ (control). Baseline sleeping area NH₃ was 62.4 (1.6) μg/m³ (HEPA) vs 65.2 (1.8) μg/m³ (control). At follow-up, HEPA families had 60% (95% CI, 41%-72%; p < .0001) and 42% (19%-58%; p = .002) lower sleeping and living area PM_2.5, respectively, consistent with prior studies. NH₃ reductions were not observed.     

A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.     

哈尔滨典型街谷空间PM2.5分布场与绿色界面指数相关性 研究

在城市化快速进程的背景下，城市 街区PM2.5污染日益严重，本文选取哈尔滨 在不同季节的典型街谷空间，对以叶面积密 度（LA D）、叶面积指数（LAI）为实测要素 的绿色界面指数以及PM2.5浓度进行实测对 比研究。通过对实测数据的分析和挖掘，最 终得出如下结论：首先，典型街谷空间PM2.5 时段浓度呈现上午比下午平均高37.75%，冬 季比夏季高4.7倍的特征；其次，街谷空间的 灌木界面对PM2.5浓度场平均积极贡献率为 18.62%；最后，对PM2.5的衰减率与实测街 谷绿色界面的叶面积密度（LAD）与叶面积 指数（LAI）进行相关性分析，结果显示街谷 绿色界面对PM2.5浓度的衰减作用与叶面积 密度（LAD）呈显著负相关关系，与叶面积指 数（LAI）的相关性程度较弱。     

Wear mechanisms and effects of monolithic Sialon ceramic tools in side milling of superalloy FGH96

FGH96 is one kind of nickel-based superalloy, being widely used in aero engine hot end components due to its superior mechanical properties, while its machinability has been a challenge because of rapid tool wear and low machining efficiency. Recently, ceramic tools have gained widespread attention for their superior performance maintained at high temperatures. This work aims to study the wear mechanisms and the wear effects of monolithic Sialon ceramic tool in the side milling of superalloy FGH96. The specific influences of average flank wear on the side milling forces, machining temperatures, surface quality and micro-hardness of subsurface and the wear modes in the early and serious stage are analyzed. The results indicate that the milling temperatures, machined surface roughness and the depth of hardening layer will increase as the wear increases. While parallel to the cutting direction, the machined surface roughness is about 1.8 μm without significant changes until entering the serious wear stage. The milling force tends to undergo a decrease when the VB is about 0.22 mm, since the temperature is close to the solute temperature of γ’ phase in this stage. The main wear modes of monolithic ceramic tools are adhesive wear and flanking in the flank surface.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.