融合拓扑信息与气象信息的空气质量预测网络

通过空气质量监测数据对正在形成或即将到来的空气污染进行预测是一项具有重要意义的工作,而空气质量监测站只能检测其周围一定范围内的空气污染情况。为了衡量整个城市的空气污染情况,获取任意时间、任意位置的空气质量信息,结合交叉注意力机制,提出了一种融合拓扑信息与气象信息的空气质量预测网络(CGMIM)。将西安市空气质量监测数据与气象数据转换为图像拼接起来,作为输入信息。在高阶非线性时空动态神经网络(MIM)的基础上引入注意力机制,并增加拓扑图编码器模块,提高模型提取能力以及对空气质量监测数据中的空间特征的利用率。最后,使用时空损失函数替代传统的均方误差损失函数,提高模型对空间关系的关注。结果表明：CGMIM网络模型能够在准确预测的同时,对位置区域合理填充,能够有效提升空气质量监测数据的空间分辨率。     

Particulate matter exchange between atmosphere and roads surfaces in urban areas

The deposition and the re-suspension of particulate matter(PM) in urban areas are the key processes that contribute not only to stormwater pollution, but also to air pollution. However, investigation of the deposition and the re-suspension of PM is challenging because of the difficulties in distinguishing between the resuspended and the deposited PM. This study created two Bayesian Networks(BN) models to explore the deposition and the re-suspension of PM as well as the important influential fact...     

利用废旧锌锰电池制备光催化剂净化甲苯

针对废旧锌锰电池回收利用难,以及光催化剂TiO₂活性低的问题,以废旧锌锰电池和商业二氧化钛为原料,通过球磨法制备了新型复合光催化剂。在紫外光灯照射下,进行了废旧锌锰电池复合改性TiO₂对甲苯的光催化氧化实验,并重点探究空速、光照强度、相对湿度和氧气体积分数等关键实验条件对甲苯净化效率的影响。结果表明,改性后的催化剂对甲苯的净化能力大幅提高;当TiO₂与废电池芯粉的质量比为2∶1时,催化剂的催化效果最好,甲苯的净化效率提高了近45%;空速越大,催化剂对甲苯的净化效率越低;净化效率随光照强度的增加呈现先增加后保持不变的规律;催化剂在相对湿度为30%的条件下具有最佳的催化活性,氧气体积分数为15%时为净化效率达到最大。本研究结果可为废旧锌锰电池的回收利用提供新的思路。     

废纸再生过程综合效能评估研究

废纸再生已成为当下解决传统制浆造纸原料匮乏问题的主要途径和趋势,为分析废纸再生过程综合效能水平,提出一种包含多指标的废纸再生综合效能评估模型。从物质流与能量流2个角度对废纸再生过程进行分析,选取5个定量评估指标,构建一套废纸再生综合效能评估指标体系。基于博弈论组合赋权理论,将主、客观权重优化组合得到评估指标最优组合权重,并基于物元模型建立废纸再生综合效能评估模型。通过评估模型对9家企业废纸再生过程进行实例计算,得到各企业综合效能等级,结果显示有2家企业处于高水平,3家企业处于较高水平,4家企业处于差水平。模型计算结果可以体现企业综合效能水平的相对高低和各企业的提升方向。

     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.     

Flotability and flotation separation of polymer materials modulated by wetting agents

The surface free energy, surface tension and contact angles were performed to investigate the properties of wetting agents. Adsorption of wetting agents changes wetting behavior of polymer resins. Flotability of polymer materials modulated by wetting agents was studied, and wetting agents change significantly flotability of polymer materials. The flotability decreases with increasing the concentration of wetting agents, and the wetting ability is lignin sulfonate (LS) > tannic acid (TA) > methylcellulose (MC) > triton X-100 (TX-100) (from strong to weak). There is significant difference in the flotability between polymer resins and plastics due to the presence of additives in the plastics. Flotation separation of two-component and multicomponent plastics was conducted based on the flotability modulated by wetting agents. The two-component mixtures can be efficiently separated using proper wetting agent through simple flotation flowsheet. The multicomponent plastic mixtures can be separated efficiently through multi-stage flotation using TA and LS as wetting agents, and the purity of separated component was above 94%, and the recovery was more than 93%.     

Recycling-oriented characterization of plastic frames and printed circuit boards from mobile phones by electronic and chemical imaging

This study characterizes the composition of plastic frames and printed circuit boards from end-of-life mobile phones. This knowledge may help define an optimal processing strategy for using these items as potential raw materials. Correct handling of such a waste is essential for its further “sustainable” recovery, especially to maximize the extraction of base, rare and precious metals, minimizing the environmental impact of the entire process chain. A combination of electronic and chemical imaging techniques was thus examined, applied and critically evaluated in order to optimize the processing, through the identification and the topological assessment of the materials of interest and their quantitative distribution. To reach this goal, end-of-life mobile phone derived wastes have been systematically characterized adopting both “traditional” (e.g. scanning electronic microscopy combined with microanalysis and Raman spectroscopy) and innovative (e.g. hyperspectral imaging in short wave infrared field) techniques, with reference to frames and printed circuit boards. Results showed as the combination of both the approaches (i.e. traditional and classical) could dramatically improve recycling strategies set up, as well as final products recovery.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

集成膜法水处理工艺的研究与应用

集成膜法除盐系统具有连续产水、出水质量好、易控制、占地少、不需酸碱、利于环保等优点。文章通过对集成膜法水处理技术进行研究与应用,将原有的化学除盐水处理方式改为集成膜法水处理工艺,该方法产水水质高且水质稳定,每年可节约酸碱200 t,阴、阳离子交换树脂10 t,切实解决电厂所面临的产水水质不稳定、酸碱废液排放等问题,有力推动了清洁生产。     

Integration & assessment of recycling into c-Si photovoltaic module’s life cycle

Photovoltaic (PV) energy generation devices have experienced a vigorous growth in production over the last decade in all major industrialised countries. In this research paper, the assessment of recycling and subsequent production of new crystalline silicon (c-Si) PV modules taking advantage of the recovered Si in terms of industrial symbiosis is being examined. With the aid of life cycle analysis method, the potential payback is thoroughly examined through a scenario application in the second useful phase of the PV module. Furthermore, key environmental performance indicators have been implemented in order to evaluate power and resource demands.