Safety assessment of the film boiling chemical vapor infiltration (FB-CVI) process through a system-theoretic accident model and process (STAMP)

Film boiling chemical vapor infiltration (FB-CVI) is considered as one of the fastest process methodologies for manufacturing carbon-carbon (C–C) composite products and possesses various advantages compared to conventional methodologies. However, there are safety concerns associated with this process for large-scale manufacturing, mainly owing to the intrinsic nature of the precursor and the process conditions. Considering the multifunctional interactions of the various systems during the process, a system-theoretic process analysis (STPA)/system theoretic accident model and process (STAMP) model is used to perform a safety analysis of the hazardous states of the FB-CVI process at the system level. As a case study, the FB-CVI process equipment employed for the manufacturing of C–C composites is considered. The safety constraints present in the system are assessed for adequacy through a hazard analysis by STPA/STAMP. The analysis through STPA/STAMP demonstrated the capability to create proactive strategies for the design and realization of process equipment that can be employed to manufacture C–C composite products through the FB-CVI process.     

Study on Assessing Economic Vulnerability of Small Island Regions

The main purpose of this study is to assess economic vulnerability of small island development regions as part of their sustainability constraints. By combining economic and environmental time series data, we assessed a composite index of economic vulnerability which is constructed from three exogenous variables, namely economic exposure, economic remoteness, and economic impact of environmental and natural disasters. We used the Amami Islands, Kagoshima Prefecture, Japan as the case studies for this paper.The results indicated that using a gross island products based valuation index, Kikaijima is the most vulnerable island in the Amami Islands with a composite economic vulnerability index (CEVI) value of 0.678, while by using a per capita based index, Okinoerabujima is considered the most vulnerable island with a CEVI value of 0.680. From the results we also revealed that smaller islands have relative higher vulnerability than the bigger one, which also confirms some previous country-level vulnerability studies.However, it is matter of fact that some islands that have relatively high vulnerability also have good economic performance as shown by their per capita income. In this regard, it can be argued that the success of these small islands could have been achieved in spite of and not because of their inherent vulnerability conditions as an indicator of sustainability constraint. Regarding these findings, we also examined a comparison between vulnerability results and the preliminary concept of an island's resilience in order to capture another perspective on sustainability assessment in a small island region.     

包装箱用碳纤维增强复合材料贮存寿命研究

目的研究碳纤维增强复合材料贮存条件下的性能变化趋势和寿命评估。方法对碳纤维增强复合材料开展四个不同温度条件下的热氧老化试验,按试验周期定期取样开展冲击性能测试,对试验数据采用寿命预估方法进行处理,对材料性能进行预估。结果通过数据计算分别得到我国热带海洋、干热沙漠等典型气候条件下的碳纤维增强复合材料贮存寿命分别为17.21~35.89年。结论碳纤维增强复合材料具有较好的贮存性能,在较为严酷的热带海洋气候和给定的失效判据条件下,寿命预计为17.21年。试验和数据处理方法可以较好地预计材料的性能变化趋势和开展寿命评估。     

Pollution prevention at ports: clearing the air

Seaports are major hubs of economic activity and of environmental pollution in coastal urban areas. Due to increasing global trade, transport of goods through ports has been steadily increasing and will likely continue to increase in the future. Evaluating air pollution impacts of ports requires consideration of numerous sources, including marine vessels, trucks, locomotives, and off-road equipment used for moving cargo. The air quality impacts of ports are significant, with particularly large emissions of diesel exhaust, particulate matter, and nitrogen oxides. The health effects of these air pollutants to residents of local communities include asthma, other respiratory diseases, cardiovascular disease, lung cancer, and premature mortality. In children, there are links with asthma, bronchitis, missed school days, and emergency room visits. The significance of these environmental health impacts requires aggressive efforts to mitigate the problem. Approaches to mitigation encompass a range of possibilities from currently available, low-cost approaches, to more significant investments for cleaner air. Examples of the former include restrictions on truck idling and the use of low-sulfur diesel fuel; the latter includes shore-side power for docked ships, and alternative fuels. A precautionary approach to port-related air pollution would encourage local production of goods in order to reduce marine traffic, greener design for new terminals, and state-of-the art approaches to emissions-control that have been successfully demonstrated at ports throughout the world.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

采用钙钛矿型催化剂(La0.8K0.2Cu0.05Mn0.95O3)同时催化去除NOx和碳烟的研究

将钙钛矿型催化剂与碳烟均匀混合后置于固定床连续流动反应体系中,利用程序升温反应技术,在模拟柴油机尾气的情况下对同时催化去除氮氧化物(NOx)和碳烟的反应进行了实验研究.通过改变含Cu原料的用量,得到不同Cu取代量的催化剂La0.8K0.2CuxMn1-xO3,性能评价结果表明,La0.8K0.2Cu0.05Mn0.95O3催化剂的综合性能较好,碳烟的起燃温度及NO向N2的最大转化率分别为280℃和58.0%.采用该催化剂,进一步考察了进气中NO浓度、O2浓度、进气总流量及催化剂与碳烟的接触状况对反应的影响.研究结果表明,进气中NO浓度、O2浓度、气体总流量和催化剂与碳烟之间的接触状况对NO的去除率的影响比较明显,而对碳烟起燃温度的影响较小.O2浓度从5%变为7.5%时,碳烟的起燃温度及最大NO转化率分别从280℃和53.8%变为270℃和96.7%.碳烟与催化剂松散接触时,碳烟的起燃温度及最大NO转化率分别为290℃和48.4%,紧密接触时分别为275℃和70.4%.而进气中NO浓度、气体总流量的变化对碳烟的燃烧基本上没有影响,虽然NO的转化率有明显变化,但生成的N2总量基本不变.     

Synergistic effect of F and triggered oxygen vacancies over F-TiO2 on enhancing NO ozonation

Oxidation-absorption technology is a key step for NO_x removal from low-temperature gas. Under the condition of low O₃ concentration (O₃/NO molar ratio = 0.6), F-TiO₂ (F-TiO₂), which is cheap and environmentally friendly, has been prepared as ozonation catalysts for NO oxidation. Catalytic activity tests performed at 120°C showed that the NO oxidation efficiency of F-TiO₂ samples was higher than that of TiO₂ (about 43.7%), and the NO oxidation efficiency of F-TiO₂-0.15 was the highest, which was 65.3%. Combined with physicochemical characteristics of catalysts and the analysis of active species, it was found that there was a synergistic effect between F sites and oxygen vacancies on F-TiO₂, which could accelerate the transformation of monomolecular O₃ into multi-molecule singlet oxygen (¹O₂), thus promoting the selective oxidation of NO to NO₂. The oxidation reaction of NO on F-TiO₂-0.15 follows the Eley-Rideal mechanism, that is, gaseous NO reacts with adsorbed O₃ and finally form NO₂.     

海水环境下玻璃纤维增强复合材料力学性能演化规律研究

目的 研究海水环境下海流能发电机组叶片用玻璃纤维复合材料力学性能的变化规律.方法 在实验室内通过海水浸泡试验、拉伸试验、弯曲试验以及剪切试验,测定叶片用玻璃纤维树脂基复合材料的吸水特性,以及在人工海水介质中各项力学性能参数的演变规律.结果 随着浸泡时间的增加,玻璃纤维树脂基复合材料吸水率先逐步增大、后趋于稳定,总吸水率约0.075％.抗拉强度呈先降低、后提高、又降低的趋势,抗拉强度最高可超过1100 MPa,最小值约为940 MPa.弹性模量和弯曲强度呈逐渐降低的趋势,弹性模量降幅约9.5％,弯曲强度降幅约为30％.弯曲模量变化起伏不定,变化幅度在15％以内.材料剪切强度呈先增大、后降低的趋势,最小值为189 MPa,较初始值高10 MPa.剪切模量呈先降低、后提高的现象,在浸泡28 d时,剪切模量最小,为16.4 GPa.结论 玻璃纤维增强树脂基复合材料经过长期海水浸泡后,拉伸及抗剪切性能略有降低,但降幅不大,抗弯性能下降明显,需要在叶片结构设计和强度计算时,充分考虑抗弯性能衰减的负面影响.     

镀液循环流量对封闭循环电沉积Ni-SiC复合镀层的影响

目的 研究封闭式镀液循环装置中不同镀液循环流量对Ni-SiC复合镀层的影响规律,优化镀液循环流量参数.方法 以Q235管状工件为待镀基体,以添加SiC颗粒的改良瓦特镀液为母液,在自主研发的封闭式镀液循环电镀装置中以0.3、0.5、0.7 m3/h的镀液循环流量于管件内壁制备Ni-SiC复合镀层,通过SEM检测、XRD测试、硬度测试和摩擦磨损性能测试等手段,对各Ni-SiC复合镀层宏微观形貌、厚度、成分、结构、硬度和耐磨性进行分析研究.结果 在0.5 m3/h流量条件下,镀层厚度为32.98μm,SiC颗粒含量为15.37％,镀层晶粒尺寸和硬度分别为10.84 nm和704HK0.245,该条件下制备的Ni-SiC复合镀层具有最佳耐磨性,摩擦系数为0.41,体积磨损率仅2.83×10–5 mm3/Nm.结论 在不同镀液循环流量参数下,采用该封闭式循环电镀装置,均可制得均匀完整的Ni-SiC复合镀层.随镀液循环流量的升高,镀层厚度和SiC颗粒体积含量均降低,镀层颜色金属光泽增强,镀层晶粒尺寸先减小、后增大,镀层硬度则先升高、后降低.     

氢氧化钠吸收—盐酸萘乙二胺分光光度法测定污染源废气中的氮氧化物

对非稳态工艺废气中氮氧化物的监测 ,目前的监测方法无法获得准确满意的结果 .氢氧化钠吸收—盐酸萘乙二胺分光光度法监测 ,可以延长采样时间 ,扩大测定范围 ,消除了推荐、试行方法中的有关缺陷