SULFUR RECOVERY WITH REDUCED EMISSIONS, LOW CAPITAL INVESTMENT AND HYDROGEN CO-PRODUCTION

The main disadvantage of the Claus process is that by introducing air as oxidant a large volume of tail gas is produced. This must be treated to reduce atmospheric emissions of sulfur-containing gases. The costs of the tail-gas unit are a significant fraction of the total capital and operating costs for sulfur recovery. A new process uses thermal decomposition of hydrogen sulfide in the presence of carbon dioxide instead of air oxidation. The products of this reaction are hydrogen, carbon monoxide, elemental sulfur, water vapor and carbonyl sulfide. Carbonyl sulfide is easily converted to H₂S and C0₂ by liquid- or vapor-phase hydrolysis. Unreacted H₂S and C0₂ are recovered by absorption and recycled to the reactor. Since no air is introduced, there is no tail gas and the tail-gas unit is eliminated, giving a substantial reduction in capital investment. The concentrations of sulfur-containing gases in the product streams depend only on the operation of the absorber and stripper units and can be controlled to very low levels by increasing stripper boil-up. Process operating costs depend on the level of sulfur recovery required and can also be much lower than those of the modified Claus Process.

The process chemistry depends on a shift in the equilibrium of H₂S decomposition caused by reaction of hydrogen with C0₂ by the reverse of the water-gas-shift reaction. Catalysts for this chemistry have been identified. Reactor conversion is further improved by rapid cooling of the reactor effluent gas. Other aspects of process design and operation confer further advantages with respect to the Claus process; however, the process equipment used is similar to that used in a Claus plant. Retrofit of existing plant to the new technology can therefore be considered.     

The psychological functions of avatars and alt(s): A qualitative study

Prior research has shown that approximately 50% of active participants in the 3D virtual world of Second Life have one or more secondary avatars or “alts” in addition to their primary avatar. Thus, these individuals are operating a “multiple or poly-identity system” composed of a physical self, a primary avatar, and one or more alts. However, little is known about the functions these virtual identities serve for the virtual-world user. The current study involved qualitative analysis of semistructured interviews with Second Life participants (N = 24) who had a primary avatar and at least one alt. Interviews were coded to examine the functions that primary avatars and alts served. Eight functions—seven suggested by previous research on virtual world identity and one that emerged from analyses—were reflected in a large majority of the transcribed interviews and are described in the article. The current findings add to our understanding of how multifaceted identity systems operate, as more individuals augment their physical self with a set of virtual identities.     

疲劳与蠕变复合作用下PS的应变与寿命

对PS在疲劳/蠕变复合作用下应变与寿命进行了研究。结果表明：其疲劳/蠕变曲线与纯蠕变曲线十分相似。加载时间周期越短和疲劳载荷变化越频繁。结束普弹应变阶段应变越小，进入延迟弹性变形的平台应变阶段越早。在疲劳/蠕变复合作用下聚苯乙烯存在疲劳和蠕变的交互损伤，其断裂寿命比纯疲劳或纯蠕变的断裂寿命低。断裂寿命减小，疲劳/蠕变的交互损伤程度与温度密切相关，PS在较低温度的疲劳/蠕变交互损伤作用大于较高温度的交互损伤作用。随温度升高，疲劳/蠕变断裂寿命下降是疲劳和蠕变各自的单独损伤增加所致。     

A robust optimization approach for pollution routing problem with pickup and delivery under uncertainty

Organizations have recently become interested in applying new approaches to reduce fuel consumptions, aiming at decreasing green house gases emission due to their harmful effects on environment and human health; however, the large difference between practical and theoretical experiments grows the concern about significant changes in the transportation environment, including fuel consumptions, carbon dioxide (CO₂) emissions cost and vehicles velocity, that it encourages researchers to design a near-reality and robust pollution routing problem. This paper addresses a new time window pickup-delivery pollution routing problem (TWPDPRP) to deal with uncertain input data for the first time in the literature. For this purpose, a new mixed integer linear programming (MILP) approach is presented under uncertainty by taking green house emissions into consideration. The objective of the model is to minimize not only the travel distance and number of available vehicles along with the capacity and aggregated route duration restrictions but also the amount of fuel consumptions and green house emissions along with their total costs. Moreover, a robust counterpart of the MILP is introduced by applying the recent robust optimization theory. Computational results for several test problems indicate the capability and suitability of the presented MILP model in saving costs and reducing green house gases concurrently for the TWPDPRP problem. Finally, both deterministic and robust mathematical programming are compared and contrasted by a number of nominal and realizations under these test problems to judge the robustness of the solution achieved by the presented robust optimization model.     

影响裂解汽油二段加氢催化剂长周期运转因素及解决措施

从裂解汽油二段加氢催化剂性能、裂解汽油和操作条件等方面论述了影响该催化剂长周期运转的因素,并针对这些因素提出相应的措施,以达到延长催化剂运转周期的目的。     

Sub-ambient cold-start emissions reduction using SwRI® PO x catalyst technology

This paper describes the application of SwRI’s cold-start PO _x catalyst technology to reduce cold-start hydrocarbon emissions from a US Tier 2 vehicle at −7 °C. A reduction in −7 °C (20 °F) cold-start hydrocarbons will help US Tier 2 vehicles meet the proposed EPA NMOG standards. Improvements in cold temperature hydrocarbon emissions would also be beneficial in many parts of Europe during the winter months. In this work, a total hydrocarbon reduction of 19% was realized at 24 °C, in line with previous results, but only up to 3% at −7 °C. Insufficient oxygen in the engine-out exhaust gas at −7 °C was determined to be the reason why the PO _x catalyst failed to significantly reduce HC emissions. Addition of supplemental oxygen to the exhaust during the cold-start, to simulate an adjustment in the engine calibration to less rich operation, resulted in a total hydrocarbon reduction of 18% with the PO _x catalysts in place, but no benefit when the PO _x catalysts were removed. Hence, the PO _x catalyst approach can be used to good effect, even under sub-ambient cold-start conditions.     

一种无线传感器网络中自主选择簇头的聚类算法

在无线传感网络中,传感器节点要定期向基站发送收集的数据。为了支持数据汇总,通过高效的网络组织将节点划分成若干簇。在这种类型的系统中,随着簇头的轮转,每个簇中的簇头选择方法是最具有挑战性的问题,有效的簇头选择算法可以提高网络的续航时间,并减少在WSN中的节点之间的通信开销。提出一个簇内民主方式选举算法来选择簇中的节点作为簇头,用MatLab对算法进行仿真,证明该算法的性能可以有效改善网络的性能。     

Field Validation of DNDC Model for Methane and Nitrous Oxide Emissions from Rice-based Production Systems of India

The DNDC (DeNitrification and DeComposition) model was tested against experimental data on CH₄ and N₂O emissions from rice fields at different geographical locations in India. There was a good agreement between the simulated and observed values of CH₄ and N₂O emissions. The difference between observed and simulated CH₄ emissions in all sites ranged from −11.6 to 62.5 kg C ha⁻¹ season⁻¹. Most discrepancies between simulated and observed seasonal fluxes were less than 20% of the field estimate of the seasonal flux. The relative deviation between observed and simulated cumulative N₂O emissions ranged from −237.8 to 28.6%. However, some discrepancies existed between observed and simulated seasonal patterns of CH₄ and N₂O emissions. The model simulated zero N₂O emissions from continuously flooded rice fields and poorly simulated CH₄ emissions from Allahabad site. For all other simulated cases, the model satisfactorily simulated the seasonal variations in greenhouse gas emission from paddy fields with different land management. The model also simulated the C and N balances in all the sites, including other gas fluxes, viz. CO₂, NO, NO₂, N₂ and NH₃ emissions. Sensitivity tests for CH₄ indicate that soil texture and pH significantly influenced the CH₄ emission. Changes in organic C content had a moderate influence on CH₄ emission on these sites. Introducing the mid-season drainage reduced CH₄ emissions significantly. Process-based biogeochemical modeling, as with DNDC, can help in identifying strategies for optimizing resource use, increasing productivity, closing yield gaps and reducing adverse environmental impacts.     

贫燃条件下汽车尾气净化催化技术的发展与展望

本文介绍了用于贫燃发动机尾气，柴油机尾气净化催化技术的发展状况，对各种催化剂及其载体材料的性能进行了比较，提出了开发贫燃条件汽车尾气净化催化技术尚需解决的问题。     

NEURAL-NETWORK-AIDED DESIGN OF AUTOMOBILE EXHAUST CATALYSTS

A priori design of catalysts is not yet possible. Such task would demand unavailable scientific knowledge of the correlations among synthesis parameters and resulting solid state and surface structures, on the one hand, and among those atomic-level structural details and their catalytic functions, on the other hand. To avoid testing every possible combination, therefore, the applied chemist or chemical engineer must identify empirical correlations underlying the existing experimental data base.

The ability of artificial neural networks to identify complex correlations and to predict the result of experiments has recently generated considerable interest in various areas of science and engineering. In this paper, neural networks are used to identify composition-performance relationships in automobile exhaust catalysts.

This work employs an artificial neural network technique to do a sensitivity analysis of the conversions of pollutant gases as a function of the catalyst composition and the operating conditions. This approach converges on the optimum catalyst composition and operating condition in order to produce specified conversions of carbon monoxide, hydrocarbons and nitrogen oxides, to carbon dioxide, water and di-nitrogen respectively.