Statistical optimization of operating parameters of microbial electrolysis cell treating dairy industry wastewater using quadratic model to enhance energy generation

The performance of Microbial electrolysis cell (MEC) is affected by several operating conditions. Therefore, in the present study, an optimization study was done to determine the working efficiency of MEC in terms of COD (chemical oxygen demand) removal, hydrogen and current generation. Optimization was carried out using a quadratic mathematical model of response surface methodology (RSM). Thirteen sets of experimental runs were performed to optimize the applied voltage and hydraulic retention time (HRT) of single chambered batch fed MEC operated with dairy industry wastewater. The operating conditions (i.e) an applied voltage of 0.8 V and HRT of 2 days that showed a maximum COD removal response was chosen for further studies. The MEC operated at optimized condition (HRT- 2 days and applied voltage- 0.8 V) showed a COD removal efficiency of 95 ± 2%, hydrogen generation of 32 ± 5 mL/L/d, Power density of 152 mW/cm² and current generation of 19 mA. The results of the study implied that RSM, with its high degree of accuracy can be a reliable tool for optimizing the process of wastewater treatment. Also, dairy industry wastewater can be considered to be a potential source to generate hydrogen and energy through MEC at short HRT.     

Initial and residual trapping of hydrogen and nitrogen in Fontainebleau sandstone using nuclear magnetic resonance core flooding

Hydrogen is among a few promising energy carriers of the future mainly due to its zero-emission combustion nature. It also plays an important role in the transition from fossil fuel to renewable. Hydrogen technology is relatively immature and serious knowledge gaps do exist in its production, transport, storage, and utilization. Although the economical generation of hydrogen to the scale required for such transition is still the biggest technical and environmental challenge, unlocking the large-scale but safe storage is similarly important. It is difficult to store hydrogen in solid and liquid states and storing it in the gaseous phase requires a huge volume which is just available in subsurface porous media. Sandstone is the most abundant and favourable medium for such storage as carbonate rock might not be suitable due to potential geochemical reactions.It is well established in the literature that interaction of the host rock-fluid and injected gas plays a crucial role in fluid flow, residual trapping, withdrawal, and more generally storing capacity. Such data for the hydrogen system is extremely rare and are generally limited to contact angle measurements, while being not representative of the reality of rock-brine-hydrogen interaction(s). Therefore, we have conducted, for the first time, a series of core flooding experiments using Nuclear Magnetic Resonance (NMR) to monitor hydrogen (H₂) and Nitrogen (N₂) gas saturations during the drainage and imbibition stages under pressure and temperature that represent shallow reservoirs. To avoid any geochemical reaction during the test, we selected a clean sandstone core plug of 99.8% quartz (Fontainebleau with a gas porosity of 9.7% and a permeability of 190 mD).Results show significantly low initial and residual H₂ saturations in comparison with N₂, regardless of whether the injection flow rate or capillary number were the same or not. For instance, when the same injection flow rate was used, H₂ saturation during primary drainage was 4% and it was <2% after imbibition. On other hand, N₂ saturation during the primary drainage was 26% and it was 17% after imbibition. However, when the same capillary number of H₂ was utilised for the N₂ experiment, the N₂ saturation values were ～15% for initial gas saturation and 8% for residual gas saturation. Our results promisingly support the idea of hydrogen underground storage; however, we should emphasise that more sandstone rocks of different clay mineralogy should be investigated before reaching a conclusive outcome.     

基于CiteSpace的资源型产业研究知识图谱分析

资源型产业发展为推进国家经济增长和工业化进程提供了重要保障。为深入了解资源型产业的研究情况，以CNKI数据库为数据源，搜集2000—2020年关于资源型产业的核心及以上期刊论文，利用CiteSpace软件从发文作者与研究机构分布、关键词共现网络和时区图谱等方面，绘制知识图谱，进行可视化分析。研究发现：资源型产业领域的研究成果愈加丰富，但研究群体间联系合作较少，且现有的合作研究主要集中在所处地域资源富集和具有学科优势的研究机构及学者；资源型产业领域的研究热点可概括为产业发展、资源型城市、产业集群、产业结构、产业链和产业集聚等方面；针对资源型产业领域未来可从资源型产业相关理论研究、创新发展模式和可持续发展等方面深入展开。     

一种提升AutoForm分析效率的方法

介绍提高AutoForm软件分析效率的两种途径,分别是:针对每个零件制作各自的设置模板文件,通过引用模板文件,减少操作步骤,可节约分析时间15 min,同时将分析文件的存储空间减小到原来的45%左右;针对每个零件建立模面控制线数据库,通过引用控制线数据库,将拉延模面的建立的效率提高了20%,进而提高了整体分析效率。     

产教融合背景下高职特色专业群“平台+模块”课程体系建设研究

In view of the problems in the construction of characteristic professional groups in higher vocational colleges, the professional group of "intelligent manufacturing" is taken as the research object, and the "platform + module" suitable for the development of the industry will be constructed according to the content of the vocational ability planning courses of the post group. The curriculum system establishes the framework of professional groups, and explores and forms a strategic study to optimize and integrate professional group resources.     

中国钢化联产发展现状与前景展望

中国是一个钢铁生产大国,也是一个油气资源相对不足、煤炭资源相对丰富的国家。基于中国能源结构的实际情况,结合钢铁行业和化工行业的发展现状,讨论了钢铁生产各个工序煤气的发生与使用情况,并对钢铁流程副产煤气合成化工产品的现状与潜力进行了分析,指出了存在的问题。结合分析结果,提出了未来可再生能源廉价制氢发展达到一定阶段,钢铁联合企业可以通过“以氢固碳”实现钢铁生产大规模减少CO₂排放的目标,提升其清洁能源转化与高附加值化工产品生产的社会功能。最后,对未来中国钢化联产的发展提出了建议。     

A systematic literature review to explore traceability and lifecycle relationship

Traceability is the ability to follow a product along its lifecycle. It ensures product safety and quality along the supply chain, managing information generated by several players. Even though regulations establish the information that has to be traced, each player generates much more product (and process) information, which could be used to add value to products, with respect to, not only traceability, but also the lifecycle approach. However, the concepts do not appear to be immediately related in scientific panorama. This paper aims to explore the relationship between traceability and lifecycle through a systematic literature review. Six industries (Software, Manufacturing, Automotive, Automation, Aircraft, and Aerospace) and seven subject areas (Software engineering; System engineering; Industry 4.0; New product development; Process management; Data Management; and Environmental sustainability) were identified through bibliometric analysis. To better explore this relationship in the context of the food industry, a content analysis on lead papers’ sample was performed to identify traceability and lifecycle definitions, methodologies and technologies and their relation. The results of the work, synthetised in a proposed research map, will be of interest to those who are approaching the subject for the first time, and for companies involved in product lifecycle management and food traceability.     

Mapping gender and marital roles on customer delight by value perception for mobile technology in India

The Indian telephony industry is a diverse platform for product and service in customer value perception. The present study organizes and synthesizes the varied research streams for developing a customer value delight (CVD) framework for marketing decisions like segmentation and targeting. The conceptual framework is developed by using ten-value predictor variables and customer delight through divergent viewpoints identified from previous studies. The significance of the segregation proposition is tested through discriminant analysis in three different dimension runs i.e. delight, gender, and marital category. The scholarship behind the study provides insight into an imperative issue of segregating customer delight by perceived value predictors in categories. The perceptual mapping and vector magnitude analysis of value predictors were performed to club customers in two categories of Mid-Town (low/moderate delight) and Extremes (high delight). The analysis rigorously supports the discriminating power of perceived price, perceived benefit, and self-congruity. The salience of study unlocks psychographic and demographic perceptual maps of customer delight with its perceived value predictors for strategic and tactful planning in the mobile industry.     

Value stream mapping approach and analytical network process to identify and prioritize production system’s Mudas (case study: natural fibre clothing manufacturing company)

The current research has been done to identify and prioritize the Mudas of the production line of a natural fibre clothing manufacturing company; in this way, value stream mapping has been used to identify the Mudas, then analytical hierarchy method has been used to screen the Mudas. In the first step, necessary information to design value stream of production process has been obtained by observation, measurement and interview; afterward, according to the obtained information and by forming a focus group, Mudas in the production line have been identified and prioritized according to seven categories of Mudas. In order to prioritizing the Mudas by the usage of analytical hierarchy method, the Super Decision software has been applied. Then, according to the obtained priorities, suggested map of the future value system has been drawn and some suggestions have been presented to eliminate Mudas and move towards the lean manufacturing.