Comparison of co-current and counter-current flow in a bifunctional reactor containing ammonia synthesis and 2-butanol dehydrogenation to MEK

In this study, a multi-tubular thermally coupled packed bed reactor in which simultaneous production of ammonia and methyl ethyl ketone (MEK) takes place is simulated. The simulation results are presented in two co-current and counter-current flow modes. Based on this new configuration, the released heat from the ammonia synthesis reaction as an extremely exothermic reaction in the inner tube is employed to supply the required heat for the endothermic 2-butanol dehydrogenation reaction in the outer tube. On the other hand, MEK and hydrogen are produced by the dehydrogenation reaction of 2-butanol in the endothermic side, and the produced hydrogen is used to supply a part of the ammonia synthesis feed in the exothermic side. Thus, 30.72% and 31.88% of the required hydrogen for the ammonia synthesis are provided by the dehydrogenation reaction in the co-current and counter-current configurations, respectively. Also, according to the thermal coupling, the required cooler and furnace for the ammonia synthesis and 2-butanol dehydrogenation conventional plants are eliminated, respectively. As a result, operational costs, energy consumption and furnace emissions are considerably decreased. Finally, a sensitivity analysis and optimization are applied to study the effect of the main process parameters variation on the system performance and obtain the minimum hydrogen make-up flow rate, respectively.     

Numerical study of entropy generation in Darcy-Forchheimer (D-F) Bödewadt flow of CNTs

Three-dimensional Bödewadt flow (fluid rotates at a large enough distance from the stationary plate) of carbon nanomaterial is examined. Single walled and multi walled CNTs are dissolved in water and gasoline oil baseliquids. Darcy-Forchheimer porous medium is considered. Stationary disk is further stretched linearly in radial direction. Heat transfer effect is examined in presence of radiation and convection. Effect of viscous dissipation is accounted. Entropy generation rate is studied. By using adequate transformation (von Kármán relations), the flow field equations (PDEs) are transmitted into ODEs. Solutions to these ODEs are constructed via implementation of shooting method (bvp4c). In addition to Entropy generation rate, Bejan number, heat transfer rate (Nusselt number), skin friction and temperature of fluid are examined through involved physical parameters. Axial component of velocity intensifies with increment in nanoparticles volume fraction and ratio of stretching rate to angular velocity parameter while it decays with higher porosity parameter. Higher nanoparticles volume fraction and porosity parameter lead to decay in radial as well as tangential component of velocity. However it enhances with higher ratio of stretching rate to angular velocity parameter. Temperature of fluid directly varies with higher ratio of stretching rate to angular velocity parameter, radiation parameter, Eckert number, Biot number and nanoparticles volume fraction. Rate of Entropy generation is reduced with higher estimations of porosity parameter, nanoparticles volume fraction and radiation parameter. Skin friction coefficient decays with higher porosity parameter and ratio of stretching rate to angular velocity parameter. Intensification in porosity parameter, nanoparticles volume fraction and Biot number leads to higher Nusselt number. Prominent impact is shown by multiple-walled CNTs with gasoline oil basefluid than single-walled CNTs with water basefluid.     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS₂ nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ sites, the fabricated 1T–MoS₂ QS/Ni(OH)₂ hybrid (quantum sized 1T–MoS₂ sheets decorated with Ni(OH)₂ via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm^?2, respectively, and has a low Tafel slope of 30 mV dec^?1 in 1 m KOH. So far, this is the best performance for MoS₂‐based electrocatalysts and the 1T–MoS₂ QS/Ni(OH)₂ hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm^?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.     

Impact of shape representation schemes used in discrete element modelling of particle packing

In different computer models, shape is represented using different methodologies, to varying degrees of precision. This paper examines two approaches to shape representation, and their effects on accuracy in the context of cylindrical particle packing. Two discrete element method (DEM) based software packages are used. A X-ray CT scan of a packed bed provides the experimental measurements for comparison. Eight sphere-composite representations of the same cylindrical pellet were tested. Two of these gave results that quantitatively follow experimental measurements. A range of factors that in theory could affect accuracy of the simulation results are examined, including edge roundedness, surface roughness and restitutional behaviour as a function of sphere-composite representations. The conclusion is that, for packing at least, matching the object's overall shape and dimensions is not enough. Only when a high enough resolution is applied to corners and edges, could the sphere-composite approach possibly match the experimental data quantitatively.     

Annual and regional variations of aflatoxin B1 levels seen in grains and feed coming from Croatian dairy farms over a 5-year period

The aim of the study was to investigate annual and regional differences in the level of aflatoxin B₁ (AFB₁) in grains and dairy cattle feed. Maize (n = 972), wheat (n = 201), barley (n = 147), oat (n = 136), grain mixtures (n = 168), and dairy cattle feed (n = 325) were sampled from 2009 to 2013 on different farms and in different farm factories situated in four Croatian regions. The samples were analysed for AFB₁ using the validated ELISA immunoassay. AFB₁ was determined in 16.4% of all investigated samples, among which maize was proven to be the most contaminated, with 21.7% of the samples recovered during 2013 harbouring AFB₁ in concentrations over the permissible ones. Levels higher than permitted were observed in 17.9% and 12.3% of grain mixtures and dairy cattle feed, respectively, whereas concentrations of AFB₁ determined in other crops throughout the investigated period met the stipulated requirements. The results revealed the AFB₁ occurrence to be significantly (p < 0.05) dependent on the cultivation region, with the highest levels generally found in maize harvested in 2013 and consequently in grain mixtures and cattle feed that can most likely be associated with climatic conditions as the most critical factor for mould formation, and thus also AFB₁ production.     

仙游抽水蓄能电站尾水系统充排水试验

为检查工程质量,查找输水系统可能存在的问题并消除隐患,保障电站安全运行,福建仙游抽水蓄能电站在投产发电前,要对输水发电系统进行充水试验与放空排水试验,在试验过程中监测输水系统的应力、应变与渗漏水情况。本文以尾水系统为例,介绍了试验所应具备的工程条件、工作程序及技术要求、试验成果分析和存在问题处理等。试验表明,仙游抽水蓄能电站尾水系统设计合理,施工质量优良,结构可靠,可供同类工程参考与借鉴。     

高温氢工质热物理性质计算分析

氢工质在新能源与动力、航天推进、化工材料等领域有着广泛应用。通过开展高温氢工质热力学与输运性质研究，建立了原子态氢、分子态氢、热解平衡态氢的热物理性质计算模型，开发了热物性计算程序Prop_H_H2，适用范围为温度100~3 500 K、压力104~5×107 Pa 。验证表明，Prop_H_H2在适用范围内计算氢工质的物性参数合理可靠，在温度200~3 000 K、压力104~107 Pa范围内，程序预测值更加准确，相对偏差在±5%左右。本研究可为氢工质相关的航天推进、应用物理学、能源动力等行业的科研和应用提供支持借鉴。     

Sensor network design based on system-wide reliability criteria. Part I: Objectives

Reliability based criteria are quite popular for optimal sensor network design. We present a modified definition of system reliability for sensor network design for two applications: reliable estimation of variables in a steady state linear flow process, and reliable fault detection and diagnosis for any process. Unlike the weakest-link based definition of system reliability in the literature, the proposed definition considers the entire system and is consistent with the reliability concept used in classical reliability literature. For each application, dual approaches for defining system reliability are proposed, and their analogy with the reliability problem in the classical reliability literature is established. Using examples and stochastic simulations, the advantage of using the proposed system reliability in contrast to the existing definition is illustrated. Part II of this series of articles presents methods for efficient generation of the system reliability function and its use in optimization-based approaches for designing optimal sensor networks.     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.