Study of thermally coupled distillation systems for energy-efficient distillation

Distillation is one of the most widely used separation unit operations in process industries, although it is quite energy intensive. In many cases, the enormous energy requirements for distillation make it economically infeasible to carry out the separation. Thermally coupled distillation system (TCDS) is an advanced distillation method that provides significant energy savings of about 30% as compared with conventional distillation column sequences. The most well-known TCDS sequence, the Petlyuk configuration, has some operational challenges due to bidirectional vapour flow, which makes its implementation difficult in two-column mode. To overcome these limitations, a number of unidirectional vapour flow configurations have been proposed in the literature. The work on simulation analysis for such configurations is limited. In this paper, simulation models for two such configurations are developed, analyzed and compared with the Petlyuk and conventional distillation column sequences for separation of equimolar mixture of benzene–toluene–ethylbenzene.     

Morphology,structural, optical,magnetic, and photocatalytic properties of Co1−xZnxFe2−yCeyO4 NPs

Journal of Materials Science: Materials in Electronics - In the current study, we looked into the effects of simultaneous trivalent Ce and divalent Zn doping on the optical, magnetic, and...     

Queries and materialized views on probabilistic databases

We review in this paper some recent yet fundamental results on evaluating queries over probabilistic databases. While one can see this problem as a special instance of general purpose probabilistic inference, we describe in this paper two key database specific techniques that significantly reduce the complexity of query evaluation on probabilistic databases. The first is the separation of the query and the data: we show here that by doing so, one can identify queries whose data complexity is #P-hard, and queries whose data complexity is in PTIME. The second is the aggressive use of previously computed query results (materialized views): in particular, by rewriting a query in terms of views, one can reduce its complexity from #P-complete to PTIME. We describe a notion of a partial representation for views, and show that, once computed and stored, this partial representation can be used to answer subsequent queries on the probabilistic databases. evaluation.     

Development of FEA-ANN hybrid model for Equivalent Stress prediction of automobile structural member

Chassis serves as a backbone by supporting the body and diverse parts of the automobile. It ought to be sufficiently rigid to endure the shock, twist, vibration and extra stresses. Then, a vital consideration in chassis design is the strength (Equivalent Stress) for sufficient bending stiffness (Deflection). The primary goal of the research is to build up an Artificial Neural Network (ANN) model for identical stress prediction. Two side members joined to a series of cross members to make the chassis frame. The number of cross members and their locations, cross-section and the sizes of the side and the cross members turn into the design variables. The chassis frame model is created in Creo 3.0 and dissected using Ansys. Since, the number of parameters and levels are more, so the probable models are too much. By changing the Parameters, using the orthogonal array the weight of the sidebar is decreased. Then, FEA is performed on those models. ANN model is prepared by using the results of FEA. For training the ANN model, the standard back-propagation algorithm is observed to be the best. A multi-layer perception network is used for non-linear mapping between the input and the output parameters. FEA-ANN hybrid model can save material used, production cost and time.     

Ultrafine-Grained Al-Mg-Sc Alloy via Friction-Stir Processing

Friction-stir processing (FSP) of twin-roll cast (TRC) Al-Mg-Sc alloy resulted into ultrafine-grained microstructure. The alloy was processed in as-received and aged (563 K [290 °C], 22 hours) conditions and at three different tool rotation rates: 800, 400, and 325 rpm. The microstructural features were characterized using electron backscattered diffraction (EBSD), scanning electron microscopy (SEM), and transmission electron microscopy (TEM). The grain size varied from 0.89 μm to 0.39 μm depending on the processing and initial thermo-mechanical conditions of the alloy. The TRC alloy processed at 325 rpm in aged condition had all the grains less than 1 μm, and 95 pct of grains had high-angle grain boundaries (HAGBs). In all the cases, the fraction of HAGBs were more than 80 pct. The variation of misorientation angle distribution was similar to the theoretical MacKenzie distribution for cubic crystal materials. Grain size analysis at different sections and locations on the transverse section of the dynamically recrystallized zone showed a homogeneous and equiaxed microstructure. The average dispersoid (Al₃(Sc,Zr)) size was ~8.0 nm in diameter obtained using high-resolution TEM. Grain size reduction was observed with increase in Zener–Hollomon parameter. It was shown that under the current microstructural and deformation conditions, dynamic recrystallization via particle-stimulated nucleation might not be possible during FSP.     

GenCLOn: An ontology for city logistics

City logistics is a discipline specialized to cope with the sustainability problems encountered in urban freight transport. A key characteristic of it is the heterogeneity of the stakeholders involved. Besides the traditional logistics actors such as shippers, carriers and receivers that share consistent interests (i.e. price and quality), city logistics highly respect the interests of public administrators and citizens that care more about the social welfare. To reach an optimal balance between private and public benefit, it is necessary to understand and in turn forecast the behavior pattern of different groups. In recent years, agent-based modeling has been practiced as an unconventional tool to fulfill this task for its strong capability on capturing the dynamic behavior of individual stakeholders and their interconnections. Referring to other domains (e.g. energy system) where the application of agent-based modeling is relatively mature, a following urgency is to achieve interoperability and in turn reusability between models via introducing formal ontology as a shared template with which developers can standardize their models. This paper introduces an initiative of developing an ontology that formalizes the domain knowledge of city logistics.     

Boron nitride-based electrocatalysts for HER,OER, and ORR: A mini-review

A reliable and efficient solution to the current energy crisis and its associated environmental issues is provided by fuel cells, metal–air batteries and overall water splitting. The heart reactions for these technologies are oxygen reduction reaction (ORR), oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Different supporters such as graphene, carbon nanotube, and graphitic carbon nitride have been used to avoid agglomeration of active materials and provide maximum active surface for these reactions. Among all the supporters, boron nitride (BN) gains extensive research attention due to its analogue with graphene and excellent stability with good oxidation and chemical inertness. In this mini-review, the well-known strategies (exfoliation, annealing, and CVD) used in the synthesis of BN with different morphologies for HER, OER and ORR applications have been briefly debated and summarized. The comparative analysis determines that the performance and stability of state-of-the-art electrocatalysts can be further boosted if they are deposited on BN. It is revealed that BN-based catalysts for HER, OER and ORR are rarely studied yet especially with non-noble transition metals, and this research direction should be studied deeply in future for practical applications.