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.     

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.     

Rooted-tree network for optimal non-local gate implementation

Quantum Information Processing - A general quantum network for implementing non-local control-unitary gates, between remote parties at minimal entanglement cost, is shown to be a rooted-tree...     

Reclamation of nickel from spent nickel catalyst

Spent nickel catalyst containing an average 9.6% nickel was obtained locally from an oil hydrogenation industry. It was digested with 1–3N HCl, HNO₃, H₂SO₄ and mixtures thereof in one to three stages of durations ranging from one to three hr at 100°C using spent nickel catalyst to acid proportions of 1:3 to 1:8 (w/v). Nickel recoveries of over 94% were obtained when one part of spent catalyst was digested for three hr with six or more parts of 3N mixture of HCl and HNO₃ (3:1, v/v). Acid extracts of spent nickel catalyst obtained using HCl, H₂SO₄ and mixtures thereof were treated with NaOCl to convert their content of iron in the ferric form. The iron from the nickel extract was precipitated out in the form of ferric hydroxide at pH 6.0. Nickel from the iron-freed acid extracts was recovered at pH 8.5±0.5 as nickel hydroxide. Nickel formate was prepared by refluxing nickel hydroxide with 10% formic acid in about 6% excess to stoichiometric requirements for 30 min. The dried nickel formate was reduced in peanut oil at 230°C to 270°C for 0.25 to 2.75 hr. The reduction at 260°C on kieselguhr support, employing nickel formate:oil:support in ratio of 50:43:7, for two hr provided catalyst of maximum activity. The hydrogenation activity of the reclaimed catalyst, assessed by standard AOCS procedure, was greater than that of the parent catalyst. Presented at the AOCS Meeting in New Orleans, LA, in May 1987.     

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.     

IS integration and knowledge sharing in multi-unit firms: the winner's curse

Knowledge sharing across business units (BUs) is paramount for enterprises that aim to exploit latent cross-BU synergies. This paper examines how information systems (ISs) integration and two forms of cross-BU knowledge complementarities (workflow interdependence and BU relatedness) affect an important dimension of a firm's absorptive capacity – cross-BU knowledge sharing. The analysis, performed on survey data from 75 enterprises, supports all of our hypotheses. First, we hypothesized that cross-BU workflow serves as a conduit for knowledge transfer as participants continually engage in spontaneous adaptations. Second, IS application integration and cross-BU relatedness should both directly contribute to knowledge sharing. Third, IS application integration should positively moderate the impacts of cross-BU relatedness. Finally, and most interestingly, we hypothesized a redistribution of the effects of IS integration by which it becomes a key contributor to knowledge sharing, but also causes a reduction in the impact of workflow interdependence. Thus, while the seamlessness of high IS application integration has obvious benefits, it paradoxically also reduces the occasions for cross-BU workflow adaptations, which is a key mechanism for knowledge transfer. That is the phenomenon we call the ‘winner's curse’.     

Network Planning for Deep Fading Area at 1.8 GHz LTE Network

Wireless Personal Communications - In the current scenario path loss, coverage and capacity by operating network under fading condition is research challenge. In this paper, signal strength of long...     

A facile route to develop electrical conductivity with minimum possible multi‐wall carbon nanotube (MWCNT) loading in poly(methyl methacrylate)/MWCNT nanocomposites

Today, we stand at the threshold of exploring carbon nanotube (CNT) based conducting polymer nanocomposites as a new paradigm for the next generation multifunctional materials. However, irrespective of the reported methods of composite preparation, the use of CNTs in most polymer matrices to date has been limited by challenges in processing and insufficient dispersability of CNTs without chemical functionalization. Thus, development of an industrially feasible process for preparation of polymer/CNT conducting nanocomposites at very low CNT loading is essential prior to the commercialization of polymer/CNT nanocomposites. Here, we demonstrate a process technology that involves in situ bulk polymerization of methyl methacrylate monomer in the presence of multi‐wall carbon nanotubes (MWCNTs) and commercial poly(methyl methacrylate) (PMMA) beads, for the preparation of PMMA/MWCNT conducting nanocomposites with significantly lower (0.12 wt% MWCNT) percolation threshold than ever reported with unmodified commercial CNTs of similar qualities. Thus, a conductivity of 4.71 × 10^?5 and 2.04 × 10^?3 S cm^?1 was achieved in the PMMA/MWCNT nanocomposites through a homogeneous dispersion of 0.2 and 0.4 wt% CNT, respectively, selectively in the in situ polymerized PMMA region by using 70 wt% PMMA beads during the polymerization. At a constant CNT loading, the conductivity of the composites was increased with increasing weight percentage of PMMA beads, indicating the formation of a more continuous network structure of the CNTs in the PMMA matrix. Scanning and transmission electron microscopy studies revealed the dispersion of MWCNTs selectively in the in situ polymerized PMMA phase of the nanocomposites. Copyright © 2012 Society of Chemical Industry