MIT-World Peace University (MIT-WPU) is a top educational institute located in Pune, India. It is recognized within&nbsp;UGC under Government of Maharashtra Act No. XXXV 2017.&nbsp;

It is part of the MIT group of institutions (established in 1983) which covers 10+ campuses across India and has more than 50,000+ students enrolled across various disciplines at a given point of time. The institute houses 15 schools ranging from Engineering &amp; Technology, Design, Pharmacy, Commerce, Governance among others. It offers undergraduate, postgraduate and PhD programs among different disciplines.&nbsp;

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MIT World Peace University

School of Chemical Engineering

Styrene which is known to be one of the most expensive monomers is conventionally produced by dehydrogenation of ethyl benzene which generates a mixture of benzene, toluene and styrene. The separation of this tertiary mixture is done through two column distillation by first removing benzene from the first column and then separating toluene from styrene in the second column. The conventional distillation system consumes high-energy and yields low purity of toluene.Therefore to overcome these drawbacks we have proposed the use of a Divided Wall Column. In this work, we have designed a Divided wall column (DWC) for styrene production and compared it with the conventional method. By using DWC arrangement we achieved less energy consumption and higher purity of products compared to the conventional method. The simulation of the DWC was done using four column arrangement in Aspen Plus software. The results show that, energy consumed when divided wall column was considered is far less as compared to conventional system used in industry. With the application of DWC column, higher purity toluene was obtained (76.15 % to 96.00 %) and for styrene purity increased from 99.67 % to 99.99 %.

World University root node

Engineering and Technology

Fulltext

International Journal of Science and Research

Optimization of Styrene Production Process using Divided Wall Column

Central receiver system (CRS) is one of the type of concentrated solar power (CSP) technology which consists of heliostat field, receiver and power generation unit. Heliostats are nothing but the mirrors which concentrate solar radiation at one point on receiver which is located at the top of a high tower. Out of the total cost of system heliostat field contributes 50% and leads to about 47% of the annual energy losses. So placing of heliostats in field is most important in order to minimize optical losses and indirectly minimizes energy losses. In this Paper work, heliostat field is designed for no shadowing, blocking losses and optimized cosine efficiency for small field area specifically for Pune location. An algorithm is developed for heliostat distribution in heliostat field as per design using a MATLAB.

School of Mechanical Engineering

International Journal of Current Engineering and Technology

Design of Heliostat Field for Small Scale Central Receiver System

Liquid–liquid equilibrium data for the system consisting of toluene, n-heptane and Aliquat 336 ionic liquid was obtained at 303.15 K and atmospheric pressure. The values of distribution coefficient and selectivity were evaluated. Mathematical model relating distribution coefficient and dispersion, dipolar interaction and hydrogen bonding has been developed. Hansen’s solubility parameters were used to determine the parameters. The model was applied for various ionic liquids as solvents. The model predicted the trends similar to the trend reported in the literature. Thus model can predict better solvent for the given extraction application. This methodology has great potential to act as a knowledge-based framework to aid development of new tailor-made solvents. This will save cost and time in experimentation and analysis.

School of Computer Engineering & Technology

Separation Science and Technology

Extraction of toluene and n- heptane mixture using ionic liquid Aliquat 336 and mathematical modeling for solvent selection

The drag coefficient plays a vital role in the modeling of gas-solid flows. Its knowledge is essential for understanding the momentum exchange between the gas and solid phases of a fluidization system, and correctly predicting the related hydrodynamics. There exists a number of models for predicting the magnitude of the drag coefficient. However, their major limitation is that they predict widely differing drag coefficient values over same parameter ranges. The parameter ranges over which models possess a good drag prediction accuracy are also not specified explicitly. Accordingly, the present investigation employs Geldart’s group B particles fluidization data from various studies covering wide ranges of Re and εs to propose a new unified drag coefficient model. A novel artificial intelligence based formalism namely genetic programming (GP) has been used to obtain this model. It is developed using the pressure drop approach, and its performance has been assessed rigorously for predicting the bed height, pressure drop, and solid volume fraction at different magnitudes of Reynolds number, by simulating a 3D bubbling fluidized bed. The new drag model has been found to possess better prediction accuracy and applicability over a much wider range of Re and εs than a number of existing models. Owing to the superior performance of the new drag model, it has a potential to gainfully replace the existing drag models in predicting the hydrodynamic behavior of fluidized beds.

International Journal of Chemical Reactor Engineering

Genetic Programming based Drag Modelwith Improved Prediction Accuracyfor Fluidization Systems

Background: Personal care and pharmaceuticals products affect the ambient water quality when these materials enter the environment in the form of human and animal excreted metabolites or as effluents from hospitals, pharmacies, and chemical manufacturing facilities. The stated compounds are difficult to capture and pose a serious threat to the aquatic ecosystem, and human health. Photocatalytic Degradation (PCD) is seen to be an attractive and inexpensive method, when compared to the ones such as ozonation, photo-Fenton oxidation, sonolysis, and photolysis for the elimination of pharmaceutical compounds from the wastewater.Methods: Owing to the underlying complex nonlinear physicochemical phenomena, the design and construction of a “first principles” model for predicting the rate constant of the PCD is a timeconsuming and tedious process. To overcome the said difficulty, in this study, the stated mathematical models have been developed-for the first time-using an artificial intelligence (AI) based novel datadriven modeling method, namely, genetic programming (GP). The GP-based model predicting the rate constant of the PCD of pharmaceuticals uses following inputs: time of exposure of pharmaceutical pollutant to the solar radiation, pH of wastewater, concentration degraded during the measured time, and the ratio of concentration degraded to the initial concentration of the sample. In this study, PCD of three pharmaceutical pollutants, namely, Ciprofloxacin, Naproxen, and Paracetamol was studied and modeled using a single GP-based model. In the model’s input space, the three pharmaceutical pollutants were differentiated using a number of attributes related to their molecular structures.Result: The GP-based model predicting the rate constant of the PCD, proposed in this study, exhibits an excellent prediction accuracy [correlation coefficient (CC) > 0.9] and generalization performance.Conclusion The GP-based modeling strategy introduced here can be fruitfully used in the development of models for a variety of other pharmaceutical degradation reactions.

Current Environmental Engineering

Prediction of Rate Constants of Photocatalytic Degradation of PharmaceuticalPollutants by Artificial Intelligence based Genetic ProgrammingFormalism

Hydrodynamic cavitation offers distinct advantages for water disinfection and waste watei treatment particularly at large scales of operations. For applying hydrodynamic cavitation foi water disinfection/treatment, water stream to be treated is passed through a fluidic device ir which there exists a low pressure region. Cavities are generated in this region when the pressurt falls below vapour pressure (in absence of any dissolved gases). These cavities are then collapsec when they travel to regions of higher pressure and lead to very high shear, temperatures anc pressures in localized regions. These high pressure/temperature as well as high shear facilitati disinfection as well as reduction in chemical oxygen demand, colour and amonical nitrogen in the water. In this work, we have investigated hydrodynamic cavitation generated by five difieren orifices have been studied which have different shapes with same fractional open area and have tested their effectiveness for water disinfection. The efficacy of generated cavitation on wate disinfection was quantified based on measurements of non-pathogenic E. coli colony forminj units (CFU/mL). The presented results and analysis will be useful for designing hydrodynamii cavitation based systems for water disinfection.

Pollution Research

Effect of Orifice Shape on Water Disinfection Efficacy

Hydrodynamic cavitation offers distinct advantages for water disinfection and wastewater treatment particularly at large scales of operations. Vortex Diode is a fluidic device, which is conventionally used as a leaky non-return valve in nuclear industry. Recently this device was shown to be effective hydrodynamic cavitation device. In the present study, we have investigated use of cavitation in vortex diode for water disinfection application. Escherichia coli contaminated water is treated successfully using vortex diode. The operating parameters desirable for the disinfection are investigated. The performance is evaluated based on the reduction in the colony forming unit (CFU/mL) of E. coli count estimated by standard spread plate method. The presented results will be useful for identifying appropriate operating conditions for using vortex diode to effectively reduce the bacterial load and disinfect water.

Asian Journal of Chemistry

Disinfection of water using vortex diode as hydrodynamic cavitation reactor

This paper describes the equilibrium, kinetics and process mechanism studies on biosorption of lead ions fromaqueous solution using ‘Aspergillus niger’ in a batch process. The results indicate that biosorption of lead is influencedby various experimental parameters such as initial concentration of lead, amount of biomass used, variation in pH ofsolution and agitation speed. The lead uptake by biomass was quantitatively evaluated using sorption isotherms likeFreundlich and Langmuir isotherm. The results indicate that Langmuir isotherm model describes the present data verywell indicating favorable biosorption. Since the process follows pseudo second order kinetics, the mechanism ofbiosorption of lead by Aspergillus niger can be explained by shrinking core model.

International Journal of Bio-Technology and Research

Parameters influencing biosorption of lead

The orange (specifically, the sweet orange) is the fruit of the citrus species Citrus sinensis in the family rutaceae. Citrus sinensis (orange) fruit is one of the common traditional plants grown in many areas in India. The wastes of the Citrus sinensis (orange) fruit called orange peels were used to prepare activated carbon through chemical activation method. The activated carbon is an excellent adsorbent and its applications are widely described in literature. During adsorption, different elements and their concentration present in the activated carbon play an important role. Therefore, elemental analysis of activated carbon is required. X-ray fluorescence spectroscopy (XRF) was used to determine quantitatively the elements present in activated carbon from Citrus sinensis (orange) peels. The result shows presence of fifteen elements with their concentration.