The present work deals with the modeling and optimization of photocatalytic degradation (UV/TiO<sub>2</sub>) of aqueous solution of Acid Red 114 (AR114) dye using Artificial Neural Networks (ANN) and RSM. Photocatalytic treatment of AR114 has been executed using suspension TiO<sub>2</sub>catalyst for commercial applications exposed to ultraviolet irradiation in a shallow pond reactor. ANN optimization has been applied to for predicting the behavior of photocatalysis. The input parameters used for analysis of aqueous dye solution are - TiO<sub>2</sub> dose, pH of the dye solution, initial dye concentration, UV light intensity, time and area/volume, and time whereas the outputs are evaluated in form of degradation and decolorization efficiency of AR114. The outcomes of ANN optimization have been experimentally validated. Results achieved establish ANN modeling as a good predictive model. Parameteric optimization using multi-parameter optimization has been employed with desirability function approach. Results obtained from RSM are in line as per the results of ANN modeling as well as experimental. First order kinetics is use to effectively express degradation and decolorization of AR114 dyes. Total organic carbon (TOC) removal and GC-MS study of the dye shows the total mineralization and formation of non-toxic intermediate products.
A turbo expander also referred as an expansion turbine, is a centrifugal or axial flow turbine through which a high pressure gas is expanded to produce work that is often used to drive a compressor. The low pressure exhaust gas from the turbine is at a very low temperature that is 120K or less depending upon the operating conditions. It is widely used as sources of refrigeration in industrial processes and liquefaction of gases such as oxygen, nitrogen, helium, argon and krypton. A cryogenic system needs many components, compressor, heat exchanger, expansion turbine, instrumentation, vacuum vessel etc. At present most of these process plants operate at medium or low pressure due to its inherent advantages. A basic component which is essential for these processes is the turbo expander. The main aim of this project to attain a minimum temperature and pressure and to study the variation of Mach number and entropy. This is done by computational fluid flow analysis of high speed rotating turbine. This involves with the three dimensional analysis of flow through a radial expansion turbine, using nitrogen as flowing fluid. The work is performed on various modules of Ansys that is BladGen, TurboGrid, CFX-Pre, CFX-Post. Bladegen is used to create the model of turbine using available data of hub, shroud and blade profile. Turbogrid is used to mesh the model. CFX-Pre is used to define the physical parameters of the flow through the Turbo expander. CFX-Post is used for examining and analyzing results. Using these results variation of different thermodynamic properties like Temperature, Pressure, Mach number, entropy etc. inside the turbine can be seen. Several graphs are plotted showing the variation of pressure, temperature, entropy and Mach number along streamline and span wise to analyze the flow through cryogenic turbine.
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