Daily Archives: July 24, 2024

Sewage Waste Water Treatment by the Hydrodynamic Cavitation Method
Authors:-Chanchal Valvi, Dr. Pankaj P. Gohil, Dr. Hemangi Desai

Abstract-The sewage water sample obtained after secondary treatment, was given treatment with Hydrodynamic Cavitation Method. Physico chemical parameters were determined using standard methods of APHA, before and after treatment at 24 hour in cavitation device. the water quality obtained is comparable to Drinking Water Standards (IS). The water quality parameters selected were: pH, Electrical Conductivity, Turbidity, TS,TSS, TDS, DO, Cl- ,Alkalinity (as CaCO3), Cu2+ ,Zn2+ ,Mg2+ Hardness, Total Hardness (as CaCO3), Phosphate and BOD. The highest reduction obtained was 88.88% for Cl- . Except TS, TSS and Cu2+ all the parameters were get back in the range of drinking water quality standards. The mechanism supports the reduction in parameter may be due to the collapse of cavities induces effects such as high shear forces, extreme temperatures, shock waves, turbulence, and extreme pressure in the fluid, formation of OHo free radicals provide to reduce pollution. The Cavitation method is proven to be the most effective over the other methods. Because, it does not require any chemical reagent, hence do not produce any hazardous chemical waste and maintain eco-friendly and economically sustainable environment benign technique for the treatment of wastewater.

DOI: 10.61137/ijsret.vol.10.issue3.185

Published by: Kajal Tripathi

Numerical Study of Flow Over NACA 2412 Airfoil at Various AOA’s
Authors:-Nadirge Chandravadan

Abstract-An aerodynamic study was conducted to examine the effect of airflow around the NACA 2412 airfoil using CFD methods. The airfoil’s coordinates were taken from the airfoil database and imported into a geometry modeler. A mesh was created, and simulations were performed using Fluid Flow (Fluent) software. The study involved solving the governing equations (Continuity, Reynolds Averaged Navier-Stokes, and Energy Equation) in 2-D using Fluent. Graphs were made to compare lift (CL) and drag (CD) coefficients at different angles of attack (α). Results showed that lift and drag forces increased with the angle of attack until reaching the stall point. The optimal angle of attack was found to be 8 degrees, where the NACA 2412 airfoil produced the highest lift-to- drag ratio. The critical stall angle was 16 degrees. Beyond this angle, the lift force decreased, indicating stall. The CFD simulation results closely matched the experimental results, indicating that CFD is a reliable alternative for determining drag and lift.

DOI: 10.61137/ijsret.vol.10.issue3.184

Published by: Kajal Tripathi

Authors: Gopichand Talluri

Abstract: Under uncertain conditions, financial decision-making needs methods that combine predictive accuracy, risk management, regulatory requirements, and explainability. Existing financial models, which include both statistical forecasting and conventional machine learning techniques, may fail in terms of describing complex nonlinear market dynamics, quantifying uncertainty in financial decisions, and explaining the effects of financial constraints on decisions. This research presents an ENSC-FI approach to generating financial decisions using a framework consisting of neural learning, symbolic financial rules, uncertainty quantification, and constraint-aware optimization. ENSC-FI seeks to create clear financial decisions using market indicators, risk constraints, budget limitations, and explanation of decisions made. Performance of the proposed framework may be compared to existing traditional machine learning and optimization techniques in terms of return, Sharpe ratio, maximum drawdown, constraint satisfaction rate, and explanation quality. As for an evaluation target of ENSC-FI, the improvement of constraint satisfaction up to 95% and decrease in decision errors by 15% compared to one of the selected baselines will be considered. Those are the targets to be achieved but not actual experimental results yet.

DOI: https://doi.org/10.5281/zenodo.23432144

Published by: vikaspatanker