Comparison of Gross Calorific Value Estimation of Turkish Coals using Regression and Neural Networks Techniques

26th International Mineral Processing Congress, IMPC (2012 : New Delhi; India)Gross calorific value (GCV) of coals was estimated using artificial neural networks, linear and non- linear regression techniques. Proximate and ultimate analysis results were collected for 187 different coal samples. Different input data sets were compared, such as both proximate and ultimate analysis data, and only proximate analysis data and only ultimate analysis data. It was observed that the best results were obtained when both proximate analysis and ultimate analysis results were used for estimating the gross calorific value. When the performance of artificial neural networks and regression analysis techniques were compared, it was observed that both artificial neural networks and regression techniques were promisingly accurate in estimating gross calorific values. In general, most of the models estimated the gross calorific value within ±3% of the expected value

Support Vector Regression and Computational Fluid Dynamics Modeling of Newtonian and Non-Newtonian Fluids in Annulus With Pipe Rotation

The estimation of the pressure losses inside annulus during pipe rotation is one of the main concerns in various engineering professions. Pipe rotation is a considerable parameter affecting pressure losses in annulus during drilling. In this study, pressure losses of Newtonian and non-Newtonian fluids flowing through concentric horizontal annulus are predicted using computational fluid dynamics (CFD) and support vector regression (SVR). SVR and CFD results are compared with experimental data obtained from literature. The comparisons show that CFD model could predict frictional pressure gradient with an average absolute percent error less than 3.48% for Newtonian fluids and 19.5% for non-Newtonian fluids. SVR could predict frictional pressure gradient with an average absolute percent error less than 5.09% for Newtonian fluids and 5.98% for non-Newtonian fluids

Mathematical Modeling of Turbulent Flows of Newtonian Fluids in a Concentric Annulus with Pipe Rotation

In this study, a mathematical model is proposed to predict flow characteristics of Newtonian fluids inside a concentric horizontal annulus. A numerical solution, including pipe rotation, is developed for calculating frictional head losses in concentric annuli for turbulent flow. Navier-Stokes equations are numerically solved using the finite differences technique to obtain the velocity field. Experiments with water are performed in a concentric annulus with and without pipe rotation. Average fluid velocities are varied in the range of 1.1-3.3 m/s at various inner pipe rotations (0120 rpm) in a horizontal concentric annulus. To verify the proposed model, estimated frictional pressure losses are compared with experimental data and the commercial software package ANSYS Workbench 10.0. The numerical model predicts frictional head losses with an error less than +/-10% in most of the test cases