Tag: modeling

Recent Articles-IJCSER

Modeling of overall volumetric oxygen transfer by plunging jets of different geometries
Author(s) – Shakti Singh, Surinder Deswal, Mahesh Pal

ABSTRACT
The paper explores the potential of computational techniques in the modeling of overall volumetric oxygen transfer by plunging jets of different geometries, namely circular, square, rectangular and rectangular with rounded edge. The results predicted from neural network, support vector machines and Gaussian process techniques are compared in terms of correlation coefficient, root mean square error and coefficient of determination. The outcome suggests the utility of all these computational techniques in the designing and performance evaluation of plunging jets oxygenation systems of different geometric shapes. However, support vector machines have performed better in comparison to other techniques. It has predicted overall volumetric oxygen transfer coefficient with a correlation coefficient of 0.985, coefficient of determination of 0.968 and root mean square error of 0.002. Further, the scattering (within 15 percent) is lowest in case of support vector machines approach. A comparison of results suggests that support vector machines works well and can be successfully used in modeling oxygen transfer by plunging jets of different geometries and configurations.

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Recent Articles-IJAERD

CFD Modeling and Experimental Validation of Combustion in Direct Ignition Engine Fueled with Diesel

Author(s)-Umakant V. Kongre, Vivek K. Sunnapwar

Abstract
This paper describes the development and use of sub models for combustion analysis in direct injection (DI) diesel engine. In the present study the Computational Fluid dynamics (CFD) code FLUENT is used to model complex combustion phenomenon in compression ignition (CI) engine. The experiments were accomplished on single cylinder and DI engine, with full load condition at constant speed of 1500 rpm. Combustion parameters such as cylinder pressure, rate of pressure rise and heat release rate were obtained from experiment. The numerical modeling is solved by unsteady first order implicit, taking into account the effect of turbulence. For modeling turbulence Renormalization Group Theory (RNG) k- ε model is used. The sub-models such as droplet collision model and Taylor Analogy Breakup (TAB) model are used for spray modeling. The wall-film model is used to assess spray-wall interaction. Modeling in-cylinder combustion, species transport and finite-rate chemistry model is used with simplified chemistry reactions. The results obtained from modeling were compared with experimental investigation. Consequences in terms of pressure, rate of pressure rise and rate of heat release are presented. The rate of pressure rise and heat release rate were calculated from pressure based statistics. The modeling outcome is discussed in detail with combustion parameters. The results presented in this paper demonstrate that, the CFD modeling can be the reliable tool for modeling combustion of internal combustion engine.

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Recent Articles-IJGGS

Integrated analysis of Geophysical Data of Ponnaiyar river basin using Arcview GIS Software

Author(s)– Ruby .D et.al.,

ABSTRACT
A model of aquifer geometry of Ponnaiyar River basin is simulated with in agreeable degree of accuracy.  The Vertical Electrical Sounding (VES) together lithologs forms the data base in the determination of depth, thickness and spatial distribution of overburden, weathered rock, fractured rock and bed rock and the corresponding themes are shown as surface plot, Contours, 3D plot and cross section with the effluent use of GIS packages Arc View. There exist close correspondence between the pattern of drainage and the aquifer dimension. Along the rivers and parts of the foothills region, deep weathered and/ or fracturing is noticed.  Themes of topsoil, weathered rock, deep weathered rock and fractured rock are integrated digitally in order to obtain the places where thickness of all the three are more, thus suitable for artificial recharge (RWS).  The results generated from this research will be of great help in various numerical solutions and GIS analysis pertaining to this basin. The technique of resistivity method proved to be successful where the data analyzed in- group for specific area reveled satisfactory results in characterizing the aquifer geometry, although the utility of this technique for locating water well sites in hard rock areas cost doubt in certain cases.

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Recent Articles-IJCSER

Multi-Objective Design Optimization of Grillage Systems by Scatter Search Methodology
Author(s) – Tugrul Talaslioglu

ABSTRACT
In this study the design of grillage systems is minimized considering both its entire weight and joint displacements. Scatter search methodology as an optimization tool is utilized for design minimization. Scatter search methodology executes its optimization procedures using predefined values of genetic operators. However, this approach causes to an increase in computational cost of optimization procedures. This bottleneck is overcome by dynamically adjusting the parameter values of genetic operators according to values of two performance metrics_ Spread and Inverted Generational Distance (IGD). Furthermore, the flexibility of proposed optimization tool based on scatter search methodology is increased by automatically generating longitudinal-transversal beams of grillage system and correspondingly distributing the loads to the related joints. It is demonstrated that proposed optimization tool has a capability of producing better optimal designations compared to those obtained by a pure usage of scatter search methodology.

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Recent Articles-IJAERD-Artificial Neural Network based Hydro Electric Generation Modelling

Abstract
Hydropower generation is a function of discharge of the generating units and the difference between the fore bay and tailrace levels of the reservoir, and is subject to penstock head losses and to the generation unit efficiency factor, which in turn is a function of the reservoir level and reservoir capacity. For this actual plant data from Sewa Hydroelectric Project Stage-II which is a run-of-the river project having installed capacity of 120 MW situated in Jammu region has been used.In this paper two hydro electric models such as reservoir level versus capacity model and head loss versus water discharge rate have been studied which are used for calculating net head and further can be used for online implementation of Availability Based Tariff in which day ahead scheduling is done. In order to accomplish this task, data from plant is employed for training, validating and testing the artificial neural network (ANN) model which provide accurate results. Thereafter with these models, a comparison is made with multiple regression models in terms of their prediction accuracy, mean square error and regression R value.

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