research centers


Search results: Found 2

Listing 1 - 2 of 2
Sort by

Article
Numerical Simulation of Natural Convection in a Square Cavity Utilizing Nanofluid and Subjected to Air Stream Cooling

Author: Khalid B. Saleem خالد بكر سليم
Journal: Basrah Journal for Engineering Science مجلة البصرة للعلوم الهندسية ISSN: Print: 18146120; Online: 23118385 Year: 2018 Volume: 18 Issue: 2 Pages: 15-25
Publisher: Basrah University جامعة البصرة

Loading...
Loading...
Abstract

In the present paper the natural convection in a squarecavity utilizing Cu-water nanofluid is examined numerically.The cavity is exposed to cooling air stream with free streamtemperature (T∞) from left wall and its right and bottom wallskept with cold and hot temperatures (TC) and (TH) respectively,while the cavity top wall considered as adiabatic. The nanofluidflow inside the cavity is assumed to be laminar and obeying toBoussinesq approximation. The governing equations are solvedby finite volume method using ANSYS FLUENT code. Theresults are accomplished with a range of nanofluid volumefraction =0–0.16, Rayleigh number Ra=103–105 and freestream Reynolds number Re∞=103–104. The effects of thesevariables are displayed on the stream function (), isotherms ()contours and average Nusselt number (Nuavg). The results showthe heat transfer rate augmented with increasing , Ra and Re∞.Also, the increment in both  and Ra increases the circulationinside the cavity while increasing Re∞ produces secondaryvortices and reduces circulation at the main vortex of the cavity.The results of local Nusselt number (Nu) and isotherms () arecompared with other studies and show good agreement withmaximum error values 14.28% and 3.2% respectively.


Article
PREDICTION OF HEAT TRANSFER CHARACTERISTICS FOR FORCED CONVECTION PIPE FLOW USING ARTIFICIAL NEURAL NETWORKS

Authors: Khalid B. Saleem --- Imad A. Kheioon --- Hussien S. Sultan
Journal: KUFA JOURNAL OF ENGINEERING مجلة الكوفة الهندسية ISSN: 25230018 Year: 2019 Volume: 10 Issue: 3 Pages: 73-89
Publisher: University of Kufa جامعة الكوفة

Loading...
Loading...
Abstract

This paper investigates the ability of utilizing the artificial neural network (ANN) in calculating the forced convection characteristics coefficients from internal flow of air inside a pipe subjected to constant heat flux. The heat transfer characteristics such as Nusselt number (Nu), Stanton number (St) and friction factor (f) which are calculated using the empirical correlations have high deviation from that obtained from the experiments. So, the ANN method is proposed for predicting these characteristics coefficients more close to the experimental results. The training and testing data for optimizing the ANN structure are based on the experimental data obtained from the experiments performed on a forced convection apparatus. Three training algorithms for the training of the ANN were used and the presented ANN is implemented by using such MATLAB program. For the preferable ANN structure acquired in the current work, an acceptable mean square error was achieved for the training and test data, using the Trainlm algorithm. The results reveal that the estimated results are very close to the experimental data. Also, a new Graphical User Interface (GUI) is implemented for the application of ANN in the calculation of the attempted heat transfer parameters.

Listing 1 - 2 of 2
Sort by
Narrow your search

Resource type

article (2)


Language

English (2)


Year
From To Submit

2019 (1)

2018 (1)