Experimental Thermal Performance Characterization of Flat Grooved Heat Pipes

ABSTRACT

The thermal characterization of aluminum flat grooved heat pipes is performed experimentally for different groove dimensions. Three heat pipes with groove widths of 0.2?mm, 0.4?mm, and 1.5?mm are used in the experiments. The effect of the amount of the working fluid is extensively studied for each groove width. The results reveal that, although all three succeed in dissipating the heat input through the phase change of the working fluid by continuous evaporation and condensation, the effectiveness of the heat transfer increases with reduced groove width. Furthermore, it is observed that there exists an optimum operating point, where the temperature difference between the heating and cooling sections is at a minimum, and the magnitude of this temperature difference is a strong function of the groove width. To the best of the authors’ knowledge, the combined effects of groove dimensions and the amount of the working fluid, from fully flooded to dry, is reported for the first time for aluminum flat grooved heat pipes.     

Adoption of Technology-Mediated Distance Education: A longitudinal analysis

We investigated the factors that facilitated the fast adoption and utilization of Technology-Mediated Distance Education (TMDE) among higher education institutions. Our analysis was based on a rich data set on the utilization of TMDE between the 1997–1998 and 2000–2001 academic years. The analysis showed that size, public/private status, and location significantly predicted its actual adoption. Being in an urban location negatively affected enrollment in the courses at the undergraduate but not at the graduate level. While the intent to adopt TMDE correlated significantly with actual adoption, many schools that were not interested in TMDE in 1997–1998 adopted it by 2000–2001. Interestingly, late adopters utilized certain technologies as frequently as early adopters, such as synchronous Internet-based instruction and the use of CD-ROMs.     

Assessment of the energy and exergy utilization efficiencies in the Turkish agricultural sector

This study deals with evaluating the energy and exergy utilization efficiencies in the Turkish agricultural sector over a 12‐year period from 1990 to 2001. In the energy and exergy analyses, two main energy sources, namely fuels and electricity, are taken into consideration, while the sectoral energy and exergy efficiencies are compared for this period. These main energy sources include diesel for tractors and other vehicles, and electricity for pumps. Overall energy utilization efficiencies are obtained to vary between 29.1 and 41.1%, while overall exergy utilization efficiencies are found to range from 27.9 to 37.4% in the analysed years, respectively. It may be concluded that the present technique proposed here may be used as a useful tool in analysing and evaluating the energy and exergy utilization efficiencies, identifying energy efficiency and/or energy conservation opportunities and dictating the energy strategies of countries. Copyright © 2005 John Wiley & Sons, Ltd.     

Forecasting based on sectoral energy consumption of GHGs in Turkey and mitigation policies

Recently, global warming and its effects have become one of the most important themes in the world. Under the Kyoto Protocol, the EU has agreed to an 8% reduction in its greenhouse gas (GHG) emissions by 2008–2012. The GHG emissions (total GHG, CO₂, CO, SO₂, NO₂, E (emissions of non-methane volatile organic compounds)) covered by the Protocol are weighted by their global warming potentials (GWPs) and aggregated to give total emissions in CO₂ equivalents. The main subject in this study is to obtain equations by the artificial neural network (ANN) approach to predict the GHGs of Turkey using sectoral energy consumption. The equations obtained are used to determine the future level of the GHG and to take measures to control the share of sectors in total emission. According to ANN results, the maximum mean absolute percentage error (MAPE) was found as 0.147151, 0.066716, 0.181901, 0.105146, 0.124684, and 0.158157 for GHG, SO₂, NO₂, CO, E, and CO₂, respectively, for the training data with Levenberg–Marquardt (LM) algorithm by 8 neurons. R² values are obtained very close to 1. Also, this study proposes mitigation policies for GHGs.     

Development of a suitable model for characterizing photovoltaic arrays with shaded solar cells

The aim of this study is to investigate the effects of non-uniform solar irradiation distribution on energy output of different interconnected configurations in photovoltaic (PV) arrays. In order to find which configuration is less susceptible to mismatch effects, a PV module model is developed. This model can take into consideration the effects of bypass diodes and the variation of the equivalent circuit parameters with respect to operating conditions. The proposed model can provide sufficient degree of precision as well as solar cell-based analysis in analyzing large scale PV arrays without increasing the computational effort. In order to produce more reliable and robust simulations, improved and extended algorithms are presented. Some results are discussed in detail and some recommendations are extracted by testing several shading scenarios.     

Surface modification of polyester and polyamide fabrics by low frequency plasma polymerization of acrylic acid

In this study, the surface characteristics of polyester and polyamide fabrics were changed by plasma polymerization technique utilizing acrylic acid as precursor. This monomer was used to produce hydrophilic materials with extended absorbency. The hydrophilicity, total wrinkle recovery angle (WRA°) and breaking strength of the fabrics were determined prior and after plasma polymerization treatment. The modification of surfaces was carried out at low pressure (<100 Pa) and low temperature (<50°C) plasma conditions. The effects of exposure time and discharge power parameters were optimized by comparing properties of the fabrics before and after plasma polymerization treatments. It was shown that two sides of polyester fabric samples were treated equally and homogeneously in plasma reactor. For polyester fabrics, the minimum wetting time, 0.5 s, was observed at two plasma processing parameters of 10 W–45 min and 10 W–20 min, where untreated fabric has a wetting time of 6 s. For polyester fabrics, the maximum value was obtained at 60 W–5 min with the wrinkle recovery angle of 306° where the untreated fabric has 290°. The optimum plasma conditions for polyamide fabrics were determined as 30 W–45 min where 2 s wetting time was observed. Wrinkle recovery angle of untreated polyamide fabric was 264°. In this study, after plasma polymerization of acrylic acid, wrinkle recovery angle values were increased by 13%. No significant change was observed in breaking strength of both fabrics after plasma treatment. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci 104: 2318–2322, 2007     

Synthesis and properties of chitosan-modified poly(vinyl butyrate)

Modification of chitosan by grafting of vinyl butyrate was carried out in homogeneous phase using potassium persulfate as redox initator and 1.5% acetic acid as solvent. The percent grafting and grafting efficiency were analysed and the high grafting efficiency up to 94% was observed. The effects of reaction variables such as monomer concentration, initiator concentration, temperature and reaction time were investigated. It was observed that the solubility of chitosan was markedly reduced after grafting with vinyl butyrate. The grafted product is insoluble in common organic solvents as well in dilute organic and inorganic acids. Characterization of the graft copolymers were carried out by using Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC) and Scanning Electron Microscopy (SEM) technics. Characteristic signal of carbonyl group was observed at 1,731 cm⁻¹ which belongs to the poly vinyl butyrate segments in the graft copolymer. The melting transition of the chitosan main chain in the copolymer shifted to 124°C from its original value 101°C. In addition to these, we have also studied topology of the graft copolymer and the SEM micrograph showed continuous homogenous matrix which means there is no phase separation.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.