An experimental study of forced convective heat transfer for fully developed Al 2 O 3 –water nanofluid in an annulus tube

Nanofluids have been known as practical materials to ameliorate heat transfer within diverse industrial systems. The current work presents an empirical study on forced convection effects of Al₂O₃–water nanofluid within an annulus tube. A laminar flow regime has been considered to perform the experiment in high Reynolds number range using several concentrations of nanofluid. Also, the boundary conditions include a constant uniform heat flux applied on the outer shell and an adiabatic condition to the inner tube. Nanofluid particle is visualized with transmission electron microscopy to figure out the nanofluid particles. Additionally, the pressure drop is obtained by measuring the inlet and outlet pressure with respect to the ambient condition. The experimental results showed that adding nanoparticles to the base fluid will increase the heat transfer coefficient (HTC) and average Nusselt number. In addition, by increasing viscosity effects at maximum Reynolds number of 1140 and increasing nanofluid concentration from 1% to 4% (maximum performance at 4%), HTC increases by 18%.     

Kernel Spectral Matched Filter for Hyperspectral Imagery

In this paper a kernel-based nonlinear spectral matched filter is introduced for target detection in hyperspectral imagery, which is implemented by using the ideas in kernel-based learning theory. A spectral matched filter is defined in a feature space of high dimensionality, which is implicitly generated by a nonlinear mapping associated with a kernel function. A kernel version of the matched filter is derived by expressing the spectral matched filter in terms of the vector dot products form and replacing each dot product with a kernel function using the so called kernel trick property of the Mercer kernels. The proposed kernel spectral matched filter is equivalent to a nonlinear matched filter in the original input space, which is capable of generating nonlinear decision boundaries. The kernel version of the linear spectral matched filter is implemented and simulation results on hyperspectral imagery show that the kernel spectral matched filter outperforms the conventional linear matched filter.     

Study of the morphology and mechanical properties of polypropylene composites with silica or rice‐husk

The mechanical, morphological behavior and water absorption characteristics of polypropylene (PP) and silica, or PP and rice‐husk, composites have been studied. The silica used in this study as filler was a commercial type produced from soluble glass or rice husks. The compatibilizing effect of PP grafted with monomethyl itaconate (PP‐g‐MMI) and/or with vinyltriethoxysilane (PP‐g‐VTES) as polar monomers on the mechanical properties and water absorption was also investigated. In general, a high loading of the studied fillers in the polymer matrix increases the stiffness and the water absorption capacity. This effect is more noticeable in the tensile modulus of the PP/silica composite with PP‐g‐VTES as compatibilizer. However, the increase of the rice‐husk charge as a natural filler in the PP matrix decreases the stiffness, and in the presence of PP‐g‐MMI as compatibilizer in PP/rice‐husk, the tensile modulus and water absorption of the composite were improved. The better adhesion and phase continuity in the PP/silica and PP/rice‐husk composites with different compatibilizers was confirmed by the morphological study. Copyright © 2004 Society of Chemical Industry     

Evaporation and Evolution of Suspended Solution Droplets at Atmospheric and Reduced Pressures

Thermal history and solute precipitation behavior of suspended solution droplets of sodium chloride (NaCl), magnesium sulphate (MgSO₄), and zirconium hydroxychloride (ZrO(OH)Cl) evaporating at atmospheric and reduced pressures are studied. Experimental measurements on the variation of droplet diameter, solution concentration, and temperature during the evaporation period are presented and discussed. The results of solute precipitation behavior in solution droplets observed under an optical microscope are displayed and discussed. Results indicate that reducing the pressure (∼ 33 kPa) results in a change in the solution droplet evaporation rate, but the thermal histories of a particular solution droplet are similar at the atmospheric and reduced pressures. At atmospheric and reduced pressures used in this study, the d² law for solution droplets is valid at early stages of the evaporation and before the solute precipitation initiates. Drying of MgSO₄ and ZrO(OH)Cl solution droplets results in the formation of spherical particles, whereas drying of spherical NaCl solution droplets results in the formation of cubic particles.     

Effect of Reactor Ambient Pressure on the Morphology of Spray Dried Magnesium Sulphate Powders

The effect of reducing the reactor air pressure on the morphology of spray dried magnesium sulphate powders is investigated, experimentally. A reactor, capable of drying and pyrolyzing solution sprays at low pressures, is designed and manufactured. A vibrating mesh nebulizer is employed to generate the spray. Four different pressures, starting from 60 Torr to the atmospheric pressure, and two different reactor air temperatures of 130°C and 420°C, are considered. In addition, two different concentrations of magnesium sulphate solutions are tested. The results are explained based on the effect of reactor air pressure on the droplet evaporation rate.     

A basic program for calculating subsurface water temperatures using chemical geothermometers-implication to geothermal reservoir estimation

GEOTHERM is a computer program written in BASIC language to estimate geothermal reservoir temperature using the well-known chemical gèothermometers. The empirical equations used in the program were obtained from the literature. Three different chemical geothermometers are included in the program: Na-K, Na-K-Ca, and silica geothermometers; this gives the user the opportunity not only to select the most reliable geothermometer in estimating subsurface temperature, but also to select the type of geothermometer according to available data. A sample input file of geothermal waters obtained from Iceland has been tested, so as to show the applicability and usefulness of the program.     

Strength evaluation of granite block samples with different predictive models

Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (V_p) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R²) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.

     

Influence of grafted polypropylene on the mechanical properties of mineral‐filled polypropylene composites

The purpose of this work was to study how mineral fillers would behave in a polypropylene (PP) matrix when PP modified with maleic anhydride (MA) and/or itaconic acid (IA) was used as a coupling agent in the preparation of mineral‐filled PP composites. The composites were characterized with tensile mechanical measurements and morphological analysis. The optimum amount of the coupling agent to be used to obtain composites with improved mechanical properties was established. The results indicated that these coupling agents enhanced the tensile strength of the composites significantly, and the extent of the coupling effect depended on the nature of the interface that formed. The incorporation of coupling agents enhanced the resistance to deformation of the composite. The behavior of IA‐modified PP as a coupling agent was similar to that of a commercial MA‐modified PP for the filled PP composites. Evidence of improved interfacial bonding was revealed by scanning electron microscopy studies, which examined the surfaces of fractured tensile test specimens; their microstructures confirmed the mechanical results with respect to the observed homogeneous or optimized dispersion of the mineral‐filler phase in these composites. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 2343–2350, 2007