Hydriding and dehydriding properties of MgH2 - x wt. % NiMn9.3Al4.0Co14.1Fe3.6 (x = 10, 25, 50) nanocomposites have been investigated in present work. Doped alloy was prepared by arc melting method ball milled with to get nanocomposites. Onset temperature as low 180 °C observed for MgH2-50 wt% system which is 80°C lower than the as-milled giving 131.34 KJ/mol activation energy. Structural analysis shows tetragonal, orthorhombic monoclinic phases MgH2, Al60Mn11Ni4 Mg2NiH4. Morphology SEM were...

In this paper, to predict the effective thermal conductivity of two-phase systems from value conductivities constituent phases and corresponding volume fractions, a theoretical model is developed by assuming particles be rigid spherical in shape, having regular three-dimensional simple cubic geometry. literature there which are assumed shape same A comparative study made it observed that both models based upon geometry produce deviations experimental results. modification incorporating...

An analysis of the effective continuous media (ECM) approach has been made for prediction thermal conductivity moist porous materials. The validity expression tested different types soils saturated with liquids having variations in liquid content and temperature. A transient method, utilising a line heat source, employed to measure conductivity. comparison between experimental predicted values. model is also on other reported In all cases developed provides close results are compared models...

A transient hot strip method developed by Gustafsson (1979), for simultaneous measurement of thermal conductivity and diffusivity solids fluids with low electrical conductivity, is used the measurements some building materials such as dry dune sand, brick powder, cement, mud powder asbestos at room temperature normal pressure. The works both a plane heat source sensing device. experimental values these are compared those obtained from probe hot-wire methods. good agreement in indicates that...

The present paper deals with the effect of geometry filler particles on effective thermal conductivity for polymer composites. In earlier models, less emphasis has been given shape particles. this paper, expressions derived using law minimal resistance and equal specific equivalent three different shapes i.e. spherical, elliptical hexagonal respectively. Calculated values various samples then compared experimental data available other models developed in literature. results calculated are...

Two semi-empirical approaches for prediction of elastic modulus biphasic composites have been proposed. Developed relations are pore free matrix and filler found to depend on nonlinear contribution volume fraction constituents as well ratio properties individual phases. These applied the calculation effective mainly Al2O3-NiAl, SiC-Al, Alumina-Zirconia, Al-Al2O3, W-glass Flax-Resin composite materials. Theoretical predictions using developed compared with experimental data. It is that...

Two-phase systems are assumed to contain spherical particles arranged in a three-dimensional cubic array. A general expression for porosity correction has been derived diverse two-phase from experimental results reported the literature. The term is found be dependent on ratio of thermal conductivities constituent phases system and gives better agreement predicted effective conductivity values with results.

In this paper, non-linear dependence of volume fraction inclusions on the effective thermal conductivity composite materials is investigated. Proposed approximation formula based Maxwell’s equation, in that a term dependent and ratio conductivities polymer continuum introduced place inclusions. The modified equation used to calculate several agreed well with earlier experimental results. A comparison proposed relation different models has also been made.

Effective thermal conductivities of three-phase systems have been experimentally determined by a differential temperature sensors method. The results are in good agreement with the values predicted geometry-dependent resistor model developed for systems. Reported ETC literature also compared those which show agreement.

This paper presents the applicability of artificial neural networks to predict effective thermal conductivity highly porous metal foams. Artificial network models are based on feedforward backpropagation with training functions such as gradient descent (GD), adaptive learning rate (GDA), momentum (GDM), and (GDX), scaled conjugate (SCG). Volume fraction fluid phase solid phases input parameters for conductivity. The algorithm neurons hidden layers different runs at uniform threshold function...

A well-known Maxwell’s model for evaluation of effective thermal conductivity has been modified incorporating a correction factor s. It is an important quantity, which influences the composite materials together with other parameters like volume fraction and conductivities constituents. Parameter estimation technique used to determine value Optimized s in estimate materials. The using artificial neural network approach also calculated. Materials different sizes filler particles/matrix have...

Silver nanoparticles have received substantial attention for various reasons—like magnetic and optical property, electrical conductivity, catalysis, antimicrobial activities. The use of silver other metal ions their sustained antifungal, antibacterial antiviral effects has also been evaluated. synthesized from wet chemical method are quite often toxic flammable, while green approach the synthesis provides an opportunity large scale production without any conflicting effect. This process is...

In this paper, experimental results on thermal conductivity of TiO₂-Water, TiO₂-Ethylene Glycol and TiO₂-Engine Oil nanofluids in concentration range between 0.25 to 2 volume percent temperature 10–70 °C is presented. Results show that increases with increasing lower enhancement observed as compared concentration. Maximum enhancements are 9.3%, 15% 8.9% for 2% TiO₂ nanoparticles at 70 respectively. 4-input 1-output Artificial Neural Network (ANN) approach used predict nanofluids....

The effective thermal conductivity (ETC) of polymer composites is studied using artificial neural networks. Artificial networks are a form intelligence, which attempt to mimic the function human brain and nervous system. provide great deal promise but they suffer from number shortcomings, such as knowledge extraction, extrapolation, uncertainty. This paper presents use network for prediction ETC metal-filled due their increasing importance in many fields engineering applications...

Mg based nanocomposites containing different concentrations of NiMnAl alloy is studied in present work. Doped was prepared by arc melting and ball milled to get its nano structure. Structural hydrogen desorption properties the composites were examined x-ray diffraction(XRD), differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), electron microscopy energy dispersive (EDX). TGA study showed higher temperature for as-milled MgH2 compared −x wt% NiMnAl. Activation found be...