Constant wall heat flux boundary conditions in micro-channels filled with porous material with internal heat generation under local thermal non-equilibrium conditions

Forced convection heat transfer in a micro-channel filled with a porous material saturated with rarefied gas with internal heat generation is studied analytically in this work. The study is performed by analysing the boundary conditions for constant wall heat flux under local thermal non-equilibrium (LTNE) conditions. Invoking the velocity slip and temperature jump, the thermal behaviour of the porous-fluid system is studied by considering thermally and hydrodynamically fully-developed conditions. The flow inside the porous material is modelled by the Darcy–Brinkman equation. Exact solutions are obtained for both the fluid and solid temperature distributions for two primary approaches models A and B using constant wall heat flux boundary conditions. The temperature distributions and Nusselt numbers for models A and B are compared, and the limiting cases resulting in the convergence or divergence of the two models are also discussed. The effects of pertinent parameters such as fluid to solid effective thermal conductivity ratio, Biot number, Darcy number, velocity slip and temperature jump coefficients, and fluid and solid internal heat generations are also discussed. The results indicate that the Nusselt number decreases with the increase of thermal conductivity ratio for both models. This contrasts results from previous studies which for model A reported that the Nusselt number increases with the increase of thermal conductivity ratio. The Biot number and thermal conductivity ratio are found to have substantial effects on the role of temperature jump coefficient in controlling the Nusselt number for models A and B. The Nusselt numbers calculated using model A change drastically with the variation of solid internal heat generation. In contrast, the Nusselt numbers obtained for model B show a weak dependency on the variation of internal heat generation. The velocity slip coefficient has no noticeable effect on the Nusselt numbers for both models. The difference between the Nusselt numbers calculated using the two models decreases with an increase of the temperature jump coefficient.

Temperature fields in a channel partially filled with a porous material under local thermal non-equilibrium condition-an exact solution

This work examines analytically the forced convection in a channel partially filled with a porous material and subjected to constant wall heat flux. The Darcy–Brinkman–Forchheimer model is used to represent the fluid transport through the porous material. The local thermal non-equilibrium, two-equation model is further employed as the solid and fluid heat transport equations. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions, for the solid and fluid temperature fields, are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio and Darcy number as parameters. The results can be readily used to validate numerical simulations. They are, further, applicable to the analysis of enhanced heat transfer, using porous materials, in heat exchangers.

Use of a Neural Network to Predict Strength and Optimum Compositions of Natural Alumina-Silica-Based Geopolymers

In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.


Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829

Development of Metal–Organic Frameworks for Catalysis : Designing Functional and Porous Crystals

Metal–organic frameworks, or MOFs, have emerged as a new class of porous materials made by linking metal and organic units. The easy preparation, structural and functional tunability, ultrahigh porosity, and enormous surface areas of MOFs have led to them becoming one of the fastest growing fields in chemistry. MOFs have potential applications in numerous areas such as clean energy, adsorption and separation processes, biomedicine, and sensing. One of the most promising areas of research with MOFs is heterogeneous catalysis. This thesis describes the design and synthesis of new, carboxylate-based MOFs for use as catalysts. These materials have been characterized using diffraction, spectroscopy, adsorption, and imaging techniques. The thesis has focused on preparing highly-stable MOFs for catalysis, using post-synthetic methods to modify the properties of these crystals, and applying a combination of characterization techniques to probe these complex materials. In the first part of this thesis, several new vanadium MOFs have been presented. The synthesis of MIL-88B(V), MIL-101(V), and MIL-47 were studied using ex situ techniques to gain insight into the synthesis–structure relationships. The properties of these materials have also been studied. In the second part, the use of MOFs as supports for metallic nanoparticles has been investigated. These materials, Pd@MIL-101–NH2(Cr) and Pd@MIL-88B–NH2(Cr), were used as catalysts for Suzuki–Miyaura and oxidation reactions, respectively. The effect of the base on the catalytic activity, crystallinity, porosity, and palladium distribution of Pd@MIL-101–NH2(Cr) was studied. In the final part, the introduction of transition-metal complexes into MOFs through different synthesis routes has been described. A ruthenium complex was grafted onto an aluminium MOF, MOF-253, and an iridium metallolinker was introduced into a zirconium MOF, UiO-68–2CH3. These materials were used as catalysts for alcohol oxidation and allylic alcohol isomerization, respectively.

Interface microstructure of alumina mechanically metallized with Ti brazed to Fe–Ni–Co using different fillers

NASCIMENTO,R.M. et al.Interface microstructure of alumina mechanically metallized with Ti brazed to Fe–Ni–Co using different fillers. Materials Science and Engineering A, v.466, n.1/2, p. 195-200, 2007.

Infiltração de sal de alumínio em fibras de sisal para obtenção de fibras de alumina

ANDRADE JR., T. E. et al. Infiltração de sal de alumínio em fibras de sisal para obtenção de fibras de alumina. Cerâmica, v.51, n.317, p.37-41.ISSN 0366-6913. Disponível em:. Acesso em: 06 out. 2010.

Efeito do Carbeto de Boro na Densificação da Alumina e na Formação de Novas Fase

O carbeto de boro tem efeito inibidor sobre a densificação da matriz de alumina. A maior densidade obtida foi de 80% da densidade teórica. A sinterização foi conduzida nas temperaturas de 1700, 1750 e 1800°C/1 hora em atmosfera de argônio. A caracterização microestrutural foi realizada por difração de raios X, MEV e MET. Foi observada a formação de uma fase identificada por MET como sendo A13B06.

Multiphase flow in porous media: meta-modeling techniques for sensitivity analysis and risk assessment

One of the biggest challenges that contaminant hydrogeology is facing, is how to adequately address the uncertainty associated with model predictions. Uncertainty arise from multiple sources, such as: interpretative error, calibration accuracy, parameter sensitivity and variability. This critical issue needs to be properly addressed in order to support environmental decision-making processes. In this study, we perform Global Sensitivity Analysis (GSA) on a contaminant transport model for the assessment of hydrocarbon concentration in groundwater. We provide a quantification of the environmental impact and, given the incomplete knowledge of hydrogeological parameters, we evaluate which are the most influential, requiring greater accuracy in the calibration process. Parameters are treated as random variables and a variance-based GSA is performed in a optimized numerical Monte Carlo framework. The Sobol indices are adopted as sensitivity measures and they are computed by employing meta-models to characterize the migration process, while reducing the computational cost of the analysis. The proposed methodology allows us to: extend the number of Monte Carlo iterations, identify the influence of uncertain parameters and lead to considerable saving computational time obtaining an acceptable accuracy.