A numerical investigation of conjugated-natural convection heat transfer enhancement of a nanofluid in an annular tube driven by inner heat generating solid cylinder

Laminar conjugate heat transfer by natural convection and conduction in a vertical annulus formed between an inner heat generating solid circular cylinder and an outer isothermal cylindrical boundary has been studied by a numerical method. It is assumed that the two sealed ends of the tube to be adiabatic. Governing equations are derived based on the conceptual model in the cylindrical coordinate system. The governing equations have been solved using the finite volume approach, using SIMPLE algorithm on the collocated arrangement. Results are presented for the flow and temperature distributions and Nusselt numbers on different cross sectional planes and longitudinal sections for Rayleigh number ranging from 10⁵ to 10⁸, solid volume fraction of 0‹φ‹0.05 with copper-water nanofluid as the working medium. Considering that the driven flow in the annular tube is strongly influenced by orientation of tube, study has been carried out for different inclination angles.     

Effect of material and processing parameters on mechanical properties of Polypropylene/Ethylene–Propylene–Diene–Monomer/clay nanocomposites

Polypropylene/Ethylene–Propylene–Diene–Monomer (PP/EPDM) blends are well known for having a combination of favourable mechanical properties. In this paper, addition of organoclay to PP/EPDM to make PP/EPDM nanocomposites with enhanced mechanical properties is studied. PP/EPDM/organoclay nanocomposites were prepared using a lab scale twin-screw extruder. Maleic anhydride grafted polypropylene (PP-g-MA) was used to enhance the intercalation/exfoliation process and to create good adhesion at the polymer/polymer and polymer/filler interfaces. Taguchi method was employed to deign the experiments and optimize material and processing parameters for optimized mechanical properties. Organoclay (NC) and compatibilizer content were selected as material parameters and the main processing variables were feeding rate and average shear rate (RPM). X-ray diffraction (XRD), Transmission Electron Microscopy (TEM) and Scanning Electron Microscopy (SEM) were used to study the microstructure of the nanocomposites samples. It was observed that NC content and shear rate in extruder improved the tensile strength and modulus. Another important result was the insignificant effect of NC content on impact strength while increasing shear rate first increased and then decreased the impact strength.     

Surface characterization and influence of anodizing process on fatigue life of Al 7050 alloy

The present study investigates the influence of anodizing process on fatigue life of aluminium alloy 7050-T7451 by performing axial fatigue tests at stress ratio ‘R’ of 0.1. Effects of pre-treatments like degreasing and pickling employed prior to anodizing on fatigue life were studied. The post-exposure surface observations were made by scanning electron microscope (SEM) to characterize the effect of each treatment before fatigue testing. The surface observations have revealed that degreasing did not change the surface topography while pickling solution resulted in the formation of pits at the surface. Energy dispersive spectroscopy (EDS) was used to identify those constituent particles which were responsible for the pits formation. These pits are of primary concern with respect to accelerated fatigue crack initiation and subsequent anodic coating formation. The fatigue test results have shown that pickling process was detrimental in reducing the fatigue life significantly while less decrease has been observed for anodized specimens. Analyses of fracture surfaces of pickled specimens have revealed that the process completely changed the crack initiation mechanisms as compared to non-treated specimens and the crack initiation started at the pits. For most of the anodized specimens, fatigue cracks still initiated at the pits with very few cracks initiated from anodic coating. The decrease in fatigue life for pickled and anodized specimens as compared to bare condition has been attributed to decrease in initiation period and multi-site crack initiations. Multi-site crack initiation has resulted in rougher fractured surfaces for the pickled and anodized specimens as compare to bare specimens tested at same stress levels.     

An accurate model for prediction of autoignition temperature of pure compounds

Accurate prediction of pure compounds autoignition temperature (AIT) is of great importance. In this study, the Artificial Neural Network-Group Contribution (ANN-GC) method is applied to evaluate the AIT of pure compounds. 1025 pure compounds from various chemical families are investigated to propose a comprehensive and predictive model. The obtained results show the squared correlation coefficient of 0.984, root mean square error of 15.44K, and average percent error of 1.6% for the experimental values.     

Effect of graphene nanoplatelets presence on the morphology,structure, and thermal properties of polypropylene in fiber melt‐spinning process

Melt spinning of graphene nanoplatelets (GnPs)‐polypropylene (PP) nanocomposite fibers are reported for the first time. PP/GnPs fibers were spun with a pilot‐plant spinning machine with varying concentration of GnPs by mixing PP/GnPs masterbatch with PP. The effect of inclusion of GnPs on the morphology and crystalline structure of PP fibers was investigated. The thermal stability of the fibers was also evaluated by thermogravimetric analysis. The light microscopy images showed that the GnPs are uniformly distributed over the PP matrix. The differential scanning calorimetry (DSC) results revealed that presence of GnPs affects both the melting and crystallization behaviors. The melting peaks of PP/GnPs nanocomposite fibers were broader than that of neat PP fibers, indicating a broader crystal size distribution in PP/GnPs nanocomposite fibers as compared to the neat PP fibers. Besides, an obvious increment in the crystallization peak temperature was observed in GnPs‐PP nanocomposite fibers. The wide‐angle X‐ray diffraction spectra (WAXD) results showed that the crystal type of nanocomposite fibers did not change and was still the α‐monoclinic crystal form. Moreover, the morphology of spherulites demonstrated that GnPs increased the nucleation sites in the nanocomposite fibers which in turn restricted the crystal growth of PP chains. This finding supported the DSC and WAXD results. Activation energies were calculated by Horowitz and Metzger's method as 77.87 and 105.41 kJ/mol for neat PP and PP/0.2 wt% GnPs fibers, respectively, suggesting an increase in the thermal stability of GnPs‐PP nanocomposite fibers. POLYM. COMPOS., 36:367–375, 2015. © 2014 Society of Plastics Engineers     

A model for the rate of catalytic oxidation of methanol in a fixed bed reactor

Oxidation of methanol to formaldehyde, using a mixture of ferric and molybdenum oxides as catalyst, has been studied in a fixed bed integral reactor, 150 mm long, 25 mm o.d. and 10 mm i.d. The catalyst was prepared by reaction between aqueous solutions of ammonium heptamolybdate and ferric chloride. It has been shown that, under experimental conditions similar to those employed in industry, neither external nor internal diffusion had been effective in the process and isothermal conditions prevailed in both gas and solid phases. A two-step mechanism has been put forward for the oxidation of methanol. According to such a mechanism, methanol is first oxidized to formaldehyde, accepting an oxygen molecule from the catalyst and changing the latter into a reduced form. In the second step, the reduced catalyst is transformed into the original form on obtaining an oxygen molecule from the gas phase. Based on this scheme, a rate model has been derived and verified by experimental results.     

Theoretical modification of the finely porous model for reverse osmosis transport

One of the most significant models used to describe and predict the performance of reverse osmosis type membranes is the finely porous model (FPM). In this paper, the basic assumptions of the model are examined and modified. The two most serious problems with FPM are that an incorrect form of material balance on the solute is used and that the osmotic pressure effects are not completely taken into account for electrolytes. A modified model (called MD-FPM), which is based on the same physical precepts is derived. Equations describing the concentration profile for both models have been derived and compared. It has been shown that the FPM can predict physically unacceptable results. Difficulties in using the parameters from the model for prediction or for membrane development work are discussed. Simulation results for the MD-FPM model are consistent with what is expected for reverse osmosis type membranes.     

Nonlinear vibration of cord-reinforced composite shells

This paper discusses ADINA finite element incremental formulations for nonlinear static and dynamic analysis of materials with nonlinear constitutive equations. The formulations are applied to axisymmetric problems of cord reinforced composites using the ADINA computer program. Numerical results on natural frequencies and mode shapes of cord reinforced inflatable toroidal shells are presented for axisymmetric modes of excitation.     

Effect of soil properties for prediction of energy consumption in land levelling irrigation

ABSTRACT

Energy conservation is regarded as one of the most important factors in the agricultural sector due to its relation to pollution which is a result of fossil fuel (particularly gasoline) usage. The objective of this research was to develop three methods including Artificial Neural Network (ANN), regression and Adaptive Neural-Fuzzy Inference System (ANFIS) to predict the effect of soil properties on the environmental indicators in land levelling and to analyse the sensitivity of these parameters. The acquired data were used to develop accurate models for fuel energy (FE), total machinery cost (TMC) and total machinery energy (TME). The results showed that four parameters of tillage depth, forward speed, cone index and cut/fill volume had significant effects on energy consumption. ANFIS and ANN had a satisfactory performance in predicting the aforementioned parameters in the various field conditions. The ANN had the most capability in FE prediction according to the least RMSE and the highest coefficient of determination (R²) values 0.0206 and 0.9983, respectively. The ANFIS model had the most capability in the prediction of the environmental and energy parameters with the least RMSE and the highest R2 for TMC, 0.0287 and 0.9966, and for TME, 0.0157 and 0.9990, respectively.