Antonio C.M. Sousa

Enhanced Thermal Conductivity and Viscosity of Nanodiamond-Nickel Nanocomposite Nanofluids

We report a new type of magnetic nanofluids, which is based on a hybrid composite of nanodiamond and nickel (ND-Ni) nanoparticles. We prepared the nanoparticles by an in-situ method involving the dispersion of caboxylated nanodiamond (c-ND) nanoparticles in ethylene glycol (EG) followed by mixing of nickel chloride and, at the reaction temperature of 140°C, the use of sodium borohydrate as the reducing agent to form the ND-Ni nanoparticles. We performed their detailed surface and magnetic characterization by X-ray diffraction, micro-Raman, high-resolution transmission electron microscopy, and vibrating sample magnetometer. We prepared stable magnetic nanofluids by dispersing ND-Ni nanoparticles in a mixture of water and EG; we conducted measurements to determine the thermal conductivity and viscosity of the nanofluid with different nanoparticles loadings. The nanofluid for a 3.03% wt. of ND-Ni nanoparticles dispersed in water and EG exhibits a maximum thermal conductivity enhancement of 21% and 13%, respectively. For the same particle loading of 3.03% wt., the viscosity enhancement is 2-fold and 1.5-fold for water and EG nanofluids. This particular magnetic nanofluid, beyond its obvious usage in heat transfer equipment, may find potential applications in such diverse fields as optics and magnetic resonance imaging.

Effects of enhanced surfaces and surface orientation on nucleate and film boiling heat transfer in R-11

Abstract A study of pool boiling heat transfer in R-11 is reported as a function of surface characterization and orientation. Two specially prepared metal coated surfaces (UNB#1, UNB#2) and a flat copper surface were subjected to heat fluxes up to 180 kW m −2 with surface orientations varying from horizontally facing upward (0°), to vertical (90°), to horizontally facing downward (180°). The resulting nuleate boiling curves display considerable boiling hysteresis and enhanced surfaces show 2–3 times better heat transfer than a plain surface. Rohsenows nucleate boiling equation is used to correlate the data and modified to account for the effects of surface characterization and orientation. In film boiling, enhanced surfaces also reveal better heat transfer characteristics and the role of surface orientation on the motion and stability of the vapor film is clarified.

Moisture transport in initially fully saturated concrete during drying

Moisture content changes during drying were investigated in the present work. Particular emphasis was placed on the initial stage of drying of saturated concrete, where moisture contents are high. For this stage of drying, experimental data are lacking, and no comprehensive theory exists to describe it.The present investigation was performed experimentally and numerically for drying of cylinders with one exposed end, made of normal weight and lightweight concrete with varying water to cement ratio (w/c). The gravimetric technique was employed to obtain the spatial distribution of moisture content. The experimental results obtained indicate that drying of concrete becomes diffusion controlled when the average moisture content decreases below 70 to 80% of the initial saturation. Typical drying rates are in the order of magnitude of 0.18 kg/day/m2 and 0.02 kg/day/m2 for the first and the second stage of drying, respectively.The lightweight concrete cylinders as compared to those made of normal weight concrete exhibited higher levels of moisture content throughout the process. At high w/c ratios, the moisture profiles for both types of cylinders, as expected, show steeper changes with time. Large, constant drying rates were observed both experimentally and numerically in the beginning of the drying.The numerical model developed is based on a generalized mathematical formulation for mass and heat transfer in porous media, and its predictions are in agreement with the experimental data within the uncertainty range of the input data.

Modeling of flow and thermo-kinetics during the cure of thick laminated composites☆

Abstract The present work describes a three-dimensional numerical model developed to simulate and to analyse the mechanisms dealing with resin flow, heat transfer and the cure of thick composite laminates during autoclave processing. The model, which incorporates some of the best features of models already reported in the literature, is based on the Darcy law, the convection-diffusion heat equation, and appropriate constitutive relations. The models predictions show that the final degree of consolidation is strongly dependent upon the compacting pressure, which corroborates previous work, and, to a great extent, upon the edge bleeding flow—a finding, which had not been clearly identified before in the literature. The simulations were conducted using the parameters that describe the resin kinetics and rheological behavior of Hercules ASA/3501-6 tape, however, the model is general enough to accommodate different types of tape. The predictions are in good agreement with the results available in the literature, notwithstanding a few concerns related to the final consolidation level of the composite.

Prediction of building interference effects on pedestrian level comfort

This paper presents results concerning the interference effect created by two auxiliary buildings located upstream of a recreation area comprising seven pavilions. Both numerical and experimental simulations were used to conduct the analyses, and the experimental and numerical results are compared against each other for vertical velocity profiles at different locations. For the numerical simulation, the RANS equations were solved with the turbulence formulated by the k2e RNG model. For the experimental work, a 1

Mesoscale SPH modeling of fluid flow in isotropic porous media

Abstract A novel numerical technique—Smoothed Particle Hydrodynamics (SPH) is used to model the fluid flow in isotropic porous media. The porous structure is resolved in a mesoscopic-level by randomly assigning certain portion of SPH particles to fixed locations. A repulsive force, similar in form to the 12-6 Lennard-Jones potential between atoms, is set in place to mimic the interactions between fluid and porous structure. This force is initiated from the fixed porous material particle and may act on its nearby moving fluid particles. In this way, the fluid is directed to pass through the porous structure in physically reasonable paths. For periodic porous systems formed by intersecting solid material with straight parallel fluid channels, the Kozeny formula of permeability was reproduced successfully, which, to a great extent, validates the reliability of the developed SPH model. Further, SPH simulations for the fluid flows induced by an applied streamwise body force in two-dimensional porous structures of different porosities are performed. The macroscopic Darcys law is confirmed to be valid only in the creeping flow regime. The derived relationship of permeability versus porosity is compared with some existing numerical results/experimental data, which demonstrates that the present SPH model is able to capture the essential features of the fluid flow in porous media.

Surface engineered surgical tools and medical devices

Surface engineered surgical tools and medical devices / , Surface engineered surgical tools and medical devices / , کتابخانه دیجیتال جندی شاپور اهواز

Thermal response analysis of LPG tanks exposed to fire

Abstract The present paper reports on the development of a numerical model for LPG tanks engulfed in flames, A detailed description of the required phenomenological relations and assumptions is also given. The model uses a lumped approach for the lading with two major control volumes linked by the evaporation of a stratified interface. Comparison between the models predictions and field test data show close agreement.

Experimental and numerical simulation of flow around two-dimensional hills

Abstract The present work is devoted to the study of the turbulent isothermal flow around two-dimensional sinusoidal hills. In this work, both experimental and numerical approaches were followed. The experimental results were obtained from a simulation carried out in two wind tunnels, for a Reynolds number, based on the hills height, ranging from 1.8 × 10 4 to 2.5 × 10 5 . The results obtained experimentally comprise static wall pressure distributions, velocity profiles at strategic locations and flow visualisation. The algorithm adopted for the numerical simulation is based on a control volume approach applied to a numerically generated boundary fitted grid. The transport equations are solved using the SIMPLEC formulation, and turbulence is modelled with a modified low-Reynolds number k - ϵ model. The comparison between numerical and experimental results shows an overall good agreement.

Neural network analysis of experimental data for air/water spray cooling

Abstract To obtain appropriate strength properties, nickel-based superalloy or titanium materials used in the aerospace industry are heat treated by cooling from high temperatures. Unacceptably high residual stresses may result, if the rate of cooling is too high. After extensive investigation, it was found that air-assisted atomised water sprays offer an excellent capability of controlling the rate of cooling, and they are a viable alternative to the widely used techniques of quenching in oil or water. The heat transfer data were obtained for a wide range of pressure ratios and hence water flows for surface temperatures of up to 850°C. This paper provides a neural methodology for heat transfer analyses of data obtained experimentally during the investigation of the use of air-assisted atomised water spray systems for the controlled cooling of high temperature forgings. The model created to train the neural network relates the spray input variables to the corresponding heat transfer data for the range of conditions observed experimentally. For comparison purposes and accurate evaluation of the predictions, part of the data is used to train the neural network and the remainder to test the model. It is described in detail how a neural network can be trained to successfully predict the resulting heat flux for specific input spray parameters. This particular knowledge can then be used to optimise the process, i.e. to establish the spray conditions that would yield the cooling rate required to attain the pre-specified mechanical properties, and to minimise the residual stresses.