Effect of water-based Al2O3 nanofluids on heat transfer and pressure drop in periodic mixed convection inside a square ventilated cavity

A numerical study of unsteady mixed convection flows through an alumina-water nanofluid in a square cavity with inlet and outlet ports due to incoming flow oscillation is performed. It is found that an oscillating velocity at the inlet port cased to creating a periodic variation in the fluid flow and temperature field in the cavity after a certain time duration. The influence of the nanoparticle on the flow and temperature fields has been plotted and discussed. The effect of the oscillation frequency is concealed in a dimensionless number which is the Strouhal number. It is observed that the heat transfer is enhanced for all the Strouhal and Richardson numbers investigated by adding the nanoparticle to the base fluid. It is also found that the performance of the nanoparticle on the enhancement of the heat transfer at higher Richardson numbers is less than that of lower Richardson numbers.     

The Emotional Wardrobe

Since the industrial revolution, fashion and technology have been linked through the textile and manufacturing industries, a relationship that has propelled technical innovation and aesthetic and social change. Today, a new alliance is emerging through the integration of electronic technology and smart materials on the body. This study addresses the integration of technology with clothing from a fashion perspective, and examines its expressive and interactive potential. It proposes the concept of The Emotional Wardrobe: clothing that represents and stimulates emotional response through the interface of technology. It asks if fashion can offer a more personal and provocative definition of self, which actively involves the wearer in a mutable aesthetic identity. A multi-disciplinary framework combines fashion, material science and the real-time, affective computing platform, called AffectiveWare. By merging technology and fashion, The Emotional Wardrobe becomes a poetic interface, shifting emphasis from human–computer interaction to computer-aided, human–human communication.     

Parameter identification of deep-bar induction motors using genetic algorithm

In recent years, the use of three-phase deep-bar induction motors in power systems has increased. Proper modeling and precise parameter identification of the model are essential for motors’ operating analysis. In this paper, among the proposed models of deep-bar induction motors, a model based on two-axis theory is discussed and developed to improve precision. A real coded genetic algorithm estimates the parameters of the model. The accuracy and validity of the model and its identified parameters are verified with the help of a 5.5 kW, 380 V, 50 Hz, 1,450 rpm deep-bar induction motor.     

Orthogonal experimental design applied for wear characterization of aluminum/C<Subscript>sf</Subscript> metal composite fabricated by the thixomixing method

High silicon content aluminum alloy (hypereutectic) possess good tribological characteristics with low coefficients of friction, when embedded with short carbon fiber (C_sf), making this composite a good material choice where good wear and high strength properties are required in light weight components. There is no previously published information available, to the knowledge of the authors, regarding the influence of wear parameters and their interactions on the tribological behavior of C_sf reinforced metal matrix composites. In this study a Taguchi design of experiment (DoE) was conducted to optimize and analyze the effects of the wear parameters on the tribological properties of Al/C_sf metal matrix composite. A novel thixomixing method which was used to process the metal within the semisolid state was employed to embed short carbon fibers homogenously into the metal matrix. The influences of the sliding speed, applied load and volume fraction, of C_sf on the specific wear rate and coefficient of friction were examined, with each of these input parameters tested at three levels(0, 4.2, 8.1%vol.). The results were indicated that Al/C_sf composite had better tribological properties than Al alloy due to which contains carbon as solid lubricant. According to the statistical analysis, the influence of volume fraction of carbon fiber on wear parameters was ranked first; so the load and sliding speed are at the following rankings. The contribution percentage for each parameter was determined by the analysis of variance. The relatively good interfacial adherence of carbon fiber and matrix alloy were demonstrated. The coherent and adherent graphite-rich layer on the worn surface was characterized using scanning electron microscopy (SEM).     

Comparison of the electronic states of alloys from the coherent potential approximation and an order-N calculation

For historical reasons, the coherent potential approximation was originally proposed for isomorphous models of alloys in which all the atoms of a given species are assumed to have the same charge distribution. Order-N methods for density-functional theory local-density approximation calculations of the electronic structure for clusters of hundreds or thousands of atoms demonstrate that a polymorphous model, in which each atom is different, is more realistic. The predictive ability of isomorphous coherent potential approximations is studied by comparison with order-N calculations.     

Catheter Kinematics for Intracardiac Navigation

Steerable catheters are utilized frequently in minimally invasive cardiac interventions. Despite their extensive applications, the properties of the steerable section of such devices have not been thoroughly investigated. In this paper, the kinematics of the distal shaft of the catheters is modeled, and the catheter's reachable workspace and its singular configurations are studied. The modeling is empirically validated through experiments with actual catheters mounted on a specialized robot. The statistical analysis of the experiments verify the effectiveness of the proposed model in estimating the catheter's tip position. In the experiments, the modeling error does not exceed 2.66 plusmn 1.96 mm, and the mean absolute error in position coordinates is less than 1.55 mm. In addition, the linear relationship between the model and the measured position vectors is demonstrated, and the significance of the modeling goodness of fit is established. Based on the precision and computational effectiveness of the method, the applicability of the modeling to control and simulation purposes is postulated.     

Electrical and structural properties of polyaniline/cellulose triacetate blend films

Polyaniline (PANI) has been blended with cellulose triacetate (CTA) to obtain both good mechanical properties and good electrical properties. The effects of PANI weight percentage on the optical, structural, morphological and electrical properties in the blend films of polyaniline and cellulose triacetate (PANI/CTA) have been investigated. The phenomenon of percolation was observed in these blend films. It is found that the electrical conductivity of the blend films increases with the increase of polyaniline content up to a value of 10⁻⁴ S cm⁻¹ at 84 weight percentage of PANI. The experimental percolation threshold of the dried blend films is obtained at 9.5 wt% of polyaniline. The values of Mott’s temperature, density of states at the Fermi level [N (E _f)], hopping distance (R _hop), and barrier height (W _hop) for PANI/CTA blend films are calculated. By applying Mott’s theory, it is found that the PANI/CTA blend films obey the three dimensional variable range hopping mechanism.     

Inventory lot-sizing with supplier selection using hybrid intelligent algorithm

In supply chain management (SCM), multi-product and multi-period models are usually used to select the suppliers. In the real world of SCM, however, there are normally several echelons which need to be integrated into inventory management. This paper presents a hybrid intelligent algorithm, based on the push SCM, which uses a fuzzy neural network and a genetic algorithm to forecast the rate of demand, determine the material planning and select the optimal supplier. We test the proposed algorithm in a case study conducted in Iran.