Mixing characteristics for the single and air-water two-phase flows in miniaturized parallel multichannel-based devices

Investigation on the miniaturized parallel multichannel-based devices packed with glass beads to improve the mass exchange execution is the critical focal point of the current study. One of the essential parameters to specify the miniaturized devices' flow distribution is the residence time distribution (RTD). In the present context, the RTDs of a liquid tracer were investigated for the air-water multiphase flows (concurrent) across the multichannel-based miniaturized devices (comprising of 11 similar dimensional parallel channels). The devices were variable in height and packed with glass beads. The conductivity estimations generated the RTD curves and were addressed by the axial dispersion model (ADM). The fluid-flow rates differed within the range of 5–23 ml min⁻¹. The axial dispersion coefficients and the rate of the specific energy dispersion were investigated. The effects of pressure difference and geometry on the hydrodynamic attributes and mixing properties were well-illustrated, and the new correlations were suggested.     

Quasi-static compressive behaviour of aluminium cenosphere syntactic foams

In this paper, cenosphere particles embedded in AA2014 aluminium matrix are used to fabricate syntactic foam by stir casting method. The particle size is about 100?µm and foam density is about 1990?kg?m^?3. Compression tests at strain rate 0.001/s are performed on foam samples to characterise their mechanical properties which are then used in numerical analysis on commercial finite element analysis software ABAQUS/CAE with isotropic elastic-plastic material model. Experimental and numerical results show good conformity in deformation behaviour with elastic and plateau zones showing average deviations less than 5% and 20%, respectively. Foams showed high yield stress and energy absorption capabilities that can be useful in making blast and impact resistant structures.     

Design and performance study of phase‐locked loop using fractional‐order loop filter

The present work reports the realization of an analog fractional‐order phase‐locked loop (FPLL) using a fractional capacitor. The expressions for bandwidth, capture range, and lock range of the FPLL have been derived analytically and then compared with the experimental observations using LM565 IC. It has been observed that bandwidth and capture range can be extended by using FPLL. It has also been found that FPLL can provide faster response and lower phase error at the time of switching compared to its integer‐order counterpart. Copyright © 2014 John Wiley & Sons, Ltd.     

Simulation of the percolation of water into rigid polyurethane foams at applied hydraulic pressures

The hydraulic resistance of polyurethane foams is studied by means of simulations of water penetration into model foams. The model foams of cubical shape are constructed by generating the centers of the cells randomly. The strength of the window separating two cells is assumed to be a function of the distance between the centers of the cells in one set of computations. In another set of computations the strengths of the windows are assigned randomly from a specified distribution. The foam is exposed to an elevated pressure at its boundaries and water penetrates into the foam by rupturing the windows with strengths lesser than the applied pressure. The variation of equilibrium volume fraction of the foam filled with water for increasing hydraulic pressures shows typical percolation behavior: there is a sharp increase in the volume filled beyond a threshold pressure. Simulations show that beyond a certain sample size there is no change in the percolation curve with sample size, and indicate that it is mainly the weaker windows that control the hydraulic resistance of the foam. The simulation results are compared with experimental data. POLYM. ENG. SCI. 46:970–983, 2006. © 2006 Society of Plastics Engineers     

Some aspects of deformation behavior

The deformation behavior of several single- and two-phase coarse microstructures has been examined using microhardness measurements. It has been found that the strength response of a coarse phase in isolation is distinctly different from its response when it exists in a two-phase system. The second phase alters the mechanical state of the first one andvice versa even in the plastically undeformed condition. This phenomenon is explained in terms of the existence of an appreciable amount of residual stresses in two-phase coarse microstructures. These stresses primarily arise due to the difference in thermal expansion coefficients of the phases. The in- fluence of elastic stress field on microhardness response is shown with a new type of experiment to support the proposed explanation. The present results question the existing expressions for deformation modeling of multiphase materials because of the uncertainties in the estimation of the average strength of the phases in a two-phase system.     

A balanced solution of a fuzzy soft set based decision making problem in medical science

The purpose of this paper is two folded. Firstly, the concept of mean potentiality approach (MPA) has been developed and an algorithm based on this new approach has been proposed to get a balanced solution of a fuzzy soft set based decision making problem. Secondly, a parameter reduction procedure based on relational algebra with the help of the balanced algorithm of mean potentiality approach has been used to reduce the choice parameter set in the parlance of fuzzy soft set theory and it is justified to the problems of diagnosis of a disease from the myriad of symptoms from medical science. Moreover the feasibility of this proposed method is demonstrated by comparing with Analytical Hierarchy Process (AHP), Naive Bayes classification method and Feng's method.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.