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A few earlier studies presented infeasible heatline trajectories for natural convection within annular domains involving an inner circular cylinder and outer square/circular enclosure. The purpose of this paper is to revisit and illustrate the correct heatline trajectories for various test cases.

Galerkin finite element based methodology and space adaptive grid have been used to simulate natural convective flows within the annular domains. The prediction of heatlines involves derivatives at the nodes, which are evaluated based on finite element basis functions and contributions from neighboring elements.

The heatlines in the earlier work indicate infeasible heat flow paths such as heat flow from one portion to the other of isothermal hot walls and heat flow across the adiabatic walls. Current results illustrate physically consistent heat flow paths involving perpendicularly emerging heatlines from hot to cold walls for conductive transport, long heat flow paths around the closed-loop heatline cells for convective transport and parallel layout of heatlines to the adiabatic walls. Results also demonstrate complex heatlines involving multiple flow vortices and complex flow structures.

Current work translates heatfunctions from energy flux vectors, which are determined by using basis sets. This work demonstrates the expected heatline trajectories for various scenarios involving conductive and convective heat transport within enclosures with an inner hot object as a first attempt, and the results are precursors for the understanding of energy flow estimates.

The concept of a heat function is introduced to visualize the path of heat flow in a buoyancy‐driven turbulent flow heated vertical flat plate. The velocities and the temperature field near the vertical plate are predicted numerically, using an algebraic flux model of turbulent heat transport. As an accurate prediction of the turbulent heat flux is required in order to predict the heat function in the flow field, the use of an algebraic flux model for the turbulent heat transport θu_i, is made as compared with a simple eddy diffusivity hypothesis. The algebraic flux expression was closed with a low‐Re‐number‐k‐ε — θ² —_θ model. The solution ofthe 4 equation low‐Re‐number‐k‐ε — θ² — ε_θ model predicts very well the local Nusselt number along the plate height as well as the velocity and the temperature field near the wall when compared with the experiments. Then the partial differential equation for the heat function is numerically solved to show the true path of heat flow in the buoyancy‐driven turbulent flow field near a heated vertical plate.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a large scale industrial size tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlets of a six strand billet caster tundish. The numerical prediction of the tracer concentration has been made with six different turbulence models (the standard k‐ε, the k‐ε RNG, the Low Re number Lam‐Bremhorst model, the Chen‐Kim high Re number model (CK), the Chen‐Kim low Re number model (CKL) and the simplest constant effective viscosity model (CEV)) which favorably compares with that of the experimental observation for a single strand bare tundish. It has been found that the overall comparison of the k‐ε model, the RNG, the Lam‐Bremhorst and the CK model is much better than the CKL model and the CEV model as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. However, the k‐ε model predicts the closest value to the experimental observation compared to all other models. The prediction of the transient behavior of the tracer is best done by the Lam‐Bremhorst model and then by the RNG model, but these models do not predict the gross quantities that accurately like the k‐ε model for a single strand bare tundish. With the help of the above six turbulence models mixing parameters such as the ratio of mix to dead volume and the mean residence time were computed for the six strand tundish for different outlet positions, height of advanced pouring box (APB) and shroud immersion depth. It was found that three turbulence models show a peak value in the ratio of mix to dead volume when the outlets were placed at 200 mm away from the wall. An APB was put on the bottom of the tundish surrounding the inlet jet when the outlets were kept at 200 mm away from the wall. It was also found that there exists an optimum height of the APB where the ratio of mix to dead volume and the mean residence time attain further peak values signifying better mixing in the tundish. At this optimum height of the APB, the shroud immersion depth was made to change from 0 to 400 mm. It was also observed that there exists an optimum immersion depth of the shroud where the ratio of mix to dead volume still attains another peak signifying still better mixing. However, all the turbulence models do not predict the same optimum height of the APB and the same shroud immersion depth as the optimum depth. The optimum height of the APB and the shroud immersion depth were decided when two or more turbulence models predict the same values.

The conception of a heat function, just like the stream function used in a laminar two dimensional incompressible flow field visualization, has been introduced to visualize the convective heat transfer or the flow of energy around a sphere when the sphere is either being cooled or heated by a stream of fluid flowing around it. The heat function is developed in a spherical polar coordinate and is used to generate the heat lines around the sphere. The heat lines essentially show the magnitude and direction of energy transfer around the sphere with and without the existence of a finite radial velocity at the surface. The steady state hydrodynamic field around the sphere is numerically obtained up to a maximum Reynolds number of 100 and the corresponding thermal field has been obtained by solving the steady state energy equation. The field properties thus obtained are utilized to form the heat function, which becomes an effective tool for visualization of convective heat transfer.

The Navier‐Stokes equation and the species continuity equation have been solved numerically in a boundary fitted coordinate system comprising the geometry of a single strand bare tundish. The solution of the species continuity equation predicts the time evolution of the concentration of a tracer at the outlet of the tundish. The numerical prediction of the tracer concentration has been made with nine different turbulence models and has been compared with the experimental observation for the tundish. It has been found that the prediction from the standard k‐ε model, the k‐ε Chen‐Kim (ck) and the standard k‐ε with Yap correction (k‐ε Yap), matches well with that of the experiment compared to the other turbulence models as far as gross quantities like the mean residence time and the ratio of mixed to dead volume are concerned. It has been found that the initial transient development of the tracer concentration is best predicted by the low Reynolds number Lam‐Bremhorst model (LB model) and then by the k‐ε RNG model, while these two models under predict the mean residence time as well as the ratio of mixed to dead volume. The Chen‐Kim low Reynolds number (CK low Re) model (with and without Yap correction) as well as the constant effective viscosity model over predict the mixing parameters, i.e. the mean residence time and the ratio of mixed to dead volume. Taking the solution of the k‐ε model as a starting guess for the large eddy simulation (LES), a solution for the LES could be arrived after adopting a local refinement of the cells twice so that the near wall y⁺ could be set lower than 1. Such a refined grid gave a time‐independent solution for the LES which was used to solve the species continuity equation. The LES solution slightly over predicted the mean residence time but could predict fairly well the mixed volume. However, the LES could not predict both the peaks in the tracer concentration like the k‐ε, RNG and the Lam‐Bremhorst model. An analysis of the tracer concentration on the bottom plane of the tundish could help to understand the presence of plug and mixed flow in it.

This paper aims at studying numerically the entropy generation of nanofluid flowing over an inclined sheet in the presence of external magnetic field, heat source/sink, chemical reaction along with slip boundary conditions imposed on an impermeable wall.

A suitable similarity transformation technique has been used to convert the coupled nonlinear partial differential equations to ordinary differential equations (ODEs). The ODEs are then solved simultaneously using the finite difference method implemented through an in-house computer program. The effects of different controlling parameters such as magnetic parameter, radiation parameter, Brownian motion parameter, thermophoresis parameter, chemical reaction parameter, Reynolds number, Brinkmann number, Prandtl number, velocity slip parameter, temperature slip parameter and the concentration slip parameter on the entropy generation and Bejan number have been discussed comprehensively through the relevant physical insights for the first time.

The relative strengths of the irreversibilities due to heat transfer, fluid friction and the mass diffusion arising due to the change in each of the controlling variables have been delineated both in the near-wall and far-away-wall regions, which may be helpful for a better understanding of the thermo-fluid dynamics of nanofluid in boundary layer flows. The numerical results obtained from the present study have also been validated with results published in open literature.

The effects of different controlling parameters such as magnetic parameter, radiation parameter, Brownian motion parameter, thermophoresis parameter, chemical reaction parameter, Reynolds number, Brinkmann number, Prandtl number, velocity slip parameter, temperature slip parameter and the concentration slip parameter on the entropy generation and Bejan number have been discussed comprehensively through the relevant physical insights for the first time.

The purpose of this paper is to demonstrate the application of river formation dynamics to size the widths of power distribution network for very large-scale integration designs so that the wire area required by power rails is minimized. The area minimization problem is transformed into a single objective optimization problem subject to various design constraints, such as IR drop and electromigration constraints.

The minimization process is carried out using river formation dynamics heuristic. The random probabilistic search strategy of river formation dynamics heuristic is used to advance through stringent design requirements to minimize the wire area of an over-designed power distribution network.

A number of experiments are performed on several power distribution benchmarks to demonstrate the effectiveness of river formation dynamics heuristic. It is observed that the river formation dynamics heuristic outperforms other standard optimization techniques in most cases, and a power distribution network having 16 million nodes is successfully designed for optimal wire area using river formation dynamics.

Although many research works are presented in the literature to minimize wire area of power distribution network, these research works convey little idea on optimizing very large-scale power distribution networks (i.e. networks having more than four million nodes) using an automated environment. The originality in this research is the illustration of an automated environment equipped with an efficient optimization technique based on random probabilistic movement of water drops in solving very large-scale power distribution networks without sacrificing accuracy and additional computational cost. Based on the computation of river formation dynamics, the knowledge of minimum area bounded by optimum IR drop value can be of significant advantage in reduction of routable space and in system performance improvement.

The purpose of this paper is to appraise Pai and Chary’s (2016) conceptual framework for measuring patient-perceived hospital service quality (HSQ).

A structured questionnaire was used to obtain data from teaching, public and corporate hospital patients. Several tests were conducted to assess the instrument’s reliability and validity. Pai and Chary’s (2016) nine dimensions for measuring HSQ were examined in this paper.

The tests confirm that Pai and Chary’s (2016) conceptual framework is reliable and valid. The study also establishes that the nine dimensions measure HSQ.

The framework empowers managers to assess service quality in any hospital settings, corporate, public and teaching, using an approach that is superior to the existing HSQ scales.

This paper helps researchers and practitioners to assess HSQ from patient perspectives in any hospital setting.

The purpose of this paper is to compute the pressure drop through sudden expansions and contractions for two‐phase flow of oil/water emulsions.

Two‐phase computational fluid dynamics (CFD) calculations, using Eulerian–Eulerian model, are employed to calculate the velocity profiles and pressure drops across sudden expansions and contractions. The pressure losses are determined by extrapolating the computed pressure profiles upstream and downstream of the expansion/contraction. The oil concentration is varied over a wide range of 0‐97.3 percent by volume. The flow field is assumed to be axisymmetric and solved in two dimensions. The two‐dimensional equations of mass, momentum, volume fraction and turbulent quantities along with the boundary conditions have been integrated over a control volume and the subsequent equations have been discretized over the control volume using a finite volume technique to yield algebraic equations which are solved in an iterative manner for each time step. The realizable per phase k‐ ε turbulent model is considered to update the fluid viscosity with iterations and capture the individual turbulence in both the phases.

The contraction and expansion loss coefficients are obtained from the pressure loss and velocity data for different concentrations of oil–water emulsions. The loss coefficients for the emulsions are found to be independent of the concentration and type of emulsions. The numerical results are validated against experimental data from the literature and are found to be in good agreement.

The present computation could not use the surface tension forces and the energy equation due to huge computing time requirement.

The present computation could compute realistically the two‐phase pressure drop through sudden expansions and contractions by using a two‐phase Eulerian model and hence this model can be effectively used for industrial applications where two‐phase flow comes into picture.

The original contribution of the paper is in the use of the state‐of‐the‐art Eulerian two‐phase flow model to predict the velocity profile and pressure drop through industrial piping systems.