Narrow Results

Turbulent Schmidt number as an important parameter in computational fluid dynamic (CFD) simulations is strongly dependent on height, whereas it is mostly considered to be constant in the literature. This paper presents a new variable turbulent Schmidt number formulation which can calculate the relative concentrations (RCs) in neutral atmospheric conditions more accurately. To achieve this aim, RCs from continuous releases are calculated in different distances by the analytical Gaussian plume mode. CFD simulations are carried out for single stack dispersion on a flat terrain surface and an inverse procedure is then applied so that different turbulent Schmidt numbers are used as inputs to determine the RCs to select the “best-fit” turbulent Schmidt number value. This process is continued for different heights to fit a curve to obtain the new formulation for turbulent Schmidt number varying with height. The values are compared with experimental results. The comparison indicates that the new formulation for turbulent Schmidt number is more accurate and reliable than previous research works.

A numerical study of pulsatile hydromagnetic flow and mass transfer of a non-Newtonian biofluid through a porous channel containing a non-Darcian porous material is undertaken. An extensively-validated biofluid dynamics variational finite element code, BIOFLOW, is employed to obtain comprehensive computational solutions for the flow regime which is described using a spatially two-dimensional momentum equation and a spatially one-dimensional mass transport equation, under appropriate boundary conditions. The Nakamura-Sawada rheological model is employed which provides a higher yield stress than the Casson model. A non-Newtonian model is justified on the basis that blood exhibits deviation from Newtonian behavior at low shear rates. The conduit considered is rigid with a pulsatile pressure applied via an appropriate pressure gradient term. One hundred two-noded line elements have been employed in the computations. The influence of magnetic field on the flow is studied via the magnetohydrodynamic body force parameter (Nm), which defines the ratio of magnetic (Lorentz) retarding force to the viscous hydrodynamic force. Blood vessel blockage effects are simulated with a Darcy-Forchheimer nonlinear drag force model incorporating a Darcian linear impedance for low Reynolds numbers and a Forchheimer quadratic drag for higher Reynolds numbers. Transformed velocity and concentration profiles are plotted for the influence of Reynolds number (Re), Darcy parameter (λ), Forchheimer inertial drag parameter (N_F), non-Newtonian parameter (β), and Schmidt number (Sc) and at various times (T). Three-dimensional profiles of velocity varying in space and time are also provided. Applications of the model include magnetic therapy, biomagnetic pharmaco-dynamics and the simulation of diseased arteries.

Cerebrospinal fluid (CSF) is a symmetric flow transport that surrounds brain and central nervous system (CNS). Hydrocephalus is an asymmetric and unusual cerebrospinal fluid flow in the lateral ventricular portions. This dumping impact enhances the elasticity over the ventricle wall. Henceforth, compression change influences the force of brain tissues. Mathematical models of transport in the hydrocephalus, which constitutes an excess of fluid in the cavities deep within the brain, enable a better perspective of how this condition contributes to disturbances of the CSF flow in the hollow places of the brain. Recent approaches to brain phase spaces reinforce the foremost role of symmetries and energy requirements in the assessment of nervous activity. Thermophysical and mass transfer effects are therefore addressed in this paper to quantify the transport phenomena in pulsatile hydrocephalus CSF transport with oscillating pressure variations that characterize general neurological activity and transitions from one functional state to another. A new mathematical model is developed which includes porous media drag for brain tissue and solutal diffusion (concentration) effects. A classical Laplace transform method is deployed to solve the dimensionless model derived with appropriate boundary conditions. The analysis reveals that with increasing permeability of the subarachnoid space, the CSF velocity is increased, and a significant fluid flux enhancement arises through the brain parenchyma as the pressure of the fluid escalates drastically due to hydrocephalus disorder. Stronger thermal buoyancy (Grashof number) also results in deceleration in the flow. CSF temperature is reduced with progression in time. Particle (e.g. ion) concentration is suppressed with increasing Schmidt number. As heat conduction parameter increases, there is a substantial depletion in CSF velocity with respect to time. Increasing Womersley parameter displaces the CSF velocity peaks and troughs. The present effects are beneficial in determining the thermo-fluidic transport mechanism of the pathological disorder hydrocephalus. Also, the present results are compared with those clinical studies for some cases. We have confirmed that our validity provides a decent justification with the neurological studies.

We draw an intuitive picture of the spatio–temporal properties of the entangled state of twin photons, where they are described as classical wave-packets. This picture predicts a precise relation between their temporal and transverse spatial separations at the crystal output. The space-time coupling described by classical arguments turns out to determine in a precise way the spatio–temporal structure of the quantum entanglement, analyzed by means of the biphotonic correlation and of the Schmidt dimensionality of the entanglement.

The Schmidt number is of crucial importance in characterizing the bipartite pure states. We explore and propose here a generalization of Schmidt number for states in multipartite systems. It is shown to be entanglement monotonic and valid for both pure and mixed states. In addition, the corresponding generalization of multipartite Schmidt coefficients is introduced. Our approach is applicable for systems with arbitrary number of parties and for arbitrary dimensions.