Estimation of the trajectory of magnetic nanoparticles in non-newtonian vascular fluid with cancer through neuronal networks

Treatments to combat cancer seek to reach specific regions to ensure maximum efficiency and reduce the possible adverse effects that occur in the treatment. One of these strategies include the treatment with magnetic nanoparticles (NPM), which has presented promising results, however, aspects involved in the trajectory of the nanoparticles are not yet known. The aim of this work is estimating the behavior of NPM through supervised neural networks, for this, artificial neural networks were implemented, such as multilayer perceptron, with optimization algorithms in which the Levenberg Marquardt algorithm stands out, different trajectories of NPM were simulated, including parameters such as time, position in X and Y, the speed that the nanoparticles can reach and physical factors that interact in the distribution were considered, such as the gravitational field, the magnetic field, the Stokes force, the force of pushing and dragging with different values of viscosity in the blood, generating a database with optimized reaction times that allows a more accurate prediction. The architecture obtained with the artificial neural the network that contains the optimization algorithm [5 4 3 2], presented the best performance with a training MSE of 1.763E-07, a validation uRMSE of 0.0049, and trend probabilities of X 0.62 % and 0.576 % in Y.

Resonance behavior for a generalized Mittag-Leffler fractional Langevin equation with hydrodynamic interactions

The phenomenological model for the heavy tracers in viscoelastic media modeled by a generalized Mittag-Leffler fractional Langevin equation with the generalized Stokes force, the Basset force, the Hookean force, and the thermal force has been revisited. Under the fluctuation-dissipation relation, the generalized Stokes force describes the viscoelastic media by a Mittag-Leffler (ML) memory kernel. Furthermore, based on the background of ML function, the generalized Mittag-Leffler fractional derivative is introduced. Moreover, the exact expression of stationary first moment and the expression of spectral amplification (SPA) of a tracer model have been deserved by the generalized form of Shapiro-Loginov formula. The generalized stochastic resonance (GSR) phenomena has been systematically studied. Moreover, the GSR, reverse stochastic resonance (SR) phenomenon, bona fide SR, stochastic multi-resonance (SMR) phenomena, increasing multi-resonance and decreasing multi-resonance have been found. Especially, the periodic resonance phenomenon could be induced by the generalized Mittag-Leffler (GML) noise, which has been few observed in the previous literatures.

Importance of Basset History Force for the Description of Magnetically Driven Motion of Magnetic Particles in Air

Lungs are used as an attractive possibility for administration of different therapeutic substances for a long time. An innovative method of such administration widely studied nowadays is the application of aerosolized magnetic particles as the carriers to the lungs in the external non-homogeneous magnetic field. For these reasons we have studied dynamics of such a system on a level of particle trajectory in air in the presence of magnetic force as a driving force exerted on micrometric magnetic particle. On two typical examples of magnetically driven systems—motion of magnetic particle in a gradient magnetic field and cyclotron-like motion of a charged particle in homogeneous magnetic field in microscale, where the external accelerating forces are very large and the relevant time scale is of the order from fraction of milliseconds to seconds, we have examined the importance of these forces. As has been shown, for particles with high initial acceleration, not only the commonly used Stokes force but also the Basset history force should be used for correct description of the motion.

Approximate Stokes Drift Profiles in Deep Water

A deep-water approximation of the Stokes drift velocity profile is explored as an alternative to the monochromatic profile. The alternative profile investigated relies on the same two quantities required for the monochromatic profile, namely, the Stokes transport and the surface Stokes drift velocity. Comparisons with parametric spectra and profiles under wave spectra from the Interim ECMWF Re-Analysis (ERA-Interim) and buoy observations reveal much better agreement than the monochromatic profile even for complex sea states. That the profile gives a closer match and a more correct shear has implications for ocean circulation models since the Coriolis–Stokes force depends on the magnitude and direction of the Stokes drift profile, and Langmuir turbulence parameterizations depend sensitively on the shear of the profile. The alternative profile comes at no added numerical cost compared to the monochromatic profile.

Interphasial energy transfer and particle dissipation in particle-laden wall turbulence

Transfer of mechanical energy between solid spherical particles and a Newtonian carrier fluid has been explored in two-way coupled direct numerical simulations of turbulent channel flow. The inertial particles have been treated as individual point particles in a Lagrangian framework and their feedback on the fluid phase has been incorporated in the Navier–Stokes equations. At sufficiently large particle response times the Reynolds shear stress and the turbulence intensities in the spanwise and wall-normal directions were attenuated whereas the velocity fluctuations were augmented in the streamwise direction. The physical mechanisms involved in the particle–fluid interactions were analysed in detail, and it was observed that the fluid transferred energy to the particles in the core region of the channel whereas the fluid received kinetic energy from the particles in the wall region. A local imbalance in the work performed by the particles on the fluid and the work exerted by the fluid on the particles was observed. This imbalance gave rise to a particle-induced energy dissipation which represents a loss of mechanical energy from the fluid–particle suspension. An independent examination of the work associated with the different directional components of the Stokes force revealed that the dominating energy transfer was associated with the streamwise component. Both the mean and fluctuating parts of the Stokes force promoted streamwise fluctuations in the near-wall region. The kinetic energy associated with the cross-sectional velocity components was damped due to work done by the particles, and the energy was dissipated rather than recovered as particle kinetic energy. Componentwise scatter plots of the instantaneous velocity versus the instantaneous slip-velocity provided further insight into the energy transfer mechanisms, and the observed modulations of the flow field could thereby be explained.

Dynamics for Dense Packing of Colloids

Colloidal packing by evaporation is a process that particles are packed by Stokes’ forces. As particles are far from each other, interactions among them are too weak to be taken into account and it’s the Stokes’ force on free particles that is in charge of packing. However, when they are close to some extent, the force is countered by particle interactions. Here, with the aid of force balance model, we demonstrate that the further packing is achieved by all drag forces of particles in the upstream.

Nanoparticle Friction Force and Effective Viscosity of Nanosuspensions

The transport properties of nanofluids are investigated by the molecular dynamics method. It is shown that the force acting on a nanoparticle is nonstationary, in contrast to the Stokes force. In the initial stage of relaxation, the friction force is greater than the Stokes value. Subsequently, this force decreases and reaches an asymptotic value. This value is comparable to the Stokes force only for a massive particle. A correlation for determining the friction coefficient is constructed. It is established that the effective viscosity coefficient of nanofluids depends not only on the volume concentration of nanoparticles but also on the nanoparticle mass and radius.