A non-perturbative renormalization group study of the stochastic NavierStokes equation

We study the renormalization group flow of the average action of the stochastic Navier-Stokes equation with power-law forcing. Using Galilean invariance, we introduce a nonperturbative approximation adapted to the zero-frequency sector of the theory in the parametric range of the Hölder exponent 4−2 ɛ of the forcing where real-space local interactions are relevant. In any spatial dimension d, we observe the convergence of the resulting renormalization group flow to a unique fixed point which yields a kinetic energy spectrum scaling in agreement with canonical dimension analysis. Kolmogorov's −5/3 law is, thus, recovered for ɛ=2 as also predicted by perturbative renormalization. At variance with the perturbative prediction, the −5/3 law emerges in the presence of a saturation in the ɛ dependence of the scaling dimension of the eddy diffusivity at ɛ=3/2 when, according to perturbative renormalization, the velocity field becomes infrared relevant.

Virtual-bound, filamentary and layered states in a box-shaped quantum dot of square potential form the exact numerical solution of the effective mass Schrodinger equation

The effective mass Schrodinger equation of a QD of parallelepipedic shape with a square potential well is solved by diagonalizing the exact Hamiltonian matrix developed in a basis of separation-of-variables wavefunctions. The expected below bandgap bound states are found not to differ very much from the former approximate calculations. In addition, the presence of bound states within the conduction band is confirmed. Furthermore, filamentary states bounded in two dimensions and extended in one dimension and layered states with only one dimension bounded, all within the conduction band which are similar to those originated in quantum wires and quantum wells coexist with the ordinary continuum spectrum of plane waves. All these subtleties are absent in spherically shaped quantum dots, often used for modeling.

Accurate Parabolic Navier-Stokes solutions of the supersonic flow around and elliptic cone

Flows of relevance to new generation aerospace vehicles exist, which are weakly dependent on the streamwise direction and strongly dependent on the other two spatial directions, such as the flow around the (flattened) nose of the vehicle and the associated elliptic cone model. Exploiting these characteristics, a parabolic integration of the Navier-Stokes equations is more appropriate than solution of the full equations, resulting in the so-called Parabolic Navier-Stokes (PNS). This approach not only is the best candidate, in terms of computational efficiency and accuracy, for the computation of steady base flows with the appointed properties, but also permits performing instability analysis and laminar-turbulent transition studies a-posteriori to the base flow computation. This is to be contrasted with the alternative approach of using order-of-magnitude more expensive spatial Direct Numerical Simulations (DNS) for the description of the transition process. The PNS equations used here have been formulated for an arbitrary coordinate transformation and the spatial discretization is performed using a novel stable high-order finite-difference-based numerical scheme, ensuring the recovery of highly accurate solutions using modest computing resources. For verification purposes, the boundary layer solution around a circular cone at zero angle of attack is compared in the incompressible limit with theoretical profiles. Also, the recovered shock wave angle at supersonic conditions is compared with theoretical predictions in the same circular-base cone geometry. Finally, the entire flow field, including shock position and compressible boundary layer around a 2:1 elliptic cone is recovered at Mach numbers 3 and 4

Characterizing chaos in a type of fractional duffing's equation

We characterize the chaos in a fractional Duffing’s equation computing the Lyapunov exponents and the dimension of the strange attractor in the effective phase space of the system. We develop a specific analytical method to estimate all Lyapunov exponents and check the results with the fiduciary orbit technique and a time series estimation method.

A second order in time modified Lagrange-Galerkin finite element method for the incompressible Navier-Stokes equations

We introduce a second order in time modified Lagrange--Galerkin (MLG) method for the time dependent incompressible Navier--Stokes equations. The main ingredient of the new method is the scheme proposed to calculate in a more efficient manner the Galerkin projection of the functions transported along the characteristic curves of the transport operator. We present error estimates for velocity and pressure in the framework of mixed finite elements when either the mini-element or the $P2/P1$ Taylor--Hood element are used.

Induced shock loads during the separation of the Ariane 5 VEB structure

Tests used to simulate the separation of the lower stage of the Ariane Vehicle Equipment Bay (VEB) were carried out on a flat full scale model. Theoretical studies carried out prior to testing are described. Three different mathematical methods, finite element, component element, and wave propagation, were used. Comparison of the predicted theoretical results with the actual test results is planned.

A 2D computational parametric analysis of the sheltering effect of fences on a railway vehicle standing on a bridge and experiencing crosswinds

In a crosswind scenario, the risk of high-speed trains overturning increases when they run on viaducts since the aerodynamic loads are higher than on the ground. In order to increase safety, vehicles are sheltered by fences that are installed on the viaduct to reduce the loads experienced by the train. Windbreaks can be designed to have different heights, and with or without eaves on the top. In this paper, a parametric study with a total of 12 fence designs was carried out using a two-dimensional model of a train standing on a viaduct. To asses the relative effectiveness of sheltering devices, tests were done in a wind tunnel with a scaled model at a Reynolds number of 1 × 105, and the train’s aerodynamic coefficients were measured. Experimental results were compared with those predicted by Unsteady Reynolds-averaged Navier-Stokes (URANS) simulations of flow, showing that a computational model is able to satisfactorily predict the trend of the aerodynamic coefficients. In a second set of tests, the Reynolds number was increased to 12 × 106 (at a free flow air velocity of 30 m/s) in order to simulate strong wind conditions. The aerodynamic coefficients showed a similar trend for both Reynolds numbers; however, their numerical value changed enough to indicate that simulations at the lower Reynolds number do not provide all required information. Furthermore, the variation of coefficients in the simulations allowed an explanation of how fences modified the flow around the vehicle to be proposed. This made it clear why increasing fence height reduced all the coefficients but adding an eave had an effect mainly on the lift force coefficient. Finally, by analysing the time signals it was possible to clarify the influence of the Reynolds number on the peak-to-peak amplitude, the time period and the Strouhal number.

A general fractional porous medium equation

A general fractional porous medium equation

Initial design with L2 Monge-Kantorovich theory for the Monge–Ampère equation method of freeform optics

The Monge–Ampère (MA) equation arising in illumination design is highly nonlinear so that the convergence of the MA method is strongly determined by the initial design. We address the initial design of the MA method in this paper with the L2 Monge-Kantorovich (LMK) theory, and introduce an efficient approach for finding the optimal mapping of the LMK problem. Three examples, including the beam shaping of collimated beam and point light source, are given to illustrate the potential benefits of the LMK theory in the initial design. The results show the MA method converges more stably and faster with the application of the LMK theory in the initial design.

Desarrollo de estructuras nanofotonicas de campo cercano para intensificacion localizada de luz en celulas solares de banda intermedia - Near-field nanophotonic structures for localized light enhancement in intermediate band solar cells

This doctoral thesis explores some of the possibilities that near-field optics can bring to photovoltaics, and in particular to quantum-dot intermediate band solar cells (QD-IBSCs). Our main focus is the analytical optimization of the electric field distribution produced in the vicinity of single scattering particles, in order to produce the highest possible absorption enhancement in the photovoltaic medium in their surroundings. Near-field scattering structures have also been fabricated in laboratory, allowing the application of the previously studied theoretical concepts to real devices. We start by looking into the electrostatic scattering regime, which is only applicable to sub-wavelength sized particles. In this regime it was found that metallic nano-spheroids can produce absorption enhancements of about two orders of magnitude on the material in their vicinity, due to their strong plasmonic resonance. The frequency of such resonance can be tuned with the shape of the particles, allowing us to match it with the optimal transition energies of the intermediate band material. Since these metallic nanoparticles (MNPs) are to be inserted inside the cell photovoltaic medium, they should be coated by a thin insulating layer to prevent electron-hole recombination at their surface. This analysis is then generalized, using an analytical separation-of-variables method implemented in Mathematica7.0, to compute scattering by spheroids of any size and material. This code allowed the study of the scattering properties of wavelengthsized particles (mesoscopic regime), and it was verified that in this regime dielectric spheroids perform better than metallic. The light intensity scattered from such dielectric spheroids can have more than two orders of magnitude than the incident intensity, and the focal region in front of the particle can be shaped in several ways by changing the particle geometry and/or material. Experimental work was also performed in this PhD to implement in practice the concepts studied in the analysis of sub-wavelength MNPs. A wet-coating method was developed to self-assemble regular arrays of colloidal MNPs on the surface of several materials, such as silicon wafers, amorphous silicon films, gallium arsenide and glass. A series of thermal and chemical tests have been performed showing what treatments the nanoparticles can withstand for their embedment in a photovoltaic medium. MNPs arrays are then inserted in an amorphous silicon medium to study the effect of their plasmonic near-field enhancement on the absorption spectrum of the material. The self-assembled arrays of MNPs constructed in these experiments inspired a new strategy for fabricating IBSCs using colloidal quantum dots (CQDs). Such CQDs can be deposited in self-assembled monolayers, using procedures similar to those developed for the patterning of colloidal MNPs. The use of CQDs to form the intermediate band presents several important practical and physical advantages relative to the conventional dots epitaxially grown by the Stranski-Krastanov method. Besides, this provides a fast and inexpensive method for patterning binary arrays of QDs and MNPs, envisioned in the theoretical part of this thesis, in which the MNPs act as antennas focusing the light in the QDs and therefore boosting their absorption

Near-field light focusing by wavelength-sized dielectric spheroids for photovoltaic applications

We explore the near-field concentration properties of dielectric spheroidal scatterers with sizes close to the wavelength, using an analytical separation-of-variables method. Such particles act as mesoscopic lenses whose physical parameters are optimized here for maximum scattered light enhancement in photovoltaic applications.

Absorption coefficient for the intraband transitions in quantum dot materials

In this paper, we present calculations of the absorption coefficient for transitions between the bound states of quantum dots grown within a semiconductor and the extended states of the conduction band. For completeness, transitions among bound states are also presented. In the separation of variables, single band k·p model is used in which most elements may be expressed analytically. The analytical formulae are collected in the appendix of this paper. It is concluded that the transitions are strong enough to provide a quick path to the conduction band for electrons pumped from the valence to the intermediate band

Decomposition driven interface evolution for layers of binary mixtures: I. Model dirivation and base states

A dynamical model is proposed to describe the coupled decomposition and profile evolution of a free surfacefilm of a binary mixture. An example is a thin film of a polymer blend on a solid substrate undergoing simultaneous phase separation and dewetting. The model is based on model-H describing the coupled transport of the mass of one component (convective Cahn-Hilliard equation) and momentum (Navier-Stokes-Korteweg equations) supplemented by appropriate boundary conditions at the solid substrate and the free surface. General transport equations are derived using phenomenological nonequilibrium thermodynamics for a general nonisothermal setting taking into account Soret and Dufour effects and interfacial viscosity for the internal diffuse interface between the two components. Focusing on an isothermal setting the resulting model is compared to literature results and its base states corresponding to homogeneous or vertically stratified flat layers are analyzed.

Reduced order modeling of three dimensional external aerodynamic flows

A method is presented to construct computationally efficient reduced-order models (ROMs) of three-dimensional aerodynamic flows around commercial aircraft components. The method is based on the proper orthogonal decomposition (POD) of a set of steady snapshots, which are calculated using an industrial solver based on some Reynolds averaged Navier-Stokes (RANS) equations. The POD-mode amplitudes are calculated by minimizing a residual defined from the Euler equations, even though the snapshots themselves are calculated from viscous equations. This makes the ROM independent of the peculiarities of the solver used to calculate the snapshots. Also, both the POD modes and the residual are calculated using points in the computational mesh that are concentrated in a close vicinity of the aircraft, which constitute a much smaller number than the total number of mesh points. Despite these simplifications, the method provides quite good approximations of the flow variables distributions in the whole computational domain, including the boundary layer attached to the aircraft surface and the wake. Thus, the method is both robust and computationally efficient, which is checked considering the aerodynamic flow around a horizontal tail plane, in the transonic range 0.4?Mach number?0.8, ?3°?angle of attack?3°.

Aerodynamic optimization of the ICE2 high-speed train nose using a genetic algorithm and metamodels

An aerodynamic optimization of the ICE 2 high-speed train nose in term of front wind action sensitivity is carried out in this paper. The nose is parametrically defined by Be?zier Curves, and a three-dimensional representation of the nose is obtained using thirty one design variables. This implies a more complete parametrization, allowing the representation of a real model. In order to perform this study a genetic algorithm (GA) is used. Using a GA involves a large number of evaluations before finding such optimal. Hence it is proposed the use of metamodels or surrogate models to replace Navier-Stokes solver and speed up the optimization process. Adaptive sampling is considered to optimize surrogate model fitting and minimize computational cost when dealing with a very large number of design parameters. The paper introduces the feasi- bility of using GA in combination with metamodels for real high-speed train geometry optimization.