Quasi-cylindrical approximation to the swirling flow in an atomizer chamber

A quasi-cylindrical approximation is used to analyse the axisymmetric swirling flow of a liquid with a hollow air core in the chamber of a pressure swirl atomizer. The liquid is injected into the chamber with an azimuthal velocity component through a number of slots at the periphery of one end of the chamber, and flows out as an anular sheet through a central orifice at the other end, following a conical convergence of the chamber wall. An effective inlet condition is used to model the effects of the slots and the boundary layer that develops at the nearby endwall of the chamber. An analysis is presented of the structure of the liquid sheet at the end of the exit orifice, where the flow becomes critical in the sense that upstream propagation of long-wave perturbations ceases to be possible. This nalysis leads to a boundary condition at the end of the orifice that is an extension of the condition of maximum flux used with irrotational models of the flow. As is well known, the radial pressure gradient induced by the swirling flow in the bulk of the chamber causes the overpressure that drives the liquid towards the exit orifice, and also leads to Ekman pumping in the boundary layers of reduced azimuthal velocity at the convergent wall of the chamber and at the wall opposite to the exit orifice. The numerical results confirm the important role played by the boundary layers. They make the thickness of the liquid sheet at the end of the orifice larger than predicted by rrotational models, and at the same time tend to decrease the overpressure required to pass a given flow rate through the chamber, because the large axial velocity in the boundary layers takes care of part of the flow rate. The thickness of the boundary layers increases when the atomizer constant (the inverse of a swirl number, proportional to the flow rate scaled with the radius of the exit orifice and the circulation around the air core) decreases. A minimum value of this parameter is found below which the layer of reduced azimuthal velocity around the air core prevents the pressure from increasing and steadily driving the flow through the exit orifice. The effects of other parameters not accounted for by irrotational models are also analysed in terms of their influence on the boundary layers.

Optimization of multidimensional cross-section tables for few-group core calculations

Multigroup diffusion codes for three dimensional LWR core analysis use as input data pre-generated homogenized few group cross sections and discontinuity factors for certain combinations of state variables, such as temperatures or densities. The simplest way of compiling those data are tabulated libraries, where a grid covering the domain of state variables is defined and the homogenized cross sections are computed at the grid points. Then, during the core calculation, an interpolation algorithm is used to compute the cross sections from the table values. Since interpolation errors depend on the distance between the grid points, a determined refinement of the mesh is required to reach a target accuracy, which could lead to large data storage volume and a large number of lattice transport calculations. In this paper, a simple and effective procedure to optimize the distribution of grid points for tabulated libraries is presented. Optimality is considered in the sense of building a non-uniform point distribution with the minimum number of grid points for each state variable satisfying a given target accuracy in k-effective. The procedure consists of determining the sensitivity coefficients of k-effective to cross sections using perturbation theory; and estimating the interpolation errors committed with different mesh steps for each state variable. These results allow evaluating the influence of interpolation errors of each cross section on k-effective for any combination of state variables, and estimating the optimal distance between grid points.

Optimal Piecewise Linear Function Approximation for GPU-based Applications

Many computer vision and human-computer interaction applications developed in recent years need evaluating complex and continuous mathematical functions as an essential step toward proper operation. However, rigorous evaluation of this kind of functions often implies a very high computational cost, unacceptable in real-time applications. To alleviate this problem, functions are commonly approximated by simpler piecewise-polynomial representations. Following this idea, we propose a novel, efficient, and practical technique to evaluate complex and continuous functions using a nearly optimal design of two types of piecewise linear approximations in the case of a large budget of evaluation subintervals. To this end, we develop a thorough error analysis that yields asymptotically tight bounds to accurately quantify the approximation performance of both representations. It provides an improvement upon previous error estimates and allows the user to control the trade-off between the approximation error and the number of evaluation subintervals. To guarantee real-time operation, the method is suitable for, but not limited to, an efficient implementation in modern Graphics Processing Units (GPUs), where it outperforms previous alternative approaches by exploiting the fixed-function interpolation routines present in their texture units. The proposed technique is a perfect match for any application requiring the evaluation of continuous functions, we have measured in detail its quality and efficiency on several functions, and, in particular, the Gaussian function because it is extensively used in many areas of computer vision and cybernetics, and it is expensive to evaluate.

Four-Band Hamiltonian for fast calculations in intermediate-band solar cells

The 8-dimensional Luttinger–Kohn–Pikus–Bir Hamiltonian matrix may be made up of four 4-dimensional blocks. A 4-band Hamiltonian is presented, obtained from making the non-diagonal blocks zero. The parameters of the new Hamiltonian are adjusted to fit the calculated effective masses and strained QD bandgap with the measured ones. The 4-dimensional Hamiltonian thus obtained agrees well with measured quantum efficiency of a quantum dot intermediate band solar cell and the full absorption spectrum can be calculated in about two hours using Mathematica© and a notebook. This is a hundred times faster than with the commonly-used 8-band Hamiltonian and is considered suitable for helping design engineers in the development of nanostructured solar cells.

Analysis by finite element calculations of light scattering in laser-textured AZO films for PV thin-film solar cells

In the thin-film photovoltaic industry, to achieve a high light scattering in one or more of the cell interfaces is one of the strategies that allow an enhancement of light absorption inside the cell and, therefore, a better device behavior and efficiency. Although chemical etching is the standard method to texture surfaces for that scattering improvement, laser light has shown as a new way for texturizing different materials, maintaining a good control of the final topography with a unique, clean, and quite precise process. In this work AZO films with different texture parameters are fabricated. The typical parameters used to characterize them, as the root mean square roughness or the haze factor, are discussed and, for deeper understanding of the scattering mechanisms, the light behavior in the films is simulated using a finite element method code. This method gives information about the light intensity in each point of the system, allowing the precise characterization of the scattering behavior near the film surface, and it can be used as well to calculate a simulated haze factor that can be compared with experimental measurements. A discussion of the validation of the numerical code, based in a comprehensive comparison with experimental data is included.

Nonhydrogenic exciton spectrum in perovskite CH3NH3PbI3

The excitons in the orthorhombic phase of the perovskite CH3NH3PbI3 are studied using the effective mass approximation. The electron–hole interaction is screened by a distance-dependent dielectric function, as described by the Haken potential or the Pollmann–Büttner potential. The energy spectrum and the eigenfunctions are calculated for both cases. The results show that the Pollmann–Büttner model, using the corresponding parameters obtained from ab initio calculations, provides better agreement with the experimental results.

The segmental approximation in multijunction solar cells

The segmental approach has been considered to analyze dark and light I-V curves. The photovoltaic (PV) dependence of the open-circuit voltage (Voc), the maximum power point voltage (Vm), the efficiency (?) on the photogenerated current (Jg), or on the sunlight concentration ratio (X), are analyzed, as well as other photovoltaic characteristics of multijunction solar cells. The characteristics being analyzed are split into monoexponential (linear in the semilogarithmic scale) portions, each of which is characterized by a definite value of the ideality factor A and preexponential current J0. The monoexponentiality ensures advantages, since at many steps of the analysis, one can use the analytical dependences instead of numerical methods. In this work, an experimental procedure for obtaining the necessary parameters has been proposed, and an analysis of GaInP/GaInAs/Ge triple-junction solar cell characteristics has been carried out. It has been shown that up to the sunlight concentration ratios, at which the efficiency maximum is achieved, the results of calculation of dark and light I-V curves by the segmental method fit well with the experimental data. An important consequence of this work is the feasibility of acquiring the resistanceless dark and light I-V curves, which can be used for obtaining the I-V curves characterizing the losses in the transport part of a solar cell.

A stochastic approximation algorithm with Markov chain Monte-Carlo method for incomplete data estimation problems

We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

Endothelin-induced conversion of embryonic heart muscle cells into impulse-conducting Purkinje fibers

A regular heart beat is dependent on a specialized network of pacemaking and conductive cells. There has been a longstanding controversy regarding the developmental origin of these cardiac tissues which also manifest neural-like properties. Recently, we have shown conclusively that during chicken embryogenesis, impulse-conducting Purkinje cells are recruited from myocytes in spatial association with developing coronary arteries. Here, we report that cultured embryonic myocytes convert to a Purkinje cell phenotype after exposure to the vascular cytokine, endothelin. This inductive response declined gradually during development. These results yield further evidence for a role of arteriogenesis in the induction of impulse-conducting Purkinje cells within the heart muscle lineage and also may provide a basis for tissue engineering of cardiac pacemaking and conductive cells.

Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7

We investigated the relative free energies of hapten binding to the germ line and mature forms of the 48G7 antibody Fab fragments by applying a continuum model to structures sampled from molecular dynamics simulations in explicit solvent. Reasonable absolute and very good relative free energies were obtained. As a result of nine somatic mutations that do not contact the hapten, the affinity-matured antibody binds the hapten >104 tighter than the germ line antibody. Energetic analysis reveals that van der Waals interactions and nonpolar contributions to solvation are similar and drive the formations of both the germ line and mature antibody–hapten complexes. Affinity maturation of the 48G7 antibody therefore appears to occur through reorganization of the combining site geometry in a manner that optimizes the balance of gaining favorable electrostatic interactions with the hapten and losing those with solvent during the binding process. As reflected by lower rms fluctuations in the antibody–hapten complex, the mature complex undergoes more restricted fluctuations than the germ line complex. The dramatically increased affinity of the 48G7 antibody over its germ line precursor is thus made possible by electrostatic optimization.

Electric field-induced reorganization of two-component supported bilayer membranes

Application of electric fields tangent to the plane of a confined patch of fluid bilayer membrane can create lateral concentration gradients of the lipids. A thermodynamic model of this steady-state behavior is developed for binary systems and tested with experiments in supported lipid bilayers. The model uses Flory’s approximation for the entropy of mixing and allows for effects arising when the components have different molecular areas. In the special case of equal area molecules the concentration gradient reduces to a Fermi–Dirac distribution. The theory is extended to include effects from charged molecules in the membrane. Calculations show that surface charge on the supporting substrate substantially screens electrostatic interactions within the membrane. It also is shown that concentration profiles can be affected by other intermolecular interactions such as clustering. Qualitative agreement with this prediction is provided by comparing phosphatidylserine- and cardiolipin-containing membranes.

Approximation algorithms

Increasing global competition, rapidly changing markets, and greater consumer awareness have altered the way in which corporations do business. To become more efficient, many industries have sought to model some operational aspects by gigantic optimization problems. It is not atypical to encounter models that capture 106 separate “yes” or “no” decisions to be made. Although one could, in principle, try all 2106 possible solutions to find the optimal one, such a method would be impractically slow. Unfortunately, for most of these models, no algorithms are known that find optimal solutions with reasonable computation times. Typically, industry must rely on solutions of unguaranteed quality that are constructed in an ad hoc manner. Fortunately, for some of these models there are good approximation algorithms: algorithms that produce solutions quickly that are provably close to optimal. Over the past 6 years, there has been a sequence of major breakthroughs in our understanding of the design of approximation algorithms and of limits to obtaining such performance guarantees; this area has been one of the most flourishing areas of discrete mathematics and theoretical computer science.

P2Y1 purinergic receptors in sensory neurons: contribution to touch-induced impulse generation.

Somatic sensation requires the conversion of physical stimuli into the depolarization of distal nerve endings. A single cRNA derived from sensory neurons renders Xenopus laevis oocytes mechanosensitive and is found to encode a P2Y1 purinergic receptor. P2Y1 mRNA is concentrated in large-fiber dorsal root ganglion neurons. In contrast, P2X3 mRNA is localized to small-fiber sensory neurons and produces less mechanosensitivity in oocytes. The frequency of touch-induced action potentials from frog sensory nerve fibers is increased by the presence of P2 receptor agonists at the peripheral nerve ending and is decreased by the presence of P2 antagonists. P2X-selective agents do not have these effects. The release of ATP into the extracellular space and the activation of peripheral P2Y1 receptors appear to participate in the generation of sensory action potentials by light touch.

Molecular mechanics calculations of the riboacetal internucleotide linkage in double and triple helices.

Structures of Watson-Crick base paired 15-nucleobase oligomer strands in A-type or B-type conformation in which one strand [a strand of alternating nucleotide and riboacetal thymidine nucleoside (RT) units, RP] is DNA and the other is composed of alternating nucleotides and riboacetal nucleosides have been studied by molecular mechanics. Analogously, oligomer strands of RNA in place of DNA have been modeled. The calculations indicate that the RP strand is more stable when complexed in an A-type duplex relative to a B-type form and that this conformational preference is presumably due to the more uniform nature of the former. Nearly planar ribose rings were more commonly observed in the minimized structures of the B-type DNA.RP duplexes as compared with A-type duplexes, despite the fact that planar ribofuranose rings are known to be energetically unfavorable in oligonucleotides. Computed relative stabilities of all duplexes containing the RP strand suggest that such heteroduplexes are less stable than the corresponding double-stranded DNA and double-stranded RNA species. These findings are in agreement with experimental results which show, when equivalent sequences were compared, that a DNA.RNA control forms a more stable duplex than RP hound to a complementary single-stranded RNA strand. In contrast, molecular mechanics studies of complementary triple-helical (DNA)2.RP, (DNA)2.DNA, and (DNA)2.RNA structures indicate that the binding of RP as a Hoogsteen strand stabilizes the underlying duplex to a greater extent compared with native oligonucleotides. These calculations suggest that puckering of the ribose ring in the riboacetal linkage leads to a more favorable interaction with a complementary nucleic acid target than the proposed planar geometry and that this puckering may account for the enhanced binding of RP to a double-stranded target.

Motor learning by field approximation.

We investigated how human subjects adapt to forces perturbing the motion of their ams. We found that this kind of learning is based on the capacity of the central nervous system (CNS) to predict and therefore to cancel externally applied perturbing forces. Our experimental results indicate: (i) that the ability of the CNS to compensate for the perturbing forces is restricted to those spatial locations where the perturbations have been experienced by the moving arm. The subjects also are able to compensate for forces experienced at neighboring workspace locations. However, adaptation decays smoothly and quickly with distance from the locations where disturbances had been sensed by the moving limb. (ii) Our experiments also how that the CNS builds an internal model of the external perturbing forces in intrinsic (muscles and / or joints) coordinates.