215 resultados para kernel density estimator
Resumo:
A direct numerical simulation (DNS) database of freely propagating statistically planar turbulent premixed flames with a range of different turbulent Reynolds numbers has been used to assess the performance of algebraic flame surface density (FSD) models based on a fractal representation of the flame wrinkling factor. The turbulent Reynolds number Ret has been varied by modifying the Karlovitz number Ka and the Damköhler number Da independently of each other in such a way that the flames remain within the thin reaction zones regime. It has been found that the turbulent Reynolds number and the Karlovitz number both have a significant influence on the fractal dimension, which is found to increase with increasing Ret and Ka before reaching an asymptotic value for large values of Ret and Ka. A parameterisation of the fractal dimension is presented in which the effects of the Reynolds and the Karlovitz numbers are explicitly taken into account. By contrast, the inner cut-off scale normalised by the Zel'dovich flame thickness ηi/δz does not exhibit any significant dependence on Ret for the cases considered here. The performance of several algebraic FSD models has been assessed based on various criteria. Most of the algebraic models show a deterioration in performance with increasing the LES filter width. © 2012 Mohit Katragadda et al.
Resumo:
The law for turbulent entrainment due to plumes and jets impinging on a density interface is subject to significant uncertainty, with reported differences in entrainment rates up to a factor of 10. We report preliminary results obtained by Direct Numerical Simulation which are part of a PRACE project on turbulent entrainment carried out on JUGENE at Jülich, Germany. Various interface tracking methods are discussed and the entrainment coefficient is determined.
Resumo:
We present an alternative method of producing density stratifications in the laboratory based on the 'double-tank' method proposed by Oster (Sci Am 213:70-76, 1965). We refer to Oster's method as the 'forced-drain' approach, as the volume flow rates between connecting tanks are controlled by mechanical pumps. We first determine the range of density profiles that may be established with the forced-drain approach other than the linear stratification predicted by Oster. The dimensionless density stratification is expressed analytically as a function of three ratios: the volume flow rate ratio n, the ratio of the initial liquid volumes λ and the ratio of the initial densities ψ. We then propose a method which does not require pumps to control the volume flow rates but instead allows the connecting tanks to drain freely under gravity. This is referred to as the 'free-drain' approach. We derive an expression for the density stratification produced and compare our predictions with saline stratifications established in the laboratory using the 'free-drain' extension of Oster's method. To assist in the practical application of our results we plot the region of parameter space that yield concave/convex or linear density profiles for both forced-drain and free-drain approaches. The free-drain approach allows the experimentalist to produce a broad range of density profiles by varying the initial liquid depths, cross-sectional and drain opening areas of the tanks. One advantage over the original Oster approach is that density profiles with an inflexion point can now be established. © 2008 Springer-Verlag.
Resumo:
A highly sensitive nonenzymatic amperometric glucose sensor was fabricated by using Ni nanoparticles homogeneously dispersed within and on the top of a vertically aligned CNT forest (CNT/Ni nanocomposite sensor), which was directly grown on a Si/SiO2 substrate. The surface morphology and elemental analysis were characterized using scanning electron microscopy and energy dispersive spectroscopy, respectively. Cyclic voltammetry and chronoamperometry were used to evaluate the catalytic activities of CNT/Ni electrode. The CNT/Ni nanocomposite sensor exhibited a great enhancement of anodic peak current after adding 5 mM glucose in alkaline solution. The sensor can also be applied to the quantification of glucose content with a linear range covering from 5 μM to 7 mM, a high sensitivity of 1433 μA mM-1 cm-2, and a low detection limit of 2 μM. The CNT/Ni nanocomposite sensor exhibits good reproducibility and long-term stability, moreover, it was also relatively insensitive to commonly interfering species, such as uric acid, ascorbic acid, acetaminophen, sucrose and d-fructose. © 2013 Elsevier B.V.
Resumo:
Despite its importance, choosing the structural form of the kernel in nonparametric regression remains a black art. We define a space of kernel structures which are built compositionally by adding and multiplying a small number of base kernels. We present a method for searching over this space of structures which mirrors the scientific discovery process. The learned structures can often decompose functions into interpretable components and enable long-range extrapolation on time-series datasets. Our structure search method outperforms many widely used kernels and kernel combination methods on a variety of prediction tasks.
Resumo:
Quantile regression refers to the process of estimating the quantiles of a conditional distribution and has many important applications within econometrics and data mining, among other domains. In this paper, we show how to estimate these conditional quantile functions within a Bayes risk minimization framework using a Gaussian process prior. The resulting non-parametric probabilistic model is easy to implement and allows non-crossing quantile functions to be enforced. Moreover, it can directly be used in combination with tools and extensions of standard Gaussian Processes such as principled hyperparameter estimation, sparsification, and quantile regression with input-dependent noise rates. No existing approach enjoys all of these desirable properties. Experiments on benchmark datasets show that our method is competitive with state-of-the-art approaches. © 2009 IEEE.
Resumo:
Hafnium oxide (HfOx) is a high dielectric constant (k) oxide which has been identified as being suitable for use as the gate dielectric in thin film transistors (TFTs). Amorphous materials are preferred for a gate dielectric, but it has been an ongoing challenge to produce amorphous HfOx while maintaining a high dielectric constant. A technique called high target utilization sputtering (HiTUS) is demonstrated to be capable of depositing high-k amorphous HfOx thin films at room temperature. The plasma is generated in a remote chamber, allowing higher rate deposition of films with minimal ion damage. Compared to a conventional sputtering system, the HiTUS technique allows finer control of the thin film microstructure. Using a conventional reactive rf magnetron sputtering technique, monoclinic nanocrystalline HfOx thin films have been deposited at a rate of ∼1.6nmmin-1 at room temperature, with a resistivity of 1013Ωcm, a breakdown strength of 3.5MVcm-1 and a dielectric constant of ∼18.2. By comparison, using the HiTUS process, amorphous HfOx (x=2.1) thin films which appear to have a cubic-like short-range order have been deposited at a high deposition rate of ∼25nmmin-1 with a high resistivity of 1014Ωcm, a breakdown strength of 3MVcm-1 and a high dielectric constant of ∼30. Two key conditions must be satisfied in the HiTUS system for high-k HfOx to be produced. Firstly, the correct oxygen flow rate is required for a given sputtering rate from the metallic target. Secondly, there must be an absence of energetic oxygen ion bombardment to maintain an amorphous microstructure and a high flux of medium energy species emitted from the metallic sputtering target to induce a cubic-like short range order. This HfOx is very attractive as a dielectric material for large-area electronic applications on flexible substrates. A remote plasma sputtering process (high target utilization sputtering, HiTUS) has been used to deposit amorphous hafnium oxide with a very high dielectric constant (∼30). X-ray diffraction shows that this material has a microstructure in which the atoms have a cubic-like short-range order, whereas radio frequency (rf) magnetron sputtering produced a monoclinic polycrystalline microstructure. This is correlated to the difference in the energetics of remote plasma and rf magnetron sputtering processes. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Resumo:
Bulk, polycrystalline MgB2 samples containing 2.5 wt.% multi-walled carbon nanotubes (CNTs) have been prepared by conventional solid state reaction at 800 °C. The effect of Mg precursor powders composed of two different particle sizes on the critical current density (Jc) of the as-sintered samples has been investigated. An enhancement of Jc at high field has been observed in MgB2 samples containing CNTs prepared with fine Mg powders, whereas the values of Jc in the sample prepared using the coarser Mg powders was slightly decreased. These results contrast significantly with measurements on pure, undoped, MgB2 samples prepared from the same Mg precursor powders. They suggest that carbon substitution into the MgB2 lattice, which accounts for increased flux pinning, and therefore Jc, is more effective in precursor Mg powders with a larger surface area. Rather surprisingly, the so-called fishtail effect, observed typically in MgB2 single crystals and in the (RE)BCO family of high temperature superconductors (HTSs), was observed in both sets of CNT-containing polycrystalline samples as a result of lattice defects associated with C substitution. Significantly, analytical fits to the data for each sample suggest that the same flux pinning mechanism accounts for the fishtail effect in polycrystalline MgB2 and (RE)BCO. © 2013 Elsevier B.V. All rights reserved.