967 resultados para Models : mixing length
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We perform simulations of several convective events over the southern UK with the Met Office Unified Model (UM) at horizontal grid lengths ranging from 1.5 km to 200 m. Comparing the simulated storms on these days with the Met Office rainfall radar network allows us to apply a statistical approach to evaluate the properties and evolution of the simulated storms over a range of conditions. Here we present results comparing the storm morphology in the model and reality which show that the simulated storms become smaller as grid length decreases and that the grid length that fits the observations best changes with the size of the observed cells. We investigate the sensitivity of storm morphology in the model to the mixing length used in the subgrid turbulence scheme. As the subgrid mixing length is decreased, the number of small storms with high area-averaged rain rates increases. We show that by changing the mixing length we can produce a lower resolution simulation that produces similar morphologies to a higher resolution simulation.
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De nouveaux modèles d'atmosphère sont présentés, incluant les profils de raie d'hélium neutre améliorés de Beauchamp (1995) et le formalisme de probabilité d'occupation pour ce même atome. Ces modèles sont utilisés pour calculer une grille de spectres synthétiques correspondant à des atmosphères riches en hélium et contenant des traces d'hydrogène. Cette grille est utilisée pour déterminer les paramètres atmosphériques principaux des étoiles de notre échantillon, soient la température effective, la gravité de surface et l'abondance d'hydrogène. Notre échantillon contient des spectres visibles de haut rapport signal-sur-bruit pour 102 naines blanches riches en hélium, dont 29 ont été observés au cours de ce projet, ce qui en fait le plus grand échantillon de spectres de qualité de naines blanches riches en hélium. Des spectres synthétiques ont été calculés en utilisant différentes valeurs du paramètre α de la théorie de la longueur de mélange dans le but de calibrer empiriquement la valeur de ce paramètre pour les DB. Afin d'améliorer la précision sur les paramètres atmosphériques de quelques étoiles, nous avons utilisé des spectres couvrant la raie Hα pour mieux déterminer l'abondance d'hydrogène. Finalement, nous avons calculé la distribution de masse de notre échantillon et la fonction de luminosité des DB. La distribution de masse montre une coupure à 0.5 fois la masse solaire qui est prédite par les modèles d'évolution stellaire et dévoile une masse moyenne significativement plus élevée pour les étoiles de type DBA. La masse moyenne de l'ensemble des DB et DBA est très proche de celle des DA. La fonction de luminosité nous permet de calculer que le rapport du nombre de DB sur le nombre de DA vaut environ 25%.
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A new frontier in weather forecasting is emerging by operational forecast models now being run at convection-permitting resolutions at many national weather services. However, this is not a panacea; significant systematic errors remain in the character of convective storms and rainfall distributions. The DYMECS project (Dynamical and Microphysical Evolution of Convective Storms) is taking a fundamentally new approach to evaluate and improve such models: rather than relying on a limited number of cases, which may not be representative, we have gathered a large database of 3D storm structures on 40 convective days using the Chilbolton radar in southern England. We have related these structures to storm life-cycles derived by tracking features in the rainfall from the UK radar network, and compared them statistically to storm structures in the Met Office model, which we ran at horizontal grid length between 1.5 km and 100 m, including simulations with different subgrid mixing length. We also evaluated the scale and intensity of convective updrafts using a new radar technique. We find that the horizontal size of simulated convective storms and the updrafts within them is much too large at 1.5-km resolution, such that the convective mass flux of individual updrafts can be too large by an order of magnitude. The scale of precipitation cores and updrafts decreases steadily with decreasing grid lengths, as does the typical storm lifetime. The 200-m grid-length simulation with standard mixing length performs best over all diagnostics, although a greater mixing length improves the representation of deep convective storms.
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In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ε model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ε model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. 3DVAR allows also to identify and quantify shortcomings of the numerical model. Such comprehensive analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows.
Local numerical modelling of magnetoconvection and turbulence - implications for mean-field theories
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During the last decades mean-field models, in which large-scale magnetic fields and differential rotation arise due to the interaction of rotation and small-scale turbulence, have been enormously successful in reproducing many of the observed features of the Sun. In the meantime, new observational techniques, most prominently helioseismology, have yielded invaluable information about the interior of the Sun. This new information, however, imposes strict conditions on mean-field models. Moreover, most of the present mean-field models depend on knowledge of the small-scale turbulent effects that give rise to the large-scale phenomena. In many mean-field models these effects are prescribed in ad hoc fashion due to the lack of this knowledge. With large enough computers it would be possible to solve the MHD equations numerically under stellar conditions. However, the problem is too large by several orders of magnitude for the present day and any foreseeable computers. In our view, a combination of mean-field modelling and local 3D calculations is a more fruitful approach. The large-scale structures are well described by global mean-field models, provided that the small-scale turbulent effects are adequately parameterized. The latter can be achieved by performing local calculations which allow a much higher spatial resolution than what can be achieved in direct global calculations. In the present dissertation three aspects of mean-field theories and models of stars are studied. Firstly, the basic assumptions of different mean-field theories are tested with calculations of isotropic turbulence and hydrodynamic, as well as magnetohydrodynamic, convection. Secondly, even if the mean-field theory is unable to give the required transport coefficients from first principles, it is in some cases possible to compute these coefficients from 3D numerical models in a parameter range that can be considered to describe the main physical effects in an adequately realistic manner. In the present study, the Reynolds stresses and turbulent heat transport, responsible for the generation of differential rotation, were determined along the mixing length relations describing convection in stellar structure models. Furthermore, the alpha-effect and magnetic pumping due to turbulent convection in the rapid rotation regime were studied. The third area of the present study is to apply the local results in mean-field models, which task we start to undertake by applying the results concerning the alpha-effect and turbulent pumping in mean-field models describing the solar dynamo.
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Reynolds averaged Navier-Stokes model performances in the stagnation and wake regions for turbulent flows with relatively large Lagrangian length scales (generally larger than the scale of geometrical features) approaching small cylinders (both square and circular) is explored. The effective cylinder (or wire) diameter based Reynolds number, ReW ≤ 2.5 × 103. The following turbulence models are considered: a mixing-length; standard Spalart and Allmaras (SA) and streamline curvature (and rotation) corrected SA (SARC); Secundov's νt-92; Secundov et al.'s two equation νt-L; Wolfshtein's k-l model; the Explicit Algebraic Stress Model (EASM) of Abid et al.; the cubic model of Craft et al.; various linear k-ε models including those with wall distance based damping functions; Menter SST, k-ω and Spalding's LVEL model. The use of differential equation distance functions (Poisson and Hamilton-Jacobi equation based) for palliative turbulence modeling purposes is explored. The performance of SA with these distance functions is also considered in the sharp convex geometry region of an airfoil trailing edge. For the cylinder, with ReW ≈ 2.5 × 103 the mixing length and k-l models give strong turbulence production in the wake region. However, in agreement with eddy viscosity estimates, the LVEL and Secundov νt-92 models show relatively little cylinder influence on turbulence. On the other hand, two equation models (as does the one equation SA) suggest the cylinder gives a strong turbulence deficit in the wake region. Also, for SA, an order or magnitude cylinder diameter decrease from ReW = 2500 to 250 surprisingly strengthens the cylinder's disruptive influence. Importantly, results for ReW ≪ 250 are virtually identical to those for ReW = 250 i.e. no matter how small the cylinder/wire its influence does not, as it should, vanish. Similar tests for the Launder-Sharma k-ε, Menter SST and k-ω show, in accordance with physical reality, the cylinder's influence diminishing albeit slowly with size. Results suggest distance functions palliate the SA model's erroneous trait and improve its predictive performance in wire wake regions. Also, results suggest that, along the stagnation line, such functions improve the SA, mixing length, k-l and LVEL results. For the airfoil, with SA, the larger Poisson distance function increases the wake region turbulence levels by just under 5%. © 2007 Elsevier Inc. All rights reserved.
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The computation of both transient and steady turbulent incompressible isothermal flows is studied. The flow is very complex, having streamline curvature, large vortex structures and stagnation resulting from an impinging rectangular jet. For transient computations, the standard k-ε model is adopted. For steady flows, the k-ε, high and low Reynolds number k-l and mixing length models are tried. Zonal approaches combining the above turbulence models are also investigated. None of the models are found to give satisfactory agreement with velocity measurements.
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We show that a simple mixing idea allows one to establish a number of explicit formulas for ruin probabilities and related quantities in collective risk models with dependence among claim sizes and among claim inter-occurrence times. Examples include compound Poisson risk models with completely monotone marginal claim size distributions that are dependent according to Archimedean survival copulas as well as renewal risk models with dependent inter-occurrence times.
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Le but de cette thèse est de raffiner et de mieux comprendre l'utilisation de la méthode spectroscopique, qui compare des spectres visibles de naines blanches à atmosphère riche en hydrogène (DA) à des spectres synthétiques pour en déterminer les paramètres atmosphériques (température effective et gravité de surface). Notre approche repose principalement sur le développement de modèles de spectres améliorés, qui proviennent eux-mêmes de modèles d'atmosphère de naines blanches de type DA. Nous présentons une nouvelle grille de spectres synthétiques de DA avec la première implémentation cohérente de la théorie du gaz non-idéal de Hummer & Mihalas et de la théorie unifiée de l'élargissement Stark de Vidal, Cooper & Smith. Cela permet un traitement adéquat du chevauchement des raies de la série de Balmer, sans la nécessité d'un paramètre libre. Nous montrons que ces spectres améliorés prédisent des gravités de surface qui sont plus stables en fonction de la température effective. Nous étudions ensuite le problème de longue date des gravités élevées pour les DA froides. L'hypothèse de Bergeron et al., selon laquelle les atmosphères sont contaminées par de l'hélium, est confrontée aux observations. À l'aide de spectres haute résolution récoltés au télescope Keck à Hawaii, nous trouvons des limites supérieures sur la quantité d'hélium dans les atmosphères de près de 10 fois moindres que celles requises par le scénario de Bergeron et al. La grille de spectres conçue dans ces travaux est ensuite appliquée à une nouvelle analyse spectroscopique de l'échantillon de DA du SDSS. Notre approche minutieuse permet de définir un échantillon plus propre et d'identifier un nombre important de naines blanches binaires. Nous déterminons qu'une coupure à un rapport signal-sur-bruit S/N > 15 optimise la grandeur et la qualité de l'échantillon pour calculer la masse moyenne, pour laquelle nous trouvons une valeur de 0.613 masse solaire. Finalement, huit nouveaux modèles 3D de naines blanches utilisant un traitement d'hydrodynamique radiative de la convection sont présentés. Nous avons également calculé des modèles avec la même physique, mais avec une traitement standard 1D de la convection avec la théorie de la longueur de mélange. Un analyse différentielle entre ces deux séries de modèles montre que les modèles 3D prédisent des gravités considérablement plus basses. Nous concluons que le problème des gravités élevées dans les naines blanches DA froides est fort probablement causé par une faiblesse dans la théorie de la longueur de mélange.
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Observed and predicted changes in the strength of the westerly winds blowing over the Southern Ocean have motivated a number of studies of the response of the Antarctic Circumpolar Current and Southern Ocean Meridional Overturning Circulation (MOC) to wind perturbations and led to the discovery of the``eddy-compensation" regime, wherein the MOC becomes insensitive to wind changes. In addition to the MOC, tracer transport also depends on mixing processes. Here we show, in a high-resolution process model, that isopycnal mixing by mesoscale eddies is strongly dependent on the wind strength. This dependence can be explained by mixing-length theory and is driven by increases in eddy kinetic energy; the mixing length does not change strongly in our simulation. Simulation of a passive ventilation tracer (analogous to CFCs or anthropogenic CO$_2$) demonstrates that variations in tracer uptake across experiments are dominated by changes in isopycnal mixing, rather than changes in the MOC. We argue that, to properly understand tracer uptake under different wind-forcing scenarios, the sensitivity of isopycnal mixing to winds must be accounted for.
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Simple first-order closure remains an attractive way of formulating equations for complex canopy flows when the aim is to find analytic or simple numerical solutions to illustrate fundamental physical processes. Nevertheless, the limitations of such closures must be understood if the resulting models are to illuminate rather than mislead. We propose five conditions that first-order closures must satisfy then test two widely used closures against them. The first is the eddy diffusivity based on a mixing length. We discuss the origins of this approach, its use in simple canopy flows and extensions to more complex flows. We find that it satisfies most of the conditions and, because the reasons for its failures are well understood, it is a reliable methodology. The second is the velocity-squared closure that relates shear stress to the square of mean velocity. Again we discuss the origins of this closure and show that it is based on incorrect physical principles and fails to satisfy any of the five conditions in complex canopy flows; consequently its use can lead to actively misleading conclusions.
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The structure of the atmospheric boundary layer (ABL) is modelled with the limited- length-scale k-ε model of Apsley and Castro. Contrary to the standard k-ε model, the limited-length-scale k-ε model imposes a maximum mixing length which is derived from the boundary layer height, for neutral and unstable atmospheric situations, or by Monin-Obukhov length when the atmosphere is stably stratified. The model is first verified reproducing the famous Leipzig wind profile. Then the performance of the model is tested with measurements from FINO-1 platform using sonic anemometers to derive the appropriate maximum mixing length.
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Many instances of differential diffusion, i e, different species having different turbulent diffusion coefficients in the same flow, can be explained as a finite mixing length effect. That is, in a simple mixing length scenario, the turbulent diffusion coefficient has the form 1 ( m )2 m m c l K w l OL = + where, wm is the mixing velocity, lm the mixing length and Lc the overall distribution scale for a particular species. The first term represents the familiar gradient diffusion while the second term becomes important when lm/Lc is finite. This second term shows that different species will have different diffusion coefficients if they have different overall distribution scales. Such different Lcs may come about due to different boundary conditions and different intrinsic properties (molecular diffusivity, settling velocity etc) for different species. For momentum transfer in turbulent oscillatory boundary layers the second term is imaginary and explains observed phase leads of shear stresses ahead of velocity gradients.
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The present paper motivates the study of mind change complexity for learning minimal models of length-bounded logic programs. It establishes ordinal mind change complexity bounds for learnability of these classes both from positive facts and from positive and negative facts. Building on Angluin’s notion of finite thickness and Wright’s work on finite elasticity, Shinohara defined the property of bounded finite thickness to give a sufficient condition for learnability of indexed families of computable languages from positive data. This paper shows that an effective version of Shinohara’s notion of bounded finite thickness gives sufficient conditions for learnability with ordinal mind change bound, both in the context of learnability from positive data and for learnability from complete (both positive and negative) data. Let Omega be a notation for the first limit ordinal. Then, it is shown that if a language defining framework yields a uniformly decidable family of languages and has effective bounded finite thickness, then for each natural number m >0, the class of languages defined by formal systems of length <= m: • is identifiable in the limit from positive data with a mind change bound of Omega (power)m; • is identifiable in the limit from both positive and negative data with an ordinal mind change bound of Omega × m. The above sufficient conditions are employed to give an ordinal mind change bound for learnability of minimal models of various classes of length-bounded Prolog programs, including Shapiro’s linear programs, Arimura and Shinohara’s depth-bounded linearly covering programs, and Krishna Rao’s depth-bounded linearly moded programs. It is also noted that the bound for learning from positive data is tight for the example classes considered.