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For the calculation of turbulent mixing in the bottom boundary layer, we present simple analytical tools for the mixing velocity wm and the mixing length lm. Based on observations of turbulence intensity measurements, the mixing velocity wm…

Geophysics · Physics 2011-04-05 Rafik Absi

Despite its limitations, Prandtl's mixing length model is widely applied in modelling turbulent free shear flows. Prandtl's extended model addresses many of the shortfalls of the original model, but is not so widely used, in part due to…

Fluid Dynamics · Physics 2021-04-07 AJ Hutchinson , N Hale , K Born , DP Mason

The saturation length of aeolian sand transport ($L_s$), characterizing the distance needed by wind-blown sand to adapt to changes in the wind shear, is essential for accurate modeling of the morphodynamics of Earth's sandy landscapes and…

Atmospheric and Oceanic Physics · Physics 2015-08-19 Thomas Pähtz , Amir Omeradžić , Marcus V. Carneiro , Nuno A. M. Araújo , Hans J. Herrmann

The aim of our study is to improve the description of suspended sediment transport over wave ripples. We will first show the importance of sediment diffusivity with convective transfer (hereafter called) which is different from the sediment…

Classical Physics · Physics 2011-05-13 Rafik Absi

Since the introduction of the logarithmic law of the wall more than 80 years ago, the equation for the mean velocity profile in turbulent boundary layers has been widely applied to model near-surface processes and parameterise surface drag.…

Fluid Dynamics · Physics 2020-02-07 Michael Heisel , Charitha M. de Silva , Nicholas Hutchins , Ivan Marusic , Michele Guala

The transverse and longitudinal current correlation functions are evaluated in liquid and amorphous sodium by computer simulation. The study of the corresponding spectra as a function of the wavevector $k$ allows the evaluation of a…

Soft Condensed Matter · Physics 2015-09-11 Giulia De Lorenzi-Venneri , Renzo Vallauri

We apply the results of Andresen A. and Spokoiny V. on profile M-estimators and the alternating maximization procedure to analyse a sieve profile quasi maximum likelihood estimator in the single index model with linear index function. The…

Statistics Theory · Mathematics 2015-02-25 Andreas Andresen

The Monin--Obukhov similarity theory-based wind speed and potential temperature profiles are inherently coupled to each other. We have developed hybrid approaches to disentangle them, and as a direct consequence, the estimation of Obukhov…

Atmospheric and Oceanic Physics · Physics 2018-09-10 Sukanta Basu

Sand production is an important issue for many hydrocarbon recovery applications in unconsolidated reservoirs. The model using the Computational Fluid Dynamics coupled with Discrete Element Method (CFD-DEM) can capture micro-scale features…

Computational Engineering, Finance, and Science · Computer Science 2022-11-14 Daniyar Kazidenov , Furkhat Khamitov , Yerlan Amanbek

Theoretical calculations of the mixed aggregation/coalescence (kFC) rate corresponding to a set of hexadecane-in-water nano-emulsions stabilized with sodium dodecyl sulphate (SDS) at different NaCl concentrations are presented. The rates…

Soft Condensed Matter · Physics 2015-07-08 German Urbina-Villalba , Neyda Garcia-Valera , Kareem Rahn-Chique

Sediment transport over wave-induced ripples is a very complex phenomenon where available models fail to provide accurate predictions. For coastal engineering applications, the 1-DV advection-diffusion equation could be used with an…

Geophysics · Physics 2011-06-07 Rafik Absi , Hitoshi Tanaka

Existence of a solution to the quasi-variational inequality problem arising in a model for sand surface evolution has been an open problem for a long time. Another long-standing open problem concerns determining the dual variable, the flux…

Analysis of PDEs · Mathematics 2012-03-09 John W. Barrett , Leonid Prigozhin

A new mixed scaling parameter $Z=z/\sqrt{Lh}$ is proposed for similarity in the stable atmospheric surface layer, where $z$ is the height, $L$ is the Obukhov length, and $h$ is the boundary layer depth. Compared to the parameter $\zeta =…

Atmospheric and Oceanic Physics · Physics 2023-09-01 Michael Heisel , Marcelo Chamecki

In this paper, we present a new ensemble-based filter method by reconstructing the analysis step of the particle filter through a transport map, which directly transports prior particles to posterior particles. The transport map is…

Machine Learning · Statistics 2026-05-14 Dengfei Zeng , Lijian Jiang

We present an analytical model of aeolian sand transport. The model quantifies the momentum transfer from the wind to the transported sand by providing expressions for the thickness of the saltation layer and the apparent surface roughness.…

Soft Condensed Matter · Physics 2019-09-20 Thomas Pähtz , Jasper F. Kok , Hans J. Herrmann

Mixture distributions with dynamic weights are an efficient way of modeling loss data characterized by heavy tails. However, maximum likelihood estimation of this family of models is difficult, mostly because of the need to evaluate…

Methodology · Statistics 2023-04-11 Marco Bee

We show how to evaluate mobility profiles, characterizing the transport of confined fluids under a perturbation, from equilibrium molecular simulations. The correlation functions derived with the Green-Kubo formalism are difficult to sample…

Chemical Physics · Physics 2020-08-26 Etienne Mangaud , Benjamin Rotenberg

We derive a two-layer depth-averaged model of sediment transport and morphological evolution for application to bedload-dominated problems. The near bed transport region is represented by the lower (bedload) layer which has an arbitrarily…

Fluid Dynamics · Physics 2019-08-12 Sergio Maldonado , Alistair G. L. Borthwick

The reconstruction of smooth density fields from scattered data points is a procedure that has multiple applications in a variety of disciplines, including Lagrangian (particle-based) models of solute transport in fluids. In random walk…

Computational Physics · Physics 2019-09-04 Guillem Sole-Mari , Diogo Bolster , Daniel Fernàndez-Garcia , Xavier Sanchez-Vila

Kalman filters constitute a scalable and robust methodology for approximate Bayesian inference, matching first and second order moments of the target posterior. To improve the accuracy in nonlinear and non-Gaussian settings, we extend this…

Statistics Theory · Mathematics 2024-09-04 L. Wang , N. Nüsken
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