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Sampling-based motion planning algorithms are widely used in robotics because they are very effective in high-dimensional spaces. However, the success rate and quality of the solutions are determined by an adequate selection of their…

A theory of the probability distribution function (PDF) tails of the blob density in plasma edge turbulence is provided. A simplified model of the fast convective radial transport is used. The theoretically predicted PDF tails corroborate…

Plasma Physics · Physics 2009-11-13 Johan Anderson , Eun-jin Kim

We focus on the probability distribution function (pdf) $P(\Delta \gamma; \gamma)$ where $\Delta \gamma$ are the {\em measured} strain intervals between plastic events in an athermal strained amorphous solids, and $\gamma$ measures the…

Soft Condensed Matter · Physics 2016-01-20 H. G. E. Hentschel , Prabhat K. Jaiswal , Itamar Procaccia , Srikanth Sastry

Eulerian-Lagrangian models of particle-laden (multiphase) flows describe fluid flow and particle dynamics in the Eulerian and Lagrangian frameworks respectively. Regardless of whether the flow is turbulent or laminar, the particle dynamics…

According to modern developments in turbulence theory, the "dissipation" scales (u.v. cut-offs) $\eta$ form a random field related to velocity increments $\delta_{\eta}u$. In this work we, using Mellin's transform combined with the Gaussain…

Fluid Dynamics · Physics 2009-11-11 Victor Yakhot

In this work, we study non-parametric estimation of joint probabilities of a given set of discrete and continuous random variables from their (empirically estimated) 2D marginals, under the assumption that the joint probability could be…

Machine Learning · Computer Science 2022-03-04 Shaan ul Haque , Ajit Rajwade , Karthik S. Gurumoorthy

Conditional statistics of homogeneous isotropic turbulent flow is investigated by means of high-Reynolds number direct numerical simulations performed with $2048^3$ collocation points. Eulerian as well as Lagrangian velocity increment…

Fluid Dynamics · Physics 2015-05-20 Holger Homann , Daniel Schulz , Rainer Grauer

Based on the canonical correlation analysis we derive series representations of the probability density function (PDF) and the cumulative distribution function (CDF) of the information density of arbitrary Gaussian random vectors as well as…

Information Theory · Computer Science 2022-07-13 Jonathan Huffmann , Martin Mittelbach

Performing likelihood ratio based detection with high dimensional multimodal data is a challenging problem since the computation of the joint probability density functions (pdfs) in the presence of inter-modal dependence is difficult. While…

Information Theory · Computer Science 2016-09-19 Thakshila Wimalajeewa , Pramod K. Varshney

We investigate the upscaling of diffusive transport parameters as function of pore scale material structure using a stochastic framework. We focus on sub-REV (representative elementary volume) scale where the complexity of pore space…

Materials Science · Physics 2021-06-21 Alraune Zech , Matthijs de Winter

In this study, we develop a probabilistic approach to map the parametric uncertainty to the output state uncertainty in first-order hyperbolic conservation laws. We analyze this problem for nonlinear immiscible two-phase transport in…

Computational Physics · Physics 2021-05-11 Farzaneh Rajabi , Hamdi A. Tchelepi

This paper investigates probability density functions (PDFs) that are continuous everywhere, nearly uniform around the mode of distribution, and adaptable to a variety of distribution shapes ranging from bell-shaped to rectangular. From the…

Machine Learning · Computer Science 2022-04-01 Osamu Fujita

We report on probability-density-functions (PDF) of the mass density in numerical simulations of highly compressible hydrodynamic flows and the corresponding structure formation of Lagrangian particles advected by the flows. Numerical…

Fluid Dynamics · Physics 2009-11-13 Christoph Beetz , Christian Schwarz , Jürgen Dreher , Rainer Grauer

Atmospheric wind speeds and their fluctuations at different locations (onshore and offshore) are examined. One of the most striking features is the marked intermittency of probability density functions (PDF) of velocity differences -- no…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 F. Böttcher , St. Barth , J. Peinke

In this paper, we propose normalizing flows (NF) as a novel probability density function (PDF) turbulence model (NF-PDF model) for the Reynolds-averaged Navier-Stokes (RANS) equations. We propose to use normalizing flows in two different…

Fluid Dynamics · Physics 2021-01-12 Deniz A. Bezgin , Nikolaus A. Adams

We use a suite of 3D simulations of star-forming molecular clouds, with and without stellar feedback and magnetic fields, to investigate the effectiveness of different fitting methods for volume and column density probability distribution…

Astrophysics of Galaxies · Physics 2023-05-22 Avery Kiihne , Sabrina M. Appel , Blakesley Burkhart , Vadim A. Semenov , Christoph Federrath

We present a general framework to treat the evolution of one-point probability distribution function (PDF) for cosmic density $\delta$ and velocity-divergence fields $\theta$. In particular, we derive an evolution equation for the one-point…

Astrophysics · Physics 2009-11-07 Yasuhiro Ohta , Issha Kayo , Atsushi Taruya

This Letter provides a theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events. Specifically, nonlinear gyrokinetic simulations of ion-temperature-gradient turbulence…

Plasma Physics · Physics 2010-11-10 Johan Anderson , Pavlos Xanthopoulos

Flamelet Progress Variable (FPV) combustion models allow the evaluation of all thermo chemical quantities in a reacting flow by computing only the mixture fraction Z and a progress variable C. When using such a method to predict a turbulent…

Fluid Dynamics · Physics 2014-01-22 Alessandro Coclite , Giuseppe Pascazio , Pietro De Palma , Luigi Cutrone

We consider problems of minimizing functionals $\mathcal{F}$ of probability measures on the Euclidean space. To propose an accelerated gradient descent algorithm for such problems, we consider gradient flow of transport maps that give…

Optimization and Control · Mathematics 2023-09-06 Ken'ichiro Tanaka
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