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Normalizing flows are a class of probabilistic generative models which allow for both fast density computation and efficient sampling and are effective at modelling complex distributions like images. A drawback among current methods is…

Computer Vision and Pattern Recognition · Computer Science 2020-10-28 Jason J. Yu , Konstantinos G. Derpanis , Marcus A. Brubaker

The majority of practical flows, particularly those flows in applications of importance to transport, distribution and climate, are turbulent and as a result experience complex three-dimensional motion with increased drag compared with the…

Fluid Dynamics · Physics 2015-03-17 B. J. McKeon , A. S. Sharma , I. Jacobi

We propose a novel framework for approximating the statistical properties of turbulent flows by combining variational methods for the search of unstable periodic orbits with resolvent analysis for dimensionality reduction. Traditional…

Chaotic Dynamics · Physics 2025-01-22 Thomas Burton , Sean Symon , Ati Sharma , Davide Lasagna

Probabilistic power flow (PPF) analysis is critical to power system operation and planning. PPF aims at obtaining probabilistic descriptions of the state of the system with stochastic power injections (e.g., renewable power generation and…

Systems and Control · Electrical Eng. & Systems 2023-08-23 Kejun Chen , Yu Zhang

High Reynolds numbers Navier-Stokes equations are believed to break self-similarity concerning both spatial and temporal properties: correlation functions of different orders exhibit distinct decorrelation times and anomalous spatial…

Fluid Dynamics · Physics 2012-10-04 Luca Biferale , Enrico Calzavarini , Federico Toschi

The two-dimensional backward-facing step flow is a canonical example of noise amplifier flow: global linear stability analysis predicts that it is stable, but perturbations can undergo large amplification in space and time as a result of…

Fluid Dynamics · Physics 2014-12-05 Edouard Boujo , François Gallaire

Certifying power flow solvability is important for reliable power system operations under volatile operating conditions, but solving power flow equations repeatedly can be costly and may encounter convergence issues. In this paper, we…

Optimization and Control · Mathematics 2026-05-26 Puskar Neupane , Bai Cui

Efficient simulation of the Navier-Stokes equations for fluid flow is a long standing problem in applied mathematics, for which state-of-the-art methods require large compute resources. In this work, we propose a data-driven approach that…

Computer Vision and Pattern Recognition · Computer Science 2022-11-10 Jonathan Tompson , Kristofer Schlachter , Pablo Sprechmann , Ken Perlin

We examine the efficacy of streamwise traveling waves generated by a zero-net-mass-flux surface blowing and suction for controlling the onset of turbulence in a channel flow. For small amplitude actuation, we utilize weakly nonlinear…

Fluid Dynamics · Physics 2011-11-29 Rashad Moarref , Mihailo R. Jovanović

A model of fully developed turbulence of a compressible fluid is briefly reviewed. It is assumed that fluid dynamics is governed by a stochastic version of Navier-Stokes equation. We show how corresponding field theoretic-model can be…

Statistical Mechanics · Physics 2018-10-09 M. Hnatič , N. M. Gulitskiy , T. Lučivjanský , L. Mižišin , V. Škultéty

This article considers the problem of reconstructing unknown driving forces based on incomplete knowledge of the system and its state. This is studied in both a linear and nonlinear setting that is paradigmatic in geophysical fluid dynamics…

Optimization and Control · Mathematics 2025-04-02 Jochen Bröcker , Giulia Carigi , Tobias Kuna , Vincent R. Martinez

Resolvent compositions were recently introduced as monotonicity-preserving operations that combine a set-valued monotone operator and a bounded linear operator. They generalize in particular the notion of a resolvent average. We analyze the…

Functional Analysis · Mathematics 2026-01-30 Diego J. Cornejo

The aim of this work is to study the Navier-Stokes-Voigt equations that govern flows with non-negative density of incompressible fluids with elastic properties. For the associated non-linear initial-and boundary-value problem, we prove the…

Analysis of PDEs · Mathematics 2023-09-04 Hermenegildo Borges de Oliveira , Khonatbek Khompysh , Aidos Ganizhanuly Shakir

Deep learning provides a versatile suite of methods for extracting structured information from complex datasets, enabling deeper understanding of underlying fluid dynamic phenomena. The field of turbulence modeling, in particular, benefits…

Machine Learning · Computer Science 2025-07-31 Anuraj Maurya

The background of this work is the problem of reducing the aerodynamic turbulent friction drag, which is an important source of energy waste in innumerable technological fields. We develop a theoretical framework aimed at predicting the…

Fluid Dynamics · Physics 2013-01-23 Marco Belan , Maurizio Quadrio

We posit that autoregressive flow models are well-suited to performing a range of causal inference tasks - ranging from causal discovery to making interventional and counterfactual predictions. In particular, we exploit the fact that…

Machine Learning · Statistics 2020-07-28 Ricardo Pio Monti , Ilyes Khemakhem , Aapo Hyvarinen

Obtaining system parameters and reconstructing the full flow state from limited velocity observations using conventional fluid dynamics solvers can be prohibitively expensive. Here we employ machine learning algorithms to overcome the…

Fluid Dynamics · Physics 2024-10-17 Vladimir Parfenyev , Mark Blumenau , Ilia Nikitin

We study the input-output response of a streamwise constant projection of the Navier-Stokes equations for plane Couette flow, the so-called 2D/3C model. Study of a streamwise constant model is motivated by numerical and experimental…

We consider the problem of making expressive static analyzers interactive. Formal static analysis is seeing increasingly widespread adoption as a tool for verification and bug-finding, but even with powerful cloud infrastructure it can take…

Programming Languages · Computer Science 2021-04-08 Benno Stein , Bor-Yuh Evan Chang , Manu Sridharan

We consider the Navier-Stokes system solution, based at parametric representation of desired function. This solution is unique and it show the velocity of a stream element as its density structure [{\rho}_S (x,y,z,t);{\rho}^\to_L (x,y,z,t)]…

Mathematical Physics · Physics 2018-11-21 Alexandr Fridrikson , Marina Kasatochkina