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Local causal structure learning aims to discover and distinguish direct causes (parents) and direct effects (children) of a variable of interest from data. While emerging successes have been made, existing methods need to search a large…

Artificial Intelligence · Computer Science 2021-01-12 Shuai Yang , Hao Wang , Kui Yu , Fuyuan Cao , Xindong Wu

Planetary turbulence is observed to self-organize into large-scale structures such as zonal jets and coherent vortices. One of the simplest models that retains the relevant dynamics of turbulent self-organization is a barotropic flow in a…

Atmospheric and Oceanic Physics · Physics 2015-01-22 Nikolaos A. Bakas , Petros J. Ioannou

This study establishes a symmetry-based framework to quantify non-equilibrium processes in complex pressure gradient (PG) turbulent boundary layers (TBLs), using a Lie-group-informed dilation-symmetry-breaking formalism. We derive a…

Fluid Dynamics · Physics 2025-09-01 Wei-Tao Bi , Ke-Xin Zheng , Jun Chen , Zhen-Su She

Local causal structure learning aims to discover and distinguish direct causes (parents) and direct effects (children) of a variable of interest from data. While emerging successes have been made, existing methods need to search a large…

Machine Learning · Computer Science 2021-03-02 Shuai Yang , Hao Wang , Kui Yu , Fuyuan Cao , Xindong Wu

We study numerically transitional coherent structures in a boundary-layer flow with homogeneous suction at the wall (the so-called asymptotic suction boundary layer ASBL). The dynamics restricted to the laminar-turbulent separatrix is…

Generative modeling typically seeks the path of least action via deterministic flows (ODE). While effective for in-distribution tasks, we argue that these deterministic paths become brittle under causal interventions, which often require…

Machine Learning · Computer Science 2026-02-24 Rui Wu , Li YongJun

Fluid thermodynamics underpins atmospheric dynamics, climate science, industrial applications, and energy systems. However, direct numerical simulations (DNS) of such systems can be computationally prohibitive. To address this, we present a…

Fluid Dynamics · Physics 2026-02-11 Luca Menicali , Andrew Grace , David H. Richter , Stefano Castruccio

Real-world problems, for example in climate applications, often require causal reasoning on spatially gridded time series data or data with comparable structure. While the underlying system is often believed to behave similarly at different…

Machine Learning · Computer Science 2026-02-16 Martin Rabel , Jakob Runge

Coherent motions associated with extreme wall shear stress events are investigated for adverse pressure gradient turbulent boundary layers (APG-TBLs). The analyses are performed using wall-resolved large eddy simulations of a NACA0012…

Fluid Dynamics · Physics 2025-11-07 Leandro J. O. Silva , William R. Wolf

This thesis reports progress in two domains, causal structures and microscopic thermodynamics, both of which are pertinent in the development of quantum technologies. The first part is dedicated to the analysis of causal structure, which…

Quantum Physics · Physics 2018-07-18 Mirjam Weilenmann

We investigate how symmetry, exact coherent structures (ECSs), and their invariant manifolds organize spontaneous flow reversals in a 2D active nematic confined to a periodic channel. In minimal flow units commensurate with the intrinsic…

Soft Condensed Matter · Physics 2026-03-13 Angel Naranjo , Rumayel Pallock , Caleb Wagner , Piyush Grover

Time irreversibility is a distinctive feature of non-equilibrium phenomena such as turbulent flows, where irreversibility is mainly associated with an energy cascade process. An Eulerian, multiscale analysis of time irreversibility in…

Hyperbolic Lagrangian Coherent Structures (LCSs) are locally most repelling or most attracting material surfaces in a finite-time dynamical system. To identify both types of hyperbolic LCSs at the same time instance, the standard practice…

Dynamical Systems · Mathematics 2015-06-12 Mohammad Farazmand , George Haller

Inference of causality is central in nonlinear time series analysis and science in general. A popular approach to infer causality between two processes is to measure the information flow between them in terms of transfer entropy. Using…

Chaotic Dynamics · Physics 2015-04-16 Jie Sun , Erik M. Bollt

Real world systems evolve in continuous-time according to their underlying causal relationships, yet their dynamics are often unknown. Existing approaches to learning such dynamics typically either discretize time -- leading to poor…

Machine Learning · Computer Science 2025-12-17 Nicholas Tagliapietra , Katharina Ensinger , Christoph Zimmer , Osman Mian

We investigate the Reynolds-shear-stress carrying structures in the outer layer of non-equilibrium pressure-gradient turbulent boundary layers using four direct numerical simulation databases, two cases of non-equilibrium pressure-gradient…

Fluid Dynamics · Physics 2025-05-16 M. Ali Yesildag , Taygun R. Gungor , Ayse G. Gungor , Yvan Maciel

Causal Bayesian Networks (CBNs) are a powerful tool for reasoning under uncertainty about complex real-world problems. Such problems evolve over time, responding to external shocks as they occur. To support decision-making, CBNs require a…

Machine Learning · Computer Science 2026-05-11 Bruno Petrungaro , Anthony C. Constantinou

We present a method for converting a time record of turbulent velocity measured at a point in a flow to a spatial velocity record consisting of consecutive convection elements. The spatial record allows computation of dynamic statistical…

Fluid Dynamics · Physics 2019-06-18 Preben Buchhave , Clara M. Velte

In this paper, we investigate the enstrophy dynamics in relation to objective Eulerian coherent structures (OECSs) and their impact on the enstrophy and scalar transport near the turbulent/non-turbulent interface (TNTI) in flows with and…

Fluid Dynamics · Physics 2021-06-30 M. M. Neamtu-Halic , J. -P. Mollicone , M. van Reeuwijk , M. Holzner

Turbulence is characterised by chaotic dynamics and a high-dimensional state space, which make this phenomenon challenging to predict. However, turbulent flows are often characterised by coherent spatiotemporal structures, such as vortices…

Fluid Dynamics · Physics 2023-06-21 Nguyen Anh Khoa Doan , Alberto Racca , Luca Magri
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