English
Related papers

Related papers: Predicting Flow Reversals in a Computational Fluid…

200 papers

Data assimilation plays a crucial role in numerical modeling, enabling the integration of real-world observations into mathematical models to enhance the accuracy and predictive capabilities of simulations. This approach is widely applied…

Numerical Analysis · Mathematics 2024-11-08 Alexander Lobbe , Dan Crisan , Oana Lang

The detailed knowledge of the inner skin temperature behavior is very important to evaluate and manage the aging of large pipes in cooling systems. We describe here a method to obtain this information as a function of outer skin temperature…

Computational Physics · Physics 2014-04-30 Jean-Philippe Argaud , Bertrand Bouriquet , Aimery Assire , Stéphane Gervais

Errors in the representation of clouds in convection-permitting numerical weather prediction models can be introduced by different sources. These can be the forcing and boundary conditions, the representation of orography, the accuracy of…

Atmospheric and Oceanic Physics · Physics 2022-03-14 Stefanie Legler , Tijana Janjic

Heat spontaneously flows from hot to cold in standard thermodynamics. However, the latter theory presupposes the absence of initial correlations between interacting systems. We here experimentally demonstrate the reversal of heat flow for…

The forecasting skill of numerical weather prediction (NWP) models critically depends on the accurate initial conditions, also known as analysis, provided by data assimilation (DA). Traditional DA methods often face a trade-off between…

Atmospheric and Oceanic Physics · Physics 2024-11-28 Yanfei Xiang , Weixin Jin , Haiyu Dong , Mingliang Bai , Zuliang Fang , Pengcheng Zhao , Hongyu Sun , Kit Thambiratnam , Qi Zhang , Xiaomeng Huang

Estimating background-error covariances remains a core challenge in variational data assimilation (DA). Operational systems typically approximate these covariances by transformations that separate geostrophically balanced components from…

Atmospheric and Oceanic Physics · Physics 2026-01-21 Boštjan Melinc , Uroš Perkan , Žiga Zaplotnik

Data assimilation (DA) improves prediction of chaotic systems by combining model forecasts with sparse, noisy observations. Many DA methods are inherently probabilistic, but accurate probabilistic DA is often computationally expensive…

Fluid Dynamics · Physics 2026-04-24 Aditya Sai Pranith Ayapilla , Kazuya Miyashita , Yuki Yasuda , Ryo Onishi

One of the challenges encountered by computational simulations at exascale is the reliability of simulations in the face of hardware and software faults. These faults, expected to increase with the complexity of the computational systems,…

Fluid Dynamics · Physics 2019-02-19 Marc T. Henry de Frahan , Ray W. Grout

We employ detailed numerical simulations to probe the mechanism of flow reversals in two-dimensional turbulent convection. We show that the reversals occur via vortex reconnection of two attracting corner rolls having same sign of…

Fluid Dynamics · Physics 2015-06-05 Mani Chandra , Mahendra K. Verma

Accurate estimation of thermospheric mass density is a prerequisite for orbit prediction and space situational awareness, where the upper atmosphere responds nonlinearly to solar and geomagnetic forcing across several orders of magnitude.…

Systems and Control · Electrical Eng. & Systems 2026-05-04 Sriram Narayanan , Daniele Sicoli , Piyush Mehta

Relevant comprehension of flood hazards has emerged as a crucial necessity, especially as the severity and the occurrence of flood events intensify with climate changes. Flood simulation and forecast capability have been greatly improved…

Image and Video Processing · Electrical Eng. & Systems 2022-11-18 Thanh Huy Nguyen , Anthéa Delmotte , Christophe Fatras , Peter Kettig , Andrea Piacentini , Sophie Ricci

In this article, we provide a methodology to reconstruct high-Reynolds number turbulent mean-flows from few time-averaged measurements. A turbulent flow over a backward-facing step at Re = 28275 is considered to illustrate the potential of…

Fluid Dynamics · Physics 2020-09-23 Lucas Franceschini , Denis Sipp , Olivier Marquet

We study compressible fluid flow in narrow two-dimensional channels using a novel molecular dynamics simulation method. In the simulation area, an upstream source is maintained at constant density and temperature while a downstream…

Condensed Matter · Physics 2009-10-22 M. Sun , C. Ebner

Using a very cheap Data Assimilation (DA) method, I show an alternative approach to classical DA for numerical climate models which produce a large amount of "big data". The problematic features of state-of-the-art high resolution Regional…

Applications · Statistics 2016-10-12 Bijan Fallah

Data assimilation (DA) is a cornerstone of scientific and engineering applications, combining model forecasts with sparse and noisy observations to estimate latent system states. Classical high-dimensional DA methods, such as the ensemble…

Machine Learning · Statistics 2026-05-28 Martin Andrae , Erik Wikingsson , So Takao , Tomas Landelius , Fredrik Lindsten

Wall-bounded turbulent flows are chaotic and multiscale, rendering real-time prediction at high Reynolds numbers computationally prohibitive in applications such as wind farms. Classical data assimilation methods are based on repeated…

Fluid Dynamics · Physics 2026-05-25 Fabian Steinbrenner , Baris Turan , Hao Teng , Heng Xiao

Data assimilation aims to estimate the states of a dynamical system by optimally combining sparse and noisy observations of the physical system with uncertain forecasts produced by a computational model. The states of many dynamical systems…

Optimization and Control · Mathematics 2024-05-08 Amit N. Subrahmanya , Andrey A. Popov , Reid J. Gomillion , Adrian Sandu

The turbulent flow of a fluid carrying trace amounts of a condensable species through a differentially cooled vertical channel geometry is simulated using single-phase direct numerical simulations. The release of latent heat during…

Fluid Dynamics · Physics 2020-01-28 Philipp Bahavar , Claus Wagner

Turbulence, namely, irregular fluctuations in space and time characterize fluid flows in general and atmospheric flows in particular.The irregular,i.e., nonlinear space-time fluctuations on all scales contribute to the unpredictable nature…

General Physics · Physics 2007-05-23 J. S. Pethkar , A. M. Selvam

Ensemble data assimilation is a problem in determining the most likely phase space trajectory of a model of an observed dynamical sys- tem as it receives inputs from measurements passing information to the model. Using methods developed in…

Chaotic Dynamics · Physics 2015-05-13 Henry D. I. Abarbanel
‹ Prev 1 3 4 5 6 7 10 Next ›