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A new computational methodology, termed "PeleLM-FDF" is developed and utilized for high fidelity large eddy simulation (LES) of complex turbulent combustion systems. This methodology is constructed via a hybrid scheme combining the Eulerian…

Fluid Dynamics · Physics 2023-01-11 Aidyn Aitzhan , Shervin Sammak , Peyman Givi , Arash G. Nouri

Dynamic Mode Decomposition (DMD) describes complex dynamic processes through a hierarchy of simpler coherent features. DMD is regularly used to understand the fundamental characteristics of turbulence and is closely related to Koopman…

Fluid Dynamics · Physics 2023-02-01 Matthew J. Colbrook , Lorna J. Ayton , Máté Szőke

A nonlocal subgrid-scale stress (SGS) model is developed based on the convolution neural network (CNN), a powerful supervised data-driven approach. The CNN is an ideal approach to naturally consider nonlocal spatial information in…

Fluid Dynamics · Physics 2023-01-27 Bo Liu , Huiyang Yu , Haibo Huang , Xi-Yun Lu

A fully (pseudo-)spectral solver for direct numerical simulations of large-scale turbulent channel flows is described. The solver utilizes the Chebyshev base functions suggested by J. Shen [SIAM J. Sci. Comput., 16, 1, 1995], that lead to…

Numerical Analysis · Mathematics 2017-01-17 Mikael Mortensen

Most Video Super-Resolution (VSR) methods enhance a video reference frame by aligning its neighboring frames and mining information on these frames. Recently, deformable alignment has drawn extensive attention in VSR community for its…

Computer Vision and Pattern Recognition · Computer Science 2021-05-13 Jiayi Lin , Yan Huang , Liang Wang

Large-eddy simulations of incompressible Newtonian fluid flows with approximate deconvolution models based on the van Cittert method are reported. The Legendre spectral element method is used for the spatial discretization to solve the…

This article presents the data-driven equation-free modeling of the dynamics of a hexafloat floating offshore wind turbine based on the application of dynamic mode decomposition (DMD). All the analyses are performed on experimental data…

Machine Learning · Computer Science 2025-02-18 Giorgio Palma , Andrea Bardazzi , Alessia Lucarelli , Chiara Pilloton , Andrea Serani , Claudio Lugni , Matteo Diez

The Method of Moments (MOM) has largely been applied to investigate sooting laminar and turbulent flames. However, the classical MOM is not able to characterize a continuous particle size distribution (PSD). Without access to information on…

Fluid Dynamics · Physics 2022-10-20 Federica Ferraro , Sandro Gierth , Steffen Salenbauch , Wang Han , Christian Hasse

Turbulence governs the transport of momentum, energy, and scalars in many geophysical and engineering flows. In large-eddy simulations (LES), parameterizing subgrid-scale (SGS) stresses remains a central challenge, as unresolved physical…

Fluid Dynamics · Physics 2025-10-02 Yu Cheng , Tianle Liu

This study presents a comprehensive spatial eigenanalysis of fully-discrete discontinuous spectral element methods, now generalizing previous spatial eigenanalysis that did not include time integration errors. The influence of discrete time…

Fluid Dynamics · Physics 2021-11-30 Niccolò Tonicello , Rodrigo C Moura , Guido Lodato , Gianmarco Mengaldo

The use of spectral proper orthogonal decomposition (SPOD) to construct low-order models for broadband turbulent flows is explored. The choice of SPOD modes as basis vectors is motivated by their optimality and space-time coherence…

Fluid Dynamics · Physics 2021-09-22 Tianyi Chu , Oliver T. Schmidt

Achieving accurate numerical results of hydrodynamic loads based on the potential-flow theory is very challenging for structures with sharp edges, due to the singular behavior of the local-flow velocities. In this paper, we introduce the…

Numerical Analysis · Mathematics 2021-09-23 Ying Wang , Yanlin Shao , Jikang Chen , Hui Liang

Ensuring the safe and reliable operation of integrated electricity and gas systems (IEGS) requires dynamic energy flow (DEF) simulation tools that achieve high accuracy and computational efficiency. However, the inherent strong nonlinearity…

Systems and Control · Electrical Eng. & Systems 2025-02-28 Zhikai Huang , Shuai Lu , Wei Gu , Ruizhi Yu , Suhan Zhang , Yijun Xu , Yuan Li

We revisit recently published high-fidelity implicit large eddy simulation datasets obtained with a high-order discontinuous Galerkin spectral element method and analyse them using Proper Orthogonal Decomposition (POD) as well as Spectral…

Fluid Dynamics · Physics 2024-03-04 Christian Morsbach , Bjoern F. Klose , Michael Bergmann , Felix M. Möller

Computational Fluid Dynamics (CFD) simulations using turbulence models are commonly used in engineering design. Of the different turbulence modeling approaches that are available, eddy viscosity based models are the most common for their…

Fluid Dynamics · Physics 2023-10-24 Minghan Chu , Weicheng Qian

This article provides a reduced-order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of a reduced-order model capable of providing…

Fluid Dynamics · Physics 2024-05-31 Matteo Zancanaro , Valentin Nkana Ngan , Giovanni Stabile , Gianluigi Rozza

Accurate crowd simulation is crucial for public safety management, emergency evacuation planning, and intelligent transportation systems. However, existing methods, which typically model crowds as a collection of independent individual…

Machine Learning · Computer Science 2026-04-14 Zijin Liu , Xu Geng , Wenshuai Xu , Xiang Zhao , Yan Xia , You Song

We propose a novel method to quantify artificial dissipation in large eddy simulation. Here, artificial dissipation is defined as the residual of the discrete turbulent kinetic energy (TKE) equation. This method is applied to turbulent…

Fluid Dynamics · Physics 2025-03-03 Jing Sun , Roel Verstappen

Simulations of complex turbulent flow are part and parcel of the engineering design process. Eddy viscosity based turbulence models represent the workhorse for these simulations. The underlying simplifications in eddy viscosity models make…

Fluid Dynamics · Physics 2024-05-15 Minghan Chu , Weicheng Qian

The spatiotemporal dynamics of turbulent flows is chaotic and difficult to predict. This makes the design of accurate and stable reduced-order models challenging. The overarching objective of this paper is to propose a nonlinear…

Fluid Dynamics · Physics 2022-11-23 Alberto Racca , Nguyen Anh Khoa Doan , Luca Magri