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Hessam Babaee on Muck Rack

Hessam Babaee

United States
As seen in: Taylor & Francis Online
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Articles

On-the-fly reduced-order modelling of the filter density function with time-dependent subspaces

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By Hessam Babaee, Aidyn Aitzhan, Peyman Givi
| Taylor & Francis Online
Abstract A dynamical low-rank approximation is developed for reduced-order modelling (ROM) of the filtered density function (FDF) transport equation, which is utilised for large eddy simulation (LES) of turbulent reacting flows. In this methodology, the evolution of the composition matrix describing the FDF transport via a set of Langevin equations is constrained to a low-rank matrix manifold.
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[2408.16591] CUR for Implicit Time Integration of Random Partial Differential Equations on Low-Rank Matrix Manifolds

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By Mohammad Hossein, Sara Akhavan, Hessam Babaee
| arxiv.org
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Open in Who Shared View Duplicates (413) Issue with article?

[2403.12826] Cross Algorithms for Cost-Effective Time Integration of Nonlinear Tensor Differential Equations on Low-Rank Tucker Tensor and Tensor Train Manifolds

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By Hessam Babaee
| arxiv.org
[Submitted on 19 Mar 2024] Title:Cross Algorithms for Cost-Effective Time Integration of Nonlinear Tensor Differential Equations on Low-Rank Tucker Tensor and Tensor Train Manifolds Download a PDF of the paper titled Cross Algorithms for Cost-Effective Time Integration of Nonlinear Tensor Differential Equations on Low-Rank Tucker Tensor and Tensor Train Manifolds, by Behzad Ghahremani and Hessam Babaee Download PDF HTML (experimental) Abstract:Dynamical low-rank approximation (DLRA) provides...
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