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• W3119404186 endingPage "113882" @default.
• W3119404186 startingPage "113882" @default.
• W3119404186 abstract "One of the principal barriers in developing accurate and tractable predictive models in turbulent flows with a large number of species is to track every species by solving a separate transport equation, which can be computationally impracticable. In this paper, we present an on-the-fly reduced order modeling of reactive as well as passive transport equations to reduce the computational cost. The presented approach seeks a low-rank decomposition of the species to three time-dependent components: (i) a set of orthonormal spatial modes, (ii) a low-rank factorization of the instantaneous species correlation matrix, and (iii) a set of orthonormal species modes, which represents a low-dimensional time-dependent manifold. Our approach bypasses the need to solve the full-dimensional species to generate high-fidelity data — as it is commonly performed in data-driven dimension reduction techniques such as the principle component analysis. Instead, the low-rank components are directly extracted from the species transport equation. The evolution equations for the three components are obtained from optimality conditions of a variational principle. The time-dependence of the three components enables an on-the-fly adaptation of the low-rank decomposition to transient changes in the species. Several demonstration cases of reduced order modeling of passive and reactive transport equations are presented." @default.
• W3119404186 created "2021-01-18" @default.
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• W3119404186 date "2021-08-01" @default.
• W3119404186 modified "2023-09-30" @default.
• W3119404186 title "On-the-fly reduced order modeling of passive and reactive species via time-dependent manifolds" @default.
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• W3119404186 doi "https://doi.org/10.1016/j.cma.2021.113882" @default.
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