Reduced-order modeling: a personal journey
Reduced-order models (ROM) have captured the interest and effort of many investigators over the years. As is well known the cost of computation can easily outpace the available computational resources, especially for multidisciplinary mathematical/computational models. In the present paper a persona...
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| Published in | Nonlinear dynamics Vol. 111; no. 11; pp. 9699 - 9720 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
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Springer Netherlands
01.06.2023
Springer Nature B.V |
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| Abstract | Reduced-order models (ROM) have captured the interest and effort of many investigators over the years. As is well known the cost of computation can easily outpace the available computational resources, especially for multidisciplinary mathematical/computational models. In the present paper a personal account of one investigator's journey is provided as enabled by substantial contributions from colleagues in several organizations over the years. This is not a review of the literature or a history of the subject; it is intended to be an account of key ideas as seen from a single perspective. By a reduced-order model is meant a model that provides a substantial reduction in the size and cost of the original computational model
without any essential loss in accuracy.
And the motivation for creating such a ROM is not only to reduce computational cost. By extracting the essential elements of a more elaborate model, a much wider range of parameters in the model may be studied and the interpretation of the results may be made easier, thereby advancing our understanding of the model and the physical phenomena it is intended to describe. |
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| AbstractList | Reduced-order models (ROM) have captured the interest and effort of many investigators over the years. As is well known the cost of computation can easily outpace the available computational resources, especially for multidisciplinary mathematical/computational models. In the present paper a personal account of one investigator's journey is provided as enabled by substantial contributions from colleagues in several organizations over the years. This is not a review of the literature or a history of the subject; it is intended to be an account of key ideas as seen from a single perspective. By a reduced-order model is meant a model that provides a substantial reduction in the size and cost of the original computational model without any essential loss in accuracy. And the motivation for creating such a ROM is not only to reduce computational cost. By extracting the essential elements of a more elaborate model, a much wider range of parameters in the model may be studied and the interpretation of the results may be made easier, thereby advancing our understanding of the model and the physical phenomena it is intended to describe. Reduced-order models (ROM) have captured the interest and effort of many investigators over the years. As is well known the cost of computation can easily outpace the available computational resources, especially for multidisciplinary mathematical/computational models. In the present paper a personal account of one investigator's journey is provided as enabled by substantial contributions from colleagues in several organizations over the years. This is not a review of the literature or a history of the subject; it is intended to be an account of key ideas as seen from a single perspective. By a reduced-order model is meant a model that provides a substantial reduction in the size and cost of the original computational model without any essential loss in accuracy. And the motivation for creating such a ROM is not only to reduce computational cost. By extracting the essential elements of a more elaborate model, a much wider range of parameters in the model may be studied and the interpretation of the results may be made easier, thereby advancing our understanding of the model and the physical phenomena it is intended to describe. |
| Author | Dowell, Earl |
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| References_xml | – reference: KonstadinopoulosPThrasherDFMookDTNayfehAHWatsonLA vortex-lattice method for general, unsteady aerodynamicsJ. Aircraft1985221434910.2514/3.45078 – reference: Eldridge-Allegra, I.K., Xu, T.Y., Bastos, K.M.K., Dowell E.H.: Computational study of transonic buffet’s sensitivity to reynolds number and wind tunnel wall effects. In: AIAA SciTech Conference (2023) – reference: HallKCEigenanalysis of unsteady flows about airfoils, cascades and wingsAIAA J.199432122426243210.2514/3.123090833.76006 – reference: HolmesPLumleyJLBerkoozGRowleyCWTurbulence, Coherent Structures, Dynamical Systems and Symmetry20122CambridgeCambridge University Press10.1017/CBO97805119197011251.76001 – reference: Dowell, E.H.: Nonlinear flutter of curved plates. AIAA J. 7(3): 424–431 (1969) and Nonlinear flutter of curved plates II. 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| SubjectTerms | Accuracy Automotive Engineering Classical Mechanics Computing costs Control Dynamical Systems Engineering Feature Article Finite volume method Literature reviews Mechanical Engineering Ordinary differential equations Partial differential equations Quantum physics Reduced order models Reynolds number Vibration |
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| Title | Reduced-order modeling: a personal journey |
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