Introduction to Low Order Modeling

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10.1016/J.JSV.2021.116067

Identification of thermoacoustic systems usually requires low-order modeling, often obtained by means of a Galerkin projection onto a single acoustic mode.

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10.1016/J.AST.2021.106655

This is insightful for low-order modeling of the compressor stall phenomena.

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10.1063/5.0040061

The results of this investigation thus demonstrate that the energized-mass framework provides a viable low-order modeling approach, and in tandem, can provide new insights into the origin of forces on accelerating bodies.

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10.1115/1.4051954

Finally, we discuss the validity limits of the proposed low-order modeling approach.

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10.1016/J.JFLUIDSTRUCTS.2021.103315

Four data-driven low-order modeling approaches, Dynamic mode decomposition (DMD) and three other variations (optimal mode decomposition, total-least-squares DMD and high-order DMD), are used to capture the spatio-temporal evolution of fluid–structure interactions.

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10.23919/ACC.2019.8814617

This paper proposes a domain decomposition scheme as a means for low order modeling of estimators for systems governed by partial differential equations.

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10.1063/1.5063265

The present work aims to demonstrate the relationship between circulation production and force production on rapidly maneuvering wings using experimental measurements and two forms of low order modeling: an empirical model based on Lamb’s point vortex impulse theory and an analytical model stemming from classical airfoil theory.

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Low Order Modeling

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Oct 07, 2022

What is/are Low Order Modeling?

Low Order Modeling - Identification of thermoacoustic systems usually requires low-order modeling, often obtained by means of a Galerkin projection onto a single acoustic mode. ^[1] This is insightful for low-order modeling of the compressor stall phenomena. ^[2] The results of this investigation thus demonstrate that the energized-mass framework provides a viable low-order modeling approach, and in tandem, can provide new insights into the origin of forces on accelerating bodies. ^[3] Finally, we discuss the validity limits of the proposed low-order modeling approach. ^[4] Four data-driven low-order modeling approaches, Dynamic mode decomposition (DMD) and three other variations (optimal mode decomposition, total-least-squares DMD and high-order DMD), are used to capture the spatio-temporal evolution of fluid–structure interactions. ^[5] This paper proposes a domain decomposition scheme as a means for low order modeling of estimators for systems governed by partial differential equations. ^[6] The present work aims to demonstrate the relationship between circulation production and force production on rapidly maneuvering wings using experimental measurements and two forms of low order modeling: an empirical model based on Lamb’s point vortex impulse theory and an analytical model stemming from classical airfoil theory. ^[7]