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Estimating flow fields with reduced order models
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DOI：10.1016/j.heliyon.2023.e20930.png)
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摘要
En 中文
The estimation of fluid flows inside a centrifugal pump in realtime is a challenging task that cannot be achieved with long-established methods like CFD due to their computational demands. We use a projection-based reduced order model (ROM) instead. Based on this ROM, a realtime observer can be devised that estimates the temporally and spatially resolved velocity and pressure fields inside the pump. The entire fluid-solid domain is treated as a fluid in order to be able to consider moving rigid bodies in the reduction method. A greedy algorithm is introduced for finding suitable and as few measurement locations as possible. Robust observability is ensured with an extended Kalman filter, which is based on a time-variant observability matrix obtained from the nonlinear velocity ROM. We present the results of the velocity and pressure ROMs based on a unsteady Reynolds-averaged Navier-Stokes CFD simulation of a 2D centrifugal pump, as well as the results for the extended Kalman filter.
Keyword:
Reduced order model
Galerkin-projection
Proper orthogonal decomposition
Centrifugal pump
Extended Kalman filter
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期刊
IF:
3.6
论文数:
3.8W
被引数:
10.5W
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