Estimating flow fields with reduced order models

Estimating flow fields with reduced order models

Blog Article

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 Scullcap 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 Food Warmers 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.