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 use a projection-based reduced order model (ROM) instead.Based on this ROM, a realtime observer can be devised product 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 chocolate chip cookie purse a unsteady Reynolds-averaged Navier-Stokes CFD simulation of a 2D centrifugal pump, as well as the results for the extended Kalman filter.