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Estimating flow fields with reduced order models
Kamil David Sommer1, Lucas Reineking1, Yogesh Parry Ravichandran2
1Automatic Control and Systems Theory, Ruhr-Universität Bochum, Universitätsstr. 150, 44801, Bochum, Germany.
Heliyon
|November 6, 2023
Summary
Realtime fluid flow estimation in centrifugal pumps is achieved using a projection-based reduced order model (ROM) and an extended Kalman filter. This method accurately predicts velocity and pressure fields, overcoming computational limitations of traditional techniques.
Area of Science:
- Fluid Mechanics
- Computational Engineering
- Control Systems
Background:
- Realtime estimation of fluid flow in centrifugal pumps is difficult with traditional Computational Fluid Dynamics (CFD) due to high computational costs.
- Existing methods lack the speed required for instantaneous monitoring and control of pump performance.
Purpose of the Study:
- To develop a computationally efficient method for realtime estimation of velocity and pressure fields within a centrifugal pump.
- To enable the monitoring of internal fluid dynamics by overcoming the limitations of established CFD approaches.
Main Methods:
- A projection-based reduced order model (ROM) was developed for the fluid-solid domain, treating the entire system as a fluid to accommodate moving rigid bodies.
- A greedy algorithm was employed to optimize sensor placement, minimizing measurement locations while ensuring observability.
- An extended Kalman filter was utilized, incorporating a time-variant observability matrix derived from the nonlinear velocity ROM for robust state estimation.
Main Results:
- The study successfully implemented velocity and pressure ROMs validated against unsteady Reynolds-averaged Navier-Stokes (URANS) CFD simulations of a 2D centrifugal pump.
- The extended Kalman filter demonstrated robust and accurate estimation of the internal flow fields.
- The greedy algorithm effectively identified minimal sensor locations for optimal system monitoring.
Conclusions:
- The developed ROM-based observer provides a computationally feasible solution for realtime fluid flow estimation in centrifugal pumps.
- This approach significantly enhances the ability to monitor and potentially control complex fluid dynamics in turbomachinery.
- The integration of ROMs with Kalman filtering offers a powerful tool for advanced diagnostics in fluid systems.
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