Estimating temperature fields in flows from sensors

Active control of scalar transport (e.g. temperature or chemical species) in engineering flows by feedback of intermediate scalar fields to the controller to determine the control action can substantially improve the performance of such processes. Key for practical application of such state-feedback control is the fast and accurate estimation of scalar fields from discrete sensor data (e.g. thermocouples in case of heat transfer), since the full field can usually not be measured. This study develops a state observer that enables such sensor-based state estimation for a representative problem: the temperature evolution during heat transfer in the 2D Rotated Arc Mixer (RAM). State observers with this capability are to the best of our knowledge non-existent
in the literature. The performance of the observer is investigated by its ability to reconstruct known temperature fields from the corresponding values at the sensor locations using fields obtained from (i) numerical simulations and (ii) infrared thermography in a RAM laboratory set-up. This shows a good performance (for typical engineering applications) that under realistic conditions most likely depends mainly on the modelling accuracy for the physical system.