Temperature Profile Estimation Downstream to T-Junction for Thermal Mixing of Fluids

Abstract

The thermal mixing of hot and cold streams at T-junctions causes temperature fluctuations which may result in thermal fatigue. Hence for a T-junction, the knowledge of the temperature profile developed by the mixing of two fluids at different temperatures is essential. In this paper, the temperature profile downstream to the T- junction for steady laminar mixing of fluids at different temperatures is estimated by the enhanced conjugate gradient method (ECGM) algorithm. The ECGM is the combination of the recently developed Jaya algorithm and the traditional conjugate gradient method (CGM). Different test cases like the number of sensors, location of sensors and errors in the measurements have been considered. The performance of algorithms is determined by the root mean square (RMS) error. The estimation of the temperature profile by the ECGM algorithm is found to be better (RMS = 6.56 K) than CGM (RMS = 14.12 K).