Session: 13-04 - Transients, Unsteadiness and Swirl
Paper Number: 123876
123876 - Heat Transfer Enhancement in Pulsating Flows: A Bayesian Approach to Experimental Correlations
This research focuses on improving the understanding of heat transfer effects in pulsating flows for turbomachinery applications. The knowledge can be applied to waste heat from reciprocating devices, pulsating turbocharger performance and flow fields where there are significant cyclic variations. We demonstrate the feasibility of characterising heat transfer augmentation in pulsating flows using a Bayesian estimation framework to correlate experimental data. The primary objective is to identify heat transfer patterns and variations in cold gas flow through a heated pipe across a range of mass flow rates and pulsating frequencies.
To achieve this, we quantify thermal performance during transitions from steady to pulsating and from laminar to turbulent flow through temperature and pressure changes. We address the challenges of understanding complex pulsating exhaust flow by employing the Metropolis-Hastings Markov Chain Monte Carlo sampling method for robust and flexible parameter estimation, accounting for measurement uncertainties.
The scarcity of experimental data in the relevant timescale characterised by high mass flows and pulsating frequencies, highlights the importance of developing new heat transfer models suitable for heavy-duty transport applications. These models have practical implications for waste heat recovery across multiple grades and scales in systems such as exhaust manifolds and Organic Rankine Cycle gas turbines.
Presenting Author: Matei Cristian Ignuta-Ciuncanu Imperial College London
Presenting Author Biography: tbc
Authors:
Matei Cristian Ignuta-Ciuncanu Imperial College LondonChris Noon Imperial College London
Ricardo Martinez-Botas Imperial College London
Heat Transfer Enhancement in Pulsating Flows: A Bayesian Approach to Experimental Correlations
Paper Type
Technical Paper Publication