59603 - Calibration of a Cfd Methodology for the Simulation of Roughness Effects on Friction and Heat Transfer in Additive Manufactured Components
It is well-known from the literature that surface roughness affects significantly friction and heat transfer. This is even more evident for additive manufactured (AM) components, which are taking an increasingly important role in the gas turbine field. However, the exploitation of numerical approaches to improve their design is hindered by the lack of dedicated correlations and CFD model developed for such high roughness conditions.
Usually the additive manufactured components are simulated considering the surfaces as smooth or applying an equivalent sand-grain roughness (ks) that results in a velocity shift in the boundary layer. However, determining a priori the most appropriate value of ks is challenging, as dozens of correlations are available, returning scattered and uncertain results. A previous work proved how the CFD prediction of friction and heat transfer returns significant deviations, even exploiting the ks values obtained from experimental tests on the very same test case.
That work allowed also to identify a promising CFD methodology based on friction and thermal corrections proposed by Aupoix from ONERA. The aim of this work is to further carry on the assessment and calibration activity of the model, by analysing additional experimental data of friction factor and Nusslet number from new test cases considering different geometries and flow conditions. This work represents a further step in the generation of a more validated and general methodology for the high-fidelity CFD analysis of additive-manufactured components.
Calibration of a Cfd Methodology for the Simulation of Roughness Effects on Friction and Heat Transfer in Additive Manufactured Components
Paper Type
Technical Paper Publication
Description
Session: 13-03 Heat Transfer Methods & Technologies
Paper Number: 59603
Start Time: June 9th, 2021, 04:00 PM
Presenting Author: Lorenzo Mazzei
Authors: Lorenzo Mazzei Ergon Research
Riccardo Da Soghe Ergon Research
Cosimo Bianchini Ergon Research