Conceptual design of a two-pass cross-flow aeroengine intercooler
Journal article, 2015

Establishing an optimal intercooled aeroengine constitutes a coupled problem where the conceptual design of the intercooler and the engine has to be considered simultaneously. The heat transfer and pressure loss characteristics will depend on the choice of the intercooler architecture. Hence, to be able to optimize the performance of an intercooled aeroengine, the performance characteristics of a given intercooler architecture has to be known in the parameter range anticipated for the aeroengine optimization. Here, the conceptual design of a tubular two-pass cross-flow intercooler architecture intended for a turbofan aeroengine application is presented. The internal flow is simulated applying a porous media model for the intercooler tubes, whereas the connecting ducts are analyzed with three-dimensional simulations allowing the assessment of a number of design solutions. The external flow is treated with two-dimensional simulations investigating the external pressure loss and heat transfer characteristics of the two elliptical tube stacks. The intercooler performance is then generalized by developing a reduced order correlation covering a parameter range anticipated for a turbofan conceptual design optimization. The paper constitutes a first effort to establish an open literature complete set of correlations for the prediction of aeroengine intercooler performance.

Intercooling intercooler concept open literature correlations compact heat exchanger conceptual design elliptical tubes

Author

Xin Zhao

Chalmers, Applied Mechanics, Fluid Dynamics

Tomas Grönstedt

Chalmers, Applied Mechanics, Fluid Dynamics

Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering

0954-4100 (ISSN) 20413025 (eISSN)

Vol. 229 11 2006-2023

Subject Categories

Mechanical Engineering

Aerospace Engineering

Fluid Mechanics and Acoustics

Areas of Advance

Transport

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

DOI

10.1177/0954410014563587

More information

Latest update

4/5/2022 6