TY - GEN
T1 - Elements of an advanced and smart HEX software tool
AU - Ladeinde, Foluso
AU - Alabi, Ken
AU - Li, Wenhai
N1 - Publisher Copyright:
© 2018, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.
PY - 2018
Y1 - 2018
N2 - The analytical tools for modern aviation heat exchangers, such as those that are additively manufactured, have to be advanced and smart. In this paper, a few of the expected features of such tools are presented in detail. Some of the features include on-the-fly-access to thermophysical database for solids and fluids, including refrigerants; more versatile procedures than the standard ε − ETU method, automatic access to heat transfer unit problems, and multiple-rating capabilities; including CFD-based multiple-rating. The tools must also support the generation and exporting of lookup tables-tables that could be readily inserted into a system-level multidisciplinary design optimization (MDO) platform. Other requirements include fast optimizers that can handle discontinuous functions, and the ability to interpret complex keyboard input of performance correlations. The software must also be smart – and predictive of user needs. Finally, user data management is a crucial component of developing a smart HEX analysis tool. Since intelligence is driven by the effectiveness and abundance of training data, a desirable tool should support modern database management techniques. The mathematical and qualitative details of a few of these requirements are presented, as are two case studies pertaining to optimization.
AB - The analytical tools for modern aviation heat exchangers, such as those that are additively manufactured, have to be advanced and smart. In this paper, a few of the expected features of such tools are presented in detail. Some of the features include on-the-fly-access to thermophysical database for solids and fluids, including refrigerants; more versatile procedures than the standard ε − ETU method, automatic access to heat transfer unit problems, and multiple-rating capabilities; including CFD-based multiple-rating. The tools must also support the generation and exporting of lookup tables-tables that could be readily inserted into a system-level multidisciplinary design optimization (MDO) platform. Other requirements include fast optimizers that can handle discontinuous functions, and the ability to interpret complex keyboard input of performance correlations. The software must also be smart – and predictive of user needs. Finally, user data management is a crucial component of developing a smart HEX analysis tool. Since intelligence is driven by the effectiveness and abundance of training data, a desirable tool should support modern database management techniques. The mathematical and qualitative details of a few of these requirements are presented, as are two case studies pertaining to optimization.
UR - https://www.scopus.com/pages/publications/85083937554
U2 - 10.2514/6.2018-4885
DO - 10.2514/6.2018-4885
M3 - Conference contribution
AN - SCOPUS:85083937554
SN - 9781624105715
T3 - 2018 International Energy Conversion Engineering Conference
BT - 2018 International Energy Conversion Engineering Conference
PB - American Institute of Aeronautics and Astronautics Inc, AIAA
T2 - 14th International Energy Conversion Engineering Conference, IECEC 2018
Y2 - 9 July 2018 through 11 July 2018
ER -