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RL for Aerodynamic Shape Optimization

Authors: Sobieczky, Florian; Dudkin, Erika; Sanchez Lopez, Luis Alfredo; Scheichl, Bernhard; Sobieczky, Helmut Erich; Schöberl, Joachim; Lackner, Christopher; +1 Authors

RL for Aerodynamic Shape Optimization

Abstract

In the research project "AIrFoil" an international consortium works on improving Air Source Heat Pumps by leveraging a new design concept involving homogenization of the airflow before the heat exchanger. This produces • less noise, and in turn • the ability to increase the ventilator otational speed, leading to • a more efficient heat transition at the heat exchanger of the air source heat pump. How much the concept improves low noise or efficiency can be chosen by the user.

https://www.wim.uni-mannheim.de/doering/conferences/rl-2025/

Keywords

Artificial intelligence, Flow control, PARSEC method, Shape optimization, Airfoil design, Reinforcement learning, Machine learning

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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