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An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model

Show simple item record Domanski, Piotr A. Yashar, David Kaufman, Kenneth A. Michalski, Ryszard S. 2006-11-03T18:17:25Z 2006-11-03T18:17:25Z 2004-02 en_US
dc.identifier.citation Domanski, P. A., Yashar, D., Kaufman, K. and Michalski, R. S., "An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model," Reports of the Machine Learning and Inference Laboratory, MLI 04-1, George Mason University, Fairfax, VA, February, 2004. en_US
dc.description.abstract Optimizing the refrigerant circuitry for a finned-tube evaporator is a daunting task for traditional exhaustive search techniques due to the extremely large number of circuitry possibilities. For this reason, more intelligent search techniques are needed. This paper presents and evaluates a novel optimization system, called ISHED1 (Intelligent System for Heat Exchanger Design). This system uses a recently developed non-Darwinian evolutionary computation method to seek evaporator circuit designs that maximize the capacity of the evaporator under given technical and environmental constraints. Circuitries were developed for an evaporator with three depth rows of 12 tubes each, based on optimizing the performance with uniform and non-uniform airflow profiles. ISHED1 demonstrated the capability to design an optimized circuitry for a non-uniform air distribution so the capacity showed no degradation over the traditional balanced circuitry design working with a uniform airflow.
dc.format.extent 2598 bytes
dc.format.extent 299358 bytes
dc.format.mimetype text/xml
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.relation.ispartofseries P 04-1 en_US
dc.relation.ispartofseries MLI 04-1 en_US
dc.subject Machine learning en_US
dc.subject evolutionary computation en_US
dc.subject engineering design en_US
dc.subject learnable evolution model en_US
dc.subject multistrategy learning en_US
dc.title An Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model en_US
dc.type Technical report en_US

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