Optimized Design of Finned-Tube Evaporators Using the Learnable Evolution Model.
Optimized Design of Finned-Tube Evaporators Using the
Learnable Evolution Model.
Domanski, P. A.; Yashar, D. A.; Kaufman, K. A.;
Michalski, R. S.
HVAC&R Research, Vol. 10, No. 2, 201-211, April 2004.
evaporators; refrigerants; heat exchanger; experiments;
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
nonuniform airflow profiles. ISHED1 demonstrated the
capability to generate designs with capacity equal or
superior to that of best human designs, particularly in
cases with non-uniform airflow.