In this article we present our approach for the multi-objective shape optimization of heat ex-changer modules. The first problem, of fundamental nature, describes a procedure for the geometric parameterization and multi-objective shape optimi-zation of two-dimensional periodic wavy channels. The geometry of the channel is parameterized either by means of linear-piecewise profiles, or by nonuni-form rational B-splines. The second case, of indus-trial interest, illustrates the development of an automatic method for the design of small gas tur-bine recuperators. For both problems the two objec-tives considered are the maximization of heat transfer rate and the minimization of friction factor, with the additional objective of minimization of heat transfer surface for the recuperator module. Since there is no single optimum to be found, we use a multi-objective genetic algorithm and the so-called Pareto dominance concept, both readily available in the modeFRONTIER optimization package. The results obtained are very encouraging, and the procedure described can be applied, in prin-ciple, to even more complex problems.
Multi-Objective Shape Optimization for Heat Exchanger Modules
MANZAN, MARCO;NOBILE, ENRICO;
2006-01-01
Abstract
In this article we present our approach for the multi-objective shape optimization of heat ex-changer modules. The first problem, of fundamental nature, describes a procedure for the geometric parameterization and multi-objective shape optimi-zation of two-dimensional periodic wavy channels. The geometry of the channel is parameterized either by means of linear-piecewise profiles, or by nonuni-form rational B-splines. The second case, of indus-trial interest, illustrates the development of an automatic method for the design of small gas tur-bine recuperators. For both problems the two objec-tives considered are the maximization of heat transfer rate and the minimization of friction factor, with the additional objective of minimization of heat transfer surface for the recuperator module. Since there is no single optimum to be found, we use a multi-objective genetic algorithm and the so-called Pareto dominance concept, both readily available in the modeFRONTIER optimization package. The results obtained are very encouraging, and the procedure described can be applied, in prin-ciple, to even more complex problems.Pubblicazioni consigliate
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