In this work, we propose to extend an efficient strategy for robust optimization when a large number of uncertainties is considered, in order to include multi-criteria decision making tools. This strategy is based on ANOVA analysis for reducing the stochastic dimension and a massive use of metamodels for predicting the sensitivity indexes in the design variables plan. This approach is applied to the optimization under uncertainty of horizontal ground heat exchangers, used in Ground Source Heat Pumps (GSHPs) for heating and cooling of buildings. System efficiency is maximized taking into account several uncertain parameters, such as the heat conductivity of the ground around the tubes, the velocity inside the tubes and the depth of installation.

Optimization under uncertainty of horizontal ground heat exchangers

PEDIRODA, VALENTINO;PARUSSINI, LUCIA
2013-01-01

Abstract

In this work, we propose to extend an efficient strategy for robust optimization when a large number of uncertainties is considered, in order to include multi-criteria decision making tools. This strategy is based on ANOVA analysis for reducing the stochastic dimension and a massive use of metamodels for predicting the sensitivity indexes in the design variables plan. This approach is applied to the optimization under uncertainty of horizontal ground heat exchangers, used in Ground Source Heat Pumps (GSHPs) for heating and cooling of buildings. System efficiency is maximized taking into account several uncertain parameters, such as the heat conductivity of the ground around the tubes, the velocity inside the tubes and the depth of installation.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2719377
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