2009
DOI: 10.1080/14786450802452332
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Monitoring and modelling energy efficiency of municipal public buildings: case study in Catalonia region

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Cited by 5 publications
(2 citation statements)
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“…More specifically, the main drawback to overcome concerns the evaluation of the convective heat transfer coefficients and the air mass flow rate. Unless sophisticated predictive tools such as Computational Fluid Dynamics codes (CFD) or Artificial Neural Networks [3], most of the existing transient dynamic prediction models use mathematical correlations which relate these two variables with the corresponding dimensionless numbers and the air flow regimes (natural, forced and mixed convection). In the previous decades forced convection in air channels have been extensively analysed by several authors.…”
Section: Introductionmentioning
confidence: 99%
“…More specifically, the main drawback to overcome concerns the evaluation of the convective heat transfer coefficients and the air mass flow rate. Unless sophisticated predictive tools such as Computational Fluid Dynamics codes (CFD) or Artificial Neural Networks [3], most of the existing transient dynamic prediction models use mathematical correlations which relate these two variables with the corresponding dimensionless numbers and the air flow regimes (natural, forced and mixed convection). In the previous decades forced convection in air channels have been extensively analysed by several authors.…”
Section: Introductionmentioning
confidence: 99%
“…Energy use benchmarking in especially in municipal service buildings has been discussed by e.g. Cipriano, Carbonell, and Cipriano (2009). This study at hand presents a case of a new Finnish municipal daycare building and its energy performance, where cost-optimality is also an optimization target besides the building energy use.…”
Section: Introductionmentioning
confidence: 99%