The home automation system to control the climatic health in confined environments is the subject of this article. The standard UNI EN ISO 7730:2006 classifies the conditions of moderate confined environments by three categories according to the PMV index. The comfort sensation is mainly affected by four variables: air temperature, mean radiant temperature, air velocity, relative humidity. They are all mechanical and thermal quantities therefore they are measured through the same measurement method. In evaluating the PMV index two more variables are taken into account: metabolism and clothing insulation. They can be evaluated by different accuracy levels. Their indirect measure is subjected to more uncertainty than the above four measuring parameters and the distribution is typically non-Gaussian. The paper analyses the uncertainty in PMV measuring through the Monte Carlo simulation. The proposed study identifies the different weight of independent variables showing as their uncertainty, particularly those referred to metabolism and clothing insulation, affects considerably the final values for classifying the moderate environments.
Home automation systems and PMV classification for moderate confined environments
MANUELLO BERTETTO, ANDREA;DI PILLA, LORENZA;RICCIU, ROBERTO
2014-01-01
Abstract
The home automation system to control the climatic health in confined environments is the subject of this article. The standard UNI EN ISO 7730:2006 classifies the conditions of moderate confined environments by three categories according to the PMV index. The comfort sensation is mainly affected by four variables: air temperature, mean radiant temperature, air velocity, relative humidity. They are all mechanical and thermal quantities therefore they are measured through the same measurement method. In evaluating the PMV index two more variables are taken into account: metabolism and clothing insulation. They can be evaluated by different accuracy levels. Their indirect measure is subjected to more uncertainty than the above four measuring parameters and the distribution is typically non-Gaussian. The paper analyses the uncertainty in PMV measuring through the Monte Carlo simulation. The proposed study identifies the different weight of independent variables showing as their uncertainty, particularly those referred to metabolism and clothing insulation, affects considerably the final values for classifying the moderate environments.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.