Athanassios A. Argiriou

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An artificial neural network (ANN)-based controller for hydronic heating plants of buildings is presented. The controller has forecasting capabilities: it includes a meteorological module, forecasting the ambient temperature and solar irradiance, an indoor temperature predictor module, a supply temperature predictor module and an optimizing module for the(More)
Artificial neural networks (ANN's) are more and more widely used in energy management processes. ANN's can be very useful in optimizing the energy demand of buildings, especially of those of high thermal inertia. These include the so-called solar buildings. For those buildings, a controller able to forecast not only the energy demand but also the weather(More)
In dry and warm environments sub-cloud evaporation influences the falling raindrops modifying their final stable isotopic content. During their descent from the cloud base towards the ground surface, through the unsaturated atmosphere, hydrometeors are subjected to evaporation whereas the kinetic fractionation results to less depleted or enriched isotopic(More)
This article describes the mechanisms affecting the thermal behavior of buildings. This behavior depends upon the temperature and humidity balance in premises. First the physical mechanisms of heat transfer are explained, followed by a description of the heat and humidity sources and sinks in premises. The next three sections deal with the physics of(More)
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