Deals with two methods for modelling and estimating the daily and annual variation of soil surface temperature. Notes that soil surface temperature is an important factor for calculating the thermal performance of buildings in direct contact with the soil as well as for predicting the efficiency of earth to air heat exchangers. Tests and validates a deterministic model and a neural network approach against extensive sets of measurements for bare soil and soil covered with short grass in Athens and Dublin. Comparisons of the two models show that the proposed intelligent technique is able to adequately estimate the soil surface temperature distribution.
Primary Author(s): Mihalakakou G
Source: Energy and Bldgs., 2002, vol.34, no.3, 251-259, 6 figs, 24 refs.
BSRIA Abstract Doc 000103183 Abs 20020332
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