A Repetitive Day Method for Predicting the Long-Term Thermal Performance of Passive Solar Buildings

[+] Author and Article Information
D. Feuermann

Applied Solar Calculations Unit, Blaustein Institute for Desert Research, Ben-Gurion University of the Negev, Sede Boqer Campus, Israel

J. Sol. Energy Eng 112(1), 34-42 (Feb 01, 1990) (9 pages) doi:10.1115/1.2930757 History: Received March 01, 1989; Revised August 01, 1989; Online June 06, 2008


The long-term thermal performance of passively-heated solar buildings is predicted by a single repetitive meteorological day which contains judiciously chosen solar radiation and ambient temperature functions. These are used as the driving functions of the governing equations that describe the passive solar building under study. The solar radiation and ambient temperature functions are chosen such that they include, both qualitatively and quantitatively, the essential radiation and temperature statistics of the climate in which the building is to be located. The relevant statistics are determined from hourly meteorological data. When hourly meteorological data are not available for a given location, the solar radiation and ambient temperature functions can be constructed from the knowledge of only two climatic data, namely, the monthly average horizontal radiation and the ambient temperature. Model calculations compare favorably with experimental data from Los Alamos solar test cells and with computer simulations.

Copyright © 1990 by The American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.





Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In