Mission and History

The solar Energy Applications Laboratory, SEAL, at Colorado State University was founded in 1972 by Dr. George O.G. Lof, whose distinctive career since the 1940's has earned him worldwide recognition as one of the pioneers of solar research. When our first structure, Solar House I, was built in 1974, it was the first house in the world to be both heated and cooled with solar energy. The unique facilities now include three similarly designed, residential-style buildings that can test different active solar systems under identical conditions. Another building allows researchers to test various passive solar designs.

The Solar Energy Applications Laboratory was established to carry out experiments in solar heating and cooling of buildings and solar water heating. The major emphasis of our solar energy research has been directed toward improving the performance of systems installed in a real-world environment so that they can reach their theoretical potential. SEAL is one of only two university laboratories that have received continuing support from the U.S. Department of Energy.

More recently, SEAL's programs have expanded into other areas of building energy technology. Researchers are studying room air motion, building and HVAC simulation, short-term energy monitoring, thermal storage, and neural networks for HVAC control.

How does our work help field practitioners?

• Much of our solar research supports development of system performance rating standards.
• Solar energy system experiments provide the basis for development of system improvements.
• Room air motion experiments support the design of new diffusers and development of design criteria, especially for cold air distribution systems.
• Thermal storage research is leading to the development of a design guide.
• We are making simulation methods easy to use so that engineers can design buildings and HVAC systems more quickly.
• We are developing short-term building and HVAC system test procedures to RcalibrateS long-term performance predictions and to help diagnose faults in the building and its energy systems.
• Neural network research may lead to new building control strategies.

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