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Analyzing the Effects of Climate and Geometry on Attic Spaces Using Fraunhofer Attic Thermal Model (FATM)

Graduate #100
Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering

Kahntinetta Pr'Out - Iowa State University
Co-Author(s): Anthony D. Fontanini, Jan Kosny, and Baskar Ganapathysubramanian, Iowa State University, Ames, IA



Residential properties are responsible for 22% of the total energy consumption within the United States and attic spaces alone are responsible for 12% of space heating and 14% of space cooling [Buildings Energy Data Book]. Attic spaces, both commercial and residential, experience the most complex heat and mass transfer phenomena in comparison to the rest of the building envelope. All modes of heat transfer i.e. conduction, convection, and radiation can occur within an attic space at any given time. The energy characteristics of these unique spaces are complicated due to varying geometries, materials, material properties, and geographical locations. For this reason, computer programs have been more than useful in approximating the energy usage attic envelopes. Currently there exists a novel framework, Fraunhofer Attic Thermal Model (FATM), which was developed off the limitations of its predecessor AtticSIM.

This research investigates the thermal loads, heat fluxes, and attic temperatures of attic spaces using the FATM framework. Considering five unique attic geometries, analyses are performed using four weather scenarios in six North American locations. The four weather patterns are statistical representations of current weather conditions and future weather conditions with low, moderate, and high carbon dioxide levels. Using these novel data sets, we can predict longevity of attic structures. This work contributes to the study of attic energy characteristics by using a state of the art framework capable of analyzing non-convex geometric configurations together with novel future weather data sets.

Not Submitted

Funder Acknowledgement(s): NSF, Fraunhofer

Faculty Advisor: Baskar Ganapathysubramanian, baskarg@iastate.edu

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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