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Abstract – Numerical and Field Investigations of Phase Change Material’s (PCM) Impacts on the Energy Performance and Thermal Comfort of Buildings in a Mild Climate

Barilelo Nghana, M.Eng. 2014
Supervisor: Dr. Fitsum Tariku

The current residential buildings are of light weight construction. As such, they tend to frequent indoor air temperature fluctuations and have been proven detrimental for thermal comfort and mechanical system energy consumption. This is reflected in the energy consumption statistics for residential buildings. More than 62% of the energy use is towards maintaining comfortable indoor conditions. A new material called BioPCM, a latent heat storage phase change material that stores excess heat during the day and releases it at night when the indoor temperature it lower, has the potential to increase the thermal mass of these building and consequently  improve thermal comfort and energy consumption, without drastically affecting current construction techniques.

To investigate this hypothesis, both field experiment and numerical investigations are carried out. The field experiment involved monitoring the Whole-Building Performance Research Laboratory located on the BCIT campus while collecting data regarding the indoor air temperature, wall temperatures and heat flux. For the numerical simulation, the same approach is taken; however, the software accuracy is first validated numerically and experimentally before an arbitrary building is simulated with operation typical of a working class citizen.

From the analysis, the phase change material is effective in moderating the indoor air temperature. Additionally, a significant amount of energy savings is realized. It is also seen that the effectiveness of the PCM is dependent on the solar radiation exposure. More solar is required in the winter and spring such that the indoor temperature is regulated around the phase change temperature. On the contrary, less exposure is required in the summer as the storage capacity is quickly expended. More work is needed to accurately predict the performance from a cost analysis perspective before application in the construction industry.

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