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Development of polynomial regression models for composite dynamic envelopes’ thermal performance forecasting

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  • Mavromatidis, Lazaros Elias
  • Bykalyuk, Anna
  • Lequay, Hervé

Abstract

The building envelope’s insulating efficiency is always a key element regarding the energy consumption control of the whole building. This article aims to propose a simple method based on classic and fractional factorial simulation plans to obtain regression models in the form of polynomial functions that link the angle, the thermal conductivity and the thickness of each envelope’s component to the overall wall’s thermal resistance. Original software that combines classic and novel modeling techniques has been used in order to have a precise and validated numerical investigation that focuses in a variety of possible composite dynamic wall’s configurations. For the purposes of this study, the combined radiation/conduction heat transfer finite volume numerical model was updated complex enough to predict the temperature distribution and heat transfer in composite envelopes for a variety of inclination angles. The model takes into account the coupling between the solid conduction of both solid and fibrous systems and the gaseous conduction and radiation. The radiation heat transfer through each insulating layer has been modeled via the two flux approximation in order to take into account both optically thick and optically thin materials, as well as potential reflective surfaces currently used on composite wall’s applications. Different simulation scenarios have been conceived according to basic fractional factorial simulation plans in order to obtain valid empirical polynomial functions. To validate this statistical forecast system, many simulation scenarios were carried out and the statistical results are in compliance with the numerical simulations. The regression models’ results show that the error caused by simplification is acceptable in most conditions, and a lot of coupling calculation could be saved. Furthermore, the reduction of the complex numerical model to simple regression models in the form of polynomial equations aims to assist architects and engineers to directly obtain during the early design stages a high precision forecast of a composite envelope’s thermal performance without mobilizing an expert’s knowledge. Hence, having this knowledge they could optimize during the early design process the envelope’s performance in order to finally achieve an integrated building design.

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  • Mavromatidis, Lazaros Elias & Bykalyuk, Anna & Lequay, Hervé, 2013. "Development of polynomial regression models for composite dynamic envelopes’ thermal performance forecasting," Applied Energy, Elsevier, vol. 104(C), pages 379-391.
  • Handle: RePEc:eee:appene:v:104:y:2013:i:c:p:379-391
    DOI: 10.1016/j.apenergy.2012.10.045
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    as
    1. Mourshed, Monjur, 2011. "The impact of the projected changes in temperature on heating and cooling requirements in buildings in Dhaka, Bangladesh," Applied Energy, Elsevier, vol. 88(11), pages 3737-3746.
    2. Rahman, M.M. & Rasul, M.G. & Khan, M.M.K., 2010. "Energy conservation measures in an institutional building in sub-tropical climate in Australia," Applied Energy, Elsevier, vol. 87(10), pages 2994-3004, October.
    3. Pisello, Anna Laura & Goretti, Michele & Cotana, Franco, 2012. "A method for assessing buildings’ energy efficiency by dynamic simulation and experimental activity," Applied Energy, Elsevier, vol. 97(C), pages 419-429.
    4. Bahadori, Alireza & Vuthaluru, Hari B., 2010. "A simple method for the estimation of thermal insulation thickness," Applied Energy, Elsevier, vol. 87(2), pages 613-619, February.
    5. Saari, Arto & Kalamees, Targo & Jokisalo, Juha & Michelsson, Rasmus & Alanne, Kari & Kurnitski, Jarek, 2012. "Financial viability of energy-efficiency measures in a new detached house design in Finland," Applied Energy, Elsevier, vol. 92(C), pages 76-83.
    6. Marinakis, Vangelis & Doukas, Haris & Karakosta, Charikleia & Psarras, John, 2013. "An integrated system for buildings’ energy-efficient automation: Application in the tertiary sector," Applied Energy, Elsevier, vol. 101(C), pages 6-14.
    7. Belusko, M. & Bruno, F. & Saman, W., 2011. "Investigation of the thermal resistance of timber attic spaces with reflective foil and bulk insulation, heat flow up," Applied Energy, Elsevier, vol. 88(1), pages 127-137, January.
    8. Dodoo, Ambrose & Gustavsson, Leif & Sathre, Roger, 2012. "Effect of thermal mass on life cycle primary energy balances of a concrete- and a wood-frame building," Applied Energy, Elsevier, vol. 92(C), pages 462-472.
    9. Aktacir, Mehmet Azmi & Büyükalaca, Orhan & YIlmaz, Tuncay, 2010. "A case study for influence of building thermal insulation on cooling load and air-conditioning system in the hot and humid regions," Applied Energy, Elsevier, vol. 87(2), pages 599-607, February.
    10. Mavromatidis, Lazaros Elias & EL Mankibi, Mohamed & Michel, Pierre & Santamouris, Mat, 2012. "Numerical estimation of time lags and decrement factors for wall complexes including Multilayer Thermal Insulation, in two different climatic zones," Applied Energy, Elsevier, vol. 92(C), pages 480-491.
    11. Fiaschi, Daniele & Bandinelli, Romeo & Conti, Silvia, 2012. "A case study for energy issues of public buildings and utilities in a small municipality: Investigation of possible improvements and integration with renewables," Applied Energy, Elsevier, vol. 97(C), pages 101-114.
    12. Al-Sanea, Sami A. & Zedan, M.F., 2011. "Improving thermal performance of building walls by optimizing insulation layer distribution and thickness for same thermal mass," Applied Energy, Elsevier, vol. 88(9), pages 3113-3124.
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