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Parametric study and multi objective optimization of window frame geometry

  • Research Article
  • Building Thermal, Lighting, and Acoustics Modeling
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Abstract

This paper describes a parametric study on window frame geometry with the goal of designing frames with very good thermal properties. Four different parametric frame models are introduced, described by a number of variables, such as dimensions of particular parts of the frame and thermal conductivity of the materials. In the first part of the study, a process of sensitivity analysis is conducted to determine which of the parameters describing the frame have the highest impact on its thermal performance. Afterwards, an optimization process is conducted on each frame. An attempt is made to optimize the design with regard to three objectives: minimizing the heat flow through the frame, maximizing the net energy gain factor and minimizing the material use. Since the objectives contradict each other, it was found that it is not possible to find a single solution that satisfies all of them. Instead, a range of semi-optimal solutions can be identified, from which the designer can select, according to their needs. A genetic algorithm was successfully used to address this problem. In the final part of the study, detailed simulations of energy use in a building are conducted to validate the results based on simplified, static simulations.

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Abbreviations

A :

area (mm2)

b :

height of the cavity (m)

C 1 :

coefficient (W/(m·K))

C 2 :

coefficient (W/(m2·K4/3))

C 4 :

coefficient (W/(m2·K))

D :

coefficient for heat loss (kKh)

d :

width of the cavity (m)

E :

net energy gain factor (kWh/(m2·year))

F i(x):

objective functions

FRP:

fiberglass reinforced polymer

g :

solar heat gain coefficient

h :

heat transfer coefficient (W/(m2·K))

I :

coefficient for heat gain (kWh/m2)

L 2D :

two-dimensional thermal conductance (W/(m·K))

l ψ :

perimeter of the glazing (m)

Q :

energy consumption of a building per square meter of floor area (kWh/m2)

U :

thermal transmittance (W/(m2·K))

α :

solar absorptivity of the outer frame surface

ΔT :

temperature difference between the cavity walls (K)

λ :

thermal conductivity (W/(m·K))

ψ :

linear thermal transmittance (W/(m·K))

a:

convective

eq:

equivalent

ex:

external

f:

frame

g:

glazing

r:

radiative

s:

surface

w:

window

References

  • Appelfeld D, Hansen CS, Svendsen S (2010). Development of a slim window frame made of glass fibre reinforced polyester. Energy and Buildings, 42: 1918–1925.

    Article  Google Scholar 

  • COMSOL AB (2010a). COMSOL Multiphysics, Version 4.0a.

    Google Scholar 

  • COMSOL AB (2010b). Livelink for MATLAB.

    Google Scholar 

  • Danish Building Research Institute (2012). SBi-BSim, Version 6.11.1.14.

    Google Scholar 

  • Danish Ministry of Economic and Business Affairs. (2010). The Danish Building Code.

    Google Scholar 

  • Deb K, Pratap A, Agarwal S, Meyarivan T (2002). A fast elitist multi-objective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6: 182–197.

    Article  Google Scholar 

  • Duer K, Svendsen S, Moller Mogensen M, Birck Laustsen J (2002). Energy labelling of glazings and windows in Denmark: Calculated and measured values. Solar Energy, 73: 23–31.

    Article  Google Scholar 

  • Duffie JA, Beckman WA (2006). Solar Engineering of Thermal Processes, 3rd edn. Hoboken, NJ, USA: John Wiley & Sons.

    Google Scholar 

  • European Committee for Standardization (2012). EN ISO 10077-2:2012. Thermal Performance of Windows, Doors and Shutters—Calculation of Thermal Transmittance, Part 2: Numerical method for frames.

    Google Scholar 

  • Giglioli N, Saltelli A (2000). SimLab 1.1, software for sensitivity and uncertainty analysis, tool for sound modelling. CoRR cs.DM/0011031.

    Google Scholar 

  • Gustavsen A, Grynninga S, Arasteh D, Jelle BP, Goudey H (2011). Key elements of and material performance targets for highly insulating window frames. Energy and Buildings, 43: 2583–2594.

    Article  Google Scholar 

  • Ift Rosenheim (2012). Saving + Gaining Energy with Windows, Facades and Glazing—“EnergyPlus”.

    Google Scholar 

  • International Organization for Standardization (2003). ISO 15099:2003, Thermal Performance of Windows, Doors and Shading Devices—Detailed Calculations.

    Google Scholar 

  • Jensen JM, Lund H (1995). Design Reference Year, DRY—et nyt dansk reference år. Department of Buildings and Energy, Technical University of Denmark.

    Google Scholar 

  • Laustsen J, Svendsen S (2005). Improved windows for cold climates. In: Proceedings of 7th Symposium on Building Physics in the Nordic Countries, Reykjavik, Iceland, pp. 987–994.

    Google Scholar 

  • Lawrence Berkeley National Laboratory (2010). Therm, Version 6.3. Berkeley, USA.

    Google Scholar 

  • Marler RT, Arora JS (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26: 369–395.

    Article  MathSciNet  Google Scholar 

  • Mathworks (2012). MATLAB, Version R2012b.

    Google Scholar 

  • Morris MD (1991). Factorial sampling plans for preliminary computational experiments. Technometrics, 33: 161–174.

    Article  Google Scholar 

  • Nielsen TR, Duer K, Svendsen S (2000). Energy performance of glazings and windows. Solar Energy, 69(Supplement): 137–143.

    Google Scholar 

  • PassivHaus Institut (2012). Certification criteria for certified passive house glazings and transparent components.

    Google Scholar 

  • Sommer Informatik GmbH (2012). WinIso2D Simulation Program, Version 7.40.

    Google Scholar 

  • Svendsen S, Laustsen J, Kragh J (2005). Linear thermal transmittance of the assembly of the glazing and the frame in windows. In: Proceedings of 7th Symposium on Building Physics in the Nordic Countries, Reykjavik, Iceland, pp. 995–1002.

    Google Scholar 

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Correspondence to Jan Zajas.

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Zajas, J., Heiselberg, P. Parametric study and multi objective optimization of window frame geometry. Build. Simul. 7, 579–593 (2014). https://doi.org/10.1007/s12273-014-0186-3

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  • DOI: https://doi.org/10.1007/s12273-014-0186-3

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