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Research Article

A procedural technique for thermal simulation and visualization in urban environments

David Muñoz( ), Gonzalo Besuievsky, Gustavo Patow
Geometry and Graphics Group, Universitat de Girona, Spain
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Abstract

Analysing the thermal behaviour of buildings is an important goal for anyand all of the tasks involving energy flow simulation in urban environments. However, the number of variables to be considered, along with the difficulty of implementing some of them, make it difficult to address the problem on an urban scale. In this paper we propose a procedural approach that, from a 3D urban model and a set of parameters, simulates the thermal exchanges that take place inside and outside buildings in an urban environment. We also provide a technique to efficiently visualise thermal variations over time of both the interior and exterior of buildings in an urban environment. We believe this technique will be helpful for performing a rapid analysis when building parameters, such as materials, dimensions, shape or number of floors, are being changed.

Keywords

thermal simulationurban physics3D city modelsurban environmentsthermal visualisation

References

 
T Ahmad, H Chen (2018). Short and medium-term forecasting of cooling and heating load demand in building environment with data-mining based approaches. Energy and Buildings, 166: 460-476.
Crossref Google Scholar
 
I Alados, I Foyo-Moreno, L Alados-Arboledas (2012). Estimation of downwelling longwave irradiance under all-sky conditions. International Journal of Climatology, 32: 781-793.
Crossref Google Scholar
 
B Beckers (2012). Solar Energy at Urban Scale. Hoboken, NJ, USA: John Wiley & Sons.
 
B Beckers, P Beckers (2014). Sky vault partition for computing daylight availability and shortwave energy budget on an urban scale. Lighting Research & Technology, 46: 716-728.
Crossref Google Scholar
 
B Beckers, JP Aguerre, G Besuievsky, E Fernández, EG Nevado, C Laborderie, R Nahon (2019). Visualizing the infrared response of an urban canyon throughout a sunny day. In: A Sayigh (ed), Sustainable Building for a Cleaner Environment. Cham, Switzerland: Springer. pp. 277-284.
Crossref
 
S Chen, HE Rushmeier, G Miller, D Turner (1991). A progressive multi-pass method for global illumination. ACM SIGGRAPH Computer Graphics, 25: 165-174.
Crossref Google Scholar
 
CitySim (2017). Citysim software. Available at http://citysim.epfl.ch.
 
G Clark, C Allen (1978). The estimation of atmospheric radiation for clear and cloudy skies. In: Proceedings of the 2nd National Passive Solar Conference (AS/ISES), Philadelphia, PA, USA, pp. 675-678.
 
J Clarke, J Hand, P Strachan, J Hensen, C Pernot (1991). ESP-r: A building and plant energy simulation research environment. Energy Simulation Research Unit, ESRU Manual U 91.
Google Scholar
 
J Clarke (2001). Energy Simulation in Building Design, 2nd edn. Oxford, UK: Butterworth-Heinemann.
 
DB Crawley, LK Lawrie, FC Winkelmann, WF Buhl, YJ Huang, CO Pedersen, RK Strand, RJ Liesen, DE Fisher, MJ Witte, J Glazer (2001). EnergyPlus: Creating a new-generation building energy simulation program. Energy and Buildings, 33: 319-331.
Crossref Google Scholar
 
DOE (1982). DOE-2, Engineer Manual—Version 2.1 a. Berkeley, USA: University of California.
 
Eley (2001). VisualDOE 3.0 Program Documentation. San Francisco: Eley Associates.
 
I Elwy, Y Ibrahim, M Fahmy, M Mahdy (2018). Outdoor microclimatic validation for hybrid simulation workflow in hot arid climates against ENVI-met and field measurements. Energy Procedia, 153: 29-34.
Crossref Google Scholar
 
EnergySoft (2016). EnergyPro 5. User’s Manual.
Crossref
 
ESRU (2017). ESRU home page. Available at http://www.esru.strath.ac.uk.
Crossref
 
L Evangelisti, C Guattari, F Asdrubali (2019). On the sky temperature models and their influence on buildings energy performance: A critical review. Energy and Buildings, 183: 607-625.
Crossref Google Scholar
 
V Fabi, RV Andersen, SP Corgnati, BW Olesen (2013). A methodology for modelling energy-related human behaviour: Application to window opening behaviour in residential buildings. Building Simulation, 6: 415-427.
Crossref Google Scholar
 
P Fairey, RK Vieira, DS Parker, B Hanson, PA Broman, JB Grant, B Fuehrlein, L Gu (2002). EnergyGauge USA: A residential building energy simulation design tool. In: Proceedings of the 13th Symposium on Improving Building Systems in Hot and Humid Climates, Houston, TX, USA.
Crossref
 
G Fraisse, C Viardot, O Lafabrie, G Achard (2002). Development of a simplified and accurate building model based on electrical analogy. Energy and Buildings, 34: 1017-1031.
Google Scholar
 
VSKV Harish, A Kumar (2016). A review on modeling and simulation of building energy systems. Renewable and Sustainable Energy Reviews, 56: 1272-1292.
Crossref Google Scholar
 
J Hirsch, et al. (2010) eQUEST: Introductory Tutorial, Version 3.63. Camarillo, CA, USA.
 
JH Kämpf, D Robinson (2007). A simplified thermal model to support analysis of urban resource flows. Energy and Buildings, 39: 445-453.
Crossref Google Scholar
 
ND Kaushika, A Mishra, AK Rai (2018). Solar radiation characteristics. In: Solar Photovoltaics. Cham, Switzerland: Springer. pp. 15-26.
Crossref
 
B Khan, R Forkel, S Banzhaf, E Russo, F Kanani-Sühring, M Mauder, M Kurppa, B Maronga, S Raasch, K Ketelsen (2018). Development and application of an online coupled chemistry urban microscale model PALM-4U. In: EGU General Assembly Conference Abstracts, vol. 20, p. 7501.
 
Q Kong, X He, Y Jiang (2017). Fast simulation of dynamic heat transfer through building envelope via model order reduction. Building Simulation, 10: 419-429.
Crossref Google Scholar
 
NP Lavery (2007). Mathematical framework for predicting solar thermal build-up of spectrally selective coatings at the Earth’s surface. Applied Mathematical Modelling, 31: 1635-1651.
Crossref Google Scholar
 
S Levine (2015). Temperature simulation in residential building by use of electrical circuits. Technical Report, Washington University in St. Louis.
 
RW Lewis, P Nithiarasu, KN Seetharamu (2004). Fundamentals of the Finite Element Method for Heat and Fluid Flow. Chichester, UK: John Wiley & Sons.
Crossref
 
F Lindberg, C Grimmond (2018). Solweig. Available at https://umep-docs.readthedocs.io/en/latest/OtherManuals/SOLWEIG.html
 
A Matzarakis, O Matuschek (2010). Skyhelios. Available at https://www.urbanclimate.net/skyhelios/description.htm
 
A Matzarakis, D Fröhlich, M Gangwisch, C Ketterer, A Peer (2015). Developments and applications of thermal indices in urban structures by Rayman and Skyhelios model. In: Proceedings of the 9th International Conference on the Urban Climate (ICUC9), Toulouse, France.
 
A Matzarakis, O Matuschek (2017). Rayman. Available at https://www.urbanclimate.net/rayman/
 
D Muñoz, B Beckers, G Besuievsky, G Patow (2018). A technique for massive sky view factor calculations in large cities. International Journal of Remote Sensing, 39: 4040-4058.
Crossref Google Scholar
 
R Nahon (2017). Modélisation des échanges radiatifs à l’échelle urbaine pour un urbanisme bioclimatique. PhD Thesis, Université de Lille 1 - Sciences et Technologies, France.
 
FX Side (2018). Houdini. Available at http://www.sidefx.com
 
F Sillion, C Puech (1994). Radiosity and Global Illumination. Eurographics Technical Report Series. San Francisco, USA: Morgan Kaufmann Publishers.
 
EM Sparrow (2018). Radiation Heat Transfer, Augmented Edition. Abingdon, UK: Routledge.
 
G Venturini (2013). Ahkab, a spice-like electronic circuit simulator written in python. Available at https://ahkab.github.io/ahkab/
 
D Yan, J Xia, W Tang, F Song, X Zhang, Y Jiang (2008). DeST — An integrated building simulation toolkit Part I: Fundamentals. Building Simulation, 1: 95-110.
Crossref Google Scholar
 
K Zakšek, K Oštir, Ž Kokalj (2011). Sky-view factor as a relief visualization technique. Remote Sensing, 3: 398-415.
Crossref Google Scholar
 
D Zhu, T Hong, D Yan, C Wang (2013). A detailed loads comparison of three building energy modeling programs: EnergyPlus, DeST and DOE-2.1E. Building Simulation, 6: 323-335.
Crossref Google Scholar
Building Simulation
Volume 12 Issue 6,
December 2019
Pages 1013-1031
DOI: 10.1007/s12273-019-0549-x
Cite this article:
Muñoz D, Besuievsky G, Patow G. A procedural technique for thermal simulation and visualization in urban environments. Building Simulation, 2019, 12(6): 1013-1031. https://doi.org/10.1007/s12273-019-0549-x

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Received: 04 November 2018
Revised: 08 March 2019
Accepted: 25 March 2019
Published: 08 July 2019
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019
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