A mixed POD–PGD approach to parametric thermal impervious soil modeling: Application to canyon streets

•We propose a parametric model dedicated to urban soil thermal modeling.•A combination of two reduced-order methods, i.e. POD and PGD, is presented.•Calculated temperatures are evaluated with respect to in situ measurements.•The parametric soil model is coupled with the SOLENE-microclimat tool.•Its...

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Veröffentlicht in:Sustainable cities and society 2018-10, Vol.42, p.444-461
Hauptverfasser: Azam, Marie-Hélène, Guernouti, Sihem, Musy, Marjorie, Berger, Julien, Poullain, Philippe, Rodler, Auline
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Sprache:eng
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Zusammenfassung:•We propose a parametric model dedicated to urban soil thermal modeling.•A combination of two reduced-order methods, i.e. POD and PGD, is presented.•Calculated temperatures are evaluated with respect to in situ measurements.•The parametric soil model is coupled with the SOLENE-microclimat tool.•Its accuracy and computational cost are evaluated in an urban setting. Numerical simulation is a powerful tool for assessing the causes of an Urban Heat Island (UHI) effect or quantifying the impact of mitigation solutions on local climatic conditions. However, the numerical cost associated with such a tool is quite significant at the scale of an entire district. Today, the main challenge consists of achieving both a proper representation of the physical phenomena and a critical reduction in the numerical costs of running simulations. This paper presents a combined parametric urban soil model that accurately reproduces thermal heat flux exchanges between the soil and the urban environment with a reduced computational time. For this purpose, the use of a combination of two reduced-order methods is proposed herein: the Proper Orthogonal Decomposition method, and the Proper Generalized Decomposition method. The developed model is applied to two case studies in order to establish a practical evaluation: an open area independent of the influences of the surrounding surface, and a theoretical urban scene with two canyon streets. The error due to the model reduction remains below 0.2 °C on the mean surface temperature for a reduced computational cost of 80%. Compared to in situ measurements the error remains bellow 1.24 °C at the surface.
ISSN:2210-6707
2210-6715
DOI:10.1016/j.scs.2018.08.010