Article

Surfer: A fast simulation algorithm to predict surface temperatures and mean radiant temperatures in large urban models

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Abstract

Outdoor thermal comfort simulation simulations rely on the mean radiant temperature (MRT) seen by pedestrians as an important input that remains difficult to compute. Especially for large urban models, computing relevant surface temperatures and radiation fluxes that make up the MRT is a daunting task in terms of simulation setup and the computational overhead. We propose a new algorithm to estimate exterior surface temperatures of building facades, roofs, and ground surfaces in an arbitrary urban 3D model. The algorithm discretizes all model surfaces and clusters them by material properties and sky and sun exposure to reduce computational complexity. The model setup is fully automated, and the algorithm is implemented in the popular Rhino3d CAD environment. We demonstrate the accuracy of the algorithm by comparing both the resulting external surface temperatures against a high-fidelity simulation and the final MRT against real-world measurements. We report an RMSE of 1.8 °C and 2.0 °C, respectively, while reducing simulation times by a factor of ∼80. Envisioned applications of the algorithm range from rapid microclimate simulations in fast-paced urban design processes to large scale urban comfort evaluation of existing cities.

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Global sensitivity indices for rather complex mathematical models can be efficiently computed by Monte Carlo (or quasi-Monte Carlo) methods. These indices are used for estimating the influence of individual variables or groups of variables on the model output.
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This paper focuses on the development of a thermal design tool for use in planning outdoor spaces by combining a heat balance simulation for urban surfaces, including buildings, the ground and greenery, with a 3D-CAD system that can be run on a personal computer. The newly developed tool is constructed by improving the previous simulation model, which uses the geographic information system (GIS) for the input data. The simulation algorithm is constructed so as to predict the surface temperature distribution of urban blocks while taking into account the actual design of the outdoor space using the 3D-CAD system. A method of multi-tracing simulation to calculate the sky view factor and radiative heat transfer is established. The optimal mesh size is examined for the tool so as to provide detailed spatial geometry within a suitable calculation time. The simulation model is integrated with an all-purpose 3D-CAD software, and the pre-processing method are constructed for practical use. The results obtained by applying this simulation tool to an area of detached houses reveals that the tool is able to evaluate the effects of building shape, materials, and tree shade on the surface temperature distribution, as well as the MRT and HIP, which are evaluation indices of the outdoor thermal environment.
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Variance based methods have assessed themselves as versatile and effective among the various available techniques for sensitivity analysis of model output. Practitioners can in principle describe the sensitivity pattern of a model Y=f(X1,X2,…,Xk) with k uncertain input factors via a full decomposition of the variance V of Y into terms depending on the factors and their interactions. More often practitioners are satisfied with computing just k first order effects and k total effects, the latter describing synthetically interactions among input factors. In sensitivity analysis a key concern is the computational cost of the analysis, defined in terms of number of evaluations of f(X1,X2,…,Xk) needed to complete the analysis, as f(X1,X2,…,Xk) is often in the form of a numerical model which may take long processing time. While the computational cost is relatively cheap and weakly dependent on k for estimating first order effects, it remains expensive and strictly k-dependent for total effect indices. In the present note we compare existing and new practices for this index and offer recommendations on which to use.