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. 2018 Oct 9;15(10):2202.
doi: 10.3390/ijerph15102202.

Quantitative Study of Using Piloti for Passive Climate Adaptability in a Hot-Summer and Cold-Winter City in China

Zeng Zhou  1 , Qinli Deng  2 , Guang Yang  3 , Yaolin Lin  4
Affiliations

Quantitative Study of Using Piloti for Passive Climate Adaptability in a Hot-Summer and Cold-Winter City in China

Zeng Zhou et al. Int J Environ Res Public Health. .

Abstract

There has been an insufficient study of passive climate adaptability that considers both the summer and winter season for the outdoor thermal environment of hot-summer and cold-winter cities. In this study, we performed a quantitative simulation to research the passive climate adaptability of a residential area, considering piloti as the main method for climate adaptation in a hot-summer and cold-winter city in China. Numerical simulations were performed with a coupled simulation method of convection, radiation, and conduction. A cubic non-linear k⁻ε model proposed by Craft et al. was selected as the turbulence model and three-dimensional multi-reflections of shortwave and longwave radiations were considered in the radiation simulation. Through the simulation, we found that setting the piloti at the two ends of the building was the optimal piloti arrangement for climate adaptation. Then the relationship between the piloti ratio (0%, 20%, 40%, 60%, and 80%) and the outdoor thermal environment was studied. It could be concluded that with the increasing piloti ratio, the wind velocity increased, the mean radiant temperature (MRT) decreased slightly, and the average standard effective temperature (SET*) decreased to 3.6 °C in summer, while in winter, with the increasing piloti ratio, the wind velocity, MRT, and SET* changed slightly. The wind environment significantly affected the SET* value, and the piloti ratio should be between 12% and 38% to avoid wind-induced discomfort.

Keywords: Piloti; climate adaptation; hot-summer and cold-winter; outdoor thermal environment.

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Conflict of interest statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to publish the results.

Figures

Figure 1
Figure 1
Location of Wuhan.
Figure 2
Figure 2
The survey results of the time of day residents go outdoors in the summer (a) and the weather data on the 1 July of a typical year (b).
Figure 3
Figure 3
The survey results of the time of day residents go outdoors in the winter (a) and weather data on the 2 January of a typical year (b).
Figure 4
Figure 4
The flowchart of the prediction method for the outdoor thermal environment.
Figure 5
Figure 5
The analysis model used in this study.
Figure 6
Figure 6
The piloti arrangements analysed for the study area.
Figure 7
Figure 7
The surface temperatures for Case 0-S and Case 0-W.
Figure 8
Figure 8
The wind velocity results.
Figure 9
Figure 9
The MRT and SET* results for the piloti arrangements in summer.
Figure 10
Figure 10
The wind velocity results for the piloti arrangements.
Figure 11
Figure 11
The criteria for assessing the wind-induced discomfort considering the temperature effect.
Figure 12
Figure 12
The relationship between the piloti ratio and the average wind velocity of non-piloti areas.
Figure 13
Figure 13
The simulation results of the MRT.
Figure 14
Figure 14
The simulation results of SET*.
See this image and copyright information in PMC

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