Abstract
The concept and implementation of Smart Cities is an important approach to improve decision making as well as quality of life of the growing urban population. An essential part of this is the presentation of data from different sources within a digital city model. Wind flow at building scale has a strong impact on many health and energy issues in a city. For the analysis of urban wind, Computational Fluid Dynamics (CFD) has become an established tool, but requires specialist knowledge to prepare the geometric input during a time-consuming process. Results are available only as predefined selections of pictures or videos. In this article, a continuous, semi-automated workflow is presented, which ❶ speeds-up the preparation of CFD simulation models using a largely automated geometry optimization; and ❷ enables web-based interactive exploration of urban wind simulations to a large and diverse audience, including experts and layman. Results are evaluated based on a case study using a part of a district in Stuttgart in terms of: ➀ time saving of the CFD model preparation workflow (85% faster than the manual method), ➁ response time measurements of different data formats within the Smart City platform (3D Tiles loaded 30% faster than geoJSON using the same data representations) and ➂ protocols (3DPS provided much higher flexibility than static and 3D container API), as well as ➃ subjective user experience analysis of various visualization schemes of urban wind. Time saving for the model optimization may, however, vary depending on the data quality and the extent of the study area.
Highlights
As more and more people live in cities, providing a sustainable future for city residents becomes increasingly pertinent
The goal of this study is to enable the integration of offline Computational Fluid Dynamics (CFD) simulation results in a Smart City platform
This paper investigated and presented, for the first time, a continuous workflow from 3D city models to the visualization of simulated wind fields in an urban environment
Summary
As more and more people live in cities, providing a sustainable future for city residents becomes increasingly pertinent. The provided 3D city models open the door for a large number of applications for environmental simulations and decision support [7], e.g., heat demand [8], photo voltaic potential estimation [9] and noise propagation [10]. Another important factor which influences various aspects regarding the quality of urban life, many of them related to health or energy issues, is the wind flow near buildings in inner cities. Wind flow has an influence on pedestrian comfort, possibilities of natural ventilation, urban micro climate, pollution dispersion or the power yield of wind turbines [11]
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