| Title |
A Continuous, Semi-Automated Workflow: From 3D City Models with Geometric Optimization and CFD Simulations to Visualization of Wind in an Urban Environment |
| ID_Doc |
42778 |
| Authors |
Deininger, ME; von der Grün, M; Piepereit, R; Schneider, S; Santhanavanich, T; Coors, V; Voss, U |
| Title |
A Continuous, Semi-Automated Workflow: From 3D City Models with Geometric Optimization and CFD Simulations to Visualization of Wind in an Urban Environment |
| Year |
2020 |
| Published |
Isprs International Journal Of Geo-Information, 9, 11 |
| DOI |
10.3390/ijgi9110657 |
| 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 speeds-up the preparation of CFD simulation models using a largely automated geometry optimization; and center dot 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: A time saving of the CFD model preparation workflow (85% faster than the manual method), A 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 A protocols (3DPS provided much higher flexibility than static and 3D container API), as well as 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. |
| Author Keywords |
smart city; urban environment; computational fluid dynamics; computational wind engineering; open geospatial consortium; environmental simulation; 3D visualization; web services; automated workflow; CityGML |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000593176500001 |
| WoS Category |
Computer Science, Information Systems; Geography, Physical; Remote Sensing |
| Research Area |
Computer Science; Physical Geography; Remote Sensing |
| PDF |
https://www.mdpi.com/2220-9964/9/11/657/pdf?version=1604479507
|