The growing complexity of urban environments has intensified the need for accurate 3D city models to support simulations and analyses in various fields such as urban planning, energy demand, and computational fluid dynamics (CFD). However, these models often contain geometric and topological errors, such as non-watertight solids, intersecting volumes, and missing surfaces, limiting their usability. This thesis presents AUTOr3pair, an automatic framework designed to repair semantic 3D city models and address these issues.

The process begins with validating 3D city models using val3dity, which ensures geometric validity based on ISO 19107 standards. Errors are addressed hierarchically, starting with ring-level fixes and progressing to solid interaction-level corrections, focusing on localized repairs to minimize alterations while preserving geometric and topological integrity. Existing repair methods are integrated alongside new algorithms designed to meet the specific needs of different use cases, including visualization, energy demand estimation, solar potential analysis, and CFD simulations. Written in C++ for optimal performance, the framework supports CityJSON and OBJ. The repairs prioritize maintaining semantic consistency and minimizing data loss, but textures are excluded. This approach results in a robust validation and repair pipeline that generates detailed error reports and post-processing outputs, significantly improving the overall quality of 3D city models.

Extensive tests on real-world datasets, including 3DBAG tiles from Leiden and a dataset from Brussels, demonstrated that AUTOr3pair successfully repaired most geometric errors, raising validity rates to nearly 100%.
The framework achieved additional requirements, such as watertight geometry and proper surface orientation, for the specific use cases, CFD, energy demand, visualization, and solar power estimation. While some floating-point errors and geometric differences, due to global repairs, persist in complex cases, AUTOr3pair significantly reduces manual pre-processing and improves model suitability for various applications.

This thesis demonstrates that automatic geometry repair is feasible and essential for improving the quality and usability of 3D city models. It provides a foundation for further research and development, particularly in extending the framework to support more file types and refining its capabilities for additional use cases.

Urbanization has led to more than half of the world’s population living in cities. The design of sustainable and resilient urban environments is becoming increasingly critical to optimize the well-being of their inhabitants and the planet. One of the major challenges in achieving this is the complex wind flow patterns in densely built-up areas, which require accurate prediction and analysis to effectively harness the potential benefits of wind flow, such as natural ventilation and wind power generation. However, the unique features of urban landscapes, such as high-rise buildings, narrow streets, and irregular building shapes, make the analysis of wind flow within urban canopies complicated.

In recent years, Computational Fluid Dynamics (CFD) has become a vital tool for studying wind flow in urban areas. Still, the complex geometries of buildings can lead to challenges, including recirculation, reattachment, intense turbulence, and dead zones. Moreover, vegetation plays a crucial role in controlling wind flow in dense areas by acting as a physical barrier, significantly reducing the wind speed and alter the wind flow direction. Additionally, generating geometry for computa-tional fluid dynamics (CFD) simulation in complex urban environments is a chal-lenging and time-consuming process.

Hence, for this thesis, the City4CFD software will be used to automatically recon-struct a 3D model of Stanford University at LoD1.2, which will significantly reduce the time and effort required to generate the complex geometry necessary for com-putational fluid dynamics (CFD) simulations in urban environments. The results will be compared to those obtained from an already manually reconstructed model at LoD2.1 and real-world measurements conducted within the area of interest. This will allow me to determine the differences introduced by different level of detail.

The research will address several sub-questions, such as the steps needed to auto-matically reconstruct a 3D city model, the potential improvements in simulation accuracy by increasing LoD, and the impact of complex geometries on wind flow. The results of the thesis indicated that a more complex geometry Level of Detail (LoD) can enhance the accuracy of simulations by providing a more precise de-piction of wind flow patterns. In other words, a higher LoD geometry, such as LoD2.1, can more accurately predict wind patterns in urban environments based on real-world measurements. The study observed that the LoD2.1 model, which in-corporates more complex features, generated simulation outcomes that were closer to the measurements compared to the less detailed LoD1.2 model.

Currently more than 4 billion people live in urban areas around the globe, a trend that is expected to be increased in the upcoming years. While urbanisation provides the space for innovation and new opportunities, in the meantime physical, technical and social challenges are rising and the cities’ vulnerability is increasing. A tool to tackle these issues are Computational Fluid Dynamics
(CFD) simulations, which can provide insight in various topics.

CFD simulations are valuable for modelling complex urban phenomena such as wind flow, microclimates and thermal comfort. A CFD requires as an input a 3D geometric dataset that represents objects in the urban environment which are most commonly buildings and then according to this input the air flow is simulated around it.

When creating geometries automatically for CFD simulations, several clean up tasks must be completed for them to be usable without any issues. One of the problems arising is related to the redundant faces shared between adjacent buildings, which have no purpose for outdoor flow simulations and cause complications when creating the mesh that is needed for the CFD. This
synthesis project focuses on addressing the aforementioned issue by removing the shared faces.

The ultimate goal of this project was to create an open-source product that can efficiently and in an automated way remove the adjacent faces between buildings. The benefits will be imminent during the meshing process, as we strive to reduce the time that consultancies spend fixing the input geometries before running a CFD simulation, along with an overall improved user experience.

This report is organised in four main sections. The first section is the general introduction of the issue that needs to resolved. The second section defines more in depth the problem and sets the research questions, in accordance to that, in the third section the research methodology is developed. In the fourth section the results of both methods are presented. The fifth sectionfocuses on a reflection of the project, while the sixth section presents the final conclusions. Finally, the seventh section contains the specifics of the project management itself.

The project was carried out in cooperation with Dassault Syst`emes and is developed in the context of the GEO1101 course in MSc Geomatics TU Delft. In addition to this report we have created a GitHub repository (https://github.com/Fabisser/facesBgone) that contains the source code of the two methods.