Computation Fluid Dynamics (CFD) simulations are used in a diverse set of fields such as aerodynamics, automotive, biomedical engineering and wind impact. With the advancements in technology the scale of these simulations has increased significantly. This has resulted in \textit{massive} CFD simulations --- simulations that do not fully fit within RAM. Due to the limitations in RAM, visualizing the results of \textit{massive} CFD simulations has become an issue, mainly on personal computers. Existing solutions necessitate either substantial external servers equipped with sufficient RAM, a costly and inefficient approach that struggles to accommodate increasingly larger CFD simulations, or reliance on manual intervention for data loading and unloading. However, manual intervention introduces potential for error.

This thesis proposes a solution to automatically load/unload data from memory based on real-time demand. To achieve the proposed solution the methodology is split into two main stages: \textbf{(a)} pre-processing and \textbf{(b)} visualization.

The pre-processing is required to efficiently manage the \textit{massive} amount of data during the visualization step. It involves segmenting the study area into smaller, more manageable regions. Furthermore, it generates multiple level of details for each region such that the desired level of detail can be used as required.

The visualization is performed within game engines --- Unity for this thesis. Game engines provide a solid starting platform as they include aspects such as read/write operations, rendering capabilities, and flexible code execution. During visualization, the relevant regions --- regions that are within the user's point of view --- are automatically loaded into memory. subsequently, regions that leave the user's point of view are automatically loaded out of memory. Utilizing iso-surfaces, volume rendering, and barbs, the loaded data is then presented to the user.

The results showcase that visualizing \textit{massive} CFD results within game engines is possible in real-time. However, through the data transformation performed in the pre-processing step the data has lost some accuracy. Thankfully, an downward trend can be seen in the loss of accuracy as the level of detail increases. The result show that for data used in the thesis the pre-processing takes between 390 seconds (6 minutes and 30 seconds) and 972 seconds (16 minutes and 12 seconds). Furthermore, a data size reduction of up to 84\% can be seen after the pre-processing has finished.

Computational Fluid Dynamics (CFD) simulations for residential areas are becoming increasingly important as the urban population keeps growing and extreme weather conditions due to climate change are becoming more prevalent. Since CFD simulations simulate and visualise fluid flows, users can analyse and predict air flows in urban environments, giving insight in pollution, heat dissipation, and weather conditions. Performing these simulations demands expertise and time: 3D urban models must be prepared, and pre-run setups must be defined to obtain accurate results. Partial automation can streamline this process. Therefore, we developed a method that identifies geometric errors and defines mesh parameters for the open source CFD software OpenFOAM. This method follows the ISO19107 standard and recent CFD guidelines for urban areas, ensuring accurate simulation results. We validated algorithms with a variety of urban models and parameters, and analysed the workflow developed for the mesh parameters definition. Additionally, we created a prototype, in the form of a web application, in which these algorithms are implemented. Our prototype will simplify the use of CFD simulations for urban areas, making them more accessible to everyone.

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.

Planting trees is widely considered an effective way to create a good urban wind environment, improve air quality, mitigate heat island effects, improve pedestrian wind comfort and reduce building energy consumption. To assess tree effects and find suitable tree setups in urban areas, Computational Fluid Dynamic (CFD) simulations can be used.
To handle trees in CFD simulations, the implicit tree modeling approach, i.e, the porosity model, is widely used where finite volume cells that roughly account for trees are marked as porous zones. Some studies have also attempted to model trees as obstacles rather than porous zones, which can be referred to as an explicit tree modeling approach. The difference between these two approaches deserves further study. Also, for practical purposes and lack of information, the geometric features of trees are usually oversimplified or even ignored in CFD simulations.
This thesis investigates the difference between implicit and explicit tree modeling approaches and analyzes the impact of tree Level of Detail (LoD) and shapes on the flow structure. For comparative analysis, several numerical test cases with different urban complexities, tree modeling approaches, tree LoDs, tree shapes, Leaf Area Density (LAD) values, and wind directions were used for CFD simulations.
The results show: (a) the implicit models always allow some of the wind flow into the porous cells no matter how high the LAD values are, resulting in smaller wind acceleration on the lateral sides of implicit tree models; (b) for the idealized street canyon and realistic urban geometry test cases simulated in this thesis, the velocity magnitude differences between the LoD2 cases and the LoD3 cases are rather limited, with maximum differences in the order of 0.5 m/s; (c) differences in tree shapes, LAD values, and wind directions will change the effects of tree modeling approaches and tree LoDs on wind. For instance, the case using an isolated explicit LoD2 conifer tree model has a different wake flow pattern from other explicit cases. Also, with the inflow direction perpendicular to buildings, the higher the LAD values, the larger the velocity magnitude difference between cases using LoD2 tree models and those using LoD3 tree models.

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.

Urban physics is a multi-scale and interdisciplinary field, that combines science and engineering for the study of physical processes in urban areas. Computational Fluid Dynamics (CFD) is considered a powerful tool for the study of these processes. In the context of microscale phenomena these processes refer to the transfer of heat and mass in the indoor and outdoor urban environment, and can be observed up to ≈1km above the surface of the Earth. Their development takes place inside the Atmospheric Boundary Layer (ABL), which for the case of urban areas is referred to as the Urban Boundary Layer (UBL), and is formed due to the interactions between the surface obstacles and the wind flows. In CFD simulations the surface of the Earth and the encountered obstacles are represented with the use of 3D models, as well as estimated values that are used to implicitly represent their roughness. In this thesis the aim is to investigate relevant to CFD parameters that could be used as 3D model semantics. For this purpose, a list of parameters was identified. From this list roughness length was selected and a methodology was developed for the assignment of roughness values for the open-source software OpenFOAM. The developed methodology that was built using built-in functions of OpenFOAM, is based on an octree data structure that is used to store the input triangulated model in obj format. The roughness length landuse names are stored in an mtl file that complements the input obj and the roughness length values are specified as a user defined parameter using the landuse names. The process is semi-automated and it entails the assignment of non-uniform roughness at the bottom of the computational domain. Additionally, a methodology to assign non-uniform roughness at the inlet of the domain was developed. The results showed that the assignment of non-uniform roughness at the bottom of the domain was successful for cases of flat terrain, however, under the restriction that the input geometry model abided by certain geometry guidelines, such as no self-intersections, no gaps. For the case of non-uniform roughness at the inlet the process also produced satisfactory results in terms of the assignment process, however the impact of multiple roughness values at the inlet on the calculated flow parameters requires further investigation.

Wind has a profound impact on the meteorological and environmental conditions in cities. And so, by understanding wind flow behaviour within the urban environment, we can use the increasingly available open data to contribute to the design of healthy cities. This Master’s thesis presents a methodology to compute urban morphological parameters and its effect on potential wind velocity. The proposed method may serve as an complementary method to Computational Fluid Dynamics (CFD) simulation or scaled wind tunnel tests. The research question in this thesis is: Can we use urban morphology to automatically calculate potential increase in wind velocity? To answer this, first an introduction to wind flows in the urban environment
is presented. Then, several methodologies are presented to compute the urban morphological parameters, such as the Urban Canyon, wind- or leeward facade, Angle of Attack and terrain roughness length. The method relies on the use of a Voronoidiagram, with cells describing the morphology. After, the urban morphological parameters are related to potential wind velocity through a scoring method. Using two meteorological stations inside the area of interest, the mean wind velocity is compared to the scores. The result show that both stations show a higher mean wind velocity for higher scores. However, more research is necessary to validate this outcome and a recommendation is given to compare the result of this thesis to a CFD simulation.

In 2017, the ‘Kustpact’, a Dutch national agreement, was signed to develop the Dutch coast without damaging its ecosystem nor its aesthetics. Consequently, the formation and protection of coastal dunes have become a focal point for research and development. For this reason, based on the idea of Performance-Based Design (PBD), this Master thesis aims to investigate the impact of certain geometric design parameters of beach house configurations on wind turbulence for the purpose of widening the dunes.

A parametric design space was set up to easily automate Computational Fluid Dynamics (CFD) simulations for different purposes throughout this study. The sediment mobility estimation was the objective function for all simulations conducted. It is based on the difference of transport rate between two lines from the beginning of the plateau to the foot of the dunes. To simplify the parametric model, a Sensitivity Analysis (SA) was conducted to statistically identify the most influential parameters in the model. Afterward, the filtered parameters from the SA are used to build a surrogate model to detect the trends that result from combining the most influential parameters. Finally, a Surrogate-Based Optimisation (SBO) is conducted based on the former surrogate and using a Genetic Algorithm (GA). Three generations were run and used to increase the accuracy of the surrogate and predict an optimum solution for widening the dunes.

The study concludes on a list of design criteria to respect in order to widen the dunes mainly pertaining to the consistent position of the configuration relative to the dunes, the important overlap between houses and the larger wind-facing direction of the configuration.

In the Netherlands, the coastal dunes are essential to protect the country against flooding. However, the rising sea levels increase the risk of flooding along these sandy shores. Moreover, due to a combination of human and natural activities, dune erosion has increased and will continue to do so in the coming decades. Besides flood protection, the Dutch shoreline is important for preserving biodiversity, the generation of drinking water and recreation. In recent year, the number of recreational buildings on the beach, such as bars and holiday homes has increased. This is relevant because previous studies show that such beach buildings affect the wind flow and limit aeolian transport of sediment towards the dunes.

This research studies the impact of beach house configurations on dune-ward sediment transport to limit the adverse effects on dune development. We use CFD simulations to study the wind flow around a 3D model of a beach with holiday houses, based on a section of the Noordwijk beach in the Netherlands. We implement the CFD software OpenFOAM to solve the RANS equations for turbulent, steady-state flow. The sediment transport that occurs is calculated using the wind direction and speed near the ground surface of the solution.

The study consists of multiple 3D models in which the placement of the houses is varied systematically, to study the effects of beach house configurations. Variations are made by rotating houses, individually or within a row, and changing the distance between the houses and dunes. We determine the annual effect on sediment transport by applying varying wind conditions based on historical wind data from Noordwijk.
As we have many simulations to run, and all need different parameters and settings, we automated the process. First, a PostgreSQL database is used to store all requirements for the CFD simulations, the metadata and the results the simulations give. Then, a Python script links the information stored in the database to the correct settings in OpenFOAM. This way, many simulations are run in a row, and the results area to compare.

The results show that rotating the houses individually towards the prevailing wind direction appears to improve the amount of dune-ward sediment that takes place, compared to beach houses placed perpendicular to the shore. Rotating a row of houses as a whole has a limited effect on the amount of sediment transport. However, combining the rotation of the row of houses and the houses individually towards the prevailing wind direction shows the best improvement in sediment transport. Changing the distance between the houses and the dune foot so that a row of houses forms a funnel shape pointing towards the dunes also yields promising results.
Because we use a simplified model and do not take factors such as moisture levels or fetch distance into account, the results of this study overestimate the amount of sediment transport that takes place and might not quite resemble the reality. Further research using scale models or wind tunnels is necessary to confirm the suggestions made in this thesis.

In current study, several fundamental and inherent problems in original Deardorff subgrid model are identified under stably stratified condition. It is found that the mixing length parameterization in this subgrid model is at the root of a long trouble problem of grid size sensitivity in large-eddy simulation (LES). A new formulation of mixing length is proposed under the consideration of some basic elements including the presence of surface, the dependence of grid size Δ and a smoothing interpolation. The performance of this modified scheme is remarkable regarding the improvement of the simulation quality and accuracy. In other words, not only is the convergence of the simulated results from a range of grid size achieved but also in the precise intensity of physical variables are modelled. The only discrepancies display in the variance of temperature in the middle of boundary layer and high turbulent kinetic energy near the surface.

To further experiment the performance of the new scheme under different scenarios, the cases of different stability condition, an independent LES code with same modification, the cases of different advection schemes and different prescribed parameters are explored. In very stable condition, the first order variables from the modified scheme are in reasonable range but with some spreads compared to the results from a dynamic code. The deviation of second order statistics shows that the proposed formulation of mixing length meets limitations due to the complex interaction between the surface and turbulent flow in shallower boundary layer. The modified scheme is model system independent based on the similar improvement of simulation results in an independent LES code system. The sensitivity of advection schemes is surprisingly hardly found in new proposed SGS model. The cases of tested parameters further verifies the limitation of original Deardroff subgrid model.

Rising temperatures due to climate change and the increased Urban Heat Island (UHI) effect both have a major impact on Singapore’s outdoor comfort. Research has reported an average UHI in Singapore of 4°C, which can even exceed 7°C at some times of the day. (Acero & Ruefenacht, 2017) Increasing convective surface heat transfer from the human body by means of induced wind speeds is an important strategy to improve outdoor thermal comfort. However, the combination of its high urban density, leading to a considerable number of obstructions for urban wind flows, and the generally low wind speeds due to its geographical proximity to the equator makes urban ventilation in Singapore challenging. (Acero & Ruefenacht, 2017) Since the 1970s, void decks, open spaces at the ground floor of buildings, have become a typical characteristic of public housing flats in Singapore. These have been shown to potentially increase wind speeds by more than twofold. (Chew & Norford, 2019) However, the effect of void deck geometries on the imbalance between outdoor thermal and pedestrian wind comfort in a realistic urban setting has not been addressed before.
Hence, the main research question of this thesis was formulated as follows: How can the geometry design of void decks be optimized to enhance urban ventilation for outdoor thermal comfort in Singapore while ensuring good pedestrian comfort?  A strong mismatch between pedestrian wind comfort and outdoor thermal comfort was observed in the study area with the simulated monsoon wind conditions. This marks the importance to perform wind microclimate analyses in a tropical environment as Singapore, focusing on both aspects. This work demonstrates a design methodology that combines parametric design tools with CFD (computational fluid dynamics) simulations with the aim to make better wind-informed design decisions for an urban context. 
Using a parametric building model, ten void deck geometry variants were generated and compared. The implications of the observed flow pattern in terms of urban planning were clarified. For example, while a horizontally converging void deck geometry was found to be effective at directing the urban ventilation towards a target location due to the funnel-shaped induced wind speed region downstream, horizontally diverging void decks led to a more evenly spread region of accelerated flow along the void length. The highest amplification factors inside the void deck were obtained for a vertically diverging geometry. This geometry was subsequently applied to all the buildings facing the prevailing wind directions in the study area, Clementi, using a parametric urban model. This model allows the user to apply various void deck geometries to different building groups independently from each other based on their orientation. A comparison of the wind speed and air temperature distributions after the urban-scale intervention to the current situation showed a wind speed increase and temperature decrease in almost all the void decks. While the amplified wind speed region extended downstream of some void decks, other areas in between the buildings showed a slowed down wind flow. The temperature effects were more extreme at the more closely-packed areas with a smaller distance in between the buildings. Overall, it was concluded that the void deck modifications did not only affect the local wind microclimate inside the void decks, but also altered the wind conditions in between the buildings. Ideally, these wind speed-amplifying void decks should be used in combination with other urban cooling strategies. 
The proposed workflow was demonstrated for the geometry design of void decks, but is also applicable in the optimization process of other building features which may affect the urban wind microclimate, such as canopies and building podia.

The surface water extent around the world is constantly changing due to natural factors (e.g. geology and over-abstraction of water), climate change (e.g. higher water evaporation due to warmer climate) or human activities (e.g. reservoir construction). Water reservoirs are important for the management of the ecosystem, as both humans and the natural environment depend highly on them for their existence and well being. Flood control, agricultural irrigation, electricity generation, drinking and municipal water supply are only some of their main uses. Considering this, it is of high importance to have accurate maps that depict the reservoir outlines to determine their surface extend and storage capacity. However, their extend is not always well defined or there are discrepancies between various surface water datasets. This dissertation aims to provide an answer about which datasets match better as well as identifying the problematic areas by performing a quality control analysis. The main challenge of this thesis is that all available datasets have certain limitations regarding their coverage and quality. The waterbody delineation from satellite images is affected by the atmospheric conditions (e.g cloud obstructions) or topographic elements that create artifacts and influence the correct classification of water pixels. OpenStreetmap (OSM) on the other hand, has uncertain quality over locations, as the data is freely supplied by volunteers. Moreover, HydroLAKES which was created based, amongst others, on the Global Reservoir and Dam Dataset (GRanD), is still incomplete. In this thesis, an intercomparison of accuracy algorithm that can perform large scale analysis is created, by using the country of Angola as a use case, five datasets as input (Global Surface Water, Sentinel 2, OSM, HydroLAKES, GRaND) in both raster and vector format and the cloud processing platform of Google Earth engine. The identification of similarities or mismatches between the datasets is performed in terms of positional accuracy. Two quality measures have been considered for the pairwise comparison of features: percentage of overlap and Hausdorff distance. In addition the completeness of the datasets respectively to the total common water area of the water reservoir datasets is reviewed. The results of this research shows that large scale analysis for the comparison of accuracy between water reservoir datasets of different formats is possible. The pre-processing of the input Satellite data is semi-automated. The created automated algorithm for the main analysis offers information for all corresponding features between datasets. More specifically, statistics about the shape similarity, the percentage of overlap and the water area completeness of the datasets are being presented.

In 2021, noise pollution monitoring will be mandatory in the Netherlands, which requires data on traffic that can be re-used for air quality estimation models. One of the important input parameters for the latter is the street type, which is required by the dilution parametrisation used within the air quality model.
The goal of this project is to show whether automatic street classification for air quality estimation is feasible and reliable, considering the geo-spatial data currently available in The Netherlands. The motivation for this project originates from the common data used in noise and air quality monitoring tools by the Dutch National Institute for Public Health and the Environment, (RIVM).
Currently, street classification is performed manually by many municipalities. The larger municipalities are legally obliged to monitor air quality levels, which makes use of the street types. Automating the process by using existing datasets can save a lot of time, costs, and resources, while providing standardised results in comparison to manual classification. In addition, our method is extendable to the whole of the Netherlands. Consequently, our method can have a large societal impact, since it allows the provision of air quality estimations for all municipalities; even those that are not yet required to do so. To our knowledge, no similar work has been conducted in this field, which made it even a bigger challenge.
The implementation of the automatic classification algorithm, which is thoroughly explained in this re- port, shows very promising results. We first tested the approaches in a small area, the Weesperstraat in Amsterdam, where we have success rates from 76.7% to 83.3% for the different classification methods when compared to the NSL classification. After evaluating the performance of each of the methods, the optimal approach has been tested on larger areas where visual inspection shows a priori promising results as well.
In addition to the automatic classification algorithm, air quality measurements with new Flow sensors from Plume Labs were performed in the city of Amsterdam. The goal was to investigate whether different street types can be identified through the use of small air quality sensors. The limited measurements did not provide distinct patterns for the different street types, and therefore identification based on pollutant concentrations was not possible within the project.
We hope that the results of this project will motivate public bodies and agencies in the Netherlands to invest in automated workflows using currently available and high accuracy geo-spatial data. This can potentially improve their efficiency, while creating a more standardised and scalable framework.