Features
This page explains the basic functionalities of City4CFD. Conceptually, features can be decomposed into:
- Terrain
- Buildings
- Surface layers
- Influence region and domain boundaries
The terrain is generated from a point cloud (LAS/LAZ, PLY, or TXT/XYZ format) as a triangulated irregular network (TIN).
Terrain can be thinned (points removed to increase efficiency) and smoothed. The intensity of thinning and smoothing can be controlled with parameters. You can see a terrain example before and after 5 smoothing iterations below.
By not including the point cloud, the terrain will be approximated as a flat surface.
Buildings can be created in different ways:
- Reconstruction using the combination of 2D polygons and a point cloud
- Reconstruction using 2D polygons containing height or number of floors attributes
- Importing existing 3D building models
Different methods can be combined.
For now, building reconstruction can be done in LoD1.2 (more information on LoDs). You can choose which percentile of building points is defined as a building height, as seen in the figure below.
Buildings are seamlessly integrated into the terrain, leaving no gaps at their intersection.
Surface layers are 2D polygons representing different surfaces (e.g. paved surfaces, water, low vegetation) that can be used to impose roughness values. They are imprinted into terrain and can be extracted as separate surfaces. They do not overlap with each other and their integration to the terrain is also seamless.
Sometimes, it is beneficial to force a flat surface. This is especially true when handling water surfaces -- due to the lack of LiDAR points in water, resulting triangulation can end up having zigzagged triangles. Flattening the surface layer solves that issue, see the figure below.
We refer to the influence region as the region where buildings are explicitly reconstructed. Both the influence region and the domain extent can be defined in three ways:
- With the point of interest and prescribed radius
- With an imported polygon or manually added polygon coordinates
- Automatically, using the best practice guidelines (BPGs)
The first method is pretty straightforward. All buildings that fall into the circle or those that are on the border of the circle with prescribed origin (i.e. point of interest) and radius are reconstructed, while the others are not. This method for the domain extent creates a round (circular) domain.
An example of the second method with manually defined polygons can be seen in the figure below.
The third method uses BPGs to automatically define the influence region and domain extent, respectively.
BGPs for the influence region are based on the work of Liu et. al (2018). The algorithm reconstructs the building of interest (defined by the point of interest) and defines the influence region as the multiplier of the largest building dimension. By default, the multiplier is set to 3.
From Liu et. al (2018)
BPGs for the domain extent use typical guidelines found in works such as COST Action 732, Franke et. al (2007) and Tominaga et. al (2008). The first condition is the multiplier of the highest building in the influence region, away from the influence region. The second condition is the blockage ratio of the buildings depending on the flow direction. Three types of domains can be set this way: rectangular, round, and oval. A schematic representation of BPGs and types of domains are shown in the figure below.
A buffer of the domain boundary replaces the non-flat terrain near the domain boundaries with a nearly flat surface. The idea is to remove perturbations near boundaries that can cause numerical stability issues in simulations.
