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Validation Case: Pedestrian Wind Comfort: AIJ Case E

This document validates pedestrian wind comfort results obtained using Incompressible (LBM) analysis type in SimScale against the experimental ones from the Architectural Institute of Japan (AIJ).

With the increase in the number of high-rise buildings all around the World, proper planning of the vicinity for comfort and safety becomes important. Computational Fluid Dynamics (CFD) seems to be an apt solution in assessing these comfort and safety levels even before the buildings are erected and also helps in faster design iterations. Pedestrian-level (micro-climate) condition is one of the first microclimatic issues to be considered in modern city planning and building design\(^1\).

Wind analysis results using CFD simulation are now seen as reliable sources of quantitative and qualitative data, and they are frequently used to make important design decisions. However, to have full confidence in those decisions, extensive verification and validation of the CFD results are necessary.

For this reason, the team of application engineers at SimScale make sure to validate all the major features that are rolled out over time, comparing the simulation results to analytical or experimental data. Recently, we used experiments from the Architectural Institute of Japan (AIJ) to validate the results gained from the SimScale platform. In this article, we will focus on AIJ Case E.

streamline animation of lbm simulation in simscale
Animation 1: CFD simulation of wind around buildings carried out using LBM analysis with SimScale.

Architectural Institute of Japan (AIJ) Pedestrian Wind Comfort Experiments

The Architectural Institute of Japan (AIJ) is a Japanese professional organization for architects, building designers, and engineers. It was founded in 1886 and has gathered over 38,000 members since. It publishes several journals, technical standards for architectural design and construction, and research committee studies.

The wind analysis test case for this validation was taken from the “Guidebook for Practical Applications of CFD to Pedestrian Wind Environment around Buildings”\(^3\), published by AIJ in 2008, which sets the standards for cross-comparison between the results of CFD predictions, wind tunnel tests, and field measurements, and helps validate the accuracy of CFD codes for pedestrian wind comfort assessments.

AIJ Case E:

Wind Analysis in an Urban Area

The case being validated is Case E, which is a simplified geometry of a complex of buildings. The urban area model treated here was an actual city block in Niigata city, Japan, with low-rise houses jammed closely together and one target high-rise building at 60m high. Wind tunnel experiments at 1/250 scale were performed on this model in a turbulent boundary layer with a power-law exponent of 0.25.

Out of the many scenarios presented in Case E, the impact of the winds from the north, east, south, and west was used to validate the lattice Boltzmann solver of SimScale.

Geometry and Methodology

The below picture shows the AIJ Case E geometry with the main buildings highlighted: 

aij case model representation
Figure 1: AIJ Case-E CAD model with main buildings highlighted.

The original CAD model was downloaded as the .DXF file from the AIJ website and converted it to an STL file. This STL file was then imported to SimScale directly and used for simulation.

Simulation Setup

Inlet velocity and turbulent kinetic intensity profiles were applied using the table-input feature in SimScale.

velocity and turbulent kinetic energy intensity used as boundary conditions
Figure 2: Velocity and turbulent intensity profiles.

In comparison to the traditional CFD solvers, which uses the k-epsilon turbulence model, the SimScale-Pacefish solver uses a Delayed Detached Eddy Simulation model (DDES). The DDES model has an advantage of switching between the Large Eddy Simulation (LES) at regions where the mesh lattice is fine enough and the Reynolds Averaged Navier-Stokes (RANS) model where the solid boundaries are present to well resolve the boundary layers.


For the simulation, the mesh is optimized with automatic refinements to capture details in the geometry and avoid a large number of cells in unnecessary regions.

cartesian mesh visualization in simscale post-processor
Figure 3: Cartesian mesh used for case E simulation.

Meshes, like the ones shown above, created in SimScale using LBM approach are Cartesian meshes which are comprised of standard cubic elements only.

CFD Analysis Results

To compare the CFD wind analysis results to the experimental data, the velocities were normalized with the reference inlet velocity at a height of 15.9 \(m\) from the ground. The measurements were taken at points listed in the AIJ guidebook\(^3\). The CFD results obtained from the SimScale platform were plotted against the experimental results to see the correlation.

Correlated results are posted here for four wind directions (North, South, West and East).

The correlation between the AIJ experiments and SimScale results were highly linear, with a majority of the points being within 0.2 value of the relative velocity.

North – Wind

comparison between graphic data from aij measures and simscale results for north wind
Figure 4: Relative velocity comparison between experimental and SimScale CFD results for a Northerly wind.

South – Wind

comparison between graphic data from aij measures and simscale results for south wind
Figure 5: Relative velocity comparison between experimental and SimScale CFD results for a Southerly wind.

East – Wind

comparison between graphic data from aij measures and simscale results for east wind
Figure 6: Relative velocity comparison between experimental and SimScale CFD results for an Easterly wind.

West – Wind

comparison between graphic data from aij measures and simscale results for west wind
Figure 7: Relative velocity comparison between experimental and SimScale CFD results for a Westerly wind.

The results shown here are statistically averaged from the transient output from SimScale. SimScale provides the feasibility of statistical analysis of data points and plotting peak values. These results show that, as the correlation plot suggested, the CFD simulation with SimScale and the wind tunnel experiments produce very similar data.

The main advantage of implementing the lattice Boltzmann method using the Pacefish® solver with SimScale mainly stands out in the improvement of accuracy over the normal OpenFOAM® models. General artifacts like overprediction of velocity values at higher velocity regimes can be tackled by this solver cutting down the runtime drastically from over 2 days of simulation (for one wind direction) to about 10 hours. This is a major advantage over computational time reduction which turns out to be a time and cost saver, especially in architectural aerodynamic simulations.


Results from SimScale LBM solver show a great correlation with the experimental results. Buildings in urban areas have complicated shapes and are distributed in an irregular manner, making physical testing difficult and expensive. With the accuracy of CFD codes steadily increasing, simulation has become a viable substitute, and it has been adopted by architecture and construction companies all over the world for assessing pedestrian wind comfort, wind loads on buildings, skyscraper aerodynamics and more. A strict verification and validation of simulation results, however, remains critical for engineers to be able to use the obtained data with confidence and base important design decisions on it.


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