Emergency room simulation

An emergency room is designed to house several patients at the same time. It is important to be able to assess and minimise the dispersion of airborne pathogens inside the emergency room to avoid the spreading of diseases. A Computational Fluid Dynamics (CFD) simulation is carried out to simulate how the pathogen travels inside the emergency room and which are the most effective solutions to control its dispersion.

Emergency room simulation using SimWorks Manager

The emergency room simulation is intended to evaluate the dispersion of an airborne pathogen and how that one is affected by tuning to the ventilation system. The simulation is carried out using SimWorks Manager Computational Fluid Dynamics (CFD) software.

The emergency room simulation tutorial is using the same boundary conditions as the ones used in the study [1]. The scope of the simulation is to evaluate how the pathogen released by a single patient in a typical emergency room is travelling in the room. In particular areas with a concentration higher than a specific value are highlighted using isosurfaces, those areas can pose a risk for other patients in the room.

The simulated emergency room has 10 beds in 2 rows and one of the bed is occupied by a patient. The body of the patient is simulated with a prism and we will apply a constant temperature to it. In the same manner, an additional geometrical feature is added to simulate the patient’s mouth.

Two rows of inlets (displayed in blued in the image above) and two rows of outlets (in red) are located on the roof to provide the required level of ventilation. All the air coming from the inlets is filtered and does not contain any contaminants. At the same time the temperature is controlled.

Before starting the tutorial download SimWorks and validate your 14-day free trial contacting us and download the tutorial geometry:

Define the simulation

As already seen in the SimWorks advanced introduction tutorial define a new project, geometry and simulation
Rename them as Hospital design, Emergency room simulations and Emergency room simulation original respectively
Load the emergency_room.igs file
Select the Part names layering and hide the Roof part

Simulation setup

For this simulation we need to enable the buoyancy to correctly simulate the flow induced by air density variations
Enable the passive scalar to simulate the dispersion of an pathogen inside the room

Surface normals check

Use the Surface normals layering to set the correct the sign of the boundary normal velocity
All the inlets, outlets and the patient’s mouth are yellow meaning that a negative value will be entering the room, so all the boundary normal velocities will have to be negative

Boundary conditions

The part group Inlet has to be defined as a Velocity Normal inlet with a speed of -0.62 m/s (the sign has been discussed in the previous paragraph) and a temperature of 23° or 296.15 K
The Outlet part group is defined as a pressure outlet with 0 Pa of pressure difference
The PatientBody will have a constant temperature of 31° which are 304.15 K
The PatientMouth will have a speed of -0.2 m/s, a value of 1.0 for the passive scalar and a temperature of 309.65 K (36.5°)

Mesh parameters

It is important to capture the dispersion of the pathogen released by the patient, it will be necessary to refine the mesh of the patient body and his mouth more than the surrounding mesh.

Define a mesh group with the PatientMouth, to define it select the PatientMouth from the dropdown menu and press the Create new part group icon in the Simulation editor. Assign a refinement values of 5 5 to it, this means that both the minimum and the maximum levels of refinement will be 5
Similarly define a new part group with the PatientBody and assign a refinement levels of 3 3
Define a new part group with the Inlet and assign a refinement levels of 2 2
The remaining patches will require a value of 1 1 refinement levels
The base mesh size will be 0.1

Output

Before running the CFD simulation it is necessary to define the output planes required and the isosurfaces necessary to visualise the portion of space where the concentration of pathogen is above certain levels.

Define 30 planes in each direction and limits in X -5, 5, Y -3,3 and finally in Z 0, 3.2
Click on the add isosurface icon in the Simulation editor menu
Define 5 isosurfaces of passive scalar with values 0.001, 0.0015, 0.0175, 0.002 and 0.0025

Running the simulation

In the Simulation editor window it is now possible to increase the number of processors to 4 and the maximum number of iterations to 2000 to make sure that the solution will fully converge before assessing the results. Afterwards you can run the setup phase, the mesh phase and the running phase, depending on the machine you are using the process can take 10-15 minutes.

Postprocessing

Load the results in the Fields viewer right clicking on the simulation and selecting Fields → Load to visualise the results of the simulation

Select the passive scalar isosurface 0.0025
The surfaces shows the area inside the room where the passive scalar value is above 0.0025 showing the areas where the pathogen concentration is the highest
Define the U value between 0 and 0.05

It is possible to use multiple isosurfaces to understand the passive scalar distribution inside the room

Show the passive scalar isosurfaces 0.0025, 0.002, 0.00175, 0.0015
Select the passive scalar as main variable and define a legend between 0.015 and 0.025
The area highlighted inside the blue area is where the passive scalar is below 0.015
The area in the corner region is where the passive scalar is above 0.0025 and this is where the pathogen concentration is the highest

Effect of increasing the mass flow rate

Increasing the inlet mass flow rate has a big effect on the passive_scalar distribution. To check this effect once the simulation is completed we can duplicate it right clicking on the simulation in the Simulation manager window and then selecting Simulation manager and Duplicate. Once the simulation is duplicated it is possible to reload the geometry in the Geometry viewer and finally double the inlet velocity in the Simulation editor from -0.62 m/s to -1.24 m/s.

Once the new simulation is completed just load it in the same Fields viewer of the first one (right click on the completed simulation and then select Load). It is now possible to directly compare the isosurfaces:

You can see in the image above that doubling the inlet velocity shows a clear improvement in the airborne pathogen dispersion, with most of the room now showing values of passive scalar concentration below 0.001. Only a small area in the top portion of the room next to the ceiling and the walls is showing values of passive scalar above that threshold, while in the original simulation the average passive scalar value was above 0.002.

Conclusions

CFD is currently one of the main tools to simulate the dispersion of an airborne pathogen. Using the passive scalar approach it was possible to predict accurately the pathogen dispersion in the emergency room [2]. From the passive scalar distribution it is also possible to assess the actual infection probability for a person inside the simulated space using the Wells-Riley equation, a successful application of this approach can also be found in [1].

Once the emergency room simulation is completed it is possible to quickly and easily modify the simulation setup parameters in SimWorks Manager to optimise the design to achieve a specific purpose. For instance in the example above it was easily proven the big effect of increasing the inlet velocity on the passive scalar dispersion, at the same time it is also possible to change the inlets and outlets positions in CAD to further optimise the design.

Disclaimers

The results and the description provided above where defined to describe physical behaviours under certain circumstances. They should not be considered a medical guidance and do not account for environmental variants such as humidity or wind.

Resources

[1] – Chang Heon Cheong ,Seonhye Lee (2018) – Case Study of Airborne Pathogen Dispersion Patterns in Emergency Departments with Different Ventilation and Partition Conditions – International Journal of Environmental Research and Public Health

[2] – Sung, M. (2015) – HVAC system and contamination control in hospital relating MERS. – Mag. Soc. Air-Cond. Refrig.

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