UV-C surface disinfection of a medical mask

This article illustrates how you can assess the performance of a lighting disinfection system through optical simulation. In this example, we will introduce a simulation workflow to analyze how the lighting conditions inside a short-wave band UltraViolet (UV-C) disinfection chamber can impact the exposure time for the surface disinfection of a COVID-19 mask.

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Overview

Understand the simulation workflow and key results

In the healthcare industry, working with sanitized equipment in critical to avoid diseases spreading, contamination and maintain a high sanitary standard.

Multiple techniques exist to efficiently sanitize medical equipment, one of the fastest being UV-based disinfection. The UV-C range of light (typically 200-280nm wavelength) has proven very efficient to directly affect DNA and kill various types of small organisms (bacteria, viruses, etc..). This technique is widely used in the pharmaceutical industry and applications such as air/water disinfection.

The disinfection efficiency, i.e., "how much light" is needed to kill the micro-organisms on an object, is commonly assessed by the UV dosage (in J/m²) given by:

$$UV_{Dosage}=\int_{t}{{UV}_{Intensity}dt}$$

where \({UV}_{Intensity}\) (W/m²) is the amount of UV radiation received on the object.

The UV dosage is obtained by integrating the UV intensity received by the micro-organisms over the time they have been exposed to the radiation. The above formula implies that the disinfection efficiency of a system highly depends on the lighting system output (wavelength, intensity) as well as the exposure time.

In this example we will only consider the surface disinfection of static objects inside a disinfection chamber.

We will assume, for reference, that a target \(UV_{Dosage}\) of 10mJ/cm² is needed to get an object fully disinfected from COVID-19 virus.

Step 1: Cabinet design with Speos

This disinfection chamber's optical setup is done inside Speos. We start with a first design of the cabinet, paying special attention to both the lighting system and the optical properties of the cabinet. We have spread the mask pieces inside, we will keep them in their original place through all this study, but results could further be improved by analyzing the optical efficiency throughout the cabinet space.

The lighting system of this first design is composed of 9x10 LEDS located on the ceiling part, each LED is individually emitting 5.5mW at 275nm, with a gaussian intensity profile. Hence, the total emitted power of the system is 0.5W.

The walls of the cabinet are made of white scattering paint, the door of clear glass.

We measure the UV intensity of the mask part with 3D irradiance sensors which enable to record the incoming irradiance directly onto the geometries, without the need of using plane sensors.

Step 2: Simulation and results analysis

After running the first simulation, we can assess the average UV intensity that reached the parts, hence we can calculate the time needed to get the 10mJ/cm² UV dose of disinfection.

In this first example, the average time needed for all the parts is 2mins and 33s. This duration can be further improved by looking at the results on each part individually, and taking the duration needed for the least exposed part. Under this consideration, we see that it would be preferable to keep the parts inside for 3mins and 20s.

Step 3: Iterate with a new design

The previous performances can be improved. By changing the lighting configuration and the optical properties of the chamber, we can reduce the time needed in the chamber for even faster disinfection.

In a second design, we have introduced more LEDS for higher UV power. We are now working with an array of 10x15 LEDS in the same previous operating conditions.

We have also added a mirror coating on all the interior walls of the cabinet, including the front door. This will enable us to keep all the UV energy inside the cabinet and redirect it towards the parts.

After running the simulations again, we see that now only 32 seconds on average is needed for all the parts, i.e., a reduction of 79% of the UV exposure time. When looking at the individual results on each part, a safer time would be 34s.

Run and Results

Instructions for running the model and discussion of key results

Step 1: Cabinet design with Speos

1. Open the "Cabin_Design_1.scdocx" project.

Inside the project, there is the geometry of the UV chamber, with the mask pieces spread inside. The lighting system is composed of a pattern of 9x10 LEDS located on the ceiling part. The following spreadsheet was considered as input for the LEDS:

We have chosen LEDS because they are known for their higher efficiency compared to neon tubes. For design simplicity, only 1 surface source is used to simulate the light from all LEDS at once. In Speos, when a surface source is emitting from multiple surfaces, the assumption is made that the energy emitted by the source object is proportionally spread according to the area of the emitting surfaces. More information about the surface source can be found here .

2. Double click on "UVc_Source" in the Speos tree.

In this example, assuming each LED emits 5.5mW radiant flux, we made the surface source emitting 0.0055x90 = 0.5W. The assumption is made that the LEDS only emit 275nm peak wavelength. The intensity distribution profile is gaussian.

Each geometry of the model has its own optical property. To easily retrieve each part's optical property and get a deeper understanding of the mode, you can follow these steps:

3. Make sure the BETA options are activated (File>Speos Options>Advanced>Enable beta features).
4. In the 3D view, right click on the geometry you are interested in.
5. Select the "Locate Materials" option.

The associated optical property is highlighted in the Simulation tab.

Alternatively, you can do the other way around:

6. Right click on the material you are interested in.
7. Select "Select associated geometry".

The associated geometries are highlighted in the 3D view and the structure tree.

For instance, in this case, the walls of the cabinet are all made of the white paint optical property. You can have a look in more details by double clicking on the "White_paint" optical property. Then in the Surface properties, you can expand the file name"9016_oven_white.brdf" and click "Open file" -> the BSDF surface viewer opens, and you can now play with the incident angles and wavelength to visualize the surface's optical response in reflection (BRDF).

Finally we have created 3D irradiance sensors mapped onto each part of the mask we want to sanitize, and an additional one mapped on all parts for an overview of all the pieces.

8. Double click on one of the sensors.

In the definition, you can see that the sensor type is set to radiometric, since the analysis is performed on the UV-C range of the light (not the visible range).

Step 2: Simulation and results analysis

1. Run the simulation "Direct_All_Parts" (it should take approximately 2mins on 12 cores CPU).
2. After the simulation is finished, double click on "Direct_All_Parts.All_Parts.xm3" to open the 3D results in the appropriate viewer.
3. Change the scale "Max" value to 1.5 W/m² and press Enter. You can see the color map directly onto the parts geometries.

4. Open the "Measures" tab.

The measure is set to obtain the average irradiance from the top of the geometries.

5. Alternatively, to get the average result, you can directly have a look in the simulation tree by expanding the "Direct_All_Parts.All_Parts.xm3" result.

The average obtained on all the pieces is 0.65 W/m². Since we want to reach the dosage of 10mJ/cm² on the pieces, the time needed for the pieces to stay in the cabinet is 154s (2mins and 34s). You can use the attached simple Excel calculator to obtain the exposure time needed.

This value is averaged over all the pieces. We can get a more accurate result by measuring the average irradiance on each piece.

6. Run the simulation "Direct_Individual_Components" (it should take approximately 2mins on 12 cores CPU).
7. After the simulation is finished, you can have a look at the average value obtained on each component directly from the simulation tree.

The table of the results obtained for each part (using the Excel calculator) is given here:

We can now see that the Gasket part is underexposed compared to the other parts. In this case, we need to leave it for at least 200s (3mins and 20s) in the cabinet to reach the target UV dose.

With this simple example, we have been able to get the duration time needed for disinfecting surfaces inside our cabinet with only one simulation. However, we want to improve the cabinet design to reduce the exposure time in the cabinet.

Step 3: Iterate with a new design

1. Open "Cabin_Design_2.scdocx" project.

It looks quite similar to the previous design, but we can note a few differences. The lighting system is now composed of 10x15 LEDS.

2. Double click on "UVc_Source".

Since we want the LEDS to work in the same conditions as in the previous case (5.5mW emitted radiant flux), the total power of the global source has been raised to 0.84W.

The walls of the cabinet, including the door, now have a mirror coating. The is now a "Mirror" face optical property in the Material tab. In Speos, the face optical properties override the surface properties indicated in the Volume and Surface property of the body. More information about Face Optical Properties can be found here .

3. Run the simulation "Direct_All_Parts" (it should take approximately 8mins on 12 cores CPU).
4. After the simulation is finished, you can directly look at the average value in the simulation tree by expanding the "Direct_All_Parts.All_Parts.xm3" result.

The average value obtained on all the pieces is now 3.14 W/m². Since we want to reach the dosage of 10mJ/cm² on the pieces, the time needed for the pieces to stay in the cabinet is now 32s. That means, with this new design, that we have been able to achieve a reduction of 79% of the average exposure time.

5. Run the simulation "Direct_Individual_Components" (it should take approximately 8mins on 12 cores CPU).
6. After the simulation is finished, you can have a look at the average value obtained on each component directly from the simulation tree.

The table of the results obtained for each part is given here:

With this new design, the gasket is still the least exposed component, but the exposure time needed for this part to get the target UV dose is reduced to 34s, hence a reduction of 83% compared to previous design.

Thanks to Speos, we have been able, by changing only a few parameters in our system, to significantly improve the performance of this disinfection cabinet.

Important Model Settings

Description of important objects and settings used in this model

Array of LEDS

An array of LEDS can quickly be modeled in Speos, with various models form different supplier datasheets. The generic workflow t do so is the following:

• Generate a single model of LED:
  • Open a blank project
  • Import the LED CAD geometry
  • Apply the right optical properties
  • Generate the source based on the datasheet (surface source, rayfile source, etc..).
  • Save the project.

Alternatively you can directly import an existing model from Speos Online Library (downloadable from Ansys Customer Portal under the Section "Add-On Packages>Optical Library").

• Generate the array of LEDS:
  • Open your main project.
  • Import the single LED file.
  • Select the component in the structure tree.
  • Go to Design>Linear Pattern.
  • In the options, choose either a One- or Two-Dimensional array.
  • Specify the dimension and orientation and validate.

Optical Properties

The optical properties of the geometries play a critical role in the results. Having accurate inputs for the simulation is key to getting accurate results. Speos comes along with an online library of materials you can use for your simulations (downloadable from Ansys Customer Portal under the Section "Add-On Packages>Optical Library").

Simulation Settings

Different types of simulation are provided in Speos such as direct and inverse simulation. The direct algorithm is the one we use here, with rays propagating from the sources towards the sensors.

Meshing settings

Meshing settings are critical for getting the correct simulation results. It defines the quality of geometries that will be simulated. The finer mesh gives better results but also requires longer time. Rough mesh can lead to poor results, especially at the precise optical component. Meshing in these projects is set to be proportional to the Face Size. Further details about mesh settings can be found in Meshing Properties .

Stop conditions/Number of rays

In an inverse simulation, you can define the criteria to reach for the simulation to end: the stop condition. To stop the simulation after a certain number of rays were sent, in the direct simulation definition panel, you can set the "number of rays limit" to True and define the number of rays to be launched. In this project, we used 20 000 000 rays to achieve a good result without too much noise.

If you want to adjust the direct simulation advanced settings, see Adjusting Direct Simulation Settings .

Post-processing settings

In this article, we measured the average irradiance coming from the top of the geometries. You can set up more advanced measurements, according to the shapes of your components. More information about measurements can be found here .

Alternatively, you can export the result data as text file by clicking on the export button from the results viewer.

Then you can integrate the absorbed power on all the parts using post-processing script. If this is interesting for you, you can contact us at support@ansys.com .

Taking the Model Further

Information and tips for users that want to further customize the model

Dynamic scenario

This study was made using a static scenario approach. However, it is also possible with Speos to investigate dynamic disinfection scenarios. The workflow would be the following:

• Create the 3D setup of your scenario.
• Apply optical properties to all surfaces.
• Define the lighting system.
• Define the motion path of the mobile parts.
• Run simulations at different time steps of the scenario.
• Calculate the cumulative irradiation on all relevant surfaces.
• Determine the speed requirements for the scenario based on the results.

Coupling with Fluent

In this study, we have been looking at the case of a surface disinfection system. More advanced cases, such as air/water disinfection, could be further investigated using Fluent simulation as input for Speos simulation. If this is interesting for you, you can contact us at support@ansys.com .

Additional Resources

Additional documentation, examples and training material

• Speos Getting Started
• Speos Workflow & Geometry Management