Corona Virus Patient Steady Breathing in Clean Room
$160.00 Student Discount
- The problem numerically simulates the Corona Virus Patient’s Breathing in Clean Room using ANSYS Fluent software.
- We design the 3-D model by the Design Modeler software.
- We mesh the model with ANSYS Meshing software, and the element number equals 5666870.
- We use the Discrete Phase Model (DPM) to define the release of coronavirus particles.
- We investigate two factors to evaluate Thermal Comfort: PMV (predicted mean vote) and PPD (predicted percentage of dissatisfaction).
If you decide to use PayPal to pay, you will get a 5% discount on your order.
To Order Your Project or benefit from a CFD consultation, contact our experts via email ([email protected]), online support tab, or WhatsApp at +44 7443 197273.
There are some Free Products to check our service quality.
If you want the training video in another language instead of English, ask it via [email protected] after you buy the product.
Corona Virus Patient Steady Breathing in Clean Room, ANSYS Fluent CFD Simulation Training
This project simulates the Corona Virus Patient STEADY Breathing in Clean Room using ANSYS Fluent software.
Hospital rooms need air conditioning. These air conditioners can continuously transfer the flow of fresh air into the interior of the room to clean the polluted air around the patient. These air conditioners are also used to provide proper cooling and heating.
In this simulation, a room with a bedridden patient is examined. The patient has corona and spreads the coronavirus particles to the environment. The patient’s mouth is distinctly defined as the source of respiratory coronavirus transmission.
Also, the patient’s body surface has a temperature of 308 K, which is one of the symptoms of his disease. The fresh air from air purification systems causes the polluted air and virus particles to be removed from the room’s interior. Secondly, it helps to cool the patient’s body surface and create thermal comfort for the patient.
Therefore, several panels are defined on the room’s ceiling for the entry of fresh air with a temperature of 294 K, and the air outlet is also from the panels of the lower part of the side walls.
The 3D geometry is drawn by Design Modeler software. The model is then meshed by ANSYS Meshing software. The model mesh is unstructured, and 5666870 cells have been created.
Corona Virus Methodology
In this modeling, the Discrete Phase Model (DPM) is used to define patient respiration and the release of coronavirus particles. If it is necessary to study the behavior of several discrete particles in a continuous medium, the solution approach must be changed from Eulerian to Lagrangian.
In this approach, their behavior is investigated by tracking discrete particles in a continuous fluid. When a corona patient breathes, the coronavirus spreads as discrete particles from the patient’s mouth to the surrounding air as a continuous environment.
So there is a need to use the Lagrangian perspective. Therefore, DPM must be used to modulate fluid behavior and define an injection for virus particles injected from the patient’s mouth. The virus particle type is inert, and the injection type is surface.
If the particles cross the boundary, the escape is used. If particles hit the wall boundary, the trap or reflect is used.
Corona Virus Conclusion
After simulation, contours of velocity, temperature, and pressure are obtained. Air conditioning pathlines are also provided. These results show that fresh airflow from the ceiling panels enters the room’s interior and is directed to the outlet panels after complete circulation inside the room.
Since DPM is used, particles of the virus released from the patient’s mouth are shown. The figures show that these virus particles are affected by the airflow of the air conditioning system. It means that they are directed by the fresh airflow to the outlet panels to be cleaned inside the room.
The concept of thermal comfort becomes important when modeling air conditioning systems. In this simulation, two parameters, PMV (predicted mean vote) and PPD (predicted percentage of dissatisfied), are used as factors to evaluate the degree of thermal comfort.
PMV value was obtained according to people’s votes in the different experimental thermal conditions. This parameter depends on various variables, including air temperature, humidity, airspeed, people’s physical activity, etc.
This parameter varies between -3 to +3. PPD value is then defined as an exponential function of PMV. This parameter indicates people’s degree of satisfaction or dissatisfaction with the thermal conditions of the environment. The results show that the values of PMV and PPD are suitable in terms of thermal comfort.