Olivia Wood

I have a strong interest in Computational Fluid Dynamics (CFD) and fluid mechanics in general. After taking Dr Jianfei Xie's CFD module, I decided to take on a project with him as his lectures were very interesting and intellectually stimulating.

For my final year project I had prior CFD knowledge using Star CCM+, however I chose to teach myself Ansys Fluent in order to broaden my software skills set. I will be staying on at the University of Derby after graduation to complete a Masters course - MSc Mechanical and Manufacturing.

I plan to complete another CFD project; a continuation of this project or a completely different area of CFD to increase my capabilities for CFD graduate jobs.

Active Control of the Climate in a Neonatal Intensive Care Unit (NICU)

Introduction

In any health care setting, it is important to monitor and control airflow and ventilation. Airborne disease and infection pose as a potential fatality to already vulnerable individuals. Bacterial transfer can be increased with certain airflow patterns which involve lots of recirculation, which is why ventilation is important in this type of environment so that recirculation can be reduced where possible. Main research aims:

• Observe flow physics and heat transfer in a Neonatal Intensive Care Unit (NICU) due to AC and hydronic wall mounted radiator
• Use steady-state CFD simulations to provide a robust indoor climate with optimal thermal comfort in a room with forced and natural convection influence using the finite volume method (FVM)
• Explore artificial intelligence (AI) applications for a NICU

Method

Using Ansys Fluent, CFD simulations were carried out on a geometry modelled on SolidWorks. A mesh independence was first conducted, using a coarse mesh throughout the domain, before mesh density was increased in all major zones: inlet, outlet, walls incubator lid, light and the radiator.

Heat transfer and air flows are modelled as air enters the domain through the inlet air-con (AC) unit, and passes over foremost geometries.

Results

Eddies are most prominent and turbulent near boundaries such as the incubator lid, especially in the corners, near the ceiling and outlet wall as expected. Recirculation occurs when air does not exit through the outlet in the first cycle and circles back toward the inlet where air mixes again and eventually leaves the domain at the outlet vent.

Conclusion

The flow physics of the NICU is predicted based on the Navier-stokes conservation equations for continuity, momentum, and energy for incompressible flows.

• Air velocity is highest at the lamp due to wall roughness, and at the inlet
• Temperature peaks at 50⁰C at the radiator, where air mixes with the inlet 15⁰C air until thermal equilibrium is reached and the room becomes 20⁰C
• Eddies mainly feature in corners and close to major boundaries
• AI can be used in unison with skin probes to track masses of bodily information and patterns, which is used for machine learning (ML) to predict fatalities like birth asphyxia, seizures, sepsis, and respiratory distress syndrome