Optimal human respiratory simulation for exhaled gas based on CFD method.

Area of Science:

• Environmental Health
• Biomedical Engineering
• Computational Science

Background:

• Human respiration significantly impacts indoor environments and health.
• Computational Fluid Dynamics (CFD) is essential for simulating respiration.
• Enhancing CFD accuracy and efficiency is critical for reliable simulations.

Purpose of the Study:

• To develop a novel simulation strategy for human respiration.
• To improve the accuracy and reduce computation time of CFD simulations.
• To identify the optimal combination of boundary conditions and models for human breathing simulation.

Main Methods:

• Examined steady versus unsteady boundary conditions for respiration simulation.
• Analyzed jet center trajectory and pollutant dispersion near the mouth.
• Compared calculation accuracy, time, and memory usage of different turbulence and flow models.

Main Results:

• Sinusoidal exhalation boundary conditions showed distinct effects on simulation outcomes.
• The RNG k-ε model during exhalation and laminar flow during inhalation proved effective.
• A specific strategy combining sinusoidal conditions, PISO algorithm, and model switching was identified as optimal.

Conclusions:

• The optimal human breathing simulation strategy balances accuracy, speed, and resource usage.
• This optimized CFD approach enhances the study of indoor environments and human health.
• The proposed method provides a more efficient and accurate tool for respiratory simulations.