Modelling and Validation of a Decentralized Breathing Gas Source.

Area of Science:

• Biomedical Engineering
• Respiratory Mechanics
• Computational Modeling

Background:

• Mechanical ventilation requires precise breathing gas delivery.
• Decentralized gas sources present unique simulation challenges.
• Digital twins offer a promising approach for modeling complex physiological systems.

Purpose of the Study:

• To develop and validate a digital twin for a decentralized breathing gas source.
• To assess the accuracy of the digital twin in simulating mechanical ventilation parameters.
• To evaluate the model's capability in predicting oxygen distribution.

Main Methods:

• Construction of a hardware setup analogous to a Simscape® model.
• Conducting experimental trials using volume-controlled ventilation.
• Comparing experimental data (pressure, oxygen concentration) with simulation results.

Main Results:

• High correlation coefficients achieved: 0.83 for FiO2 in the dosage chamber and 0.74 in the airway.
• The digital twin demonstrated accurate simulation of pressure and oxygen concentration.
• Validation confirmed the model's reliability for ex-vivo applications.

Conclusions:

• The developed digital twin effectively simulates mechanical ventilation processes.
• Accurate prediction of oxygen distribution is achievable with this model.
• This technology holds potential for improving ex-vivo research and applications in respiratory care.