Enhancing respiratory comfort with fan respirators: computational analysis of carbon dioxide reduction, temperature regulation, and humidity control

Respirators provide protection from inhalation exposure to dangerous substances, such as chemicals and infectious particles, including SARS-Covid-laden droplets and aerosols. However, they are prone to exposure to stale air as the masks creat a microclimate influenced by the exhaled air. As a result, exhaled air from the lungs accumulating in the mask produce a warm and humid environment that has a high concentration of carbon dioxide (CO2), unsuitable for re-inhalation. Fans are a favourable option for respirators to ventilate the mask and remove the stale air. This study utilized computational fluid dynamics simulation consisting of a hybrid Reynolds-averaged Navier-Stokes (RANS)-large eddy simulation (LES) turbulence method to compare the inhalation flow properties for different fan locations (bottom, top, and side) with regular respirator breathing. Three mask positions, top, side, and bottom, were evaluated under two breathing cycles (approximately 9.65s of breathing time). The results demonstrated that adding a fan respirator significantly decreased internal mask temperature, humidity, and CO2 concentration. The average CO2 concentration decreased by 87%, 67% and 73% for locations bottom, top and side respectively. Whilst the top and side fan locations enhanced the removal of the exhaled gas mixture, the bottom-fan respirator was more efficient in removing the nostril jet gas mixture and therefore provided the least barrier to respiratory function. The results provide valuable insights into the benefits of fan respirators for long-term use for reducing CO2 concentration, mask temperature, and humidity, improving wearer safety and comfort in hazardous environments, especially during the COVID-19 pandemic.Comment: 23 Pages, 7 Figure

NC01 - Nasal Cavity 01

A reconstructed nasal cavity from CT-scans. The nasal cavity is in .tin file format. The demographic data for the model is a healthy 25 year old, healthy non-smoking Asian male (170 cm height, 75 kg mass)<br><div><br></div><div>Journal publications using this model:</div><div><div><h4>NASAL SPRAY DRUG DELIVERY</h4><ol><li>Inthavong, K. Tian ZF, Tu JY, Yang W, Xue C (2008) Optimising nasal spray parameters for efficient drug delivery using computational fluid dynamics. Computers in Biology and Medicine 38(6):713-26.</li><li>Tian ZF, Inthavong, K. Tu JY (2007) Deposition of inhaled wood dust in the nasal cavity. Inhalation Toxicology 19(14):1155-65</li><li>Inthavong, K. Tian ZF, Li HF, Tu JY, Yang W, Xue CL (2006) A numerical study of spray particle deposition in a human nasal cavity. Aerosol Science Technology 40(11):1034-45</li></ol></div><div><p></p><h4>INHALATION TOXICOLOGY</h4><ol><li>King Se CM, Inthavong, K. Tu J. (2010) Inhalability of micron particles through the nose and mouth. Inhalation Toxicology 22(4):287-300.</li><li>Inthavong, K. Tu JY, Ahmadi G. (2009) Computational modelling of gas-particle flows with different particle morphology in the human nasal cavity Journal of Computational Multiphase Flows 1(1):57-82</li><li>Wang SM, Inthavong, K. Wen J, Tu JY, Xue CL (2009) Comparison of micron- and nanoparticle deposition patterns in a realistic human nasal cavity. Respiratory Physiology Neurobiology 166(3):142-151</li><li>Inthavong, K. Wen J, Tian ZF, Tu JY. (2008) Numerical study of fibre deposition in a human nasal cavity. Journal of Aerosol Science 39(3):253-65.</li></ol></div><div><p></p><h4>RESPIRATORY PHYSIOLOGY</h4><ol><li>Inthavong, K. Tu J, Ye Y, Ding S, Subic A, Thien F. (2010) Effects of airway obstruction induced by asthma attack on particle deposition. Journal of Aerosol Science 41(6):587-601.</li><li>Inthavong, K. Choi L-T, Tu J, Ding S, Thien F. (2010) Micron particle deposition in a tracheobronchial airway model under different breathing conditions. Medical Engineering ;amps Physics 32(10):1198-212.</li><li>Se, C., Inthavong, K. and Tu, J.Y. (2010). Unsteady particle deposition in a human nasal cavity during inhalation. Journal of Computational Multiphase Flows 2:207-218</li><li>Inthavong, K. Wen J, Tu JY, Tian ZF, (2009) From CT scans to CFD modelling fluid and heat transfer in a realistic human nasal cavity. Engineering Applications of Computational Fluid Mechanics 3(3):321-35.</li><li>Wen J, Inthavong, K. Tu JY, Wang S (2008) Numerical simulations for detailed airflow dynamics in a human nasal cavity. Respiratory Physiology Neurobiology 161:125-35</li></ol></div></div

Computational Fluid and Particle Dynamics in the Human Respiratory System

Traditional research methodologies in the human respiratory system have always been challenging due to their invasive nature. Recent advances in medical imaging and computational fluid dynamics (CFD) have accelerated this research. This book compiles and details recent advances in the modelling of the respiratory system for researchers, engineers, scientists, and health practitioners. It breaks down the complexities of this field and provides both students and scientists with an introduction and starting point to the physiology of the respiratory system, fluid dynamics and advanced CFD modeling tools. In addition to a brief introduction to the physics of the respiratory system and an overview of computational methods, the book contains best-practice guidelines for establishing high-quality computational models and simulations. Inspiration for new simulations can be gained through innovative case studies as well as hands-on practice using pre-made computational code. Last but not least, students and researchers are presented the latest biomedical research activities, and the computational visualizations will enhance their understanding of physiological functions of the respiratory system

Computational Fluid and Particle Dynamics in the Human Respiratory System

XVIII, 374 p.online resource

Computational hemodynamics: theory, modelling and applications

This book discusses geometric and mathematical models that can be used to study fluid and structural mechanics in the cardiovascular system.  Where traditional research methodologies in the human cardiovascular system are challenging due to its invasive nature, several recent advances in medical imaging and computational fluid and solid mechanics modelling now provide new and exciting research opportunities. This emerging field of study is multi-disciplinary, involving numerical methods, computational science, fluid and structural mechanics, and biomedical engineering. Certainly any new student or researcher in this field may feel overwhelmed by the wide range of disciplines that need to be understood. This unique book is one of the first to bring together knowledge from multiple disciplines, providing a starting point to each of the individual disciplines involved, attempting to ease the steep learning curve. This book presents elementary knowledge on the physiology of the cardiovascular system; basic knowledge and techniques on reconstructing geometric models from medical imaging; mathematics that describe fluid and structural mechanics, and corresponding numerical/computational methods to solve its equations and problems. Many practical examples and case studies are presented to reinforce best practice guidelines for setting high quality computational models and simulations. These examples contain a large number of images for visualization, to explain cardiovascular physiological functions and disease. The reader is then exposed to some of the latest research activities through a summary of breakthrough research models, findings, and techniques. The book’s approach is aimed at students and researchers entering this field from engineering, applied mathematics, biotechnology or medicine, wishing to engage in this emerging and exciting field of computational hemodynamics modelling