Development of numerical prediction method for indoor air quality distribution and inhalation exposure concentration(Fostering Joint International Research)

2018 Fiscal Year Final Research Report

• Project/Area Number: 15KK0211
• Research Category: Fund for the Promotion of Joint International Research (Fostering Joint International Research)
• Allocation Type: Multi-year Fund
• Research Field: Architectural environment/Equipment
• Research Institution: Kyushu University
• Principal Investigator: Ito Kazuhide 九州大学, 総合理工学研究院, 教授 (20329220)
• Research Collaborator: Tu Jiyuan RMIT University, School of Engineering, Professor ; Inthavong Kiao RMIT University, School of Engineering, Associate Professor
• Project Period (FY): 2016 – 2018
• Keywords: 数値気道モデル / ほ乳類 / 経気道暴露

Outline of Final Research Achievements

In vivo studies involving mammal surrogate models for toxicology studies have restrictions related to animal protection and ethics. Computer models, i.e., in silico models, have great potential to contribute towards essential understanding of heat and mass transfer phenomena in respiratory tracts in place of in vivo and in vitro studies. Here, we developed numerical upper airway models of a rat, a dog, a monkey, and two humans by using computed tomography data and then applied computational fluid dynamics analysis.
The present study identified fundamental qualities of flow and heat/mass transfer phenomena in airways for mammals and has enabled discussions about quantitative differences of heat and mass transfer efficiency between different animals/species. The computer simulation results outlined, and physical insight provided in this study can be applied to the discussions of factor of safety between animal testing, human response, and other inhalation toxicology problems.

Free Research Field

建築環境工学

Academic Significance and Societal Importance of the Research Achievements

鼻腔から気管支に至る気道内流れは，幾何形状が複雑で，層流から乱流への遷移を含む複雑流れ場であり，その解明と予測モデル構築は流体工学分野において学術的な意義を有する．またヒトを含むほ乳類の数値気道モデル開発に関する成果は，動物実験結果の人体への外挿精度の向上に加え，健康影響予測や薬剤開発といった公衆衛生学・医学分野への直接的な貢献も期待される．