Matrix-Based Simulation for Patient-Specific Human Respiratory Air-Particle Flow Analysis

Conventional approach of simulating patient specific human respiratory air-particle flow involves tedious steps that include solid-fluid grid generations, air-particle solutions and results visualizations. A novel approach of combining the efficient Immersed Boundary method and Finite Difference Spl...

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Veröffentlicht in:AIMS 2013 : proceedings : first International Conference on Artificial Intelligence, Modelling & Simulation : 3-5 December 2013, Kota Kinabalu, Sabah, Malaysia S. 63 - 67
Hauptverfasser: Ngali, Mohd Zamani, Manshoor, Bukhari, Khalid, Amir, Kahar, Osman, Azis, Mohd Hazmil Syahidy Abdol
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.12.2013
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Zusammenfassung:Conventional approach of simulating patient specific human respiratory air-particle flow involves tedious steps that include solid-fluid grid generations, air-particle solutions and results visualizations. A novel approach of combining the efficient Immersed Boundary method and Finite Difference Splitting solver within a matrix-based open source programming platform achieved in this work has radically simplified the procedure especially in the pre-processing stage. Air and particle interactions are based on Eulerian-Lagrangian technique while convergence error of less than 1 x 10-6 in all validations. Quantitative comparisons were made based on standard five percent difference. Air flow rate of 30 litre/minute was used throughout the analyses representing normal inhalation condition while a number of 10,000 and 5,000 micro particles were modeled for simplified and image based airways respectively. Three patient-specific air-particle flow analysis showed that 42.35% of particles inhaled by female subject managed to reach the end of trachea while male subject with epiglottis blockage recorded a very minimum of 0.43%. Oversized male subject recorded merely none of complete particle inhalation. Apart from the attainment of more practical matrix-based algorithm, this work also suggests that such possible pattern analyses are crucial to facilitate medical practitioners in their diagnosis and decision making process of airway flow related diseases.
DOI:10.1109/AIMS.2013.18