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Updated: Dec 1, 2025
15:04
Modeling and Simulations of Olfactory Drug Delivery with Passive and Active Controls of Nasally Inhaled Pharmaceutical Aerosols
Published on: May 20, 2016
11.2K
Computational modelling of nasal respiratory flow
H Calmet1, K Inthavong2, H Owen1
1Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC-CNS), Barcelona, Spain.
Computer Methods in Biomechanics and Biomedical Engineering
|November 11, 2020
Summary
Simplified computational fluid dynamics (CFD) models can achieve adequate accuracy for respiratory flow analysis in large clinical trials. Focusing on mean flow and starting from the second cycle ensures reliable, rapid results for clinical applications.
Area of Science:
- Fluid dynamics
- Biomedical engineering
- Computational modeling
Background:
- Computational fluid dynamics (CFD) shows promise for clinical trials.
- Large-scale clinical applications require rapid, statistically relevant findings from multiple models.
- Current methods often prioritize high resolution over speed, hindering clinical utility.
Purpose of the Study:
- To determine minimum modeling criteria for accurate respiratory flow simulations in large-scale clinical applications.
- To evaluate the trade-offs between model resolution, computational time, and accuracy.
- To provide guidance for simplified modeling approaches in clinical and engineering contexts.
Main Methods:
- A highly-resolved Large Eddy Simulation (LES) was used as a reference.
- Lower resolution models with larger time steps and no turbulence modeling were compared.
- Quantified differences in pressure loss, flow resistance, unsteadiness, turbulence intensity, and hysteresis.
Main Results:
- Sufficient accuracy is achievable with lower resolution models when considering mean flow.
- Results should be analyzed from at least the second respiration cycle to avoid initial transient effects.
- The exhalation phase was identified as exhibiting significant turbulence.
Conclusions:
- Simplified CFD models can be adequate for clinical applications requiring rapid turnaround times.
- Focusing on mean flow characteristics and appropriate cycle selection is key for accuracy.
- These findings support the use of efficient modeling for large-scale respiratory flow studies.
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