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PMID: 41871949 Published · ppublish English

An experimental validation of computational fluid dynamics for airflow in a subject-specific normal human nasal model using a precise 3D-printed replica.

Inhalation toxicology ·Vol. 38 ·No. 4 ·2026-04-00

Cheng Y, Zhu Y, Yan S, Liao J, Ge Q, Fu X, Peng H

Abstract

Computational fluid dynamics (CFD) is widely used for studying nasal airflow but is rarely rigorously validated against experimental data. This study aimed to validate a subject-specific CFD model by comparing intranasal air pressure with measurements from a precise physical replica. 1:1 scale resin model of a single healthy human nasal cavity was fabricated using high-precision 3D printing (0.1 mm tolerance). Static pressures at 63 checkpoints within the nasal cavity were measured under three steady-state flow rates (180, 560, and 1100 mL s-1) corresponding to different respiratory intensities. These experimental data were compared with results from a standard k-ε CFD simulation. At low to moderate flow rates (180 and 560 mL s-1), pressures showed excellent consistency between experimental and CFD data. Quantitative analysis confirmed a strong correlation (Pearson's r = 0.98) and low error margins (RMSE < 6 Pa). However, at the high flow rate of 1100 mL s-1, a significant deviation (RMSE = 18.5 Pa) was observed in the posterior nasal cavity during expiration. This study establishes a methodological framework for validating subject-specific nasal airflow simulations using high-fidelity 3D-printed replicas. Our findings confirm the accuracy of the standard k-ε turbulence model for this specific anatomy at low to moderate physiological flow rates. However, deviations at high flow rates highlight the limitations of standard turbulence models and experimental uncertainties in complex regimes. This validated methodology offers a robust tool for future clinical assessments of nasal resistance.

Keywords
3D printing Three-dimensional reconstruction computational fluid dynamics experimental validation nasal airflow modeling
Article Info
Journal
Inhalation toxicology
Abbr.
Inhal Toxicol
ISSN
1091-7691
Published
2026-04-00
Language
English
Country/Region
England
NLM ID
8910739
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