A Numerical Study of Heat and Water Vapor Transfer in MDCT-Based Human Airway Models

Abstract

A three-dimensional (3D) thermo-fluid model is developed to study regional distributions of temperature and water vapor in three multi-detector row computed-tomography (MDCT)-basedhuman airwayswith minute ventilations of 6, 15 and 30 L/min. A one-dimensional (1D) model is also solved to provide necessary initial and boundary conditionsforthe 3D model. Both 3D and 1D predicted temperature distributions agree well with available in vivo measurement data. On inspiration, the 3D cold high-speed air stream is split at the bifurcation to form secondary flows, with its cold regions biased toward the inner wall. The cold air flowing along the wall is warmed up more rapidly than the air in the lumen center. The repeated splitting pattern of air streams caused by bifurcations acts as an effective mechanism for rapid heat and mass transfer in 3D. This provides a key difference from the 1D model, where heating relies largely on diffusion in the radial direction, thus significantly affecting gradient-dependent variables, such as energy flux and water loss rate. We then propose the correlations for respective heat and mass transfer in the airways of up to 6 generations: Nu=3.504(ReDaDt)0.277, R = 0.841 and Sh=3.652(ReDaDt)0.268, R = 0.825, where Nu is the Nusselt number, Sh is the Sherwood number, Re is the branch Reynolds number, Da is the airway equivalent diameter, and Dt is the tracheal equivalentdiameter.

A Numerical Study of Water Loss Rate Distributions in MDCT-Based Human Airway Models

“…The three subjects were the same subjects used in a previous computational study. 28 All subjects were normal non-smokers: subject A was a 32 year-old male with BMI of 21.6; subject B was a 20 year-old male with BMI of 22.33; subject C was a 32 year-old female with BMI of 26.63. Imaging was acquired with the subjects placed in the supine body posture and coached to breath-hold near total lung capacity.…”

“…One such assumption is axisymmetric air velocity, temperature, and humidity profiles in the airway radial direction, whereas previous studies have shown non-axisymmetric distributions especially near bifurcations. 28 Second, 1D and 2D geometric models lack many 3D geometric features, such as variation in cross-sectional area along an airway, curvature, and non-circular cross-sectional profiles. Moreover, most previous studies 6,8 have been limited to Weibel’s symmetric airway model, 26 and do not account for inter-subject variability.…”

“…28 The objectives of the present study are three-fold. First, both 1D and 3D models are applied to study the characteristics of regional water loss and water loss rate in response to our previously studied humidity and temperature distribution patterns in the human airways.…”

A 4DCT imaging-based breathing lung model with relative hysteresis

“…While image registration can provide information on regional ventilation and lung deformation, computational fluid dynamics (CFD) models can provide information regarding gas flow, particle transport, and heat transfer in the human lung (Lin et al (2007), Miyawaki et al (2012), Wu et al (2014)). For example, CFD-based models can predict the location of particle deposition on the airway wall to investigate the regional differences associated with specific particulate matter, e.g., aerosolized pharmaceutical drugs and pollutants, to the human lung.…”

Numerical assessment of airflow and inhaled particles attributes in obstructed pulmonary system

“…In this way, the airflow characteristics, along with the density and the deposition of the particles on the respiratory airways, are discerned. As of today, various CFD models have been employed to analyze the function of the lungs in terms of inspiration and expiration [10]- [12]. Also, several approaches, based on the data acquired by the CFD analysis, introduce calculations of the particles features [13]- [16].…”