Computational Modeling of Oxygen Transfer in Artificial Lungs

Abstract

Under physiological conditions, up to 97% of the oxygen in blood that is transported from lungs to tissue is bound to hemoglobin. To predict oxygen transfer in artificial lungs on a membrane fiber level with computational fluid dynamics (CFD), previous investigators have incorporated the hemoglobin-oxygen interaction into an effective diffusivity coefficient to modify the convection-diffusion equation. Based on our own simulations and experiments, these approaches tend to significantly overestimate the oxygen transfer. The present study introduces a novel approach to model the oxygen transfer in blood on a fiber level with CFD. Plasma and red blood cells were implemented as two phases and the reaction of hemoglobin and oxygen to oxyhemoglobin was included in the convection-diffusion equation in form of a source term. The model was implemented with the commercial software Ansys CFX 18.1. CFD simulations were compared with in vitro experiments on three micro oxygenators with a staggered fiber configuration under multiple blood flow conditions. To calibrate the model, a reaction rate R was introduced and experimental data was fitted to a blood flow of 50 mL/h. Our model approximated the oxygen transfer rates with a difference, relative to in vitro results, of -23.7 and +6.3% for blood flows of 20 and 90 mL/h, respectively. The effective diffusivity model, used by previous authors, was implemented for comparison and approximated oxygen transfer rates with a difference, relative to in vitro data, of +13.7, +68.8, and +121.0% for blood flows of 20, 50, and 90 mL/h, respectively. A well-established numerical mass transfer correlation approximated the gas transfer with a difference, referenced on the average in vitro data, of 31.8, 13.1, and 5.0% for blood flows of 20, 50, and 90 mL/h, respectively. Even though results are promising, a thorough validation of the model will require extensive CFD and in vitro studies of multiple fiber arrangements, fiber diameters, and therefore fiber bundle porosities in the future. This article should be understood as a first feasibility study to evaluate the potential of the novel oxygen transfer model.

Computation of Global and Local Mass Transfer in Hollow Fiber Membrane Modules

“…In Figure 8a, the blood side velocity magnitude distribution of the prototype oxygenator at a flow rate of 1300 mL/min can be seen. Five cross-sections perpendicular to the longitudinal axis of the module are presented at five different longitudinal positions (20,40,50,60, and 80 mm distance from the beginning of the fiber packing, Figure 4). The flow profiles show that, in coiled up fiber mats with parallel aligned fibers and a tangential and radial spacing of 200 µm, the fibers tend to stay in the slipstream of each other.…”

“…For instance, simulations of transmembrane CO 2 transport are not limited to two-dimensional flat sheet models, but are extended towards periodic fiber arrangements [3] or parts of packings [19]. Kaesler et al [20] used an Eulerian-Eulerian approach to model the O 2 transfer in an prototype oxygenator and treated blood as two phases, red blood cells and blood plasma, to account for the heterogenous distribution of hemoglobin. As the concentration polarization layer in blood is the main transport resistance [21], most simulations include only the blood side of the oxygenator.…”

“…Red dotted lines: line sources at the angular position φ = 0 • used for sampling of radial velocity profiles, shown in Section 3.1. Turquoise dot-and-dashed line: cross-sections at five different longitudinal positions(20, 40, 50, 60, and 80 mm) used for velocity magnitude and radial velocity fraction contour plots, shown in Section 3.1.…”

Toward a Long-Term Artificial Lung

“…The results showed good agreement between the theoretical and experimental values for PP fibers; thus, the correctness of the model was shown. 62,63 Of particular importance in the context of gas exchange is the diffusion path of the gas, which is significantly influenced by the thickness of the fiber membrane and the effective positions of the red blood cells (erythrocytes) in the blood. Therefore, it is essential to take the erythrocyte dynamics into account, transferred to the artificial flow channels of oxygenators.…”

Correction of the Hematological Homeostasis Parameters during Physical Loads by Using Energy Orientation Pharmacological Agents

“…Висновки. Отримані дані свідчать, що застосування препарату дає можливість стабілізувати гематологічний гомеостаз, особливо його еритроцитарну ланку, при інтенсивних фізичних тренуваннях, що покращує кисень транспортну функцію крові [19,23]. Можливо, одним з механізмів зростання витривалості спортсменів при аеробному механізмі енергозабезпечення м'язової діяльності є збіль-шення вмісту гемоглобіну в еритроцитах, яке обумовлене поліпшенням структурно-функціонального стану їх мембран під дією АТФ-лонг.…”