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Abstract

The study proposes a fluid simulation and analysis of oxygenated membrane fabrics for Extracorporeal Membrane Oxygenation (ECMO) by applying knitting technology from the field of textile technology. This is aimed at addressing the lack of research on the impact of the oxygenator flow field before and after knitting of oxygenated membrane fabrics. For this investigation, a commercial oxygenator was selected, featuring a polymethylpentene (PMP) hollow fiber membrane as the oxygenator membrane material, along with a knitted yarn made of a 50D/24F polyester low-elasticity filament. The knitting organization utilized warp knitting technology with a pillar stitch/weft lining structure. Through the integration of theoretical geometric modeling and finite element analysis method of flow-solid coupling, the study examined the influence of knitting on the oxygenator before and after the knitting of the PMP membrane material. Extracorporeal membrane oxygenation (ECMO) technology represents a sophisticated equipment within the domain of in vitro medical treatment. The research findings indicated that the total pressure drop in the oxygenator’s flow field was 472.6 Pa for the unknitted PMP membrane and 269.4 Pa for the knitted oxygenator fabric, signifying a near 40% reduction in pressure with the knitted PMP membrane. This reduction in pressure also led to a 50% decrease in turbulence within the flow field. The maximum displacement of the knitted PMP membrane within the flow field was measured at 0.16 mm, whereas the unknitted membrane displayed a maximum displacement of 0.37 mm. The knitted PMP membrane significantly enhanced the pressure and velocity uniformity of the oxygenator’s flow field, resulting in decreased stress-strain effects and improved service life of the oxygenator. In conclusion, the study illustrates that knitting the PMP membrane can substantially improve the flow field distribution of ECMO oxygenators, leading to enhanced oxygenation efficiency and membrane durability.

Keywords

Extracorporeal membrane oxygenation oxygenator polymethylpentene hollow fiber membrane knitting technology fluid-solid coupling simulation analysis

Introduction

Extracorporeal membrane oxygenation (ECMO), also referred to as the “artificial membrane lung,” is a method of extracorporeal life support.^1,2 The technology of ECMO has its origins in the pioneering developments of cardiac surgery in 1953. It works by providing an extracorporeal blood circulation pathway for patients in critical condition with temporary cardiopulmonary dysfunction, facilitating the completion of cardiac surgical procedures.^3,4 Over the years, ECMO technology has seen expanded applications, including patients undergoing cardiopulmonary surgery, lung transplantation, neonatal cases of cardiopulmonary failure,^5,6 as well as the management of acute respiratory distress syndrome, such as in cases associated with novel coronavirus infections.

ECMO devices consist of several key components, including the oxygenator, centrifugal pump, control system, and support system.^7,8 The oxygenator is the key technology of the ECMO device, comprising blood and gas inlet and outlet components, along with oxygenated membrane fabric.^9,10 There are primarily two types of oxygenators: cylindrical and flat plate-shaped, as illustrated.^11,12 Oxyfilm fabrics are created by knitting individual polymethylpentene (PMP) membranes together, as illustrated in Figure 1(a).^13–15 Following the completion of the knitting process, Figure 1(d) elucidates the operational principle of the oxygenator membrane: the blood flow field and the oxygen flow field are arranged vertically within the oxygenator.^16–18 Blood passes through the surface of the oxygenation membrane, while oxygen travels through the inner hole of the membrane. This enables oxygen and carbon dioxide in the blood to undergo gas exchange by passing through the dense layer of the PMP membrane. Consequently, this process leads to the successful oxygenation of blood.

Figure 1.

Oxygenator operating principle. (a) Oxygenated membrane fabric; (b) flat plate oxygenator; (c) column oxygenator; (d) oxygenation principle of oxyfilm fabrics.

Experimental research methods enable the measurement of the oxygenator’s overall flow field outcomes,^19,20 but the test platform is bulky and does not facilitate monitoring the impact of the woven tissue of the oxygenated membrane fabric on the blood flow field.^18,21 In contrast, Computational Fluid Dynamics (CFD) simulations have emerged as an effective approach for optimizing the structure, evaluating flow fields, and understanding mass and heat transfer within oxygenators.²² For instance, Juntao Zhang²³ developed a porous medium model and a fluid simulation calculation approach to investigate pressure distribution and fluid dynamics within the oxygenator. Similarly, Buetehorn S²⁴ utilized a porous media model to conduct flow field simulation calculations. The study compared how the arrangement, inlet velocity, and blood concentration of unknitted PMP membranes influenced the flow field results. Furthermore, Yang X²⁵ utilized simulation calculations to analyze the cross-sectional design of microporous structured PMP membranes and determined that tooth-structured PMP membranes demonstrate superior flow field transport capability. Moreover, Liwei Zhuang²⁶ and Liu X²⁷ employed a porous medium model and flow field simulation methods to optimize the spatial dimensions and arrangement of monolithic oxygenation membranes. While previous studies by researchers have focused on simulating and calculating the performance of PMP membranes as porous medium models to optimize the oxygenator’s flow field space, they have overlooked the impact of the specific knitting organization and method of the PMP membrane. As a result, the existing simplification fails to capture the true flow dynamics among the individual hollow fiber membranes within the oxygenator.

This study aims to address the gaps in the key technology of PMP membrane knitting for oxygenators by proposing a fluid simulation analysis study of the ECMO membrane before and after knitting, based on knitting technology. The research involves exploring the knitting method of PMP membrane fabric, comparing the flow field distribution law of the oxygenator before and after knitting, and revealing the flow field changes that occur before and after the knitting process of the oxygenator membrane. These findings provide essential insights for enhancing the efficiency and lifespan of the oxygenator. The study encompasses an examination of the working principle of the oxygenator, a discussion of the preparation method of PMP membrane fabric, an exploration of the modeling method of PMP membrane before and after knitting, and an analysis of the flow field law before and after knitting through simulation calculations. The overarching goal of this research is to offer valuable insights for improving the efficiency and service life of oxygenators.

Materials and methods

Preparation of PMP hollow fiber

Commercial oxygenators were used to select representative products with varying parameters, as summarized in Table 1 (shown in Figure 2). The oxygenation membranes predominantly consist of PP and PMP hollow fiber materials.^28,29 Specifically, the PMP hollow fiber membrane distinguishes itself by presenting a multi-microporous structure that enhances blood gas exchange efficiency while maintaining low impedance and initial flow rates. This material is currently considered the superior medium for oxygenator performance.³⁰

Table 1.

Product specification comparison.

Manufacturer	Products	Type	Membrane material	Membrane area/m²	Perfusion volume/ml	Lifetime
Maquet (Germany)	HLS	Flat-shaped	PMP	1.8	273	30 days
Maquet (Germany)	PLS	Flat-shaped	PMP	1.8	250	14 days
Medtronic (America)	Affinity Fusion	Cylindrical type	PP	2.5	260	/
Medtronic (America)	Nautilus ECMO	Cylindrical type	PMP	1.8	226	0.25 days
Xenios (Germany)	Medos hilite LT	Cylindrical type	PMP	1.9	320	10-14 days
Sorin (Italy)	EOS ECMO	Cylindrical type	PMP	1.2	150	5 days
Terumo (Japan)	CAPIOXÒ RX	Cylindrical type	PP	2.5	250	0.25 days
Kewei Medical(China)	Children ECMO	Cylindrical type	PMP	0.8	150	/
Kewei Medical(China)	Adult version	Cylindrical type	PMP	1.2/2.0	2500/4000	/
MicroPort(China)	Lifemotion	Cylindrical type	PMP	2.0	300	7 days

Figure 2.

Medos Hilite LT-type oxygenator. (a) Medos Hilite LT-type oxygenator; (b) three-dimensional modeling diagram; (c) operating schematic.

The oxygenator is comprised of an outer chamber, middle chamber, and inner chamber, as well as fluid inlet and outlet components. The fluid working process within the oxygenator is illustrated in Figure 2(c). Initially, blood is transported from the inlet tube to the intermediate transformer area in the middle chamber, where heat exchange occurs through direct contact. Subsequently, oxygen traverses from the top to the bottom of the PMP membrane via the inner perforations. Finally, the blood flows from the top to the bottom of the PMP membrane surface, facilitating the passage of carbon dioxide out of the blood and the influx of oxygen into the blood. This process is achieved through the microporous structure on the membrane surface, as depicted in Figure 3(d), enabling the removal of carbon dioxide from the blood and the enrichment of oxygen levels, thus contributing to the improvement of the blood’s oxygen concentration.

Figure 3.

Analysis of the knitted organization of the oxygenated membrane. (a) Transverse density measurement of PMP membrane fabric; (b) longitudinal density measurement of PMP membrane fabric; (c) microscopic diagram of oxygenated membrane fabric; (d) scanning electron microscope diagram of PMP membrane; (e) Tissue simulation of PMP membrane fabric; (f) diagram of the weaving process of PMP membrane.

Currently, the main methods for preparing PMP hollow fiber membranes are melt stretching and thermally induced phase separation (TIPS), which is also referred to as the TIPS method .^31,32 In this study, a PMP hollow fiber membrane was prepared in the laboratory using the TIPS method, and Figure 3(d) displays its cross-sectional shape, while Table 2 provides information on its material properties.

Table 2.

Performance parameters of PMP films prepared by TIPS method.

Research and development firm	3M	Tsinghua university	Nanjing university of technology	Laboratory preparation
Outer surface diameter/um	380 ± 30	580 ± 30	400 ± 30	380 ± 30
Bore diameter/um	200 ± 50	350 ± 50	200 ± 30	180 ± 30
Dense layer thickness/um	0.4	/	/	/
Porosity/%	61%	60%–70%	≥55	60%
Tensile strength/cN	>60	110–115	≥70	≥60
Nitrogen flux/ml/cm2min-*bar	0.2–2	12.75	0.2-10	0.2-10

Knitting organization analysis of oxyfilm fabrics

The research focused on analyzing the row pattern and weaving method of the oxygen membrane in Kewei Medical’s large oxygenator. The oxygen membrane fabric was dismantled for closer examination, revealing key characteristics. It was determined that the woven oxygen membrane fabric had a width of 18 cm, with a transverse density of 0.95 longitudinal rows/cm and a longitudinal density of 18 transverse columns/cm, as illustrated in Figure 3(a) and (b). Additionally, the knitting yarn type used was identified as a medical-grade polyester low elastic yarn material with a material specification of 50D/24F.

A thorough examination of the knitting method of the oxygenated membrane was conducted utilizing an electron microscope and integrating iTDS1.0, the Internet textile CAD system of Jiangnan University. This analysis confirmed that the knitting organization of the PMP hollow fiber membrane followed a pillar stitch/weft lining organization, illustrated in Figure 3(c) and (e). The axial warp knitting machine was selected to complete the knitting experiment as shown in Figure 3(f). During the knitting process, it was found that the PMP film has the characteristics of low strength and high elongation, and the tension control during the knitting process is particularly important. Through knitting experiments, it was found that the positive yarn feeding method with constant tension control is a more reliable knitting method.

Modeling approach for oxygenator simulation analysis

Geometric modeling approach for oxygenators

Based on Kewei Medica’s adult oxygenator by mapping its external dimensions as shown in Figure 4(a), the oxygenated membrane fabric was encapsulated as shown in Figure 4(b).By following laws of geometric similarity, kinematic similarity, dynamic similarity, and similarity of initial and boundary conditions, the modeling and simulation calculation of the oxygenator are completed. Engaging in full-scale 3D geometry modeling of the physical object according to the figure size involves a significant workload and simulation analysis difficulties. According to the similarity theory of fluids, the modeling membrane of the oxygenator follows the laws of geometric similarity, kinematic similarity, dynamic similarity, and similarity of initial and boundary conditions.

(1) Geometric Similarity: The model’s geometry closely resembles the actual working condition, with proportional line segments and equal corresponding angles, as shown in equation (1).

C_{L} = \frac{L_{N}}{L_{M}}

(1)

Figure 4.

Oxygenator dimensioning and simulation analysis platform construction. (a) Oxygenator dimensions; (b) oxygenated membrane encapsulation arrangement method; (c) fluid-solid coupling interface; (d) simulation platform construction.

In the above equation, L_N is the physical parameter, L_M is the model parameter, and C_L is the length scale between the physical and model.

(2) Similarity of motion: The velocities (or accelerations) at the points corresponding to the two flow fields are in the same direction and proportional in magnitude, as shown in equation (2).

C_{u} = \frac{U_{p}}{U_{m}}

(2)

In the above equation, C_u denotes the velocity scale, and U_p and U_m denote the velocities of the real flow field and the model, respectively.

(3) Dynamic similarity: The real and modeled fluids are subjected to loads in the same direction and proportional magnitude at each point, as shown in equation (3).

C_{F} = \frac{T_{p}}{T_{m}} = \frac{P_{p}}{P_{m}}

(3)

In the above equation, C_F is the force scale, T is the viscous force, and p is the pressure.

(4) Fluid movement of the initial conditions and boundary conditions are similar: both are necessary to ensure that the two flows are similar. Initial conditions are similar, including the fluid domain import and export speed, pressure and other conditions are similar; boundary conditions are similar to refer to the same boundary characteristics of the two fluids.

The results of the values of the similar eigenquantities

Prior to the simulation calculations, the values of the eigenvectors in the fluid domain are calculated based on the similarity theory in the previous section.

(1) Geometric similarity: The setting of appearance size, material property similarity and feature structure of fluid and solid domains should follow the principle of geometric similarity, and the results are shown in Table 3.

(2) Similarity of motion: the motion characteristics of the fluid and solid domains of the oxygenator have similar laws to those of the physical object. Kewei Medica’s adult oxygenator has a blood flow rate of 1.5 to 7 L/min and an inlet diameter of 20 mm.

(3) Dynamic similarity: The state of blood flow is described by the Reynolds number. The calculation of Reynolds number is based on the density, viscosity, velocity and characteristic length of the fluid. The density of blood is 1059 kg/m³, the Reynolds number is calculated according to the Reynolds number formula as shown in equation (4).

Re = \frac{ρ ν L}{μ}

(4)

where ρ, μ is the fluid density and dynamic viscosity coefficient, ν, L is the characteristic velocity and characteristic length of the flow field. The range value of blood viscosity of healthy adults is 3∼5 mPa*s, which is taken as 3.5; the characteristic length of the flow field is taken as 0.1 m according to the physical dimensions, which is accounted for to give Re as 9.6, and the velocity of the oxygenator is 0.07∼0.37 m/s.

Table 3.

Results of similar eigenvalues taking values in the fluid domain.

Solution type	Fluid domain	Solid-body field
Solution type	Fluid domain	Oxygenated membrane	Bundled yarn
Scale size	1000	1000	1000
Material	Blood	PMP	Low-stretch polyester yarn
Density kg/m³	1059	850	1.38*10⁶
Viscosity kg/(m*s)	0.0035	/	/
Elastic modulus MPa	/	110	75

(4) The initial and boundary conditions for the blood flow field are determined by the Kewei Medica oxygenator. At the inlet, a velocity inlet boundary condition is applied, with an inlet flow rate ranging from 1.5 to 7 L/min. The outlet pressure is set to 0 Pa, which equals the default atmospheric pressure of 101,325 Pa. In addition, no-slip boundaries are set for all wall surfaces at the edge of the blood flow field according to the model specified by the Kewei Medica oxygenator.

Equation solving methods for simulation calculations

In the working process of the oxygenator, the blood flow field generates pressure on the surface of the oxygenator membrane, leading to a displacement change in the membrane, which, in turn, affects the blood flow field. This action process of blood and the oxygenator membrane fabric falls under the category of flow-solid coupling, as depicted in Figure 4(c) and (d).

Theoretical equations solved by fluid domain simulation

The Fluent software analysis solves the laws of fluid motion at each spatial location through the conservation of mass and momentum, as depicted in equation (5).^33,34 In the case of steady-state incompressible blood flow, the density ρ remains constant over time.

\frac{\partial (ρ v_{x})}{\partial x} + \frac{\partial (ρ v_{y})}{\partial y} + \frac{\partial (ρ v_{z})}{\partial z} = 0

(5)

where ν_x, ν_y and ν_z are velocity vectors in the x, y, and z directions, and ρ is the density.

The conservation of momentum of blood can be described by the Navier-Stokes (N-S) equation as shown in equation (6).

\sum \vec{F} = \frac{d (m \vec{v})}{d t} = \frac{\partial}{\partial t} \int_{c ν} ρ \vec{v} d + \int_{c s} ρ \vec{v} \vec{v} \cdot d \vec{A}

(6)

where

\vec{F}

is the rate of increase of the momentum of the fluid system,

\vec{V}

is the velocity of the fluid, and ρ is the density of the fluid.

Simulation of solid domains to solve theoretical equations

The transient analysis of the solid is to study the results of the change in displacement of the oxygenated membrane after it is subjected to a time-dependent pressure load from the blood fluid, and the solution process is shown in Figure 4(d). The transient calculation is done by considering the relationship between the inertia force of the system, the damping force, the spring force and the external load of the system together as shown in equation (7).

[F (t)] = [M] [\ddot{x}] + [C] [\dot{x}] + [K] [x]

(7)

where [F] is the external load matrix, [M] is the mass matrix, [C] is the damping matrix, [K] is the stiffness matrix,

[\ddot{x}]

is the solid structure acceleration,

[\dot{x}]

is the solid structure velocity, and [x] is the solid structure displacement.

Results and discussion

Calculation of simulation results

The calculation model of Kewei Medica’s product simplifies the temperature flow field and gas flow field, incorporating blood and PMP membrane components. To complete the calculation, a geometric similarity ratio of 1000 was chosen based on the results provided in Table 3. Additionally, modeling of the PMP membrane both before and after braiding was conducted, with the outcomes illustrated in Figure 5.

Figure 5.

Modeling and meshing of oxygenator simulation. (a) Fluid domain model; (b) knitted oxygenated membrane model; (c) mesh delineation of unknitted oxygenated membrane flow field; (d) mesh delineation of knitted oxygenated membrane flow field.

The mesh quality Ave>0.80 of the oxygenator and the local mesh quality of the simulation model of the oxygenator before and after knitting are shown in Figure 5(c) and (d). The selection of meshing method, number of meshes, mesh quality, and mesh size in this study is shown in Table 4.

Table 4.

Oxygenator mesh before and after knitting.

Solution type	Before knitting		After knitting
Solution type	Fluid domain	Solid-body field	Fluid domain	Solid-body field
Mesh method	Tetrahedral mesh	Tetrahedral mesh	Tetrahedral mesh	Tetrahedral mesh
Element number/million	1.8	0.29	2.83	1.03
Node number/million	0.2	0.065	0.51	0.22
Mesh quality	0.84	0.84	0.84	0.83
Grid size/mm	1	0.5	0.5	0.1
Local encryption method	/	/	Inflation	Inflation

The blood fluid simulation utilizes the RNG k-ε model with a blood density of 1059 kg/m³ and a viscosity of 0.0035 kg/(m*s). The blood fluid velocity is prescribed as 4 L/min, and the outlet pressure is maintained at 0 Pa. To ensure accurate pressure-velocity coupling calculations, the Couple algorithm is employed. The time step size is defined as 0.01 s, and the simulation runs for 100-time steps until all velocity and turbulence residuals are below 10-5, indicating convergence. Table 3 details the density, Young’s modulus, and Poisson’s ratio of the PMP membrane material. The simulation concludes at 1 s, with a step size of 0.01 s.

Simulation results and analysis of flow field

Analysis of simulation results on pressure within the flow field

The simulations in Figures 6 and 7 show the flow field pressure results before and after knitting the oxygenated membrane. From the results shown in Figure 6(a) and 7(a), it is evident that the flow field pressure of the unknitted PMP membrane varies from −70.6 Pa to 402 Pa, resulting in a total pressure drop of 472.6 Pa. Conversely, the flow field pressure of the knitted oxygenated membrane fabric ranges from −10.4 Pa to 259 Pa, with a total pressure drop of 269.4 Pa. It is noteworthy that the maximum fluid pressure values before and after knitting are located at the blood inlet position, which can be attributed to the non-axisymmetric design of the blood inlet position, oxygenated membrane position, and outlet position.

Figure 6.

Pressure clouds of the flow field of the unknitted PMP membrane. (a) oxygenator pressure cloud; (b) X-Y cross section pressure cloud; (c) Tangential pressure cloud at the inlet cross section; (d) tangential pressure cloud at the intermediate cross section; (e) tangential pressure cloud at the outlet cross section.

Figure 7.

Pressure clouds of the flow field after knitting the PMP membrane. (a) Pressure cloud of the oxygenator; (b) pressure cloud of the X-Y section; (c) tangential pressure cloud of the inlet section; (d) tangential pressure cloud of the intermediate section; (e) Tangential pressure cloud of the outlet section.

The pressure values of the oxygenator experienced significant variations mainly in the X-Y direction as illustrated in Figure 6(b) and 7(b). Specifically, the pressure values within the flow field ranged from −45 Pa to 384 Pa and −33.5 Pa to 256 Pa. For the tangential direction, the tangential pressures were measured at 171 Pa to 396 Pa at the inlet position, 246 Pa to 247 Pa at the intermediate planes, and 0 Pa to 245 Pa at the outlet position, as depicted in Figure 6(c)–(e). At the inlet position, the tangential pressures ranged from 171 Pa to 396 Pa, while the intermediate planes experienced pressures of 246 Pa to 247 Pa, and the outlet position recorded pressures ranging from 0 Pa to 245 Pa. In Figure 7(c)-(e), the results further reveal that the tangential pressures at the knitted inlet position varied from 128 Pa to 249 Pa, at the intermediate plane from 153 Pa to 158 Pa, and at the outlet position from 7 Pa to 158 Pa.

Upon comparing the results presented in Figures 6 and 7, it is evident that the tangential flow field distribution of the oxygenator is more uniform following the installation of the knitted PMP membrane. The knitted oxygenator membrane not only diminishes the pressure fluctuation range at the fluid inlet position but also mitigates turbulent phenomena within the flow field. Additionally, at the middle position, the pressure distribution of the knitted flow field exhibits greater uniformity in the Y-Z section, with the maximum and average pressures in the oxygenator’s flow field after incorporating the knitted PMP membrane displaying a decreasing trend. Notably, the pressure in the knitted flow field registers a reduction of approximately 40% compared to the unknitted flow field. Furthermore, the flow field post-knitting demonstrates no spatial slippage, thereby effectively enhancing the uniformity of the oxygenator’s flow field.

Simulation results and analysis of velocity in the flow field

The simulation results of the velocity of the oxygenator flow field before and after the knitting of the PMP membrane are shown in Figures 8 and 9.The velocity of the blood fluid before the knitting of the PMP membrane is 0∼0.68 m/s, and the velocity of the blood fluid after the knitting is 0∼0.54 m/s. The difference in velocity between the two flow fields is due to the pressure distribution law in Figures 6∼7.

Figure 8.

Velocity clouds of the flow field with unknitted PMP membrane. (a) Velocity streamlines of the oxygenator; (b) velocity clouds in the X-Y section; (c) tangential velocity clouds in the inlet section; (d) tangential velocity clouds in the intermediate section; (e) tangential velocity clouds in the outlet section.

Figure 9.

Velocity clouds of the flow field of the knitted PMP membrane. (a) velocity streamlines of the oxygenator; (b) velocity cloud of the X-Y section; (c) tangential velocity cloud of the inlet section; (d) tangential velocity cloud of the intermediate section; and (e) tangential velocity of the outlet section.

By extracting the velocity clouds in the X-Y plane of the oxygenator before and after knitting, the tangential direction of the inlet position, the middle position and the outlet position, the results are shown in Figures 8 and 9(b) ∼ (e). The sudden change of the oxygenator fluid velocity occurs mainly in the lower part of the X-Y plane. The unknitted PMP membrane is susceptible to more pronounced turbulence phenomenon under the action of blood fluid, and the appearance of turbulence phenomenon tends to lead to the damage of blood cells in the blood, and such phenomenon should be avoided. From the flow field diagram of the oxygenated membrane in the X-Y plane after knitting, it can be seen that its turbulence phenomenon is reduced by more than 50%. By comparing the results of the cloud diagrams of the oxygenator in the Y-Z cross section before and after the knitting of the oxygenated membrane, it is found that the velocity distribution of the flow field in the knitted oxygenator is more uniform, which is consistent with the pattern of the pressure distribution results.

Analysis of results from solid domain simulation

The solid domain simulation analysis shows the stress-strain results of the PMP membrane in the blood flow field before and after knitting, and the results are shown in Figure 10. Under the action of the flow field, the maximum value of the pressure on the surface of the unknitted PMP membrane is 0.128 MPa, and the maximum displacement that occurred is 0.37 mm. After knitting, the maximum value of the pressure on the surface of the knitted PMP membrane under the action of the flow field is 0.66 MPa, and the maximum displacement that occurred is 0.16 mm. By comparing the two sets of results, it is found that the displacement of the knitted PMP membrane is reduced by two times compared to that of the unknitted membrane. This indicates that the knitting method significantly improves the spatial arrangement uniformity of the PMP membrane under the action of the blood flow field.

Figure 10.

Stress-strain maps of the oxygenated membrane before and after knitting. (a) Stress cloud of the unknitted oxygenated membrane; (b) strain cloud of the unknitted oxygenated membrane; (c) stress cloud of the knitted oxygenated membrane; (d) strain cloud of the knitted oxygenated membrane.

Under the time-domain condition, stress-strain results for PMP membranes before and after being knitted are analyzed under the pressure of the flow field. The Transient Structural software is utilized to solve the nodes’ data during 100 flow-solid coupling calculations within 1 s, leading to the plotting of stress-strain results of the PMP membrane as depicted in Figure 11. The findings illustrate that the unknitted PMP membrane experiences substantial displacement at the onset of the flow field’s action phase. Subsequently, as the number of action cycles increases, the displacement of the PMP membrane exhibits a pattern of initial reduction followed by augmentation. Furthermore, both the trend and magnitude of stress-strain in the knitted PMP membrane are notably lower than those in the unknitted counterpart.

Figure 11.

Time-domain stress-strain curves of oxygenated films before and after knitting.

In summary, the knitted PMP membrane can withstand larger flow field loads; simultaneously, the spatial position between the oxygenated membranes undergoes less change and has a more uniform blood flow field. The maximum displacement of the unknitted PMP membrane under the flow field was 0.37 mm (the outer diameter of the PMP membrane was 0.38 mm), and the adjacent PMP membranes would overlap. This phenomenon may be the main reason for the significant pressure and velocity changes in the flow field of the unknitted PMP membrane. Combined with the force law of the knitted PMP membrane, it was found that the pressure and velocity of the blood fluid in the oxygenator had variable characteristics, and the oxygenated membrane and the knitted yarn would be subjected to the pressure of the complex and variable flow field. The oxygenated membrane might have fatigue failure. This may be the main reason why the oxygenation efficiency of the oxygenator decreases and coagulation failure tends to occur in clinical use.

Conclusion

The knitting organization of the PMP membrane was determined as pillar stitch/weft lining organization based on the working principle of the oxygenator through experimental and simulation methods. This study aims to reveal the results of the effect on the flow field of the oxygenator prior to and post knitting of the oxygenated membrane. Through the use of theoretical modeling and a flow-solid coupling method, simulations were conducted to analyze the flow field law of the PMP membrane and the stress-strain results before and after knitting. The main conclusions drawn from this investigation are as follows:

(a) The knitting technique significantly improved the fluid flow characteristics of the oxygenator: The overall flow field pressure uniformity of the knitted PMP Membrane Oxygenator was significantly improved. Comparison of flow field pressures before and after knitting showed that the knitted fluid pressure was reduced by approximately 40% compared to the unknitted, and was more spatially uniform with less slippage. The knitted oxygenated membrane reduced the turbulence phenomenon and lowered the maximum velocity of the blood flow field from 0.68 m/s from unknitted to 0.54 m/s after knitting, a result that helped reduce blood cell damage.

(b) Improved structural stability and durability: The knitting method significantly improves the spatial arrangement uniformity and stability of the membranes by increasing the maximum value of pressure applied to the surface of the knitted PMP membranes. The maximum displacement is reduced by a factor of two, from 0.37 mm to 0.16 mm compared to the unknitted membranes, indicating enhanced structural stability. Knitted PMP membranes exhibit less variation in stress-strain response and a more stable trend, which suggests that they can better maintain structural integrity under flow field pressure, reducing the risk of fatigue failure.

(c) Potential improvement of oxygenation efficiency and service life: Simulation analysis shows that the knitted oxygenation membrane can effectively reduce turbulence and pressure fluctuation under the action of flow field, which is of great significance for improving oxygenation efficiency. The reduction of turbulence phenomenon can improve the exchange efficiency of blood and oxygen and reduce the mechanical damage of blood cells. The advantages of knitting technology in improving the structural stability of the oxygenation membrane can effectively extend the service life of the oxygenator and reduce clinical failures due to fatigue and structural damage.

(d) Guidance for design and optimization: The results of the study show that the knitting technique has a significant reference value for the design optimization of oxygenators. The hydrodynamic properties of the oxygenator membrane can be further optimized by the knitting method to improve the overall performance of the device. The methodology and results of this study can provide new ideas and technical support for future ECMO device development, especially in improving oxygenation efficiency and device durability.

In summary, the PMP hollow fiber membrane oxygenator employing knitting technology exhibits substantial advantages in fluid simulation analysis. The knitting technique enhances flow field uniformity, decreases turbulence, and boosts structural stability. Consequently, this enhances oxygenation efficiency and prolongs the device’s lifespan. Such outcomes not only establish a crucial theoretical foundation but also offer valuable technical insights for the enhancement and innovation of ECMO devices in the future.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the financial support from the Shenzhen Science and Technology Major Special Project (Zhong 202327D238).

ORCID iDs

Wei Jia

Pibo Ma

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Fluid simulation analysis of ECMO hollow-fiber membrane fabrics from knitting technology

Abstract

Keywords

Introduction

Materials and methods

Preparation of PMP hollow fiber

Knitting organization analysis of oxyfilm fabrics

Modeling approach for oxygenator simulation analysis

Geometric modeling approach for oxygenators

The results of the values of the similar eigenquantities

Equation solving methods for simulation calculations

Theoretical equations solved by fluid domain simulation

Simulation of solid domains to solve theoretical equations

Results and discussion

Calculation of simulation results

Simulation results and analysis of flow field

Analysis of simulation results on pressure within the flow field

Simulation results and analysis of velocity in the flow field

Analysis of results from solid domain simulation

Conclusion

Footnotes

Declaration of conflicting interests

Funding

ORCID iDs

References