Startseite Numerical and experimental flow analysis in centifluidic systems for rapid allergy screening tests
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Numerical and experimental flow analysis in centifluidic systems for rapid allergy screening tests

  • Manuel Dethloff EMAIL logo , Marc Dangers , Boris Wilmes und Hermann Seitz
Veröffentlicht/Copyright: 12. September 2015
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Current Directions in Biomedical Engineering
Aus der Zeitschrift Current Directions in Biomedical Engineering Band 1 Heft 1

Abstract

For the development of the automated processing of a membrane-based rapid allergy test, the flow characteristics in one part of the test, the reagents module, are analysed. This module consists of a multichannel system with several inputs and one output. A return flow from one input channel into another should be avoided. A valveless module with pointed channels at an angle of 12° is analysed with numerical and experimental methods with regard to the flow characteristics.

Keywords: rapid allergy test; computational fluid dynamics (CFD); experimental validation; contact angle

1 Introduction

Allergies are on the rise and all age groups are affected. Furthermore untreated allergies can become chronic. Early allergy testing is essential for an accurate medical history and to quickly determine therapy possibilities. The FastCheckPOC® 20 (FCP20) is a rapid point of care test which is performed outside the lab (see Figure 1). The FCP20 is based on an ELISA protocol for the semi-quantitive determination of allergen specific IgE (for detailed information on ELISA in a fluidic allergy dia-gnostic device see [1]). With a range of 20 test para-meters, FCP20 covers over 90% of the most frequently occurring allergies in central and northern Europe. So far, this test is performed manually. A concept for an automa-ted test execution of the FCP20 has being developed.

In this study the flow characteristics in one part of the automated test execution, the reagents module, are analysed with computational fluid dynamics (CFD) and experimental validations. CFD is a branch of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows [2]. CFD studies are very suitable for the implementation of parameter variations. It is possible to change several options or variables in the preprocessing, and the simulations themselves can be calculated parallel on a computing cluster. This saves time and money in comparison to experimental analysis. But although CFD is a powerful tool for the execution of flow calculations, it is necessary to validate the results by experimental analysis.

Figure 1 FastCheckPOC® 20 (FCP20) Test Kit.
Figure 1

FastCheckPOC® 20 (FCP20) Test Kit.

2 Methods

2.1 Concept of automated test execution

The concept of the automated test execution includes a modular design (see Figure 2), consisting of the FCP20 (1), a disposable reagents module (2), and a multiple usable stationary unit (3), which delivers the operating liquid.

The current study focuses on the reagents module (2). It consists of several inputs, one output and a channel system, in which the reagents are dried up. The operating fluid passes through the channel and removes the reagents. The channels have a thickness of at least 2 mm with a flow rate of up to 60 ml/min.

In previous studies a return flow from one input-channel into the other input-channels was observed, which would lead to erroneous results of the allergy test. The main objective is therefore to avoid a return flow and thus a mixing of the various dried reagents without using active components like valves.

In a previous study, modified surfaces were investigated, but these elements did not show any functionality. The current approach uses a purely geometrical solution. This includes pointed channels at an angle of 12° (see Figure 2 right, top: model for simulation, bottomml: model for experiment). The analysis of the flow characteristics in these channels is realized with numerical and experimental methods.

Figure 2 Schematic structure of the modular design (left); model of the reagents module for the simulation (top right), model for experiment (bottom right).
Figure 2

Schematic structure of the modular design (left); model of the reagents module for the simulation (top right), model for experiment (bottom right).

Figure 3 Individual steps of a CFD-calculation (left to right) for the reagents module.
Figure 3

Individual steps of a CFD-calculation (left to right) for the reagents module.

2.2 Numerical analysis

The fluid flow in the reagents module is simulated with computational fluid dynamics (CFD). For the simulation the software tool ANSYS CFX 14.5 (ANSYS, Canonsburg USA) is used. A general CFD calculation for this problem contains the following steps (see Figure 3):

  • – The geometry (physical bounds of the channels) of the problem is defined (see Figure 3 a).

  • – The volume occupied by the fluid is divided into discrete cells; here: uniform mesh with only one input on the right side (see Figure 3 b).

  • – The physical modeling and the boundary conditions are defined, e.g. initial conditions, inlet, outlet, etc. (see Figure 3 c).

  • – After preprocessing, the simulation is started on a computing cluster and the Navier-Stokes equations, which describe the motion of viscous fluids, are solved iteratively in a transient way.

  • – Finally a postprocessor is used for the analysis and visualization of the resulting solution (see Figure 3 d).

In this CFD simulation the following parameter variations are made: the channel depth, the volume flow and the type of infilling.

Figure 4 Infilling of the reagents module in the CFD simulation.
Figure 4

Infilling of the reagents module in the CFD simulation.

The channel depth varies from 0.2 mm to 0.8 mm and the volume flow from 10 ml/min to 60 ml/min. The infilling takes place at two inlets. Depending on the operating point of the test execution, only one of the two inlets is open, while the other is treated like a wall. Figure 4 demonstrates the infilling in channel 2 for the numerical simulation. The operating fluid is water, which is initially filled into the airfilled channels.

2.3 Experimental analysis

As already explained above, experimental analysis is essential for CFD-calculations. The validations provide the experimental proof of the correctness of the flow dynamic models and calculations. Apart from the validations, other experimental analyses had to be per-formed before the CFD calculations, as they were needed to determine data, which was required for the simulation as input information. An important value is the contact angle . In general, the contact angle is the angle where a liquid interface meets a solid surface, see Figure 5 [3]. It quantifies the wettability of a solid surface by a liquid via the Young equation (see Eq. 1).

(1)cosΘσSS−σIσSL

The Young equation establishes a relationship between the contact angle Θ, the surface free energy σSS of the solid body, the specific interface energy σI between the solid and the liquid drop thereon, and the surface tension σSL of the liquid.

Figure 5 Static contact angle between a water drop and the solid surface of the channel.
Figure 5

Static contact angle between a water drop and the solid surface of the channel.

In the present case, the dynamic contact angle plays an important role for the flow characteristics in the simulations (see Figure 6). It is measured by the contact angle measuring instrument OCA 40 Micro (DataPhysics Instruments, Filderstadt, Germany) and optical analysis.

The validations are conducted using the syringe pump Nemesys (Cetoni, Krobußen, Germany), a tube system with valves and the digital camera EXILIM (CASIO Europe, Norderstedt, Germany) for the optical analysis. Furthermore, the pco.edge 5.5 sCMOS camera (PCO, Kel-heim, Germany) with a frame rate of about 100 fps is used for a detailed analysis of the fluid meniscus in critical areas like the channel branching (see Figure 7, right).

Figure 6 Dynamic contact angle in a simulation (left) and the experimental analysis (right).
Figure 6

Dynamic contact angle in a simulation (left) and the experimental analysis (right).

Two cases are considered in the present study. In the first case water is filled into the air filled channel, either through channel inlet 1 or 2. A return flow from one input channel into the other should be avoided. In the second case water is filled into the already water-filled channel, where the filled water is mixed with the coloring matter Rhodamine B (Sigma-Aldrich, Taufkirchen, Germany) for a better visualization of a possible mixing.

3 Results and discussion

The experimental results for the contact angle needed for the simulation, fluctuate within a wide range. The angle between water, air and the wall of the channel varies between 70° and 110°. The reason for this change is that the surface of the channel is not totally plane and smooth due to the mechanical manufacturing process. Smallest notches manipulate the meniscus of the interface. The average value of 90° is chosen for the simulation

3.1 Water is filled into the air-filled channel

If water is filled into the air filled channel, two important aspects can be identified: At small volume flows (up to 30 ml/min), and thus also small flow velocities, the flow behaviour seems to be stable and no return flow can be identified. For high volume flows (from 40 ml/min up to 60 ml/min) the flow characteristic is very unstable and water gets into the other inlet channel irrespective of which inlet is used. These facts can be observed in the simulation as well as in most cases of the validation (see Figure 8 and 9).

Figure 7 Experimental analysis of the contact angle in the channel branching.
Figure 7

Experimental analysis of the contact angle in the channel branching.

Figure 8 No return flow from channel 2 into channel 1 at a volume flow of 10 ml/min (left: simulation, right: exp. validation).
Figure 8

No return flow from channel 2 into channel 1 at a volume flow of 10 ml/min (left: simulation, right: exp. validation).

At volume flows from 30 ml/min to 40 ml/min the simulation and the validation are not identical for some cases. While some simulations predict a stable flow without a return flow at a volume flow of 35 ml/min, experimental validations show a return flow for the same volume flow. Possible reasons for this could be adhesion forces between smallest solid particles in the channel and the water, which induce the fluid to move forwards at this critical flow velocity.

3.2 Water is filled into the water-filled channel

This case of investigation reflects an operating status of the test execution, where a jetting liquid passes through the channels filled with a reagents fluid. A mixing of the two fluids could be avoided. For this investigation, coloured water is filled into the vertical channel (inlet 2), while the horizontal channel (inlet 1) is already filled with static water. In all simulated cases, no mixing of the two fluids is visible (see Figure 10).

Figure 9 Return flow from inlet channel 2 into channel 1 at a volume flow of 60 ml/min (left: simulation, right: exp. validation)
Figure 9

Return flow from inlet channel 2 into channel 1 at a volume flow of 60 ml/min (left: simulation, right: exp. validation)

Figure 10 CFD Simulation (left to right): Initially the reagents module is filled with static water (light blue) and air (red); Water (dark blue) flows continuously through inlet 2 (at the top), air and static water are pressed out.
Figure 10

CFD Simulation (left to right): Initially the reagents module is filled with static water (light blue) and air (red); Water (dark blue) flows continuously through inlet 2 (at the top), air and static water are pressed out.

Only in a few experimental studies, a mixing occurs, but there is no correlation between the volume flow or the channel depth. Possible reasons for this could be vortices of very small dimensions in the channel branching that are not determined by the simulation.

4 Conclusion

The tested reagents module with pointed channels does not provide sufficient protection against a return flow or a mixing in the channels of the reagents module for the whole range of volume flow. Only 100% safety ensures a precise operation of the test execution. If water is filled into an air filled channel, the probability for a return flow increases for higher flow velocities and volume flows respectively. For very low or very high volume flows, CFD simulations and experimental analyses agree very well. Only for critical flow velocities, smallest changes in the channel (e.g. particles, notches) influence the flow in such a manner, that the real flow in the experiment shows a different characteristic to that of the simulation.

Funding: This project is funded by the Bundesministerium für Bildung und Forschung initiative “Entrepreneurial Regions” – “The BMBF Innovation Initiative for the New German Länder” (“Unternehmen Region”). In the program “Innovative Regional Growth Cores (German: Innovative regionale Wachstumskerne”).

Author’s Statement

  1. Conflict of interest: Authors state no conflict of interest. Material and Methods: Informed consent: Informed consent is not applicable. Ethical approval: The conducted research is not related to either human or animals use.

References

[1] Drescher P, Dangers M, Rübenhagen R, Seitz H. The effects of various flow velocities on the sensivity of an ELISA in a fluidic allergy diagnostic device. Point of Care: The Journal of Near-Patient Testing and Technology, 2 2014; 35-4010.1097/POC.0000000000000016Suche in Google Scholar

[2] Ferziger J, Peric M. Computational Methods for Fluid Dynamics. 3th ed. Berlin: Springer 2002.10.1007/978-3-642-56026-2Suche in Google Scholar

[3] Oertel jr H, Böhle M, Reviol T. Strömungsmechanik. 6. Auflage. Wiesbaden: Vieweg+Teubner 201110.1007/978-3-8348-8110-6Suche in Google Scholar

Published Online: 2015-9-12
Published in Print: 2015-9-1

© 2015 by Walter de Gruyter GmbH, Berlin/Boston

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Schlagwörter für diesen Artikel
rapid allergy test; computational fluid dynamics (CFD); experimental validation; contact angle
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Heruntergeladen am 8.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/cdbme-2015-0105/html
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