An experimental study on real–time analysis of two–phase peristaltic slug flows in dialysis machines

https://doi.org/10.1016/j.flowmeasinst.2021.101941Get rights and content

Highlights

  • An experimental study on two–phase peristaltic slug flows is presented.

  • The measurement algorithm is based on the image processing technology.

  • Slug length, velocity and frequency are considered as flow characteristic parameters.

  • The effect of liquid superficial velocity on characteristic parameters is studied.

Abstract

Two–phase flows appear in many industrial and biomedical applications. One of the most vital biomedical applications of two–phase flows is in hemodialysis machines due to air embolism and heparin injection. Since these flows have a very complex and intermittent nature, studying their dynamics is a very challenging and fundamental problem. The purpose of this article is to present an experimental study on the dynamics of two–phase peristaltic slug flows. The measurement strategy is based on the image processing technology. The characteristic parameters of the two–phase pulsatile slug flows, including the slug length, as well as the translational velocity and frequency of the slug motion, are measured, and the effect of the liquid flow rate and liquid superficial velocity is investigated. The results show that the average and maximum slug velocities, and also the dominant amplitude of the slug velocity increase with the flow rate and liquid superficial velocity, while it is not possible to clearly predict a correlation between the liquid superficial velocity and the slug length. The measurement strategy presented in this article can be used in the control and alarm systems of smart dialysis machines.

Introduction

The simultaneous stream of two different fluids, such as air and water, is called two–phase flow, which can be found in a wide variety of industrial and biomedical applications. Due to the deformable nature of fluids, several flow regimes, including bubbly, slug, churn, wispy, and annular flow, can appear in the two–phase flows depending on the properties of the fluids, the length and diameter of pipe, and the superficial velocities of the fluids [1]. One of the most important two–phase flow regimes is known as the slug flow. In this regime, the flow is separated by some bullet–shaped long bubbles, known as slugs, which occupy most of the cross sectional area of the pipe [2]. Sharma et al. [3] demonstrated that the most crucial parameters to characterize a slug flow are the length, velocity, and frequency of the slug. These parameters, known as the characteristic parameters, are also important to the optimal design of industrial and biomechanical devices and processes such as nuclear reactors, geothermal power plants, membrane and crystallization processes, hydrocarbon production, biosensors, and biochips [4,5].

One of the most vital applications of two–phase flows is in biomedical devices in which this type of flow offers an alternative approach to process biological samples [5]. Dialysis, the most common form of treatment for kidney failure, is one of the most popular medical processes in which two–phase flow is inevitable. In this process, the patient's blood is cyclically placed in contact with a dialysate solution across a semi–permeable membrane in order to remove excess water and cleanse the blood of metabolic toxins. It is also sometimes referred to as hemodialysis, which is defined as any procedure in which impurities and wastes are removed from the blood. A schematic representation of the basic components of hemodialysis system is shown in Fig. 1.

In hemodialysis systems, the blood is taken from the patient's body through an extracorporeal blood delivery circuit; then it passes across a dialyzer for filtration, and finally returns to the patient. The hemodialysis machine is mainly composed of an access device (needles or catheter), a blood pump, a heparin pump, a dialyzer, and an air trap detector [6]. Since, in human body, the blood is transported by the continuous and cyclical contraction and/or relaxation of the heart muscle, the blood pump used in hemodialysis machines is a flow–regulated or peristaltic pump, which leads to a peristaltic flow [6]. This type of pumps consists of a rotor with rollers, a stator and flexible tubing compressed between the rollers and the stator (Fig. 2). In these pumps, the fluid is transported into a tube or channel due to contraction and/or expansion waves, which propagate along the length of the tube or channel. Two–phase slug flows in which a peristaltic pump is used to transfer the fluids are called two–phase peristaltic or pulsatile slug flows.

The role of the Heparin pump is to deliver the anti–coagulant heparin to the blood to suppress potential clotting stimulated by the extracorporeal blood circuit [6]. The Heparin pump is a regular syringe operated by a controlled motor (Fig. 3). Therefore, it is clear that two–phase flow inevitably occurs in the process of dialysis. In addition, air embolism is one of the most critical and fatal complications of hemodialysis therapy. Air enters the system mostly from the pre–pump section and the access device due to the negative pressure [7].

In order to analyze the two–phase flows more precisely and provide more reliable data for the validation of computer simulations, researchers have introduced several experimental approaches, such as X–ray scanning [8], gamma–ray tomography [9], ultrasound [10], optical tomography [11], and high–speed camera [12]. However, none of them have studied peristaltic slug flows. Zabaras et al. [13] examined several methods for predicting the slug frequency in horizontal and inclined pipes, including both empirical correlations and mechanistic models. They also developed a novel correlation and demonstrated that the developed correlation represents a significant improvement in the accuracy of the slug frequency prediction over other methods. Also, it was a continuous slug flow. Van Hout et al. [14] used multiple optical fiber probes and image processing techniques to measure the translational velocities of elongated bubbles in a continuous slug flow for various flow rates, pipe inclinations and pipe diameters. They also proposed a simplified model to calculate the effective translational velocity in the continuous slug flow. Wang et al. [15] carried out an experimental study on the gas–liquid slug flow in a horizontal test loop. They used two pairs of conductivity probes in order to measure the characteristic parameters of two–phase flows. Based on their experimental results, they concluded that the slug frequency weakly depends on the gas superficial velocity, and strongly depends on the liquid superficial velocity.

Mayor et al. [16,17] concentrated on the free–bubbling gas–liquid (air–water) vertical slug flow in the laminar and turbulent regime experimentally and numerically. In experiments, they used an image processing based measurement algorithm, while their simulations were based on a slug flow simulator (SFS). They obtained a single correlation for the prediction of the bubble velocity as a function of the length of the liquid slug ahead of the bubble. They also demonstrated that the flow stability increases with increasing superficial liquid velocity and with decreasing superficial gas velocity in the laminar regime. Han et al. [18] measured the liquid film thickness in a micro–tube slug flow using a laser focus displacement meter. They carried out several experiments using air, ethanol, water, and fully fluorinated liquid (Fluorinert™ FC–40) as working fluids to clarify the effects of bubble length, liquid slug length, gravity, and Capillary, Reynolds, and Weber numbers on the formation and thickness of the thin liquid film in a micro–tube two–phase flow. More recently, do Amaral et al. [19] introduced a video processing based measurement technique to automatically estimate bubble parameters, including dimension, velocity, and frequency in a horizontal pipe. They used a high–speed camera and several image processing techniques and showed that their proposed method is a powerful tool in the investigation of two–phase flows through comparing the results with theoretical predictions. It should be noted that none of the above cited articles have studied the peristaltic slug flows. However, Abishek et al. [20] carried out a computational analysis to investigate the impacts of co–current steady and pulsatile flow on the dynamics of Taylor bubbles in both Newtonian and shear–thinning non–Newtonian liquids in a vertical tube. They found that the velocity of Taylor bubbles is independent of the bubble size under both steady and pulsatile co–current flows. In addition, it was concluded that, in comparison with the frequency, the amplitude of the pulsatile flow has a more significant effect on the oscillating characteristics of the rising Taylor bubbles. It is worth mentioning that this article studies the pulsatile flow in a numerical way using the finite–volume based interFoam/interDyMFoam solver of OpenFOAM–2.1 software.

Nowadays, the performance of smart dialysis machines is considered satisfactory and continues to be optimized; nevertheless, there are still several unresolved issues that require real–time analysis of the dialysis process, understanding the changes in patient homeostasis, and consequently making an appropriate response in real time. In recent years, there has been a significant increase in the number of elderly patients with co–morbid conditions, which can lead to several complications including stenosis of hemodialysis vascular access, intradialytic hypotension, arrhythmia, and air embolism, which have been frequently observed during hemodialysis therapy, and which put the patient's life at risk [6,7]. Therefore, designing an on–line monitoring system seems essential for early detection and correction of the aforementioned complications, and subsequently increasing the chance of success in hemodialysis therapy. Furthermore, to the author's knowledge, there is currently no consensus on the most optimal administration pattern of heparin injection [6,7].

However, in the recent years, many researchers have focused on the two–phase flows by means of the experimental and theoretical techniques under different conditions; to the best knowledge of the authors, none of them have studied the two–phase peristaltic slug flows in an experimental way. Hence, the purpose of the present article is to present an experimental study on measuring the characteristic parameters of the two–phase pulsatile slug flows, including the slug length, as well as the velocity and frequency of the slug motion. In this regard, a mechanical flow loop similar to the hemodialysis machines is developed, and the effect of the flow rate and liquid superficial velocity on the characteristic parameters is investigated. The approach presented in this article can also be employed in the control and alarm system of smart dialysis machines, the optimal design of dialysis devices, and the improvement of clinical tolerance of dialysis process.

Section snippets

Experimental setup

In this study, a mechanical flow loop partially analogous to the hemodialysis machine with the intent of studying the characteristic parameters of two–phase peristaltic slug flows was developed. The schematic setup to generate a pulsatile slug flow and capture the slug motion is depicted in Fig. 4. In this experiment, air and water are used as the working fluids to conduct the peristaltic slug flow tests.

The experiments are performed in a mini channel with the length of 30 cm and the internal

Measurement technique

In this section, the proposed image processing based measurement strategy is comprehensively described. The final output is the slug length, as well as the translational velocity and frequency of the slug motion. First of all, it is required to deconstruct the recorded video of the flow into a set of sequential images before processing them through the proposed image processing strategy. Fig. 5 illustrates the flowchart of the proposed strategy in order to quantitatively measure the

Results and discussion

In this section, first of all, the accuracy of the experimental results is validated by three–dimensional (3–D) simulation of the slug flow using the finite–volume based interFoam/interDyMFoam solver in OpenFOAM–2.1. Then, the quantitative results obtained from the experiments are presented. The experiments are carried out for various flow rates of water; and accordingly, the effect of the flow rate and liquid superficial velocity on the characteristic parameters of the pulsatile slug flow,

Conclusions

Two–phase peristaltic flows inevitably appear in many biomedical devices, such as the hemodialysis machines due to the air embolism and heparin injection. This article presented an experimental study on the characteristic parameters of a two–phase peristaltic slug flow. An image processing based algorithm was used to automatically measure the characteristic parameters of the peristaltic slug flow, including the slug length, as well as the translational velocity, and frequency of the slug

Funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not–for–profit sectors.

Author contributions

Mohsen Mirzaei: Conceptualization, Project administration, Resources, Supervision, Methodology, Validation, Writing–Review & Editing. Ahmad Mahdian Parrany: Data curation, Investigation, Formal analysis, Software, Visualization, Validation, Writing–Original Draft Preparation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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