Sinusoidal Microchannel with Descending Curves for Varicose Veins Implantation

micromachines

Article Sinusoidal Microchannel with Descending Curves for Varicose Veins Implantation

Muhammad Javaid Afzal 1 ID , Muhammad Waseem Ashraf 2,*, Shahzadi Tayyaba 3, M. Khalid Hossain 4 ID and Nitin Afzulpurkar 5

1 Department of Physics, The University of Lahore, Lahore 54000, Pakistan; [email protected] 2 Department of Physics (Electronics), GC University, Lahore 54000, Pakistan 3 Department of Computer Engineering, The University of Lahore, Lahore 54000, Pakistan; [email protected] 4 Institute of Electronics, Atomic Energy Research Establishment, Bangladesh Atomic Energy Commission, Dhaka 1349, Bangladesh; [email protected] 5 Department of Mechanical Engineering Technology (MCET), Higher Colleges of Technology (HCT), Ras al-Khaimah P.O. Box 4793, UAE; [email protected] * Correspondence: [email protected]; Tel.: +92-321-830-2864

Received: 18 October 2017; Accepted: 25 January 2018; Published: 31 January 2018

Abstract: Approximately 26% of adult people, mostly females, are affected by varicose veins in old age. It is a common reason for distress, loss of efficiency, and worsening living conditions. Several traditional treatment techniques (sclerotherapy and foam sclerotherapy of large veins, laser surgeries and radiofrequency ablation, vein ligation and stripping, ambulatory phlebectomy, and endoscopic vein surgery) have failed to handle this disease effectively. Herein, authors have presented an alternative varicose vein implant method—the descending sinusoidal microchannel (DSMC). DSMC was simulated by Fuzzy logic MATLAB (The MathWorks, Natick, MA, USA) and ANSYS (ANSYS 18.2, perpetual license purchased by Ibadat Education Trust, The University of Lahore, Pakistan) with real and actual conditions. After simulations of DSMC, fabrication and testing were performed. The silver DSMC was manufactured by utilizing a micromachining procedure. The length, width, and depth of the silver substrate were 51 mm, 25 mm, and 1.1 mm, respectively. The measurements of the DSMC channel in the silver wafer substrate were 0.9 mm in width and 0.9 mm in depth. The three descending curves of the DSMC were 7 mm, 6 mm, and 5 mm in height. For pressure, actual conditions were carefully taken as 1.0 kPa to 1.5 kPa for varicose veins. For velocity, actual conditions were carefully taken as 0.02 m/s to 0.07 m/s for these veins. These are real and standard values used in simulations and experiments. At Reynolds number 323, the flow rate and velocity were determined as 1001.0 (0.1 nL/s), 11.4 cm/s and 1015.3 (0.1 nL/s), 12.19 cm/s by MATLAB (The MathWorks, Natick, MA, USA) and ANSYS simulations, respectively. The flow rate and velocity were determined to be 995.3 (0.1 nL/s) and 12.2 cm/s, respectively, at the same Reynolds number (323) in the experiment. Moreover, the Dean number was also calculated to observe Dean vortices. All simulated and experimental results were in close agreement. Consequently, DSMC can be implanted in varicose veins as a new treatment to preserve excellent blood flow in human legs from the original place to avoid tissue damage and other problems.

Keywords: descending sinusoidal microchannel (DSMC); varicose vein; fuzzy logic; ANSYS; biomedical microdevice; tissue damage

1. Introduction A varicose vein is an enlarged and disrupted vein which is visible under the skin. They often seem swollen and blue in color, which are abnormal conditions. Major complications are found in

Micromachines 2018, 9, 59; doi:10.3390/mi9020059 www.mdpi.com/journal/micromachines Micromachines 2018, 9, 59 2 of 16

Micromachines 2018, 9, x 2 of 16 the lower legs in humans. These varicose veins become worse with time. This crucial disease is actuallylower an legs enlarged in humans. and stretched These varicose vascular veins form become in the worse lower with legs, time. and This has crucial been reporteddisease is asactually a common chronican conditionenlarged and in medicalstretched science.vascular Theform latest in the research lower legs has, and recognized has been areported marital as clustering a common of this disease.chronic The condition genomic in component medical science. is usually The latest recognized, research has as well recognized as the inﬂuencesa marital clustering of age, profession,of this pregnancy,disease. and The obesity. genomic The component morphological is usually features recognized of this, as disease well as havethe influen been veryces of well age, documentedprofession, [1]. Tortuouspregnancy veins, can and become obesity. varicoseThe morphological veins, and features are seen of withthis disease several have shapes, been lengths,very well and documented diameters [2]. [1]. Tortuous veins can become varicose veins, and are seen with several shapes, lengths, and These veins can have any shape. The ascending and descending sinusoidal veins are shown in diameters [2]. These veins can have any shape. The ascending and descending sinusoidal veins are Figure1 below. shown in Figure 1 below.

Figure 1. Normal veins which can become varicose veins. Figure 1. Normal veins which can become varicose veins. Their lengths and diameters can be in the micrometer range, and even in the nanometer range. TheirThere lengthsare two andaspects diameters related to can the be types in the of micrometervaricose veins. range, One is and the even location in the of nanometeroccurrence of range. Therevaricose are two veins aspects in relatedthe human to the body types, and of the varicose second veins. is the One variety is the and location intensity ofoccurrence of appearance of varicose of veinsvaricose in the human veins. In body, the human and the body, second the first is the type variety of varicose and intensityvein is the ofgreat appearance saphenous of vein varicose, which veins. In theishuman linked to body, the femoral the ﬁrst vein type from of the varicose inner part vein of isthe the ankle. great The saphenous second type vein, is the which lesser issaphenous linked to the vein, which is linked to the deep veins at the back side of knees. The third is the branch-type vein, femoral vein from the inner part of the ankle. The second type is the lesser saphenous vein, which is which is linked with the side veins that are branched with the great saphenous vein. The fourth is the linked to the deep veins at the back side of knees. The third is the branch-type vein, which is linked genital area vein, which is linked from the groin to the back side of the femur and near the womb and with theovary. side The veins fifth thatare the are reticular branched and with web the-type great vein saphenouss, which are vein.found Theanywhere fourth on is the human genital body. area vein, whichAs is for linked the variety from thein the groin intensity to the of back appearance side of theof these femur veins, and they near have the four womb types. and Two ovary. of them The ﬁfth are thehave reticular severe andand web-typemoderate intensity. veins, which The t arehird found is related anywhere to pregnancy on the, and human the fourth body. type As foris known the variety in theas intensity the spider of vein appearance, and can be of found these anywhere veins, they [3–9] have. four types. Two of them have severe and moderateThe intensity. conventional The third treatment is related methods to pregnancy,—self-care and (exercise, the fourth weight type isloss) known and ascompression the spider vein, and canstockings be found—can anywhere ease pain [3and–9]. prevent the disease from getting worse. The additional treatment Themethods conventional for varicose vein treatment disease methods—self-careare described below. (exercise, weight loss) and compression stockings—can ease pain and prevent the disease from getting worse. The additional treatment 1.1. Sclerotherapy and Foam Sclerotherapy of Large Veins methods for varicose vein disease are described below. In this invasive treatment method, a solution or foam solution is injected in varicose veins. After 1.1. Sclerotherapysome days, the and varicose Foam Sclerotherapyveins should disappear. of Large Veins However, there is a risk involved with this type of treatment method, such as deep vein thrombosis (DVT) transmitting the risk of pulmonary embolism. InTherefore, this invasive it is not treatmenta safe treatment method, method a solution[2,10,11]. or foam solution is injected in varicose veins. After some days, the varicose veins should disappear. However, there is a risk involved with this type1.2. of treatment Laser Surge method,ries and Radiofrequency such as deep vein thrombosis (DVT) transmitting the risk of pulmonary embolism.The Therefore, use of laser it treatment is not a safe to treat treatment minor varicose method veins [2,10 is,11 a ].new technology. This type of surgery works by transporting laser light spurts in to the veins, or a thin catheter can be inserted into an 1.2. Laserenlarged Surgeries varicose and Radiofrequencyvein and the high temperature of the catheter tip treats these veins with Theradiofrequency use of laser or laser. treatment It is a non to- treatinvasive minor method varicose, but the veinsre is a risk is a of new hyperpigmentation technology. This [2,7,12 type]. of surgery works by transporting laser light spurts in to the veins, or a thin catheter can be inserted

Micromachines 2018, 9, 59 3 of 16 into an enlarged varicose vein and the high temperature of the catheter tip treats these veins with radiofrequency or laser. It is a non-invasive method, but there is a risk of hyperpigmentation [2,7,12].

1.3. Vein Ligation and Stripping Vein litigation and stripping is an invasive method, and the removal of a main vein can cause tissue damage when the blood moves from small veins as the main vein is removed [2,13,14].

1.4. Ambulatory Phlebectomy In this treatment method, there is a removal of smaller varicose veins with a long sequence of small punctures in the skin. It is very painful method with complications of imperfect removal bruising, intra-arterial injection, hyperpigmentation, skin necrosis, and swelling of varicose veins that can lead to other diseases [2,15,16].

1.5. Endoscopic Vein Surgery Endoscopic vein surgery is a major operation in severe cases, and involves the removal of leg ulcers. In this method, a tiny video camera is injected into the legs and observed from inside. These veins are then removed through surgery. This treatment comes with a rapid onset of side effects after surgery which include pain, tissue damage, bruising, skin discoloration, and swelling. After-effects are very severe with ligation and stripping [2,12,17,18]. The main reason for the failure of all these treatment methods is the tissue damage. These traditional methods cannot stop tissue damage. Consequently, the idea of a very safe treatment method has been introduced, which is the implant of silver bioengineered vein as varicose vein. No tissue damage loss occurs with the use of this technique. The biocompatibility of the fabrication material of these microchannels has been discussed in our previous paper [2]. For this method, there is a need of straight, curved, spiral, circular, ascending, and descending sinusoidal microchannels which can act like bioengineered veins. The shape of varicose veins is exactly like these microchannels. This study focuses on the descending sinusoidal microchannel (DSMC). To date, microchannels have been used broadly in biomedical applications in the field of bioMEMS (bio-microelectromechanical systems) [19]. Huang et al. (2017) worked on bioMEMS device with horizontal straight microchannels for effectual 3D rotation and solitary cell loading [20]. Wang and Fan (2017) worked on stretching DNA with microchannels [21]. Faustino et al. (2016) worked on low-cost microfluidic devices with biomedical applications [22]. Hu and Ohta (2017) worked on cell manipulation in microdevices [23]. Birch and Landers (2017) worked on microfluidic systems for DNA handling and separation [24]. Pinto et al. (2017) worked on blood flow analysis with the help of biomedical microdevices [25]. Rodionov et al. (2013) worked on the brain implant of intracranial electroencephalogram electrodes [26]. Gibney Elizabeth (2015) reported on a brain implant for neurons [27]. Afzal et al. (2017) worked on an ascending sinusoidal microchannel (ASMC) for the treatment of varicose veins disease [2]. Sundell et al. (2017) worked on humanoid dental implants at the atomic scale [28]. Slepian et al. (2017) worked on a cardiovascular implant in the heart [29]. Dillon et al. (2017) worked on an intraocular lens with a revised technique for iris suture [30]. Abdollahi et al. (2017) worked on a cochlear implant for kids [31]. Ramesh et al. (2017) worked on metal stents for the heart [32]. Wang et al. (2017) worked on artificial dermis implantation for the replacement of dead skin [33]. Furthermore, the medical devices as an implant in human body are listed below in Table1. An ASMC was simulated, fabricated, and tested in the previous paper, with the idea of implantation in the human body. All the surgical problems for implantation were discussed in the first part of the study. ASMC cannot be used in every place because of velocity and flow rate difference [2]. Therefore, a new microdevice, DSMC, has been simulated using ANSYS (ANSYS 18.2, perpetual license purchased by Ibadat Education Trust, The University of Lahore, Pakistan) and MATLAB (The MathWorks, Natick, MA, USA), Micromachines 2018, 9, 59 4 of 16 fabricated and tested for varicose veins near the thigh bone and in other places where DSMC is necessary to implant for increased blood flow rate and velocity.

MicromachinesTable 1. Medical 2018, 9, x devices implant in human body. ASMC: ascending sinusoidal microchannel.4 of 16

ReferencesTable 1. Medical devices Medical implant Device in human body. Organ ASMC: ascending Material/Type sinusoidal microchannel. Software

AfzalReferences et al. [2] Medical ASMC Device VaricoseOrgan veinMaterial/Type Silver ANSYS,Software MATLAB SundellAfzal et et al. al. [ 26[2]] DentalASMC implant Varicose Human vein jaw Silver Titanium ANSYS,IVAS 3.6.6MATLAB software KüçükSundell et al.et al. [27 [26]] CardiovascularDental implant implant Human Heart jaw Titanium Electronics IVASCorrosion 3.6.6 software Analyzer DaiKüçük et al. et [al.28 ][27] Cardiovascular Intraocular lenses implant Heart Eyes Electronics Plastic Corrosion ANSYS Analyzer ToddDai et and al. [28] Intraocular lenses Eyes Plastic ANSYS Cochlear implant Ears Electronics ANSYS Naghdy [29] Todd and CochlearIntracranial implant Ears Electronics FiniteANSYS element ZhangNaghdy et al. [3029]] Brain Electronics electroencephalogram electrodes simulation Intracranial electroencephalogram Finite element GeorgiaZhang et et al. al. [ 31[30]] Heart stentBrain Heart MetalElectronics or plastic ANSYS electrodes simulation Titanium and ShahGeorgia et al. et [al.32 ][31] KneeHea implantrt stent Heart Knee Metal or plastic ANSYSANSYS Stainless Steel Titanium and Stainless Wearable artificial Charcoal, activated KimShah et al.et al. [33 [32] ] Knee implant KidneyKnee ANSYSANSYS Fluent kidney (WAK) carbon,Steel and zeolite Charcoal,Donated activated skin tissues ZakKim et al.et al. [34 [33]] Wearable Artificial artificial dermis kidney (WAK) Kidney Skin ANSYSANSYS Fluent carbon,and and polymers zeolite Donated skin tissues Zak et al. [34] Artificial dermis Skin ANSYS 2. Blood Rheology and polymers

The2. Blood human Rheology body is composed of 7% blood by weight. A mature person has 10 pints of blood in the body. The investigation of the ﬂow characteristics of blood (plasma and cells) is called blood The human body is composed of 7% blood by weight. A mature person has 10 pints of blood in rheology. Suitable tissue perfusion occurs when the rheological blood characteristics are within the body. The investigation of the flow characteristics of blood (plasma and cells) is called blood certainrheology. ranges. ChangesSuitable tissue in the perfusion characteristics occurs canwhen play thean rheological important blood role cha in theracteristics growth are rate with of diseases.in The viscositycertain ranges. of blood Changes is obtained in the by characteristics plasma and thecan hematological play an important values role of in red the blood growth cells rate (RBCs) of [35]. As a ﬂuid,diseases. blood The has viscosity non-Newtonian of blood is obtained behavior, by andplasma the and viscidity the hematological of blood changes values of intrinsically red blood cells with the shear( rateRBC ands) [35 temperature.]. As a fluid, blood The viscosity has non-Newtonian of blood has behavior an inverse, and relationshipthe viscidity of with blood the changes temperature. Whenintrinsically blood becomes with the less shear viscous, rate and it temperature. develops high The shearviscosity rates of blood for systolic has an inverse blood relation pressure.ship In the coursewith of diastolic the temperature. pressure, When blood blood travels becomes very less slowly. viscous Therefore,, it develops it develops high shear thickness. rates for systolic Thus, blood blood pressure. In the course of diastolic pressure, blood travels very slowly. Therefore, it develops is taken as a shear-thinning liquid [36]. Humanoid blood has a property named as viscoelasticity. thickness. Thus, blood is taken as a shear-thinning liquid [36]. Humanoid blood has a property named The distortionas viscoelasticity. of RBCs The (red distortion blood of cells) RBC iss (red the blood main cells) reason is the for main the storagereason for of the elastic storage potential of elastic energy becausepotential of the energy pumping because of heart. of the Bloodpumping constituents of heart. Blood are constituents shown below are inshown Figure below2. in Figure 2.

Figure 2. Blood and its components. Figure 2. Blood and its components. This elastic potential energy is transmitted to the blood by the pumping of the heart. It is stored Thisto some elastic extent potential in the elastic energy edifice is transmitted of blood vessels to the, and blood the byother the smaller pumping part ofis thevanished heart. due It isto stored to someviscosity. extent The in theresidual elastic energy ediﬁce is the of rea bloodson for vessels, blood’sand kinetic the movement other smaller. Blood part rheology is vanished is helpful due to in making the choice of the model being used in ANSYS Fluent. The density (1048 kg/m3) and viscosity. The residual energy is the reason for blood’s kinetic movement. Blood rheology is helpful viscosity (0.0032 kg·m−1·s−1) of blood was measured by rheometer for this research. Blood was taken in making the choice of the model being used in ANSYS Fluent. The density (1048 kg/m3) and as a non-Newtonian fluid in this study; the measured rheological data of the blood sample presents

Micromachines 2018, 9, 59 5 of 16 viscosity (0.0032 kg·m−1·s−1) of blood was measured by rheometer for this research. Blood was taken as a non-Newtonian fluid in this study; the measured rheological data of the blood sample presents the non-Newtonian rheological property, which can help to determine the non-Newtonian viscosity model to be used in the ANSYS simulation. The optimal model can be determined by the consideration of the blood flow physics. In research, there is always the requirement of conventional practice for a definite problem and the level of accuracy. In simulation through ANSYS Fluent software, scientists alwaysMicromachines use ten different 2018, 9, x models, depending on the research problem. Among them, the5 K-epsilonof 16 model was selected due to the flow conditions in the set up tool of ANSYS. K-epsilon is a perfect the non-Newtonian rheological property, which can help to determine the non-Newtonian viscosity model for the elucidation of two more equations: turbulent kinetic energy and its dissipation (both are model to be used in the ANSYS simulation. The optimal model can be determined by the zero inconsideration laminar flow). of the ANSYS blood simulationflow physics. was In research, done in there order is always to provide the requirement the actual bloodof conventional flow situation. In blood-bloatedpractice for veins,a definite velocity problem decreases and the due level to frictionof accuracy. from In the simulation blood hitting through the ANSYS walls ofFluent the vessels duringsoftware, its flow. scientists In this case,always the use K-epsilon ten different model models was, depending used as aon reference the research setpoint. problem The. Among K-epsilon modelthem is a, turbulence the K-epsilon model. model was The selected turbulence due to models the flow can conditions present in effects the set whichup tool areof ANSYS. not physical K- in blood flow,epsilon even is a perfect if the flowmodel is for purely the elucidation laminar. of Furthermore, two more equations: scientists turbulent have kinetic nominated energy this and modelits in dissipation (both are zero in laminar flow). ANSYS simulation was done in order to provide the actual several research works [2,37–43]. blood flow situation. In blood-bloated veins, velocity decreases due to friction from the blood hitting the walls of the vessels during its flow. In this case, the K-epsilon model was used as a reference 3. Fuzzy Logic MATLAB Simulation for Descending Sinusoidal Microchannel (DSMC) setpoint. The K-epsilon model is a turbulence model. The turbulence models can present effects Fuzzywhich logic are not controller physical in (FLC) blood was flow managed, even if the to flow evaluate is purely various laminar. parameters Furthermore of, DSMC.scientists This have system had thenominated same input this andmodel output in several parameters research works with [ same2,37–43 membership]. functions. Their ranges were set according to the descending nature of the DSMC. In the Fuzzy logic MATLAB technique, there are three 3. Fuzzy Logic MATLAB Simulation for Descending Sinusoidal Microchannel (DSMC) membership functions taken for each input and output variable. The ranges for Reynolds Number are: 0–175 for smallest,Fuzzy logic 0–350 controller for smaller, (FLC) was and managed 175–350 to for evaluate small. various The ranges parameters for pressure of DSMC. are: This 1–1.25 system for low, had the same input and output parameters with same membership functions. Their ranges were set 1–1.5 for medium, and 1.25–1.5 for high. The ranges for curve height are: 5–6 for small, 5–7 for medium, according to the descending nature of the DSMC. In the Fuzzy logic MATLAB technique, there are and 6–7three for high.membership The ranges functions for %taken loss for are: each 0.1–0.55 input forand small,output 0.1–1 variable. for medium,The ranges and for 0.55–1Reynolds for large. The rangesNumber for are: flow 0–175 rate for are: smallest, 0–525 0 for–350 small, for sma 0–1050ller, and for 175 medium,–350 for small. and The 525–1050 ranges for pressure high. The are: ranges for velocity1–1.25 are: for low, 0–7.5 1–1.5 for for small, medium 0–15, and for 1.25 medium,–1.5 for andhigh. 7.5–15 The ranges for high. for curve MATLAB height are: simulation 5–6 for small, was done on the5 basis–7 for of medium the following, and 6–7 for equations: high. The ranges for % loss are: 0.1–0.55 for small, 0.1–1 for medium, and 0.55–1 for large. The ranges for flow rate are: 0–525 for small, 0–1050 for medium, and 525–1050 for high. The ranges for velocity are: 0–ρ7.5VD for small,π 0R–154∆ forP medium, and 7.5–15 for high. MATLAB R = , Q = , Q = AV. simulation was done on the basise of theµ following equations8ηD : = , = , = . 4 Here Reynolds number = Re, velocity𝜌𝜌𝜌𝜌𝜌𝜌 = Uin,𝜋𝜋 viscosity𝑅𝑅 ∆𝑃𝑃 = µ, curve height = Dh, fluid density = ρ, Here Reynolds number = , velocity𝑒𝑒 𝜇𝜇 = , viscosity8𝜂𝜂𝜂𝜂 = , curve height = , fluid density = , diameter = d, velocity = V, and flow rate𝑅𝑅 = Q.𝑄𝑄 The rule𝑄𝑄 viewer𝐴𝐴𝐴𝐴 of MATLAB is shown in Figure3. diameter = d, velocity = , and flow rate = . The rule viewer of MATLAB is shown in Figure 3. 𝑅𝑅𝑒𝑒 𝑈𝑈𝑖𝑖𝑖𝑖 𝜇𝜇 𝐷𝐷ℎ 𝜌𝜌 𝑉𝑉 𝑄𝑄

Figure 3. Rule Viewer (MATLAB). Figure 3. Rule Viewer (MATLAB). The surface viewer graphs (3D) of flow rate and velocity with pressure, curve radius, and % loss are shown below in Figure 4. The MATLAB function generates these three-dimensional graphs. These graphs show the dependence of one parameter on the two others.

Micromachines 2018, 9, 59 6 of 16

The surface viewer graphs (3D) of ﬂow rate and velocity with pressure, curve radius, and % loss are shown below in Figure4. The MATLAB function generates these three-dimensional graphs. These graphs show the dependence of one parameter on the two others. Micromachines 2018, 9, x 6 of 16

Figure 4. The graphs of surface viewer (3D): (a) Flow rate relies upon pressure and Reynolds number; Figure(b) 4. FlowThe rate graphs relies of upon surface Reynolds viewer number (3D): (anda) Flow curve rate height; relies (c) uponFlow rate pressure relies andupon Reynolds pressure and number; (b) Flow% loss rate; (d) relies Flow rate upon relies Reynolds upon curve number height and and curvepressure height;; (e) Flow (c) rate Flow relies rate upon relies Reynolds upon pressure number and % loss;and (d )% Flow loss; rate(f) Flow relies rate upon relies curve upon height curve andheight pressure; and % loss (e) Flow; (g) Velocity rate relies relies upon upon Reynolds % loss and number and %Reynold loss; (sf number) Flow; rate (h) Velocity relies upon relies curveupon % height loss and and pressure % loss;; ( (i)g )Velocity Velocity relies relies upon upon % loss % lossand and Reynoldscurve number; height; ( (j)h Velocity) Velocity relies relies upon upon curve % loss height and and pressure; Reynolds (i) Velocity number; relies (k) Velocity upon % relies loss andupon curve height;pressure (j) Velocity and curve relies height upon; (l curve) Velocity height relies and upon Reynolds Reynolds number; number and (k) pressure Velocity. relies upon pressure and curve height; (l) Velocity relies upon Reynolds number and pressure. Mamdani’s value, MATLAB simulation results, difference, and error percentage are given in Table 2 below.

Micromachines 2018, 9, 59 7 of 16

Mamdani’s value, MATLAB simulation results, difference, and error percentage are given in Table2 below.

Table 2. Simulated results with Mamdani’s results.

Model Flow Rate in 0.1 nL/s Velocity in cm/s Mamdani’s value 1001.2 11.5 Micromachines 2018MATLAB, 9, x simulation 1001.0 11.4 7 of 16 Difference 0.2 0.1 Error percentageTable 2. Simulated results 0.02% with Mamdani’s results. 0.85%

Model Flow Rate in 0.1 nL/s Velocity in cm/s The results of this simulationMamdani’s are value presented in Table1001.2 2. In order to11.5 confirm the MATLAB simulation results, Mamdani’s model wasMATLAB used. simulation With the of Mamdani’s1001.0 relation,11.4 the results of velocity and flow rate were 11.5 cm/s and 1001.2Difference (0.1 nL/s), respectively.0.2 MATLAB0.1 values for velocity and flow rate measured as 11.4 cm/s andError 1001.0 percentage (0.1 nL/s), respectively.0.02% The0.85% percentage errors for velocity and flow rate wereThe 0.85% results and of 0.02%this simulation respectively. are presented The results in Table are 2. veryIn order close. to confirm In the the succeeding MATLAB segment, blood rheologysimulation is discussed results, Mamdani’s for the model justification was used. of With the modelthe of Mamdani’s used for fluidrelation, flow the beforeresults of the ANSYS simulationvelocity and to and confirm flow rate the were above 11.5 cm/s results and 1001.2 for DSMC. (0.1 nL/s), respectively. MATLAB values for velocity and flow rate measured as 11.4 cm/s and 1001.0 (0.1 nL/s), respectively. The percentage errors for velocity and flow rate were 0.85% and 0.02% respectively. The results are very close. In the succeeding 4. ANSYS Fluent Simulation for DSMC segment, blood rheology is discussed for the justification of the model used for fluid flow before the This sectionANSYS simulation has been and added to confirm with the above aim ofresults illustrating for DSMC. some of the capabilities of ANSYS Fluent as a powerful4. ANSYS simulation Fluent Simulation tool that givesfor DSMC an accurate analysis of the silver-based descending sinusoidal microchannel. Design Modeler is a designer tool of ANSYS that can create and modify the geometry This section has been added with the aim of illustrating some of the capabilities of ANSYS Fluent for its analysisas a powerful in ANSYS simulation Workbench tool that gives by using an accurate different analysis steps of the like silver extrude,-based descending sweep, etc.sinusoidal Meshing is the second essentialmicrochannel. part ofDesign the simulationModeler is a designer process. tool Through of ANSYS thethat optimizedcan create and meshing, modify the accurate geometry results of flow rate andfor its speed analysis are in obtained. ANSYS Workbench Setup, solution,by using different and results steps like optimization extrude, sweep, in ANSYSetc. Meshing are is the the final parts second essential part of the simulation process. Through the optimized meshing, accurate results of of the simulation process. The K-epsilon model was carefully chosen from the setup tool of ANSYS, flow rate and speed are obtained. Setup, solution, and results optimization in ANSYS are the final and the powerparts of law the modelsimulation was process. also chosen The K-epsilon due to model the rheologicalwas carefully propertieschosen from ofthe blood. setup tool The of estimated calculationsANSYS of Reynolds, and the power and Deanlaw model numbers was also for chosen DSMC due wereto the obtainedrheological withproperties the helpof blood. of theThe equations given below:estimated calculations of Reynolds and Dean numbers for DSMC were obtained with the help of the equations given below: ρDhUin p R = , D = R d/2r. e µ e e = , = 2 . 𝜌𝜌𝐷𝐷ℎ𝑈𝑈𝑖𝑖𝑖𝑖 Here Reynolds number = Re, velocity𝑒𝑒 = Uin𝜇𝜇, viscosity𝑒𝑒 𝑒𝑒 =𝑑𝑑µ, hydraulic diameter = Dh, fluid density = ρ, Here Reynolds number = , velocity𝑅𝑅 = , viscosity𝐷𝐷 𝑅𝑅 � = �, hydraulic𝑟𝑟 diameter = , fluid density diameter ==d , and, diameter radius = d =, andr for radius DSMC. = r for DSMC. 𝑅𝑅𝑒𝑒 𝑈𝑈𝑖𝑖𝑖𝑖 𝜇𝜇 𝐷𝐷ℎ Twenty iterationsTwenty iterations for the ANSYSfor the ANSYS simulation simulation were were performed performed with with the the same same conditionsconditions of of previous 𝜌𝜌 study (Afzalprevious et al. study 2017: (Afzal ASMC) et al. [ 22017:]. The ASMC) contours [2]. The of contours velocity of andvelocity pressure and pressure are shown are shown in Figure in 5a,b. Figure 5a,b.

Figure 5. Cont.

Micromachines 2018, 9, 59 8 of 16

Micromachines 2018, 9, x 8 of 16 Micromachines 2018, 9, x 8 of 16

Figure 5. (a) Velocity contour plot; (b) Pressure contour plot for the descending sinusoidal Figure 5. (amicrochannel) Velocity contour (DSMC) plot;. (b) Pressure contour plot for the descending sinusoidal microchannel (DSMC). FigurePressure 5. (a) isVelocity increased contour at the inputplot; and(b) reducedPressure atcontour the output plot of forthe theDSMC. descending Therefore, sinusoidal a direct Pressuremicrochannelrelation is increasedis present (DSMC) between at. the Reynolds input and number reduced and pressure at the difference. output However of the DSMC., there are Therefore, also three a direct relation isdescending present between curves involved Reynolds in this number extension and of pressureprevious resea difference.rch. Consequently, However, based there on arethe also three Pressuregraphical ispresentation increased in at Figure the input 6a, it andcan be reduced seen that at the the fluid output flows of through the DSMC. DSMC Therefore, gives a better a direct descending curves involved in this extension of previous research. Consequently, based on the relationupsurge is present in pressure between difference Reynolds than number ASMC [2 and]. The pressure simulation difference. through ANSYS However was, theredone toare detect also three graphicaldescendingthe presentation flow curves rate and involved in velocity Figure parameters in6a, this it can extension for be DSMC. seen of that previous the fluid resea flowsrch. Consequently, through DSMC based gives on athe better Figure 6a shows that the pressure difference increased gradually with Reynolds number. The upsurgegraphical in pressure presentation difference in Figure than 6a, ASMC it can [ 2be]. seen The simulationthat the fluid through flows through ANSYS DSMC was done gives toa better detect the results for all curves were analogous to the investigations of Chiam et al. (2016) and Afzal et al. (2017) flow rateupsurge and in velocity pressure parameters difference than for DSMC. ASMC [2]. The simulation through ANSYS was done to detect for sinusoidal microchannels (SMCs) and the ASMC, respectively [44]. Due to the dominance of Figurethe flowviscid6a rate showsforces, and thevelocity that flow thewas parameters truly pressure laminar. for difference DSMC. Therefore, the increased Reynolds number gradually in this withstudy was Reynolds taken as number. The resultsFijustgure forbelow 6a all 350.shows curves Figure that 6b werethe presents pressure analogous a linear difference relationship to the increased between investigations gradually Reynolds number ofwith Chiam Reynolds and flow et rate.number. al. The (2016) The and Afzalresults et al.rate (2017)for of all flow curvesfor and sinusoidal velocitywere analogous were microchannels obtained to the as investigations 1015.3 (SMCs) (0.1 nL/s) of and and Chiam 12.1 the9 et ASMC,cm/s al. (2016)at a Reynolds respectively and Afzal number et [al.44 of (2017) ]. Due to the dominancefor sinusoidal323. This of research viscidmicrochannels forces,shows an the( SMCagreement flows) and was between the truly ASMC the laminar. results, respective of Therefore, Fuzzyly Logic[44]. the DueMATLAB Reynolds to the and dominance ANSYS number of in this viscidsimulations. forces, the flow was truly laminar. Therefore, the Reynolds number in this study was taken as study was taken as just below 350. Figure6b presents a linear relationship between Reynolds number just below 350. Figure 6b presents a linear relationship between Reynolds number and flow rate. The and flow rate. The rate of flow and velocity were obtained as 1015.3 (0.1 nL/s) and 12.19 cm/s at rate of flow and velocity were obtained as 1015.3 (0.1 nL/s) and 12.19 cm/s at a Reynolds number of a Reynolds323. This number research of shows 323. Thisan agreement research between shows antheagreement results of Fuzzy between Logic the MATLAB results and of Fuzzy ANSYS Logic MATLABsimulations. and ANSYS simulations.

Figure 6. Cont.

Micromachines 2018, 9, 59 9 of 16

Micromachines 2018, 9, x 9 of 16

Figure 6. (a) The graph between Reynolds number and pressure difference; (b) Flow rate vs. Reynolds Figurenumber 6. (a) for The DSMC. graph between Reynolds number and pressure difference; (b) Flow rate vs. Reynolds number for DSMC. Figure 6. (a) The graph between Reynolds number and pressure difference; (b) Flow rate vs. Reynolds 5. Fabrication of DSMC and Experimental Setup number for DSMC. 5. FabricationThe channel of DSMC was fabricated and Experimental on silver by Setup using a micromachining process [1]. The diameter of the The5.DSMC Fabrication channel 900 micron.was of DSMC fabricated This processand Experimental on can silver be used by Setup using to achieve a micromachining product dimensions process in [micron1]. The scale diameter. In this of the DSMCfabrication 900The micron. channel proce This dure,was fabricated process a callous can andon silver be sharp used by knife using to achieve of a the micromachining cutting product machine dimensions process AgieCharmilles [1]. inThe micron diameter FORM scale. of 1000 the In this (Georg Fischer Ltd, Schaffhausen, Switzerland) was used to eliminate the minor chips from the silver fabricationDSMC procedure,900 micron. This a callous process and can sharp be used knife to achieve of the cutting product machine dimensions AgieCharmilles in micron scale FORM. In this 1000 substrate with the relative motion of speed and feed [2,45]. The silver substrate was fabricated with (Georgfabrication Fischer Ltd,proce Schaffhausen,dure, a callous Switzerland)and sharp knife was of the used cutting to eliminate machine theAgieCharmilles minor chips FORM from the1000 silver similar dimensions as in our previous study. The fabricated DSMC is shown in Figure 7. substrate(Georg with Fischer the Ltd, relative Schaffhausen, motion of Switzerland) speed and was feed used [2,45 to]. eliminate The silver the substrateminor chips was from fabricated the silver with substrate with the relative motion of speed and feed [2,45]. The silver substrate was fabricated with similar dimensions as in our previous study. The fabricated DSMC is shown in Figure7. similar dimensions as in our previous study. The fabricated DSMC is shown in Figure 7.

Figure 7. Simple micromachining fabrication of DSMC [2]: (a) Raw silver substrate; (b) Electro- polishing and ultra-clean surface; (c) The real fabrication of the DSMC; and (d) Scale of the DSMC. Figure 7. Simple micromachining fabrication of DSMC [2]: (a) Raw silver substrate; (b) Electro- FigureIn 7.orderSimple to confirm micromachining the ANSYS fabrication software of results, DSMC the [2]: experimentation (a) Raw silver substrate; was accomplished (b) Electro-polishing after the polishing and ultra-clean surface; (c) The real fabrication of the DSMC; and (d) Scale of the DSMC. andfabrication ultra-clean process. surface; The (c )flow The rate real fabricationand velocity of theparameters DSMC; and were (d )obtained Scale of thewith DSMC. the fabricated DSMC. A piezoelectricIn order to confirmdiaphragm the ANSYS micropump software mP results,6 was theemployed experimentation with the was electronic accomplished circuit afterfor the In order to confirm the ANSYS software results, the experimentation was accomplished after experimentation.fabrication process. The The clotting flow rate of bloodand velocity was prevented parameters in werethe micropump obtained with with the the fabricated use of heparinDSMC. the fabricationadmixedA piezoelectric in the process. blood diaphragm before The flow use.micropump The rate m andP6 micropumpm velocityP6 was employed parameters pressurize withd the were theblood obtainedelectronic flow with with circuit 55,000 the forPa fabricated andthe DSMC.0experimentation.–7 A mL/min piezoelectric flow Therate. diaphragm clotting These pressureof micropumpblood valueswas prevented can mP6 be was varied in employed the with micropump some with adjustments thewith electronic the usein the of circuit heparinmP6. forA the experimentation.commerciallyadmixed in the-available Theblood clotting before electronic use. of bloodThe circuit mP was6 (mmicropumpP prevented6-EVA, Rise pressurize in Technology the micropumpd the blood, Santa flow Clara, with with theCA, 55,000 useUSA Pa of) wasand heparin admixedused0–7 mL/min inwith the m bloodPflow6, which rate. before permitThese use. tedpressure The the adjustment mP6 values micropump can of be pumping varied pressurized with factors some which theadjustments bloodis done flow partly in the with with mP 55,0006. the A Pa outer regulation. The source voltages could be given with the help of USB. It was attached to the and 0–7commercially mL/min- flowavailable rate. electronic These pressure circuit (m valuesP6-EVA can, Rise be variedTechnology with, Santa some Clara, adjustments CA, USA in) was the mP6. power supply (USB) and the parameter estimation began. Electric power could be provided by a 2.5– A commercially-availableused with mP6, which permit electronicted the circuit adjustment (mP6-EVA, of pumping Rise Technology, factors which Santa is done Clara, partly CA, with USA) the was outer regulation. The source voltages could be given with the help of USB. It was attached to the used with mP6, which permitted the adjustment of pumping factors which is done partly with the power supply (USB) and the parameter estimation began. Electric power could be provided by a 2.5– outer regulation. The source voltages could be given with the help of USB. It was attached to the power supply (USB) and the parameter estimation began. Electric power could be provided by a 2.5–5 V Micromachines 2018, 9, 59 10 of 16

source,Micromachines and this 2018 circuit, 9, x could produce 270 V; its output power was significantly small. There10 of 16 were connectors and jumpers present in this module. Connector number 1 was the screw terminal which 5 V source, and this circuit could produce 270 V; its output power was significantly small. There were was used for the external power supply. It was also used for the exterior clock or the signal amplitude. connectors and jumpers present in this module. Connector number 1 was the screw terminal which Connector number 2 was the solder element for the extension cable and it was used for the connection was used for the external power supply. It was also used for the exterior clock or the signal amplitude. of theC mP6onnector micropump number 2 (Risewas the Technology, solder element Santa for Clara,the extension CA, USA). cable and Connector it was used number for the 3 connection was called the Molex,of the used mP for6 micropump the connection (Rise Technology of the mP6, Santa pump Clara, with CA, USB USA to). provideConnector supply number voltage. 3 was called There the were threeMolex jumpers, used present for the in connection this circuit: of the JP1, m usedP6 pump for settingwith USB the to frequency provide supply of the voltage. micropump; There we JP2,re used to setthree the amplitude;jumpers present and in JP3, this used circuit for: JP1 setting, used for the setting supply. the There frequency was of also the amicropump variable resistor; JP2, used for the amplitudeto set the adjustment. amplitude; and JP3, used for setting the supply. There was also a variable resistor for the Theamplitude DSMC adjustment. was roofed strongly by glass glue and glass pane. In this way, the outflow of blood was prevented.The DSMC The was results roofed were strongly obtained by glass after glue the and experiment, glass pane. In which this way, verified the outflow the ANSYS of blood results. was prevented. The results were obtained after the experiment, which verified the ANSYS results. The whole experimental apparatus is presented in Figure8. The whole experimental apparatus is presented in Figure 8.

Figure 8. Experimental test setup. Figure 8. Experimental test setup. The mP6 micropump was utilized with a supplementary electrical circuit (mP6-EVA). The blood Thehad high mP6 viscosity micropump and it was would utilized certainly with clot a inside supplementary micropump. electrical Consequently, circuit heparin (mP6-EVA). was blended The blood had highwith viscositythe blood andin order it would to decrease certainly its viscosity. clot inside This micropump. technique prevented Consequently, the blood heparin from wasclotting blended with theinside blood the micropump. in order to decrease The pump its was viscosity. able to estimate This technique all the required prevented parameters the blood for fromthis study. clotting This inside the micropump.module contain Theed pump jumpers was and able connectors to estimate attached all the requiredwith the parameterscontroller. Therefore, for this study. the required This module containedpressure jumpers could be and adjusted. connectors In order attached to implant with the the DSMC controller. (bioengineered Therefore, vein) the in required a human pressure body, the could be adjusted.line of action In order and toprocedural implant theplan DSMC should (bioengineered be made. The particular vein) in area a human of the body,varicose the vein line would of action be and proceduralefficiently plan shaved should and be anesthetized. made. The The particular DSMC w areaould of be the separated varicose before vein implantation. would be efficiently The implant shaved would be done by a tiny duct (catheter) made of biocompatible materials. This varicose vein and anesthetized. The DSMC would be separated before implantation. The implant would be done by operation is analogous to the angioplasty procedure. The Holter Monitor will observe heart rate and a tinyblood duct (catheter)pressure. If made the doctor of biocompatible is satisfied materials.with procedure This, varicosethen reasonable vein operation blood flow is analogous would be to the angioplastyreinstated procedure. after the operation The Holter [2]. Monitor will observe heart rate and blood pressure. If the doctor is satisfied with procedure, then reasonable blood flow would be reinstated after the operation [2]. 6. Results and Discussion 6. Results and Discussion At a Reynolds number of 323, 1001.0 (0.1 nL/s) flow rate and 11.4 cm/s velocity were calculated Atby using a Reynolds Fuzzy logic number simulation. of 323, At 1001.0 the same (0.1 nL/s)Reynolds flow number rate and, 1015.3 11.4 (0.1 cm/s nL/s) velocity flow rate were and calculated12.19 by usingcm/s Fuzzyvelocity logicwere calculated simulation. by using At the ANSYS same software. Reynolds DSMC number, was simulated 1015.3 (0.1 twice nL/s) with very flow close rate and 12.19and cm/s fine velocity results in were this calculatedstudy. Fuzzy by logic using is actually ANSYS the software. parametric DSMC approximation was simulated component twice of with the very closeMATLAB and fine resultssoftware in. An this important study. Fuzzy aspect logicof this is is actuallyits ability theto show parametric the performance approximation of FLC system components by using mathematical models. The ANSYS software is a dominant computational fluid dynamics of the MATLAB software. An important aspect of this is its ability to show the performance of (CFD) tool. This software has widespread modeling abilities, and blood flow can be analyzed FLC systemsaccurately. by The using discussion mathematical is provided models. below The. ANSYS software is a dominant computational fluid dynamics (CFD) tool. This software has widespread modeling abilities, and blood flow can be analyzed accurately.6.1. Experimental The discussion Results is provided below.

Micromachines 2018, 9, 59 11 of 16

6.1. ExperimentalMicromachines 2018 Results, 9, x 11 of 16

The experimentalThe experimental results results are shownare shown in Figure in Figure9. In Figure9. In Figure9a, the 9a, pressure the pressure difference difference first increased first almostincrease linearly,d almost and then linearly there, wasand anthen upsurge there ofwas pressure—especially an upsurge of pressure beyond—especially the Reynolds beyond number the 250. This isReynolds because ofnumber the descending 250. This natureis because of the of DSMC. the descending Blood flow nature in descending of the DSMC. order isBlood always flow increased. in Theredescending was also the order DSMC is always which increased. was tested There in anwas experiment also the DSMC for thewhich blood was flow. tested The in an results experiment in Figure 9 clearlyfor show the blood that flo therew. The was results a sudden in Figure upsurge 9 clearly of pressure show that difference there was asa sudden compared upsurge to ASMC of pressure [2]. Note the errordifference bars in as Figure compared9a; the to statistical ASMC [2 standard]. Note the deviation error bars calculated in Figure from 9a; thethe errorstatistical bars wasstandard 32.47865, and thedeviation 5% pressure calculated difference from the for theerror curves bars was was 32.47865 5.03, 3.843,, and 3.0725, the 5% 2.565, pressure 1.9695, difference 1.4995, for 0.977, the 0.459,curves 0.0945 was 5.03, 3.843, 3.0725, 2.565, 1.9695, 1.4995, 0.977, 0.459, 0.0945 for all points (minimum to maximum) for all points (minimum to maximum) of the graph. of the graph.

Figure 9. Experimental graphical results (a) Graph relating Reynolds number and pressure difference Figure 9. Experimental graphical results (a) Graph relating Reynolds number and pressure difference with error bars; (b) bar graph between Flow rate and Reynolds number for DSMC; (c) graph between with error bars; (b) bar graph between Flow rate and Reynolds number for DSMC; (c) graph between Flow rate and Reynolds number with error bar. Flow rate and Reynolds number with error bar. Micromachines 2018, 9, 59 12 of 16

Figure9b,c shows that the flow rate increased gradually with Reynolds number. There are nine points in the graph which show the percentage increase. At the first point, the simulated increase in flow rate was 3.63% whereas in the experimental result it was 3.38%. At the second point, the simulated increase in flow rate was 5.45%, whereas in the experimental result it was 5.26%. At the third point, the simulated increase in flow rate was 7.27%, whereas in the experimental result it was 7.14%. At the fourth point, the simulated increase in flow rate was 9.49%, whereas the experimental result was 9.44%. At the fifth point, the simulated increase in flow rate was 10.94%, whereas the experimental result was 10.9%. At the sixth point, the simulated increase in flow rate was 13.16%, whereas the experimental result was 13.23%. At the seventh point, the simulated increase in flow rate was 14.54%, whereas the experimental result was 14.65%. At the eighth point, the simulated increase in flow rate was 16.87%, whereas the experimental result was 17.06%. Finally, at the ninth point the simulated increase in flow rate was 18.68%, whereas the experimental result was 18.94%. This data show that there was a small decrease in flow rate in the experiment compared to simulation. However, the results are very close. The standard deviation calculated from the error bars in Figure9c was 279.58033 for each point, and the 5% pressure difference for the curves was 49.765, 44.825, 38.5, 34.765, 28.625, 24.79, 18.75, 13.815, and 8.875 for all points in the graph. Here, in comparison with previous paper results there is a better flow of blood in the DSMC. Blood flow is the motion of blood through the human body. The deceleration of blood flow is resistance. Blood applies a force on the veins and vessels, which becomes blood pressure. In this study, the pulse pressure was used, which is approximately 120 to 80 Pa in smaller varicose veins [2,46].

6.2. Dean Number The Dean number was obtained for each curve of the DSMC [2]. DSMC curves with 7 mm radius of curvature had the Dean numbers 80.75, 74.25, 64.625, 56.5, 48.45, 40.375, 32.3, 24.225, and 16.15. Curves with 6 mm radius of curvature had the Dean numbers 87.21, 80.19, 69.795, 61.02, 52,326, 43.605, 34.884, 26.163, and 17.442. Curves with 5 mm radius of curvature had the Dean numbers 96.9, 89.1, 77.5, 67.8, 58.14, 48.45, 38.76, 29.07, and 19.38. These statistics demonstrate the direct relationship between Reynolds and Dean numbers. The Dean number decreases with the increase of curve radii. Consequently, there were no Dean vortices established, even in the curves of the DSMC [2].

6.3. The Role of Diameter and Viscosity of the Vein and Tissue Damage with the Flow of Blood Blood pressure decreases irregularly when it moves from arteries, capillaries, and veins to much smaller linked vessels [47]. The blood velocity varies as the blood moves from arteries to arterioles to capillaries, and vice versa. In veins, the velocity increases when blood goes back to the heart. The diameter of the blood vessels plays a dramatic role in the variation of flow rate and velocity [47,48]. The thickness of the blood affects its flowing capacity. This is because of erythrocytes (formed elements) and plasma proteins. Generally, the blood viscosity does not change over smaller distances and time periods. When viscosity changes, blood pressure changes [49,50]. The tissue damage presents as the damage of muscles, ligaments, and tendons due to more or less blood flow in smaller veins [2,12]. When the blood flow is normal, then no tissue damage will occur. That is why there is a need for a proper microdevice (DSMC) for implantation.

6.4. Implantable Devices in Humans The definition of the word “implant” is the insertion of an organ or device in the human body in a surgical process. The history of metal implants is very old, dating from 1875 to the present for pure silver, gold, and copper. Polymers and ceramics are now also used for implantation. Intraocular lenses, cochlear implants, brain implants, heart implants (pacemakers, heart valves, stents), joint implants, wearable artificial kidneys (WAKs), and artificial dermis are implantable devices for humans. Micromachines 2018, 9, 59 13 of 16

6.5. Comparison of ASMC and DSMC In first part of this study, we discussed our previous work (Afzal et al., 2017), wherein we developed the ASMC as an implant for varicose veins [2]. It was found that the flow rate and velocity was low because of the ascending nature of the ASMC. Now in this second phase of the study, the authors have found that the flow rate and velocity was much better due to the descending nature of the DSMC. Simulations were done with the same boundary conditions. Fabrication was done with the same process, and the same experimental technique was used in this study as well. All of the surgical problems with their severe effects were discussed previously [2]. The authors came to know that the ASMC cannot be implanted at those places where increased flow rate and velocity are required [35,51]. Therefore, the DSMC was simulated twice, fabricated, and tested experimentally to evaluate the possibility of implantation in human varicose veins. As a fluid, blood has high viscosity, and the flow was not complex in this microchannel. Therefore, neither channel showed Dean vortices, especially in the curved parts of the microchannel. The flow displayed a small Reynolds number. Therefore, the Dean numbers were also relatively low. Dean vortices are prominent in larger channels with less-viscous fluid and complex flow. This microchannel has straight parts between the curves and blood flowed steadily through them. However, the Dean number was calculated and found to be even lower than the Reynolds number.

6.6. Results Comparison The three major steps of this research show a clear agreement between simulation and experimental results. The MATLAB results were 1005.8 (0.1 nL/s) ﬂow rate and 11.8 cm/s velocity. The ANSYS results were 1015.3 (0.1 nL/s) and 12.19 cm/s velocity. Finally, the experimental results showed 995.3 (0.1 nL/s) ﬂow rate and 12.2 cm/s velocity. All of the results were at the same Reynolds number (323). The results are shown in Table3 below.

Table 3. The results of simulations and experiment.

MATLAB Results ANSYS Results Experimental Results Reynolds Number = 323 Reynolds Number = 323 Reynolds Number = 323 Flow Rate = 1001.0 (0.1 nL/s) Flow Rate = 1015.3 (0.1 nL/s) Flow Rate = 995.3 (0.1 nL/s) Velocity = 11.4 cm/s Velocity = 12.19 cm/s Velocity = 12.2 cm/s

Although there is no data for the DSMC with flow rate and velocity parameters for verification, these parameters have been measured with other channels [2,52]. The deviance in results can be explained by many factors, namely friction, pressure, and the ascending and descending nature of the microchannel. These features can modify the results. The authors have performed the current study with real and ideal conditions by changing the parameters. Fuzzy conditions were very close to ideal conditions and were found to be more accurate than ANSYS, because it provides thousands of infinite values between 0 and 1, and is therefore more reliable. Fuzzy controllers have been used in many appliances, such as blood pressure apparatuses, glucometers, washing machines, dryers, air conditioners, etc. ANSYS has a different environment than MATLAB Fuzzy logic. After the geometry was created in the design modeler, the meshing technique was used. In meshing, the mesh size is very important. Sometimes simulation is not done for every mesh size. Therefore, a proper mesh size must be created for the correct simulation. For the ANSYS results, the authors have taken twenty iterations for each simulation process. The testing was very close to the ideal and real environments. Therefore, the Fuzzy results were very close to the testing results. The testing was done many times at different ideal values of pressure. Micromachines 2018, 9, 59 14 of 16

7. Conclusions The objective of this work was to conduct MATLAB and ANSYS simulations, fabrication, and experimentation with the DSMC. Moreover, the DSMC (bioengineered vein) was used to determine the velocity and the flow rate of blood. The flow of blood was without Dean vortices. Additionally, a complete evaluation was performed comparing experiment and simulation. Silver was used because of its cheapness and biocompatibility. These bioengineered veins can be inserted in place of varicose veins for the sufficient flow of blood. This microdevice (DSMC) can be implanted at those places where the ASMC cannot be implanted. For this objective, the DSMC must be parted from the silver substrate for implant as the bioengineered vein. DSMCs of various designs and dimensions can also be prepared as required. The present study has some limitations. The DSMC was restricted for single-phase streamline flow. In this study, valves were neglected and the natural elasticity was present in the veins because of the very small size of the DSMC. The final restriction in this study was the silver material. We will use polymer materials for the fabrication of ASMCs and DSMCs in the future.

Author Contributions: Muhammad Javaid Afzal, Shahzadi Tayyaba, Muhammad Waseem Ashraf, M. Khalid Hossain, and Nitin Afzulpurkar participated/helped in one/more tasks of this work, including designing of device, simulation, fabrication, conceiving and designing the experiments, performing the experiments, contributing reagents/materials/analysis tools, and writing the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

References

1. Anwar, M.A.; Adesina-Georgiadis, K.N.; Spagou, K.; Vorkas, P.A.; Li, J.V.; Shalhoub, J.; Holmes, E.; Davies, A.H. A comprehensive characterisation of the metabolic profile of varicose veins; implications in elaborating plausible cellular pathways for disease pathogenesis. Sci. Rep. 2017, 7, 2989. [CrossRef] [PubMed] 2. Afzal, M.J.; Tayyaba, S.; Ashraf, M.W.; Hossain, M.K.; Uddin, M.J.; Afzulpurkar, N. Simulation, fabrication and analysis of silver based ascending sinusoidal microchannel (ASMC) for implant of varicose veins. Micromachines 2017, 8, 278. [CrossRef] 3. Hirai, M.; Naiki, K.; Nakayama, R. Prevalence and risk factors of varicose veins in Japanese women. Angiology 1990, 41, 228–232. [CrossRef][PubMed] 4. Sansilvestri-Morel, P.; Rupin, A.; Badier-Commander, C.; Kern, P.; Fabiani, J.; Verbeuren, T.J.; Vanhoutte, P.M. Imbalance in the synthesis of collagen type I and collagen type III in smooth muscle cells derived from human varicose veins. J. Vasc. Res. 2001, 38, 560–568. [CrossRef][PubMed] 5. Tessari, L.; Cavezzi, A.; Frullini, A. Preliminary experience with a new sclerosing foam in the treatment of varicose veins. Dermatol. Surg. 2001, 27, 58–60. [PubMed] 6. Blomgren, L.; Johansson, G.; Dahlberg-Åkerman, A.; Norén, A.; Brundin, C.; Nordström, E.; Bergqvist, D. Recurrent varicose veins: Incidence, risk factors and groin anatomy. Eur. J. Vasc. Endovasc. Surg. 2004, 27, 269–274. [CrossRef][PubMed] 7. Lawaetz, M.; Serup, J.; Lawaetz, B.; Bjoern, L.; Blemings, A.; Eklof, B.; Rasmussen, L. Comparison of endovenous radiofrequency ablation, laser ablation, foam sclerotherapy and surgical stripping for great saphenous varicose veins. Extended 5-year follow-up of a RCT. Int. Angiol. 2017, 53, e14. [CrossRef] 8. Belcaro, G.; Dugall, M.; Luzzi, R.; Corsi, M.; Ledda, A.; Ricci, A.; Pellegrini, L.; Cesarone, M.R.; Hosoi, M.; Errichi, B.M. Management of varicose veins and chronic venous insufficiency in a comparative registry with nine venoactive products in comparison with stockings. Int. J. Angiol. 2017, 26, 170–178. [PubMed] 9. Dabbs, E.; Nemchand, J.L.; Whiteley, M.S. Suprapubic varicose vein formation during pregnancy following pre-pregnancy pelvic vein embolisation with coils, without any residual pelvic venous reflux or obstruction. SAGE Open Med. Case Rep. 2017, 5, 2050313X17724712. [CrossRef][PubMed] 10. Bothra, N.; Panda, L.; Sheth, J.; Tripathy, D. Role of intralesional bleomycin sclerotherapy as the sole or adjunct treatment of superficial ocular adnexal lymphatic malformations. Eye 2017, 32, 152–155. [CrossRef] [PubMed] 11. Saleh, M.S. Duplex ultrasound guided catheter directed foam sclerotherapy for treatment of axial varicose veins of the lower limbs and its preliminary results. Int. J. Surg. Res. 2017, 6, 1–4. Micromachines 2018, 9, 59 15 of 16

12. Pires, M.F.B.; Nogueira, R.F.; Navarro, T.P. Chronic Venous Disease and Varicose Veins, in Vascular Diseases for the Non-Specialist; Springer: Berlin, Germany, 2017; pp. 167–181. 13. Rao, S.V.S.; Datta, A.S.; Anvesh, D. Spectrum of chronic venous insufficiency of lower limbs-A katuri perspective. J. Evid. Based Med. Healthc. 2017, 4, 1246–1253. 14. Argyriou, C.; Papasideris, C.; Antoniou, G.A.; Georgakarakos, E.; Papanas, N.; Lazarides, M.K.; Georgiadis, G.S. The effectiveness of various interventions versus standard stripping in patients with varicose veins in terms of quality of life. Phlebology 2017.[CrossRef][PubMed] 15. Hager, E.S.; Ozvath, K.J.; Dillavou, E.D. Evidence summary of combined saphenous ablation and treatment of varicosities versus staged phlebectomy. J. Vasc. Surg. Venous Lymphat. Disord. 2017, 5, 134–137. [CrossRef] [PubMed] 16. Zafarghandi, M.R.; Farsavian, H.; Davoudi, M.; Farsavian, A.A. Outcome of ultrasonography-guided foam sclerotherapy versus stab avulsion ambulatory phlebectomy in the treatment of varicosis in small veins of the leg: A single blinded randomized clinical trial. Iran. J. Radiol. 2017, in press. [CrossRef] 17. Rajam, V.; Kathaperumal, K.D.A.; Hemant, U.; Rajavelu, N. Study of clinical outcomes of subfascial perforator ligation surgery in perforator incompetence. J. Evid. Based Med. Healthc. 2017, 4, 810–815. [CrossRef] [PubMed] 18. Lin, Y.-N.; Hsieh, T.-Y.; Huang, S.-H.; Liu, C.-M.; Chang, K.-P.; Lin, S.-D. Management of venous ulcers according to their anatomical relationship with varicose veins. Phlebology 2017, 33, 44–52. [CrossRef] [PubMed] 19. Kumar, S.P.; Ramesh, R.; Aravind, T. Analysis of different size microchannel through particle tracing for biomolecule separation. J. Comput. Theor. Nanosci. 2017, 14, 3351–3355. [CrossRef] 20. Huang, L.; Zhao, P.; Bian, S.; Shi, G.; Liu, P.; Zong, S.; Wang, W. A novel bioMEMS device for efficient on-chip single cell loading and 3D rotation. In Proceedings of the 2017 IEEE 30th International Conference on Micro Electro Mechanical Systems (MEMS), Las Vegas, NV, USA, 22–26 January 2017. 21. Wang, S.-L.; Fan, S.-K. DNA stretching in surfactant-stabilized microchannel. In Proceedings of the 2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS), Kaohsiung, Taiwan, 18–22 June 2017. 22. Faustino, V.; Catarino, S.O.; Lima, R.; Minas, G. Biomedical microfluidic devices by using low-cost fabrication techniques: A review. J. Biomech. 2016, 49, 2280–2292. [CrossRef][PubMed] 23. Hu, W.; Ohta, A.T. Editorial for the Special Issue on Microdevices and Microsystems for Cell Manipulation; Multidisciplinary Digital Publishing Institute: Basel, Switzerland, 2017. 24. Birch, C.; Landers, J.P. Electrode materials in microfluidic systems for the processing and separation of DNA: A mini review. Micromachines 2017, 8, 76. [CrossRef] 25. Pinto, E.; Faustino, V.; Rodrigues, R.O.; Pinho, D.; Garcia, V.; Miranda, J.M.; Lima, R. A rapid and low-cost nonlithographic method to fabricate biomedical microdevices for blood flow analysis. Micromachines 2014, 6, 121–135. [CrossRef] 26. Sundell, G.; Dahlin, C.; Andersson, M.; Thuvander, M. The bone-implant interface of dental implants in humans on the atomic scale. Acta Biomater. 2017, 48, 445–450. [CrossRef][PubMed] 27. Küçük, M.; Çömleko˘glu,M.E.; Zor, M. The effect of crown geometry on stress distribution of a single implant restoration: A finite element analysis. Turkiye Klinikleri J. Dent. Sci. 2010, 16, 136–141. 28. Dai, P.; Wang, B.; Bao, C.; Ju, Y. Constructing a computer model of the human eye based on tissue slice images. J. Biomed. Imaging 2010, 2010, 15. [CrossRef][PubMed] 29. Todd, C.; Naghdy, F. Virtual cochlear implant insertion for medical education. In Proceedings of the Eurohaptics Conference, 2005 and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems, Pisa, Italy, 18–20 March 2005. 30. Zhang, W.; Li, Z.; Gilles, M.; Wu, D. Mechanical simulation of neural electrode-brain tissue interface under various micromotion conditions. J. Med. Biol. Eng. 2014, 34, 386–392. [CrossRef] 31. Karanasiou, G.S.; Sakellarios, A.I.; Tripoliti, E.E.; Petrakis, E.G.M.; Zervakis, M.E.; Migliavacca, F.; Dubini, G.; Dordoni, E.; Michalis, L.K.; Fotiadis, D.I. Modeling stent deployment in realistic arterial segment geometries: The effect of the plaque composition. In Proceedings of the 2013 IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE), Chania, Greece, 10–13 November 2013. 32. Shah, Y.; Bhave, A.; Sonetha, V. Fatigue analysis of the knee joint. Procedia Comput. Sci. 2015, 45, 250–255. [CrossRef] Micromachines 2018, 9, 59 16 of 16

33. Kim, S.; Feinberg, B.; Kant, R.; Chui, B.; Goldman, K.; Park, J.; Moses, W.; Blaha, C.; Iqbal, Z.; Chow, C. Diffusive silicon nanopore membranes for hemodialysis applications. PLoS ONE 2016, 11, e0159526. [CrossRef][PubMed] 34. Zak, J.; Hadas, Z.; Dusek, D.; Pekarek, J.; Svatos, V.; Janak, L.; Prasek, J.; Hubalek, J. The charge push-through electronics design for fully implantable artificial cochlea powered by energy harvesting technologies. Microsyst. Technol. 2016, 22, 1709–1719. [CrossRef] 35. Baskurt, O.K.; Meiselman, H.J. Blood rheology and hemodynamics. In Seminars in Thrombosis and Hemostasis; Thieme Medical Publishers, Inc.: New York, NY, USA, 2003. 36. Skalak, R.; Keller, S.; Secomb, T. Mechanics of blood flow. J. Biomech. Eng. 1981, 103, 102–115. [CrossRef] [PubMed] 37. Zhang, J.; Zhang, P.; Fraser, K.H.; Griffith, B.P.; Wu, Z.J. Comparison of fluid dynamic numerical models for a clinical ventricular assist device and experimental validation. Artif. Organs 2013, 37, 380. [CrossRef] [PubMed] 38. Shih, T.-C.; Hsiao, H.-D.; Chen, P.-Y.; Tu, C.-Y.; Tseng, T.-I.; Ho, Y.-J. Study of pre-and post-stent implantation in the trachea using computational fluid dynamics. J. Med. Biol. Eng. 2014, 34, 150–156. [CrossRef] 39. Qian, Y.; Liu, J.L.; Itatani, K.; Miyaji, K.; Umezu, M. Computational hemodynamic analysis in congenital heart disease: Simulation of the Norwood procedure. Ann. Biomed. Eng. 2010, 38, 2302–2313. [CrossRef] [PubMed] 40. Heck, M.L.; Yen, A.; Snyder, T.A.; O'Rear, E.A.; Papavassiliou, D.V. Flow-field simulations and hemolysis estimates for the food and drug administration critical path initiative centrifugal blood pump. Artif. Organs 2017, 41, E129–E140. [CrossRef][PubMed] 41. Rahman, I.A. Computational fluid dynamics as a tool for testing functional and ecological hypotheses in fossil taxa. Palaeontology 2017.[CrossRef] 42. Cherng, W.-J.; Dong, Z.-S.; Chou, C.-C.; Yeh, C.-H.; Pan, Y.-H. Hydrodynamic simulation of an orbital shaking test for the degradation assessment of blood-contact biomedical coatings. Micromachines 2017, 8, 132. [CrossRef] 43. Elblbesy, M.A.; Hereba, A.T. Computation of the coefficients of the power law model for whole blood and their correlation with blood parameters. Appl. Phys. Res. 2016, 8.[CrossRef] 44. Chiam, Z.L.; Lee, P.S.; Singh, P.K.; Mou, N. Investigation of fluid flow and heat transfer in wavy micro-channels with alternating secondary branches. Int. J. Heat Mass Transf. 2016, 101, 1316–1330. [CrossRef] 45. Folch, A. Introduction to bioMEMS; CRC Press: Boca Raton, FL, USA, 2016. 46. Nicolaides, A.N.; Zukowski, A.J. The value of dynamic venous pressure measurements. World J. Surg. 1986, 10, 919–924. [CrossRef][PubMed] 47. Fung, Y.-C. Biomechanics: Circulation; Springer Science & Business Media: Berlin, Germany, 2013. 48. Smieško, V.; Kožík, J.; Doležel, S. Role of endothelium in the control of arterial diameter by blood flow. J. Vasc. Res. 1985, 22, 247–251. 49. Letcher, R.L.; Chien, S.; Pickering, T.G.; Sealey, J.E.; Laragh, J.H. Direct relationship between blood pressure and blood viscosity in normal and hypertensive subjects: Role of fibrinogen and concentration. Am. J. Med. 1981, 70, 1195–1202. [CrossRef] 50. Fu, G.-X.; J, M.; Han, L.-Z.; Xu, C.-Z.; Pan, F.-F.; Hu, T.-J.; Zhong, Y. Erythrocyte rheological properties but not whole blood and plasma viscosity are associated with severity of hypertension in older people. Zeitschrift für Gerontologie und Geriatrie 2017, 50, 233–238. [CrossRef][PubMed] 51. Anand, M.; Rajagopal, K.R. A short review of advances in the modelling of blood rheology and clot formation. Fluids 2017, 2, 35. [CrossRef] 52. Bento, D.; Sousa, L.; Yaginuma, T.; Garcia, V.; Lima, R.; Miranda, J.M. Microbubble moving in blood flow in microchannels: Effect on the cell-free layer and cell local concentration. Biomed. Microdevices 2017, 19, 6. [CrossRef][PubMed]

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).