nazishshahid@fccollege.edu.pk; An investigation of thixotropic parameter inﬂuence on blood ﬂow in a stenosed nshahid@princeton.edu Department of Mathematics, tapered vessel has been carried out by means of analytical and numerical methods. Forman Christian College, We have studied how variation of a parameter in a range [0, 1], chosen following the A Chartered University, Lahore, evolution of transient shear, ﬂows with time in this particular range and impacts the Pakistan Department of Mechanical and dynamics of an unsteady, non-Newtonian ﬂuid ﬂow. An approximation of a simpler Aerospace Engineering, Princeton dynamical system was approached with the help of a particular set of University, Princeton, USA non-dimensional variables. Unique representations of axial velocity, shear stress and ﬂow rate have been made such that their dependence on pressure gradient can be further analysed. Some factors that either impede the ﬂow or help to accelerate it in a narrow channel in addition to varying yield stress and thixotropic parameter have been numerically investigated. The purpose of the current investigation is also to decide whether the particular model parameter regulates the dynamics of ﬂow in a vessel diﬀerently from other known non-Newtonian models and what speciﬁc range or values of this parameter bring this model’s results to coincide with other models’ results Keywords: Thixotropy; Blood ﬂow; Tapering; Axial velocity; Pressure-gradient; Structural parameter 1 Introduction The understanding of vascular dynamics and mechanism of arterial blood rheology has been important not only for advancement of medical science but also to overcome the development of complexities caused by overlooking minute details that can potentially change the course of a system. The arterial malfunction and disturbance in blood ﬂow propagation caused by stenosis have been a subject of long-term investigation and has added to valuable material to smooth understanding and better projection of rather a com- plex scenario. The study of modelling of blood ﬂow through arterial stenosis by means of theoretical and experimental methods has been done to establish grounds for implanted vascular system. Over the course of time, many researchers have contributed to this area of investiga- tion. Young [1] and Young and Tsai [2] laid grounds for the study of dynamics of ﬂow through stenosed arteries and recorded results for steady ﬂow on the matter. An inves- tigation of ﬂow dynamics in a tubular channel on arterial stenosis with inclusion of time © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, pro- vided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. Shahid Boundary Value Problems (2018) 2018:84 Page 2 of 22 parameter was also done by Young [3]. These studies invited multi-faceted analyses [4– 17] of propagation of Newtonian ﬂuid through constricting channels including factors of magnetic ﬁeld, body acceleration and pulsatile nature of blood ﬂow. Deshpande et al. [18] gave a new dimension to this investigation by developing a scheme to study Newtonian ﬂuid ﬂow through a stenosis that can be described axisymmetrically. How approximation of Reynolds number depending upon particular geometric facet of ﬂow can alter the dy- namics was discussed analytically by Smith [19]. Due to non-Newtonian characteristics of blood, many investigations were carried out to encompass these characteristics in ﬂow modelling. In addition to inclusion of non- Newtonian behaviour of blood in propagation, structural limitations of stenosis were ac- commodated by considering various appropriate models such as power law, Herschel– Bulkley, Casson and Carreau models [20–33]. A study of blood rheology brings up thixotropic and viscoplastic nature of dense blood suspension, platelets, leucocytes, etc. These characteristics along with responses of blood cells to varying shear were analysed by Merill, Cokelet and Dintenfass [34–36]. Classiﬁcation of appropriate models to describe blood ﬂow through stenosis involving the aspect of particular structural aggregation in low-shear was done by Owens [37]. According to his experimental and theoretical results, non-Newtonian characteristics of blood were better projected by Herschel–Bulkley and Casson models. However, limitation of Casson model in a complete description of blood ﬂow dynamics was brought up by Blair and Spanner [38]. The use of Herschel–Bulkley model to include many physiological characteristics of blood ﬂow was adopted by Priyad- harshini and Ponalgusamy [39, 40]. The factors of timed movement of channel due to peristaltic ﬂow and tapering of the channel wall were studied by Mandal, Manton and Whitemore [41–43]. An elaborate analysis of thixotropic characteristic of blood was prepared [44, 45]by means of structural parameter, but Mewis and Wagner [46] studied the characteristics of yield stress and time-dependent viscosity by relating these with above structural pa- rameter. This parameter time evolution was discussed in deﬁning the characteristics of thixotropy.AstudybyApostolidisand Beris[47] reﬂected on suitability of Casson model to describe the properties of thixotropy and viscoplasticity for low-shear rate ﬂows, but its lack of encompassing the time-dependent viscosity as in colloidal blood suspension was already pointed out by Mewis [48]. The current investigation has also been inspired by an experimental study conducted by Apostolidis [47] in which he linked the characteristics of yield stress and thixotropy with a structural, time-evolving parameter. In addition to describing non-Newtonian character- istics of time-dependent viscosity of blood, this model’s limiting results can help to validate available results in history. Here, we have prepared a theoretical analysis of unsteady blood ﬂow though a stenosed artery with tapering described by a model such that this model’s structural parameter is linked with yield stress and shear thinning of ﬂuid in time. Follow- ing a recent analysis prepared by Apostolidis [49], we have chosen [0, 1] as the range of structural parameter, and over this range, we have recorded variation in dynamics of ﬂow. In addition to collecting analytical and numerical results regarding axial velocity, shear stress, ﬂow rate and ﬂow resistance with the help of chosen pressure gradient, we have pointed out a range of parameter variation that hints at our model’s results being closer to experimental results than the results obtained by Herschel–Bulkley model. Shahid Boundary Value Problems (2018) 2018:84 Page 3 of 22 Figure 1 Two-dimensional stenosed and tapering channel 2 Geometry of ﬂow in a tapered artery A cylindrical coordinate system (r, θ, z) has been chosen to study dynamics of blood ﬂow through an elastic tapered vessel with mild stenosis. We have considered z-axis to be in the direction of channel such that it is perpendicular to radius of channel, r to be in the direction of radius of a vessel (Fig. 1)and θ is taken along the circumferential direction. In order to model unsteady motion of a non-Newtonian ﬂuid, we have considered a structural parameter modelling that is thixotropic modelling for incompressible ﬂuid. The tapering of channel has been represented by an angle φ which is diﬀerent from circumferential angle. The following geometric representation of artery with stenosis has been considered [41]: γ sec φ(z–d) ⎪ m ⎨ ((m z + R )– (l –(z – d)))η ¯(t), for d ≤ z ≤ d + l , 0 2 0 0 0 2 2 –γ sin φ R(z, t)= 4 (1) (m z + R )η ¯(t), otherwise, where R(z, t) describes the radius of tapered artery. φ is taken as an angle of tapering where φ <0, φ >0 and φ = 0 represent converging tapering, diverging tapering and no tapering, respectively. Also, d, R , l , γ and m = tan φ denote the position of stenosis, constant ra- 0 0 m dius of non-tapered artery in the non-stenotic region, length of stenosis, height of stenosis at z = d + (no tapering) and slope of tapering, respectively. In the above geometry, η ¯(t)is deﬁned as –gωt η ¯(t)=1 – g cos(ωt)–1 e , where the constant g represents the amplitude of small oscillations and angular frequency is deﬁned as ω =2πf with f being the pulse frequency. 3 Mathematical formulation The description of two-dimensional, axisymmetric ﬂow has been made through the conti- nuity equation and the governing equations of momentum for r and z components. These equations are ∂u ∂u ∂u 1 ∂(rτ ) ∂(τ ) ∂p rr zr ρ + u + w =– + –,(2) ∂t ∂r ∂z r ∂r ∂z ∂r ∂w ∂w ∂w 1 ∂(rτ ) ∂(τ ) ∂p rz zz ρ + u + w =– + –,(3) ∂t ∂r ∂z r ∂r ∂z ∂z ∂u u ∂w + + =0, (4) ∂r r ∂z Shahid Boundary Value Problems (2018) 2018:84 Page 4 of 22 where u = u(r, z, t), w = w(r, z, t)and ρ represent radial component of velocity, axial com- ponent of velocity and density of incompressible ﬂuid, respectively. The constitutive equations are taken to be τ = λτ +(1– λ)k(–γ˙ ) ; τ > τ,0< λ <1, (5) y y where τ , γ˙ , τ , k and n denote shear stress, rate of deformation, yield stress, consistency index and ﬂow behaviour index, respectively, along with τ = |τ | =–τ . rz rz The time-dependent thixotropic model (5) describes the ﬂow of non-Newtonian ﬂu- ids. Particularly, those ﬂuids which are viscoplastic in nature and depend on deformation history for complete description of ﬂow dynamics. The phenomenon of resting state of ﬂuid under static condition and movement of particles under application of shear (change of viscosity) is completely enveloped in this model. This model encompasses the time- dependence variation of viscosity through the link of single structural parameter, λ.Also [50], γ˙ =0, τ ≤ τ (6) has been placed to ensure the continuation of ﬂow for our considered model (5). The boundary conditions chosen for our system are w(r, z, t)=0 at r = R(z, t); τ (r, z, t)=0 at r =0. (7) rz Following the analysis of mechanism in human beings by Burton [51], pressure gradient hasbeenconsideredinthe givenform ∂p – = A + A cos(ωt), t >0, (8) 0 1 ∂z where A represents the constant amplitude of pressure gradient and A helps to describe 0 1 systolic and diastolic pressure, being amplitude of pulsatile component. The following non-dimensional variables have been chosen: w u w t z p ∗ ∗ ∗ ∗ ∗ w = , u = , t = , z = , p = , w u l l p 0 0 0 R τ lτ l u l r 0 rz zz 0 ∗ ∗ ∗ τ = , τ = , t = , w = , r = , 0 0 rz zz μw μw w R R 0 0 0 0 0 d l t ω μlw R 0 0 0 ∗ ∗ ∗ ∗ d = , l = , ω = , p = , R = , 0 (9) l l 2π R m l γ ρR w Q m 0 0 ∗ ∗ m = , γ = , R = , Q = , R R μ w R 0 0 0 n–1 2 2 A R A R R τ k w 0 1 0 y 0 ∗ 0 ∗ 0 ∗ A = , A = , τ = , K = , 0 1 y μw μw μw μ R 0 0 0 0 where w and u are characteristic scales. 0 0 Shahid Boundary Value Problems (2018) 2018:84 Page 5 of 22 Simpliﬁcation of our system is reached using non-dimensional quantities (9), very small Reynolds number, R ,and R l, where l is the ﬁnite length of artery. Thus, we obtain (ignoring ) ∂p 1 ∂(rτ ) rz – = , (10) ∂z r ∂r ∂p = 0, (11) ∂r ∂w τ = λτ +(1– λ)K – , (12) ∂r ∂p – = A + A cos(2πωt), t > 0. (13) 0 1 ∂z And the boundary conditions are w(r, z, t)=0, r = R(z, t); τ (r, z, t)=0, r = 0. (14) rz Now the geometry of the wall will be presented as 4γ sec φ(z – d)(l –(z – d)) m 0 R(z, t)= (mz +1)– η(t), (15) for d ≤ z ≤ d + l ,where –2πgωt η(t)=1 – g cos(2πωt)–1 e . (16) 4 Analytical expressions of velocity, shear stress and ﬂow rate x = has been used to make a coordinate transformation, and we obtain from R(z,t) Eqs. (10), (11), (12)and (14) the following: ∂p 1 ∂(xτ ) xz – = , (17) ∂z xR(z, t) ∂x ∂p – = 0, (18) ∂x (1 – λ)K ∂w τ = λτ + – (19) R (z, t) ∂x with boundary conditions w(x, z, t)=0 at x =1; τ (x, z, t)=0 at x = 0. (20) xz We also have ∂w =0, 0 ≤ x ≤ R , (21) pc ∂x Shahid Boundary Value Problems (2018) 2018:84 Page 6 of 22 Figure 2 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =1, τ =0.4, K =1.6 where R is the radius of plug core region. pc With the help of Eqs. (17)and (18), we can write pressure as a function of only an axial coordinate, that is, p = p(z). (22) Solving Eq. (17)with(20) and (22), we obtain an expression of shear stress xR(z, t) ∂p τ = – . (23) xz 2 ∂z And the expression for wall shear stress (x =1) is R(z, t) ∂p τ = – . (24) ws 2 ∂z Solving Eq. (19)with(20) and (23), we get an expression for axial velocity nR(z, t) w(x, z, t)= (n +1)(M +2λτ )(2K(1 – λ)) n+1 n+1 × M – Mx +2λτ (x –1) , (25) ∂p where M = R(z, t)(– )–2λτ and R ≤ x ≤ R(z, t). y pc ∂z And the velocity in the plug core region is nR(z, t) n+1 w (x, z, t)= M (26) pc (n +1)(M +2λτ )(2K(1 – λ)) 2λτ for 0 < x ≤ R and R = . pc pc –∂p R(z,t) ∂z Shahid Boundary Value Problems (2018) 2018:84 Page 7 of 22 Figure 3 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =3, τ =0.4, K =1.6 Figure 4 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =5, τ =0.4, K =1.6 Volume ﬂow rate is deﬁned as r=R(z,t) Q =2π rw(r, z, t) dr (27) r=0 which in non-dimensional form (ignoring ∗)can be writtenas r=R(z,t) Q(z, t)=2π rw(r, z, t) dr. (28) r=0 Equation (28)interms of x coordinate is Q(z, t)=2πR (z, t) xw(x, z, t) dx. (29) 0 Shahid Boundary Value Problems (2018) 2018:84 Page 8 of 22 Figure 5 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =7, τ =0.4, K =1.6 Figure 6 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =9, τ =0.4, K =1.6 Equation (29) can be simpliﬁed using Eqs. (25)and (26). Thus, we obtain πnR (z, t) Q(z, t)= 2 3 (2n +3n + 1)(3n +1)(M +2λτ ) (2K(1 – λ)) 3n+1 × (n + 1)(2n +1)M 2n+1 +4λτ (n + 1)(3n +1)M n+1 2 2 +4λ τ (2n + 1)(3n +1)M , (30) ∂p where M = R(z, t)(– )–2λτ . ∂z Shahid Boundary Value Problems (2018) 2018:84 Page 9 of 22 Figure 7 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =11, τ =0.4, K =1.6 Figure 8 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =13, τ =0.4, K =1.6 For a given time, resistance to ﬂow can be obtained using ∂p (– ) ∂z = dz (31) with the help of Eqs. (13)and (30). Table 1 has been constructed to get an estimate of the values of axial velocity corre- sponding to λ-variation for converging tapering at a given position of stenosis and time. Shahid Boundary Value Problems (2018) 2018:84 Page 10 of 22 Table 1 Values of axial velocity w(x, z, t; λ) resulting from Eq. (25) corresponding to λ-values for φ =–0.1, t =0.45 and z =28 x 0.6 0.7 0.8 0.9 1 w(x, z, t; 0) 1.071 0.879 0.639 0.347 0 w(x, z, t; 0.1) 1.242 1.020 0.742 0.404 0 w(x, z, t; 0.2) 1.467 1.206 0.879 0.478 0 w(x, z, t; 0.3) 1.776 1.462 1.066 0.581 0 w(x, z, t; 0.4) 2.220 1.829 1.335 0.728 0 w(x, z, t; 0.5) 2.900 2.392 1.747 0.953 0 w(x, z, t; 0.6) 4.037 3.334 2.437 1.331 0 w(x, z, t; 0.7) 6.217 5.138 3.760 2.055 0 w(x, z, t; 0.8) 11.507 9.521 6.974 3.815 0 w(x, z, t; 0.9) 33.402 27.669 20.286 11.109 0 Figure 9 Shear stress vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =15, τ =0.4, K =1.6 5 Discussion In order to get validation for results corresponding to approximation of our modelling parameter, we have considered the following numerical values [41]: γ =0.2, l = 16, d = 20, l = 50, ω =6, g =0.1, m 0 n = 0.639, R =0.8. In Figs. 2–9, time-dependent shear stress has been plotted against radial distances at a given position of stenosis, z = 28, and varying time in the range t ∈ [1, 15]. These graphs show consistent increase in shear stress such that it reaches its maximum value on the boundary wall (x = 1). Also it is noted that shear stress is higher for the case of diverging tapering in comparison to the cases of converging and no tapering. In these images, ob- serving the wall shear stress, τ (x, z, t)(x = 1) (say for diverging tapering) data points show ws that shear stress decreases initially (t ∈ [1, 5]), starts increasing (t ∈ (5, 9]), decreases again (t ∈ (9, 15]) and the cycle goes on, concluding that shear stress varies in an oscillating pat- tern. The oscillations in shear stress correspond to relaxing and constricting movement of a vessel with change in time. Shahid Boundary Value Problems (2018) 2018:84 Page 11 of 22 Figure 10 Wall shear stress vs time for φ = –0.1, 0, 0.1 at z =28, τ =0.4, K =1.6 Figure 11 Axial velocity vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =0.45, τ =0.4, K =1.6, λ =0.7 A clear image of oscillating pattern of wall shear stress variation in response to change in time has also been presented in Fig. 10 for the cases of converging, diverging and no- tapering. Figures 11–13 represent variation in axial velocity corresponding to changes in near-wall radial distances. It is observed that the axial velocity continues to decrease in such a way that it reaches zero on the wall vessel (x = 1), satisfying the no-slip bound- ary condition. It is also noted that the magnitude of axial velocity for diverging tapering is higher than that for the cases of converging and no-tapering. It is due to the fact that diverged opening in the neighbourhood of stenosis provides a way for ﬂuid to propagate with higher speed, comparatively. An analysis of axial velocity dependence on thixotropic parameter λ was also made through these graphs. It shows that the axial velocity decreases for decreasing values of λ. Thus, in a theoretical scheme, the higher values of λ can play a Shahid Boundary Value Problems (2018) 2018:84 Page 12 of 22 Figure 12 Axial velocity vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =0.45, τ =0.4, K =1.6, λ =0.5 Figure 13 Axial velocity vs radial distances for φ = –0.1, 0, 0.1 at z =28, t =0.45, τ =0.4, K =1.6, λ =0.1 role in increasing the magnitude of axial velocity that can be used in further implementa- tion of model in the construction of an implanted vascular system. We have made a comparison of axial velocity proﬁles in Figs. 14–16 for power law ﬂuid, Newtonian ﬂuid and thixotropic ﬂuid (for some diﬀerent values of λ). In response to changing radial distances, near the boundary wall, velocity is decreasing and reaching zero on the vessel wall. For all the cases of converging, diverging and no-tapering, we have made a note of increasing velocity for increasing values of λ. Interestingly, the velocity for power law ﬂuid attains values smaller than thixotropic velocity for λ = 0.1, indicating the phenomenological diﬀerences of both models in regards to describing the viscosity and viscoplasticity levels. The lower magnitude of velocity for power law ﬂuid also points to its lesser viscosity (in comparison to thixotropic ﬂuid for λ = 0.1) that needed lesser pressure-gradient for ﬂow propagation, which resulted in higher magnitude of velocity Shahid Boundary Value Problems (2018) 2018:84 Page 13 of 22 Figure 14 Axial velocity vs radial distances (near wall) for φ =–0.1, λ = 0.1, 0.5, 0.7 at z =28, t =0.45, τ =0.4, K = 1.6, Power Law model (λ → 0) and Newtonian ﬂuid (λ → 0, K = 0.035, n =1) Figure 15 Axial velocity vs radial distances (near wall) for λ = 0.1, 0.5, 0.7 and φ =0 at z =28, t =0.45, τ =0.4, K = 1.6, power law model (λ → 0) and Newtonian ﬂuid (λ → 0, K = 0.035, n =1) for λ = 0.1 level ﬂuid. An observation of lowest proﬁles of Newtonian ﬂuid is also made in all Figs. 14–16, validating the lowest pressure gradient required for Newtonian ﬂuid ﬂow. The lowest-velocity-magnitude proﬁles for Newtonian ﬂuid is more apparent in di- verging tapering case (Fig. 16). The lowest magnitude of velocity for power law ﬂuid in comparison to thixotropic ﬂuid (λ = 0.1, 0.5, 0.7) velocity also corroborates the available results in non-Newtonian ﬂuid modelling [41]. It canbeseenthatvelocityfor allmodels attains higher values for diverging tapering in comparison to no-tapering and converging tapering, the latter being smallest in terms of magnitude. In Figs. 17–19, we have plotted ﬂow resistance against time for the case of converging tapering. It is observed that the resistance to ﬂow increases in the beginning of a cycle at the position of stenosis due to propagation of ﬂuid through constriction and then it starts Shahid Boundary Value Problems (2018) 2018:84 Page 14 of 22 Figure 16 Axial velocity vs radial distances (near wall) for φ =0.1, λ = 0.1, 0.5, 0.7 at z =28, t =0.45, τ =0.4, K = 1.6, power law model (λ → 0) and Newtonian ﬂuid (λ → 0, K = 0.035, n =1) Figure 17 Flow resistance vs time for φ =–0.1 at z =28, τ =0.4, K =1.6, λ =0.7 decreasing for the relaxation part of the cycle. The continuation of cyclic movement of ﬂow resistance with time leads to an oscillating pattern depicted in graphs. It is interesting to observe that resistance to ﬂow increases for smaller values of λ and decreases for larger values of λ. Figures 20–22 express the ﬂow rate tendency to change in response to varying pres- sure gradient for the cases of converging, diverging and no-tapering. It is interesting to note that the rate of increase in ﬂow rate for rising pressure-gradient is non-linear for thixotropic ﬂuid unlike the established results in history. However, the ﬂow rate proﬁle for converging tapering is almost linear. A direct relation between ﬂow rate and thixotropic parameter λ has also been observed here for the same values of pressure-gradient. Shahid Boundary Value Problems (2018) 2018:84 Page 15 of 22 Figure 18 Flow resistance vs time for φ =–0.1 at z =28, τ =0.4, K =1.6, λ =0.5 Figure 19 Flow resistance vs time for φ =–0.1 at z =28, τ =0.4, K =1.6, λ =0.1 In Figs. 23–25, we have investigated the response of axial velocity against radial dis- tances for varying yield stress τ and for the case of converging tapering. These graphs show that the axial velocity decreases for rising values of yield stress in corroboration with phenomenal results of higher-yield stress ﬂuid being subject to higher resistance in comparison to lower-yield stress ﬂuid. It is interesting to note that, for smaller values of λ (say 0.1 < λ < 0.5), not only the axial velocity curve mutual separation is decreasing, but also for very small values (say λ = 0.1) near the wall of a vessel, the proﬁles seem to be coinciding. A direct relation of axial velocity and parametric value of λ is also veriﬁed as in the case of one-value yield stress ﬂuid. The analysis of variation ﬂow rate with respect to time has been done through graphs. We have obtained the proﬁles for ﬂow rate at the position of stenosis, z = 28, and for the cases of converging, diverging and no-tapering. In Figs. 26–28,ﬂowratehasbeenobserved Shahid Boundary Value Problems (2018) 2018:84 Page 16 of 22 Figure 20 Flow rate vs pressure gradient for φ = –0.1, 0, 0.1 at z =28, t =0.45, τ =0.4, K =1.6, λ =0.7 Figure 21 Flow rate vs pressure gradient for φ = –0.1, 0, 0.1 at z =28, t =0.45, τ =0.4, K =1.6, λ =0.5 to follow an oscillating pattern with respect to time. It is also noted that ﬂow rate assumes higher magnitude for diverging tapering in comparison to no-tapering. Also, due to con- striction of the channel at the position of stenosis, z = 28, ﬂow rate for converging tapering assumes smallest magnitude with varying time. These ﬁgures also reﬂect on the inﬂuence of thixotropic parameter λ on ﬂow rate. It can be observed that ﬂow rate decreases for smaller values of λ. 6Conclusions The following conclusions have been reached regarding the study of propagation of blood through a stenosed channel with tapering. How a structural parameter and timed move- ment of vessel inﬂuence dynamics and validation of some of available results has also been Shahid Boundary Value Problems (2018) 2018:84 Page 17 of 22 Figure 22 Flow rate vs pressure gradient for φ = –0.1, 0, 0.1 at z =28, t =0.45, τ =0.4, K =1.6, λ =0.1 Figure 23 Axial velocity vs radial distances (near wall) for varying yield stress at z =28, t =0.45, K =1.6, φ =–0.1, λ =0.7 recorded here with the help of analytical and numerical analysis. These salient points are as follows: 1. At given stenosis position and time, shear stress continues to increase with increasing radial distances, attaining its maximum value on a boundary wall of the vessel. Shear stress assumes higher magnitudes for diverging tapering due to comparatively higher inﬂux of ﬂuid in a diverged part of the channel. 2. The oscillating movement of shear stress (or wall shear stress) with time owes its pattern to the nature of pressure gradient in particular and the wall movement of the vessel in general. 3. In a manner of verifying the no-slip boundary condition, the response of axial velocity was recorded for near-wall radial distance changes. In addition to Shahid Boundary Value Problems (2018) 2018:84 Page 18 of 22 Figure 24 Axial velocity vs radial distances (near wall) for varying yield stress at z =28, t =0.45, K =1.6, φ =–0.1, λ =0.5 Figure 25 Axial velocity vs radial distances (near wall) for varying yield stress at z =28, t =0.45, K =1.6, φ =–0.1, λ =0.1 continuous drop in axial velocity while approaching boundary wall, the velocity magnitude is higher for diverging tapering as ﬂuid endures lesser hindrance in its propagation in a widening channel. 4. The magnitude of axial velocity at a given radial distance drops for decreasing values of thixotropic parameter λ (0< λ <1). 5. The study of comparative proﬁles of axial velocity for Newtonian, power law and thixotropic ﬂuid (λ = 0.1, 0.5, 0.7) reﬂects on two interesting phenomena. The ﬁrst being the occurrence of lower proﬁle of axial velocity for power law ﬂuid among non-Newtonian ﬂuids, matching with available theoretical results and obtaining lowest-magnitude-velocity proﬁle for Newtonian ﬂuid being the second one. The ﬁrst fact describes that the thixotropic ﬂuid for λ =0.1 encounters more resistance Shahid Boundary Value Problems (2018) 2018:84 Page 19 of 22 Figure 26 Flow rate vs time for φ = –0.1, 0, 0.1 at z =28, τ =0.4, K =1.6, λ =0.7 Figure 27 Flow rate vs time for φ = –0.1, 0, 0.1 at z =28, τ =0.4, K =1.6, λ =0.5 in its propagation than power law and Newtonian ﬂuids. Also, axial velocity increases for increasing values of λ. 6. The comparison of axial velocity proﬁles for diﬀerent models here with theoretical and experimental values of axial velocity proﬁle for Herschel–Bulkley ﬂuid model [39] reﬂects on the possibility for the latter to coincide with thixotropic ﬂuid proﬁle for 0.6 ≤ λ ≤ 0.8. Thus, it would be interesting to further investigate ﬂow properties of thixotropic ﬂuid for 0.8 < λ <1, treating a thixotropic ﬂuid model diﬀerent from Herschel–Bulkley ﬂuid model. 7. For converging tapering, resistance to ﬂow follows an oscillating pattern with time in accordance with oscillating variation in pressure gradient. 8. The resistance to ﬂow decreases for larger values of λ, verifying the fact here that axial velocity increases for larger values of λ. Shahid Boundary Value Problems (2018) 2018:84 Page 20 of 22 Figure 28 Flow rate vs time for φ = –0.1, 0, 0.1 at z =28, τ =0.4, K =1.6, λ =0.1 9. Flow rate increases with increase in pressure gradient. This increase is represented by slight parabolic curves for diverging and no tapering unlike the available results for Newtonian and non-Newtonian ﬂuids. However, the increase in ﬂow rate with rising pressure gradient for converging tapering is almost linear. 10. Flow rate assumes higher values for diverging tapering in comparison to no-tapering and converging tapering, respectively. 11. Flow rate has a direct relation to parametric value λ in validation with the results here that ﬂow resistance increases for smaller λ-values and vice-versa. 12. For converging tapering, axial velocity decreases for increasing values of yield stress τ and its response to λ is observed to be direct. 13. As λ assumes values near zero, axial velocity response to varying yield stress gets considerably smaller. This phenomenon is apparent in axial velocity proﬁles for λ =0.1. 14. Owing to rise and drop of pressure gradient, ﬂow rate varies in oscillations with time, assuming a direct relation with λ. Acknowledgements The author thanks Dr. Howard Stone and Dr. Bhargav Rallabandi from the Department of Mechanical and Aerospace Engineering, Princeton University for their insightful discussions on the topic and Princeton University for providing a wonderful working atmosphere for completion of this project. Funding No funding was obtained or used for completion of this work. Availability of data and materials Not applicable. Competing interests The author declares that there are no competing interests in regards with the current article. Authors’ contributions This entire work has been completed by the author, Dr. Nazish Shahid. Analytical solutions were determined by her and matching simulations were completed by her as well as graphical analysis through graphs had also been prepared by her. The author read and approved the ﬁnal manuscript. 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Published: May 29, 2018
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