<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article">
 <front>
  <journal-meta>
   <journal-id journal-id-type="publisher-id">
    ojmsi
   </journal-id>
   <journal-title-group>
    <journal-title>
     Open Journal of Modelling and Simulation
    </journal-title>
   </journal-title-group>
   <issn pub-type="epub">
    2327-4018
   </issn>
   <issn publication-format="print">
    2327-4026
   </issn>
   <publisher>
    <publisher-name>
     Scientific Research Publishing
    </publisher-name>
   </publisher>
  </journal-meta>
  <article-meta>
   <article-id pub-id-type="doi">
    10.4236/ojmsi.2025.134010
   </article-id>
   <article-id pub-id-type="publisher-id">
    ojmsi-145271
   </article-id>
   <article-categories>
    <subj-group subj-group-type="heading">
     <subject>
      Articles
     </subject>
    </subj-group>
    <subj-group subj-group-type="Discipline-v2">
     <subject>
      Physics 
     </subject>
     <subject>
       Mathematics
     </subject>
    </subj-group>
   </article-categories>
   <title-group>
    Pulsatile Flow Hemodynamics in a Stenosed Artery for Newtonian and Non-Newtonian Rheological Models
   </title-group>
   <contrib-group>
    <contrib contrib-type="author" xlink:type="simple">
     <name name-style="western">
      <surname>
       Md. Jashim
      </surname>
      <given-names>
       Uddin
      </given-names>
     </name>
    </contrib>
   </contrib-group> 
   <aff id="affnull">
    <addr-line>
     aDepartment of Applied Mathematics, Noakhali Science and Technology University, Noakhali, Bangladesh
    </addr-line> 
   </aff> 
   <pub-date pub-type="epub">
    <day>
     29
    </day> 
    <month>
     08
    </month>
    <year>
     2025
    </year>
   </pub-date> 
   <volume>
    13
   </volume> 
   <issue>
    04
   </issue>
   <fpage>
    185
   </fpage>
   <lpage>
    195
   </lpage>
   <history>
    <date date-type="received">
     <day>
      15,
     </day>
     <month>
      July
     </month>
     <year>
      2025
     </year>
    </date>
    <date date-type="published">
     <day>
      26,
     </day>
     <month>
      July
     </month>
     <year>
      2025
     </year> 
    </date> 
    <date date-type="accepted">
     <day>
      26,
     </day>
     <month>
      August
     </month>
     <year>
      2025
     </year> 
    </date>
   </history>
   <permissions>
    <copyright-statement>
     © Copyright 2014 by authors and Scientific Research Publishing Inc. 
    </copyright-statement>
    <copyright-year>
     2014
    </copyright-year>
    <license>
     <license-p>
      This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/
     </license-p>
    </license>
   </permissions>
   <abstract>
    Atheromatous disease can cause a heart attack or stroke in humans. This present research aims to investigate the comparison between Newtonian and rheological models in terms of hemodynamic risk factors. A three-dimensional computational model has been considered here for 45%, 60%, and 75% stenoses. The COMSOL Multiphysics software has been used in fluid flow simulation to solve the governing equations. The comparison between Newtonian and non-Newtonian has been performed to predict the model’s suitability. Hemodynamic parameters such as time-averaged wall shear stress (TAWSS), oscillatory shearing index, and blood residence time show a lower disturbed flow regime for non-Newtonian fluid compared to Newtonian fluid. The TAWSS for 75% stenosis is increased by 54.84% and 37.18% to those of 45% and 60% stenoses. A suitable non-Newtonian model can be used in bioengineering fields.
   </abstract>
   <kwd-group> 
    <kwd>
     Pulsatile Flow
    </kwd> 
    <kwd>
      Stenosis
    </kwd> 
    <kwd>
      Hemodynamics
    </kwd> 
    <kwd>
      Recirculation
    </kwd> 
    <kwd>
      Non-Newtonian Rheological Model
    </kwd>
   </kwd-group>
  </article-meta>
 </front>
 <body>
  <sec id="s1">
   <title>1. Introduction</title>
   <p>One of the main causes of illness and death worldwide is cardiovascular disorder. Arterial blockage is a disorder in which plaque builds up in the arteries and causes them to narrow, leading to decreased blood flow <xref ref-type="bibr" rid="scirp.145271-1">
     [1]
    </xref>-<xref ref-type="bibr" rid="scirp.145271-5">
     [5]
    </xref>. Due to the blood flow’s straight connection to cardiovascular health, research on it via narrowed arteries has attracted a lot of attention. The aforementioned arteries have extremely complicated blood flow that is affected by a number of variables, including the stenosis’s shape, the blood’s characteristics, and the existence of disorder <xref ref-type="bibr" rid="scirp.145271-6">
     [6]
    </xref>-<xref ref-type="bibr" rid="scirp.145271-10">
     [10]
    </xref>. Customarily, blood is treated as a Newtonian fluid, presuming a uniform viscosity that does not change with shear rate. In actuality, though, blood behaves with non-Newtonian characteristics, changing viscosity in response to shear rate, especially in narrow lumens or in sick circumstances <xref ref-type="bibr" rid="scirp.145271-11">
     [11]
    </xref>-<xref ref-type="bibr" rid="scirp.145271-15">
     [15]
    </xref>.</p>
   <p>The evaluation of changes in hemodynamic risk factors across various viscosity models has made extensive use of computational fluid dynamics (CFD) simulations <xref ref-type="bibr" rid="scirp.145271-16">
     [16]
    </xref> <xref ref-type="bibr" rid="scirp.145271-17">
     [17]
    </xref>. Important hemodynamic risk factors that are essential for comprehending how blockage affects blood circulation include wall shear stress (WSS), time-averaged wall shear stress (TAWSS), oscillatory shear index (OSI), and relative residence time (RRT) <xref ref-type="bibr" rid="scirp.145271-18">
     [18]
    </xref>-<xref ref-type="bibr" rid="scirp.145271-20">
     [20]
    </xref>. This study seeks to examine the influences of the nature of Newtonian and non-Newtonian fluids on the hemodynamic flow properties within constricted vessels. Because of Newtonian fluids’ straightforwardness, they have been widely employed in the past years <xref ref-type="bibr" rid="scirp.145271-21">
     [21]
    </xref>-<xref ref-type="bibr" rid="scirp.145271-24">
     [24]
    </xref>. In order to better comprehend the types of flow, non-Newtonian model—specially, the Carreau model—has been suggested as a more factual description of the rheological characteristics of blood <xref ref-type="bibr" rid="scirp.145271-25">
     [25]
    </xref>-<xref ref-type="bibr" rid="scirp.145271-27">
     [27]
    </xref>.</p>
   <p>The stenosed geometry has been found to have an important impact on blood flow-related research. A significant volume of research has focused on comprehending blood circulation in arteries, in both normal and narrowed states. Past research shows that the Newtonian model is widely utilized because of its ease. In this present computational investigation, the study seeks to explore the impacts of the variational approach of Newtonian and non-Newtonian fluids on the hemodynamic flow behaviors in narrowed arteries. This study also intends to show the great impact of the severity of stenosis on flow fields.</p>
  </sec><sec id="s2">
   <title>2. Methodology Techniques</title>
   <sec id="s2_1">
    <title>2.1. Simulated Geometry</title>
    <p>A stenosed model of three-dimensional geometry (<xref ref-type="fig" rid="fig1">
      Figure 1
     </xref>) for 45%, 60%, and 75% stenoses has been considered here to investigate the pulsatile atherosclerotic hemodynamics in mimics blood flow. The directions of the horizontal and vertical axes are shown by the coordinates X and Y. The length of pre-stenosis is 3D and the post-stenosis is 10D. The parameter D indicates the artery diameter. The laminar and incompressible flow is assumed for the investigated trapezium model of stenosis.</p>
   </sec>
   <sec id="s2_2">
    <title>2.2. Governing Equations and Boundary Conditions</title>
    <p>The fluid flow simulations are governed by the continuity and Navier-Stokes equations, as given in the following way:</p>
    <p>The general continuity equation’s form for fluid flow is</p>
    <p>
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <mo>
         ∇ 
       </mo> 
       <mo>
         ⋅ 
       </mo> 
       <mstyle mathvariant="bold" mathsize="normal"> 
        <mi>
          v 
        </mi> 
       </mstyle> 
       <mo>
         = 
       </mo> 
       <mn>
         0 
       </mn> 
      </mrow> 
     </math> (1)</p>
    <p>The Navier-Stokes equations’ form is</p>
    <p>
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <mi>
         ρ 
       </mi> 
       <mrow> 
        <mo>
          ( 
        </mo> 
        <mrow> 
         <mfrac> 
          <mrow> 
           <mo>
             ∂ 
           </mo> 
           <mstyle mathvariant="bold" mathsize="normal"> 
            <mi>
              v 
            </mi> 
           </mstyle> 
          </mrow> 
          <mrow> 
           <mo>
             ∂ 
           </mo> 
           <mi>
             t 
           </mi> 
          </mrow> 
         </mfrac> 
         <mo>
           + 
         </mo> 
         <mrow> 
          <mo>
            ( 
          </mo> 
          <mrow> 
           <mo>
             ∇ 
           </mo> 
           <mo>
             ⋅ 
           </mo> 
           <mstyle mathvariant="bold" mathsize="normal"> 
            <mi>
              v 
            </mi> 
           </mstyle> 
          </mrow> 
          <mo>
            ) 
          </mo> 
         </mrow> 
         <mstyle mathvariant="bold" mathsize="normal"> 
          <mi>
            v 
          </mi> 
         </mstyle> 
        </mrow> 
        <mo>
          ) 
        </mo> 
       </mrow> 
       <mo>
         = 
       </mo> 
       <mo>
         ∇ 
       </mo> 
       <mo>
         ⋅ 
       </mo> 
       <mi>
         σ 
       </mi> 
      </mrow> 
     </math> (2)</p>
    <p>where 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mstyle mathvariant="bold" mathsize="normal"> 
       <mi>
         v 
       </mi> 
      </mstyle> 
     </math> is the velocity vector, t is the time, 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mi>
        ρ 
      </mi> 
     </math> indicates the density of the fluid, and p is the fluid pressure. The Cauchy stress tensor 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mi>
        σ 
      </mi> 
     </math> can be given as follows:</p>
    <p>
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <mo>
         − 
       </mo> 
       <mi>
         P 
       </mi> 
       <mi>
         I 
       </mi> 
       <mo>
         + 
       </mo> 
       <mi>
         μ 
       </mi> 
       <mrow> 
        <mo>
          ( 
        </mo> 
        <mrow> 
         <mo>
           ∇ 
         </mo> 
         <mstyle mathvariant="bold" mathsize="normal"> 
          <mi>
            v 
          </mi> 
         </mstyle> 
         <mo>
           + 
         </mo> 
         <msup> 
          <mrow> 
           <mrow> 
            <mo>
              ( 
            </mo> 
            <mrow> 
             <mo>
               ∇ 
             </mo> 
             <mstyle mathvariant="bold" mathsize="normal"> 
              <mi>
                v 
              </mi> 
             </mstyle> 
            </mrow> 
            <mo>
              ) 
            </mo> 
           </mrow> 
          </mrow> 
          <mtext>
            T 
          </mtext> 
         </msup> 
        </mrow> 
        <mo>
          ) 
        </mo> 
       </mrow> 
      </mrow> 
     </math></p>
    <fig id="fig1" position="float">
     <label>Figure 1</label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 1. The current simulation domain.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId27.jpeg?20250829014557" />
    </fig>
    <p>where 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mi>
        μ 
      </mi> 
     </math> presents the dynamic viscosity of the fluid, and 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mi>
        I 
      </mi> 
     </math> is the identity matrix. The non-Newtonian Carreau model is as follows:</p>
    <p>
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <mi>
         μ 
       </mi> 
       <mo>
         = 
       </mo> 
       <msub> 
        <mi>
          μ 
        </mi> 
        <mrow> 
         <mi>
           inf 
         </mi> 
        </mrow> 
       </msub> 
       <mo>
         + 
       </mo> 
       <mrow> 
        <mo>
          ( 
        </mo> 
        <mrow> 
         <msub> 
          <mi>
            μ 
          </mi> 
          <mn>
            0 
          </mn> 
         </msub> 
         <mo>
           − 
         </mo> 
         <msub> 
          <mi>
            μ 
          </mi> 
          <mrow> 
           <mi>
             inf 
           </mi> 
          </mrow> 
         </msub> 
        </mrow> 
        <mo>
          ) 
        </mo> 
       </mrow> 
       <msup> 
        <mrow> 
         <mrow> 
          <mo>
            [ 
          </mo> 
          <mrow> 
           <mn>
             1 
           </mn> 
           <mo>
             + 
           </mo> 
           <msup> 
            <mrow> 
             <mrow> 
              <mo>
                ( 
              </mo> 
              <mrow> 
               <mi>
                 λ 
               </mi> 
               <mfrac> 
                <mrow> 
                 <mo>
                   ∂ 
                 </mo> 
                 <mi>
                   γ 
                 </mi> 
                </mrow> 
                <mrow> 
                 <mo>
                   ∂ 
                 </mo> 
                 <mi>
                   t 
                 </mi> 
                </mrow> 
               </mfrac> 
              </mrow> 
              <mo>
                ) 
              </mo> 
             </mrow> 
            </mrow> 
            <mn>
              2 
            </mn> 
           </msup> 
          </mrow> 
          <mo>
            ] 
          </mo> 
         </mrow> 
        </mrow> 
        <mrow> 
         <mfrac> 
          <mrow> 
           <mi>
             n 
           </mi> 
           <mo>
             − 
           </mo> 
           <mn>
             1 
           </mn> 
          </mrow> 
          <mn>
            2 
          </mn> 
         </mfrac> 
        </mrow> 
       </msup> 
      </mrow> 
     </math></p>
    <p>where infinite shear rate 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <msub> 
        <mi>
          μ 
        </mi> 
        <mrow> 
         <mi>
           inf 
         </mi> 
        </mrow> 
       </msub> 
       <mo>
         = 
       </mo> 
       <mn>
         0.00345 
       </mn> 
      </mrow> 
     </math>, zero shear rate 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <msub> 
        <mi>
          μ 
        </mi> 
        <mn>
          0 
        </mn> 
       </msub> 
       <mo>
         = 
       </mo> 
       <mn>
         0.056 
       </mn> 
      </mrow> 
     </math>, time constant 
     <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"> <mrow> 
       <mi>
         λ 
       </mi> 
       <mo>
         = 
       </mo> 
       <mn>
         3.313 
       </mn> 
      </mrow> 
     </math>, and index n = 0.3568. The pulse given in <xref ref-type="fig" rid="fig2">
      Figure 2
     </xref> presents the</p>
    <fig id="fig2" position="float">
     <label>Figure 2</label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 2. Time-dependent input flowrate pulse.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId40.jpeg?20250829014557" />
    </fig>
    <p>inlet flowrate pulse for the present computational fluid model <xref ref-type="bibr" rid="scirp.145271-28">
      [28]
     </xref>. A no-slip boundary condition is applied at the wall, while the outlet pressure remains static. The pulsatile flow exhibits a waveform of 4.3 ± 2.6 ml with a duration of 0.345 s, produced by a frequency of 2.9 Hz. The fluid has a density of 755 kg/m<sup>3</sup> and a viscosity of 0.00143 N∙s/m<sup>2</sup>. The inlet pulse is a sinusoidal wave with an average Reynolds number of 575 and a peak value of 930 <xref ref-type="bibr" rid="scirp.145271-29">
      [29]
     </xref>.</p>
   </sec>
   <sec id="s2_3">
    <title>2.3. Numerical Methods</title>
    <p>Newtonian and non-Newtonian rheological models have been assumed for incompressible, laminar and time-dependent flow. The finite element approach in the COMSOL Multiphysics software has been activated for numerical computational techniques. Time-dependent solver takes the fully coupled, advanced and iterative approach for the execution of pulsatile blood flow simulation. Different mesh densities, namely 36,405, 80,542, 107,835, 206,940, and 307,560, have been selected to decide the appropriate mesh for the prediction of outcomes. The mesh elements of 206,940 are appropriate to acquire the results because the last two elements, 206,940 and 307,560, carry approximately the same TAWSS magnitudes. <xref ref-type="fig" rid="fig3(a)">
      Figure 3(a)
     </xref> shows the grid, and <xref ref-type="fig" rid="fig3(b)">
      Figure 3(b)
     </xref> presents the grid test in TAWSS. In unsteady flow, the second cycle has been taken to get the simulated results.</p>
    <fig id="fig3" position="float">
     <label>Figure 3</label>
     <caption>
      <title>(a)<p class="imgGroupCss_v"><img class=" imgMarkCss lazy" data-original="https://html.scirp.org/file/2860327-rId42.jpeg?20250829014557" /></p>(b)<xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 3. (a) Grid resolution and (b) grid independence test in TAWSS.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId41.jpeg?20250829014557" />
    </fig>
   </sec>
   <sec id="s2_4">
    <title>2.4. Method Validation</title>
    <p>In the present research, axial velocity through the radial direction is employed to contrast the results with those of Lee et al. , aiming to verify and affirm the precision and reliability of the computational evaluation. The axial velocity is taken as a post-stenotic distance of 21.5 mm at t = 0.1725 sec. Moreover, as shown in <xref ref-type="fig" rid="fig4">
      Figure 4
     </xref>, the comparison of the currently predicted axial velocity results with those obtained by Lee et al. demonstrates significant agreement.</p>
    <fig id="fig4" position="float">
     <label>Figure 4</label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 4. Axial velocity through radial direction is validated with Lee et al. <xref ref-type="bibr" rid="scirp.145271-30">
        [30]
       </xref>.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId43.jpeg?20250829014558" />
    </fig>
   </sec>
  </sec><sec id="s3">
   <title>3. Results and Discussion</title>
   <sec id="s3_1">
    <title>3.1. Hemodynamic Biomarker Factors’ Impact</title>
    <p>
     <xref ref-type="bibr" rid="scirp.145271-"></xref>WSS is the key hemodynamic factor that signifies the level of risk for patients. Elevated WSS is associated with the development of susceptible plaques, whereas diminished WSS may result in intimal thickening. <xref ref-type="fig" rid="fig5">
      Figure 5
     </xref> illustrates the distributions of WSS with noticeable variations of Newtonian and non-Newtonian fluids at various significant time points (t = 0.08623 s, t = 0.1725 s, t = 0.25875 s, t = 0.345 s). Since the flow directly affects the stenosis’s inlet region, the WSS peaks there, WSS then abruptly increases, remains somewhat elevated throughout the constricted region, and then decreases from the terminating regions. While both fluids result in elevated WSS close to the narrowed portion, the rheological non-Newtonian model generates a greater WSS at every site except the closely post-stenotic part. The Newtonian fluid exhibits a higher recirculation in the area immediately downstream of the blockage than the rheological fluid. The arterial wall displays time-averaged markers such as TAWSS, OSI, and RRT, serving as indicators of endothelial deterioration (<xref ref-type="fig" rid="figFigures 6(a)-(c)">
      Figures 6(a)-(c)
     </xref>). The top values of OSI and RRT signify the reattachment locations, which align with zero for TAWSS, and Newtonian fluid gives a more disturbed flow area.</p>
   </sec>
   <sec id="s3_2">
    <title>3.2. Stenosis Severity’s Impact on Hemodynamics</title>
    <p>Without a doubt, the intensity or size significantly influences the flow area of the narrowed channels of blockage. To examine the impact of stenosis intensity, three</p>
    <fig id="fig5" position="float">
     <label>Figure 5</label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 5. WSS distributions at (t = 0.08625 s, 0.1725 s, 0.25875 s, and 0.345 s) for Newtonian and non-Newtonian fluids.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId44.jpeg?20250829014600" />
    </fig>
    <fig id="fig6" position="float">
     <label>Figure 6</label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 6. Distributions of (a) TAWSS, (b) OSI, and (c) RRT for Newtonian and non-Newtonian fluids.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId45.jpeg?20250829014600" />
    </fig>
    <p>distinct sizes, specifically 45%, 60%, and 75% (<xref ref-type="fig" rid="fig7(a)">
      Figure 7(a)
     </xref>), have been analyzed in terms of WSS. As the severity of the blockage deepens, the flow field diminishes, resulting in an increase in velocity, which significantly affects the WSS, leading to a peak in the WSS due to the acceleration of flow. The TAWSS for 75% stenosis rises by 54.84% and 37.18% compared to 45% and 60% stenoses, respectively. Finally, it may be concluded that the more vascular injury generates the more WSS. <xref ref-type="fig" rid="fig7(b)">
      Figure 7(b)
     </xref> presents the contours of WSS distributions for the various sizes of blockage severity. At the stenosis location, the flow area is reduced and experiences a maximum shearing stress. The higher blockage (75%) attains a maximum value of WSS compared to the lower blockages.</p>
    <fig id="fig7" position="float">
     <label>Figure 7</label>
     <caption>
      <title>(a)<p class="imgGroupCss_v"><img class=" imgMarkCss lazy" data-original="https://html.scirp.org/file/2860327-rId47.jpeg?20250829014600" /></p><xref ref-type="bibr" rid="scirp.145271-"></xref>(b)<xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 7. (a) Distribution of TAWSS and (b) WSS contours for 45 %, 60%, and 75%.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId46.jpeg?20250829014601" />
    </fig>
   </sec>
   <sec id="s3_3">
    <title>3.3. Pressure Contours Due to Newtonian and Non-Newtonian Fluids</title>
    <p>Pressure distributions for Newtonian and rheological models may vary greatly because of their different viscosities and responses to shear stress. The comparison of pressure contours between the two aforementioned models reveals a significant difference in <xref ref-type="fig" rid="fig8">
      Figure 8
     </xref>, in which the non-Newtonian model generates greater pressure. The artery’s initial higher pressure drops sharply at the blockage’s midpoint, followed by a gradual rise until the artery’s end, indicating a slight variation between the fluids. The lowest pressure is observed just downstream of the blockage, suggesting a condition favorable to the development of atherosclerosis.</p>
    <fig id="fig8" position="float">
     <label>Figure 8</label>
     <caption>
      <title>
       <xref ref-type="bibr" rid="scirp.145271-"></xref>Figure 8. Pressure contour distributions for Newtonian and non-Newtonian fluids.</title>
     </caption>
     <graphic mimetype="image" position="float" xlink:type="simple" xlink:href="https://html.scirp.org/file/2860327-rId48.jpeg?20250829014601" />
    </fig>
   </sec>
  </sec><sec id="s4">
   <title>
    <xref ref-type="bibr" rid="scirp.145271-"></xref>4. Conclusions</title>
   <p>Atherosclerosis is associated with blood flow characteristics and the intensity of constriction in the arterial lumen and the walls of the arterial geometry, making it essential to examine blood circulation in a diseased arterial geometry. In order to demonstrate the laminar, pulsating, and incompressible blood flow in an injured artery, the current work used CFD modeling. The Newtonian and Carreau models of blood have both been taken into consideration in this study. The code of COMSOL Multiphysics is validated with literature findings. The applicability of the model has been predicted by comparing Newtonian and non-Newtonian models. When comparing non-Newtonian fluids to Newtonian fluids, hemodynamic metrics, including TAWSS, OSI, and RRT, reveal a reduced disturbed flow regime. Compared to 45% and 60% stenosis, the TAWSS for 75% stenosis is raised by 54.84% and 37.18%, respectively. An appropriate non-Newtonian model can be applied in the field of bioengineering.</p>
   <p>In the future, the rigid wall geometry assumptions can be extended to a realistic patient-specific fluid-structure interaction model.</p>
  </sec>
 </body><back>
  <ref-list>
   <title>References</title>
   <ref id="scirp.145271-ref1">
    <label>1</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Akbar, S. and Shah, S.R. (2024) Mathematical Modeling of Blood Flow Dynamics in the Cardiovascular System: Assumptions, Considerations, and Simulation Results. Journal of Current Medical Research and Opinion, 7, 2216-2225.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref2">
    <label>2</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Anamika Shah, S.R. and Singh, A. (2017) Mathematical and Computational Study of Blood Flow through Diseased Artery. International Journal of Computer Science, 5, 1-6.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref3">
    <label>3</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Dutt, M.G., Shah, S.R. and Arya, S. (2024) Optimizing Cardiovascular Health: Ayurvedic Insights into Blood Flow through Normal and Stenosed Arteries. International Journal of AYUSH, 13, 18-35.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref4">
    <label>4</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Udupa, M.C., Saha, S. and Natarajan, S. (2025) Study of Blood Flow Patterns in a Stenosed Artery through the Combined Effect of Body Acceleration and Generalized Womersley Solution. Scientific Reports, 15, Article No. 1845. &gt;https://doi.org/10.1038/s41598-025-85566-2
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref5">
    <label>5</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Shah, S.R., Siddiqui, S.U. and Singh, A. (2015) Mathematical Modelling and Analysis of Blood Flow through Diseased Blood Vessels. International Journal of Engineering and Management Research, 5, 366-372.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref6">
    <label>6</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Singh, S. and Shah, R.R. (2010) A Numerical Model for the Effect of Stenosis Shape on Blood Flow through an Artery Using Power-Law Fluid. Advance in Applied Science Research, 1, 66-73.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref7">
    <label>7</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Shah, S.R. and Kumar, R. (2017) A Mathematical Approach to Study the Blood Flow through Tapered Stenosed Artery with the Suspension of Nanoparticles. DEStech Transactions on Engineering and Technology Research, 1, 1-6. &gt;https://doi.org/10.12783/dtetr/amsm2017/14809
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref8">
    <label>8</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Shah, S.R. (2013) A Mathematical Model for the Analysis of Blood Flow through Diseased Blood Vessels under the Influence of Porous Parameter. Journal of Biosciences and Technology, 4, 534-541.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref9">
    <label>9</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Singh, A. and Shah, S.R. (2024) Influence of Transverse Magnetic Field on Steady Blood Flow in a Stenosed Artery: Numerical and Analytical Insights. International Journal of Mathematical Archive, 15, 1-10.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref10">
    <label>10</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Kumar, V. and Shah, S.R. (2022) A Mathematical Study for Heat Transfer Phenomenological Processes in Human Skin. International Journal of Mechanical Engineering, 7, 683-692.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref11">
    <label>11</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Sapna, K. and Siddiqui, S.U. (2004) Study of Blood Flow through a Stenosed Capillary Using Casson’s Fluid Model. Ultra Science: International Journal of Physical Sciences, 16, 133-142.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref12">
    <label>12</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Sapna, S. (2009) Analysis of Non-Newtonian Fluid Flow in a Stenosed Artery. Inter-national Journal of Physical Sciences, 4, 663-671.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref13">
    <label>13</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wu, H., Wang, H., Wang, H., Zhang, Y. and Guo, L. (2025) Numerical Simulation of Flow and Heat Transfer Characteristics in the Extrusion and Stretching Process of Non-Newtonian Fluid in Microchannel. Chemical Engineering Science, 306, Article ID: 121252. &gt;https://doi.org/10.1016/j.ces.2025.121252
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref14">
    <label>14</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wajihah, S.A. and Sankar, D.S. (2023) A Review on Non-Newtonian Fluid Models for Multi-Layered Blood Rheology in Constricted Arteries. Archive of Applied Mechanics, 93, 1771-1796. &gt;https://doi.org/10.1007/s00419-023-02368-6
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref15">
    <label>15</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Eberhard, U., Seybold, H.J., Secchi, E., Jiménez-Martínez, J., Rühs, P.A., Ofner, A., et al. (2020) Mapping the Local Viscosity of Non-Newtonian Fluids Flowing through Disordered Porous Structures. Scientific Reports, 10, Article No. 11733. &gt;https://doi.org/10.1038/s41598-020-68545-7
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref16">
    <label>16</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Nader, E., Skinner, S., Romana, M., Fort, R., Lemonne, N., Guillot, N., et al. (2019) Blood Rheology: Key Parameters, Impact on Blood Flow, Role in Sickle Cell Disease and Effects of Exercise. Frontiers in Physiology, 10, Article 1329. &gt;https://doi.org/10.3389/fphys.2019.01329
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref17">
    <label>17</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wang, S., Wu, D., Li, G., Zhang, Z., Xiao, W., Li, R., et al. (2023) Deep Learning-Based Hemodynamic Prediction of Carotid Artery Stenosis before and after Surgical Treatments. Frontiers in Physiology, 13, Article 1094743. &gt;https://doi.org/10.3389/fphys.2022.1094743
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref18">
    <label>18</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Rahman, M.M., Hossain, M.A., Mamun, K. and Akhter, M.N. (2018) Comparative Study of Newtonian and Non-Newtonian Blood Flow through a Stenosed Carotid Artery. AIP Conference Proceedings, 1980, Article ID: 040017. &gt;https://doi.org/10.1063/1.5044327
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref19">
    <label>19</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Liu, H., Lan, L., Abrigo, J., Ip, H.L., Soo, Y., Zheng, D., et al. (2021) Comparison of Newtonian and Non-Newtonian Fluid Models in Blood Flow Simulation in Patients with Intracranial Arterial Stenosis. Frontiers in Physiology, 12, Article 718540. &gt;https://doi.org/10.3389/fphys.2021.718540
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref20">
    <label>20</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Wong, K.K.L., Wu, J., Liu, G., Huang, W. and Ghista, D.N. (2020) Coronary Arteries Hemodynamics: Effect of Arterial Geometry on Hemodynamic Parameters Causing Atherosclerosis. Medical&amp;Biological Engineering&amp;Computing, 58, 1831-1843. &gt;https://doi.org/10.1007/s11517-020-02185-x
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref21">
    <label>21</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Kumar, J.P., Sadique, M. and Shah, S.R. (2022) Mathematical Study of Blood Flow through Blood Vessels under Diseased Condition. International Journal of Multidisciplinary Research and Development, 9, 31-44.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref22">
    <label>22</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Kumar, A. and Shah, S.R. (2024) Hemodynamic Simulation Approach to Understanding Blood Flow Dynamics in Stenotic Arteries. International Journal of Scientific Research in Science and Technology, 11, 630-636. &gt;https://doi.org/10.32628/ijsrst241161116
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref23">
    <label>23</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Akbar, S., Sharma, R.K., Sadique, M., Jaiswal, K.M., Chaturvedi, P., Kumar, V., et al. (2024) Computational Analysis of Clot Formation Risk in Diabetes: A Mathematical Modeling Approach. Bibechana, 21, 233-240. &gt;https://doi.org/10.3126/bibechana.v21i3.64973
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref24">
    <label>24</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Chaturvedi, P. and Shah, S.R. (2023) Mathematical Analysis for the Flow of Sickle Red Blood Cells in Microvessels for Bio Medical Application. The Yale Journal of Biology and Medicine, 96, 13-21. &gt;https://doi.org/10.59249/atvg1290
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref25">
    <label>25</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Shah, S.R. (2012) A Case Study on Non-Newtonian Viscosity of Blood through Atherosclerotic Artery. Asian Journal of Engineering and Applied Technology, 1, 47-52. &gt;https://doi.org/10.51983/ajeat-2012.1.1.2501
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref26">
    <label>26</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ratan Shah, S. (2011) Non-Newtonian Flow of Blood through an Atherosclerotic Artery. Research Journal of Applied Sciences, 6, 76-80. &gt;https://doi.org/10.3923/rjasci.2011.76.80
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref27">
    <label>27</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Zid, I., Alilat, D., Rebhi, R., Alliche, M., Chamkha, A.J. and Zeguai, S. (2025) MHD Natural Convection of Non-Newtonian Carreau-Yasuda Nanofluid in a Square Porous Cavity by Dupuit-Darcy Model. The European Physical Journal Plus, 140, Article No. 450. &gt;https://doi.org/10.1140/epjp/s13360-025-06407-9
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref28">
    <label>28</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Ojha, M., Cobbold, R.S.C., Johnston, K.W. and Hummel, R.L. (1989) Pulsatile Flow through Constricted Tubes: An Experimental Investigation Using Photochromic Tracer Methods. Journal of Fluid Mechanics, 203, 173-197. &gt;https://doi.org/10.1017/s0022112089001424
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref29">
    <label>29</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Toufique Hasan, A.B.M. and Dipak Kanti, D. (2008) Numerical Simulation of Sinusoidal Fluctuated Pulsatile Laminar Flow through Stenotic Artery. Journal of Applied Fluid Mechanics, 1, 25-35.
    </mixed-citation>
   </ref>
   <ref id="scirp.145271-ref30">
    <label>30</label>
    <mixed-citation publication-type="other" xlink:type="simple">
     Lee, K.W. and Xu, X.Y. (2002) Modelling of Flow and Wall Behaviour in a Mildly Stenosed Tube. Medical Engineering&amp;Physics, 24, 575-586. &gt;https://doi.org/10.1016/s1350-4533(02)00048-6
    </mixed-citation>
   </ref>
  </ref-list>
 </back>
</article>