Non-Newtonian Flow Between 2 Concentric Cylinders (Eulerian) — ANSYS Fluent CFD SimulationDescriptionThis project presents a CFD simulation of two-phase non-Newtonian flow between two concentric cylinders — a benchmark geometry used across drilling engineering, polymer processing, biomedical devices, and food technology. Unlike Newtonian fluids such as water or air, non-Newtonian fluids change their viscosity in response to applied shear, and capturing that behavior correctly is critical for accurate predictions. In this project, you'll model a Power-Law non-Newtonian base fluid (k = 0.021, n = 0.75) flowing through an annular channel with a rotating inner cylinder, while a denser soluble secondary phase travels through it using the Eulerian multiphase model. As the opening project of the Non-Newtonian Flow: Beginner CFD Training Package, it introduces the core idea of shear-dependent viscosity in the simplest, most fundamental geometry — the concentric annulus.MethodologyThe 3D annular geometry (1 m length, 0.0225 m inner diameter, 0.03125 m outer diameter) is designed in Design Modeler and meshed in ANSYS Meshing with a structured grid of roughly 1.4 million elements, appropriate for annular and rotating-flow problems. The Power-Law viscosity model is configured in Fluent by setting the consistency index k, the flow behavior index n, and clamping the minimum and maximum viscosity bounds. The Eulerian multiphase model is set up with two implicit phases, including phase-specific densities, viscosities, and inlet volume fractions. A rotating wall boundary condition (100 rpm on the inner cylinder) is applied — essential for any Taylor–Couette-type analysis — and Coupled pressure–velocity coupling with PRESTO! pressure discretization is chosen for the rotating multiphase flow.AnalysisPost-processing produces 2D and 3D contours of pressure, velocity, and volume fraction for both phases, revealing how the Power-Law fluid responds to the shear imposed by the rotating inner cylinder and how the denser secondary phase distributes through the annulus. From these fields you can study how the apparent viscosity varies with shear rate and how the two phases interact in the rotating annular flow. The same workflow underpins drilling mud analysis, polymer extrusion, blood flow in narrow vessels, paint coating, and food processing — anywhere viscosity isn't constant. By the end of this project, you'll be able to configure the Power-Law non-Newtonian viscosity model, set up an Eulerian two-phase flow with a rotating wall, and interpret the pressure, velocity, and volume-fraction fields that characterize non-Newtonian flow in a concentric-cylinder geometry.

Non-Newtonian Fluid Flow Between Two Moving Eccentric Cylinders — ANSYS Fluent CFD SimulationDescriptionThis project simulates the two-phase flow of a non-Newtonian fluid — a mixture of drilling fluid and CMC (carboxymethyl cellulose) — in the annular gap between two eccentric cylinders with a rotating inner cylinder. Unlike a Newtonian fluid, a non-Newtonian fluid's viscosity changes with applied shear: it can thin or thicken under stress (ketchup, blood, toothpaste, starch suspensions, and many polymer and salt solutions behave this way). This makes the case directly relevant to drilling engineering, where shear-dependent muds circulate through eccentric annuli between the drill pipe and the borehole wall. Within the Non-Newtonian Flow: Beginner CFD Training Package, this project builds on the concentric-cylinder case by adding eccentricity, introducing the asymmetric flow that characterizes real drilling annuli.MethodologyThe methodology combines a Eulerian multiphase model for the two phases (drilling fluid and CMC) with the standard k-ω turbulence model, and the low-Re correction is activated to better resolve the near-wall flow patterns that dominate in a narrow, eccentric annulus. The rotation of the inner cylinder is imposed through the Moving Wall boundary condition — the key driver that sets up the shearing flow and exercises the fluid's non-Newtonian response. The drilling–CMC mixture enters the gap between the eccentric cylinders at 0.25 m/s while the inner cylinder rotates. Geometry and meshing are done in Gambit as a structured mesh of 179,820 elements — structured here because the regular annular geometry suits a clean, aligned grid.AnalysisThe results provide 2D and 3D contours of pressure, velocity, streamlines, phase volume fraction, and eddy viscosity. The phase distribution tells the central story — the drilling-fluid volume fraction peaks exactly where the CMC fraction is lowest, and vice versa — showing how the two phases separate and redistribute across the eccentric gap under rotation and shear. By the end of this project, you'll be able to set up a Eulerian two-phase non-Newtonian case, apply the Moving Wall condition to drive annular shear flow, use the k-ω model with low-Re correction for near-wall resolution, and interpret phase separation from volume-fraction and eddy-viscosity contours.

DescriptionThis study simulates well drilling and cuttings (sludge) transport using ANSYS Fluent. The wellbore is modeled as a cylindrical annulus containing a rotating inner cylinder (100 rpm). A non-Newtonian drilling fluid (CMC) flows through the cavity, entraining and lifting solid mud particles. An Eulerian multiphase framework is adopted: the primary phase is the CMC base fluid and the secondary phase comprises drilling solids.The Eulerian approach is suitable for high dispersed-phase loadings (>10%), slurry and liquid–solid transport, and deposition studies. Here, the base fluid volume fraction is 0.87 and the solids (drilling particles) volume fraction is 0.13. Viscosity behavior is non-Newtonian for the CMC phase (contrast to Newtonian fluids, whose shear stress varies linearly with strain rate).Geometry & MeshThe 3D domain consists of two eccentric coaxial cylinders, each 10 m long. The inner cylinder diameter is 0.128 m and the outer cylinder diameter is 0.444 m. Meshing is performed in ANSYS Meshing with an unstructured grid totaling 179,820 elements.Simulation SetupA pressure-based, transient (unsteady) solver is used. Gravity is included with a magnitude of −9.81 m/s². Because the well axis is inclined by 30° relative to gravity, the gravitational acceleration resolves to 4.9 m/s² in the xxx direction and 8.5 m/s² in the zzz direction. The inner cylinder’s rotation is prescribed at 100 rpm to promote solids lifting and separation within the annulus.Results & DiscussionPost-processing yields 2D and 3D contours of pressure, CMC velocity, drilling-solids velocity, CMC volume fraction, drilling-solids volume fraction, and turbulent kinetic energy. These fields characterize the coupling between rotation-induced shear and buoyancy components, illustrating how the non-Newtonian carrier mobilizes and transports the cuttings while mitigating deposition within the inclined wellbore.

Forced Convection of a Non-Newtonian Nanofluid in a Tube, Paper Numerical Validation, ANSYS Fluent TrainingDescriptionThis project simulates the forced-convection heat transfer of a non-Newtonian nanofluid flowing through a horizontal tube under constant wall heat flux, using ANSYS Fluent. It reproduces and validates against the reference paper "Modeling of forced convective heat transfer of a non-Newtonian nanofluid in the horizontal tube under constant heat flux with computational fluid dynamics."The defining feature of this case is the non-Newtonian flow model. A Newtonian fluid has a single, constant viscosity, but many real fluids do not — their apparent viscosity changes with the local shear rate. Here the working fluid is water carrying Al₂O₃ nanoparticles together with xanthan: the aluminium-oxide particles make it a nanofluid, while the xanthan makes it non-Newtonian, so its viscosity is no longer constant and cannot be described by Newton's law. Capturing this shear-dependent viscosity is exactly what the non-Newtonian flow model does, and this tube flow is a clean setting to demonstrate it.Rather than treating the nanofluid as a multiphase mixture, it is defined as a single new material with effective thermophysical properties taken from the paper: density 1126.384 kg/m³, specific heat 3700.264 J/kg·K, and thermal conductivity 0.615 W/m·K. Its non-Newtonian viscosity is described with the Herschel-Bulkley model — a yield-stress fluid that only begins to flow once a threshold stress is exceeded, after which it follows a power law. The model parameters are a power-law index of 0.149, a yield stress of 2.92 Pa, and a critical shear rate of 58.4 s⁻¹, all from Table 1 of the paper, at a 4% nanofluid concentration.The 2-D geometry was built in Design Modeler as a horizontal tube 1.2 m long and 0.00475 m in diameter. Because it is symmetric about its centerline, it is modeled as axisymmetric. The domain was meshed in ANSYS Meshing using a structured grid of 40,000 elements.Simulation MethodologyThe simulation uses a pressure-based, steady solver with gravity neglected, a laminar viscous model, and the energy equation enabled. The flow is studied at two Reynolds numbers, 900 and 1600. Because the fluid is non-Newtonian, the inlet velocity for each case is computed from the generalized Reynolds-number definition given in the paper, giving 1.2698 m/s for Re = 900 and 1.7327 m/s for Re = 1600. The nanofluid enters at 295 K, and the tube wall carries a constant heat flux of 8846.4 W/m². Pressure-velocity coupling uses SIMPLE, with second-order discretization for pressure, momentum, and energy.Paper Validation & ResultsValidation follows Figure 3-a of the paper, which plots the convective heat transfer coefficient (h) against Reynolds number at a dimensionless station of x/D = 147 (with D = 0.00475 m). The heat transfer coefficient is evaluated from Equation 9 of the paper using the applied heat flux (8846.4 W/m²) together with the wall temperature (Tw) and the fluid bulk temperature (Tf), extracted at that station from the wall and from a line through the tube.The simulation matches the paper closely at both Reynolds numbers:CasePresent simulationPaperErrorh at Re = 9001676.1 W/m²·K1700 W/m²·K≈ 1.4%h at Re = 16001846.8 W/m²·K1750 W/m²·K≈ 5.5%The agreement is strong on both counts that matter: the error magnitude stays within about 5.5%, and the behavior is reproduced correctly — the heat transfer coefficient rises with Reynolds number, exactly as in the reference. Two-dimensional temperature and velocity contours are also obtained at both Reynolds numbers along the mid-section of the tube.

Non-Newtonian Blood Pulsatile Flow in a Vein — ANSYS Fluent CFD Simulation TrainingThis project simulates non-Newtonian, pulsatile blood flow through a vein using ANSYS Fluent, with the full case analyzed through CFD post-processing.The working fluid is blood, a non-Newtonian fluid. Non-Newtonian fluids are those whose viscosity changes with shear rate, meaning they have no single fixed viscosity. In such fluids the relationship between shear stress and applied strain rate is nonlinear, so no constant viscosity coefficient applies. The simulation is run as transient over 0.5 s, and a User-Defined Function (UDF) is applied to model the pulsing of the blood flow. Because blood flow is not steady but pulsed, the velocity is prescribed as a periodic function through the UDF code.The geometry was created in Gambit. The model consists of a main cylindrical vessel and two smaller branch vessels of reduced size and diameter — one branching at a 90-degree angle and the other with a 45-degree curvature. It has one inlet section and two outlet sections.Meshing was performed in ANSYS Meshing using an unstructured grid, for a total of 397,388 cells.MethodologyThe working fluid is blood, with a density of 1050 kg/m³. Because blood is non-Newtonian, its viscosity is described using the Carreau model with appropriate parameters.Newtonian fluids maintain a constant viscosity under applied force, whereas non-Newtonian fluids exhibit variable viscosity, of which there are several types. Time-dependent non-Newtonian fluids fall into two categories: rheopectic fluids, such as printer ink and cream, whose viscosity increases over time under load, and thixotropic fluids, such as honey, whose viscosity decreases as force is applied. Time-independent non-Newtonian fluids divide into three groups: dilatants, such as starch and clay, whose viscosity depends only on the magnitude of the applied force; pseudoplastics, such as greases, paints, soaps, and ketchup, whose viscosity is inversely related to the applied force; and Bingham fluids, such as toothpaste and silica nanocomposites, which require a threshold stress before they begin to flow.In this simulation, blood is treated as a pseudoplastic non-Newtonian fluid defined by the Carreau model. This model spans a wide range of fluid behavior by fitting a curve that matches both Newtonian and shear-thinning (pseudoplastic) responses.ResultsAfter the solution is complete, contours of pressure and wall shear stress are obtained at several time instants. The results confirm that the flow inside the vessel is fully pulsatile, since the pressure varies over time. They also show that pressure and wall shear stress are correlated: as the pressure inside the vessel rises, the wall shear stress increases accordingly.

Aorta, Non-Newtonian Pulsating Blood Flow — ANSYS Fluent CFD SimulationDescriptionThis project studies non-Newtonian pulsating blood flow in the aorta using ANSYS Fluent. The aorta geometry is obtained from a real CT scan, provided as an STL file that must be repaired before meshing — a workflow representative of patient-specific biomedical CFD. Blood is a non-Newtonian fluid whose apparent viscosity changes with shear rate, and the aorta's pulsatile flow, curvature, and branching make it a rich, realistic case for studying how such a fluid behaves in a large vessel. Within the Non-Newtonian Flow: Beginner CFD Training Package, this project builds on the earlier blood-flow case by moving to a larger, geometrically complex vessel reconstructed from real medical imaging.MethodologyThe aorta geometry is obtained from a CT scan, and tools such as SpaceClaim, ICEM CFD, and Design Modeler can be used to repair it; here ICEM CFD was used to fix the geometry and generate the mesh. The mesh was first generated with the octree method using five layers of prism cells at a ratio of 1.2, then improved with the Delaunay method, giving a final count of 457,864 cells. A UDF defines the pulsatile inlet velocity. The non-Newtonian behavior of blood is captured with the Carreau model, in which viscosity depends on the shear rate, defined by the zero-shear viscosity (µ₀), the infinite-shear viscosity (µ∞), the power index (n), and the relaxation time (λ). No energy equation is included, so temperature is neglected. The solver is transient, the flow is turbulent, and the density is constant at 1060 kg/m³, with a no-slip condition on the inner surface of the vessel wall. The UDF used to define the pulsating inlet velocity is provided.AnalysisThe results illustrate the inlet velocity and pressure drop over the pulse cycle, with the maximum velocity occurring at 0.15 s. The wall shear stress (WSS) contours show the maximum values in the aorta sections of smaller diameter, while the static-pressure contours show that at the beginning of the blood pumping, the pressure is highest at the entrance of the branches. When suction occurs at 0.4 s, it has the greatest impact on the inlet section of the aorta. Animation files of pressure and shear stress are included to reveal the pulsatile behavior and give a clearer understanding of the flow. By the end of this project, you'll be able to repair a real STL geometry from medical imaging, generate a prism-layer mesh, apply the Carreau non-Newtonian model with a UDF-defined pulsatile inlet, and interpret the velocity, pressure, and wall-shear-stress fields that characterize pulsatile blood flow in the aorta.

DescriptionThis project simulates a lumen blood vessel using coupled Fluid-Structure Interaction (FSI) and a non-Newtonian blood model in ANSYS Fluent, with the results examined through CFD analysis. Because blood is a shear-thinning fluid whose viscosity changes with the local strain rate, a non-Newtonian treatment is essential for capturing the flow behavior realistically inside the vessel.The three-dimensional geometry was created in SpaceClaim. The computational domain is 164 mm long, 262 mm high, and 5 mm wide. Meshing was performed in ANSYS Meshing, producing a total of 356,794 elements. Owing to the pulsatile nature of the problem, a transient solver was used.MethodologyHere, a blood vessel together with its wall is simulated in ANSYS Fluent. The solver's intrinsic FSI module was enabled so that displacement of the vessel wall could be captured in response to the flow.The inlet boundary condition was defined as a pulsatile velocity using a UDF, while the outlet was defined as a pulsatile pressure, also supplied through a UDF. The blood itself was modeled as a non-Newtonian fluid using the Carreau model, which reproduces the shear-thinning drop in viscosity as the shear rate increases. A laminar model was enabled to solve the fluid equations.ConclusionOn completion of the solution, three-dimensional contours of wall displacement and von Mises stress were obtained. As the results show, the blood flowing through the vessel exerts stress on the vessel walls, deforming them and demonstrating the two-way coupling between the pulsatile non-Newtonian flow and the compliant vessel structure.