1. DEPARTMENT OF MECHANICAL ENGINEERING K.I.E.T, GHAZIABAD NUMERICAL ANALYSIS OF FLUID FLOW AND HEAT TRANSFER IN MICROCHANNEL UNDER THE GUIDANCE OF Mr. Deepak Kumar Singh PRESENTED BY- PARUL SINGH(0902940066) PRESHITA JAIN (0902940069) VIVEK SINGH (0902940118) ANURAG SHARMA(1002940901)

2. TABLE OF CONTENT Objective of Project Geometry Details Computational Fluid Dynamics Calculations Result Conclusion Work Plan Tentative Date for the completion of Project

3. OBJECTIVE To investigate hydrodynamic & thermal characteristics of micro-channel through Computational Fluid Dynamic modeling & simulation. Parameter sensitivity study of micro-channel.  Input parameters: (Reynolds‘ Number, Cross-section, Waviness)  Output parameters: (Friction loses, Convective heat transfer coefficient, Temperature)

4. Rectangular size410*200 mm² Channel geometryWavy Rectangular micro- channel Micro-channel length0.01 m Mesh sizing 2 x 10ˉ ⁵ µm Material usedSilicon LiquidWater-liquid Reynolds' Number50-300 GEOMETRIC SPECIFICATIONS

5. Based on the previous researches that have been made so far, we have confined our work to the micro- channel in the wavy structure of varying relative wavy amplitude with constant length of the micro- channel at various Reynolds’ number. Values of various relative wavy amplitude (γ) of the channels are 0.05, 0.075, 0.1, & 0.125. Then we’d be comparing our result with that of the straight channel of similar dimensions.

6. GEOMETRY Wavy line equation y=A cos (2πx/L) where y= channel relative wavy amplitude A= channel’s wavy amplitude L= channel wavelength = 0.833 mm x= x co-ordinate

7. DIMENSIONLESS PARAMETERS Dimensionless channel width (α e ): α e = S c /L where α e = 0.1 S c = Spacing between two wavy planes Cross-section aspect ratio (β): β = S c /H where β = 1/3 H= Depth of channel

8. Relative wavy amplitude (γ): γ= A/L where γ varies as 0.05,0.075,0.1,0.125. Number of wavy unit (n)= 12 Total length of channel is fixed & equals to 0.01 m and is given by: “n x L”

9. VARIOUS GEOMETRY Straight Rectangular channel Wavy channel with γ= 0.05 Wavy channel with γ= 0.075

10. VARIOUS GEOMETRY Wavy channel with γ= 0.1 Wavy channel with γ= 0.125

11. MESHING

12. SETUP & SOLUTION Models : Energy Model Materials used: Fluid: Water-liquid PROPERTIES: Density-998.2 kg/m³ Specific Heat-4182 J/kg-K Thermal Conductivity-0.6 W/m-K Viscosity-0.001003 kg/m-s Channel material: Silicon PROPERTIES: Density-2570 kg/m³ Specific Heat-710 J/kg-K Thermal Conductivity-149 W/m-K

13. BOUNDARY CONDITIONS INLET: Velocity Inlet (Based on Reynolds Number) Temperature at inlet = 300 K WALL: Constant Wall Heat Flux (direction –from wall surface to fluid) = 50 W/cm² Stationary Wall No-Slip boundary condition at wall surface OUTLET: Outflow boundary condition at channel outlet. Reynolds’ number 50100150200250300 Velocity(m/s)0.18680.37370.56060.74740.93431.1212

14. SOLVER SETTINGS PRESSURE-VELOCITY COUPLING:- Pressure-velocity coupling refers to the numerical algorithm which uses a combination of continuity and momentum equations to derive an equation for pressure (or pressure correction) when using the pressure-based solver. Four algorithms are available in FLUENT:  Semi-Implicit Method for Pressure-Linked Equations (SIMPLE)  This is a guess and correct procedure for the calculation of pressure.  SIMPLE-Consistent (SIMPLEC)  Allows faster convergence for simple problems (e.g., laminar flows with no physical models employed).  Pressure-Implicit with Splitting of Operators (PISO) o It is useful for unsteady flow problems. The steady state PISO algorithm adds an extra correction step to SIMPLE to enhance its performance per iteration. Coupled

15. SOLVER SETTINGS INTERPOLATION METHODS (GRADIENTS) :- Gradients of solution variables are required in order to evaluate diffusive fluxes, velocity derivatives, and for higher-order discretization schemes. The gradients of solution variables at cell centers can be determined using three approaches:  Green-Gauss Cell-Based – The default method; solution may have false diffusion (smearing of the solution fields).  Green-Gauss Node-Based – More accurate; minimizes false diffusion.  Least-Squares Cell-Based – Recommended for polyhedral meshes; has the same accuracy and properties as Node-based Gradients. Gradients of solution variables at faces are computed using multi-dimensional Taylor series expansion.

16. SOLVER SETTINGS INTERPOLATION METHODS FOR PRESSURE :-  Standard – The default scheme; reduced accuracy for flows exhibiting large surface-normal pressure gradients near boundaries (but should not be used when steep pressure changes are present in the flow – PRESTO! scheme should be used instead.)  PRESTO! – Use for highly swirling flows, flows involving steep pressure gradients (porous media, fan model, etc.), or in strongly curved domains.  Linear – Use when other options result in convergence difficulties or unphysical behavior.  Second-Order – Use for compressible flows; not to be used with porous media, jump, fans, etc.  Body Force Weighted – Use when body forces are large.

17. SOLVER SETTINGS DISCRETIZATION:- Field variables (stored at cell centers) must be interpolated to the faces of the control volumes. Interpolation schemes for the convection term:  First-Order Upwind – Easiest to converge, only first-order accurate.  Power Law – More accurate for one-dimensional problems since it attempts to represent the exact solution more closely.  Second-Order Upwind – Uses larger stencils for 2nd order accuracy, essential with tri/tetra mesh or when flow is not aligned with grid; convergence may be slower.  Monotone Upstream-Centered Schemes for Conservation Laws (MUSCL) – Locally 3rd order convection discretization scheme for unstructured meshes; more accurate in predicting secondary flows, vortices, forces, etc.  Quadratic Upwind Interpolation (QUICK) – Applies to quad/hex and hybrid meshes, useful for rotating/swirling flows, 3rd-order accurate on uniform mesh.

19. Variation of Nusselt number at different relative wavy amplitude (γ) with varying Reynolds’ number

20. Values of Nusselt number of wavy channel at different relative wavy amplitude (γ) and straight channel with varying Reynolds’ number γ0.050.0750.10.125 STRAIGHT CHANNEL ReNu 501.8761.941.922.081.75 1002.62.82.924.12.53 1503.183.623.966.563.1 2003.74.455.018.63.46 2504.165.265.5110.173.78 3004.55.986.4312.134.06

21. Heat transfer enhancement factor for various wavy channels & a straight line channel at various Reynolds’number

22. y0.050.0750.10.125 ReE Nu 501.0481.081.0951.162 1001.0511.1061.1541.62 1501.0641.1671.2772.116 2001.0691.2861.4482.485 2501.091.3911.4582.69 3001.1081.4731.5842.987 Values of Heat transfer enhancement factor of wavy channel at different relative wavy amplitude (γ) with varying Reynolds’ number

23. Temperature variation of fluid in wavy channel with different relative wavy amplitude (γ) and straight channel at various Reynolds’ number

24. Values of average temperature of fluid in wavy channel with different relative wavy amplitude (γ) & straight channel at various Reynolds’ number y0.050.0750.10.125 STRAIGHT CHANNEL Retemp 50407.14411.07412.52413.6408.69 100372.55371.07367.54354.67375.03 150356.32353.32347.86342.56362.06 200346.92332.79330.01332.39354.45 250340.58327.17320.96327.38349.25 300336.23322.16318.43324.15345.3

25. Variation of Pressure drop penalty factor( E f ) with varying Reynolds’ number at various relative wavy amplitude (γ =0.05, 0.075, 0.1, 0.125)

26. Values of Pressure drop penalty factor( E f ) with varying Reynolds’ number at various relative wavy amplitude (γ =0.05, 0.075, 0.1, 0.125) y0.050.0750.10.125 Re PRESSURE DROP PANELTY FACTOR 50 1.0161.0541.0631.07 100 1.0371.1091.1371.172 150 1.041.1541.2181.314 200 1.0461.2111.341.438 250 1.0541.2811.421.54 300 1.0631.381.5481.672

27. TEMPERATURE PROFILE

28. VELOCITY PROFILE

29. CONCLUSION The result of the above graph shows that the heat transfer coefficient increases with the increasing Reynolds’ number. The heat transfer coefficient greatly increases with the increasing wavy amplitude of the micro-channel. It can also be observed that the temperature drop in the fluid while its flow through the micro-channel, increases with the increase in the waviness of the micro-channel and the Reynolds’ number.

30. WORKPLAN Month / Activity SeptemberOctoberNovemberDecemberJanuaryFebruaryMarchApril Literature Survey Software Training Designing the model Data collection Validation Result & Comparison Report Submission

31. DATE OF SUBMISSON The project will be submitted to the concerned authorities on April 10, 2013.