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Structural functional surface design and manufacture

Structural functional surface design and manufacture. James Wharton ( AMTReL ). Director of Studies: Professor X. Chen Supervisors: Dr D. Allanson, Professor D. Burton . Structure of Seminar. Aims and Objectives Background to Project Initial Modelling of Bearing

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Structural functional surface design and manufacture

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  1. Structural functional surface design and manufacture James Wharton (AMTReL) Director of Studies: Professor X. Chen Supervisors: Dr D. Allanson, Professor D. Burton

  2. Structure of Seminar • Aims and Objectives • Background to Project • Initial Modelling of Bearing • Wind Tunnel Experimentation • Initial Modelling of Drag Reduction • Further Work

  3. Aims and Objectives The aim of this investigation is: “ To investigate how a micro-scale surface geometry can be manipulated to improve the properties relating to texture-induced lift, frictional reductions, drag reductions, heat transfer and self-cleaning.”

  4. Aims and Objectives • Using commercially available computational fluid dynamics (CFD) software packages, numerically solve the Navier-Stokes equations to predict the beneficial behavior of micro-scale textured surfaces interacting with moving fluids. • Validate the CFD predictions by performing experimentation using the facilities available within the university. • Investigate the manufacturability of structural surfaces and develop a feasible manufacturing strategy. • Demonstrate the benefits of structural functional surfaces for engineering applications.

  5. Bruzzoneand Costa (2013) stated: “Recent technological developments now permit us to texture surfaces in a flexible way and to assess the tribological efficiency of different microtopologies.”

  6. Background: Drag Reduction (Zhang et al., 2011) (Dean and Bhushan, 2012)

  7. Background: Heat Transfer Improvement (Brandner et al., 2006)

  8. Background: Frictional Reduction (Ramesh et al., 2013)

  9. Overall Conclusions of Literature • CFD has been used to try and predict interaction of fluid with surface but has been limited. • Ramesh et. al. (2013) concluded that modellingis the key step in predicting functional surfaces. • Manufacturing methods are not suitable for large scale production of surfaces. • More evidence needs to be created in order to justify, for certain functions, whether it is of benefit to manipulate the surface in a certain way for an application.

  10. Initial Modelling (Hydrodynamic Journal Bearing) • Based on: RAMESH ET. AL. Friction Characteristics of Microtextured Surfaces Under Mixed and Hydrodynamic Lubrication. Tribology International, vol.57, no.1, p.170-176, 2013. • Investigation relating micro-scale textured surfaces to friction characteristics. • Paper simulates circular and square pockets in cross section. Makes vague assumption that the 2D model has a small error, when compared to 3D model. • If error is small, then similar geometries can modelled two dimensionally, significantly reducing computational time (cost).

  11. Model Setup • Fluid: Trident 15w40 Oil • Density = 883 kg.m-3 Dynamic viscosity = 0.088 Pa.s • Assumptions: • - Incompressible • - Isoviscous • - Isothermal • Steady state solver (SIMPLE) • Very small Reynolds number (Re < 1.5) • Laminar (no turbulence model) • Convergence criteria: 10-6 MAX

  12. Three Dimensional Domain Shear Wall, Vx=0.36, Vy=Vz=0 Opening = 0 Pa (Gauge Pressure) Symmetry BC Applied to Sides Inlet = 0.36 m/s All Remaining Faces, No Slip Wall Refined Mesh Cylinders in Cross-Section (Side View) Top View

  13. Results: Velocity Contour Plot Two Dimensional Three Dimensional

  14. Results: Velocity Contour Plot 3D Model Results • Force acting normal to moving wall BC: 0.0314 N • Friction force: 3.668x10-4N • Average gauge pressure on moving wall: 0.3735 MPa 2D Model Results • Average gauge pressure on moving wall: 0.3429 MPa • Using wall area of 3D model (8.467x10-8m2), force acting on moving wall: 0.0290 N Error Between Load Capacity Forces 8.3% Between

  15. Make model match up with what's achievable in manufacturing methods. • Laborious model setup will be automated with python script. • The script will make it easier to correlate changing variables (i.e. angle with flow direction) with frictional reductions. • Continue with bearing test rig experimentation.

  16. (Syed and Sarangi, 2014)

  17. Wind Tunnel Experimentation • Test textured sheet from 10m.s-1to 40m.s-1 • Measured drag, fore and aft Forces Textured Surface Characteristics Pocket Depth = 40 μm Pocket Width = 500 μm Space Between Pockets = 500 μm

  18. Wind Tunnel Results

  19. Domain and Boundary Conditions Opening = 0 Pa (gauge) Geometry using same parameters as described before. Domain is a 1mm thick slice. Inlet = 40 m/s 10° Symmetry BC on Sides Geometry with no slip wall Textured Refined Mesh

  20. Velocity Contour Plot: 10° Rotate

  21. Drag Force Comparison: Flat • Nominal: 1.544 x 10-3 N [0.139 N] • Textured (Parallel to Flow): 1.583 x 10-3 N [0.142 N] • Textured (Perpendicular to Flow): 1.444 x 10-3 N [0.129 N] • Drag of Holding Arm: • Reynolds Number of Cylinder = 15484.3 • Approx. Drag Coefficient = 1.3 • Hence Drag Force = 1.49 N • Drag Force Comparison: Rotated 10° • Nominal Model: 3.306 x 10-2N [2.980 N] • Textured (Perpendicular to Flow): 3.281 x 10-2 N [2.953 N]

  22. Comparison of Results 7.6 % Drag Force Reduction (Wind Tunnel) 7.8 % Drag Force Reduction (CFD Simulation)

  23. Further Work • Investigate model with higher speed flow (100 m/s) • Run a transient model and analyse for any time dependent behaviour • Higher speed wind tunnel testing • Analyse how the boundary layer is being affected • Perform wettability tests for contact angle and surface energy

  24. Thank you for listening… Any Questions? Special thanks to… Professor X. Chen, Dr D. Allanson, Professor D. Burton …For continual support throughout.

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