A thesis defense - PowerPoint PPT Presentation

1 / 62
About This Presentation
Title:

A thesis defense

Description:

A thesis defense – PowerPoint PPT presentation

Number of Views:494
Avg rating:3.0/5.0
Slides: 63
Provided by: brya87
Category:
Tags: defense | thesis | wth

less

Transcript and Presenter's Notes

Title: A thesis defense


1
Solution Adaptive Meshing for Flows With Vortices
  • A thesis defense
  • Submitted in Partial Fulfillment of the
    Requirements
  • For the Degree of Master of Science
  • In Aerospace Engineering

Naser Talon Shamsi Kasmai June 27, 2008
2
Graduate Committee
  • David S. Thompson, Ph.D.
  • Associate Professor of Aerospace Engineering
  • Major Professor
  • Edward Luke, Ph.D.
  • Associate Professor of Computer Science and
    Engineering
  • Committee Member
  • Keith Koenig, Ph.D.
  • Professor of Aerospace Engineering
  • Committee Member

3
Acknowledgements
  • This work is supported by the NASA Constellation
    Universities Project (CUIP, NCC3-994)
  • Great thanks goes out to Monika Jankun-Kelly for
    her great software that makes this work possible
  • Thanks to Dr. Yasushi Ito for his cooperation and
    work on this project

4
Overview
  • Introduction
  • Vortices
  • Solution Adaptive Meshing
  • Related Work
  • Thesis Statement
  • Meshing Strategies
  • Feature-based Adaptive Meshing
  • Vortex Characterization
  • Adaptive Mesh Refinement
  • Adaptive Mesh Regeneration using Embedded
    Surfaces
  • Results
  • Wing in wind tunnel
  • Spinning Missile
  • Conclusion

5
Vortices
  • A vortex is a fluid flow characterized by spiral
    streamlines
  • Caused by a pressure difference between the lower
    and upper surface of the wing
  • Two important aspects
  • Formation at the wingtip
  • Convection downstream

6
Vortices
7
Solution Adaptive Meshing
  • For meshing in general, desire to have a balance
    of accuracy and computational efficiency
  • Refinement increases accuracy, but adds
    computational cost
  • Solution adaptive meshing produces a mesh that
    evolves in response to the solution
  • Allows refinement in places that need it the most
  • Maximizes accuracy to cost balance

8
Solution Adaptive Meshing Related Work
  • Finite volume methods used in CFD do not provide
    a direct mechanism for error estimation
  • Local error estimation techniques include
  • Divided difference
  • Solution and local solution reconstruction
    difference
  • Eigenvalues of a symmetric Hessian matrix for a
    field quantity
  • Gradient-based weight functions can be considered
    as an error technique because the functions
    approximate truncation error of the numerical
    scheme used

9
Solution Adaptive Meshing Related Work
  • Dindar et al. and Kenwright Haimes applied
    refinement at the core line of a vortex
  • Refinement was performed in a region defined by a
    percentage of the cores vorticity
  • Found that feature-based refinement resolved
    small-scale features while error-based refinement
    did not
  • Murayama et al. also employed refinement at the
    vortex core line
  • Found that solutions computed on meshes with
    refinement along the core line showed improved
    agreement with experimental data
  • Turnock et al. used a statistical vortex
    detection method to identify core regions
  • Refinement was achieved by using a set mesh
    density across the core surrounded by an annulus
    of lower density cells.
  • Significant improvement was seen when compared to
    computations on an unrefined mesh

10
Thesis Statement
  • Abstract feature descriptors can be employed
    along with mesh refinement or mesh regeneration
    with embedded surfaces to facilitate an effective
    solution adaptive meshing strategy. Strategies
    will be applied to different configurations to
    evaluate the robustness of the strategy and to
    verify the approach

11
Feature-based Adaptive Meshing
  • Vortex feature characteristics are used to locate
    flow field regions that are near vortices
  • Regions near the vortices are marked for
    enrichment
  • Assume that the quality of the solution will
    improve if a mesh is enriched near flow features
    i.e. vortices
  • Two mesh improvement techniques are used
  • Mesh refinement
  • Mesh regeneration using embedded surfaces
  • Algorithm described by Jankun-Kelly is used to
    produce a high-level description of vortices
  • Previous research shows that mesh improvement
    needs to be performed around and in the region of
    the vortex core
  • Can an initial solution computed on a coarse mesh
    be used to initiate adaptive meshing?

12
Vortex Characterization
  • Output of the process is a set of high-level
    descriptors, including geometric, kinematic, and
    dynamic properties
  • Vortex core line
  • Vortex extent surface (MTV)
  • Two important attributes of the vortex
    characterization and extraction process
  • Able to extract core lines from complex vortex
    configuration
  • Extent surface is an unambiguous descriptor that
    captures regions of high velocity curvature

13
Vortex Characterization
(1) Aggregation of candidate cells
(2) Identification and classification of
aggregates
14
Vortex Characterization
(3) Core line extraction
(4) Extent surface extraction
15
Adaptive Mesh Refinement
  • Uses geometric, feature-based descriptors to
    identify regions that should be refined
  • Mesh independent set of descriptors
  • UGSensor marks nodes in regions defined by the
    vortex characterization process, UGVortex
  • User may choose which regions to mark
  • Near core
  • Near extent
  • Inside extent
  • Near extent and near core

16
Adaptive Mesh Refinement
Near the core line Near the extent surface
17
Adaptive Mesh Refinement
18
Adaptive Mesh Refinement
(a) Prism (b) tetrahedron
(c) hexahedron
(d) Refined pyramid (e) refined/unrefined
cell neighbors
19
Adaptive Mesh Regeneration Using Embedded Surfaces
  • Strategy uses feature aligned embedded surface
    meshes
  • Surface meshes are used as interior boundaries
    for mesh regeneration
  • Strategy allows for more specific control over
    the volume mesh compared to standard
    redistribution methods
  • Strategy may improve feature resolution because
    of alignment of faces with those features for
    Riemann based flow solvers, like CHEM

20
Adaptive Mesh Regeneration Using Embedded Surfaces
21
Adaptive Mesh Regeneration Using Embedded Surfaces
22
Results
  • Two configurations
  • Wing in a wind tunnel at 10º AoA
  • Two mesh improvement techniques
  • Missile spinning at 30Hz and 60Hz with canards
    deflected to 15º
  • All flow solutions were computed using the HPCCs
    Raptor cluster
  • Flow solver used in all cases was CHEM

23
Results Wing in Wind Tunnel
  • Low-speed turbulent flow past a rectangular
    planform half-wing
  • Aspect ratio of 0.75, NACA 0012 cross-section
  • 10º AoA, Re 4.6 x 106
  • Experimental and additional CFD results reported
    by Dacles-Mariani et al.
  • C-O topology structured grid, Baldwin-Barth
    turbulence model (modified)
  • High-order (5th) CFD simulations were used,
    yielding superior numerical results

24
Results Wing in Wind Tunnel
25
Results Wing in Wind Tunnel
  • Turbulence model used is Spalart-Allmaras
  • Modified to decrease the production of turbulence
    in the vortex core
  • Inflow boundary conditions (fixed mass)
  • Mass flow rate 81.2 kg/s
  • Stagnation temp 290.4 K
  • Outflow boundary (farfield)
  • Pressure 1 atm
  • Temperature 288.15 K
  • Velocity 67.528 m/s

26
Results Wing in Wind Tunnel
27
Wing Adaptive Mesh Refinement
  • Vortex computed on the baseline mesh is quite
    diffuse and shorter in length compared to further
    refinements
  • Due to artificial dissipation associated with
    comparatively large elements
  • Unwise to perform multiple refinements using the
    solution from the coarse baseline mesh
  • To alleviate this, only two levels of refinement
    were performed on the baseline and the two
    following adaption cycles
  • An additional refinement cycle was performed
    using four levels of refinement using different
    refinement strategies

28
Wing Adaptive Mesh Refinement
Baseline solution CYCLE 0
After 1st refinement CYCLE 1
After 2nd Refinement CYCLE 2
29
Wing Adaptive Mesh Refinement
30
Wing Adaptive Mesh Refinement
31
Wing Adaptive Mesh Refinement
  • Cycle 3A Refinement in a region near the vortex
    core line. The radius of refinement is limited to
    25 of the local distance to the extent surface
  • Cycle 3B Refinement in a region near the extent
    surface. The refinement is limited to 25 of the
    local distance from the core line to the extent
    surface on either side of the extent surface

32
Wing Adaptive Mesh Refinement
  • Cycle 3C Refine inside the extent surface.
    Fairly conservative technique, but it ensures
    that the vortex is fully captured in the
    refinement section of the mesh.
  • Cycle 3D Refine inside and near the extent
    surface. Provides the highest level of
    refinement, near refinement is limited to 25 of
    the local distance from the core line to the
    extent, on either side

33
Wing Adaptive Mesh Refinement
34
Wing Adaptive Mesh Refinement
35
Wing Adaptive Mesh Refinement
(a) Baseline
(b) Cycle 1
(c) Cycle 2
36
Wing Adaptive Mesh Refinement
(a) Cycle 3A core refinement
(b) Cycle 3B refinement near extent
37
Wing Adaptive Mesh Refinement
(a) Cycle 3C
(b) Cycle 3D
38
Wing Adaptive Mesh Refinement
  • Results suggest that refinement inside and near
    the extent yields the best results in terms of
    the solution achieved
  • Vortex was successfully captured within the
    refinement region
  • Use of the local maximum tangential velocity
    surface as a measure of vortex extent provides an
    unambiguous and grid-independent geometrical
    characteristic
  • The capability to initiate computation and
    subsequent refinement from a very coarse baseline
    mesh was fully demonstrated

39
Wing Adaptive Mesh Refinement
40
Wing Mesh Regeneration Using Embedded Surfaces
  • Again, attaining a good enough initial solution
    from a coarse baseline mesh remains as a hurdle.
  • Hurdle is overcome by being able to refine enough
    in the general area of the vortex to achieve a
    better solution for the next iteration
  • Each mesh is generated using the vortex extent
    surface extracted from the previous mesh in
    sequence
  • The extracted extent surface is then used as an
    internal boundary on which the surface mesh was
    generated

41
Wing Mesh Regeneration Using Embedded Surfaces
42
Wing Mesh Regeneration Using Embedded Surfaces
43
Wing Mesh Regeneration Using Embedded Surfaces
44
Wing Mesh Regeneration Using Embedded Surfaces
45
Wing Mesh Regeneration Using Embedded Surfaces
(a) baseline
(b) Cycle 1
46
Wing Mesh Regeneration Using Embedded Surfaces
(a) Cycle 2
(b) Cycle 3
47
Wing Mesh Regeneration Using Embedded Surfaces
Mesh spacing for the embedded surface meshes
Mesh statistics for the wing in wind tunnel using
mesh regeneration using embedded surfaces
48
Wing Mesh Regeneration Using Embedded Surfaces
  • Results reiterate the need to refine in all
    critical areas, i.e. core and extent, especially
    over the wingtip
  • As more iterations are performed, the location of
    the extent surface becomes, for the most part,
    stationary
  • For the most part, the vortex location has been
    accurately predicted
  • For further solution improvement, the nodal
    density of the mesh has to be increased in other
    critical regions, namely along the vortex core
    line over the wingtip

49
Results Spinning Missile
  • Missile spinning with forward canards deflected
    15
  • Two cases
  • 30Hz spin
  • 60Hz spin
  • M 1.6
  • Re 41.3 x 106

50
Results Spinning Missile
  • Rotation occurs about the missiles long axis
    with the rotation vector (right-handed) pointing
    out of the nose of the missile
  • Both rotation rates display significant vortex
    asymmetry and curvature
  • For the 60Hz case, the inboard, port side vortex,
    shed from the forward canard, impinges on the
    missile body, causing it to terminate prematurely
  • CHEM used to compute the flow solution
  • Menters SST k-? turbulence model was used

51
Results Spinning Missile
(a) Baseline mesh at 30Hz
(b) Baseline mesh at 60Hz
52
Results Spinning Missile
  • Based on results from the wing case, the mesh was
    refined inside and near the extent surface
  • Baseline mesh used is roughly equivalent to the
    cycle 2 mesh used for the wing case
  • Mesh improvement between cycles consisted of 3
    levels of refinement

53
Results Spinning Missile
30Hz Case
54
Results Spinning Missile
60Hz Case
55
Results Spinning Missile
  • As shown, the refinements made for both cases
    show improved resolution of the stagnation
    pressure contours
  • For the 30Hz case, the resolution of the vortices
    is noticeably improved, especially the outermost
    two
  • The innermost vortices are only slightly improved
    because they lie close to the missile body, a
    naturally more refined region
  • The 60Hz case contains highly asymmetric vortex
    structure, including a vortex that wraps around
    the missile body (outboard, port)
  • The two starboard vortices can be seen
    interacting, and are in the process of merging
  • Significant improvement can be seen in all
    vortices
  • For the port vortex, improvement can be seen
    along the entire missile body
  • For the starboard vortex, improvement can be seen
    over ¾ of the body

56
Conclusions
  • Overall, the effectiveness of vortex-based
    solution adaptive meshing has been demonstrated
    for two different configurations.
  • Two strategies were employed to achieve adaptive
    meshing
  • Adaptive mesh refinement
  • Adaptive mesh regeneration using embedded
    surfaces

57
Conclusions Wing in Wind Tunnel
  • For mesh refinement, through comparison to
    experimental data, the most effective method was
    determined refinement in and near the vortex
    extent
  • Results obtained were noticeably improved across
    the board when compared to any previous iteration
  • Mesh regeneration using embedded surfaces was
    able to effectively improve the flow solution
    through adaptive mesh improvement
  • Through comparison to experimental results, it
    was determined that full solution correlation
    could not be had
  • Adequate mesh resolution in the core over the
    wingtip region could not be obtained

58
Conclusions Wing in Wind Tunnel
  • Through the application of both adaptive meshing
    strategies, refinement performed near and inside
    the vortex extent surface was determined to be
    the highest performer
  • Method was seen to have superior definition in
    crossflow velocity contours
  • Method was determined to have the closest
    agreement with experimental data (tangential
    velocity vs. local vortex extent radius)

59
Conclusions Wing in Wind Tunnel
(a) Mesh refinement near and inside extent
(b) Mesh regeneration final refinement
60
Conclusion Spinning Missile
  • Baseline mesh used was somewhat refined in the
    region near the missile body
  • Comparable to the cycle 2 mesh used for the wing
    refinement
  • In one refinement cycle, the solution was greatly
    improved for both the 30Hz and 60 Hz scenario
  • Based on overall observed vortex resolution and
    coherence of the vortex core line
  • The vortical asymmetry caused by missile rotation
    highlights the need for solution based adaptive
    meshing

61
Conclusion
  • The study presented demonstrates that abstract
    feature descriptors can be used along with mesh
    refinement or regeneration to facilitate
    effective solution adaptive meshing
  • Verification of the strategies was achieved
    through application to various configurations,
    including more complex flows, showing the
    robustness and plausibility of each.

62
Thank You
Write a Comment
User Comments (0)
About PowerShow.com