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Visualization of finite element data of a multi-phase concrete model
M. Ritter1, M. Aschaber1, W. Benger2, G. Hofstetter1
1 University of Innsbruck, Austria2 Louisiana State University, USA
10.7.2013, Vienna
Center for Comput-ation and Technology ASTRO@
UIBK
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• Outline– Motivation– Numerical Simulation– Data Modeling– Visualization– Conclusion & Future Work
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• Motivation:
by Neal Stone
Scientific Visualization Techniques and
Research
Engineering Simulation Tools and Visualization
Gap
Motivation
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• Motivation:
by Neal Stone
Scientific Visualization Techniques and
Research
Engineering Simulation Tools and Visualization
Motivation
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• Motivation:• Simulation techniques are used more frequently• Produced data sets growing• Data complexity is increasing
• Visualization used for data interpretation of results is important.
Motivation
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Numerical Simulation
10.7.2013, Vienna
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• Aim:– More realistic simulation of drying shrinkage
• Application:– Strengthening of a RC structure by adding an overlay
Numerical Simulation
New top concrete layer
Old concrete structure
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• Drying shrinkage:– Long term drying process in concrete– Decrease of relative pore humidity– Increase of capillary pressure– Capillary pressure results in volumetric shrinkage
Numerical Simulation
concrete
drying
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• Drying Shrinkage:
Numerical Simulation
New top concrete layer
Old concrete structure
Different internal stresses Critical region at joint
Drying shrinkage
Swelling
concrete
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• Numerical Simulation:– Finite element simulation on multiple grids of
concrete specimen– Hexahedral Mesh of 9 x 9 x 13 Cells
Numerical Simulation
100 x 100 x 56 mm
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• Numerical Simulation:– Finite element simulation on multiple grids of
concrete specimen– Hexahedral Mesh of 9 x 9 x 13 Cells
Numerical Simulation
Undeformed linear element Deformed quadratic elementThe element has curved faces
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• Multiphase concrete model• Solid, water, and gas phase
(dry air and water vapor)• Coupled hygral-thermo-mechanical
model
Numerical Simulation:
• Balance equations• Mass • Enthalpy• Linear Momentum
• Linear kinematic relations• Constitutive equations
Governing equations:
Numerical Simulation
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Multiple solution variables (Data fields)• Gas pressure scalar• Capillary pressure scalar• Displacements vector• Temperature scalar
Derived data fields• Strain 2nd order tensor• Stress 2nd order tensor
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• Drying shrinkage – Effective stress:
– Hydrostatic pressure of the water on the solid phase:
Numerical Simulation
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Data Modeling
10.7.2013, Vienna
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Before doing data visualization one has to deal with data• Many different kinds• Many formats
Data management and handling is crucial in computational sciences• Reusability of methods and techniques• Sustainability• Exchangeability of data (collaborations)
We propose using a concept based on mathematics to systematically organize data
Data Modeling
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Separation of Geometry (Grids) and Datafield (Fields)
Inspired by concepts of:Topology Differential Geometry Geometric Algebra
Fiber Bundle Data Model
Grid
Field
Data Modeling
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• Manifold describing the base space• Topology• Refinement level• Coordinate representation• Vertex positions in representation• Neighborhood
Gridthe base space
Data Modeling
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• Dataset holding numerical data • per k-cell on the grid (vertex, edge, cell, … )• Array of arbitrary type, for example:
• Scalar• Vector, BiVector, …• Tensor• Any other user defined type
Fieldthe fiber
space
Data Modeling
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Data Modeling
• Hierarchical structure:
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Supported Grid types:• Uniform Grid• Curvilinear Grid• Rectilinear Grid• Adaptive Mesh Refinement Grid (AMR)• Point Cloud• Lines• Triangular/Quad and Mixed Surfaces
Grids can be fragmented (Blocks) having Ghost Zones
Grids can have refinement levels
Work in progress:• Hexahedral Grid• FEM Grid• Connected Graph Data• Full Waveform LIDAR Laser Data
Data Modeling
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Fiber: 0D 1D 3D 6D BA
SE:
3D
2D
1D
0D
Data Modeling
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Data Modeling
• Data at Vertices:
T=0.0 FE-Mes h
PointsCarte s ian
Pos itions PointDis placement VectorPre s s ure Scalar
<3 x double><3 x double><double>
Ce llsCe lls AsPoints
Pos itions Indice s<8 x uns igned long>
Stre s s Av Tens or<6 x double>( )
S tre s s Av Tens or<8 x <6 x double> >( )
(optional)
(optional)
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Data Modeling
• Data at Integration Points:
T=0.0 FE-Mes h_IP
PointsCarte s ian
Stre s s Te ns or<6 x double >Ce lls
Ce lls As PointsPos itions Indice s<8 x uns igne d long>
No positions can be computed
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Data Modeling
• Sets of Nodes and Sets of Elements:
T=0.0 FE-Me s h
PClus te rPClus te rAs Points
Pos itions<uns igne d long>
CClus te rCClus te rAs Ce lls
Pos itions
PName 1
<uns igne d long>CName1<uns igne d long>CName2
Indices of vertices in named fragments
Indices of integration pointsin named fragments
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Data Modeling
• Linked groups for alternative data access:– E.g. time frames and time steps in ABAQUS
No data stored
T=0.0 Bundle - frames
T=0.2 T=0.4 T=0.6 T=0.8 T=1.0 T=1.2 T=1.4
T=0.0 Bundle - s teps
T=1.0 Link
Link
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Data Modeling
HDF5 Based Data format: independent, free, open, data browserwww.hdfgroup.org
FEM - Example
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Visualization
10.7.2013, Vienna
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• Visualization framework• Highly modular design
– Small Core – Plug-Ins
• Mainly developed by Werner Benger– Currently about 8 people are actively contributing
• C++, OpenGL• Open Academic License• Runs on Linux, Windows (and MacOS)• http://vish.fiberbundle.net
Visualization Shell VISH
Visualization
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Visualization
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Data handling
• Based on the fiber bundle concept
• Allows to implement highly reusable visualization modules
Visualization
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• Colored Cages– Show FE grid
• Positive• Negative
– Shaded colored surface– Illustrates data at vertices– One scalar field via color-map– One vector field via displacement– Can be combined with other visualization
techniques
Visualization
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• Colored Cages– Integration point data is extrapolated and averaged on demand
Visualization
Extrapolation from integration points
Averaged,smoothed
Over-scaled deformation
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• Tensor analysis:– Shape factors by [Westin97]– Stress/strain are 3x3 symmetric tensors– 3 Eigen-Values:
– Shape factors:
[BBHKS06]
Visualization
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• Direct stress tensor visualization:– Ellipsoids representing the shape factors– Tensor Splats [BengerHege04]
-> barycentric
Visualization
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• Direct stress tensor visualization:– Ellipsoids representing the shape factors– Tensor Splats [BengerHege04]
-> barycentric
Visualization
Works only for positive Eigenvalues!
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• Direct stress tensor visualization:– Ellipsoids representing the shape factors– Tensor Splats [BengerHege04]
-> barycentric[BBHKS06]
Visualization
Works only for positive Eigenvalues!
Enhancement:Color a splat in blue, when any Eigenvalues is negative
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Visualization
• Drying simulation:– Tensor splats:
Biaxial tension
Uniaxial tension
Pressure region
+ Multiple stress directions+ Tension vs pressure regions
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• Scalar fields by volume rendering:– Texture based volume rendering ( requires resampling on
uniform grid to be improved)– Shows inner structure of data fields– Example: tri-axial compression of a cuboid
Visualization
and Mises in ABAQUS and Mises via volume rendering
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• Drying simulation:– After 30 days of drying– Volume rendering of drying shrinkage – Cages show an uplift of the corner and the edges
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• Dual volume rendering:– One scalar field controls color– Another controls transparency
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Conclusion &Future Work
10.7.2013, Vienna
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Fiber bundle data model for FEM• Captures many other types of scientific data• Comes with an HDF5 based data format (big data)
Good for collaborations and transparent data storage
Visualization:• Colored cages • Direct tensor field visualization• Scalar fields via volume rendering• Dual volume rendering
Future work:• Enhancing the direct tensor field visualization• Volume rendering on the FEM grid (GPU raycasting)• Support more FEM data (also shells)
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-The END-
10.7.2013, Vienna
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• Balance equations of the multiphase modelMass of the water w
Mass of the steam gw
Mass of the dry air ga
Mass of the solid phase s
Enthalpy of the whole system
Impulse of the whole system
Numerical Simulation