ASTRO@UIBK
Center for Computation and Technology
Visualization of finite element data of a
multi-phase concrete model
M. Ritter1, M. Aschaber1, W. Benger2, G. Hofstetter1
1 University
of Innsbruck, Austria
2 Louisiana State University, USA
10.7.2013, Vienna
• Outline
– Motivation
– Numerical Simulation
– Data Modeling
– Visualization
– Conclusion & Future Work
Motivation
• Motivation:
Scientific Visualization
Techniques and
Research
Engineering Simulation
Tools and Visualization
by Neal Stone
Gap
Motivation
• Motivation:
Scientific Visualization
Techniques and
Research
Engineering Simulation
Tools and Visualization
by Neal Stone
Motivation
• Motivation:
• Simulation techniques are used more frequently
• Produced data sets growing
• Data complexity is increasing
• Visualization used for data interpretation of results
is important.
10.7.2013, Vienna
Numerical Simulation
• Aim:
– More realistic simulation of drying shrinkage
• Application:
– Strengthening of a RC structure by adding an overlay
New top concrete layer
Old concrete structure
Numerical Simulation
• Drying shrinkage:
–
–
–
–
Long term drying process in concrete
Decrease of relative pore humidity
Increase of capillary pressure
Capillary pressure results in volumetric shrinkage
drying
concrete
Numerical Simulation
• Drying Shrinkage:
New top concrete layer
Old concrete structure
Different internal stresses
Critical region at joint
Drying shrinkage
Swelling
concrete
Numerical Simulation
• Numerical Simulation:
– Finite element simulation on multiple grids of
concrete specimen
– Hexahedral Mesh of 9 x 9 x 13 Cells
100 x 100 x 56 mm
Numerical Simulation
• Numerical Simulation:
– Finite element simulation on multiple grids of
concrete specimen
– Hexahedral Mesh of 9 x 9 x 13 Cells
Undeformed linear element
Deformed quadratic element
The element has curved faces
Numerical Simulation
Numerical
Simulation:
• Multiphase concrete model
• Solid, water, and gas phase
(dry air and water vapor)
• Coupled hygral-thermo-mechanical
model
Governing
equations:
• Balance equations
• Mass
• Enthalpy
• Linear Momentum
• Linear kinematic relations
• Constitutive equations
Multiple solution variables (Data fields)
• Gas pressure
• Capillary pressure
• Displacements
• Temperature
scalar
scalar
vector
scalar
Derived data fields
• Strain
• Stress
2nd order tensor
2nd order tensor
Numerical Simulation
• Drying shrinkage ε𝑠ℎ
– Effective stress:
– Hydrostatic pressure of the water on the solid phase:
10.7.2013, Vienna
Data Modeling
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
Fiber Bundle Data Model
Inspired by concepts of:
Topology
Differential Geometry
Geometric Algebra
Separation of Geometry (Grids) and Datafield (Fields)
Grid
Field
Data Modeling
Grid
the base space
• Manifold describing the base space
• Topology
• Refinement level
• Coordinate representation
• Vertex positions in representation
• Neighborhood
Data Modeling
Field
the fiber
space
• 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
Data Modeling
• Hierarchical structure:
Data Modeling
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
Data Modeling
• Data at Vertices:
(optional)
(optional)
Data Modeling
• Data at Integration Points:
No positions  can be computed
Data Modeling
• Sets of Nodes and Sets of Elements:
Indices of vertices in named fragments
Indices of integration points
in named fragments
Data Modeling
• Linked groups for alternative data access:
– E.g. time frames and time steps in ABAQUS
Li
nk
Bundle - frames
Bundle - steps
T=0.0
T=0.0
Link
T=0.2
T=1.0
T=0.4
T=0.6
T=0.8
T=1.0
T=1.2
T=1.4
No data stored
Data Modeling
FEM - Example
HDF5 Based Data format:
 independent, free, open, data browser
www.hdfgroup.org
10.7.2013, Vienna
Visualization
Visualization Shell VISH
• 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
Visualization
Visualization
• 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
• Colored Cages
– Integration point data is extrapolated and averaged on demand
Extrapolation from integration points
Over-scaled deformation
Averaged,
smoothed
Visualization
• Tensor analysis:
– Shape factors by [Westin97]
– Stress/strain are 3x3 symmetric tensors
– 3 Eigen-Values:
– Shape factors:
[BBHKS06]
Visualization
• Direct stress tensor visualization:
– Ellipsoids representing the shape factors
– Tensor Splats [BengerHege04]
-> barycentric
Visualization
• Direct stress tensor visualization:
– Ellipsoids representing the shape factors
– Tensor Splats [BengerHege04]
Works only for positive
Eigenvalues!
-> barycentric
Visualization
• Direct stress tensor visualization:
– Ellipsoids representing the shape factors
– Tensor Splats [BengerHege04]
Works only for positive
Eigenvalues!
 Enhancement:
Color a splat in blue, when
any Eigenvalues is negative
-> barycentric
Visualization
• Drying simulation:
– Tensor splats:
Biaxial tension
Uniaxial tension
Pressure region
+ Multiple stress directions
+ Tension vs pressure regions
Visualization
• 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
σ𝑚 and Mises in ABAQUS
σ𝑚 and Mises via volume rendering
• Drying simulation:
– After 30 days of drying
– Volume rendering of drying shrinkage ε𝑠ℎ
– Cages show an uplift of the corner and the edges
• Dual volume rendering:
– One scalar field controls color
– Another controls transparency
10.7.2013, Vienna
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)
10.7.2013, Vienna
Numerical Simulation
• Balance equations of the multiphase model
Mass 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