CFD Modelling as an Integrated Part of
Multi-Level Simulation of Process Plants
– Semantic Modelling Approach
Marek Gayer, Juha Kortelainen and Tommi Karhela
www.marekgayer.com www.simantic.org
Technical Research Centre of Finland (VTT), Espoo
www.vtt.fi
42th Summer Computer Simulation Conference,
Ottawa, Canada, 11. – 15. July, 2010.
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Presentation outline - What we are using and doing?
 We are developing process simulators software (for e.g. plants)
 We are using “semantic” based software tools for that
 We have a software platform for easy building and connecting such
and other simulation applications
 We are building a 3D CFD simulation environment for this platform
 We want to optimally connect 1D process and 3D CFD simulations
 Our CFD software includes pre/post processing - defining
geometry, meshing, boundary conditions, solver, visualization, of
the modeled case
 We are using open source technologies for that
 We are using OpenFOAM in the 3D CFD environment and plan
to use and integrate also other solvers, including commercial
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Dynamic process simulation tools are used for example in:
 Nuclear energy sector for planning
 Operator support and training
 Operation state analysis
 Automation design and testing
 Safety analysis, and verifications the power plant lifecycle.
 The advantages gained using these tools and methods can result
in significant time and money savings, and improved safety.
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Demystifying “semantic modelling approach” and
Semantic graph
 Defining semantics ~ Adding “meaning” of data objects by specifying their
relations and by annotating them using statements.
 Based on ontologies (basically “objects and relations between them”
model, see: http://en.wikipedia.org/wiki/Ontology_(information_science)
 Data consists of resources, statements (forming triplets) and literals.
 Resource: a node of the graph. A resource has a unique identity.
 Statement: an edge of the graph. A statement consists of three
resources: subject, predicate (relation), object.
 Literal: any binary data attached to a resource.
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APROS 6 – Process simulator based on Simantics
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Example – Ontology based simulation model
configuration in APROS 6
Different modelling
and simulation
approaches are
modelled as
ontologies and
mapped together to
form a consistent
graph of model
configurations.
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Simantics based Modelica version - modeling language for
component-oriented modeling of complex systems
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Example – model configuration ontologies in
Modelica
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Simantics Ontology Development application
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Semantic modelling in simulation
 Using few concepts and building blocks, we can describe
 Control and storage of simulation model and experiments
configuration data and tasks
 Used data structures, flows and it’s relations
 Annotations for real-time gained results
 Higher level semantic language abstractions (Layer 0,
APROS, Modelica)
 Extendibility – all data described by the same simple model
 Using semantics in process simulations is quite a new concept
 Building software applications based on platform “Simantics”
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Plug-in Architecture for Modelling and Simulation
Plug-in
Plug-in

APROS simulation engine
Plug-in
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OpenFOAM based
3D CFD simulation
environment
Plug-in
Elmer FEM-based
multi-physics simulation
environment
BALAS simulation engine
Plug-in

VTT-Talo building
simulation environment
Plug-in
OpenModelica system
simulation environment
NuSMV
Model checking environment
Plug-in
Simantics Platform
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Plug-in
Eclipse based application framework
2D diagram framework
OpenCASCADE 3D geometry kernel
VTK post-processing and visualisation tools
…
Editors (text, 2D diagram, 3D geometry)
Structural data handling and mapping
Project/team management tools
Distributed modelling and simulation facilities
…

PhaseField solidification
modelling
Plug-in
System dynamics
environment
Plug-in
Simantics Core
Triplestore modelling
database management
Simantics Databoard
Simulation results and
real time
data management
For more information, visit: www.simantics.org
???
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Linking 1D process simulation and 3D CFD
 Mapping of the mass and heat
flow variables between the
models
 At in/outflow boundaries, reduce
the flow variables of the 3D to 1D
 Numerical stability - important
issue
 Necessary to establish
appropriate interfaces and
standards
 CFD modelling environment
with pre-processing, postprocessing, solver OpenFOAM,
visualization
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CFD modelling overview of our software prototype
Post-processing
Input
data,
files,
etc.
PRE-PROCESSING
Geometry
Boundary
conditions
Mesh
Case
configuration
Results
POST-PRO.
Results
Simulation case
Internal
Visualization
External
visualization
SOLVING
OpenFOAM
Permanent
storage
Other
solvers
Actuation --- Feedback
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Our CFD environment based on OpenFOAM
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Pre-processing - Geometry
 OpenCASCADE for importing CAD
models (STEP, IGES, BREP)
 Using Open CASCADE would also
provide interactive geometry editor.
In the present version of the
environment, this feature is
however missing.
 Visualization based on VTK
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Pre-processing - Meshing
 Currently NETGEN tetrahedron
meshing
 Integrated as command line tool
 Built as custom executable
 Some experiences with
hexahedron meshes
(snappyHexMesh)
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Using OpenFOAM solver
 Integrated as command line tools, which are launched from our
environment
 Using OpenFOAM 1.5 (SF openfoam-mswin) and 1.6 (BlueCFD)
 Currently 2 test experiments
 Tank – (compressible, turbulent flow - rhoTurbFoam)
 S-pipe – (imcompressible flow - icoFoam)
 Currently dictionaries in cases directories are edited separately
 We plan to create ontological representation of OpenFOAM cases
dictionaries, - based on sample dictionaries bundled with OF
 This way ontologies will be presented in the user interface and
from which OpenFOAM dictionaries files will be generated
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Post-processing – Visualization of OpenFOAM results
 Using VTK
 Surface plots
 Mapping of variables
 3D cuts
 Streamlines
 Iso-surfaces
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Additional future work includes:
 Boundary conditions module, preferably independent on the solver
 Using additional solvers, including some commercial
 Establish data transfer and interfaces between process simulation
models (1D) and 3D CFD link using Ontologies based interface
 Higher level ontological representation of simulation configuration
(e.g. without specifying too much details) and possible to work with
various solvers
 FEM tools integration (e.g. for structural analysis)
 More simulation cases and more work with OpenFOAM
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VTT creates business from
technology
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