Current Software Developments
|name||license||problem class||programming language||contact|
|DaStGen||BSD-like||Data structure generator for scientific datatypes in C++||Java||Wolfgang Eckhardt, Tobias Weinzierl|
|Peano||BSD-like||PDE solver framework with CFD/Poisson solver/heat equation plugin||C++||Tobias Neckel, Tobias Weinzierl|
|preCICE||t.b.a.||Multiphysics coupling||C++||Bernhard Gatzhammer|
|TifaMMy||t.b.a.||TifaMMy isn't the fastest matrix multiplication, yet||C++||Michael Bader, Alexander Heinecke|
Finished Software Developments
|name||problem class||programming language||contact|
|SToRM||computational steering||C++||Martin Bernreuther|
|F3F||numerical fluid dynamics||C||Ioan Lucian Muntean|
|quadfluid||numerical fluid dynamics||matlab||Tobias Neckel|
|quickfluid||numerical fluid dynamics||matlab||Tobias Neckel|
|FSI*ce||multiphysics simulations||C++||Bernhard Gatzhammer|
|Nast||numerical fluid dynamics||C++||Miriam Mehl|
|NaSt2D/3D||numerical fluid dynamics||C||Michael Bader|
|Sparse Grids||sparse grid solvers||C||Stefan Zimmer|
|FlowSi||combination method||C||Stefan Zimmer|
|Pendulum||BGCE project: self-erecting pendulum||Matlab/Simulink/C||Martin Buchholz|
DaStGen is a data structure generator, designed and written by Wolfgang Eckhardt and Tobias Weinzierl in 2007. DaStGen reads a record specification and creates corresponding C++ types. Its most prominent features are:
- Packs different data types, i.e. if two bools are assigned to one record, these two records are stored within one integer. DaStGen is able to back the types enum, integer, bool and double.
- Creates corresponding setter and getter oerations, along with other utility funcions like toString().
- Automatic generation of a derived MPI-Datatype
DaStGen is available at www5.in.tum.de/dastgen
preCICE (Precise Code Interaction Coupling Environment) is a coupling tool for partitioned simulations of multi-physics scenarios. Partitioned means, that existing programs capable of simulating a subpart of the complete physics involved in the complete simulation, are taken and coupled together. The conceptual ideas of preCICE are not completely new, preCICE is basically an advancement of FSI*ce which has been developed by Markus Brenk.
The main goals of preCICE are the following:
- Provide a high-level programming environment for all basic tasks appearing in the development of partitioned coupling simulation tools, i.e. communication, data mapping, and transient coupling schemes.
- Exploit the flexibility coming with the partitioned approach.
- Serve as a basis for the development of new coupling algortihms, methodologies and functionalities.
Peano is a framework for mesh-based PDE solvers. Among Peano's highlights are the support of
- Arbitrary dimensions
- Multiscale solvers and models
- Parallel on distributed memory and multicores
- Low memory demands
- High cache efficiency
- Dynamic h-adaptivity
There's a couple of plugins for this framework available with a sophisticated fluid solver being perhaps the most prominent one. We are right now discussing the legal status of the source code. Afterwards, Peano will be available here. Peano is available at www5.in.tum.de/peano
The aim of FSI*ce is the development of a modular simulation environment for a class of coupled problems as large as possible. The modular approach means here that the modelling as well as the programming effort shall be highly reduced by the use of already available program codes. This leads to a great flexibility regarding the treated problems as well as the used codes. In addition, a structuring is given, which e. g. simplifies the distributed computation of the system.
For that purpose , FSI*ce includes:
- a "coupling language" for a specification of the coupling,
- efficient iteration methods,
- well-defined interfaces between the control modul and each of the involved simulation codes,
- conversion moduls between the different data representations,
- a general description of the geometry with adaptation possibilities to the used programms, e. g. for the connection to CAD systems,
- modules for the realization and synchronisation of the data transport.
First investigations were made on the basis of the two- and threedimensional simulation of the fluid-structure interaction in a valve-driven micro pump. As CFD-solver, we used #F3F, which was developed at the chair, as structure solver, we used ADINA, NASTRAN and AdHoc, which was developed at the chair for Computing in Engineering.
description coming soon
Matlab package for the numerical simulation of 2D laminar, incompressible fluid flow on adaptive grids
quadfluid solves the unsteady Navier-Stokes equations in two dimension on adaptive Cartesian grids (quadtree) as a testbed for mathematical and physical methods in the context of flow simulation.
Based on the Chorin projection method, the time discretisation of the momentum equations is done by an explicit Euler method. The discretisation of the space is realised by bilinear elements for the velocities using constant pressure per cell as the corresponding Lagrangeian multiplier for the continuity constraint. In each time step, thus, a linear system of equations (the discrete pressure poisson equation) is solved whose solution is used to update the velocities for the next time step. For the calculation of force values (on obstacles, e.g.), the method of consistent forces is used. Special care (interpolation etc.) is applied whenever coarser and finer grid cells touch each other.
Screenshot of the matlab-GUI
Via the use of obstacle node lists, arbitrary geometries can be used in a rectangular domain. Built in scenarios are e.g. driven cavity, free channel flow, cylinder channel benchmarks, and the CFD1 benchmark of the Forschergruppe 493 zur Fluid-Struktur-Wechselwirkung.
This is an extension of the version for regular grids: quickfluid.
The program package comes with an easy to use visualisation GUI called quadvis.
A version of this matlab package is available by contacting Tobias Neckel
Matlab package for the numerical simulation of 2D laminar, incompressible fluid flow
quickfluid solves the unsteady Navier-Stokes equations in two dimension on (regular) Cartesian grids as a testbed for mathematical and physical methods in the context of flow simulation.
Based on the Chorin projection method, the time discretisation of the momentum equations is done by an explicit Euler method. The discretisation of the space is realised by bilinear elements for the velocities using constant pressure per cell as the corresponding Lagrangeian multiplier for the continuity constraint. In each time step, thus, a linear system of equations (the discrete pressure poisson equation) is solved whose solution is used to update the velocities for the next time step. For the calculation of force values (on obstacles, e.g.), the method of consistent forces is used.
Screenshot of the matlab-GUI
Via the use of obstacle node lists, arbitrary geometries can be used in a rectangular domain. Built in scenarios are e.g. driven cavity, free channel flow, and cylinder channel benchmarks.
An extension to adaptive cartesian grids exists and is named quadfluid.
The program package comes with an easy to use visualisation GUI called quickvis.
A GNU GPL version of this matlab package is available by contacting Tobias Neckel
The task of Nast++ is the simulation of instationary laminar flows of incompressible fluids in two and three dimensions. The underlying mathematical model are the Navier-Stokes equations.
The Navier-Stokes equations are discretised via finite differences on a staggered grid. Using a projection method, we get a Poisson equation for the pressure. The resulting pressure field is used to guaranty the mass conservation property of the method.
Programm zur numerischen Simulation laminarer Strömungen viskoser, inkompressibler Fluide in zwei und drei Raumdimensionen.
Das Programm Nast sowie die zugrunde liegenden numerischen Verfahren sind beschrieben in:
Michael Griebel, Thomas Dornseifer, Tilman Neunhoeffer:
Numerische Simulation in der Strömungsmechanik - eine praxisorientierte Einführung, Vieweg, 1995.
NaSt2D/NaSt3D behandelt die instationären Navier-Stokes-Gleichungen in zwei bzw. drei Raumdimensionen. Grundlage ist die Chorinsche Projektionsmethode. Die Zeitdiskretisierung der Impulsgleichungen erfolgt durch ein explizites Eulerverfahren. Der Ortsdiskretisierung liegt ein finites Differenzenverfahren auf einem versetzten äquidistanten Gitter zugrunde. Die konvektiven Terme der Impulsgleichung werden durch Flux-Blending diskretisiert, d.h. es ist eine Mittelung aus zentralen Differenzen und Upwind-Differenzen (Donor-Cell-Schema) möglich. Durch Flagfelder können beliebige Gebiete des rechteckigen Grundgebietes ausgeblendet werden, so daß auch stark zerklüftete Strömungsgebiete behandelt werden können.
Es können folgende Problemklassen behandelt werden:
- Strömungen in festen Geometrien
- Temperaturgetriebene Strömungen mittels Boussinesq-Approximation
- Transport chemischer Stoffe
- Freie Randwertprobleme mit dem Marker-und-Cell Verfahren
Die Eingabe der Parameter erfolgt durch problemspezifische Eingabedateien.
A powerfull tool for the solution of elliptic partial differential equations is the concept of hierarchical bases: they allow for a simple construction of adaptive grids and lead to a much faster convergence of iterative solvers. If, in addition, hierarchical grids with different aspect ratios (so-called Sparse Grids) are used, the complexity that is the dimension of the solution space can be reduced substantially without accuracy losses.
Two standard examples for Sparse Grids in 2D and 3D:
The software can be applied to 2D and 3D scenarios and allows for adaptive refinements and higher order discretisation schemes.
The combination method leads to solutions on Sparse Grids. It's a special case of a multivariate extrapolation scheme. The computations are performed distributedly on the single grids involved in the combination process.
The combination method can be seen as an enhancement of existing algorithms. Such, existing codes canbe reused. The method can be parallelised in a trivial way. In the existing version, a process parallel approach was chosen. The storage requirements reduse to O(N) in comparison to O(N^3) for previous approaches on full grids with similar accuracy (N is the number of grid points per coordinate direction).
The method is implemented for
- Poisson-like problems on the unit square/cube
- laminar flow scenarios in simple and complex geometries
- turbulent flow scenarios (via DNS) in simple geometries.
Programm zur parallelen, adaptiven numerischen Simulation mit Hilfe der Finite-Element-Methode
ARESO is a divide-and-conquer approach based on an adaptive, recursive decomposition of technical objects according to the substructure technique. The top-down decomposition allows for the distribution of data and for the parallelisation on a heterogeneous workstation network.
ARESO can be used for general engineering problems and supports the teamwork of engineers in the numerical simulation of technical objects. Existing routines or codes can be used for the computation on subdomains as ARESO offers interfaces for their link-up.
In the algorithm, direct as well as iterative solvers based on mathematical methods such as hierarchical bases, adaptive relaxation are implemented. The solvers work highly memory efficient on the basis of the Jacobi and the conjugate gradient method. Also the combined usage of the methods - direct solvers for small subdomain, iterative solvers for large ones - is possible.
The following problem classes can be handled:
- stationary heat equation,
- linear planar elasticity,
- convection-diffusion scenarios.
The current version of the code is written in Java. Thereby, the upper coordination layer in the functional language FASAN offers a highly flexible possibiliy for parallelisation and distribution and is translated into Java as well by the FASAN compiler. Existing, mostly written in C or FORTRAN, programs can be integrated via the Java Native Interface (JNI) into ARESO.
MSPAI is a preconditioner for large sparse and ill-conditioned systems of
linear equations. We extended the basic SPAI minimization
to target form and further generalized it in order to add additional probing constraints:
TifaMMy (TifaMMy isn't the fastest matrix multiplication, yet) is an implementation of the Peano-curve algorithm for matrix multiplication. It is intended as a student project, and available on http://sourceforge.net/projects/tifammy/.