DAE Tools is a collection of software tools for modeling, simulation, and optimization of dynamic and steady state processes. It was initially developed to model and simulate processes in chemical process industry (mass, heat, and momentum transfers, chemical reactions, separation processes, and thermodynamics). However, high-accuracy models of (in general) many different kind of processes and phenomena can be developed and simulated/optimized, and the results visualized.
| Tags | Simulation Optimization Visualization modelling Scientific/Engineering computing |
|---|---|
| Licenses | GPLv3 |
| Operating Systems | GNU/Linux Windows |
| Implementation | C++ Python |
Recent releases


Release Notes: This release has a new type of ports (Event ports) and a new function (ON_EVENT) in the daeModel class that specifies how the incoming events on a specific event port are handled. A new way of handling state transitions: the function ON_CONDITION in daeModel that specifies actions to be undertaken when the logical condition is satisfied. Non-linear least square minimization (the scipy wrapper of Minpack). Examples of DAE Tools and Scipy interoperability (scipy.optimize). Shell scripts to compile third party libraries and DAE Tools modules. Tutorials are available in C++ (cDAE). Several small bugfixes and enhancements.


Release Notes: New linear solvers were added: Standalone SuperLU_MT (multithreaded sparse direct), Trilinos AztecOO (iterative Krylov; Ifpack, ML, or built-in preconditioners), and NVidia CUDA enabled (experimental): CUSP (iterative Krylov), SuperLU_CUDA (sparse direct). New NLP solvers were added: NLOPT (from the Massachusetts Institute of Technology) and a Standalone IPOPT solver. Models can now be exported to pyDAE and cDAE. A new data reporter exports results in the Matlab MAT file format.


Release Notes: Optimization of steady-state and dynamic processes (IPOPT/Bonmin) was implemented. Several new features were added. Bugs were fixed.