DAETools

DAETools

DAETools is an open-source software framework for modeling and simulation of differential-algebraic equation (DAE) systems. It provides tools for modeling physical systems described by DAEs and simulating them using advanced numerical methods.
differential-equations numerical-methods simulation modeling open-source

DAETools: Open-Source Framework for Modeling & Simulation of Differential-Algebraic Equations

DAETools is an open-source software framework for modeling and simulation of differential-algebraic equation (DAE) systems. It provides tools for modeling physical systems described by DAEs and simulating them using advanced numerical methods.

What is DAETools?

DAETools is an open-source software framework designed for modeling and simulation of large-scale systems of differential-algebraic equations (DAEs), ordinary differential equations (ODEs) and partial differential equations (PDEs). It is suitable for a wide range of applications including chemical processes, energy systems, biological systems, fluid dynamics, mechanical systems and more.

Some of the key features of DAETools include:

  • An object-oriented approach to modeling complex DAE systems
  • Support for large, sparse systems through vectorization and exploitation of sparsity patterns
  • Advanced numerical methods such as DAE solvers, linear solvers, ODE/DAE sensitivity analysis
  • Scripting interface for Python to facilitate model development and custom numerical methods
  • Versatile postprocessing through integrated plotting library
  • Parallel computation capabilities for increased simulation speed

DAETools enables users to focus more on the modeling without worrying about underlying mathematics and numerical analysis. Models can be rapidly built up from basic equation-oriented components while retaining the ability to customize and extend almost every aspect of the modeling and simulation workflow. An extensive collection of examples helps new users come up to speed.

DAETools Features

Features

  1. Modeling of DAE systems
  2. Simulation using advanced numerical methods
  3. Linear and nonlinear solvers
  4. Automatic differentiation
  5. Optimization
  6. Parameter estimation
  7. Uncertainty quantification
  8. Parallel computing support
  9. Visualization and data analysis tools

Pricing

  • Open Source

Pros

Open source and free

Flexible architecture

Python API for easy scripting and customization

Good documentation and examples

Active community support

Cons

Steep learning curve

Limited number of ready-to-use components

Not as feature rich as commercial tools like gPROMS


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