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Process Systems Engineering Laboratory

Process Systems Engineering Laboratory

PSEL@MIT

Software

  • DAEPACK
    • Overview
    • Features
      • Symbolic components
      • Numeric Components
    • Examples
      • Tennessee Eastman Process Control Challenge Problem
      • MINPACK-2 Test Problem IAP
      • MINPACK-2 Test Problem SFI
      • MINPACK-2 Test Problem IER
      • MINPACK-2 Test Problem FIC
      • MINPACK-2 Test Problem DCF
      • MINPACK-2 Test Problem EPT
    • Grapical Interface
    • Applications
    • Documentation
    • Licensing
    • Bibliography
  • DFBSIM
    • How to use DFBSIM
    • How to obtain DFBSIM
    • Example
      • Simulation file
      • Environment file
      • Uptake kinetics
      • Running DFBSIM
      • Bibliography
    • Bibliography
    • Whom to contact
  • CompGraph
    • How to obtain CompGraph
    • How to use CompGraph
    • Bibliography
  • DFBAlab
    • How to use DFBAlab
    • How to obtain DFBAlab
    • Example
      • Simulation file
      • Environment file
      • Uptake kinetics
      • Bibliography
    • Bibliography
  • DSL48S
  • GDOC
    • How to use GDOC
    • How to obtain GDOC
      • GDOC-1.0 License Terms and Conditions
    • Who uses it
    • Example
      • Mathematical Description
      • Input and Data Files
      • Running GDOC
      • References
    • Whom to contact
    • Bibliography
  • Jacobian
  • PSD Bounding Tools
  • libMC
    • Definitions
    • How to obtain libMC
    • How to use libMC
    • Whom to contact
    • Bibliography

Tennessee Eastman Process Control Challenge Problem

This is a FORTRAN model of the Tennessee Eastman process control challenge problem. The model consists of 50 equation and 50 variables. The sparsity pattern, shown on the right, has been automatically generated using DAEPACK.

Automatically generated derivative code

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Recent Publications

  • •

    Level sets of nonsmooth functions, part 2: Lipschitz and piecewise-differentiable manifolds

  • •

    Evaluating Economic Feasibility of Liquid Air Energy Storage Systems in Future US Electricity Markets

  • •

    Tighter Bounds on Transient Moments of Stochastic Chemical Systems

  • •

    Generalized derivatives of optimal-value functions with parameterized convex programs embedded

More…

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