Trajectory optimization of an oscillating industrial two-stage evaporator utilizing a Python-Aspen Plus Dynamics toolchain

Research output: Contribution to journalArticle


Evaporators are integral parts of many separation processes across production industries, and they need to be well understood in order to be operated well, thereby enabling high resource-efficiency and productivity. In a previous investigation, the effects of disturbing oscillations in a two-stage evaporator system were quantified. In the current study, these oscillations were reduced through trajectory optimization using steam consumption as a temporally discretized decision variable, taking advantage of a dynamic process flowsheet model in Aspen Plus Dynamics (APD) employed as if it were a black-box model. The optimization was performed utilizing a Python-APD toolchain with the SciPy implementation of COBYLA. The optimal trajectory was able to successfully reduce the objective function value (including the product stream mass flow variance and a bang-bang penalty on the trajectory itself) to slightly less than 0.3 % of that of the nominal case, in which a time-invariant steam consumption was employed. This in turn grants opportunities to increase throughput of the process, leading to significant financial gains.


External organisations
  • Perstorp AB
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Chemical Process Engineering


  • Aspen Plus Dynamics, Derivative-free optimization, Dynamic optimization, Evaporator system, Oscillations, Python
Original languageEnglish
Pages (from-to)12-17
Number of pages6
JournalChemical Engineering Research and Design
Publication statusPublished - 2020 Mar 1
Publication categoryResearch