Trajectory optimization of an oscillating industrial two-stage evaporator utilizing a Python-Aspen Plus Dynamics toolchain
Artikel i vetenskaplig tidskrift, 2020

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.

derivative-free optimization

dynamic optimization

Aspen Plus Dynamics


evaporator system



Mikael Nolin

Lunds universitet

Niklas Andersson

Lunds universitet

Bernt Nilsson

Lunds universitet

Mark Max-Hansen

Perstorp AB

Oleg Pajalic

Perstorp AB

Chemical Engineering Research and Design

0263-8762 (ISSN) 1744-3563 (eISSN)

Vol. 155 12-17





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