| 1. |
- Yamanee-Nolin, Mikael, et al.
(author)
-
Analysis of an oscillating two-stage evaporator system through modelling and simulation: An industrial case study
- 2017
-
In: Chemical Engineering Transactions. - 2283-9216. ; 69, s. 481-486
-
Journal article (peer-reviewed)abstract
- With increasing demands on the industry for resource efficiency, processes are often built or retrofitted with recycle streams in order to decrease energy and raw material demands. However, this also increases the complexity of the process as a whole and may bring unexpected effects. In this contribution, such a case, consisting of a two-stage evaporator system, fed with the product stream of an upstream batch system and a continuous recycling stream from downstream separation processes, was analyzed. This evaporator system was subject to potentially performance-limiting oscillating disturbances. The purpose of this study was to, through modelling and simulation, expand the knowledge of the system by analyzing the system dynamics, and to discover any co-oscillations and their extent in the process, as well as their effect on process parameters such as product purity and the energy usage in terms of steam consumption. The investigation was performed by modelling using Aspen Plus Dynamics. Simulation, data-extraction, and analysis was performed via a COM enabled Python interface. The results of the study highlight the full-system propagation of oscillations along with co-oscillation of selected key parameters, and support the conclusion that there is potential for cost-reductions by decreasing steam consumption by 1.1 %, without any investments.
|
|
| 2. |
- Yamanee-Nolin, Mikael, et al.
(author)
-
Unbiased Selection of Decision Variables for Optimization
- 2017
-
In: 27 European Symposium on Computer Aided Process Engineering. - 1570-7946. - 9780444639653 ; 40, s. 253-258
-
Conference paper (peer-reviewed)abstract
- Complex chemical processes require complex simulation models. Selecting decision variables for optimization is increasingly difficult. This paper presents a study of a Subset Selection Algorithm (SSA) applied to the selection of decision variables to facili-tate a reduction of the decision variable combination sets to consider for a process designer, aimed towards improving said selection, optimization, and thereby resource efficiency. The results help conclude that SSA is able to reduce the consideration set of decision variable combinations for the process designer, and selects combination sets that are more effective in terms of minimizing the objective.
|
|
