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Cascade Optimization Using Controlled Random Search Algorithm and CFD Techniques for ORC Application
UNIFEI - Federal University of Itajubá Brazil. (MERO)
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. (MERO)
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. (MERO)ORCID iD: 0000-0002-8466-356X
UNIFEI - Federal University of Itajubá Brazil.
2016 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The methodology for performance optimization of a cascade using CFD techniques for ORC (Organic Rankine Cycle) application are presented. The turbine ORC cascade is parameterized to achieve the maximum efficiency while using different organics fluids. The main objective of this work is to attain a maximal Cl/Cd ratio from a preliminary design. The CRSA (Controlled Random Search Algorithm) was chosen for the optimization process integrated with CFD techniques, using schemes with automatic building of parameterized geometries and meshes via "script files" interpreted by the commercial software ICEM-CFD®. Finally, for the numerical calculation of the fluid flow, the commercial software FLUENT® is used with the fluids properties, the real gases model, the turbulence model and the boundary conditions being set through "journal files". In this paper, R245fa and Toluene are used as working fluids, chosen for their characteristics curves being very different, directly influencing the behavior of the fluid during its expansion process. The results show that the methodology allows for making corrections in the initial design of the cascade shape. It will be necessary to introduce the camber function to correct for the separation of the boundary layer in the trailing edge, which is a proposal for future work.

Place, publisher, year, edition, pages
2016.
Keyword [en]
ORC; optimization; CFD; CRSA; turbomachinery; real gas; equations of state.
National Category
Energy Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-33291OAI: oai:DiVA.org:mdh-33291DiVA: diva2:1045385
Conference
9th EUROSIM Congress on Modelling and Simulation, EUROSIM2016
Available from: 2016-11-09 Created: 2016-09-29 Last updated: 2017-06-07Bibliographically approved

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Authority records BETA

Kyprianidis, Konstantinos G.

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
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  • Other locale
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Output format
  • html
  • text
  • asciidoc
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