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Performance and model calibration ofhigh-pressure compressors
KTH, School of Industrial Engineering and Management (ITM), Energy Technology.
2018 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

To fully determine the performances of high-pressure compressors (HPC), modeling and partial tests can beperformed to characterize its different operating conditions. Nevertheless, there are still noticeable errorsbetween the results of these models and the tests: deformations and differences can appear, and notably becauseof a modeling defect or the assumptions made during the analysis (measurement corrections for example). Tomodel the closest to the tests, it is therefore necessary to include all the different elements impacting theperformances of the compressor performance map to model the operating points correctly. The purpose ofthe thesis is to take in charge a new software that predicts the performances of high-pressure compressors,built in Python where a compressor can be decomposed in elementary axial and/or centrifugal compressorsusing their respective compressor performance map. By a stacking technique it is possible to characterize theoperating point of the main compressor by knowing the inlet and the outlet conditions, and to include severaldeformation models such as Reynolds number effects, Variable Stator Vanes (VSV) effects, or tip clearanceeffects on the performances of the compressor. A calibration function also allows the development of newversions of the previous deformations models and it quantifies the unknowns and uncertainties betweencomputed and tested results. Several working points at off-design conditions were computed with specificoperating conditions such as the opening of a handling bleed valve. Deformations models of this specificcondition was built to mitigate the uncertainties between computed and tested results and include thephenomenon to the modeling. Several deformations models were also compared for efficiency purposes.

Abstract [sv]

För att fullt ut kunna bestämma prestanda hos högtryckskompressorer (HPC) kan modellering och delprovutföras för att karakterisera kompressorns olika driftsförhållanden. Det finns emellertid fortfarande märkbaraskillnader mellan resultaten av dessa modeller och testerna: deformationer och skillnader kan uppstå på grundav en modelleringsdefekt eller antaganden som har gjorts under analysen (t.ex. mätkorrigeringar). För att närmamodellen till prov är det därför nödvändigt att inkludera alla de olika elementen som påverkar kompressornsprestanda för att korrekt modellera de olika arbetspunkterna i en kompressor mapp. Syftet med avhandlingenär att implementera en ny Python-baserad programvara som förutspår prestationerna hoshögtryckskompressorer, där en kompressor kan brytas ner i elementära axiella och / ellercentrifugalkompressorer med tillhörande kompressor prestandamappar. Med en staplingsteknik är det möjligtatt karakterisera huvudkompressorns driftspunkt genom att känna till förhållanden vid inloppet och utloppetav huvudkompressorn. Modellen inkluderar olika effekter som Reynolds-tal effekter, ”Variable Stator Vanes”-effekter (VSV) eller påverkan av toppspel. En kalibreringsfunktion tillåter också utveckling av nya versioner avtidigare modeller och kvantifierar osäkerheter och skillnader mellan resultat från simuleringar och de frånprövningar. Flera arbetspunkter vid off-design-förhållanden simulerades med specifika driftsförhållanden,såsom öppnandet av avtappningsventiler (”bleed air valves”) och deformationsmodeller för dessa specifikatillstånd togs fram för att minska osäkerheten hos simuleringsresultat.

Place, publisher, year, edition, pages
2018. , p. 52
Series
TRITA-ITM-EX ; 2018:22
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-232326OAI: oai:DiVA.org:kth-232326DiVA, id: diva2:1233594
Supervisors
Examiners
Available from: 2018-07-18 Created: 2018-07-18 Last updated: 2018-07-18Bibliographically approved

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