{"title":"CFD Based Investigation of Effects of Liquid Contamination on Dry Gas Seal Performance","authors":"Abhay V. Patil, Aaron M. Rimpel, R. Kurz","doi":"10.1115/gt2022-82572","DOIUrl":null,"url":null,"abstract":"\n Previous studies identified liquid contamination as a major root cause of dry gas seal (DGS) failures and highlighted the need for model development to simulate the liquid-gas interaction and its effect on DGS operation. The current study presents Computational Fluid Dynamics (CFD) based performance prediction of a DGS under single-phase (gas) and two-phase (gas-liquid) flow conditions. The presented numerical model includes the conjugate heat transfer (CHT) analysis for the three pressure conditions at a constant rotational speed. Initial modeling involved the qualification of different turbulent models by analyzing and comparing leakage flow, torque, and temperature distribution. The two-phase CFD model employs the Eulerian approach to predict the oil distribution and modified pressure and temperature predictions. Two-phase flow simulations focused on improving the understanding of oil distribution as a function of droplet size at the imposed inlet volume fraction and the consequential effect on the seal performance parameters. The presence of liquid causes localized pressure and temperature change while flow transitions from the cavity to the seal area. Also, two-phase interaction due to oil presence increases heat generation and consequential temperature rise in the pressure dam region. Overall, the systematic variation in performance parameters with liquid fraction provides greater insight into DGS performance, also laying out a path for establishing an incipient failure mechanism that will be validated in future testing.","PeriodicalId":301910,"journal":{"name":"Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications","volume":"52-54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 7: Industrial and Cogeneration; Manufacturing Materials and Metallurgy; Microturbines, Turbochargers, and Small Turbomachines; Oil & Gas Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/gt2022-82572","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Previous studies identified liquid contamination as a major root cause of dry gas seal (DGS) failures and highlighted the need for model development to simulate the liquid-gas interaction and its effect on DGS operation. The current study presents Computational Fluid Dynamics (CFD) based performance prediction of a DGS under single-phase (gas) and two-phase (gas-liquid) flow conditions. The presented numerical model includes the conjugate heat transfer (CHT) analysis for the three pressure conditions at a constant rotational speed. Initial modeling involved the qualification of different turbulent models by analyzing and comparing leakage flow, torque, and temperature distribution. The two-phase CFD model employs the Eulerian approach to predict the oil distribution and modified pressure and temperature predictions. Two-phase flow simulations focused on improving the understanding of oil distribution as a function of droplet size at the imposed inlet volume fraction and the consequential effect on the seal performance parameters. The presence of liquid causes localized pressure and temperature change while flow transitions from the cavity to the seal area. Also, two-phase interaction due to oil presence increases heat generation and consequential temperature rise in the pressure dam region. Overall, the systematic variation in performance parameters with liquid fraction provides greater insight into DGS performance, also laying out a path for establishing an incipient failure mechanism that will be validated in future testing.