Journal of the Korean Society of Propulsion Engineers (한국추진공학회지)

The Korean Society of Propulsion Engineers (한국추진공학회)
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Cubic Equation of State Analysis for the Prediction of Supercritical Thermodynamic Properties of Hydrocarbon Fuels with High Critical Compressibility Factor

고 임계 압축인자를 갖는 탄화수소 연료의 초임계 열역학적 물성 예측을 위한 상태방정식 분석

  • Jae Seung Kim (Department of Aerospace Engineering, Seoul National University) ;
  • Jiwan, Seo (Department of Aerospace Engineering, Seoul National University) ;
  • Kyu Hong Kim (Department of Aerospace Engineering, Seoul National University)
  • 김재승 ;
  • 서지완 ;
  • 김규홍
  • Received : 2022.06.17
  • Accepted : 2022.10.13
  • Published : 2022.10.31
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Abstract

In order to predict the cooling performance of a regenerative cooling channel using hydrocarbon fuel operating in the supercritical region, it is essential to predict the thermodynamic properties. In this study, a comparative analysis was performed on two-parameter equations of state (SRK(Soave-Redlich-Kwong), PR(Peng-Robinson) equations of state) and three-parameter equations of state (RK-PR equations of state) to appropriately predict density and specific heat according to the critical compressibility factor of polymer hydrocarbons. Representatively, n-dodecane fuel with low critical compressibility factor and JP-10 fuel with high critical compressibility factor were selected, and an appropriate equation of state was presented when predicting the thermodynamic properties of the two fuels. Finally, the prediction results of density and specific heat were compared and verified with NIST REFPROP data.

초임계 영역에서 작동하는 탄화수소 연료를 사용하는 재생냉각채널의 냉각성능을 예측하기 위해서는 타당한 물성 예측이 필수이다. 본 연구는 고분자 탄화수소의 임계 압축인자에 따라 밀도와 비열을 적절하게 예측하기 위해 2-파라미터 상태방정식인 SRK(Soave-Redlich-Kwong) 및 PR(Peng-Robinson) 상태방정식과 이를 합한 3-파라미터 상태방정식인 RK-PR 상태방정식에 대한 비교 분석을 수행하였다. 대표적으로 낮은 임계압축 인자를 갖는 n-dodecane 연료와 높은 임계압축 인자를 갖는 JP-10 연료를 선정하여 두 연료의 열역학적 물성을 예측할 때 적합한 상태방정식을 제시하였다. 마지막으로 밀도와 비열의 예측 결과를 NIST REFPROP 데이터와 비교하여 검증하였다.

Keywords

Acknowledgement

본 연구는 스크램제트 복합추진시스템 특화연구실 과제(과제코드: 16-106-501-035)의 지원을 받아 수행하였으며, 이에 감사드립니다.

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