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TECHNICAL PAPERS

Technical Analysis of Prediction Models for Transport Properties of Nanofluids

나노 유체의 전달 물성치 예측 모델 기술 분석

Minseo Leea
,
Hyung Ju Leea*
이민서 a
,
이형주 a*
aDepartment of Mechanical Engineering, Pukyong National University
*E-mail: hj.lee@pknu.ac.kr
29 February 2024. pp. 56-66
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Abstract

By mixing nano-size catalysts into hydrocarbon aviation fuels which are used as coolants in active regenerative cooling systems, the endothermic decomposition reaction is facilitated leading to increased cooling efficiency. In order to apply these nanofluids as fuel, it is essential to acquire their transport properties for understanding the internal flow and heat transfer characteristics. In this study, therefore, the viscosity and thermal conductivity prediction models are analyzed based on the shape of nanoparticles mixed in fluids. Regarding viscosity, we categorized the prediction models with spherical and nonspherical particles while for thermal conductivity, its prediction models are classified with spherical, nonspherical, ellipsoidal, and plate-like particles. Even though these models perform particularly well with low volume fractions near room temperature conditions, further validation is necessary through experimentation under high-temperature conditions in the future.

Keywords
Hypersonic Vehicle
Regenerative Cooling System
Nano-size Catalyst
Viscosity
Thermal Conductivity

능동재생냉각시스템의 냉매로 사용되는 탄화수소 항공유에 나노입자 형태의 촉매를 혼합하면 흡열 분해 반응이 촉진되어 재생냉각 효율을 더욱 높일 수 있다. 이러한 나노 흡열 연료를 사용하기 위해서는 내부 유동 및 열전달 파악을 위해 나노입자의 포함에 따른 전달 물성치 획득이 필수적이다. 따라서 본 연구에서는 나노입자의 모양에 따른 점도와 열전도도 예측 모델을 분석하였다. 점도의 경우, 구형 입자와 비구형 입자의 점도 예측 모델로 구분하였으며, 열전도도의 경우, 구형 입자, 비구형 입자, 타원형 입자, 판형 입자의 열전도도 예측 모델로 구분하여 정리하였다. 이러한 모델들은 특히 낮은 부피분율에서 예측성능이 뛰어나지만, 고온 조건에서의 예측성능은 향후 실험을 통해 검증이 필요하다.

키워드
극초음속 비행체
재생냉각시스템
나노촉매
점도
열전도도
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Information
  • Publisher :The Korean Society of Propulsion Engineers
  • Publisher(Ko) :한국추진공학회
  • Journal Title :Journal of the Korean Society of Propulsion Engineers
  • Journal Title(Ko) :한국추진공학회지
  • Volume : 28
  • No :1
  • Pages :56-66
  • Received Date : 2023-11-16
  • Revised Date : 2024-02-10
  • Accepted Date : 2024-02-15
  • DOI :https://doi.org/10.6108/KSPE.2024.28.1.056
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