SNUEI

Modeling and simulation of thermodynamic behavior of an LNG fuel tank by using artificial neural network based on operational data

2024 · Energy

저자

Hye-Yeong Jeong, Andrew Park, Jinki Chung, Donghoon Lee, Dong‐Kil Lee, Hoki Lee, Dongyeon Lee, 임영섭 (Youngsub Lim)

연구주제

Spacecraft and Cryogenic Technologies

NTIS 과학기술표준분류

에너지/자원만에너지·환경·원자력 확장

지원 과제·AI 키워드로 잡을 근거가 없어 분류하지 않았다.

AI 연구 키워드·방법

boil off gas generation liquefied natural gas fuel tank

기계학습

키워드 (OpenAlex)

thermodynamic behavior LNG-fueled ships boil-off gas cryogenic storage filling factor ship motion effects data-driven modeling

초록

As marine environmental regulations have been strengthened, the use of LNG (Liquefied Natural Gas) as a marine fuel is increasing. In an LNG tank under cryogenic condition, boil-off gas is generated due to heat ingress, and the pressure and temperature of the tank continuously change. For safe and efficient operation of LNG fueled ships, it is necessary to accurately predict the thermodynamic state of an LNG fuel tank. In this paper, a difference estimating artificial neural network (D-ANN) model is proposed to evaluate the thermodynamic behavior in an IMO type C fuel tank. The D-ANN model predicts the pressure, temperature and filling ratio of the LNG fuel tank under marine operating conditions through the initial tank state and operating variables. Input factors that are difficult to be included in conventional physics-based thermodynamic models, such as the effects of ship motions and…

이 논문을 지원한 국가R&D 과제 (NTIS 성과)

NTIS 성과DB(2020–24)에서 DOI 매칭 없음

인접 그래프

노드 hover = 이웃 강조 · 1회 클릭 = 고정 · 고정된 노드 다시 클릭 = 페이지 이동

이 문서와 연결된 페이지

교수 1

임영섭

연구주제 1

Spacecraft and Cryogenic Technologies

방법 1

기계학습