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Calculation models for prediction of Liquefied Natural Gas (LNG) ageing during ship transportation

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  • Miana, Mario
  • Hoyo, Rafael del
  • Rodrigálvarez, Vega
  • Valdés, José Ramón
  • Llorens, Raúl

Abstract

A group of European gas transportation companies within the European Gas Research Group launched in 2007 the [`]MOLAS' Project to provide a software program for the analysis of the Liquefied Natural Gas (LNG) ageing process during ship transportation. This program contains two different modeling approaches: a physical algorithm and an [`]intelligent' model. Both models are fed with the same input data, which is composed of the ship characteristics (BOR and capacity), voyage duration, LNG composition, temperature, pressure, and volume occupied by liquid phase at the port of origin, together with pressure at the port of destination. The results obtained are the LNG composition, temperature and liquid volume at the port of destination. Furthermore, the physical model obtains the evolution over time of such variables en route as it is based on unsteady mass balances over the system, while the i-model applies neural networks to obtain regression coefficients from historical data composed only of origin and destination measurements. This paper describes both models and validates them from previous published models and experimental data measured in ENAGAS LNG regasification plants.

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  • Miana, Mario & Hoyo, Rafael del & Rodrigálvarez, Vega & Valdés, José Ramón & Llorens, Raúl, 2010. "Calculation models for prediction of Liquefied Natural Gas (LNG) ageing during ship transportation," Applied Energy, Elsevier, vol. 87(5), pages 1687-1700, May.
    • Handle: RePEc:eee:appene:v:87:y:2010:i:5:p:1687-1700
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    References listed on IDEAS

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    2. Forouzanfar, Mehdi & Doustmohammadi, A. & Hasanzadeh, Samira & Shakouri G, H., 2012. "Transport energy demand forecast using multi-level genetic programming," Applied Energy, Elsevier, vol. 91(1), pages 496-503.
    3. Mohd Shariq Khan & Muhammad Abdul Qyyum & Wahid Ali & Aref Wazwaz & Khursheed B. Ansari & Moonyong Lee, 2020. "Energy Saving through Efficient BOG Prediction and Impact of Static Boil-off-Rate in Full Containment-Type LNG Storage Tank," Energies, MDPI, vol. 13(21), pages 1-14, October.
    4. Querol, E. & Gonzalez-Regueral, B. & García-Torrent, J. & Ramos, Alberto, 2011. "Available power generation cycles to be coupled with the liquid natural gas (LNG) vaporization process in a Spanish LNG terminal," Applied Energy, Elsevier, vol. 88(7), pages 2382-2390, July.
    5. Marques, C.H. & Belchior, C.R.P. & Caprace, J.-D., 2018. "Optimising the engine-propeller matching for a liquefied natural gas carrier under rough weather," Applied Energy, Elsevier, vol. 232(C), pages 187-196.
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    8. Kwak, Dong-Hun & Heo, Jeong-Ho & Park, Seung-Ha & Seo, Seok-Jang & Kim, Jin-Kuk, 2018. "Energy-efficient design and optimization of boil-off gas (BOG) re-liquefaction process for liquefied natural gas (LNG)-fuelled ship," Energy, Elsevier, vol. 148(C), pages 915-929.
    9. Kayal, Sibnath & Sun, Baichuan & Chakraborty, Anutosh, 2015. "Study of metal-organic framework MIL-101(Cr) for natural gas (methane) storage and compare with other MOFs (metal-organic frameworks)," Energy, Elsevier, vol. 91(C), pages 772-781.
    10. Tomasz Włodek & Mariusz Łaciak, 2023. "Rollover Prevention Model for Stratified Liquefied Natural Gas in Storage Tanks," Energies, MDPI, vol. 16(22), pages 1-23, November.
    11. Fernández, Ignacio Arias & Gómez, Manuel Romero & Gómez, Javier Romero & Insua, Álvaro Baaliña, 2017. "Review of propulsion systems on LNG carriers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 1395-1411.
    12. Jung, Byungchan & Park, Kiheum & Sohn, Younghoon & Oh, Juyoung & Lee, Joon Chae & Jung, Hae Won & Seo, Yutaek & Lim, Youngsub, 2022. "Prediction model of LNG weathering using net mass and heat transfer," Energy, Elsevier, vol. 247(C).
    13. Peng Yu & Yuanchao Yin & Qianjin Yue & Shanghua Wu, 2022. "Experimental Study of Ship Motion Effect on Pressurization and Holding Time of Tank Containers during Marine Transportation," Sustainability, MDPI, vol. 14(6), pages 1-23, March.
    14. Kang, Goanwoo & Im, Junyoung & Lee, Chul-Jin, 2024. "Operational strategy to minimize operating cost in LNG terminal using a comprehensive numerical boil-off gas model," Energy, Elsevier, vol. 296(C).
    15. Duan, Zhongdi & Wang, Jianhu & Yuan, Yuchao & Tang, Wenyong & Xue, Hongxiang, 2023. "Near-wall thermal regulation for cryogenic storage by adsorbent coating: Modelling and pore-scale investigation," Applied Energy, Elsevier, vol. 349(C).
    16. Kumar, Satish & Kwon, Hyouk-Tae & Choi, Kwang-Ho & Lim, Wonsub & Cho, Jae Hyun & Tak, Kyungjae & Moon, Il, 2011. "LNG: An eco-friendly cryogenic fuel for sustainable development," Applied Energy, Elsevier, vol. 88(12), pages 4264-4273.
    17. Perez, Fernando & Al Ghafri, Saif Z.S. & Gallagher, Liam & Siahvashi, Arman & Ryu, Yonghee & Kim, Sungwoo & Kim, Sung Gyu & Johns, Michael L. & May, Eric F., 2021. "Measurements of boil-off gas and stratification in cryogenic liquid nitrogen with implications for the storage and transport of liquefied natural gas," Energy, Elsevier, vol. 222(C).
    18. Huerta, Felipe & Vesovic, Velisa, 2019. "A realistic vapour phase heat transfer model for the weathering of LNG stored in large tanks," Energy, Elsevier, vol. 174(C), pages 280-291.

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