Predicting saturated vapor pressure of LNG from density and temperature data with a view to improving tank pressure management

Petroleum - Tập 7 - Trang 91-101 - 2021
David A. Wood1
1DWA Energy Limited, Lincoln, LN5 9JP, United Kingdom

Tài liệu tham khảo

2019, The LNG industry annual report 2019 2019, 20 Kulitsa, 2017, Part 1: improved monitoring onboard FSRUs is required to enhance operating performance and cut cargo loss, LNG Journal, 22 Kulitsa, 2018, Enhanced application for FSRU recondensing equipment during periods of low or No gas send out to minimize LNG cargo losses, Petroleum, 4, 365, 10.1016/j.petlm.2018.01.002 MEPC, Guidelines for the Development of a Ship Energy Efficiency Management Plan (SEEMP). Resolution MEPC.282(70), Adopted by Marine Environment Protection Committee vol. 28 October (2016). DNV-GL ICS-Shipping Mackin Kulitsa, 2019, Soft metal blanket with optional anti-sloshing conceptual designs to improve pressure control for floating and land-based liquefied natural gas tanks, Advances in Geo-Energy Research, 3, 424, 10.26804/ager.2019.04.09 Chen, 2004, Analysis of temperature and pressure changes in liquefied natural gas (LNG) cryogenic tanks, Cryogenics, 44, 701, 10.1016/j.cryogenics.2004.03.020 Li, 2018, Study on calculation of liquid level and storage of tanks for LNG-fuelled vessels, IOP Conf. Ser. Earth Environ. Sci., 111, 10.1088/1755-1315/111/1/012030 Shao, 2019, Dynamic optimization of boil-off gas generation for different time limits in liquid natural gas bunkering, Energies, 12, 1130, 10.3390/en12061130 Shah, 1995, Effect of weathering of LNG in storage tanks, 253 Wood, 2007, Natural gas interchangeability in focus as sources of LNG widen, LNG Journal (February), 14 Yang, 2014, Measurement method of liquid level in LNG tank[J], Tianjin chemical, 4, 54 Wood, 2018, Weathering/ageing of LNG cargoes during marine Transport and processing on FSU and FSRU, J. Energy Resour. Technol., 140, 10.1115/1.4039981 Benito, 2009, 1 Miana, 2010, Calculation models of Liquefied Natural Gas (LNG) weathering during ship transportation, Appl. Energy, 87, 1687, 10.1016/j.apenergy.2009.10.023 Adom, 2010, Modelling of boil-off gas in LNG tanks: a case study, Int. J. Eng. Technol., 2, 292 Dobrota, 2013, Problem of boil - off in LNG supply chain, Trans. Marit. Sci., 91, 10.7225/toms.v02.n02.001 Dimopoulis, 2008, A dynamic model for liquefied natural gas evaporation during marine transportation, Int. J. Therm., 11, 123 Pellegrini, 2014, The weathering in above-ground storage tanks, Ind. Eng. Chem. Res., 53, 3931, 10.1021/ie404128d Migliore, 2015, Weathering prediction model for stored liquefied natural gas (LNG), J. Nat. Gas Sci. Eng., 26, 570, 10.1016/j.jngse.2015.06.056 Capello, 2016, 305 Hubert, 2019, Predicting liquefied natural gas (LNG) rollovers using computational Fluid dynamics, J. Loss Prev. Process. Ind., 62, 10.1016/j.jlp.2019.103922 Migliore, 2017, A non-equilibrium approach to modelling the weathering of stored Liquefied Natural Gas (LNG), Energy, 124, 684, 10.1016/j.energy.2017.02.068 Wood, 2018, Open-Box learning network provides insight to complex systems and a performance benchmark for more-opaque machine learning algorithms, Advances in Geo-Energy Research, 2, 148, 10.26804/ager.2018.02.04 Fausett, 1994 Haykin, 1994 Hornik, 1989, Multilayer feedforward networks are universal approximators, Neural Network., 2, 359, 10.1016/0893-6080(89)90020-8 Hornik, 1991, Approximation capabilities of multilayer feedforward networks, Neural Network., 4, 251, 10.1016/0893-6080(91)90009-T Battiti, 1992, First and second order methods for learning: between steepest descent and Newton’s method, Neural Comput., 4, 141, 10.1162/neco.1992.4.2.141 Wood, 2019, Transparent open-box learning network provides auditable predictions for coal gross calorific value, Modeling Earth Systems and Environment, 5, 395, 10.1007/s40808-018-0543-9 Solvers, 2020