Boil-Off Gas in the Liquefied Natural Gas Supply Chain: A Recent Collective Data DOI

Mays Nassar,

Saad A. Al‐Sobhi, Fares Almomani

и другие.

Опубликована: Янв. 1, 2023

The Boil-Off Gas (BOG) phenomenon in the liquefied natural gas (LNG) supply chain is a consequence of significant temperature difference between extremely low LNG (-162 ºC) and ambient temperatures (≥25ºC). This issue poses substantial challenge within sector. paper presents comprehensive review examination research undertaken on this spanning 2015 to 2022. primary objective elucidate progress innovations field benefit both readers researchers. articles under evaluation are classified based BOG formation location along chain. These locations include processing facilities, ships, regasification terminals. Among many papers evaluated, 70 have matched established criteria. Notably, 62% reviewed publications centered generated onboard carriers. Our analysis highlights that main approach tackle generation revolves around its re-liquefaction. Significantly, an increasing amount scholarly literature significance dynamic simulations due inherent constraints steady-state effectively managing variable properties BOG.

Язык: Английский

The LNG Flow Simulation in Stationary Conditions through a Pipeline with Various Types of Insulating Coating DOI Creative Commons

I.A. Shammazov,

Ekaterina Karyakina

Fluids, Год журнала: 2023, Номер 8(2), С. 68 - 68

Опубликована: Фев. 14, 2023

Liquefied natural gas (LNG) is one of the most promising fuels for energy supply because it has a favorable combination environmental and economic properties in connection with new trends aimed at development ecological sustainable consumption resources, which ensure constant growth LNG consumption. The article presents an analytical review main technical solutions construction cryogenic pipelines insulating coating structures. ANSYS Fluent software was used simulation flow pipeline section 10 m long outer diameter 108 mm three types (polyurethane (PU) foam, aerogel, vacuum-insulated pipe (VIP)). In addition, assessment made effect on temperature distribution along length pipeline. largest increase from 113 K to 113.61 occurs PU foam-insulated pipes; smallest observed VIP. Further, as alternative steel, use ultra-high molecular weight polyethylene (UHMWPE) material considered. optimal result terms distributions obtained while simulating foam by increasing thickness 0.05 m.

Язык: Английский

Процитировано

14

Dynamic modeling of hydrogen production from boil-off gas (BOG) at onshore LNG facilities: Technical and socio-economic analysis DOI Creative Commons
Noor Yusuf, Fares Almomani, Hazim Qiblawey

и другие.

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 67, С. 949 - 958

Опубликована: Фев. 28, 2024

Integrating hydrogen (H2) production systems within natural gas (NG) supply chains can support smoothening transition to cleaner energy resources by utilizing existing infrastructures. This work investigates the dynamic conversion of boil-off (BOG) using steam methane reforming (SMR) produce H2 liquified (LNG) process. The study extends beyond technical considerations encompass a socio-economic approach, exploring optimal allocation different monetization techniques (e.g., ammonia and methanol) subject final market price demand data. Dynamic simulation showed an excellent ability address variations in BOG flow, change LNG temperature pressure drop chain, highlighting need for adaptive flowrate process setpoints. productivity yield are dependent on flow rates, carbon ration (S/C) input system. Optimizing reformer is best practice enhanced H2. Allocating approximately 74% produced CO2-free production, remainder methanol via CO2 hydrogenation, achieves annual profitability $1.36 billion. However, when considering variable data over ten years, model proposes flexible both routes, resulting average yearly $6.84 These findings underscore importance integrating interactive approaches exogenous endogenous uncertainties, providing robust strategy against risks. comprehensive approach presented this contributes understanding strategic planning chains, emphasizing adaptability economic viability landscape transition.

Язык: Английский

Процитировано

5

Reducing the CO2 footprint at an LNG asset with replicate trains using operational data-driven analysis. A case study on end flash vessels DOI Creative Commons
Rakesh Paleja,

Ekhorutomwen Osemwinyen,

Matthew Jones

и другие.

Data-Centric Engineering, Год журнала: 2025, Номер 6

Опубликована: Янв. 1, 2025

Abstract A liquefied natural gas (LNG) facility often incorporates replicate liquefaction trains. The performance of equivalent units across trains, designed using common numerical models, might be expected to similar. In this article, we discuss statistical analysis real plant data validate assumption. Analysis operational for end flash vessels from a pair trains at an LNG indicates that one train produces 2.8%–6.4% more than the other. We then develop models operation, facilitating reduced flaring and hence reduction up 45% in CO 2 emissions, noting emissions typical account ~4%–8% overall emissions. recommend data-driven considered generally improve facilities reduce their footprint, particularly when replica are present.

Язык: Английский

Процитировано

0

Onshore hydrogen production from boil-off gas (BOG) via natural gas steam reforming process: Process simulation and techno-economic analysis DOI
Noor Yusuf, Fares Almomani, Saad A. Al‐Sobhi

и другие.

International Journal of Hydrogen Energy, Год журнала: 2023, Номер 52, С. 1046 - 1057

Опубликована: Июль 4, 2023

Язык: Английский

Процитировано

9

Simulation analysis and field verification of static evaporation characteristics of full-scale LNG storage tanks DOI
Jiahang Li,

Shengzhu Zhang,

Qingshan Feng

и другие.

Applied Thermal Engineering, Год журнала: 2024, Номер 253, С. 123721 - 123721

Опубликована: Июнь 18, 2024

Язык: Английский

Процитировано

2

Comparative Analysis of Heat Transfer in a Type B LNG Tank Pre-Cooling Process Using Various Refrigerants DOI Creative Commons
Qiang Sun, Yanli Zhang, Yan Lv

и другие.

Energies, Год журнала: 2024, Номер 17(16), С. 4013 - 4013

Опубликована: Авг. 13, 2024

This study presents a comprehensive three-dimensional Computational Fluid Dynamics (CFD) analysis of the pre-cooling process Type B LNG tank using various refrigerants, including liquid nitrogen (LN), gas (NG), liquefied natural (LNG), boil-off (BOG), and their combinations. The simulation model accounts for phase change (through mixture multiphase model), convective heat transfer, conjugate exchange between fluid structure. results indicate that is most efficient refrigerant, achieving highest cooling rate through both latent sensible heat. also demonstrated relatively high rate, 79% nitrogen. Gas-only schemes relying solely on exhibited slower rates, with BOG achieved 79.4% NG. Mixed refrigerants such as NG + LN can achieve comparable, while slightly slower, than pure outperforming gas-only strategies. A further assessment transfer coefficient suggests mixed have almost identical inner surface to scheme, over 5% higher refrigerants. highlighted uneven temperature distribution within due bulkhead’s blockage effect, which induce significant thermal stress potentially compromise structural integrity. exhibit gradients those but lower schemes, speeds comparable if inlet velocity properly configured. These findings offer valuable insights developing safer more procedures tanks similar cryogenic storage tanks.

Язык: Английский

Процитировано

1

Study of Predictive Control Model for Cooling Process of Mark III LNG Bunker DOI Creative Commons
Guozhi Bao, Weiguang Qin, Qingfeng Jiang

и другие.

Polish Maritime Research, Год журнала: 2024, Номер 31(3), С. 102 - 112

Опубликована: Авг. 21, 2024

Abstract When loading liquefied natural gas (LNG) onto a dual-fuel LNG container ship fuelled by LNG, there is considerable temperature difference between and the fuel tank at room temperature. The current solution to pre-cool with through spray line but cooling process, if not correctly handled, can result in excessive rates Boil-Off Gas (BOG), which expose increased stress pressure. Therefore, this paper takes Mark III of specific type as object realises real-time predictive control system writing UDF (User Defined Function) simulate analyse influence rate on change effect, time cost under unidirectional mode. Compared results experiment, deviation numerical model simulation less than 5%. Under same rate, scheme achieve more uniform reduce total consumption 25%. With increase time, usage, BOG exhaust volume all decrease; however, decreased range gradually decreases well. provide parameters suggestions for optimising improving monitoring system.

Язык: Английский

Процитировано

1

Simulation of boil-off gas recovery and fuel gas optimization for increasing liquefied natural gas production DOI Creative Commons

Agung Widodo,

Yuswan Muharam

Energy Reports, Год журнала: 2023, Номер 10, С. 4503 - 4515

Опубликована: Ноя. 1, 2023

In a natural gas liquefaction plant, boil-off (BOG) is generated in both and loading processes. During the holding mode (no operation), fuel supply, including BOG process, less than demand. Therefore, make-up added to system. recovery systems are designed absorb maximum amount of during liquefied (LNG) ships (loading mode). Additional process At this stage, supply higher To avoid flaring, from reduced by cooling LNG main heat exchanger (MHE) lower temperature, which consequently reduces production more 1%. This study aimed optimize liquefaction, storage, loading, processes increase production. study, plant producing 8 mtpa (million tonnes/ year), where was limited capacity system demand, modelled using UniSim software. model, optimization increased 46,850 year. The volumetric flow rate decreasing temperature ship's cargo tanks, pumps' discharge pressure, reducing pressure compressors, rate. shows that can be significantly around 50% initial rate, increases 36,576 total, potential 90,260 year or equivalent 1.4 per

Язык: Английский

Процитировано

2

Dynamic simulation models for an LNG storage tank DOI

Aruna Coimbatore Meenakshi Sundaram,

Iftekhar A. Karimi

Elsevier eBooks, Год журнала: 2024, Номер unknown, С. 293 - 304

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0

Multi-period optimisation of flexible natural gas production network infrastructure with an operational perspective: A mixed integer linear programming approach DOI Creative Commons
Noor Yusuf, Roberto Baldacci, Ahmed AlNouss

и другие.

Energy Conversion and Management X, Год журнала: 2024, Номер unknown, С. 100818 - 100818

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

0