(140e) Reliable Thermodynamic Data for Improving Lng Scrub Column Design
AIChE Spring Meeting and Global Congress on Process Safety
2008
2008 Spring Meeting & 4th Global Congress on Process Safety
AIChE / ACS Jointly Co-sponsored Sessions
Liquefied Natural Gas (LNG) - Equipment II
Tuesday, April 8, 2008 - 3:20pm to 3:40pm
The fabrication and operation of a liquefaction facility is a capital intensive expenditure in which optimized simulations would reduce the total cost of ownership. The thermodynamic properties of the fluid mixtures at each process condition required by the simulator are usually calculated using an equation of state (EOS).
The LNG Scrub Column is an area of particular focus within this study because it operates at both low temperatures and elevated pressures, and with the widest range of components. Currently, the equation of state (typically cubic) embedded in the process simulator is not anchored to fluid data representative of industrial scrub columns and, consequently, the inaccurate VLE and phase density predictions increase the uncertainty of the calculated process conditions. Therefore, the size of the equipment includes an increased design margin in overall size to ensure safe operation and performance of the equipment. An experimental determination of the fluid mixture's thermodynamic properties at scrub column conditions will allow the EOS utilized within the simulator to be improved. In turn, the simulator will be able to calculate more accurate and precise process conditions thereby allowing the size of equipment to be optimized which will reduce the overall capital and operating costs.
Chevron has initiated a joint project with the Western Australia Energy Research Alliance to study more extensively and determine experimentally the relevant thermodynamic properties of multi-component mixtures at cryogenic conditions. This paper will briefly discuss this alliance and the work being performed; however, the focus of the paper will be the inaccuracies of LNG process simulations at cryogenic conditions. We will show a comparison between available operational data and results predicted by the simulator using various equations of state. The resulting design margin and the oversizing of the Scrub Column will also be discussed to emphasize the business case for this project.
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