Journal ArticleDOI
Optimization of propane pre-cooled mixed refrigerant LNG plant
TLDR
In this paper, a genetic algorithm (GA) from Matlab optimization toolbox was used to optimize a propane pre-cooled mixed refrigerant (C3-MR) LNG plant that was originally designed by Mortazavi et al.About:Â
This article is published in Applied Thermal Engineering.The article was published on 2011-05-01. It has received 211 citations till now. The article focuses on the topics: Liquefied natural gas & Refrigerant.read more
Citations
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Journal ArticleDOI
Current Status and Perspectives of Liquefied Natural Gas (LNG) Plant Design
Wonsub Lim,Kwangho Choi,Il Moon +2 more
TL;DR: In this article, more complex refrigeration cycle designs that combine two or more different conventional single refrigeration cycles are being developed to obtain synergistic effects in the liquefaction process, which is expected that this trend in the use of LNG will lead to steady increases in demand over the next few decades.
Journal ArticleDOI
The correlation between mixed refrigerant composition and ambient conditions in the PRICO LNG process
TL;DR: In this paper, a genetic algorithm (GA) method was used to optimize the mixed refrigerant (MR) composition in the PRICO process under different cold box inlet temperatures, and linear regression was performed on the MR composition to derive a set of functions.
Journal ArticleDOI
Thermodynamic and economic optimization of LNG mixed refrigerant processes
TL;DR: In this article, the authors performed thermodynamic and economic optimization of mid-scale mixed refrigerant cycles including propane precooled mixed-refrigerant (C3MR) and dual-mixed refrigerant (DMR) processes.
Journal ArticleDOI
Review on the design and optimization of natural gas liquefaction processes for onshore and offshore applications
TL;DR: A review of the recent progress on the design and optimization of NG liquefaction processes for onshore and offshore applications is presented in this paper, where the authors propose several potential developments for NG LNG process design and optimisation.
Journal ArticleDOI
Knowledge based decision making method for the selection of mixed refrigerant systems for energy efficient LNG processes
TL;DR: In this article, a knowledge-based optimization approach was proposed to select the appropriate refrigerant composition, which was inspired by knowledge of the boiling point difference in MR components, and their specific refrigeration effect in bringing a MR system close to reversible operation.
References
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Book
Introduction to Optimum Design
TL;DR: This fourth edition of the introduction to Optimum Design has been reorganized, rewritten in parts, and enhanced with new material, making the book even more appealing to instructors regardless of course level.
Book
Cryogenic Mixed Refrigerant Processes
TL;DR: In this article, the authors present fundamental principles and processes for simulation of cryogenic processes, including the need for refrigerant mixtures, constant-temperature refrigeration processes, optimal mixture composition, and natural gas liquefaction.
Journal ArticleDOI
An exergy analysis of small-scale liquefied natural gas (LNG) liquefaction processes
TL;DR: In this article, four processes for small-scale liquefied natural gas (LNG) production are evaluated, including a single-stage mixed refrigerant (SMR), a two-stage expander nitrogen refrigerant and two open-loop expander processes.
Journal ArticleDOI
Heat and power networks in process design. Part I: Criteria for placement of heat engines and heat pumps in process networks
D. W. Townsend,B. Linnhoff +1 more
TL;DR: In this article, the concept of appropriate heat engine and heat pump placement in process networks based on a fundamental new insight is presented, which takes advantage of integration opportunities with the remainder of the process and yields marginal efficiencies far greater than could be achieved through stand-alone heat engines.
Journal ArticleDOI
An optimization-simulation model for a simple LNG process
TL;DR: A gradient free optimization-simulation method for processes modelled with the simulator Aspen HYSYS that has a high probability of obtaining a better solution with significantly fewer simulation runs than other metaheuristic methods.
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