• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.68-78
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• 2012

A layout of an LNG FPSO should be elaborately determined as compared with that of an onshore plant because many topside process systems are installed on the limited area; the deck of the LNG FPSO. Especially, the layout should be made as multi-deck, not single-deck and have a minimum area. In this study, a multi-floor layout for the liquefaction process, the dual mixed refrigerant(DMR) cycle, of LNG FPSO was determined by using the optimization technique. For this, an optimization problem for the multi-floor layout was mathematically formulated. The problem consists of 589 design variables representing the positions of topside process systems, 125 equality constraints and 2,315 inequality constraints representing limitations on the layout of them, and an objective function representing the total layout cost. To solve the problem, a hybrid optimization method that consists of the genetic algorithm(GA) and sequential quadratic programming(SQP) was used in this study. As a result, we can obtain a multi-floor layout for the liquefaction process of the LNG FPSO which satisfies all constraints related to limitations on the layout.

• Korean Chemical Engineering Research
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• v.52 no.4
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• pp.467-474
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• 2014

Preliminary design in chemical process furnishes economic feasibility through calculation of both mass balance and energy balance and makes it possible to produce a desired product under the given conditions. Through this design stage, the process possesses unchangeable characteristics, since the materials, reactions, unit configuration, and operating conditions were determined. Unique characteristics could be very economic, but it also implies various potential risk factors as well. Therefore, it becomes extremely important to design process considering both economics and safety by integrating process simulation and quantitative risk analysis during preliminary design stage. The target of this study is LNG liquefaction process. By the simulation using Aspen HYSYS and quantitative risk analysis, the design variables of the process were determined in the way to minimize the inherent explosion risks and operating cost. Instead of the optimization tool of Aspen HYSYS, the optimization was performed by using stochastic optimization algorithm (Covariance Matrix Adaptation-Evolution Strategy, CMA-ES) which was implemented through automation between Aspen HYSYS and Matlab. The research obtained that the important variable to enhance inherent safety was the operation pressure of mixed refrigerant. The inherent risk was able to be reduced about 4~18% by increasing the operating cost about 0.5~10%. As the operating cost increases, the absolute value of risk was decreased as expected, but cost-effectiveness of risk reduction had decreased. Integration of process simulation and quantitative risk analysis made it possible to design inherently safe process, and it is expected to be useful in designing the less risky process since risk factors in the process can be numerically monitored during preliminary process design stage.