This paper shows the sequential search algorithm that makes it possible to find the optimum operating conditions of Advanced Dual Refrigerant Expansion Cycle that is used for LNG liquefaction process. The operating conditions are key parameters in determining the overall liquefaction efficiency of system, so it is the core process to find out these optimized key parameters in LNG industries. The steps of this method are as follows. 1) Defining input variables based on understanding of liquefaction cycle and thermodynamics. 2) Setting simulation to apply the sequential search algorithm. 3) Searching sequentially several local optimum points between the upper and lower limits of several input variables considering minimum/average efficiencies and the number of points satisfied with minimum approach 4) Repeat step 3) with narrower ranges and step sizes of each input variable based on previous results. 5) Get the global (final) optimum point considering final results and realistic operation. The operating conditions of Advanced Dual Refrigerant Expansion Cycle are eventually optimized with the best overall liquefaction efficiency of system by using the sequential search method. It is directly related to economical effect in terms of the high production rate against supply power, small size of equipment and the associated pipe lines, simple system layout and so on. During searching, several local optimum points of the operating conditions can be recorded in order to compare the liquefaction efficiencies at each of points by using this method. It serves as the objective evidence to understand trends of the efficiencies calculated from variable inputs. In addition, this method can provide a variety of selecting the main equipment such as compressor, expander, heat exchanger and so on because it is possible to identify several local optimum points have similar efficiencies. This new sequential search method can be applied for the optimization of existing other gas expansion liquefaction cycles and the mixed refrigerant (MR) LNG liquefaction cycles by making adjustments to input variables e.g. MR compositions can be available input variables as well in case of MR cycles.

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