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This method is based on the application of both generalized pattern optimization and channel surfing reinitialization.
Four key technologies of UGS, i.e., trap sealing evaluation, gas storage parameter design, well pattern optimization and monitoring programs design were created.
It is anticipated that after pattern optimization and manufacturing scale up, a CVC with the Sharklet micropattern will demonstrate reduced CRBSI and CRT rates through preclinical and clinical studies.
This approach requires iterative pattern optimization and is sensitive to a number of optical parameters (such as the input laser wave front, optical elements imperfections, etc).
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In view of the large area, low abundance and high heterogeneity of Sulige gas field, a series of techniques have been developed including hierarchical description for the reservoir architecture of large composite sand bodies and well spacing optimization, well pattern optimization, design and optimization for horizontal trajectory and deliverability evaluation for different types of gas wells.
Optimization was implemented using simulated annealing in a spatial pattern optimization model (OLPSIM), and developments predicted by the drivers of past land-use changes were modeled with the CLUE-s model.
Well type and pattern optimization is the key technology to improve single well estimated reserves and recovery factor and to achieve effective field development.
A dendrogram for the PFGE patterns was constructed using the Dice similarity coefficient and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) algorithm, with settings for pattern optimization of 1.0% and band tolerance of 1.0%.
In the design of multistream plate-fin heat exchangers (MPFHEs), surface selection and layer pattern optimization have been investigated as two independent problems and still remain at the empirical stage, which becomes an obstacle for optimizing the performance of MPFHEs.
Results indicate that the convergence rate and reliability of the SGHS method are quite promising and practically, SGHS improves the quality of loading pattern optimization results relative to HS and GHS algorithms.
NAVA therefore does not seem to alter the closed loop that controls the PaCO2 and respiratory pattern optimization.
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