Abstract
Uncertainties, present in any engineering calculations would impact on decision making. In this work, uncertainty propagation in the simulation of condensate stabilization column in gas refinery is performed by Monte Carlo (MC) and Latin hypercube sampling (LHS) methods. Furthermore, a novel approach of building a statistical emulator of a simulation model for uncertainty analysis is presented. The results showed that the emulator is enormously more efficient than conventional approaches and the LHS is superior to MC due to its convergence in small sampling size.
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