Abstract

The paper discusses a Bayesian framework for calibration of a gas turbine simulator in presence of uncertainty in the model structure. The framework is proposed for inference of a compressor map. Combined uncertainty in the compressor map and model structure is probabilistically specified using Gaussian stochastic process. Markov Chain Monte Carlo (MCMC) method is used to sample from the posterior distribution. The proposed framework is demonstrated for simulation of a single spool turbojet engine with artificially introduced uncertainty in the model structure.

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