Abstract
The objective of this paper is to introduce applications of Bayesian filters to state estimation problems in heat transfer. A brief description of state estimation problems within the Bayesian framework is presented. The Kalman filter, as well as the following algorithms of the particle filter: sampling importance resampling and auxiliary sampling importance resampling, are discussed and applied to practical problems in heat transfer.
Cite
CITATION STYLE
Orlande, H. R. B., Colaco, M. J., Dulikravich, G. S., Vianna, F., da Silva, W., Fonseca, H., & Fudym, O. (2012). STATE ESTIMATION PROBLEMS IN HEAT TRANSFER. International Journal for Uncertainty Quantification, 2(3), 239–258. https://doi.org/10.1615/int.j.uncertaintyquantification.2012003582
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