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Inferring pressure profiles from neutron data through Bayesian calibration

Abstract : We propose employing Bayesian calibration to match observed neutron data with calculated moisture contents. Hereby the calibration effort aims at minimizing the uncertainty regarding the experimental boundary conditions, after which the model can be interrogated for pressure data. The proposed formulation explicitly accounts for image noise and model bias. The approach is illustrated for the case of evaporative drying in limestone.
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https://hal.archives-ouvertes.fr/hal-01815873
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Peter Moonen, Hannelore Derluyn. Inferring pressure profiles from neutron data through Bayesian calibration. 2nd International Conference on Tomography of Materials and Structures ICTMS 2017, Jun 2017, Lund, Sweden. ⟨hal-01815873⟩

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