[2B13-17] Analysis Method 2

4:00 PM - 4:15 PM JST(7:00 AM - 7:15 AM UTC)

[2B13] Dimension-reduced cross-section adjustment method based on Bayesian Monte-Carlo method

*Yuhei Fukui¹, Tomohiro Endo¹, Akio Yamamoto¹ (1. Nagoya University)

Keywords:

Cross-section adjustment,Dimension reduction,Bayesian Monte-Carlo method,Data assimilation

We are investigating a cross-section adjustment method incorporating dimension reduction and the Bayesian Monte-Carlo method, which is a robust data assimilation method. Virtual “true” cross-sections are generated using a perturbation set based on the covariance data, and the numerical result using the “true” cross-section is considered as a virtual “true” experimental value. We applied the proposed cross-section adjustment method to the virtual “true” experimental value and verified the performance of the method.