Bayesian Model Calibration Using Geotechnical Centrifuge Tests

Author(s):  
L. L. Zhang ◽  
W. H. Tang ◽  
L. M. Zhang
Author(s):  
Hae Na Yoon ◽  
Lucy Marshall ◽  
Ashish Sharma ◽  
Seokhyeon Kim

Author(s):  
Shizuo Tsurumaki ◽  
Hiroyuki Watanabe ◽  
Akira Tateishi ◽  
Kenichi Horikoshi ◽  
Shunichi Suzuki

In Japan, there is a possibility that interim storage facilities for recycled nuclear fuel resources may be constructed on quaternary layers, rather than on hard rock. In such a case, the storage facilities need to be supported by pile foundations or spread foundations to meet the required safety level. The authors have conducted a series of experimental studies on the dynamic behavior of storage facilities supported by pile foundations. A centrifuge modeling technique was used to satisfy the required similitude between the reduced size model and the prototype. The centrifuge allows a high confining stress level equivalent to prototype deep soils to be generated (which is considered necessary for examining complex pile-soil interactions) as the soil strength and the deformation are highly dependent on the confining stress. The soil conditions were set at as experimental variables, and the results are compared. Since 2000, the Nuclear Power Engineering Corporation (NUPEC) has been conducting these research tests under the auspices on the Ministry of Economy, Trade and Industry of Japan.


Author(s):  
Jerry A. McMahan ◽  
Brian J. Williams ◽  
Ralph C. Smith ◽  
Nicholas Malaya

We describe a framework for the verification of Bayesian model calibration routines. The framework is based on linear regression and can be configured to verify calibration to data with a range of observation error characteristics. The framework is designed for efficient implementation and is suitable for verifying code intended for large-scale problems. We propose an approach for using the framework to verify Markov chain Monte Carlo (MCMC) software by combining it with a nonparametric test for distribution equality based on the energy statistic. Our matlab-based reference implementation of the framework is shown to correctly distinguish between output obtained from correctly and incorrectly implemented MCMC routines. Since correctness of output from an MCMC software depends on choosing settings appropriate for the problem-of-interest, our framework can potentially be used for verifying such settings.


2008 ◽  
Vol 148 (2) ◽  
pp. 309-327 ◽  
Author(s):  
Daniel M. Ricciuto ◽  
Martha P. Butler ◽  
Kenneth J. Davis ◽  
Bruce D. Cook ◽  
Peter S. Bakwin ◽  
...  

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