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Preprint ANL/MCS-P1833-0111 Gradient-Enhanced Universal Kriging for Uncertainty Propagation in Nuclear Engineering
 

Summary: Preprint ANL/MCS-P1833-0111
Gradient-Enhanced Universal Kriging for Uncertainty Propagation in Nuclear Engineering
Brian A. Lockwood*
and Mihai Anitescu+
*
University of Wyoming, Department of Mechanical Engineering, 1000 E. University
Avenue, Laramie, WY 82071. E-mail: blockwoo@uwyo.edu
+
Argonne National Laboratory, Mathematics and Computer Science Division, 9700 S. Cass
Avenue, Argonne, IL 60439. E-mail: anitescu@mcs.anl.gov
In this work, we investigate a surrogate for modeling
the response of a simulated nuclear engineering system
for use in uncertainty propagation. Building on our recent
work using a gradient-enhanced regression approach, we
examine the ability of a universal gradient-enhanced
Kriging model to provide a means for inexpensive
uncertainty quantification.
I. INTRODUCTION
In this work, we wish to rapidly characterize the
distribution of simulation outputs based on the probability

  

Source: Anitescu, Mihai - Mathematics and Computer Science Division, Argonne National Laboratory

 

Collections: Mathematics