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Title: Development of a Test System for Verification and Validation of Nuclear transport Simulations

Conference ·
OSTI ID:962255
 [1];  [2];  [3]
  1. Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
  2. General Electric Co., Boston, MA (United States)
  3. University of Florida, Gainesville, FL (United States)

Verification and validation of nuclear data is critical to the accuracy of both stochastic and deterministic particle transport codes. In order to effectively test a set of nuclear data, the data must be applied to a wide variety of transport problems. Performing this task in a timely, efficient manner is tedious. The nuclear data team at Los Alamos National laboratory in collaboration with the University of Florida has developed a methodology to automate the process of nuclear data verification and validation (V and V). This automated V and V process can efficiently test a number of data libraries using well defined benchmark experiments, such as those in the International Criticality Safety Benchmark Experiment Project (ICSBEP). The process is implemented through an integrated set of Python scripts. Material and geometry data are read from an existing medium or given directly by the user to generate a benchmark experiment template file. The user specifies the choice of benchmark templates, codes, and libraries to form a V and V project. The Python scripts generate input decks for multiple transport codes from the templates, run and monitor individual jobs, and parse the relevant output automatically. The output can then be used to generate reports directly or can be stored into a database for later analysis. This methodology eases the burden on the user by reducing the amount of time and effort required for obtaining and compiling calculation results. The resource savings by using this automated methodology could potentially be an enabling technology for more sophisticated data studies, such as nuclear data uncertainty quantification. Once deployed, this tool will allow the nuclear data community to more thoroughly test data libraries leading to higher fidelity data in the future.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States); Univ. of Florida, Gainesville, FL (United States); General Electric Co., Boston, MA (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA), Nuclear Criticality Safety Program (NCSP)
DOE Contract Number:
AC52-06NA25396
OSTI ID:
962255
Report Number(s):
LA-UR-08-05664; LA-UR-08-5664; TRN: US200919%%23
Resource Relation:
Conference: PHYSOR'08: International Conference on the Physics of Reactors, Interlaken (Switzerland), 14 Sep 2008
Country of Publication:
United States
Language:
English