Monte Carlo techniques for analyzing deep-penetration problems

Journal Article · Sat Feb 01 04:00:00 EST 1986 · Nucl. Sci. Eng.; (United States)

OSTI ID:5903948

Cramer, S N; Gonnord, J; Hendricks, J S

Current methods and difficulties in Monte Carlo deep-penetration calculations are reviewed, including statistical uncertainty and recent adjoint optimization of splitting, Russian roulette, and exponential transformation biasing. Other aspects of the random walk and estimation processes are covered, including the relatively new DXANG angular biasing technique. Specific items summarized are albedo scattering, Monte Carlo coupling techniques with discrete ordinates and other methods, adjoint solutions, and multigroup Monte Carlo. The topic of code-generated biasing parameters is presented, including the creation of adjoint importance functions from forward calculations. Finally, current and future work in the area of computer learning and artificial intelligence is discussed in connection with Monte Carlo applications.

• Research Organization: Oak Ridge National Laboratory, Oak Ridge, TN 37831
• OSTI ID: 5903948
• Journal Information: Nucl. Sci. Eng.; (United States), Journal Name: Nucl. Sci. Eng.; (United States) Vol. 92:2; ISSN NSENA
• Country of Publication: United States
• Language: English

Related Subjects

22 GENERAL STUDIES OF NUCLEAR REACTORS
220100* -- Nuclear Reactor Technology-- Theory & Calculation
ALBEDO
ARTIFICIAL INTELLIGENCE
COMPUTER CALCULATIONS
DATA COVARIANCES
DISCRETE ORDINATE METHOD
MATHEMATICS
MONTE CARLO METHOD
NEUTRON TRANSPORT THEORY
NUMERICAL SOLUTION
OPTIMIZATION
SCATTERING
STATISTICS
TRANSPORT THEORY