Source Nuclide Density First-Order and Second-Order Sensitivities in Monte Carlo Codes

References

• M. C. G. HALL, “DUCKPOND—A Perturbation Monte Carlo and Its Applications,” Proc. Specialists’ Mtg. Nuclear Data and Benchmarking for Reactor Shielding, Paris, France, October 27–29, 1980, p. 205, Organisation for Economic Co-operation and Development (1980); https://www.oecd-nea.org/jcms/pl_13276/nuclear-data-and-benchmarks-for-reactor-shielding.
   Google Scholar
• M. C. G. HALL, “Cross-Section Adjustment with Monte Carlo Sensitivities: Application to the Winfrith Iron Benchmark,” Nucl. Sci. Eng., 81, 423 (1982); https://doi.org/10.13182/NSE82-A20283.
   Web of Science ®Google Scholar
• H. RIEF, “Generalized Monte Carlo Perturbation Algorithms for Correlated Sampling and a Second-Order Taylor Series Approach,” Ann. Nucl. Energy, 11, 455 (1984); https://doi.org/10.1016/0306-4549(84)90064-1.
   Web of Science ®Google Scholar
• “MCNP User’s Manual, Code Version 6.2,” LA-UR-17-29981, C. J. WERNER, Ed., Los Alamos National Laboratory (Oct. 27, 2017).
   Google Scholar
• J. FAVORITE, “Using the MCNP Taylor Series Perturbation Feature (Efficiently) for Shielding Problems,” Proc. 13th Int. Conf. Radiation Shielding (ICRS-13) and 19th Topl. Mtg. Radiation Protection and Shielding Division of the American Nuclear Society (RPSD-2016), Paris, France, October 3–6, 2016; EPJ Web Conf., 153, 06030 ( 2017); https://doi.org/10.1051/epjconf/201715306030.
   Google Scholar
• R. L. PEREL, J. J. WAGSCHAL, and Y. YEIVIN, “Monte Carlo Calculation of Point-Detector Sensitivities to Material Parameters,” Nucl. Sci. Eng., 124, 197 (1996); https://doi.org/10.13182/NSE96-A24235.
   Web of Science ®Google Scholar
• R. L. PEREL, “Upgrading of the MCSEN Sensitivity Software to Comply with the Current Standard of the MCNP-5 Monte Carlo Code,” Final report on Task 3.1 of the F4E Grant F4E-FPA-168.01 (Feb. 2014).
   Google Scholar
• E. BRUN et al., “TRIPOLI-4®, CEA, EDF and AREVA Reference Monte Carlo Code,” Ann. Nucl. Energy, 82, 151 (2015); https://doi.org/10.1016/j.anucene.2014.07.053.
   Web of Science ®Google Scholar
• S. D. RICHARDS et al., “MONK and MCBEND: Current Status and Recent Developments,” Proc. Joint Int. Conf. Supercomputing in Nuclear Applications and Monte Carlo 2013 (SNA + MC 2013), Paris, France, October 27–31, 2013, American Nuclear Society ( 2013); https://answerssoftwareservice.com/resource/pdfs/mc2013_status.pdf.
   Google Scholar
• J. A. FAVORITE and D. K. PARSONS, “Second-Order Cross Terms in Monte Carlo Differential Operator Perturbation Estimates,” Proc. Int. Conf. Mathematical Methods for Nuclear Applications, Salt Lake City, Utah, September 9–13, 2001, American Nuclear Society ( 2001).
   Google Scholar
• A. CHARLES, ANSWERS Software Service from Jacobs, Personal Communication (Aug. 16, 2022).
   Google Scholar
• Y. NAGAYA et al., “MVP/GMVP Version 3: General Purpose Monte Carlo Codes for Neutron and Photon Transport Calculations Based on Continuous Energy and Multigroup Methods,” Japan Atomic Energy Agency (Mar. 2017); https://doi.org/10.11484/jaea-data-code-2016-018.
   Google Scholar
• Y. NAGAYA, Japan Atomic Energy Agency, Personal Communication (July 28, 2022).
   Google Scholar
• J. TICKNER, “Arbitrary Perturbations in Monte Carlo Neutral-Particle Transport,” Comput. Phys. Commun., 185, 1628 (2014); https://doi.org/10.1016/j.cpc.2014.03.003.
   Web of Science ®Google Scholar
• T. YAMAMOTO and H. SAKAMOTO, “Monte Carlo Sensitivity Calculation in Fixed Source Problems with the Derivative Source Method,” J. Comput. Phys., 460, 111155 (2022); https://doi.org/10.1016/j.jcp.2022.111155.
   Web of Science ®Google Scholar
• J. A. FAVORITE, “Using the MCNP6 Perturbation Capability for Source Nuclide Density Sensitivities,” Proc. 14th Int. Conf. Radiation Shielding and 21st Topl. Mtg. Radiation Protection and Shielding Division of the American Nuclear Society (ICRS 14/RPSD 2022), Seattle, Washington, September 25–29, 2022, p. 312, American Nuclear Society (2022); https://doi.org/10.13182/ICRSRPSD22-37722.
   Google Scholar
• T. E. BOOTH, “A Sample Problem for Variance Reduction in MCNP,” LA-10363-MS, Los Alamos National Laboratory (Oct. 1985); https://mcnp.lanl.gov/pdf_files/la-10363.pdf.
   Google Scholar
• T. HE and B. SU, “On Using Correlated Sampling to Simulate Small Changes in System Response by MCNP,” Ann. Nucl. Energy, 37, 34 (2010); https://doi.org/10.1016/j.anucene.2009.10.006.
   Web of Science ®Google Scholar
• T. HE and B. SU, “Comparison Between Correlated Sampling and the Perturbation Technique of MCNP5 for Fixed-Source Problems,” Ann. Nucl. Energy, 38, 1318 (2011); https://doi.org/10.1016/j.anucene.2011.02.006.
   Web of Science ®Google Scholar
• C. J. SOLOMON, “MCNP Intrinsic Source Constructor (MISC): A User’s Guide,” LA-UR-12-20252, Los Alamos National Laboratory (Mar. 27, 2012).
   Google Scholar
• W. B. WILSON et al., “SOURCES 4C: A Code for Calculating (alpha,n), Spontaneous Fission, and Delayed Neutron SOURCES and Spectra,” Proc. American Nuclear Society/Radiation Protection and Shielding Division 12th Biennial Topl. Mtg., Santa Fe, New Mexico, April 14–18, 2002, American Nuclear Society ( 2002).
   Google Scholar
• J. A. FAVORITE and S. L. WEIDENBENNER, “Sensitivity of a Response to the Composition of an (α,n) Neutron Source,” Proc. 20th Topl. Mtg. Radiation Protection and Shielding Division of the American Nuclear Society (RPSD-2018), Santa Fe, New Mexico, August 26–31, 2018, American Nuclear Society ( 2018).
   Google Scholar
• J. A. FAVORITE, “Second Derivative of an (α,n) Neutron Source with Respect to Constituent Isotope Densities,” Proc. Int. Conf. Mathematics and Computational Methods Applied to Nuclear Science and Engineering (M&C 2019), Portland, Oregon, August 25–29, 2019, p. 2335, American Nuclear Society (2019).
   Google Scholar
• A. ZOIA, Commissariat à l’Énergie Atomique-Saclay, Personal Communication (Oct. 26, 2022).
   Google Scholar
• S. BOURGANEL, O. PETIT, and C. M. DIOP, “Three-Dimensional Particle Transport Using Green’s Functions in TRIPOLI-4 Monte Carlo Code: Application to PWR Neutron Fluence and Ex-Core Response Studies,” Nucl. Technol., 184, 29 (2013); https://doi.org/10.13182/NT13-A19866.
   Web of Science ®Google Scholar
• J. A. FAVORITE, “SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, keff, and α Using PARTISN,” Nucl. Sci. Eng., 192, 1, 80 (2018); https://doi.org/10.1080/00295639.2018.1471296.
   Web of Science ®Google Scholar
• J. A. FAVORITE, “SENSMG: First-Order Sensitivities of Neutron Reaction Rates, Reaction-Rate Ratios, Leakage, keff, α, and Subcritical Multiplication Using PARTISN,” LA-UR-22-28919, Los Alamos National Laboratory (Aug. 22, 2022).
   Google Scholar
• R. E. ALCOUFFE et al., “PARTISN: A Time-Dependent, Parallel Neutral Particle Transport Code System,” LA-UR-17-29704, Los Alamos National Laboratory (Feb. 2022).
   Google Scholar