ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Mar 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
March 2026
Nuclear Technology
February 2026
Fusion Science and Technology
April 2026
Latest News
Fixing the barriers: How new policies can make U.S. nuclear exports competitive again
The United States has a strong marketplace of ideas on future civil nuclear technology. President Trump wants to see 10 large reactors under construction by 2030 and has discussed making $80 billion available for that objective. Evolutionary small modular reactors based on light water reactor technology are on the market now, and the Tennessee Valley Authority expects a construction permit for a project at its Clinch River Site later this year.
M. Dion, G. Marleau
Nuclear Science and Engineering | Volume 183 | Number 2 | June 2016 | Pages 261-274
Technical Paper | doi.org/10.13182/NSE15-60
Articles are hosted by Taylor and Francis Online.
The sensitivity coefficients of self-shielded cross sections to isotopic densities are computed for a subgroup resonance self-shielding model. The method we propose is based on the derivatives of the collision probabilities used in the slowing-down equation. In this work, we look at how the sensitivities vary as a function of the position inside a fuel pin or of the position of a fuel pin within an assembly. Moreover, we evaluate the importance of the superhomogenization factors, used to correct self-shielded cross sections for the subgroup method, on the cross-section sensitivities. We also present a comparison with the Monte Carlo code Serpent where the sensitivity coefficients are approximated using a finite difference method.