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
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
Standards Program
The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
Latest Magazine Issues
Aug 2025
Jan 2025
Latest Journal Issues
Nuclear Science and Engineering
September 2025
Nuclear Technology
Fusion Science and Technology
August 2025
Latest News
New report lays out path to U.S. nuclear energy dominance
The new report “How America Can Achieve Nuclear Energy Dominance,” from the Working Group on U.S. Nuclear Energy Dominance, outlines a plan of action for the Trump administration that includes deploying new nuclear reactors, developing domestic supply chains, promoting nuclear exports, reforming regulations, and developing the workforce.
Working group chair Todd Abrajano said, “We welcome the Trump administration’s bold moves to kick-start the U.S. nuclear energy sector, but we recognize that President Trump’s executive orders alone can’t achieve our goals.”
Toshihiro Yamamoto, Hiroki Sakamoto
Nuclear Science and Engineering | Volume 198 | Number 8 | August 2024 | Pages 1607-1619
Research Article | doi.org/10.1080/00295639.2023.2266623
Articles are hosted by Taylor and Francis Online.
The inverse reactor period α is a fundamental mode eigenvalue of the α-mode nonlinear Boltzmann eigenvalue equation that considers delayed neutron contributions. Thus far, several Monte Carlo methods, including the α-k, weight balancing, and transition rate matrix methods, have been developed to calculate α. This study presents a new Monte Carlo method for predicting α by using the derivatives of the k-eigenvalue with respect to α. Formulae are derived to calculate the first and second derivatives using the differential operator sampling method. The key feature of the new proposed method is its ability to estimate the uncertainty of the predicted α by considering the uncertainty of the k-eigenvalue and its derivatives with respect to α.