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
Feb 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
February 2026
Nuclear Technology
January 2026
Fusion Science and Technology
Latest News
Godzilla is helping ITER prepare for tokamak assembly
ITER employees stand by Godzilla, the most powerful commercially available industrial robot available. (Photo: ITER)
Many people are familiar with Godzilla as a giant reptilian monster that emerged from the sea off the coast of Japan, the product of radioactive contamination. These days, there is a new Godzilla, but it has a positive—and entirely fact-based—association with nuclear energy. This one has emerged inside the Tokamak Assembly Preparation Building of ITER in southern France.
Nicolas Crouzet, Paul J. Turinsky
Nuclear Science and Engineering | Volume 123 | Number 2 | June 1996 | Pages 206-214
Technical Paper | doi.org/10.13182/NSE96-A24183
Articles are hosted by Taylor and Francis Online.
In solving few-group neutron kinetic equations in multidimensions, one must select time step sizes as a function of time such that the temporal truncation error introduced by the discrete time derivative approximation is limited to ensure the desired fidelity. When using the Euler backward finite difference to approximate the first derivative of the flux—a popular approximation because it ensures numerical stability—the truncation error is know to be O(Δt2) and proportional to the second derivative. By employment of the double-time-step-size technique, modified to reduce the frequency that double-time-step-size solutions are required, an estimate of the second derivative can be obtained, leading to an efficient computational algorithm for determining the near-optimum time-step-size sequence to ensure the desired fidelity.