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
Apr 2026
Jan 2026
Latest Journal Issues
Nuclear Science and Engineering
June 2026
Nuclear Technology
March 2026
Fusion Science and Technology
May 2026
Latest News
DOE selects first companies for nuclear launch pad
The Department of Energy’s Office of Nuclear Energy and the National Reactor Innovation Center have announced their first selections for the Nuclear Energy Launch Pad: three companies developing microreactors and one developing fuel supply.
The four companies—Deployable Energy, General Matter, NuCube Energy, and Radiant Industries—were selected from the initial pool of Reactor Pilot Program and Fuel Line Pilot Program applicants, the two precursor programs to the launch pad.
T. W. Petrie, G. H. Miley
Nuclear Science and Engineering | Volume 64 | Number 1 | September 1977 | Pages 151-162
Technical Paper | doi.org/10.13182/NSE77-A27086
Articles are hosted by Taylor and Francis Online.
Phase-space grouping techniques have been applied to two distinct problems in fusion product physics: (a) slowing down drift motion of highly energetic alpha particles in a symmetric toroidal field, and (b) first wall loading by 3.52-MeV alpha particles resulting from magnetic ripple. In the former, a weighted energy-loss approximation method permits the evolving orbits to be determined for any representative phase-space group. This enables rapid computation of several important suprathermal effects in a tokamak plasma. For example, code SYMALF, which embodies this idea, is applied to plasma heating and alpha-particle thermalization source problems. In the ripple field case, a probabilistic density function is employed to determine drift losses associated with ripple-trapped, 3.52-MeV alpha particles. When used to determine 3.52-MeV alpha-particle wall loadings, code RIPALF, which is based on this probability function, predicts the position of local “hot spots” along the first wall.