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
April 2026
Nuclear Technology
February 2026
Fusion Science and Technology
Latest News
Going Nuclear: Notes from the officially unofficial book tour
I work in the analytical labs at one of Europe’s oldest and largest nuclear sites: Sellafield, in northwestern England. I spend my days at the fume hood front, pipette in one hand and radiation probe in the other (and dosimeter pinned to my chest, of course). Outside the lab, I have a second job: I moonlight as a writer and public speaker. My new popular science book—Going Nuclear: How the Atom Will Save the World—came out last summer, and it feels like my life has been running at full power ever since.
P. E. McGrath, W. K. Foell
Nuclear Science and Engineering | Volume 45 | Number 3 | September 1971 | Pages 237-244
Technical Paper | doi.org/10.13182/NSE71-A19076
Articles are hosted by Taylor and Francis Online.
A new collision probability formulation of integral transport theory is applied in the analysis of small-sample reactivity measurements. The calculational technique features a blending of diffusion theory, used to represent the unperturbed reactor, and integral transport theory, used to represent the sample and that portion of the reactor significantly perturbed by the sample. The theory forms the basis for a perturbation theory computer program, COPERT, which, in conjunction with the one-dimensional diffusion theory program MACH-1, has been applied to the analysis of central reactivity measurements in the ZPR-3 fast critical assembly. The method provides a convenient means of accounting for sample-size effects.