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
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
March 2026
Nuclear Technology
February 2026
Fusion Science and Technology
April 2026
Latest News
Pacific Fusion pulsed-power facility to host external users
Concept art of Pacific Fusion’s demonstration system. (Image: Pacific Fusion)
Pacific Fusion is preparing to start construction on a pulsed-power inertial fusion facility in New Mexico, and today the company announced it is seeking expressions of interest from researchers in industry, academia, and government who may want to run experiments at the facility.
Indrajeet Singh, S. B. Degweker, Amod Kishore Mallick, Anurag Gupta
Nuclear Science and Engineering | Volume 193 | Number 8 | August 2019 | Pages 868-883
Technical Paper | doi.org/10.1080/00295639.2019.1576453
Articles are hosted by Taylor and Francis Online.
In a recent paper, we described the development of a method for calculating exact collision probabilities between different regions (namely, fuel kernels, graphite matrix, moderator, and coolant) of a lattice cell of a high temperature reactor (HTR) of the pebble bed variety. The method was shown to adequately represent the double heterogeneity in such reactors. In the present paper, we use some of the results obtained in that paper to construct a fast Monte Carlo algorithm for treatment of HTRs. This paper discusses the theoretical basis of the Monte Carlo algorithm, its implementation for the case of a lattice cell with the energy variable treated using a multigroup library, and results obtained. The method can be easily extended to full-core calculations using point cross-section data.