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.
Division Spotlight
Robotics & Remote Systems
The Mission of the Robotics and Remote Systems Division is to promote the development and application of immersive simulation, robotics, and remote systems for hazardous environments for the purpose of reducing hazardous exposure to individuals, reducing environmental hazards and reducing the cost of performing work.
Meeting Spotlight
ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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
Mar 2025
Jul 2024
Latest Journal Issues
Nuclear Science and Engineering
March 2025
Nuclear Technology
Fusion Science and Technology
February 2025
Latest News
NRC begins special inspection at Hope Creek
The Nuclear Regulatory Commission is conducting a special inspection at Hope Creek nuclear plant in New Jersey to investigate the cause of repeated inoperability of one of the plant’s emergency diesel generators, the agency announced in a February 25 news release.
J. L. Kloosterman, J. E. Hoogenboom
Nuclear Science and Engineering | Volume 117 | Number 1 | May 1994 | Pages 10-21
Technical Paper | doi.org/10.13182/NSE94-A13565
Articles are hosted by Taylor and Francis Online.
An expression to calculate point values (the expected detector response of a particle emerging from a collision or the source) is derived and implemented in the MORSE-SGC/S Monte Carlo code. It is outlined how these point values can be smoothed as a function of energy and as a function of the optical thickness between the detector and the source. The smoothed point values are subsequently used to calculate the biasing parameters of the Monte Carlo runs to follow. The method is illustrated by an example that shows that the obtained biasing parameters lead to a more efficient Monte Carlo calculation.