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
Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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
Jan 2025
Jul 2024
Latest Journal Issues
Nuclear Science and Engineering
February 2025
Nuclear Technology
January 2025
Fusion Science and Technology
Latest News
Biden executive order to facilitate AI data center power
As demand for artificial intelligence and data centers grows, President Biden issued an executive order yesterday aimed to ensure clean-energy power supply for the technology.
Thomas E. Booth
Nuclear Science and Engineering | Volume 156 | Number 3 | July 2007 | Pages 403-407
Technical Paper | doi.org/10.13182/NSE07-A2707
Articles are hosted by Taylor and Francis Online.
A method to provide an unbiased Monte Carlo estimate of the reciprocal of an integral is described. In Monte Carlo transport calculations, one often uses a single sample as an estimate of an integral. This paper shows that a similar situation exists with respect to a single sample for an unbiased estimate of the reciprocal of an integral. If an appropriate approximation to the integrand is known, then obtaining a single unbiased estimate of the reciprocal of an integral will not be much more time consuming than obtaining a single unbiased estimate of the integral itself.