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Accelerator Applications
The division was organized to promote the advancement of knowledge of the use of particle accelerator technologies for nuclear and other applications. It focuses on production of neutrons and other particles, utilization of these particles for scientific or industrial purposes, such as the production or destruction of radionuclides significant to energy, medicine, defense or other endeavors, as well as imaging and diagnostics.
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2025 ANS Annual Conference
June 15–18, 2025
Chicago, IL|Chicago Marriott Downtown
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!
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BREAKING NEWS: Trump issues executive orders to overhaul nuclear industry
The Trump administration issued four executive orders today aimed at boosting domestic nuclear deployment ahead of significant growth in projected energy demand in the coming decades.
During a live signing in the Oval Office, President Donald Trump called nuclear “a hot industry,” adding, “It’s a brilliant industry. [But] you’ve got to do it right. It’s become very safe and environmental.”
Scott A. Turner, Edward W. Larsen
Nuclear Science and Engineering | Volume 127 | Number 1 | September 1997 | Pages 22-35
Technical Paper | doi.org/10.13182/NSE127-22
Articles are hosted by Taylor and Francis Online.
A new automated variance reduction method for the Monte Carlo simulation of multigroup neutron transport source-detector problems is described. The method is based on a modified transport problem that can be solved by analog Monte Carlo with zero variance. The implementation of this modified problem is impractical, in part because it requires the exact solution of an adjoint transport problem. The new local importance function transform (LIFT) method is developed to overcome this difficulty by approximating the exact adjoint solution with a piecewise-continuous function containing parameters that are obtained from a deterministic adjoint calculation. The transport and collision processes of the transformed Monte Carlo problem bias source distribution, distance to collision, and selection of postcollision energy groups and directions. A companion paper provides numerical results that demonstrate the efficiency of the LIFT method.