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Division Spotlight
Human Factors, Instrumentation & Controls
Improving task performance, system reliability, system and personnel safety, efficiency, and effectiveness are the division's main objectives. Its major areas of interest include task design, procedures, training, instrument and control layout and placement, stress control, anthropometrics, psychological input, and motivation.
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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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NuScale Energy Exploration Center opens at SC State
NuScale Power Corporation’s latest Energy Exploration (E2) Center has opened at South Carolina State University, in Orangeburg. E2 Centers are designed to provide visitors with hands-on experiences in simulated scenarios of operations at nuclear power plants. NuScale has established 10 such centers around the world. The company officially presented the fully installed E2 Center to SC State on May 21, after a collaborative setup and training process was completed.
S. K. Fraley, T. J. Hoffman
Nuclear Science and Engineering | Volume 70 | Number 1 | April 1979 | Pages 14-19
Technical Paper | doi.org/10.13182/NSE79-A18923
Articles are hosted by Taylor and Francis Online.
Two methods to improve the variance of statistical flux-at-a-point estimators over conventional unbounded estimators are developed that are readily implemented in multigroup Monte Carlo radiation transport computer codes. The theory behind the methods is developed, and the procedures for their application to Monte Carlo computer codes are outlined where necessary for clarity. Their application is demonstrated by the solution of a sample problem. These methods do not require a modification of the random walk, are easily implemented in multigroup Monte Carlo computer codes, and provide results that are comparable to other finite variance techniques.