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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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Conference on Nuclear Training and Education: A Biennial International Forum (CONTE 2025)
February 3–6, 2025
Amelia Island, FL|Omni Amelia Island Resort
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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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How to talk about nuclear
In your career as a professional in the nuclear community, chances are you will, at some point, be asked (or volunteer) to talk to at least one layperson about the technology you know and love. You might even be asked to present to a whole group of nonnuclear folks, perhaps as a pitch to some company tangential to your company’s business. So, without further ado, let me give you some pointers on the best way to approach this important and surprisingly complicated task.
Andreas Szeless, Lawrence Ruby
Nuclear Science and Engineering | Volume 45 | Number 1 | July 1971 | Pages 7-13
Technical Paper | doi.org/10.13182/NSE71-A20340
Articles are hosted by Taylor and Francis Online.
A method has been devised to calculate exactly the probability distribution of reactor neutron noise. The distribution is calculated from a complicated generating function which has been known for some time. The method depends on the success achieved in obtaining a closed-form expression for the n'th derivative of a differentiable r-fold composite function. As an application of the technique, exact probability distributions are calculated for a variety of parameters. The resultant distributions are compared with the approximative negative binomial distribution. In some cases, rather similar variances are found, where the negative binomial is not expected to be a good approximation to the exact distribution. The explanation lies in an interlacing of the exact and approximative distributions. A procedure is described for fitting an experimental distribution to the exact distribution, thereby obtaining the best values of the parameters α1 and Y1 ∞. When the negative binomial is a good approximation to the exact distribution, only the product α1 Y1 ∞ can be obtained by the fitting procedure. In such cases, a Feynman-variance experiment can be performed to determine the parameters separately.
