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2026 Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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What’s the most difficult question you’ve been asked as a maintenance instructor?
Blye Widmar
"Where are the prints?!"
This was the final question in an onslaught of verbal feedback, comments, and critiques I received from my students back in 2019. I had two years of instructor experience and was teaching a class that had been meticulously rehearsed in preparation for an accreditation visit. I knew the training material well and transferred that knowledge effectively enough for all the students to pass the class. As we wrapped up, I asked the students how they felt about my first big system-level class, and they did not hold back.
“Why was the exam from memory when we don’t work from memory in the plant?” “Why didn’t we refer to the vendor documents?” “Why didn’t we practice more on the mock-up?” And so on.
Marc A. Cooper, Edward W. Larsen
Nuclear Science and Engineering | Volume 137 | Number 1 | January 2001 | Pages 1-13
Technical Paper | doi.org/10.13182/NSE00-34
Articles are hosted by Taylor and Francis Online.
A new method for efficiently solving global Monte Carlo particle transport problems is presented. (In these problems, flux information is desired across the entire system, not just at a small number of detector locations.) The method is based on the use of a weight window that distributes Monte Carlo particles uniformly throughout the system. This (a) ensures that all subregions of the system are adequately sampled and (b) controls the particle weights, even in subregions far from sources. The weight window is constructed from an approximate deterministic solution of the forward transport problem. It is argued that a weight window based on the forward transport solution is more appropriate for global problems than the more familiar concept of basing a weight window on an adjoint solution for source-detector problems. It is also shown that by using Monte Carlo-generated Eddington factors in deterministic solutions of the quasi-diffusion equation, one can inexpensively compute updated forward-based weight windows and obtain a more efficient global Monte Carlo calculation.