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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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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Latest News
Shifting the paradigm of supply chain
Chad Wolf
When I began my nuclear career, I was coached up in the nuclear energy culture of the day to “run silent, run deep,” a mindset rooted in the U.S. Navy’s submarine philosophy. That was the norm—until Fukushima.
The nuclear renaissance that many had envisioned hit a wall. The focus shifted from expansion to survival. Many utility communications efforts pivoted from silence to broadcast, showcasing nuclear energy’s elegance and reliability. Nevertheless, despite being clean baseload 24/7 power that delivered a 90 percent capacity factor or higher, nuclear energy was painted as risky and expensive (alongside energy policies and incentives that favored renewables).
Economics became a driving force threatening to shutter nuclear power. The Delivering the Nuclear Promise initiative launched in 2015 challenged the industry to sustain high performance yet cut costs by up to 30 percent.
Ely M. Gelbard
Nuclear Science and Engineering | Volume 94 | Number 3 | November 1986 | Pages 274-276
Technical Note | doi.org/10.13182/NSE86-A17271
Articles are hosted by Taylor and Francis Online.
Two different descriptions have been used for Monte Carlo source biasing. One relies on a direct optimization of biasing parameters, the other on an intuitive application of the adjoint flux. But use of the adjoint flux is based on the assumption that importance sampling will be used throughout the calculation, and that source sampling will not be stratified. It is shown that if these conditions are not satisfied, use of the importance functions has no theoretical justification and, in principle, biasing parameters must be optimized directly.
