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Conference Spotlight
2025 ANS Winter Conference & Expo
November 9–12, 2025
Washington, DC|Washington Hilton
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Dry Ice Blasting: A Game-Changer for Safe Cleaning and Decontamination in Nuclear Power Plants
The nuclear energy industry is critical not only for meeting the world’s growing demand for electricity but also for advancing global decarbonization goals. As the sector evolves—through life extensions of existing plants, decommissioning, innovations like small modular reactors (SMRs) and microreactors, and new facility construction—the need for safe, efficient, and environmentally responsible maintenance and decommissioning continues to grow. Whether a plant is coming online, operating beyond its original design life, or entering decommissioning, cleanliness and operational integrity remain non-negotiable. That’s where dry ice blasting stands out—a powerful, safe cleaning method ideally suited for the high-stakes demands of nuclear environments.
Brian C. Kiedrowski
Nuclear Science and Engineering | Volume 185 | Number 3 | March 2017 | Pages 426-444
Technical Paper | doi.org/10.1080/00295639.2017.1283153
Articles are hosted by Taylor and Francis Online.
Since the 1960s, Monte Carlo methods have been used to compute the effect of perturbations on system responses and for computing sensitivity coefficients. This review article focuses on 21st-century developments specific to k-eigenvalue calculations. The theory of correlated sampling, differential operator sampling, and adjoint-based approaches and their historical methods from the 20th century are briefly summarized. Specific focus is given to four recent and significant developments: fission source correction using the correlated sampling and differential operator sampling methods, adjoint-based perturbations for the k eigenvalue using the iterated fission probability method, an extension to reaction rate ratios using generalized perturbation theory, and a recent development using a collision history approach allowing for the calculation of sensitivity coefficients of bilinear ratios and generalized responses. Differences and similarities of the four methods are discussed along with a comparison to the 20th-century approaches. A perspective on future developments is also given.