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2026 Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
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Nuclear power’s new rule book: Managing uncertainty in efficiency, safety, and independence
The U.S. nuclear industry is standing at its most volatile regulatory moment yet—one that will shape the trajectory and the safety of the industry for decades to come. Recent judicial, legislative, and executive actions are rewriting the rules governing the licensing and regulation of nuclear power reactors. Although these changes are intended to promote and accelerate the deployment of new nuclear energy technologies, the collision of multiple legal shifts—occurring simultaneously and intersecting with profound technological uncertainties—is overwhelming the Nuclear Regulatory Commission and threatening to destabilize investor and industry expectations.
Luis A. Perles, Dragan Mirkovic, Gabriel O. Sawakuchi, Uwe Titt
Nuclear Technology | Volume 175 | Number 1 | July 2011 | Pages 22-26
Technical Paper | Special Issue on the 16th Biennial Topical Meeting of the Radiation Protection and Shielding Division / Radiation Biology; Radiation Used in Medicine | doi.org/10.13182/NT11-A12264
Articles are hosted by Taylor and Francis Online.
In this work we present a Monte Carlo study of proton irradiation of lung parenchyma phantoms for particle energies that are typically used for proton therapy, ranging from 150 to 200 MeV. The Bragg peaks of the proton beams were scored in a water phantom distal to voxelized slabs of lung material. A detailed lung parenchyma phantom was modeled and converted into a voxelized structure, with a resolution similar to that obtained by computed tomography, to study differences in the dose deposited by the proton beams distal to the phantom caused by merging small structures into larger voxels. The results show that the Bragg peak dose in water can vary by up to 11%, the distal edge degradation can be as large as 1.1 mm, and the maximum observed changes in the range at 90% of the dose are 0.4 mm in water. From our results, we conclude that computational proton dose predictions in a lung are associated with large uncertainties. To improve the accuracy of dose calculations, a more detailed model of lung parenchyma is needed.