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From theory to reality
Craig Piercycpiercy@ans.org
Recently, I spent an afternoon at Kairos Power’s Hermes construction site in Oak Ridge, Tenn. What I saw there was not a rendering, not a licensing presentation, not another panel about the future of advanced nuclear. I saw dozens of pilings built to NQA-1 standards. I saw seismic isolators ready for installation. I saw heavy equipment moving dirt and crews preparing concrete and steel.
I also saw a company doing genuinely innovative work with precast concrete techniques that could materially improve how we construct reactors in the future. None of it looked theoretical. It looked industrial.
Rui Zhang, Jonas D. Fontenot, Dragan Mirkovic, John S. Hendricks, Wayne D. Newhauser
Nuclear Technology | Volume 183 | Number 1 | July 2013 | Pages 101-106
Technical Paper | Radiation Transport and Protection | doi.org/10.13182/NT13-A16995
Articles are hosted by Taylor and Francis Online.
Monte Carlo simulations are increasingly used to reconstruct dose distributions in radiotherapy research studies. Many studies have used the MCNPX Monte Carlo code with a mesh tally for dose reconstructions. However, when the number of voxels in the simulated patient anatomy is large, the computation time for a mesh tally can become prohibitively long. The purpose of this work was to test the feasibility of using lattice tally instead of mesh tally for whole-body dose reconstructions. We did this by comparing the dosimetric accuracy and computation time of lattice tallies with those of mesh tallies for craniospinal proton irradiation. The two tally methods generated nearly identical dosimetric results, within 1% in dose and within 1 mm distance-to-agreement for 99% of the voxels. For a typical craniospinal proton treatment field, simulation speed was 4 to 17 times faster using the lattice tally than using the mesh tally, depending on the numbers of proton histories and voxels. We conclude that the lattice tally is an acceptable substitute for the mesh tally in dose reconstruction, making it a suitable potential candidate for clinical treatment planning.