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Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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INL makes a case for eliminating ALARA and setting higher dose limits
A report just released by Idaho National Laboratory reviews decades of radiation protection standards and research on the health effects of low-dose radiation and recommends that the current U.S. annual occupational dose limit of 5,000 mrem be maintained without applying ALARA—the “as low as reasonably achievable” regulatory concept first introduced in 1971—below that threshold.
Noting that epidemiological studies “have consistently failed to demonstrate statistically significant health effects at doses below 10,000 mrem delivered at low dose rates,” the report also recommends “future consideration of increasing this limit to 10,000 mrem/year with appropriate cumulative-dose constraints.”
C. J. Solomon, A. Sood, T. E. Booth, J. K. Shultis
Nuclear Science and Engineering | Volume 176 | Number 1 | January 2014 | Pages 1-36
Technical Paper | doi.org/10.13182/NSE12-81
Articles are hosted by Taylor and Francis Online.
A method for deterministically minimizing the cost of a single Monte Carlo tally employing weight-dependent weight-window variance reduction has been developed. This method relies on deterministic calculations of the tally's variance and average computational time per history, the product of which is the cost (inverse figure of merit) of the tally calculation. The tally's variance is deterministically computed by solving the history-score moment equations that describe the moments of the tally's score distribution, and the average time per history is computed by solving the future time equation that describes the expected amount of computational time a particle and its progeny require to process to termination. Both equations are solved by the Sn method. Results are presented for one- and two-dimensional problems that demonstrate increased calculation efficiency, by factors of 1.1 to 2, of the optimized problems over standard adjoint (importance) biasing.
