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HPS's Eric Goldin: On health physics
Eric Goldin, president of the Health Physics Society, is a radiation safety specialist with 40 years of experience in power reactor health physics, supporting worker and public radiation safety programs. A certified health physicist since 1984, he has served on the American Board of Health Physics, and since 2004, he has been a member of the National Council on Radiation Protection and Measurements’ Program Area Committee 2, which provides guidance for radiation safety in occupational settings for a variety of industries and activities. He was awarded HPS Fellow status in 2012 and was elected to the NCRP in 2014.
Goldin’s radiological engineering experience includes ALARA programs, instrumentation, radioactive waste management, emergency planning, dosimetry, decommissioning, licensing, effluents, and environmental monitoring.
The HPS, headquartered in Herndon, Va., is the largest radiation safety society in the world. Its membership includes scientists, safety professionals, physicists, engineers, attorneys, and other professionals from academia, industry, medical institutions, state and federal government, the national laboratories, the military, and other organizations.
The HPS’s activities include encouraging research in radiation science, developing standards, and disseminating radiation safety information. Its members are involved in understanding, evaluating, and controlling the potential risks from radiation relative to the benefits.
Goldin talked about the HPS and health physics activities with Rick Michal, editor-in-chief of Nuclear News.
Dan G. Cacuci
Nuclear Science and Engineering | Volume 184 | Number 1 | September 2016 | Pages 31-52
Technical Paper | dx.doi.org/10.13182/NSE16-31
Articles are hosted by Taylor and Francis Online.
This work presents an illustrative application of the second-order adjoint sensitivity analysis methodology (2nd-ASAM) to a paradigm nonlinear heat conduction benchmark, which models a conceptual experimental test section containing heated rods immersed in liquid lead–bismuth eutectic (LBE). This benchmark admits an exact solution, thereby making transparent the underlying mathematical derivations. The general theory underlying 2nd-ASAM indicates that for a physical system comprising Nα parameters, the computation of all of the first- and second-order response sensitivities requires (per response) at most Nα large-scale computations using the first-level adjoint sensitivity system (1st-LASS) and second-level adjoint sensitivity system (2nd-LASS), respectively. For this illustrative problem, six large-scale adjoint computations sufficed to compute exactly all 5 first-order and 15 distinct second-order derivatives of the temperature response to the five model parameters. The construction and solution of the 2nd-LASS require very little additional effort beyond the construction of the adjoint sensitivity system needed for computing the first-order sensitivities. Very significantly, only the sources on the right sides of the heat conduction differential operator needed to be modified; the left side of the differential equations (and hence the solver in large-scale practical applications) remains unchanged.
The second-order sensitivities play the following roles: (1) They cause the expected value of the response to differ from the computed nominal value of the response; for the nonlinear heat conduction benchmark, however, these differences were insignificant over the range of temperatures (400 to 900 K) considered. (2) They contribute to increasing the response variances and modifying the response covariances, but for the nonlinear heat conduction benchmark, their contribution was smaller than that stemming from the first-order response sensitivities, over the range of temperatures (400 to 900 K) considered. (3) They provide the leading contributions to causing asymmetries in the response distribution. For the benchmark test section considered in this work, the heat source, the boundary heat flux, and the temperature at the bottom boundary of the test section would cause the temperature distribution in the test section to be skewed significantly toward values lower than the mean temperature. On the other hand, the model parameters entering the nonlinear, temperature-dependent expression of the LBE conductivity would cause the temperature distribution in the test section to be skewed significantly toward values higher than the mean temperature. These opposite effects partially cancel each other. Consequently, the cumulative effects of model parameter uncertainties on the skewness of the temperature distribution in the test section are such that the temperature distribution in the LBE is skewed slightly toward higher temperatures in the cooler part of the test section but becomes increasingly skewed toward temperatures lower than the mean temperature in the hotter part of the test section. Notably, the influence of the model parameter that controls the strength of the nonlinearity in the heat conduction coefficient for this LBE test section benchmark would be strong if it were the only uncertain model parameter. However, if all of the other model parameters are also uncertain, all having equal relative standard deviations, the uncertainties in the heat source and boundary heat flux diminish the impact of uncertainties in the nonlinear heat conduction coefficient for the range of temperatures (400 to 900 K) considered for this LBE test section benchmark.
Ongoing work aims at generalizing the 2nd-ASAM to enable the exact and efficient computation of higher-order response sensitivities. The availability of such higher-order sensitivities is expected to affect significantly the fields of optimization and predictive modeling, including uncertainty quantification, data assimilation, model calibration, and extrapolation.