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The Education, Training & Workforce Development Division provides communication among the academic, industrial, and governmental communities through the exchange of views and information on matters related to education, training and workforce development in nuclear and radiological science, engineering, and technology. Industry leaders, education and training professionals, and interested students work together through Society-sponsored meetings and publications, to enrich their professional development, to educate the general public, and to advance nuclear and radiological science and engineering.
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Remembering ANS President John Kelly
John Kelly, ANS past president (2018–19 ), passed away peacefully in his sleep on October 3, 2024, in Gilbert Ariz., at the age of 70. Kelly was born on March 9, 1954, and was the eldest of Jack and Aileen Kelly’s six children.
His career, which spanned more than 40 years, began at Sandia National Laboratories in Albuquerque, N.M., where he focused on safety and severe accident analysis. His leadership led him to Washington D.C., where he served as the deputy assistant secretary for nuclear reactor technologies at the U.S. Department of Energy. Kelly played a critical role in shaping nuclear policy and guiding the world through significant events, including the Fukushima Daiichi accident in Japan. At the end of his career, he was honored to serve as the American Nuclear Society’s president. In retirement, he was actively involved with ANS in technology events and mentoring the next generation of scientists.
Kelly is survived by his wife, Suzanne; his children Julie Kelly-Smith (Byron), John A. (Sarah), and Michael (Nicole); and grandchildren Kiri and Kyson Smith and John and Maximilian Kelly. His family was his pride and joy, including his cherished dog, Covie, who brought him happiness in recent years.
In lieu of flowers, donations may be made to the American Nuclear Society or Detroit Catholic Central High School (27225 Wixom Road, Novi, MI 48374). Please designate Memorial and specify John Kelly ’72 Memorial Fund.
In honor of Kelly's commitment to ANS and to celebrate his life, his profile from the July 2018 issue of Nuclear News is published below.
Pew Basu, R. Sarangapani, D. Datta, B. Venkatraman
Nuclear Technology | Volume 208 | Number 7 | July 2022 | Pages 1192-1204
Technical Paper | doi.org/10.1080/00295450.2021.2018275
Articles are hosted by Taylor and Francis Online.
The present study is envisaged with an aim to highlight a novel approach of applying the statistical factorial design analysis (FDA) technique in radiation shielding design. In FDA, the estimated total dose rate (TDR) and concentration of elements in shielding material are termed as “Response” and “Factors.” The impact on the response due to the change in the level of factors is defined as “Effects.” Monte Carlo simulation (MCS) is performed using the MCNP4A code to compute the surface TDRs due to the coupled neutron-gamma field arising from the 740-GBq 241Am-Be source housed inside a shielding container made of composite polymer (CP). The composition of CP is hydrogen, carbon, and oxygen with lead and natural boron as fillers. In the present work, the weight percent of hydrogen, carbon, and lead is optimized in the CP by minimizing the surface TDR at the exit of the shield, and a proposed CP (PCP) is obtained. For the first time, a detailed regression analysis is performed to develop a model linking TDR and the three factors, namely, hydrogen weight percent, carbon weight percent, and lead weight percent. Three levels of each factor are considered, and the impact due to the linear, quadratic, and interaction effects of the factors that influences the TDR is investigated using Student’s t-test analysis. The results from the statistical analysis indicate that the weight percent of hydrogen and lead have a greater influence on TDR. The interaction effects arising out of the combination of hydrogen, carbon, and lead are observed to be negligible. Hence, the regression model is modified by dropping the statistically insignificant terms from the equation, and the new model has shown excellent correlation within ±1% of the estimated TDRs using MCS. The R2 and R2Adj values are found to be 0.99970 and 0.99966, which explains the computation power of the model. The model can be applied to compute the TDRs for any combinations of factors within the range of variability as studied in the present work. The shielding container made of PCP obtained from the present study provides a minimum of 20% reduction in volume and mass compared to the conventional high-density polyethylene and other polymer-based materials.
