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Radiation Protection & Shielding
The Radiation Protection and Shielding Division is developing and promoting radiation protection and shielding aspects of nuclear science and technology — including interaction of nuclear radiation with materials and biological systems, instruments and techniques for the measurement of nuclear radiation fields, and radiation shield design and evaluation.
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2024 ANS Annual Conference
June 16–19, 2024
Las Vegas, NV|Mandalay Bay Resort and Casino
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Former Exelon CEO Chris Crane remembered for “transformational milestones”
Crane
Exelon announced that Chris Crane, the company’s former chief executive, passed away on Saturday in Chicago at the age of 65.
Crane served as the company’s president and CEO from 2012 until his retirement in December 2022. During his tenure, he steered the energy company through several transformational milestones, including the successful mergers with Constellation Energy in 2012 and Pepco Holdings in 2016, creating the largest utility business by customer count in the United States.
In 2022, with the spin-off of Constellation as the generation and retail side of energy business (with the largest U.S. nuclear fleet), Crane led the creation of a stand-alone transmission and delivery energy company.
John Pevey, Briana Hiscox, Austin Williams, Ondřej Chvála, Vladimir Sobes, J. Wesley Hines
Nuclear Science and Engineering | Volume 196 | Number 12 | December 2022 | Pages 1559-1571
Technical Paper | doi.org/10.1080/00295639.2021.1987133
Articles are hosted by Taylor and Francis Online.
This paper presents a gradient-informed design optimization of nuclear reactor core components based on neutronics objectives with both continuous and discrete materials. The main argument in favor of using gradient-informed design optimization is that it scales well with increasing dimensionality of the design space. First, a challenge problem with 121 free parameters is solved with a gradient-informed method and then with a genetic algorithm. Then, a challenge problem to optimize the flux profile of a simplified assembly with eight axial zones is solved. Both challenge problems are solved using directly calculated derivatives from Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI) in the SCALE package. This work also demonstrates how a discrete optimization problem—selection of materials for 121 voxels—can be lifted into a continuous problem with mixed materials. In the continuous space, adjoint-based gradients are well-defined, and gradient descent is applicable. Then, a forcing function is introduced that with the selection of an appropriately sized hyperparameter can be used to guide the optimized continuous solution back into a discrete solution. This paper presents an account of the challenges that were faced when applying a gradient-informed optimization algorithm using a Monte Carlo calculation to estimate the gradient information and compares a gradient descent optimization method to a genetic algorithm optimization of the same geometry. Overall, this work demonstrates the potential use of adjoint-based gradient calculations in design optimization of nuclear systems.