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Nuclear Installations Safety
Devoted specifically to the safety of nuclear installations and the health and safety of the public, this division seeks a better understanding of the role of safety in the design, construction and operation of nuclear installation facilities. The division also promotes engineering and scientific technology advancement associated with the safety of such facilities.
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Nuclear Science and Engineering
Fusion Science and Technology
What is involved in radiation protection at accelerator facilities?
Particle accelerators have evolved from exotic machines probing hadron interactions to understand the fundamentals of our world to widely used instruments in research and for medical and industrial use. For research purposes, high-power machines are employed, often producing secondary particle beams through primary beam interaction with a target material involving many meters of shielding. The charged beam interacts with the surrounding structures, producing both prompt radiation and secondary radiation from activated materials. After beam termination, some parts of the facility remain radioactive and potentially can become radiation hazards over time. Radiation protection for accelerator facilities involves a range of actions for operation within safe boundaries (an accelerator safety envelope). Each facility establishes fundamental safety principles, requirements, and measures to control radiation exposure to people and the release of radioactive material in the environment.
S. Beetham, J. Capecelatro
Nuclear Technology | Volume 209 | Number 12 | December 2023 | Pages 1977-1986
Research Article | doi.org/10.1080/00295450.2023.2178251
Articles are hosted by Taylor and Francis Online.
Turbulence in two-phase flows drives many important natural and engineering processes, from geophysical flows to nuclear power generation. Strong interphase coupling between the carrier fluid and disperse phase precludes the use of classical turbulence models developed for single-phase flows. In recent years, there has been an explosion of machine learning techniques for turbulence closure modeling, though many rely on augmenting existing models. In this work, we propose an approach that blends sparse regression and gene expression programming (GEP) to generate closed-form algebraic models from simulation data. Sparse regression is used to determine a minimum set of functional groups required to capture the physics, and GEP is used to automate the formulation of the coefficients and dependencies on operating conditions. The framework is demonstrated on homogeneous turbulent gas-particle flows in which two-way coupling generates and sustains carrier-phase turbulence.