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Las Vegas, NV|Mandalay Bay Resort and Casino
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ANS names new Fellows, award winners ahead of Annual Meeting
The American Nuclear Society extends its congratulations to the new ANS Fellows and recipients of this year’s honors and awards, which will be presented at the President’s Special Session during the opening plenary of the 2024 ANS Annual Conference. Those being honored this year have made outstanding contributions to nuclear science and technology. The full list of awards follows below.
Robert Nshimirimana, Ajith Abraham, Gawie Nothnagel, Andries Engelbrecht
Nuclear Technology | Volume 207 | Number 1 | January 2021 | Pages 147-166
Technical Paper | doi.org/10.1080/00295450.2020.1740562
Articles are hosted by Taylor and Francis Online.
A manual approach to radiography process optimization is a time-consuming and labor-intensive process. Therefore, a virtual environment in which all of the processes of optimization for a desired radiography experiment or setup are conducted is highly desirable. Such an environment should be able to provide the capability to arrive at radiographic scanning parameters that are optimized to within preset criteria for design purposes. In this paper, a simplified approach toward achieving this is described, and calculated radiography results are benchmarked against experiments. A ray-tracing technique combined with the exponential law of attenuation was used to provide the primary function of such a virtual environment, which is the modeling of the radiography system. Radiography quality parameters such as contrast, penetration, unsharpness, and resolution were calculated using predefined definitions and fed directly into a particle swarm optimization routine that searched for the best radiography design parameters in an iterative feedback loop between the simulator and the optimizer modules. The aim of this paper is to show that a rather simple radiography simulation approach can already provide sufficient data for system design optimization purposes without the need to develop or utilize a comprehensive, competitive radiography simulator. The simplified approach provides a direct “uncomplicated” virtual environment for basic radiography training and basic experimental planning.