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Conference Spotlight
Nuclear Energy Conference & Expo (NECX)
September 8–11, 2025
Atlanta, GA|Atlanta Marriott Marquis
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Hash Hashemian: Visionary leadership
As Dr. Hashem M. “Hash” Hashemian prepares to step into his term as President of the American Nuclear Society, he is clear that he wants to make the most of this unique moment.
A groundswell in public approval of nuclear is finding a home in growing governmental support that is backed by a tailwind of technological innovation. “Now is a good time to be in nuclear,” Hashemian said, as he explained the criticality of this moment and what he hoped to accomplish as president.
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.