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This division promotes the development and timely introduction of fusion energy as a sustainable energy source with favorable economic, environmental, and safety attributes. The division cooperates with other organizations on common issues of multidisciplinary fusion science and technology, conducts professional meetings, and disseminates technical information in support of these goals. Members focus on the assessment and resolution of critical developmental issues for practical fusion energy applications.
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Fusion Science and Technology
Inspecting nuclear facilities with unmanned aerial systems
Over the past decade, unmanned aerial systems (UASs), more commonly referred to as drones, have played an increasing role in the day-to-day activities of the energy sector. Applications range from visually inspecting wind turbines, flare stacks, pipelines, and facilities to evaluating vegetation encroachment near power lines. Although the benefits of UASs have been reported in these industries, their use in the nuclear community has only recently been explored. For instance, a drone was sent into a waterbox at a Duke Energy facility to inspect for leaks.1 And at Fukushima Daiichi, a drone was used to conduct a post-accident radiation survey inside Unit 3, and drones are being investigated for use inside the damaged containments.2
A. Turner, A. Burns, B. Colling, J. Leppänen
Fusion Science and Technology | Volume 74 | Number 4 | November 2018 | Pages 315-320
Technical Paper | dx.doi.org/10.1080/15361055.2018.1489660
Articles are hosted by Taylor and Francis Online.
Nuclear analysis supporting the design and licensing of ITER is traditionally performed using MCNP and the reference model C-Model; however, the complexity of C-Model has resulted in the geometry creation and integration process becoming increasingly time-consuming. Serpent 2 is still a beta code; however, recent enhancements mean that it could, in principle, be applied to ITER neutronics analysis. Investigations have been undertaken into the effectiveness of Serpent for ITER neutronics analysis and whether this might offer an efficient modeling environment.
An automated MCNP-to-Serpent model conversion tool was developed and successfully used to create a Serpent 2 variant of C-Model. A version of the deuterium-tritium plasma neutron source was also created. Standard reference tallies in C-Model for the blanket and vacuum vessel heating were implemented, and comparisons were made between the two transport codes assessing nuclear responses and computer requirements in the ITER model. Excellent agreement was found between the two codes when comparing neutron and photon flux and heating in the ITER blanket modules and vacuum vessel.
Comparing tally figures of merit, computer requirements for Serpent were typically three to five times that of MCNP, and memory requirements were broadly similar. While Serpent was slower than MCNP when applied to fusion neutronics, future developments may improve this, and Serpent offers clear benefits that will reduce analyst time, including support for meshed geometry, robust universe implementation that avoids geometry errors at the boundaries, and mixed geometry types. Additional work is proceeding to compare Serpent against experiment benchmarks relevant for fusion shielding problems. While further developments are needed to improve variance reduction techniques and reduce simulation times, this paper demonstrates the suitability of Serpent to some aspects of ITER analysis.