Cerberus Nuclear hosted the 47th Shielding Forum meeting online this week. It had been hoped that the meeting would be held as part of the ANSWERS Seminar as usual; however, due to ongoing restrictions associated with COVID19 an online format was once again chosen, with the experience of hosting the previous meeting online making for a smoother and more involved process.
Attendees from Cerberus Nuclear, ARC, Atkins, Aurora, BAE Systems, Cavendish Nuclear, Davis & Musgrove, EDF, Edvance UK, INS, Jacobs, Magnox Ltd, Mott MacDonald, NNL, ONR, Orano, PHE, Rolls-Royce, RPS, Sellafield Ltd, SRP, STFC, Tokamak Energy, TUV SUD and UKAEA were there and the meeting was very well received by all participants.
Learning from the previous meeting was taken onboard and the opportunity was taken to break participants out into smaller groups to discuss topics of interest. Answers from these groups were obtained and collated using the online collaboration tool Menti, which allowed word clouds to be generated of the results. This was considered to be a very successful exercise by all concerned.
“Once again, a big thank you to all attendees of TSF47, online engagement from members was up even from the last meeting, which itself far exceeded expectations. Therefore, we would like to thank everyone for their contributions during the meeting, particularly during the breakout sessions and to those who provided technical presentations for the meeting.”
Daniel Cork (TSF Chair)
One of the best received technical presentations was given by Cerberus’ own Peter Evans. The presentation was on Eddy, a program (freely available on GitHub either as an EXE or as source code) that Pete has written that takes MCNP outputs and processes them into a much more user-friendly HTML format. Significant interest was shown in the program from participants who use MCNP as their primary or cross-check shielding code and Pete fielded numerous questions on the current and planned capabilities of the program.
The next TSF members meeting (TSF48) is currently due to be held in May 2021 at the ANSWERS Seminar, COVID19 allowing. Further details will be found closer to the event at https://www.shieldingforum.com/.
Eddy - MCNP & SCALE Html Generator
Cerberus Nuclear has created Eddy, an open-source Html output generator for MCNP and SCALE. The function of Eddy is to parse MCNP and SCALE output files into an easy-to-read and user-friendly format. Eddy has been written to work for both radiation transport and criticality calculations.
Eddy collates key information from an output file so that it can be quickly reviewed. Normalisation factors can also be specified to simplify interpretation of tally outputs.
Eddy Html outputs include:
Normalised Tally Results with Error
Highlighted Statistical Checks
K-effective and Error
Comments and Warnings
Cell Mass and Volumes
Full MCNP Input
Eddy is simple to use from the command line or via its built-in interface. Hyperlinks within the Html enable the user to navigate to the required part of the output with ease.
The Html output from Eddy assists in the preparation of technical reports supports QA processes and improves workflow efficiency. The contained nature of the Html output and its small file size also facilitates the sharing of calculation outputs for independent review purposes.
If you would like to provide any feedback or would like to request additional features please get in touch by emailing firstname.lastname@example.org
RWM Criticality Safety Framework
We are really pleased to announce that Cerberus Nuclear and Galson Sciences Limited have teamed up to support Radioactive Waste Management (RWM) on their Criticality Safety Framework. We believe our combined criticality teams offer RWM a really strong capability, with a blend of operational criticality safety experience and unique repository operational expertise. We are looking forward to working on a wide range of tasks during this exciting time for GDF development in the UK.
Kimberley has joined Cerberus Nuclear after working with us on a project to use deep learning and computer vision to identify defects on the surface of waste containers. Kimberley is a developer specialising in data science and she holds a Master’s degree in Advanced Computer Science. Kimberley has contributed to several successful machine learning and computer vision projects, both in her academic career and in industry. Her experience includes machine learning, medical imaging and bioinformatics, as well as natural language processing and front-end development.