Cyclus Newsletter May 2018



Cyclus

Greetings! Warm weather is upon us and the Cyclus development team is looking forward to a productive summer. This past fall and spring have been busy for us! Accordingly, we still have some wonderful things to share.

Developments

Cyclus has been undergoing a number of changes recently. These changes have not been released in a full version as of yet. However, as they are forthcoming the following is a list of changes coming with the next release.

  • New Decision Phase: This phase occurs at the end of a time step and allows agents to make decisions about the operations that occured during the time step.

  • TimeSeriesRecord Updates: This update allows agents to see the TimeSeriesRecord calls from other agents if they desire.

Third Party Modules

D3ploy

This package is designed to manage the deployment of facilities automatically based on a increasing demand. It uses autoregressive time series methods to predict future demand and supply from historical data.

Information on this can be obtained at the github page. https://github.com/ergs/d3ploy

Peddler

This agent aims to simulate trucks that transport materials between facilities. It is currently under development. If you’re interested in this agent for use or development please contact Robert Flanagan at flanagrr@mailbox.sc.edu.

News

Gyu Tae Park received an undergrad research award for his geopositioning work with Cyclus. Information about the award can be found here. http://arfc.github.io/jekyll/update/2018/04/20/park-ugrad-award/

Dr. Paul Whitney from Pacific Northwest National Laboratory visited CNERG at the University of Wisconsin-Madison as a Consortium for Verification Technology Lab Fellow to discuss the use of Cyclus as part of an ongoing effort to simulate misuse and diversion in nuclear fuel cycles. This use case is similar to the work funded by the CVT project at UW-Madison and Dr. Whitney bring valuable experience with applying machine learning and decision analysis methodologies to this problem.

Publications

  • Gwendolyn Chee, Jin Whan Bae, and Kathryn D. Huff. Numerical Experiments For Testing Demand-Driven Deployment Algorithms. In American Nuclear Society 2018 National Student Conference. Gainsville, Florida, 2018.

  • R. Flanagan and A. Scopatz. USING AUTOREGRESSIVE MOVING AVERAGE METHOD TO DETERMINE THE DEPLOYMENT OF NUCLEAR FUEL CYCLE FACILITIES . In Physor 2018. Cancun, Mexico, April 2018.