TY - CONF
T1 - Demonstration of demand driven deployment capabilities in cyclus
AU - Chee, Gwendolyn J.
AU - Bae, Jin Whan
AU - Flanagan, Robert R.
AU - Fairhurst Agosta, Roberto E.
AU - Huff, Kathryn D.
N1 - Funding Information:
This research is funded by the Department of Energy (DOE) Office of Nuclear Energy’s Nuclear Energy University Program (Project 16-10512, DE-NE0008567) "Demand-Driven Cycamore Archetypes". The authors want to thank members of the Advanced Reactors and Fuel Cycles (ARFC) group at the University of Illinois at Urbana-Champaign. We also thank our colleagues from the Cyclus community, particularly those in the University of Wisconsin Computational Nuclear Engineering Research Group (CNERG) and the University of South Carolina Energy Research Group (ERGS) for collaborative Cyclus development.
Funding Information:
This research is funded by the Department of Energy (DOE) Office of Nuclear Energy's Nuclear Energy University Program (Project 16-10512, DE-NE0008567) "Demand-Driven Cycamore Archetypes". The authors want to thank members of the Advanced Reactors and Fuel Cycles (ARFC) group at the University of Illinois at Urbana-Champaign. We also thank our colleagues from the Cyclus community, particularly those in the University of Wisconsin Computational Nuclear Engineering Research Group (CNERG) and the University of South Carolina Energy Research Group (ERGS) for collaborative Cyclus development.
PY - 2020
Y1 - 2020
N2 - In this work, we developed demand-driven deployment capabilities in Cyclus, d3ploy. User-controlled capabilities such as supply/capacity buffers, constraint deployment, prediction algorithms, and installed capacity deployment were introduced to give a user tools to minimize commodity undersupply in the simulation. We demonstrate d3ploy's capability to automatically deploy fuel cycle facilities to meet various types of user-defined power demands: constant, linearly increasing, and sinusoidal.
AB - In this work, we developed demand-driven deployment capabilities in Cyclus, d3ploy. User-controlled capabilities such as supply/capacity buffers, constraint deployment, prediction algorithms, and installed capacity deployment were introduced to give a user tools to minimize commodity undersupply in the simulation. We demonstrate d3ploy's capability to automatically deploy fuel cycle facilities to meet various types of user-defined power demands: constant, linearly increasing, and sinusoidal.
UR - http://www.scopus.com/inward/record.url?scp=85081083545&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081083545&partnerID=8YFLogxK
M3 - Paper
AN - SCOPUS:85081083545
SP - 394
EP - 401
T2 - 14th International Nuclear Fuel Cycle Conference, GLOBAL 2019 and Light Water Reactor Fuel Performance Conference, TOP FUEL 2019
Y2 - 22 September 2019 through 27 September 2019
ER -