Demand-Driven Deployment Capabilities in Cyclus, a Fuel Cycle Simulator

The present U.S. nuclear fuel cycle faces challenges that hinder the expansion of nuclear energy technology. The U.S. Department of Energy identified four nuclear fuel cycle options that make nuclear energy technology more desirable. Successfully analyzing the transitions from the current fuel cycle to these promising fuel cycles requires a nuclear fuel cycle simulator that can predictively and automatically deploy fuel cycle facilities to meet user-defined power demand. This work introduces and demonstrates the demand-driven deployment capabilities in Cyclus, an open-source nuclear fuel cycle simulator framework. User-controlled capabilities such as time-series forecasting algorithms, supply buffers, and facility preferences were introduced to give users tools to minimize power undersupply in a transition scenario simulation. The demand-driven deployment capabilities are referred to as d3ploy. We demonstrate the capability of d3ploy to predict future commodities’ supply and demand, and automatically deploy fuel cycle facilities to meet the predicted demand in four transition scenarios. Using d3ploy to set up transition scenarios saves the user simulation setup time compared to previous efforts that required a user to manually calculate and use trial and error to set up the deployment scheme for the supporting fuel cycle facilities.