An agent-based framework for fuel cycle simulation with recycling

Simulation of the nuclear fuel cycle is an established field with multiple players. Prior development work has utilized techniques such as system dynamics to provide a solution structure for the matching of supply and demand in these simulations. In general, however, simulation infrastructure development has occured in relatively closed circles, each effort having unique considerations as to the cases which are desired to be modeled. Accordingly, individual simulators tend to have their design decisions driven by specific use cases. Presented in this work is a proposed supply and demand matching algorithm that leverages the techniques of the well-studied field of mathematical programming. A generic approach is achieved by treating facilities as individual entities and actors in the supply-demand market which denote preferences amongst commodities. Using such a framework allows for varying levels of interaction fidelity, ranging from low-fidelity, quick solutions to high-fidelity solutions that model individual transactions (e.g. at the fuel-assembly level). The power of the technique is that it allows such flexibility while still treating the problem in a generic manner, encapsulating simulation engine design decisions in such a way that future simulation requirements can be relatively easily added when needed.