A methodology for determining the dynamic exchange of resources in nuclear fuel cycle simulation

Simulation of the nuclear fuel cycle can be performed using a wide range of techniques and methodologies. Past efforts have focused on specific fuel cycles or reactor technologies. The CYCLUS fuel cycle simulator seeks to separate the design of the simulation from the fuel cycle or technologies of interest. In order to support this separation, a robust supply–demand communication and solution framework is required. Accordingly an agent-based supply-chain framework, the Dynamic Resource Exchange (DRE), has been designed implemented in CYCLUS. It supports the communication of complex resources, namely isotopic compositions of nuclear fuel, between fuel cycle facilities and their managers (e.g., institutions and regions). Instances of supply and demand are defined as an optimization problem and solved for each timestep. Importantly, the DRE allows each agent in the simulation to independently indicate preference for specific trading options in order to meet both physics requirements and satisfy constraints imposed by potential socio-political models. To display the variety of possible simulations that the DRE enables, example scenarios are formulated and described. Important features include key fuel-cycle facility outages, introduction of external recycled fuel sources (similar to the current mixed oxide (MOX) fuel fabrication facility in the United States), and nontrivial interactions between fuel cycles existing in different regions

Fuel cycle transition simulation capabilities in CYCLUS

Recent interest in advanced reactors and the following need for techno-economic transitions has increased the demand for tools necessary to model complex nuclear fuel cycles (NFCs) and advanced reactor technologies. This thesis demonstrates the capability of CYCLUS , the agent-based fuel cycle simulator, to model, simulate, and analyze real-life fuel cycle transition scenarios. I introduce new methods and tools that use various databases to model and simulate real-world nuclear fuel cycle transition scenarios involving advanced reactor technologies. The work in this thesis contains: (1) benchmarking Cyclus to other nuclear fuel cycle simulators (NFC simulators); (2) developing new methods and tools necessary for modeling and simulating real-world fuel cycle transition scenarios; (3) simulation of both domestic and international nuclear technology transitions. The methods and tools developed for such capabilities include: (1) modeling and simulating past and current nuclear fleets using historic nuclear reactor operations database; (2) modeling individual reactors and their operating history to calculate nuclear material inventory; (3) modeling Molten Salt Reactor (MSR) behavior in a large-scale fuel cycle simulation. Benchmark work shows that CYCLUS results coincide with results from other NFC simulators with minor differences due to modeling choices. Additionally, this thesis demonstrates the CYCLUS capability to effectively model and simulate real-life NFC transition scenarios that involve advanced reactor technologies such as MSRs

Autonomous dynamic decision making in fuel cycle simulators using a game theoretic approach

A novel methodology for optimizing nuclear fuel cycle transitions that captures interactions between a policy maker and electric utility company is presented. The methodology is demonstrated using a two-person general-sum sequential game with uncertainty that is implemented using a nuclear fuel cycle simulator capable of calculating a material- and technology-constrained material balance, coupled to a multi-objective optimization solver. The solver explicitly treats uncertainties using a stochastic programming approach with chance nodes depicted as a Nature player who moves randomly. The methodology is demonstrated through a Transition Game that features tradeoffs between investments in competing reprocessing and waste disposal technologies, dynamic reactor deployment responses to resolutions in reactor capital cost uncertainty, and the influence of capital subsidies on the future nuclear technology mix. Each player in the game uses a unique set of decision criteria to identify optimal near-term hedging strategies that consider all of Nature’s possible moves as well as the other player’s available decisions. These hedging strategies balance the exchange between the risk of immediate action and delay and maintain flexibility to allow for intelligent recourse decisions once uncertainties are resolved. Results from the Transition Game indicate that early transition to high-temperature gas-cooled reactors is preferred, with the option to abandon the transition following a learning period if capital costs are unfavorable. Under these conditions, transition to used fuel recycling in sodium-cooled fast reactors may be spurred by policy incentives under some certain decision criteria weightings. Otherwise, operating with a baseline set of decision criteria weightings, transition to a closed fuel is never observed when players hedge optimally against Nature’s moves. It is only when players have perfect information regarding Nature’s future moves will transition to a closed fuel be observed.Mechanical Engineerin

Automated Problem-Specific Nuclide-Transition Selection for Reduced Order Modeling

A method for automated library reduction for the nuclide generation code Origen was developed for increased computational efficiency. The requirement for a reduced burnup chain micro-depletion code has been identified in many code frameworks in fuel cycles, neutronics, and nonproliferation where the increased accuracy of a micro-depletion code with hundreds, if not thousands, of nuclides is needed. These large library inventories result in relatively large memory requirements and runtimes that become burdensome within codes that require many depletion zones and/or depletion substeps per time step. However, the tracked nuclides do not equally contribute to the problem, and therefore a subset of the total nuclides can be removed from the system with little loss of accuracy. To do this in a generalized manner the application for the libraries need to be considered. To this end a number of metrics are available to measure library accuracy for a given problem, such as depletion inventory, total activity, gamma dose, decay heat, and individual nuclide inventory. Using these metrics, and their sensitivities to nuclide inventories, it is possible to reduce Origen\u27s full inventory of thousands of nuclides to several hundred nuclides while only affecting the metric of interest by less than 1 pcm (per cent mille or 10^(-5)). The method for this problem specific reduction relies on maintaining the physical meaning of the transition system to the highest degree reasonable. This means maintaining the integrity of the subsystem in relation to its behavior within the full system. Though a number of methods to achieve this have been studied, with varying degrees of success, the most successful method is one that takes a layered approach. This method makes an estimate of the final system through the cutting planes method then makes successive corrections to that estimate in each layer to account for the physical behavior of truncating the transition system that is not present in standard system problems

Simulation model to estimate emotions in collaborative networks

This work has been funded in part by the Center of Technology and Systems and the Portuguese FCT-PEST program UID/EEA/00066/2019 (Impactor project), and partly by the GloNet project funded by the European Commission.In recent years, the research on collaborative networks has been pointing to the need to put more emphasis on the social interactions of its participants, along with technical features, as a potential direction to finding solutions to prevent failures and potential conflicts. In this context, a modelling framework called Collaborative EMOtion modelling framework (C-EMO), conceived for appraising the collaborative network emotions that might be present in a collaborative networked environment, is presented, and an implementation approach, based on system dynamics and agentbased simulation modelling techniques, for estimating both the collaborative network emotional state and each member's emotions, is described. The work is divided in two parts: the first considers the design of the models and the second comprises the transformation of these conceptual models into a computer model, providing the proposed simulation model. In order to validate the simulation model, and taking into consideration the novelty of the research area, experiments are undertaken in different scenarios representing several aspects of a collaborative environment and a sensitivity analysis and discussion of the results is performed.publishe