Autonomous dynamic decision making in fuel cycle simulators using a game theoretic approach
| dc.contributor.advisor | Haas, Derek Anderson, 1981- | |
| dc.contributor.advisor | Leibowicz, Benjamin D. | |
| dc.contributor.committeeMember | Landsberger, Sheldon | |
| dc.contributor.committeeMember | Wilson, Paul | |
| dc.creator | Phathanapirom, Urairisa Birdy | |
| dc.creator.orcid | 0000-0002-8992-4917 | |
| dc.date.accessioned | 2019-09-05T21:05:27Z | |
| dc.date.available | 2019-09-05T21:05:27Z | |
| dc.date.created | 2018-12 | |
| dc.date.issued | 2018-12 | |
| dc.date.submitted | December 2018 | |
| dc.date.updated | 2019-09-05T21:05:28Z | |
| dc.description.abstract | 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. | |
| dc.description.department | Mechanical Engineering | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | https://hdl.handle.net/2152/75732 | |
| dc.identifier.uri | http://dx.doi.org/10.26153/tsw/2834 | |
| dc.language.iso | en | |
| dc.subject | Nuclear fuel cycle | |
| dc.subject | Systems analysis | |
| dc.subject | Sequential decision making under uncertainty | |
| dc.subject | Game theory | |
| dc.title | Autonomous dynamic decision making in fuel cycle simulators using a game theoretic approach | |
| dc.type | Thesis | |
| dc.type.material | text | |
| thesis.degree.department | Mechanical Engineering | |
| thesis.degree.discipline | Mechanical Engineering | |
| thesis.degree.grantor | The University of Texas at Austin | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy |
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