Combining GIS Spatial Analysis and PRA Concepts to Support Advanced Reactor Siting
Collaborator: Salisbury University
Background & Objectives
Siting advanced reactors, including small modular reactors (SMRs) and microreactors, presents decision problems that differ fundamentally from those for conventional large light-water reactors (LWRs). Due to their smaller power output, modularity, and suitability for non-conventional locations, advanced reactors may be deployed in large numbers across a geographic region with a wide range of siting characteristics. This transforms siting from a traditional single-site decision into a portfolio decision problem that identifies combinations of sites whose joint selection meets regional reactor deployment objectives. Existing siting frameworks are not designed for this problem structure and treat site selection as a one-time, static decision, without accounting for the temporal dynamics of sequential deployment, where earlier selections affect the feasibility and suitability of later ones. This research develops a computational framework for advanced reactor siting decision analysis by adapting concepts and methods from portfolio decision analysis and nuclear PRA.
Our Approach
This research is organized around three main tasks:
- Conduct a literature review to identify decision criteria relevant to advanced reactor siting. Analyze interdependencies among the decision criteria and represent their causal relationships.
- Develop a geospatial decision-support platform using ArcGIS to evaluate and rank siting portfolios (i.e., sequences of site selections) based on the identified criteria. The platform applies exclusion criteria through spatial screening and aggregates ranking criteria into composite suitability scores through multi-criteria decision analysis (MCDA).
- Integrate PRA concepts and methods with the GIS platform. A dynamic decision tree module is being developed to generate and analyze candidate deployment sequences while capturing the conditional dependencies among successive reactor siting decisions. A sensitivity analysis module adapts PRA importance measures to the siting context, enabling identification of which contextual shifts in the relative weights of the decision criteria and alterations in underlying assumptions significantly influence suitability rankings.
In the PSAM 18 paper, the literature review and baseline GIS platform have been developed, and preliminary suitability results have been presented for the Western PA region. The portfolio decision analysis capability is under development.
Impact and Broader Applicability
- Provide systematic insights to inform regional deployment strategies for SMRs and microreactors, explicitly addressing portfolio-level siting decisions that account for sequential dependencies and criterion interdependencies across candidate locations.
- Support siting decisions for nuclear reactors co-located with large-scale data centers, or coal-to-nuclear transition, where proximity to load, available land, infrastructure access, and community acceptance jointly determine feasible locations.
- The GIS-based decision-support platform developed in this project is expandable to other portfolio siting problems, such as determining the optimal combination of locations for operations and maintenance support centers serving distributed advanced reactor fleets.
References
A. Dozier, D. Ashton, W. Morioka, and T. Sakurahara, "Combining GIS Spatial Analysis and PRA Concepts to Support Advanced Reactor Siting Decisions," Proceedings of the 18th Probabilistic Safety Assessment & Management Conference (PSAM18), Pittsburgh, PA, 2026.