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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Unique safety features and licensing requirements of the NuScale small modular reactor

Small modular reactors (SMR) offer a novel approach to the construction and operation of nuclear power plants. The NuScale VOYGR™ plant uses a simplified SMR design that is based on proven light-water reactor technology with substantial improvements in nuclear safety. It consists of a 250 MWt reactor core housed with other primary system components in an integral reactor pressure vessel surrounded by a steel containment vessel, all of which is immersed in a large pool of water that also serves as the ultimate heat sink. At the core of the NuScale safety case are three primary safety systems: the decay heat removal system, the emergency core cooling system, and the containment. The ability of the NuScale Power Module (NPM) passive safety systems to remove core decay heat for an unlimited duration is demonstrated through analysis of a beyond-design-basis extended loss of AC power with no replenishment of water to the ultimate heat sink or operator actions. The NuScale methodology to evaluate an indefinite loss of AC power uses the proprietary NRELAP5 systems analysis computer code. Analysis results show that the reactor coolant system liquid level above the core is maintained and that containment pressure remains below the vessel design pressure. Once full passive air cooling is established, containment pressure and temperature will decrease over time with decreasing core decay heat. NuScale received standard design approval in September 2020 and design certification in January 2023 for its 50 MWe NPM configured as a 12 module plant. NuScale is currently seeking standard design approval to increase its core power to 250 MWt, nominally 77 MWe per module, in a 6-module plant (VOYGR™-6) configuration. The high-level safety of NuScale’s SMR technology is foundational to a new standard of nuclear power plant resilience.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Assessment of NuScale SMR Steam Heat Augmentation for Chemical Plant Decarbonization

Nearly 50% of the total energy consumed by the industrial sector in the United States is used to produce process steam with natural gas and coal-fired boilers1 . This project conducts a technoeconomic assessment of a NuScale Small Modular Reactor (SMR) coupled with a chemical plant as an Integrated Energy System (IES) where nuclear produces steam and electric power to meet the requirements of a large chemical plant. In a 2020 study, ORNL evaluated the feasibility of using advanced SMRs, including the NuScale design, to supply energy to the Eastman Chemical Plant. However, since that report was published, NuScale received NRC approval for its uprated 77 MWe design with 56% more power and has also introduced a high-temperature, high pressure, steam heat-augmentation system, a key focus of the new study. The new study also benefits from revised capital costs, a 10-day refueling outage time, reduced plant staffing, higher capacity factors, and a site boundary Emergency Planning Zone methodology. The study consists of a techno-economic assessment of two possible energy sources (nuclear and natural gas) in a number of steam and power generation configurations (NuScale Power Modules (NPMs), boilers and combinations of both) to satisfy the steam and power demand with the most reliable and cost competitive system. A total of 2,947.3 klb/hr of steam and 72.5 MWe of electricity are required for the demonstration case. A range of scenarios and solutions are explored, from a 12-NPM plant (3,000 MWth)—with excess capacity and redundancy, capable of supplying a significant amount of extra power to the grid—to a 4-NPM (1,000 MWth) plant—supplemented with existing boilers or grid power for redundancy. The study uses historical steam and power data from a chemical plant and examines the sensitivity to natural gas and grid power cost variations. Scenarios with up to two times gas and electricity costs were considered. Profitability in a 60-year time horizon was analyzed, consistent with NuScale’s design life specification. A steady-state site integration and reliability analysis was performed, and trade-offs were identified.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Simulation of the NuScale SMR and Investigation of the Effect of Load-Following on Component Lifetimes

The NuScale SMR has been modelled using the Virtual Environment for Reactor Applications (VERA) multiphysics environment and the results compared with the publicly reported data in the Design Certification Application (DCA). The results show an excellent agreement for the compared axial and radial power distributions, temperature coefficients of reactivity, boron and control rod worths, and fast neutron flux. This NuScale model is then used to investigate the effect of different operational modes on reactor components to determine how flexible load-following operation may affect control rod and reactor pressure vessel (RPV) lifetimes. The control rod degradation is confirmed to primarily affect the silver-indium-cadmium (AIC) rod tip. The degradation rate is observed to follow a non-linear function of core power level where the increase in degradation decreases with insertion depth. For the variation in core power levels expected with current load-following schemes, the total control rod degradation is found to be mild, at 5-10% of usable life per cycle for a reactor operating at <80% power. Nonetheless, this enables load following strategies to be confirmed and/or modified to ensure that control rods do not need to be replaced during the 60+ year life of the reactor. The RPV degradation was found to be almost directly proportional to the core power level and was not overly sensitive to flux shape perturbations. Future work is planned using these damage functions to optimize operation over multiple NuScale SMR units and develop strategies for prognostics and health management.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Towards Realistic and High Fidelity Models for Nuclear Reactor Power Synthesis Simulation with Self-Powered Neutron Detectors

As presented in this report, a weighting function–based inferencing method is being applied to synthesize the power distribution in next-generation and university research reactors based on simulated self power neutron detector (SPND) responses. The overall goal is to assess the impacts of sensor uncertainty and true power distribution perturbations on the error in the synthesized power distribution. Regarding sensor uncertainty, the NuScale Small Modular Reactor (SMR) and the Westinghouse AP1000 serve as testbeds for analyzing the impact of varying the sensor uncertainty, as well as varying the number of sensors per sensor string in the reactor core. The reactor models are informed by Monte Carlo N-Particle (MCNP) neutron flux tallies. For the NuScale SMR and Westinghouse AP1000, the SPND response functions (i.e., the response of the SPNDs to individual segments of fuel) were determined homogeneously. Regarding an analysis of power distribution perturbation detection, the Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor was used as a demonstration case with one particular arrangement of SPNDs; the response functions for this reactor model were determined heterogeneously, making this a uniquely high-fidelity demonstration of perturbation detection. Finally, SPND models generated in the Geometry and Tracking 4 (Geant4) code have been generated and tested for comparison with traditionally implemented analytical SPND models, with the intent for Geant4 integration with the full methodological framework. SPND current outputs as a function of distance from some fuel assembly segment in the NuScale SMR are compared with the analytically determined currents. Results from the sensor uncertainty simulations for the NuScale SMR and AP1000 indicate that the average error in the inferred power distribution on the fuel assembly segment level is reasonably low, being slightly less than the random uncertainty applied to all respective SPNDs in both cores. For example, if all SPNDs in the core have a random uncertainty of 5%, then the corresponding fuel assembly segment level error (i.e. difference between the true and inferred local power) is ~2–3%. However, the maximum error in the inferred power distribution on the fuel assembly segment level can be considerably high (>15%) when SPND random uncertainties start to exceed ~3%. In general, the average and maximum errors in the inferred power distribution were slightly higher in the AP1000 as opposed to the NuScale SMR for the sensor string configurations considered herein. Another result determined from analysis of the sensor uncertainty simulations was that increasing the number of SPNDs per string does not clearly reduce inferred power distribution error and can in fact make the error large in some cases; however, this assessment may skewed due to imposed iteration limits. Results from the perturbation detection demonstration using the high-fidelity TAMU TRIGA model indicate that, given the arrangement of 17 SPND strings and 4 SPNDs per string considered herein, there is a clear, provable ability to infer a localized Gaussian-type peak perturbation in the 3D power distribution. Such a perturbation was detected with an average fuel assembly segment level error of 0.19%, and the general visualization of the detected perturbation clearly indicates that the magnitude and shape were appropriately resolved. Finally, the electrical current output generated by the Geant4 modeled SPND indicates significant magnitude differences than the analytically modeled SPND, demonstrating the need for accurate SPND models which account for finite sensor geometry effects to inform the power synthesis work described herein.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Dispatch analysis of flexible power operation with multi-unit small modular reactors

The relevance of nuclear power plant flexible power operation (FPO) is rising due to increased penetration of variable renewables. Small Modular Reactors (SMRs) such as NuScale are envisaged to have multiple units on one site. This provides opportunities for coordinating FPO between units, but also introduces challenges as common services (e.g., refueling equipment) must be shared between units and fuel loadings may be standardized. It is therefore important to quantify whether FPO with SMRs is economically beneficial. Here, this paper quantifies the economics of FPO on different timescales to analyze refueling outages of such multi-unit SMRs. A 24-h price-taker profit maximization of SMR operation is first solved considering revenues from wholesale power and ancillary service (AS) markets. The results are then used to find the most profitable operation strategy over several years for multiple units at the site accounting for the physics and materials limits on NPP operation, including refueling outages. Results show a small but appreciable participation of nuclear into AS, contributing 4% of revenues. Due to the longer fuel cycle, over a decade of operation the units’ refueling outages drifted by 3 months, ultimately leading to refueling during summer.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Investigating the impact of a multi-module operation environment on the task performance time of human operators – An explanatory study

The worldwide demand for Small Modular Reactors (SMRs) has surged in recent years due to their enhanced safety and versatility in supporting diverse industrial sectors. A unique feature of SMR operation is that a single human operator is responsible for managing multiple modules. Therefore, securing a sufficient amount of human performance data pertaining to this new environment is essential for the safe operation of SMRs. In this explanatory study, a series of experiments were conducted using the NuScale simulator, a representative SMR design, with student operators. A total of 12 student operators were assigned two types of off-normal events and asked to cope with them using paper-based procedures. Subsequently, their task performance times were compared with those of student operators responsible for a single unit based on the Task Complexity (TACOM) measure. Results indicate that the performance of student operators under the experimental conditions of this study degraded by a factor of 2 to 3, depending on the characteristics of the off-normal events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2023

Advanced Modeling and Simulation to Characterize Advanced Boiling Water Reactor Source Terms to Support a Regulatory Approval Pathway for Right-Sized Emergency Planning Zone. Advanced Boiling Water Reactor (A-BWR) Project Phase 2

The United States Department of Energy (US DOE) is currently supporting the development of various small modular reactor (SMR), microreactor and advanced reactor designs. These reactors have improved safety features as compared to conventional Large Light Water Reactors (LLWRs), which include features that improve potential reduction of radiological source terms in the event of design and beyond-design basis accidents. Specifically, some reactors feature a relatively smaller containment volume with respect to the available surface area for fission product deposition; these include Integrated Pressurized Water Reactors (iPWRs), such as the NuScale SMR and SMR-type Boiling Water Reactors (BWRs) such as General Electric-Hitachi’s BWRX-300 design.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Preliminary Process and Instrumentation Design of Advanced Reactor Integration with Refineries and Hydrogen Production Facilities

With the ongoing push to decarbonize energy use and especially greenhouse gas emissions across all sectors, there are incentives to investigate how nuclear reactors may be used to generate clean energy and be used in various energy economies beyond just the electrical grid. Two initial integrations, high temperature steam electrolysis (HTSE) and oil refineries, are investigated in this first DOE Integrated Energy Systems (IES) program detailed industrial integration design report. Increasingly detailed reports are anticipated both for the industries discussed in this report and for additional industries in the future of the program. This report is a robust starting point showing how integration thermodynamic analysis establishes the requirements on the reactor and methods by which those requirements can be evaluated for specific reactor designs. Two Advanced Reactor Demonstration Program awardees are selected as representative designs for their respective technologies: NuScale for light-water reactors (LWRs) and X-Energy for high temperature gas reactors (HTGRs). Other reactor technologies or specific reactor configurations would require specific analysis similar to what is done in this report, thus this report can be a reference point by which to extend this work to other nuclear plant designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Feasibility and strategic implications of deploying nuclear power reactors in Africa

This report assesses the feasibility and strategic implications of deploying nuclear power reactors, including large-scale plants, advanced small modular reactors (SMRs), and microreactors, in African countries. Case studies focus on South Africa, Egypt, Kenya, Ghana, and Nigeria, examining nuclear energy’s role in Africa’s rapidly evolving energy landscape, marked by fast-growing demand, significant electricity access gaps, increasing renewable penetration, and strong policy commitments to industrialization and energy security. Several U.S. reactor technologies and designs are considered based on their development status and readiness for deployment. The analysis finds that nuclear power can provide reliable, clean baseload and flexible generation, as well as high-temperature process heat for desalination, hydrogen production, and industrial applications. However, suitability is highly country-specific, depending on grid size and stability, transmission capacity, cooling water availability, regulatory readiness, and fuel supply chains. Near-term deployment opportunities are strongest for light-water reactors (such as NuScale, BWRX-300, AP300, and SMR-300) that use low-enriched uranium and build on proven technology. More advanced concepts, including gas-cooled, sodium-cooled, molten-salt cooled reactors, and microreactors, will likely be relevant for African deployment in the 2030s or later, contingent on demonstration projects, high-assay low-enriched uranium (HALEU) fuel availability, and mature international licensing frameworks. Economic analysis shows that SMRs are capital-intensive, with projected overnight costs for 300 MWe units in 2025 ranging from approximately 1.4 to 2.6 billion USD per module. The levelized cost of electricity (LCOE) is highly sensitive to the weighted average cost of capital (WACC). Given typically higher financing costs and utility balance-sheet weaknesses in many African countries, bankable project structures will require sovereign guarantees, robust offtake arrangements, and layered financing from export credit agencies, development finance institutions, and vendor nations. Comparisons with recent large nuclear projects in the United Arab Emirates (UAE) and Egypt underscore the central role of state-backed loans, long tenors, and concessional terms. Country case studies illustrate a spectrum of readiness and opportunity. South Africa operates two 920 MWe pressurized light water reactors (totaling 1,840 MWe) at Koeberg and has the most mature regulatory and industrial base, positioning it as a prime candidate for both large reactors and SMRs to replace coal, support desalination, and anchor industrial hubs. Egypt is constructing four VVER-1200 units at El Dabaa with strong state leadership and could later complement this fleet with SMRs for coastal and industrial applications. Kenya and Ghana are advancing through IAEA Milestones with growing institutional capacity and clear interest in SMRs that match their smaller grids and industrialization plans. Nigeria has the largest demand potential but faces acute constraints in grid reliability, project bankability, and regulatory capacity; targeted deployments of large reactors and SMRs near coastal or industrial sites could have high impact if accompanied by major grid upgrades and institutional reforms. The report identifies cross-cutting challenges such as financing, political continuity, public acceptance, nonproliferation and security, waste and back-end management, regulatory capacity, grid adequacy, and long deployment timelines for first-of-a-kind designs, and ANL/NSE-26/3 ii proposes broad directions for resolution. These include stronger multifaceted financing for nuclear, long-term national energy strategies that transcend electoral cycles, proactive stakeholder engagement, strengthened regional and national regulators, and systematic workforce development through centers of excellence and expanded training. The United States should develop partnerships with African countries and offer end-to-end nuclear package similar to those used effectively by competitors: coordinated project development, state-backed financing, long-term fuel services, and durable in-country support through regional offices and sustained workforce/regulatory training. With timely planning, sustained political commitment, and appropriate financing and institutional support, nuclear energy, both large reactors and advanced SMRs, can become a meaningful, though not dominant, pillar of Africa’s future power mix, enhancing energy security, enabling industrial growth, and supporting climate goals.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Evaluation of AI-Enabled Digital Documented Safety Analysis: A Case Study

Safety basis documentation development and review under U.S. Department of Energy (DOE) authorization have emerged as critical constraint throttling deployment of advanced nuclear reactors, with traditional processes demanding extraordinary resource investment that delays the delivery of these technologies. Traditional Documented Safety Analysis (DSA) processes rely on static documents with limited traceability [U.S. DOE]. The regulatory review and engagement processes are similarly constrained, often requiring significant effort and extensive manual verification. The scale of this challenge is exemplified by the U.S. Nuclear Regulatory Commission (NRC) review of the NuScale application, which required over 250,000 staff hours and the evaluation of approximately two million pages of documentation [Bergman 2021]. The volume and complexity of information within nuclear licensing applications or authorization reviews demands innovative approaches to document generation and data management.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Programmable Digital Devices used in Advanced Reactors

This paper introduces the concepts of common cause failure, diversity, and defense-in-depth used by the nuclear industry to analyze resilience in reactors. A survey of publicly traded and private companies building advanced reactors and their licensing status is presented. Safety and non-safety systems found in the NuScale Power design are summarized and the likely hardware and software categories used by those systems are enumerated. The importance of industry partners is highlighted. This paper also identifies an alternate path forward without industry partners to advance the knowledge needed to use artificial intelligence to analyze HBOMs and SBOMs to better understand reactor resiliency.

cybersecurity↗
DOE OSTI2024

Data-Informed Evaluation Framework for Integrated Energy Systems: Insights from Power, Process Heat, and Hydrogen Production Applications

The multi-criteria decision analysis (MCDA) framework provides a systematic evaluation of the diverse preferences and performance metrics associated with alternative solutions. This approach is advantageous over a single-criterion methodology, which are only valid under conditions that assume ceteris paribus or an "apples-to-apples" comparison. However, selecting suitable technologies for integrated energy systems (IES) can be likened to an "apples-to-oranges" comparison, given the heterogeneous factors at stake. These factors include economics and performance parameters, geological compatibility, and environmental impacts. Consequently, past research has often employed a mixture of qualitative and quantitative criteria tailored to the specific interests of each study. While the method proves effective in handling the intricate interplay of criteria, the resulting rankings and scores can vary from study to study. This inconsistency is introduced from the use of subjectively defined thresholds and weights. As a result, decision-makers frequently find it challenging to establish clear connections between specific criteria and the resulting scores, as the transformation of criteria into ordinal scores results in a substantial loss of information. To address this challenge, we introduce a data-informed IES evaluation framework that offers comprehensive, interpretable, and traceable evaluations backed by quantifiable rationale. First, we identified key IES evaluation criteria from a decade of literature, focusing on relevant IES applications in power, process heat, and hydrogen production. We leveraged state-of-the-art cost estimates from the Idaho National Laboratory (INL) and technical data from 78 reactor designs from the International Atomic Energy Agency (IAEA) and the Organization for Economic Co-operation and Development - Nuclear Energy Agency (OECD-NEA). Lastly, we established thresholds by analyzing the mean, variance, root mean square, and slope of values across alternatives, categorizing the preferences of decision-makers into distinct utility functions, such as linear, saturating, exponential, and stepwise. Our approach yielded two main outcomes: (1) it provided consistent assessments across different stakeholder groups and (2) it visualized uncertainties in the decision-making context via comprehensive sensitivity analysis. To demonstrate the impact of our framework, we conducted case studies on 6 reactor designs (AP1000, NuScale, BWRX-300, Xe-100, eVinci, iMSR) for the three applications. Our data-driven framework proved to be highly effective in addressing heterogenous uncertainties faced by varied decision-makers? preferences and IES applications, as well as cost and technical estimates of advanced reactors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗