Evaluating the Benefits of Nuclear–Data Center Tight Integration: Enhancing Plant Utilization via Heat-Driven Absorption Cooling
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Cho, So-Bin↗
Engineering topics
Stauff, Nicolas
Publications and source records attributed to Stauff, Nicolas.
NE-COST plug-in: Expanding ACCERT's Capabilities for Life-Cycle Cost Modeling
The Algorithm for the Capital Cost Estimation of Reactor Technologies (ACCERT) is a structured methodology and software tool designed to simplify and standardize cost estimation for nuclear reactor technologies [1]. By utilizing a relational database structure and modular cost estimation algorithms, ACCERT delivers a robust, flexible, and scalable framework for evaluating costs across various reactor types and configurations [2]. The recent integration of the NE-COST plugin further expands ACCERT’s scope by introducing detailed life-cycle cost modeling and probabilistic analysis of uncertainties. This addition enables users to evaluate costs across front-end processes such as uranium enrichment and fabrication, as well as back-end activities including waste disposal and geologic storage. Through Monte Carlo statistical cost simulations, the plugin provides probabilistic insights into cost ranges, offering critical decision-making support for stakeholders including reactor developers, policymakers, and researchers.
Zhou, Jia↗
Status of New Models Hosted on the Virtual Test Bed (VTB) in 2024
The National Reactor Innovation Center (NRIC) mission is to support deployment of novel reactor concepts. This is achieved by providing physical and virtual spaces for building and testing various components, systems, and complete pilot plants. The Virtual Test Bed (VTB) represents the virtual counterpart to the physical test bed. It is in development in collaboration with the Department of Energy’s (DOE) Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. The mission of the VTB is to accelerate the deployment and licensing of advanced reactors by leveraging state-of-the-art modeling and simulation (M&S) tools developed by the DOE NEAMS program. This is accomplished by three primary means: (1) openly hosting simulations that showcase analysis capabilities, (2) continuously testing the models hosted against code updates to avoid deprecation, and (3) filling key M&S gaps that are relevant for the physical NRIC test beds. The VTB repository consists of two sub-entities: 1. A documentation website detailing the models (https://mooseframework.inl.gov/virtual_test_bed). 2. A GitHub repository that hosts the corresponding files (https://github.com/idaholab/virtual_test_bed). Previous documentation on the models hosted in the VTB can be found in [1,2,3,4]. These references also include additional background information on the various NEAMS codes showcased in the VTB (which is omitted here for brevity). This paper primarily provides a status update of the most recent additions to the repository.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Nuclear Energy Cost Estimates for Net Zero World Initiative – 2024 Update
This report provides recommended parameters for incorporating nuclear energy systems into decarbonization modeling scenarios. The values are primarily intended for the Net Zero World (NZW) Initiative but are expected to prove useful to other related efforts. Both costs and operational metrics are provided in the study for large reactors and small modular reactors (SMR).
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Meta-Analysis of Advanced Nuclear Reactor Cost Estimations
Supporting Data can be downloaded at: https://gain.inl.gov/content/uploads/4/2024/06/INL-RPT-24-77048-R1.xlsx Nuclear energy is a critical cornerstone of the current United States clean energy supply and may play a larger role in the future in support of a transition to a net-zero economy. The current fleet of nuclear reactors predominantly consists of large light-water reactors (LWRs), while many of the reactor designs under consideration are smaller and/or different technologies. Because these new designs have not yet been built, there is a high degree of uncertainty associated with their cost. This complicates energy-planning efforts because cost projections are not always standardized, consistent, and centralized in an easily accessible location. To help support energy planning in the US, this report provides advanced nuclear cost ranges using a transparent methodology along with other relevant information that can be used to help support decision making and energy planning. The purpose of this work was to conduct a methodical process for cost evaluation using only public information that was vetted with the end-goal to provide reference cost projections for nuclear energy. To provide a solid basis for these values, the approach and assumptions are explicitly laid out throughout the report allowing any user of the data to challenge or reconsider them. Because future US nuclear-reactor costs are still unknown due to little recent observed data, the report opted to compile a comprehensive list of bottom-up estimates and evaluate averages/trends within the data to identify reference ranges. This was deemed preferable to opining on the robustness or validity of one cost estimation versus another. To that end, the work evaluated thousands of lines of cost subaccounts from several bottom-up cost estimates. A wide variety of different reactor types captured in the data are of various sizes and technologies. Some of these reactors will be representative of advanced reactors under development while others will not. Thus, the results here are dependent on the data that are available and the accuracy of the estimates that are used. Each bottom-up estimate was reviewed to determine whether it was complete. Incomplete data sets were corrected to ensure an adequate basis of cross-comparison. The report is not without limitations and should be interpreted as an initial step to develop cost ranges for nuclear technology. Ultimately, future work can build upon the methodology with refined cost estimates to reduce uncertainty. US-based overnight capital cost (OCC) estimates were compiled from extensive data sets into ranges for both large and small reactor sizes for 2030. To project the cost declines over time, learning rates were sampled from literature sources. No SMRs were previously built; hence, learning rates based on bottom-up approaches (e.g., by quantifying the impact stemming from fabrication of different components, modular work, site construction, commissioning) were prioritized. For larger reactors, actual learning rates from deployments were used to project future costs (adjusted to account for standardization or lack thereof between designs). Other costs included are fixed and variable operations and maintenance costs. The final variables were capacity factors and ramp rates to support energy planning.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Recent Advanced Reactor Multiphysics Model Highlights in the Virtual Test Bed (VTB)
The Virtual Test Bed (VTB) host over 30 distinct simulations that showcase state-of-the art capabilities across the national lab complex. An update on the status of models on the VTB is summarized here, along with a more detailed overview of select recent new capabilities to showcase. All of the major advanced reactor types are represented in the VTB. The first example consists of a multiphysics simulation to track the transport of species in Molten Salt Reactors using depletion, advection, and thermochemical calculations. The second consists of a coupled neutronic and thermal hydraulic simulation to validate a gas cooled reactor. The third consist of pebble-bed equilibrium model for a fluoride high-temperature reactor. The fourth is a high-fidelity neutronic and thermal hydraulic model of a liquid metal reactor assembly. And lastly the fifth consists of transient multiphysics simulations of heat pipe microreactors.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗