Study on start-up of molten salt fast modular reactor from shutdown based on two-phase flow CFD analysis
Not provided.
Nuclear Science & Technology↗
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Core Model Proposal #373: Add Exogenous Shutdown Decider
This core model proposal adds an exogenous shutdown decider that can scale the output of a vintaged technology in years after its initial operating period. The output can be scaled above or below the technology vintage's original output. This proposal also includes code changes to disable the behavior of the s-curve shutdown decider and profit shutdown decider in calibration periods. The proposal does not include any changes to data to utilize the new exogenous shutdown decider (it only introduces the capability). It should be noted that the exogenous shutdown decider and s-curve shutdown decider serve similar functions and generally should not be used together; however, the exogenous shutdown decider and profit shutdown decider reflect different dynamics and can be used in combination.
97 MATHEMATICS AND COMPUTING↗
Shutdown dose rate analysis with the Shift Monte Carlo radiation transport code and modular verification workflow
Calculation of the shutdown dose rate is crucial for safe fusion reactor operations. The Rigorous-two-step (R2S) method is a method that requires connected neutron transport, activation, and gamma transport. Shift has integrated variance reduction with a deterministic solver Denovo, supports multiple geometry formats, and is scalable. These features make it an attractive transport solver choice for an R2S workflow. An R2S workflow for the Shift Monte Carlo code is developed and compared to the existing Oak Ridge National Laboratory Shutdown Dose Rate Code Suite (ORCS) workflow. Also, a Python framework for integrating two R2S workflows is developed to mix and match each step in the R2S workflow for improved collaboration and verification experience. In this study, results show that the Shift-Denovo R2S workflow and the ORCS workflow calculate the shutdown dose rate of the ITER Shutdown Dose Rate benchmark problem with an average relative error of 2.285%.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Development and validation of fully open-source R2S shutdown dose rate capabilities in OpenMC *
We present the first fully open-source capabilities for shutdown dose rate (SDR) calculations of fusion energy facilities based on the Rigorous 2-Step (R2S) methodology. These capabilities have been implemented in the OpenMC Monte Carlo particle transport code, building on its existing capabilities while also leveraging new features that have been added to the code to support SDR calculations, such as decay photon source generation. Each of the individual physics components in the R2S workflow—neutron transport, activation, decay photon source generation, and photon transport—have been verified through code-to-code comparisons with MCNP6.2 and FISPACT-II 4.0. These comparisons generally demonstrate excellent agreement between codes for each of the physics components. The full cell-based R2S workflow was validated by performing a simulation of the first experimental campaign from the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For short cooling times, the dose calculated by OpenMC agrees with the experimental measurements within the stated experimental uncertainties. For longer cooling times, an overprediction of the shutdown dose was observed relative to experiment, which is consistent with previous studies in the literature. Altogether, these features constitute a combination of capabilities in a single, open-source codebase to provide the fusion community with a readily-accessible option for SDR calculations and a platform for rapidly analyzing the performance of fusion technology.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A knowledge-informed large language model framework for U.S. nuclear power plant shutdown initiating event classification for probabilistic risk assessment
Identifying and classifying shutdown initiating events (SDIEs) is critical for developing shutdown probabilistic risk assessment for nuclear power plants. Existing computational approaches cannot achieve satisfactory performance due to the challenges of unavailable large, labeled datasets, imbalanced event types, and label noise. To address these challenges, we propose a hybrid pipeline that integrates a knowledge-informed machine learning model to prescreen non-SDIEs and a large language model (LLM) to classify SDIEs into four types. In the prescreening stage, we proposed a set of 44 SDIE text patterns that consist of the most salient keywords and phrases from six SDIE types. Text vectorization based on the SDIE patterns generates feature vectors that are highly separable by using a simple binary classifier. The second stage builds Bidirectional Encoder Representations from Transformers (BERT)-based LLM, which learns generic English language representations from self-supervised pretraining on a large dataset and adapts to SDIE classification by fine-tuning it on an SDIE dataset. The proposed approaches are evaluated on a dataset with 10,928 events using precision, recall ratio, F 1 score, and average accuracy. In conclusion, the results demonstrate that the prescreening stage can exclude more than 97% non-SDIEs, and the LLM achieves an average accuracy of 95.1% for SDIE classification.
99 - GENERAL AND MISCELLANEOUS↗
Particle balance of deuterium during deuterium shattered pellet injection shutdown in DIII-D
A particle balance analysis was conducted during a deuterium (D 2 ) shattered pellet injection-induced plasma shutdown on the DIII-D tokamak to determine why less than 20% of the pellet material is assimilated into the core plasma by the mid-current quench (CQ). Initially, most of the D 2 is injected as frozen shards and ionized upon entering the vessel. During the thermal quench, ionized particles move to the divertors and subsequently to the center post (CP) walls, where they rapidly recycle and partially accumulate as neutrals without assimilating into the core plasma. In contrast, the particle flux to the outer midplane walls is negligible, despite being accompanied by hot plasma with electron temperatures exceeding 100 eV. During mid-CQ, volume recombination effects, although not large enough to impact overall particle balance, were significant enough to require accounting for accurate interpretation of fast-framing camera D-alpha signals and the estimation of the CP wall particle flux. In addition, toroidal asymmetries, observed in measurements of toroidal electron density perturbations and the phase of magnetohydrodynamic modes, are present throughout the shutdown and can account for a discrepancy in the assimilation rate for up to 50% of the observed D 2 particle inventory. These sources and sinks of particles and fluxes were identified using absolutely calibrated D-alpha brightness and Langmuir probes.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Measurement of near- and far-field impurity flows during pellet-induced rapid shutdown in DIII-D
Both near-field (<1 m away toroidally from the pellet) and far-field (>1 m away toroidally from the pellet) poloidal and toroidal impurity (carbon ion) flows are measured using visible imaging and fast bolometry during a polypropylene pellet-induced rapid plasma shutdown in the DIII-D tokamak. In the near field, the pellet appears to increase poloidal flow in the ion diamagnetic direction, possibly due to the strong radial temperature gradient caused by the pellet ablation. In the far field, the poloidal impurity flow typically appears slower and in the opposite direction. Toroidal impurity flow appears to be strongly influenced by the plasma initial toroidal rotation, especially in the far field. These results demonstrate that rapid shutdown impurity flows are not necessarily global in structure but can be quite different close to and far from the injected pellet.
Electromagnetic radiation detectors↗
Flexible Operation of Natural Gas Power Plants in Texas: Startup and Shutdown Durations and Nitrogen Dioxide Emissions
This dataset provides insights into historical flexible operation of natural gas power plants in Texas, with a focus on startup and shutdown events. The dataset includes tables summarizing startup and shutdown durations as well as nitrogen oxide (NOx) emission factors during these events, and compares these emission factors with those observed during all other operating phases (referred to here as “steady-state operation”). The dataset is derived using the U.S. Environmental Protection Agency (EPA)’s Clean Air Markets Program Data (CAMPD). Historical hourly data from 2015–2024, including electricity generation, heat input, and NOx emission factors, are used for natural gas combined cycle units, combustion turbine units, and steam turbine units in Texas. This work was authored by the National Laboratory of the Rockies, operated by the Alliance for Energy Innovation, LLC, for the U.S Department of Energy (DOE) under contract no. DE-AC36-08GO28308. Funding was provided by the U.S. Department of Energy as part of its Grid Modernization Laboratory Consortium, a strategic partnership between DOE and the national laboratories to bring together leading experts, technologies, and resources to collaborate on the goal of modernizing the nation’s grid. The views expressed in the dataset do not necessarily represent the views of the DOE or the U.S. Government.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Automated power-following control for nuclear thermal propulsion startup and shutdown using MOOSE-based applications
This paper describes an investigation of various automated control strategies applied to a full-core multiphysics Griffin/Bison/RELAP-7 model of a prototypical nuclear thermal propulsion system. In all cases, control is achieved by actuating control drums based on the demanded power and predicted quantities from the numerical model. One key finding is that hybrid proportional integral derivative controllers – a novel type of controller that uses both power and reactivity predicted signals – can demonstrate a level of performance rivaling that of period-generated control. The former requires parameter tuning, while the latter mostly necessitates providing reactivity coefficients and temperature rates of change, which could be very challenging to accurately measure in real-time. In addition, decay heat plays an important role in determining cooling requirements during cooldown phases. A decay heat model, accounting for burn time and throttling, was derived, and is incorporated within the model to simulate the steady-state and shutdown phases and satisfyingly follow the power demand. However, temperature overshoots and non-constant specific impulse during throttling will necessitate further improvements.
33 ADVANCED PROPULSION SYSTEMS↗
Comprehensive Analysis of Streaming and Shutdown Dose Rate Experiments at JET with ORNL Fusion Neutronics Workflows
Current experimental fusion systems and conceptual designs of fusion pilot plants (FPPs) are growing in complexity and size. Several radiation metrics are crucial to the safe operation of fusion machines, including neutron flux streaming through openings and the shutdown dose rate (SDDR). Most current designs of advanced experimental fusion systems—and the most probable candidates for FPPs—are based on the tokamak concept, which is prone to neutron streaming through the myriad openings needed for diagnostic and support systems. SDDR is caused by decay gamma rays from radionuclides that become activated by neutrons during the operation of a fusion system that use deuterium-deuterium (DD), tritium-tritium, or deuterium-tritium plasma. Because computational tools have become essential for determining these radiation metrics, they must be validated against reliable and applicable experimental data. Experiments at the Joint European Torus (JET) provide a unique source of experimental data for validating computational tools and nuclear data used to determine SDDR and neutron fluxes in streaming-dominated geometries. Here, this paper presents the comprehensive analysis of the high-performance DD JET SDDR, and streaming experiments performed using Oak Ridge National Laboratory (ORNL) fusion workflows. The computational results were compared with experimental results that consist of online SDDR measurements with ionization chambers and neutron fluence streaming measurements using thermoluminescent detectors. The ratio of calculated-to-experimental SDDR values ranges from 0.6 to 2.5, and the streaming results range from 0.5 to 8.0. Future work will include analyzing the JET 2021 DTE2 campaign alongside the integration of the Shift Monte Carlo transport code into all ORNL fusion neutronics workflows.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Implementation of the D1S Methodology for Shutdown Dose Rate Calculations in the OpenMC Monte Carlo Particle Transport Code
We present an implementation of the direct one-step (D1S) methodology for shutdown dose rate (SDR) calculations in the OpenMC Monte Carlo particle transport code. In addition to being the first fully open-source D1S implementation, it is also the first to require no ad hoc source code or nuclear data library modifications. The code can seamlessly switch between production of prompt and decay photons based on a user input parameter, and the decay data needed for decay photon generation are made available through a depletion chain file, which is already used for OpenMC’s built-in depletion/activation solver. A set of Python functions significantly eases the burden of computing and applying time correction factors needed to properly account for the time dependence of radionuclide activity. To assess the accuracy of the D1S implementation, SDR calculations have been carried out for three problems: a prism of iron irradiated by 14-MeV neutrons, the ITER port plug computational benchmark, and the Frascati Neutron Generator (FNG) ITER dose rate benchmark problem from the Shielding INtegral Benchmark Archive and Database (SINBAD). For each of these problems, comparisons were made to calculations using the rigorous two-step (R2S) method. The results on the iron prism problem illustrate how the D1S method achieves superior spatial resolution compared to the R2S method without the need for spatial discretization of the activation regions. The D1S and R2S results for the ITER port plug benchmark agree well with previously reported results in the literature. While the D1S results are 10% to 15% lower than the R2S results, this may be due to stochastic uncertainty and/or spatial discretization in the R2S calculations. On the FNG dose rate benchmark problem, the D1S method produces dose rate estimates that are within 4% of the dose rates predicted using a cell-based R2S workflow. The D1S estimates of the SDR are also in reasonable agreement with the experimental measurements and show the same basic trends that have been observed in previous works. A qualitative analysis of the execution time and uncertainty for the R2S and D1S workflows suggests that the D1S method would attain a higher figure of merit.
D1S method↗
A New Shutdown Dose Rate Benchmark Problem for Representative Fusion Applications
Here, this work introduces a new benchmark problem for calculating shutdown dose rates (SDDRs) aimed at fusion reactor applications. The model is designed to represent a simplified version of a typical ITER port plug. The responses of interest include neutron flux, gamma flux, and gamma SDDR at 12 different locations scattered throughout the port. This article outlines the geometry specifications of the problem, provides material definitions for the components, specifies the required responses to be calculated, and presents the source definition information. The need for this benchmark arises from the limited availability of publicly accessible references, with only one benchmark representing the typical dimensions and materials found in fusion systems. This existing benchmark has been cited extensively, reflecting the demand within the scientific community to test both established and novel workflows for SDDR calculations. However, since its presentation at a conference in 2011, the results have become increasingly well known. Moreover, the absence of formal publication and peer review has led to the details of this benchmark being extracted from secondary sources, such as subsequent studies that reference it. As a result, analysts are left with significant flexibility in interpreting the key parameters, which can be adjusted to account for unknown systematic errors, ultimately reproducing the already well-known responses. This new benchmark serves as an updated version of that earlier work, with the aim of providing a more reliable description of the materials and their impurities, which is crucial for assessing activation and subsequent gamma emission. Additionally, it seeks to provide a geometry that more closely represents an ITER port plug. The improvements in the problem definition will lead to a more reproducible benchmark problem, while also presenting the radiation transport community with a completely new challenge. The results will be published in a future article to allow analysts adequate time to analyze this problem independently.
Benchmark↗
Applying AI/ML Techniques to Nuclear Operating Experience Program and Low-Power Shutdown Initiating Event Study
This is a presentation to the INL AI/ML Activities Workshop in May 2023 discussing the application of AI/ML in nuclear operating experience program and low power shutdown initiating event study.
99 GENERAL AND MISCELLANEOUS↗
ECAR-7448 Rev 0 MARVEL Post-Shutdown Dose Analysis in the Upper Confinement
This report documents a bounding post-shutdown dose rates over time in the upper confinement area and above the top of the TREXc Pit Shield at the end of two years of operation of the MARVEL microreactor. The dose rates take into consideration the doses from the core fission products, the sodium-potassium coolant (NaK), the steel components, the Stirling engines, and the gallium eutectic (EGaInSn) secondary coolant. The MCNP model in this analysis is based on the 90% design of the MARVEL reactor from ECAR- 7447. Neutron fluence used as inputs to this analysis were calculated in ECAR-7447.
21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
ALICE upgrades during the LHC Long Shutdown 2
A Large Ion Collider Experiment (ALICE) has been conceived and constructed as a heavy-ion experiment at the LHC. During LHC Runs 1 and 2, it has produced a wide range of physics results using all collision systems available at the LHC. In order to best exploit new physics opportunities opening up with the upgraded LHC and new detector technologies, the experiment has undergone a major upgrade during the LHC Long Shutdown 2 (2019–2022). This comprises the move to continuous readout, the complete overhaul of core detectors, as well as a new online event processing farm with a redesigned online-offline software framework. These improvements will allow to record Pb-Pb collisions at rates up to 50 kHz, while ensuring sensitivity for signals without a triggerable signature.
47 OTHER INSTRUMENTATION↗
Validation of Pronghorn’s subchannel code using EBR-II shutdown heat removal tests: SHRT-17 and SHRT-45R
Not Available
42 ENGINEERING↗
Trepanning Graphite Samples at a Shutdown Magnox Reactor: A US-UK Joint Exercise for Nuclear Verification
In April 2022, a team sponsored by the US DOE Office of Nuclear Verification (ONV) shipped trepanning equipment to the nuclear power station at Trawsfynydd, Wales, UK to collect samples from the graphite moderator of Reactor 1. The sampling campaign to collect 48 graphite samples was completed in five weeks beginning July 11. Half the samples will be analyzed in the US to determine the total energy production of the facility. The other half will be analyzed by Magnox Ltd. to support decisions for options for the ultimate decommissioning path for the facility. This paper provides a description of the equipment and the operations required to trepan, collect, and package the samples while controlling the small amounts of radioactive graphite dust entrained on and within the tool. The most important sample parameter needed is the precise location of the sample, to within ±6 mm in a fuel channel, while the tool is deployed to between 12 and 20 meters below the operations floor; our means of achieving this precision is given.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Validation of Pronghorn’s Subchannel code using the EBR-II shutdown heat removal tests
A Subchannel application (Pronghorn-SC) is developed in MOOSE, which affords the required flow field resolution, while still preserving an engineering-scale approach. This new solver can be natively coupled to Pronghorn and other MOOSE objects to enable full-core, multi-physics, multi-scale engineering studies. This work utilizes the EBR-II SHRT tests to validate the subchannel capabilities. Multi-scale and multi-physics coupling is used to improve the fidelity of the subchannel code calculations.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗