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At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Gamma-ray Spectroscopy in Low-Power Nuclear Research Reactors

Gamma-ray spectroscopy is an effective technique for radioactive material characterization, routine inventory verification, nuclear safeguards, health physics, and source search scenarios. Gamma-ray spectrometers typically cannot be operated in the immediate vicinity of nuclear reactors due to their high flux fields and their resulting inability to resolve individual pulses. Low-power reactor facilities offer the possibility to study reactor gamma-ray fields, a domain of experiments hitherto poorly explored. In this work, we present gamma-ray spectroscopy experiments performed with various detectors in two reactors: The EPFL zero-power research reactor CROCUS, and the neutron beam facility at the Ohio State University Research Reactor (OSURR). We employed inorganic scintillators (CeBr3), organic scintillators (trans-stilbene and organic glass), and high-purity germanium semiconductors (HPGe) to cover a range of typical—and new—instruments used in gamma-ray spectroscopy. The aim of this study is to provide a guideline for reactor users regarding detector performance, observed responses, and therefore available information in the reactor photon fields up to 2 MeV. The results indicate several future prospects, such as the online (at criticality) monitoring of fission products (like Xe, I, and La), dual-particle sensitive experiments, and code validation opportunities.

Pakari, Oskari V. (ORCID:0000000337048190)↗
DOE OSTI2020

A Novel Physiologically Based Model of Creatinine Renal Disposition to Integrate Current Knowledge of Systems Parameters and Clinical Observations

Creatinine is the most common clinical biomarker of renal function. As a substrate for renal transporters, its secretion is susceptible to inhibition by drugs, resulting in transient increase in serum creatinine and false impression of damage to kidney. Novel physiologically based models for creatinine were developed here and (dis)qualified in a stepwise manner until consistency with clinical data. Data from a matrix of studies were integrated, including systems data (common to all models), proteomics‐informed in vitro – in vivo extrapolation of all relevant transporter clearances, exogenous administration of creatinine (to estimate endogenous synthesis rate), and inhibition of different renal transporters (11 perpetrator drugs considered for qualification during creatinine model development and verification on independent data sets). The proteomics‐informed bottom‐up approach resulted in the underprediction of creatinine renal secretion. Subsequently, creatinine‐trimethoprim clinical data were used to inform key model parameters in a reverse translation manner, highlighting best practices and challenges for middle‐out optimization of mechanistic models.

Scotcher, Daniel↗
DOE OSTI2025

Southwest Regional Partnership on Carbon Sequestration: Phase III (Final Scientific/Technical Report)

The Southwest Regional Partnership on Carbon Sequestration (SWP) is one of 7 regional partnerships formed in 2003 under the U.S. Department of Energy’s (DOE) Regional Carbon Sequestration Partnerships (RCSPs) initiative. The overall purpose of the initiative was to help determine and implement the technology, infrastructure, and regulations most appropriate to promote carbon storage in different regions of the country. Covering Arizona, Colorado, New Mexico, Oklahoma, Utah, and parts of Texas, Wyoming, and Kansas, the SWP evaluated regional carbon storage and utilization potential and focused on technologies and sites that could complement the region’s strong position in energy production. The project progressed through three phases: • Phase I (2003–2005): Characterized regional geologic formations and CO 2 sources, assessed sequestration potential, and identified pilot test sites. • Phase II (2005–2013): Conducted small-scale field tests to validate sequestration methods, including geologic and terrestrial projects. • Phase III (2008–2022): Demonstrated large-scale CO 2 injection at a commercial oil field to test monitoring, verification, and long-term storage strategies. This report covers Phase III. The final project site, the Farnsworth Unit (FWU) in Texas, provided real-world testing of reservoir characterization, monitoring, and risk evaluation tools and processes that could be used in any commercial scale carbon capture, utilization, and storage (CCUS) project. Extensive data collection and analysis helped refine best practices for reservoir characterization, injection monitoring, and storage verification. The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Key lessons learned include the importance of robust data management, strategic site selection, regulatory navigation, and effective industry collaboration. The project’s findings will inform ongoing and future carbon storage initiatives. Task 1 (Regional Characterization) • The SWP continued to participate in national outreach efforts and NATCARB. • The SWP evaluated multiple potential sites before selecting the FWU as the primary field test location. Task 2 (Public Outreach and Education) • The SWP contributed to national databases, DOE best practice manuals, and regional geological assessments to support future sequestration efforts. Task 3 (Permitting and Regulatory Compliance) • The SWP ensured compliance with federal and state regulations, including National Environmental Policy Act (NEPA) requirements. • The SWP obtained all necessary permits for drilling, injection, and monitoring activities. Task 4 (Site Characterization and Planning) • The SWP developed work plans for four key activities: characterization, simulation, monitoring and verification, and risk evaluation. • The SWP collected and synthesized legacy data from multiple sources to build initial static geological models and dynamic reservoir models demonstrating project feasibility. • The SWP conducted an initial risk evaluation and developed mitigation plans. Task 5 (Field Operations and Data Collection) • The SWP drilled, logged, and cored three characterization wells to gather critical subsurface data. • The SWP conducted multiple geophysical surveys, including 3D seismic, crosswell seismic, and vertical seismic profiling, to improve reservoir characterization. Task 6 (Monitoring and Verification) • The SWP performed extensive geological characterization using data from characterization wells and seismic surveys. • The SWP established a surface monitoring network to track CO 2 flux in soil gas, groundwater chemistry, and near-surface atmospheric CO 2 levels. • The SWP built and refined reservoir models to study the effects of relative permeability on simulation behavior and improve calibration with experimental data. Task 7 (Risk Assessment and Model Refinement) • The SWP conducted multiple studies to evaluate reservoir integrity, predict CO 2 plume behavior and improve predictive modeling capabilities. • The SWP refined geological models and used them to enhance the accuracy of simulation models. • The SWP continued quantitative risk assessment of top-ranked risks and strengthened the link between qualitative and quantitative risk methodologies.

02 PETROLEUM↗
DOE OSTI2021

ICARUS: new voyage to sterile neutrino search in the Short Baseline Program

The ICARUS collaboration operated the 760-ton T600 detector in a successful three-year physics run at the underground LNGS laboratories studying neutrino oscillations with the CNGS neutrino beam from CERN, and searching for atmospheric neutrino interactions. ICARUS performed a sensitive search for LSND-like anomalous νe appearance in the CNGS beam, which contributed to the constraints on the allowed parameters to a narrow region around $Δm^2=1 e\text{V}^2$, where all the experimental results can be coherently accommodated at 90% C.L. After a significant overhaul at CERN, the T600 detector has been installed at Fermilab. In 2020 cryogenic commissioning began with detector cool down, liquid Argon filling and recirculation. ICARUS has started operations and is presently in its commissioning phase with the aim of collecting its first neutrino events from the Booster Neutrino Beam and the NuMI off-axis beam. The main goal of the first year of ICARUS data taking will then be the definitive verification of the recent claim by NEUTRINO-4 short baseline reactor experiment both in the $ν_μ$ channel with the BNB and in the $ν_e$ with NuMI. After the first year of operations, ICARUS will commence its search for evidence of a sterile neutrino jointly with the SBND near detector, within the Short Baseline Neutrino (SBN) program. The ICARUS exposure to the NuMI beam will also give the possibility for other physics studies such as light dark matter searches and neutrino-Argon cross section measurements. The proposed contribution addresses ICARUS achievements, its status and plans for the new run at Fermilab and the ongoing developments of the analysis tools needed to fulfill its physics program.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Assessment of Condition Monitoring Methods and Technologies for Inservice Inspection and Testing of Nuclear Power Plant Components

This report was prepared for the U.S. Nuclear Regulatory Commission (NRC) to explore the application of advanced technologies toward meeting the current and future regulatory requirements for maintenance and condition monitoring of structures, systems, and components. The advanced technologies considered in this work are advanced sensors and instrumentation, data analytics, machine learning and artificial intelligence (ML/AI), physics-based models, and digital twins (DT). The interest in the application of advanced technologies for condition monitoring in nuclear power plants continues to grow, and current and future licensees are expected to implement advanced technologies as part of their inservice inspection (ISI) and inservice testing (IST) programs. This report delineates the outcomes of an exploratory investigation into the implementation of advanced condition monitoring technologies to address ISI and IST requirements. A thorough review was conducted of the existing regulatory requirements for ISI and IST, along with an analysis of associated industry practices. Additionally, a state-of-the-art assessment was performed on advanced condition monitoring technologies frequently employed in non-nuclear sectors. This research incorporated two nuclear-specific case studies to illustrate the application of these technologies within the current nuclear fleet. The report provides an exhaustive discussion on the technical challenges, considerations, and opportunities associated with the deployment of advanced condition monitoring technologies. The following are key considerations in the application of advanced technologies for the ISI and IST of nuclear power plant components: • Developing adequate verification and validation procedures to confirm the functional and non-functional requirements, • Developing technical capabilities to conduct real-time asset condition monitoring, • Establishing guidance and protocol for modeling and simulation tools to continuously meet regulatory requirements, • Addressing trustworthiness, explainability, and interpretability of ML/AI methods, • Evaluating maintenance activities to maintain an adequate safety margin and avoid undesirable conditions, • Establishing cybersecure condition monitoring programs associated with a computer-based software system, and • Establishing standardized evaluation metrics for advanced condition monitoring programs. Interest in the use of advanced technologies for condition monitoring in ISI and IST programs continues to grow, and the technology is expected to experience rapid and wide industry adoption in the near future. Adoption of advanced technologies for condition monitoring could have novel and unique impacts on regulatory activities associated with ISI and IST programs. The NRC is continuing to explore the regulatory aspects of advanced technologies as part of ISI and IST programs by pursuing additional research in this technical area.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Inversion of Time-Lapse Seismic Reservoir Monitoring Data Using CycleGAN: A Deep Learning-Based Approach for Estimating Dynamic Reservoir Property Changes

Carbon capture and storage is being pursued globally as a geoengineering measure for reducing the emission of anthropogenic CO 2 the atmosphere. Comprehensive monitoring, verification, and accounting programs must be established for demonstrating the safe storage of injected CO 2 . One of the most commonly deployed monitoring techniques is time-lapse seismic reservoir monitoring (also known as 4-D seismic), which involves comparing 3-D seismic survey data taken at the same study site but over different times. Analyses of 4-D seismic data volumes can help improve the quality of storage reservoir characterization, track the movement of injected CO 2 plume, and identify potential CO 2 spillover/leakage from the storage reservoirblue. However, the derivation of high-resolution CO 2 saturation maps from 4-D seismic data is a highly nonlinear and ill-posed inverse problem, often requiring significant computational effort. In this research, we apply a physics-based deep learning method to facilitate the solution of both the forward and inverse problems in seismic inversion while honoring physical constraints. A cycle generative adversarial neural network (CycleGAN) model is trained to learn the bidirectional functional mappings between the reservoir dynamic property changes and seismic attribute changes, such that both forward and inverse solutions can be obtained efficiently from the trained model. We show that our CycleGAN-based approach not only improves the reliability of 4-D seismic inversion but also expedites the quantitative interpretation. Our deep learning-based workflow is generic and can be readily used for reservoir characterization and reservoir model updates involving the use of 4-D seismic data.

58 GEOSCIENCES↗
DOE OSTI2024

Summary of FY2024 Experimental Results to Support Development of New Inelastic Material Models and Validation of Section III, Division 5, Class A Design Rules

To address the data gap crucial for updating existing viscoplastic constitutive material models for the Class A materials in the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code, Section III, Division 5, High Temperature Reactors (ASME, 2023) for inelastic design analysis, Oak Ridge National Laboratory (ORNL) conducted experimental studies on Alloy 800H and Alloy 617 across a range of temperatures up to their maximum temperature limits in Section III, Division 5. The studies aim to characterize the materials' deformation behavior under both strain-controlled mechanical cyclic loading and thermal cycling conditions. This report summarizes ORNL's FY 2024 experimental findings on Alloy 800H and Alloy 617, focusing on pure fatigue tests, cyclic stress-strain curves, thermomechanical fatigue experiments, and verification of the high temperature cyclic damage summation design rules.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Convection-Permitting Ensembles of an Isolated Mountain Thunderstorm during RELAMPAGO/CACTI

Abstract The north–south-oriented Sierras de Córdoba (SDC) ridge in central Argentina is noted for initiating thunderstorms that may grow into intense mesoscale convective systems (MCSs). It also initiates more isolated, shorter-lived cells under weaker synoptic forcing. These cells are less impactful than MCSs but may be difficult to predict in convective-scale numerical weather prediction (NWP) due to their strong sensitivities to subgrid and partially resolved processes. To study the mechanisms and predictability of such cells, convection-permitting ensemble simulations were conducted of an isolated, diurnally forced SDC thunderstorm during Cloud, Aerosol, and Complex Terrain Interactions (CACTI)/Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO). The rich observational data facilitated detailed ensemble verification, where dry biases in the surface energy balance and soil moisture were identified. These biases promoted rapid removal of convective inhibition and an early onset of precipitating cells over the SDC that were shallower and weaker than the observed cell. Correction, and then overcorrection, of the soil moisture bias in two successive ensembles was required to rectify the surface energy balance and improve the representation of the SDC cell. Nevertheless, substantial ensemble variability in convective precipitation was found, with some members producing more widespread convection than observed and others producing no deep convection at all. This variability was largely explained by a combination of thermodynamic and dynamic mechanisms, dominated by a positive sensitivity of convective precipitation to preconvective moist instability over the ridge. Secondary sensitivities were found to low-level upward mass flux and midlevel cross-barrier winds, the latter of which caused gravity waves with elevated downdrafts that tended to suppress incipient clouds.

Lopez, Andres [Department of Atmospheric and Ocean↗
DOE OSTI2024

Study of the heat pipe vapor flow using the MOOSE application Sockeye and the CFD code Nek5000

Heat pipes are efficient heat transfer devices used in various applications, including nuclear microreactors. Heat pipe-cooled microreactors offer advantages in size and cost, which can significantly accelerate their deployment and adoption. Developing accurate models of heat pipes is crucial for a heat pipe-cooled microreactor design and operation. In this work a verification and validation of the heat pipe application Sockeye is presented. Results are compared against RANS simulations, performed with the code Nek5000, and the SPHERE experiment, conducted at INL.

42 ENGINEERING↗
DOE OSTI2021

Data Analysis of Energy Code Compliance in Commercial Buildings

What percent of newly constructed commercial buildings comply with the energy code? How much energy and cost could be saved if the compliance increased? Which code requirements have both low compliance rates and high savings potential? These are the questions U.S. Department of Energy (DOE) is trying to answer through its Commercial Energy Code Field Study. Previous commercial studies have been very limited and did not result in a widely accepted and tested methodology. DOE’s goal is to create a standardized methodology that can produce actionable results at a reasonable study cost, that can be used by state and local governments and utilities and provides valuable information to policy makers. The field study team implemented the pilot methodology, compiling a data set of 230 office and retail buildings in two climate zones. The approach is based on identifying lost savings on a total energy cost basis rather than simply counting the quantity of measures that do not meet code. This report is focused on the analysis of the collected data. The primary goal was to analyze the data collected during the field study and determine the actual energy cost impact of each measure in a non-compliance situation. The energy impact results allowed for ranking the measures to identify which have the highest potential for lost savings. These results combined with the time required to verify each measure will allow future compliance verification to focus on measures that had a large impact on energy use over the life of the building and those that have the greatest savings recovery potential per verification hour.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Data Analysis of Energy Code Compliance in Commercial Buildings (Rev. 1)

What percent of newly constructed commercial buildings comply with the energy code? How much energy and cost could be saved if the compliance increased? Which code requirements have both low compliance rates and high savings potential? These are the questions U.S. Department of Energy (DOE) is trying to answer through its Commercial Energy Code Field Study. Previous commercial studies have been very limited and did not result in a widely accepted and tested methodology. DOE’s goal is to create a standardized methodology that can produce actionable results at a reasonable study cost, that can be used by state and local governments and utilities and provides valuable information to policy makers. The field study team implemented the pilot methodology, compiling a data set of 230 office and retail buildings in two climate zones. The approach is based on identifying lost savings on a total energy cost basis rather than simply counting the quantity of measures that do not meet code. This report is focused on the analysis of the collected data. The primary goal was to analyze the data collected during the field study and determine the actual energy cost impact of each measure in a non-compliance situation. The energy impact results allowed for ranking the measures to identify which have the highest potential for lost savings. These results combined with the time required to verify each measure will allow future compliance verification to focus on measures that had a large impact on energy use over the life of the building and those that have the greatest savings recovery potential per verification hour.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Evaluation of a Reduced-Order Model for IBR Fault Response Representation via OEM Blackbox Models

This paper presents a fully implemented inverter reduced-order-model (ROM) in an EMT simulation (PSCAD) library component for direct user utilization in protection studies. The developed inverter ROM has the following features: Equivalent to a full inverter-based resource (IBR) inverter model with positive- and negative-sequence current formulation and representation. A Python script is developed to fully automate this process, including training data generation, ROM parameter training, updating parameters, and model verification and validation. The ROM is validated using both IEEE 2800-compliant and non-compliant OEM modes in a real-world system, building confidence of its usability by protection engineers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Development of a Performance Portable Non-Equilibrium Plasma Fluid Solver on Adaptive Grids

This presentation will describe the numerical techniques, programming paradigms, verification, and performance of a non-equilibrium plasma fluid solver that can effectively utilize current and upcoming central processing and graphics processing unit (CPU+GPU) architectures. Our plasma fluid model solves the conservation equations for self-consistent electrostatic Poisson, electron and heavy species transport, and electron temperature on adaptive Cartesian grids. Our solver is written using performance portable adaptive mesh management library, AMReX (Zhang et al., JOSS, 4 (37) 1370, 2019), and can be built and run on widely available vendor specific GPU architectures (NVIDIA/AMD/Intel). We utilize a non-subcycled second order semi-implicit time-stepping method where all adaptive mesh refinement (AMR) levels are advanced with the same time step. The composite multi-level multigrid solver from within AMReX is used for each of the governing equations that are cast into a Helmholtz equation form. We have also developed a python based chemical mechanism parser framework that uses a similar format as CANTERA (Goodwin et al., Zenodo, 2018) yaml files as input. Our custom parser reads the yaml file and provides C++ files with transport and production rate functions that can be executed on both host (CPU) and device (GPU). We present verification of our solver using method of manufactured solutions that indicate formal second order accuracy with central diffusion and fifth order weighted-essentially-non-oscillatory (WENO) advection scheme. We also verify our solver with published literature on low-pressure capacitive and high-pressure streamer discharges. Our initial performance studies indicate 10X speed-up using 20 NVIDIA GPUs versus 200 CPUs for an atmospheric streamer discharge problem solved on a 512 x 1024 x 512 grid.

graphics processing units↗
DOE OSTI2020

Cross talk between RNA N6‐methyladenosine methyltransferase‐like 3 and miR‐186 regulates hepatoblastoma progression through Wnt/β‐catenin signalling pathway

Abstract Objectives N6‐methyladenosine (m6A) is a ubiquitous epigenetic RNA modification that plays a pivotal role in tumour development and metastasis. In this study, we aimed to investigate the expression profiling, clinical significance, biological function and the regulation of m6A‐related genes in hepatoblastoma (HB). Materials and Methods The mRNA and protein expression levels of m6A‐related genes were analysed using Gene Expression Omnibus (GEO) and tissue microarray (TMA) cohort. Kaplan‐Meier analysis was performed to evaluate the prognostic value of m6A‐related genes in HB. Knockdown of m6A‐related genes was conducted to analyse its function on cell proliferation, migration and invasion. Furthermore, bioinformatics analysis and experimental verification were used to explore the potential molecular mechanism and signalling pathway. Results We found that most m6A‐related genes were significantly upregulated in HB tumour tissues. High levels of methyltransferase‐like 3 (METTL3, P = .013), YTHDF2 ( P = .037) and FTO ( P = .032) indicated poor clinical outcomes, and the upregulation of METTL3 was an independent prognostic factor in HB patients. Functional assays showed that knockdown of METTL3 could dramatically suppress the proliferation, migration and invasion of HB cells. In addition, METTL3 was identified to be a direct target of microRNA‐186 (miR‐186). Consistently, miR‐186 was low expressed in HB tumour tissues. Moreover, overexpression of miR‐186 significantly inhibited cell aggressive phenotype both in vitro and in vivo, while the inhibitory effect could be reversed by METTL3 overexpression. Mechanism study indicated that miR‐186/METTL3 axis contributed to the progression of HB via the Wnt/β‐catenin signalling pathway. Conclusions M6A‐related genes were frequently dysregulated in HB. miR‐186/METTL3/Wnt/β‐catenin axis might serve as novel therapeutic targets and prognostic biomarkers in HB.

Cui, Xichun↗
DOE OSTI2021

EIF3H knockdown inhibits malignant melanoma through regulating cell proliferation, apoptosis and cell cycle

Highlights: • EIF3H is highly expressed in malignant melanoma and correlated with tumor stage and risk of lymphatic metastasis. • Knockdown of EIF3H inhibits cell proliferation, cell migration and promotes cell apoptosis of melanoma in vitro. • Knockdown of EIF3H suppresses tumor growth in vivo. Malignant melanoma (MM) causes 80% of skin cancer-related deaths and becomes the most lethal type of skin cancer. The molecular mechanism of MM is still not clear. This study aimed to reveal the relationship between MM and EIF3H. Clinical specimens were collected to preliminarily explore the role of EIF3H in MM. MM cell lines with EIF3H knockdown were constructed for investigating the effects of EIF3H on cell proliferation, apoptosis, cell cycle and cell motility. Mice xenograft model was constructed for verification in vivo. We found that EIF3H was obviously upregulated in MM tissues compared with normal skin tissues, which was correlated with tumor stage and risk of lymphatic metastasis. The in vitro results indicated that silencing EIF3H in MM cells could significantly suppress cell proliferation, promote cell apoptosis and induce cell cycle arrest. Moreover, EIF3H knockdown significantly restrained cell motility through regulating EMT-related proteins. The effects of EIF3H knockdown were also verified in mice xenograft model, which were represented by slower growth rate, smaller volume and lighter weight of tumors. Therefore, EIF3H was identified as a critical factor in the development and progression of MM which may be used as a novel therapeutic target in the treatment of MM.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

MOOSE Reactor Module Meshing Enhancements to Support Reactor Physics Analysis

The U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program develops an integrated suite of advanced reactor physics tools built upon the Multiphysics Object-Oriented Simulation Environment (MOOSE) framework. Each code generally requires an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The meshing process is often burdensome for the complex geometries present in reactors due to lack of easy-to-use, open-source meshing tools. To address the bottleneck associated with meshing complex geometries found in nuclear reactors, NEAMS initiated the development of the MOOSE Reactor Module starting in FY21. The Reactor Module builds off the existing MOOSE Mesh System to include targeted meshing capabilities such as the ability to generate hexagonal pin cells, assemblies with ducts, rotating control drums, cores, peripheral zones around a core, as well as the automatic labeling (“reporting IDs”) of pin, assembly, and planar zones to simplify post-processing of results. As a Physics Module in MOOSE, the Reactor Module is open-source, available with any MOOSE installation, directly compatible with MOOSE-based tools, and can be invoked from MOOSEbased applications to generate meshes. Functionality from the Reactor Module has been applied to several advanced reactor concepts to demonstrate user workflow improvements and accuracy. The primary objective of the Reactor Module is to improve useability of MOOSEbased tools by streamlining mesh generation and output inspection processes. During FY22, the functionality of the Reactor Module (and accompanying Mesh System) has been expanded based on user needs. First, the Reactor Geometry Mesh Builder capability developed primarily in FY21 has been refactored and merged to the public MOOSE repository. This capability wraps underlying Reactor Module mesh generators into a “Pin – Assembly – Core” workflow appropriate for conventional Cartesian and hexagonal geometries, and notably assigns material IDs during mesh generation stage and generates only the minimal number of blocks needed in order to reduce computational burden. Biasing and boundary layer options have been added to the base mesh generators as required by thermal hydraulics solvers. The reporting ID functionality has been expanded to differentiate ring-wise and azimuthal sectors within a pin for use with depletion algorithms, and VectorPostProcessor and Reporter objects are now available to integrate solution variables across zones based on ID combinations. Functionality to trim hexagonal meshes along the center or periphery has been developed so users may leverage symmetry and reflective boundary conditions to reduce the mesh size. A flexible and powerful tool to fill the space between two sidesets has been introduced to the framework and can be used for transition layers such as stitching two assemblies together with different numbers of pins, or for complex geometries which do not follow conventional Cartesian/hexagonal patterns. Finally, additional verification problems were performed with NEAMS physics tools in complement with existing NEAMS work.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗