Developmental Assessment and Verification and Validation of RELAP5-3D
Presentation on work completed on RELAP5-3D developmental assessment and verification and validation documentation processes.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
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Implementation and Validation of a Generalized Actuator Disk Parameterization for Wind Turbine Simulations Within the FastEddy Model
ABSTRACT Fast and accurate large‐eddy simulation (LES) of the atmospheric boundary layer plays a crucial role in advancing wind energy research. Long‐duration wind farm studies at turbine‐resolving scales have become increasingly important to understand the intricate interactions between large wind farms and the atmospheric boundary layer. However, the prohibitive computational cost of these turbulence‐ and turbine‐resolving simulations has precluded such modeling to be exercised on a regular basis. To that end, we implement and validate the generalized actuator disk (GAD) model in the computationally efficient, graphics processing unit (GPU)–resident, LES model FastEddy. We perform single‐turbine simulations under three atmospheric stabilities (neutral, unstable, and stable) and compare them against observations from the Scaled Wind Farm Technology (SWiFT) facility and other LES codes from the recent Wakebench turbine wake model benchmark. Our idealized LES results agree well with observed wake velocity deficit and downstream recovery across stability regimes. Turbine response in terms of rotational speed, generated power, torque, and thrust coefficient are well predicted across stability regimes and are consistent with the LES results from the benchmark. The FastEddy simulations are found to be at least two orders of magnitude more efficient than the traditional CPU‐based LES models, opening the door for realistic LES simulations of full wind plants as a viable standard practice.
17 WIND ENERGY↗
Validation of a Tapered Impact Damper for Traffic Signal Structure Vibrations Using the Method of Harmonic Balance
Significant vibration amplitudes and cycles can be produced when traffic signal structures with low inherent damping are excited near one of their natural frequencies. For the mitigation of wind-induced vibrations, dynamic vibration absorbers coupled to the structure are often used. Here, this research investigates the performance of a tapered impact damper, consisting of a hanging spring-mass oscillator inside a housing capable of reducing vibration amplitude over a broader frequency range than the conventional tuned mass damper. A nonlinear, two degree-of-freedom model is developed with coordinates representing the traffic structure and the tapered impact damper. This research focuses on the application of the harmonic balance method to approximate the periodic solutions of the nonlinear equations to compute the nonlinear dynamics of the damped traffic signal structure. After designing and manufacturing a tapered impact damper, the traffic signal structure is tested with and without the damper using free vibration snapback tests. The experimental frequency and damping backbone curves are used to validate the analytical model, and the effectiveness of the damper is discussed.
42 ENGINEERING↗
Fundamental microscopic properties as predictors of large-scale quantities of interest: Validation through grain boundary energy trends
Correlations between fundamental microscopic properties computable from first principles, which we term canonical properties, and complex large-scale quantities of interest (QoIs) provide an avenue to predictive materials discovery. Here, we propose that such correlations can be efficiently discovered through simulations utilizing approximate interatomic potentials (IPs), which serve as an ensemble of “synthetic materials”. As a proof of principle we build a regression model relating canonical properties to the symmetric tilt grain boundary (GB) energy curves in face-centered cubic crystals, characterized by the scaling factor in the universal lattice matching model of Runnels et al. (2016), which we take to be our QoI. Our analysis recovers known correlations of GB energy to other properties and discovers new ones. We also demonstrate, using available density functional theory (DFT) GB energy data, that the regression model constructed from IP data is consistent with DFT results, confirming the assumption that the IPs and DFT belong to same statistical pool and thereby validating the approach. Regression models constructed in this fashion can be used to predict large-scale QoIs based on first-principles data and provide a general method for training IPs for QoIs beyond the scope of first-principles calculations.
36 MATERIALS SCIENCE↗
Grain boundary segregation in BCC vanadium-based alloys: Quantum-accurate computed segregation spectra and targeted experimental validations
Grain boundaries are critically important to the material performance of fusion reactor materials such as vanadium, particularly mechanical properties and irradiation resistance. A key challenge to the design and control of grain boundaries in vanadium alloys is the lack of quantitative data on grain boundary segregation. In this study, we combine computational and experimental methods to address this gap. Furthermore, using a machine learning-accelerated quantum mechanics/molecular mechanics approach, we calculated the segregation spectra for 28 transition metal elements in polycrystalline vanadium, and validated these predictions experimentally for a subset of solutes that sample a range of segregation behavior, specifically zirconium, titanium, and tungsten, using analytical transmission electron microscopy. Furthermore, the agreement between experiment and theory highlights the predictive capability of our approach. Critically, this work provides a comprehensive database of quantum-accurate solute segregation enthalpies in vanadium, enabling the development of advanced alloys for fusion reactors applications.
Fusion materials↗
Validating automated resonance evaluation with synthetic data
The integrity and precision of nuclear data are crucial for a broad spectrum of applications, from national security and nuclear reactor design to medical diagnostics, where the associated uncertainties can significantly impact outcomes. A substantial portion of uncertainty in nuclear data originates from the subjective biases in the evaluation process, a crucial phase in the nuclear data production pipeline. Recent advancements indicate that automation of certain routines can mitigate these biases, thereby standardizing the evaluation process and enhancing reproducibility. This research aims to provide a methodology, framework, and metrics for the validation of automated nuclear data evaluation software leveraging high-quality synthetic data that closely mimic real experimental observables. An introduced error metric provides a scale and intuitive measure of the evaluation quality by quantifying the estimate’s accuracy and performance across the specified energy range. Synthetic data provides access to experimental observables and underlying resonance parameters, enabling comparison of different evaluations. The methodology is demonstrated using Ta-181 isotope data in the resolved resonance region. The Automated Resonance Identification Subroutine (ARIS), which operates without prior resonance information, was used to test and showcase the framework’s capabilities utilizing the proposed error metrics. The results demonstrate the effectiveness of the proposed approach and framework for optimizing software parameters and testing hypotheses through “what-if” controlled experiments, such as modifying assumptions about experimental conditions or average resonance parameters.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
High-throughput validation of phase formability and simulation accuracy of Cantor alloys
High-throughput methods enable accelerated discovery of novel materials in complex systems such as high-entropy alloys, which exhibit intricate phase stability across vast compositional spaces. Computational approaches, including Density Functional Theory (DFT) and calculation of phase diagrams (CALPHAD), facilitate screening of phase formability as a function of composition and temperature. However, the integration of computational predictions with experimental validation remains challenging in high-throughput studies. In this work, we introduce a quantitative confidence metric to assess the agreement between predictions and experimental observations, providing a quantitative measure of the confidence of machine learning models trained on either DFT or CALPHAD input in accounting for experimental evidence. The experimental dataset was generated via high-throughput in-situ synchrotron X-ray diffraction on compositionally varied FeNiMnCr alloy libraries, heated from room temperature to ~1000 °C. Agreement between the observed and predicted phases was evaluated using either temperature-independent phase classification or a model that incorporates a temperature-dependent probability of phase formation. This integrated approach demonstrates where strong overall agreement between computation and experiment exists, while also identifying key discrepancies, particularly in FCC/BCC predictions at Mn-rich regions to inform future model refinement.
36 - MATERIALS SCIENCE↗
Validating the rhenium proxy for rock organic carbon oxidation using weathering profiles
Chemical weathering over geological timescales acts as a source or sink of atmospheric carbon dioxide (CO 2 ), while influencing long-term redox cycling and atmospheric oxygen (O 2 ) at Earth's surface. There is a growing recognition that the oxidative weathering of rock organic carbon (OC petro ) can release more CO 2 than is locally drawn down by silicate weathering, and may vary due to changes in erosion and climate. The element rhenium (Re) has emerged as a proxy to track the oxidative weathering of OC petro , yet uncertainties in its application remain namely that we lack a systematic assessment of the comparative mobility of Re and OC petro during sedimentary rock weathering. Here we measure Re and OC petro loss across gradients in rock weathering at 9 global sites, spanning a range of initial OC petro values from ~0.2 % to >10 %. We use titanium to account for volume changes during weathering and assess Re and OC petro loss alongside major elements that reflect silicate (Na, Mg), carbonate (Ca, Mg) and sulfide (S) weathering. Across the dataset, Re loss is correlated with OC petro loss but not with loss of any other major element. Further, across the weathering profiles, the average molar ratio of OC petro to Re loss was 0.84 ± 0.15, with 8 out of 9 sites having a ratio >0.74. At one site (Marcellus Shale), the average ratio was lower at 0.58 ± 0.11. The excess loss of Re matches expectations that, typically, between ~0 and 20 % of the Re liberated by sedimentary rock weathering derives from silicate or sulfide phases, while some OC petro may be physically or chemically protected from weathering. Overall, our measurements provide validation for the Re proxy of OC petro oxidation and allow future work to further improve our knowledge of regional and global-scale rates of this important source of CO 2 in the geochemical carbon cycle.
58 GEOSCIENCES↗
Validating corrosion models: A comparison of governing equations
Experimental validation of Finite Element Method (FEM) models varying electrochemical governing equations, inclusion of chemical reactions, and time on the resultant damage profile for two galvanic couples is explored. Two anode materials (Magnesium AZ31 and Carbon Steel) in contact with a cathode (Stainless Steel 304 L) were modeled in/exposed to NaCl (1 and 0.1 M respectively for the anode materials) for up to one week. The physics approach, inclusion of chemical reactions, and the boundary conditions required to accurately represent the damage profile in FEM models depended on the galvanic couple materials and, ultimately, the corrosion rate. For high rates of corrosion (i.e., magnesium anode), the Nernst-Planck equation with Electroneutrality was sufficient to describe the damage, while, for low rates of corrosion (i.e., carbon steel anode), the Laplace equation was sufficient. In all cases, the most complete governing equation (Nernst-Planck-Poisson Equation) was not necessary to accurately describe the damage. Precipitation reactions in solution also played a critical role in the predicted damage profile, especially for high corrosion rate systems. Finally, for short time periods (< 6 h), the choice of governing equations does not significantly influence damage profile results. Overall, the choice of physics to reduce error in simulations relies on the boundary conditions, geometry, conductivity of the solution, electrochemical potential differences, and time of exposure. The above results are discussed with regard to accuracy and computational savings.
Carbon steel↗
A network-enabled pipeline for gene discovery and validation in non-model plant species
Identifying key regulators of important genes in non-model crop species is challenging due to limited multi-omics resources. To address this, we introduce the network-enabled gene discovery pipeline NEEDLE, a user-friendly tool that systematically generates coexpression gene network modules, measures gene connectivity, and establishes network hierarchy to pinpoint key transcriptional regulators from dynamic transcriptome datasets. After validating its accuracy with two independent datasets, we applied NEEDLE to identify transcription factors (TFs) regulating the expression of cellulose synthase-like F6 ( CSLF6 ), a crucial cell wall biosynthetic gene, in Brachypodium and sorghum. Our analyses uncover regulators of CSLF6 and also shed light on the evolutionary conservation or divergence of gene regulatory elements among grass species. These results highlight NEEDLE’s capability to provide biologically relevant TF predictions and demonstrate its value for non-model plant species with dynamic transcriptome datasets.
59 BASIC BIOLOGICAL SCIENCES↗
Experimental platforms for investigating feature-driven jets for HED mix model validation
High-energy-density (HED) systems, such as inertial confinement fusion (ICF), are susceptible to hydrodynamic instabilities that can significantly affect both experimental results and modeling predictions. Isolated features, such as fill tubes or divots in the capsule, can cause material to jet as a result of the compressive shock exciting the Richtmyer–Meshkov instability, and serve as one of the primary degradation mechanisms in ICF yield. Simulations of feature-driven jets and how they mix require extensive experimental validation, particularly for understanding to what degree the initial size and shape of a feature influence jet dynamics, and how much instability feeds through downstream layers. A better understanding of feature-driven jetting can improve our mix modeling capabilities and increase hydrodynamic simulation accuracy. This manuscript describes a series of experimental platforms fielded by Los Alamos National Laboratory as a part of the Mshock Omega 60 and ModCons Omega EP campaigns to explore feature-driven jetting. These platforms are designed to benchmark jet evolution and growth as a function of initial feature size and shape, investigate jet-layer interactions leading to instability feedthrough, and will be used to characterize jet-jet interactions resulting from clusters of features. In conclusion, preliminary results for both platforms are shown. The ModCons experiments are on-going, and a discussion of future work directions is included.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Microstructurally validated stable and predictable swelling in low-enriched uranium monolithic U-10Mo fuel mini-plates
Qualification of the low-enriched uranium (LEU) monolithic U-10 wt%Mo (U-10Mo) plate-type fuel system requires a demonstration of a stable and predictable fuel swelling behavior over the anticipated operating conditions of the United States high-performance research reactors (USHPRRs) selected for conversion to LEU operation. This will allow each reactor to develop appropriate safety margins that will retain fuel element lifetime coolability. Additionally, the fuel system must maintain performance attributes when fabricated at a commercial scale. The Mini-plate 1 experiment represents the first irradiation test of commercially fabricated miniaturized monolithic LEU U-10Mo fuel plates. Here, the swelling behavior within this experiment was compared against that of historical fuel developmental tests to reveal that the commercially fabricated fuel performed within the current recommended U-10Mo swelling model's predictions. Additionally, the fuel microstructural evolution was evaluated to link initial conditions to subtle variations detected in the swelling response, providing validation and confidence that the fuel system is robust.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Radiation-induced bowing of SiC/SiC composites under neutron flux gradients—integral experimental data for model validation
Here, the radiation-induced swelling of SiC and its composites, including strong dependencies on temperature and dose, can drive significant lateral bowing in the presence of temperature and/or dose gradients. In recent years, simulations have been performed to assess the extent of bowing in SiC composite light-water reactor (LWR) fuel cladding and boiling water reactor (BWR) channel boxes. However, to date, no integral experimental data exist to validate these models. This work provides the first experimental bowing evaluation of three ∼380 mm long SiC composite specimens irradiated under varying neutron dose gradients (∼50°C–60°C, 0.03–0.06 dpa): two tubes (∼9.8 mm diameter) and a miniature BWR channel box (∼30 mm square). The measured radiation-induced length swelling (∼0.3%–0.7% linear) was consistently 10%–21% higher than values obtained from 3D finite element structural analyses with inputs from 3D radiation transport calculations. This discrepancy could be at least partially explained by differences in dose rate (∼10 -8 dpa/s) compared to the literature data (∼10-6 dpa/s) used to establish the dose-to-swelling correlations in the model. Nevertheless, the modeled bowing magnitudes (<2 mm) obtained from finite element analyses and simple analytical equations were within the bounds of the experimental measurements for all specimens. With improved confidence in the ability to predict the structural response and measure the macroscopic deformations, future experiments will target transient bowing under neutron flux gradients at representative LWR temperatures and assess whether grid spacers can mitigate the tens of millimeters of bowing that would otherwise be expected in ∼4 m long LWR components.
bowing↗
Development and validation of a software for simulating γ-γ coincidence emission and detection probabilities
Gamma-gamma coincidence spectrometers have the potential to significantly enhance detection sensitivity for ultra-trace radionuclide measurements. The implementation of these spectrometers, however, is limited by the complexity of acquisition hardware, data processing and quantification. This work reports development of a novel radionuclide quantification software for γ-γ coincidence measurements. For any radionuclide, the software parses the Evaluated Nuclear Structure Data File (ENSDF) database, recursively simulating all possible γ-γ coincidence signatures and their respective emission and detection probabilities. Implemented using Python programming language, the software employs several strategies to boost overall computational performance. Since coincidence-based spectrometers are of notable interest in monitoring compliance for the Comprehensive Nuclear-Test-Ban Treaty (CTBT), the software’s execution was tested for 84 CTBT-relevant radionuclides. To date, the software has been experimentally validated for 15 radionuclides using the Advanced Radionuclide Gamma spectrOmeter (ARGO) at Pacific Northwest National Laboratory, USA (PNNL). Notably, the software can be operated in convergence mode, whereby coincidence detection efficiency’s convergence behavior can help avoid unreliable radionuclide activity estimates. With growing number of coincidence spectrometers worldwide, this paper aims to assist the radiation metrology community in developing similar software for their system.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Validation and demonstration of the AEFC as a practical safeguards tool for inventory verification
The Advanced Experimental Fuel Counter (AEFC) is a nondestructive assay (NDA) instrument designed to determine the residual fissile mass in irradiated fuel assemblies for safeguards verification purposes. This is done by actively interrogating an assembly with a neutron source and measuring the total (Singles) and correlated (Doubles) neutron count rates resulting from induced fissions in the irradiated nuclear fuel and relating those rates to the residual fissile mass using calibration curves. Comprehensive NDA measurements of the irradiated fuel inventory at Israeli Research Reactor 1 (IRR-1) were taken with the AEFC to validate a set of previously developed calibration curves. During the campaign, measurements were acquired of 32 standard fuel assemblies and three control assemblies in just nine days. This is a significant majority of the research reactor's irradiated fuel inventory and the largest data set gathered by the AEFC to date. Many of the fuel assemblies measured during the campaign had much shorter cooling times than those assemblies previously measured with the instrument. Calibration curves developed from previous AEFC deployments were used to determine the residual 235 U mass in the measured standard fuel assemblies. The results of the campaign demonstrated that the AEFC can be used to estimate the 235 U mass remaining in a large number of irradiated fuel assemblies with 1%–5% uncertainty in a reasonable amount of time despite operating in a high dose environment.
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
Design and performance validation of a high-temperature downhole permanent magnet generator used for an electro-pulse boring system in geothermal energy applications
Novel, direct-energy drilling technologies such as electro-pulse boring, have the potential to significantly increase the speed and depth of geothermal drilling but have not achieved widespread adoption due to several economic and technical barriers. One major challenge is that these drilling systems require electric power downhole. The current practice is to supply power to the drill string components by running electric cables down the geothermal well, but at the targeted well depths, this practice is cost-inhibitive, inefficient in terms of power consumption, and adds an additional failure point with the long cabling going through a highly corrosive, high-temperature environment. A solution to this problem is to develop high-temperature electric generator technology that can generate the required power downhole. Such a generator must also operate with high efficiency at the target downhole ambient temperature of 250 °C. In this paper, we investigate the various design considerations for this concept and subsequently design the downhole electric generator using a multi-objective design optimization approach. Through electromagnetic-, thermal- and short-circuit fault condition analysis, it is demonstrated that the optimized downhole electric generator concept presented in this paper can meet the performance requirements within this extreme drilling environment. Most remarkably, it is shown that a generator efficiency of 90% is achieved. In conclusion, to validate the results presented in this paper, a prototype generator is built and its performance is measured at 250 °C using a test bench uniquely developed for this application.
15 GEOTHERMAL ENERGY↗
Full-scale validation gaps and opportunities for low-head hydropower: a review and perspective
Hydropower is undergoing technological innovation as future development increasingly targets low-head sites (<10 m), primarily through retrofits, rehabilitation, and upgrades of existing infrastructure. This shift toward smaller systems creates a timely opportunity: unlike conventional large projects, many emerging low-head technologies may be small enough for direct full-scale validation. Full-scale testing is particularly important for environmental mitigation technologies, including fish passage, sediment continuity, and water-quality improvements, whose performance is difficult to assess reliably using reduced-scale models. Yet adoption remains constrained by the limited risk-bearing capacity of small hydropower owners, discouraging manufacturers from bringing unvalidated technologies to market. This review and perspective paper examines hydropower trends driving innovation, selected emerging technologies, conventional testing methods, and current U.S. testing capabilities as a case study. We then evaluate the gap between existing capabilities and the needs of low-head powertrains and environmental mitigation measures. Many technologies exceed existing facility flow capacities; in the U.S., the highest combined head–flow capability is limited to 5.66 m3/s, compared with median and 90th-percentile low-head turbine-unit flows of 14.3 and 60 m3/s. To mitigate this gap, we advocate repurposing large, retired, or underused hydraulic infrastructure as full-scale testing facilities to reduce first-adoption risk and support sustainable low-head hydropower deployment.
Tseng, Chien-Yung [Colorado State University, Fort↗
Revisiting the validity of eddy viscosity models for predicting airflow over water waves
In this study, we revisit the validity of eddy viscosity models for predicting wave-induced airflow disturbances over ocean surface waves. We first derive a turbulence curvilinear model for the phase-averaged Navier–Stokes equations, extending the work of Cao, Deng & Shen (2020 J. Fluid Mech. 901, A27), by incorporating turbulence stress terms previously neglected in the linearised viscous curvilinear model. To verify our formulation, we perform a priori tests by numerically solving the model using mean wind and turbulence stress profiles from large-eddy simulations (LES) of airflow over waves across various wave ages. Results show that including turbulence stress terms improves wave-induced airflow predictions compared with the previous viscous curvilinear model. We further show that using a standard mixing-length eddy viscosity yields inaccurate predictions at certain wave ages, as it fails to capture wave-induced turbulence, which fundamentally differs from mean shear-driven turbulence. The LES data show that accurate representations of wave-induced stresses require a complex-valued eddy viscosity. The maximum magnitude of this eddy viscosity scales as ∼𝑢 𝜏 𝜁 𝑖𝑛𝑛𝑒𝑟 , where 𝑢 𝜏 is the friction velocity and 𝜁 𝑖𝑛𝑛𝑒𝑟 is the inner-layer thickness, the height at which the eddy-turnover time matches the wave advection time scale. This scaling aligns with the prediction by Belcher & Hunt (1993 J. Fluid Mech. 251, 109–148). Overall, the findings demonstrate that traditional eddy viscosity models are inadequate for capturing wave-induced turbulence. More sophisticated turbulence models are essential for the accurate prediction of airflow disturbances and form drag in wind–wave interaction models.
16 TIDAL AND WAVE POWER↗