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At least 37 records · Page 2

Computational Thermal Hydraulics of a High-Performance Low-Enriched-Uranium Annular Target for HFIR Irradiation

Molybdenum-99 has historically been generated via isolation from fissioned highly enriched uranium (HEU) targets. Here, this isotope is in high demand due to its daily use across the world in radiopharmaceutical medical procedures. The primary objective of this work was to design and analyze an experimental target assembly containing one low-enriched-uranium (LEU) annular target for irradiation at the High Flux Isotope Reactor (HFIR). Efforts included incorporating spatially dependent energy sources from neutron and gamma interactions, quantifying thermal contact conductance at material interfaces, performing grid-independent studies, comparing turbulence models, and simulating various steady-state and transient scenarios relevant for irradiation qualification and eventual insertion. These models provide velocity, pressure, and temperature distributions in both space and time. Such results enable the selection of an appropriate irradiation location, fission rate density, and flow-limiting orifice size and demonstrate compliance with HFIR safety requirements such that insertion into the reactor can be approved. This analysis shows that across all scenarios, wetted surface temperatures remain below the coolant saturation temperature with no net vapor formation in the coolant. In every scenario, all components stay below 30% of the aluminum 6061 melting temperature. Computational fluid dynamics and system-level models predict peak target temperatures that agree within 4%, though the predicted axial location of the peak differs by about 10% of the heated length due to differences in flow development length. These results de-risk the irradiation of LEU (annular targets) and strengthen a domestic, HEU-independent 99 Mo supply by providing important fuel performance data to form the foundation for a robust licensing basis.

Molybdenum-99↗

A Co-Simulation Framework for Steady-State Analyses of Multiple Droop-based MTdc Grids in Continental-Scale Systems

The growing scale and complexity of planning continental hybrid ac and multi-terminal dc (MTdc) systems require scalable steady-state modeling and analysis approaches not currently available in commercial tools. This paper presents a comprehensive multi-fidelity model-conversion framework that enables the efficient transition of MTdc grid models from production cost modeling (PCM) and approximated ac power flow to detailed ac–MTdc power flow for large-scale planning studies. The core of this framework is a scalable co-simulation approach that, for the first time, enables power flow analysis in continental-scale ac–MTdc systems. It seamlessly couples commercial ac solvers with a detailed MTdc grid model that incorporates droop-based control and current-limiting strategies of multiple meshed MTdc grids. Leveraging this capability, an evaluation framework to systematically assess and compare different MTdc power redispatch strategies under ac and dc contingencies is introduced. The proposed framework and algorithm are evaluated using a combined Western and Eastern Interconnection system with 11 MTdc grids of various sizes, showing a coherent transition from PCM to detailed ac–MTdc power flow and improved system performance in voltage regulation and line overload mitigation following typical contingencies.

Nguyen, Quan H.↗

Large Eddy Simulation of Low-Reynolds-Number Turbulent Flow of Low-Prandtl-Number Fluid in a Tight Lattice Bundle for Assessment of Reynolds-Averaged Navier-Stokes Turbulence Model

The MARVEL (Microreactor Applications Research Validation and Evaluation) microreactor utilizes natural circulation as core cooling mechanism and liquid metal as a primary coolant. Moreover, the reactor core has a pitch-to-diameter ratio of 1.056, which is considered a tight lattice configuration. Numerous studies have widely reported that Reynolds-Averaged Navier-Stokes (RANS) turbulence models inaccurately predict heat transfer in liquid metals and fail to capture flow pulsations that can occur within tight lattices, leading to further inaccuracies in simulation results. Therefore, evaluating the accuracy of RANS turbulence models in the thermal-hydraulic analysis of the MARVEL microreactor core is crucial for assessing reactor safety. In this study, a Large Eddy Simulation (LES) of the MARVEL microreactor core subchannel was conducted and compared with a RANS simulation to evaluate the accuracies and conservatism of the RANS model. The flow pulsation in a tight lattice predicted by LES enhanced the heat transfer, whereas the RANS model underpredicted it. Consequently, the RANS model predicted the peak cladding temperature higher than the LES model, but the discrepancy between the two approaches was not significant due to the good thermal characteristics of the liquid metal. It can be concluded that the steady-state RANS model is effective for the thermal analysis of liquid-metal-cooled MARVEL microreactor core and can provide conservative predictions from a safety analysis perspective.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Transient Pulse-Response Time-of-Flight Mass Spectrometry for Complex, Deactivating Heterogeneous Catalytic Systems: Application to Ethane Dehydroaromatization

The study of complex, multistep bond-forming and -breaking reactions in heterogeneous catalytic systems often encounters challenges associated with the involvement of large numbers of intermediates among branching pathways. Kinetic information obtained from traditional steady-state measurements can be complemented with that from time-resolved methods to uncover details of the underlying chemistry. Herein, we describe an approach for tracking the complete time-resolved chemical composition (ca. 4–200 u) of a reactor effluent in response to a reactant pulse. We use a six-port rotary valve with a metered sampling loop to pulse reactants at ambient pressure into a flow reactor packed with a catalyst bed within the isothermal region of a heated furnace. The temporal evolution of effluent species is tracked using time-resolved molecular-beam time-of-flight mass spectrometry. We highlight the possibilities that this method has to offer by studying the complex bifunctional mechanism of ethane dehydroaromatization over an HZSM-5-supported platinum catalyst. We demonstrate that energy-tunable ionization sources, which facilitate isomer resolution, enable the measurement of the full mass spectral time-dependent system response. This includes the evolution of major products and mechanistically relevant reactive intermediates such as 1,3-butadiene and cyclopentadiene; these species have not previously been observed from this reaction. In additional studies, we also assess the role of platinum in the catalyst by examining temporal responses to ethane and ethylene feeds. Results show that two temporally distinct formation pathways exist for methane and benzene, and that their importance depends on both catalyst composition and reactant identity. Additionally, characteristics of catalyst deactivation are uniquely observable in the time-resolved mass spectral response, including the selective deactivation of a benzene formation pathway. The combination of time-of-flight mass spectrometry with tunable ionization enables the simultaneous observation of all effluents in a complex mixture of intermediates with isomer/isobar differentiation capabilities that can be applied to any complex reaction system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-temperature seals for supercritical carbon-dioxide (sCO 2 ) turbines (Final Report)

This is the final report for project DE-FE0031924 titled “High-temperature seals for supercritical carbon-dioxide (sCO 2 ) turbines.” The report provides a summary of the entire project efforts from October 2020 through December 2024 including the high-temperature commercial dry gas seal (DGS) tests and thermal modeling of Task 2, as well as the high-temperature, large-diameter seal design and high-temperature tests of large-diameter seals in Task 3. A key outcome of Task 2 was the testing completion of specially instrumented commercial DGS in the GE-SwRI Apollo sCO 2 compressor (27,000 rpm). Test data from the DGS showed elevated temperatures upwards of 350 o F, which are close to the higher operating temperature limit of the DGS. The temperature measurements provide insight into the expected thermal loads on DGS operating in high-speed sCO 2 compressor and provided test data for validation of an in-house thermal model of the compressor/seal. Under Task 2.0, this report also presents the development of a steady-state conjugate heat-transfer model of the DGS operating in the sCO 2 compressor – a first of its kind model for modeling heat transfer of sCO 2 in an actual operating compressor. The findings of the thermal model show a reasonable match between temperature predictions of the model and the measured temperature data, also pointing out the validity of the approach and assumptions made in modeling the flows, heat transfer coefficients and windage modeling in the rig. Under Task 3.0, this report presents the preliminary design of a large-diameter hybrid face seal (14 inch and 26-inch diameter) for field testing in a land-based GE turbine. The preliminary seal design effort presented in this report under project DE-FE0031924 builds on the development and successful laboratory testing for such large diameter hybrid face seal under the prior DE-FE0024007 project. Key aspects of seal fluid analyses with CFD, mechanical design considerations and assembly considerations in a land-based turbine are presented. Finally, under Task 3.0, this report also presents the continued high-temperature testing of the 14-inch diameter hybrid face seal developed previously under the DE-FE0024007 program. Specifically, test data demonstrating successful non-contact seal operation and seal effective leakage of 0.001-inch with seal inlet temperatures above 700 o F are presented in this report. Successful hybrid seal operation in a laboratory environment for a large diameter (14-inch) seal at temperatures above 700 o F is a major technological milestone for this technology.

01 COAL, LIGNITE, AND PEAT↗

Casimir interactions between two parallel graphene sheets carrying steady-state drift currents

Here, we investigate the fluctuation-induced Casimir interactions between two parallel graphene sheets carrying steady-state drift currents. The graphene properties are modeled based on the shifted Fermi disk model to capture the nonequilibrium optical response of the system. We find that the drift current introduces a repulsive correction to the perpendicular to the layers Casimir interaction, thereby reducing the overall attractive force. Although the correction is repulsive, it does not overcome the underlying attraction between the layers. It also generates a lateral force that opposes the carrier flow direction. Both contributions are studied in terms of distance and drift velocity functionalities showing pathways for Casimir force control.

Ke, Modi [University of South Florida, Tampa, FL (↗

Studies of Flame Structure in Microgravity

The present research endeavor is concerned with gaining fundamental understanding of the configuration, structure, and dynamics of laminar premixed and diffusion flames under conditions of negligible effects of gravity. Of particular interest is the potential to establish and hence study the properties of spherically- and cylindrically-symmetric flames and their response to external forces not related to gravity. For example, in an earlier experimental study of the burner-stabilized cylindrical premixed flames, the possibility of flame stabilization through flow divergence was established, while the resulting one-dimensional, adiabatic, stretchless flame also allowed an accurate means of determining the laminar flame speeds of combustible mixtures. We have recently extended our studies of the flame structure in microgravity along the following directions: (1) Analysis of the dynamics of spherical premixed flames; (2) Analysis of the spreading of cylindrical diffusion flames; (3) Experimental observation of an interesting dual luminous zone structure of a steady-state, microbuoyancy, spherical diffusion flame of air burning in a hydrogen/methane mixture environment, and its subsequent quantification through computational simulation with detailed chemistry and transport; (4) Experimental quantification of the unsteady growth of a spherical diffusion flame; and (5) Computational simulation of stretched, diffusionally-imbalanced premixed flames near and beyond the conventional limits of flammability, and the substantiation of the concept of extended limits of flammability. Motivation and results of these investigations are individually discussed.

Law, C. K.↗

Representation and Impact of Water Head on Power System Planning and Operation

Representing water head information in power system model files, can provide a more realistic model of the system and thereby inform operation and planning personnel in the decision-making process. This article describes a procedure for modifying the power system model files (steady-state and dynamic) to represent water head information. Additionally, the impact of representing the water head on power system reliability studies including contingency analysis, cascading failure analysis and dynamic frequency response analysis has been investigated, using the modified power system models. This paper considers the detailed Western Electricity Coordination Council model during summer and winter conditions as the test system for the impact analysis. Results show that under reduced water head: 1) the number of critical voltage and branch flow violations increases; 2) chances of cascading failure and island formation increases; and 3) frequency nadir decreases as compared to those of the base cases where the water head information is not represented.

13 - HYDRO ENERGY↗

Design improvements for a recirculating reactor: Enhanced temperature measurement and sample-isolated reactivity in steady-state kinetic studies

Building upon a previous recirculating reactor design [S.A. Tenney, K. Xie, J.R. Monnier, A. Rodriguez, R.P. Galhenage, S. Audrey, D.A. Chen, Rev. Sci. Instrum. 84, 104101 (2013)], we present significant improvements that address key limitations in steady-state kinetic measurements for heterogeneous catalysis. The enhanced reactor design features direct sample heating with a focused IR lamp and temperature measurement in direct contact with the sample, enabling more accurate temperature control and improved kinetic analysis. A critical advancement is the isolation of sample reactivity from reactor wall contributions, ensuring that only the sample contributes to measured reaction rates. This was a limitation in earlier designs where the entire reactor contributed to the observed reactivity. The system incorporates a bypass flow cell for direct comparison with powder catalysts under identical conditions using a standard plug-flow reactor configuration. We demonstrate these capabilities through CO oxidation experiments on Pt(111) single crystals and graphene-passivated Pt(111), highlighting the system's ability to differentiate catalytic activity in model systems and directly compare them with high surface area powder catalysts. This reactor is particularly suited for thin films and low surface area catalysts that are not effectively evaluated in traditional flow reactors, especially for samples with low numbers of active sites or slow reaction rates.

36 MATERIALS SCIENCE↗

Preliminary Testing of a Continuous Cryopump for Primary Fusion Device Pumping and Direct Internal Recycling

Here, the concept of directly recirculating fusion machine exhaust gas, bypassing the tritium plant, to make fuel pellets was proposed in the 1990s and later termed direct internal recycling (DIR). In the DIR concept, the residual fusion fuel in the machine exhaust stream is separated from impurities locally and diverted directly to the fueling systems, bypassing isotopic separation and other processing equipment, and therefore significantly reducing the required size of the fuel processing plant, reducing plant inventory, and thus increasing the economic viability of fusion as an energy source. One concept for DIR consists of a series of cryogenic pumps to separate the impurities from the machine exhaust gas using different triple point temperatures and saturation curves of exhaust constituents. In this concept, the plasma exhaust is initially passed through an impurity trap operating at ~25–30 K to desublimate impurities such as hydrocarbons, argon, oxygen, and nitrogen. The resulting process stream will consist of DT fuel and helium. The process stream is then pumped by a continuous cryopump known as a “snail pump.” This pump is a steady-state continuous cryopump that desublimates all remaining exhaust gas constituents while allowing helium, a byproduct of the fusion reaction, to pass through. The helium is pumped to the tritium plant for processing while the desublimated material is continuously scraped off, heated up, and transported to the fueling system. This article will present the cryogenic DIR concept and outline the design and operation of the snail pump, along with results from preliminary testing. Tests to assess pumping and separation efficiency found that at D2 flows below 50.7 Pa ⋅ m3/s with 1% helium, the pump is capable of pumping and separating the gas with a resulting DIR fraction of >99%, with no helium entrained in the primary fuel exhaust stream. The main limitation is due to the thermal performance of the cryogenic circuits of the pump, which will be addressed in future testing.

Gebhart III, Trey E. [Oak Ridge National Laborator↗

SAM Finite Volume Method Development Status Update: GCR Application, Restart, and MultiApp

The System Analysis Module (SAM) is being developed as a modern system analysis code for advanced non-light-water-reactor safety analysis under the U.S. DOE NEAMS program. Previous feasibility studies have demonstrated that a staggered-grid finite volume method (SG-FVM), implemented under the MOOSE framework, can deliver more than an order of magnitude speedup over the existing continuous Galerkin finite element method (CG-FEM) solver for liquid-cooled, incompressible but thermally expandable flow systems. This work extends the previous effort to compressible, gas-cooled reactor applications, where pressure couples directly into the mass equation adding additional nonlinearity into the equation system. New code capabilities are implemented for pebble bed high-temperature gas-cooled reactor (PB-HTGR) analysis, including a pebble bed CoreChannel component, built-in pebble bed effective thermal conductivity model and channel-to-channel crossflow model. The capabilities are tested, benchmarked, and demonstrated for problems with increased level of model and physical complexities, including the HTTU effective thermal conductivity test, the SANA passive cooling test, and a demonstration case using the GPBR200 reactor design covering steady-state operation, DLOFC and PLOFC transients. Across all cases, the SG-FVM solver demonstrated strong robustness and efficiency, and the solutions agree well with reference results and data. The finding of this work proves that SG-FVM is a viable and efficient solver pathway for compressible, gas-cooled reactor system analysis in SAM. In addition, work has been done to successfully support SAM-FVM recover/restart code feature that is essential to reactor safety analysis applications, and MultiApp code feature that is essential to multi-scale and multi-physics simulations. In summary, this work continued from previous feasibility studies, and further demonstrated that the SG-FVM will serve as a strong foundation for SAM’s advanced solver algorithm for future deployment.

Zou, Ling↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production by conducting a statistical analysis of historical wind data over a five-year period (2020-2025) from a single 1.5MW turbine manufactured by General Electric (GE) located at NLR’s Flatirons Campus, to generate an experimental test profile that was deployed on a 1.25-MW proton exchange membrane type MC250 electrolyzer system manufactured by Nel Hydrogen . [1] While the electrolyzer balance-of-plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. The historical wind data provided several metrics, however, the analysis particularly focused on the measured power output by the wind turbine. The power output time series of data for each day was categorized by total energy generation and standard deviation, and the day that represented the highest combination of these two metrics was chosen – December 25th, 2022. This process was then repeated for a moving four-hour window within this day to identify the most statistically variable period. Finally, this four-hour period was scaled by 65% to match the 1.25 MW electrolyzer. The electrolysis system controls hydrogen production by varying DC current applied to the stack, from a maximum of 3000 A to a minimum safe operation of 300 A, or 10%. Because the current – voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical wind profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1 Hz frequency. For more details on the statistical analysis process, see the presentation labeled “ Public Reference Data for Megawatt-Scale Hydrogen Electrolysis” provided with each data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}_{scaling factor}-{electrolyzer ramp rate in amperes/second} For instance, “wind-GE1.5MW_0.65-400.zip” represents the hour-long experiment using historical data from the wind-GE1.5MW turbine, scaled to 65%, with the electrolyzer power supply set to a maximum ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and wind power input. A PDF file detailing the historical wind data statistical analysis used to generate the wind profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_historical_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis [1] nelhydrogen.com/product/mc-series-electrolyser .

08 HYDROGEN↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Solar PV

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) research platform. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence data centers and other variable loads. This dataset entry describes the behavior of a 1.25-MW proton exchange membrane MC250 electrolyzer system, manufactured by Nel Hydrogen , [1] when fed historical data generated by the 430-kW, fixed-axis solar photovoltaic (PV) array located at NLR’s Flatirons Campus. (While the electrolyzer balance of plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack.) Solar PV power output data for the 2020 calendar year were categorized on a daily basis by total energy generation and standard deviation. Each day was then ranked by these metrics, and the 25th, 50th, and 100th percentiles were selected. The 75th percentile day did not exhibit sufficient variability to make for a valuable experiment. A similar process was used for the related historical wind dataset . [2] The historical days in 2020 that represented these percentiles are Dec. 19, March 29, and May 4, respectively. The entire solar day’s power profile was then fed through the MC250 electrolyzer. Due to its length, the 100th percentile day experiment was split into two parts, and the final 3 hours of the solar day were not captured. These final 3 hours contained no spikes or dips of interest and simply represented a slow decay of input solar power. Also, a single timestamp (13:13:47 on Jan. 14, 2026) was lost in the hydrogen system supervisory control and data acquisition. Finally, during the 25th percentile experiment (solar day Dec. 19, 2020) data recording was lost from 11:00:13 to 11:14:45. The roughly 15 minutes of the solar profile were rerun at the end of the experiment and spliced into this time slot during post-processing. The electrolysis system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operation of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical solar profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz frequency. For more details on the statistical analysis process, see the slide deck “Public Reference Data for Megawatt-Scale Hydrogen Electrolysis: NLR Historical Solar PV Analysis and Profile Generation” accessible with this data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single solar PV electrolysis experiment and is formatted as: {technology}_{percentile}_{scaling factor} For instance, “solarPV-430kW_25_2x.zip” reports the experiment using the 25th percentile solar data from the historical 2020 solar PV dataset, scaled to 200%. Scaling factors were applied to the generated solar PV power output files to more closely match the 1.25-MW capacity of the electrolyzer. Each .zip folder contains the following files: A .csv file containing raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and solar power input. A PDF file detailing the historical solar data statistical analysis used to generate the solar profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all experiments combined into one dataset labeled "combined_solarPV_experiments.csv". [1] nelhydrogen.com/product/mc-series-electrolyser . [2] data.nlr.gov/submissions/316 .

08 HYDROGEN↗

Computationally inexpensive part-scale thermal history of additive friction-stir deposition

This study presents an analytical model for steady-state power generation and tool heat loss in additive friction-stir deposition (AFSD), developed to enable part-scale thermal simulation while remaining computationally inexpensive. The model predicts total generated power, yielding 3.7–4.7 kW across deposition temperature setpoints of 400–460 °C for the deposition of AA6061 with a Be-Cu tool. This corresponds to 90–95% of the reported spindle power. Tool heat loss is experimentally determined by calibrating a steady-state energy balance between the generated power, the substrate-deposition thermal gradient, and a temperature dependent tool heat loss term: q tool (T) = a + b (T - 400°C) with a = 2.7 x 10 6 Wm -2 and b = 9.5 x 10 3 Wm -2 K -1 . The calibration indicates that about 69% of the generated heat is conducted into the tool for this configuration, which is much higher than previously reported. The calibrated heat-source is implemented in finite element software (Adamantine) to simulate the transient thermal history of a 100 cm 3 representative build in 8 min on a standard desktop (at 0.635 mm build-height resolution). For the first three layers, the substrate temperatures between simulation and experiment are within 10% mean absolute percentage error. Sensitivity analysis indicates that uncertainties in average deposition temperature and deformation localization (stir-zone geometry, depth, and spatial dependance of strain-rate and flow stress) dominate model variance, motivating additional experimental verification.

Additive Friction-Stir Deposition↗

Transient uncertainty quantification and Global Sensitivity Analysis of the open-source Molten Chloride Reactor Experiment (MCRE) using GP-PCA surrogate models

Uncertainties in the thermophysical properties of molten salts impact both the steady-state and transient behavior of Molten Salt Reactors (MSRs). In this work, we aim to quantify the influence of such uncertainties on the transient operation of the Molten Chloride Reactor Experiment (MCRE), utilizing the open-source specifications provided for this reactor. Seven representative transient scenarios are considered. For each scenario, we evaluate the impact of thermophysical property uncertainties on four key multiphysics model output variables of interest (VoIs): maximum power density, maximum fuel temperature, maximum reflector temperature, and average fuel velocity magnitude. In addition, we perform a Global Sensitivity Analysis (GSA) by computing Sobol’ indices for the uncertain input parameters to determine their contribution to the variability of each VoI. Conducting GSA is computationally intensive due to the large number of required evaluations of the high-fidelity multiphysics model. To mitigate this cost, we develop a surrogate modeling framework that combines Gaussian Process (GP) regression with Principal Component Analysis (PCA), enabling efficient sample generation for the GSA. Our results show that for energy-related VoIs, thermal conductivity is the dominant contributor to uncertainty. In contrast, for flow-related VoIs, density and dynamic viscosity are the primary sources of uncertainty. The specific heat of the fuel salt was found to play a secondary role in the transient analyses.

42 - ENGINEERING↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - Simulated Marine Hydrokinetic Tidal Turbine

The U.S. Department of Energy and National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis, hydrogen compression and storage, and variable hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset is part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with other energy technologies. This dataset contains inputs and outputs from simulations of a floating marine hydrokinetic turbine over approximately half a tidal cycle (~6.6 hours). Inflow conditions were derived from field measurements in Alaska’s Cook Inlet and represent a tidal environment in which the current speed ramps from near 0 m/s to a peak of 3 m/s and back. The original acoustic doppler current profiler dataset is publicly available on the Marine and Hydrokinetic Data Repository. In a full tidal cycle, the flow reverses and the rotor would reorient; this reversal was not modeled. In the Cook Inlet campaign , turbulence intensity was similar in both directions. Two inflow cases are included. In the first case, labeled “raw” in the files, the measured current time series was used directly in the InflowWind module of OpenFAST. Speed and direction were applied as a function of time and elevation, uniformly in the horizontal direction. With full spatial coherence, this approach captures high turbulent variability and results in pronounced power fluctuations, so it is considered a conservative, near-worst-case representation of loading. In the second case, labeled “average” in the files, a 30-minute moving average was applied to extract the slowly varying mean speed. The residual fluctuations about this mean were used to generate spatially varying, full-field turbulence inputs with TurbSim, giving a more physically realistic representation of the inflow across the rotor disk. Two random realizations were used to produce distinct inflow conditions for two OpenFAST simulations representing a two-turbine array. The same turbulence intensity is applied across the full time series, producing larger fluctuations at the start and end, where the mean speed is low. The second case is the more appropriate framework for performance and power assessment but overpredicts turbulence at lower flow speeds and underpredicts it at higher speeds. As the floating platform moves and the rotor changes its x-position, Taylor’s frozen turbulence hypothesis used by InflowWind assumes a constant rather than a time-varying mean velocity, introducing some inaccuracy in the velocity plane sampling. The turbine modeled is the 500-kW Reference Model 1, a horizontal-axis two-bladed hydrokinetic turbine on a four-column floating semisubmersible substructure . Simulations were performed using OpenFAST v4.1 with the Reference Open Source Controller (ROSCO) v2.10. All input files required to reproduce the simulations are included. The electrolyzer is a 1.25-MW proton exchange membrane type MC250 system manufactured by Nel . This unit supports up to 2.5 MW, but NLR has only a single 1.25-MW stack. The datasets report hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. The system controls hydrogen production by varying direct current applied to the stack, from a maximum of 3,000 A to a minimum safe operating current of 300 A, or 10%. Because the current–voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The simulated tidal turbine time series data was translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1-Hz. Each zip file represents a single tidal electrolysis experiment and is named: {technology}_{inflow method}_{number of 500 kW tidal turbines connected} For instance, “tidal-500kW-RM1_average_2.zip” is a 6-hour experiment using the 500-kW tidal reference model, scaled by 2x (1-MW) to better match the electrolyzer maximum of 1.25MW, fed with the 30-minute moving average current case. Each zip folder contains the following files: A .csv file of raw data. An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production in kilograms per hour, electrolysis power consumption, and input wave power. A .csv file combines all tidal profiles as "combined_tidal_experiments.csv." A separate experiment, “characterization_200.zip,” shows the MC250 electrolyzer steady-state response with 30-minute load steps over 5 hours and is accessible with this entry.

08 HYDROGEN↗

Non-dimensional performance and safety parameters for heat pipes

The use of heat pipes in safety-critical systems such as nuclear microreactors dictates the development of generalized, practical, scalable performance and safety parameters. Traditional dimensional metrics, while informative, lack the universality required for comparative analysis across varying designs and operating regimes. Here, this work introduces a comprehensive set of non-dimensional parameters to characterize heat pipe performance and safety, including capillary performance, effective thermal conductivity, response time, exergetic efficiency, allowable temperature gradients, allowable rate of temperature change, priming coefficients, and factor of safety. A reference heat pipe design representative of microreactor applications was analyzed via the developed parameters using both traditional analytical models and Sockeye simulations under transient and steady-state conditions. Sodium, potassium, and water were evaluated as working fluids to demonstrate the applicability of the framework across a broad temperature range. The proposed non-dimensional parameters effectively captured key thermal-hydraulic behaviors and safety concerns, as was demonstrated via Sockeye simulations. This framework supports the development of design optimization strategies, operational protocols, and safety assurance practices for advanced reactor systems and other high-reliability applications.

42 - ENGINEERING↗

High-Order Methods in NASA’s Next Generation of Computational Fluid Dynamics Tools

The missions of the National Aeronautics and Space Administration (NASA) routinely produce unique requirements and challenges for development and application of Computational Fluid Dynamics (CFD) methods. NASA presently embodies four distinct Mission Directorates: Aeronautics Research, Exploration Systems, Science, and Space Operations. These missions generate requirements for systems that operate in a wide variety of environments. They range from the high-speed flight of aerodynamically optimized vehicles operating in the earth’s atmosphere to spacecraft designed for missions that don’t favor aerodynamic optimization, some operating in the atmosphere of planets and planetary moons such as Mars and Venus or Saturn’s moon Titan. Systems supporting these vehicles, such as rocket and jet propulsion, reaction control systems, fluid and thermal transfer systems, etc. can also generate their own unique set of flow phenomena that challenge today’s CFD methodology. Through the NASA Engineering and Safety Center (NESC), NASA annually conducts state-of-the-discipline assessments in fifteen distinct engineering disciplines. These assessments are performed by the NASA Technical Fellows that lead Technical Discipline Teams (TDT) of recognized experts in these fifteen areas. In the Aerosciences discipline, three topics have been identified as the top challenges for the discipline: aero-plume interaction prediction, unsteady separated flows, and aerothermodynamic prediction. These challenge areas are defined by the Agency’s high-risk projects and problems on which the NESC is requested to perform independent testing, analysis, and assessments. When viewed as a whole, these tests, analyses, and assessments provide a clear view of the recurring technical challenges facing Agency engineers and researchers and can be used to guide future research and technology development. The present state-of-the-art in the application of CFD at NASA is the use of Reynolds-Averaged Navier- Stokes (RANS) solvers, primarily executed in a steady-state mode of operation. In isolated cases, Unsteady RANS (URANS) solvers have been employed when steady RANS solutions produce poorly converging or oscillating results or in cases, such as aeroelastic analysis, which require unsteady aerodynamic simulation. For most traditional external and internal aerodynamic flows, structured overset grids or unstructured grids are employed to minimize geometric modeling and grid generation times. Grid adaptation, primarily as a series of coarse-grain intermediate processing steps is also seeing use on particularly complex flow problems and configurations. In the case of aerothermodynamic flows, engineers have been forced to continue to employ structured grid techniques as the present unstructured grid methodology has proven inadequate in the prediction of surface heating. In the area of aero-plume interaction modeling, two-gas, frozen chemistry simulation is generally the state-of-the- art, with some production solvers capable of predicting flows with only a single gas component. Prediction of flows falling into the afore-mentioned top Aerosciences technical challenges have severely stressed the present state-of-the-art in CFD prediction and for some problems, such as unsteady separated flows and aero-plume interaction cases, engineers have begun employing Large Eddy Simulation (LES) and Hybrid RANS/LES techniques. In some isolated aero-propulsion interaction cases, chemically reacting flow simulations have been applied. These methods are highly evolutionary and engineers have little experience in their application, so they cannot be heavily relied upon in today’s application environment. Therefore, this leads one to muse over which numerical technologies will be included in the CFD tools that will be employed 30 years in the future. This presentation will describe specific technical problems that have stressed NASA’s traditional CFD methods to their breaking point and will link these issues to the Agency’s top Aerosciences technical challenges. The discussion will then shift to the characteristics of future CFD solvers that will be required to attack these challenges and how these characteristics differ from the present state-of-the- art. High-order methods certainly appear to have a place in the development of future CFD tools and some of the physical characteristics of our most challenging problems suggest that high-order methods are the only way to effectively solve them. But there are some relatively severe implementation issues that face these methods, particularly in the area of general applicability and robust operation as an engineering tool. Desired characteristics of next-generation CFD solvers will be discussed and the author’s view of which emerging numerical technologies might be employed to address these attributes will also be presented

David M Schuster↗