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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Energy Management Operations for the InSight Solar-Powered Mission at Mars

This paper discusses how the change in launch date has changed the energy management challenges for InSight, and how the energy management approach for surface operations has been adapted to address those challenges. It also describes how energy balance and battery life are protected over the course of the InSight landed mission, in terms of a deliberate balance between autonomous on-board fault protection and ground commanding into reduced-load configurations that still make progress versus specific, prioritized mission success criteria. It describes the project’s unique statistical analysis and usage of Mars Exploration Rovers (MER) archived data on solar energy collection to develop and validate an explicit prelaunch margin policy versus energy reductions due to environment variability over multiple-sol sequences. And finally, the paper explains how this archived energy data has influenced the modification of the Phoenix-heritage autonomous fault protection, to guard against quickly-arising inclement power-generation conditions, such as rapid onset of a local dust storm or water ice cloud front.

Lisano II, MIchael E.↗
NASA NTRSDate not supplied

Comparison of two Calibrations of NASA's MC60 Five-component Semi-span Balance

Two separate manual calibrations of NASA’s MC60 five–component semi–span balance were compared. The calibrations were performed in 1999 and 2019using CALSPAN Force Measurement System’s Large Load Rig. The Iterative Method was chosen as the load prediction algorithm and data reduction matrices were generated from both calibration data sets. Then, the applied calibration load schedules, the standard deviations of the calibration load residuals, the prime sensitivities of the five gages, and the maximum outputs at capacity of the five gages were compared. In addition, the calibration data of 1999 was used as check load data for the data reduction matrix that was obtained from the 2019 data. Overall, the agreement between the data analysis results is very good considering the facts that two different load schedules were used for the calibrations, different people performed the calibrations, different instrumentation was used to measure the loads and the outputs, the Large Load Rig was moved to a different site in between the calibrations, and no tare load corrections could be applied to the 1999 data set. Nevertheless, the calibration data of 2019 is clearly the better data set. This observation is no surprise considering that CALSPAN Force Measurement Systems made significant investments in calibration hardware and process improvements during the last 20 years.

wind tunnel balance↗
DOE OSTI2022

Ultralow platinum loading for redox-flow battery by electrospinning the electrocatalyst and the ionomer in core-shell fibers

Hydrogen Bromine Redox Flow Batteries (HBRFB) are promising candidates for large scale energy storage, having an excellent balance of system, inexpensive and abundant electrolytes, high power density and near zero kinetic limitations. However, they suffer from corrosion of the hydrogen electrode due to bromine species crossover, which requires a high loading of precious group metal (PGM) electrocatalyst. Herein, a standard catalyst has been used in an electrospun (ES) fiber mat electrode, allowing for a significant (six-fold) reduction in platinum loading from 0.3 mg Pt /cm 2 down to 0.05 mg Pt /cm 2 . At this very low loading, the electrospun electrode attained an impressive specific power of 11.5W/mg Pt , and exhibited excellent durability, with constant power output for 140 charge/discharge cycles. Further, the excellent performance of the electrospun hydrogen electrode is attribute to its unique core-shell nanofiber structure, which improves the stability of the catalyst by preventing bromide species from reaching the catalyst surface.

25 ENERGY STORAGE↗
NASA NTRS2012

Method and apparatus for calibrating multi-axis load cells in a dexterous robot

A robotic system includes a dexterous robot having robotic joints, angle sensors adapted for measuring joint angles at a corresponding one of the joints, load cells for measuring a set of strain values imparted to a corresponding one of the load cells during a predetermined pose of the robot, and a host machine. The host machine is electrically connected to the load cells and angle sensors, and receives the joint angle values and strain values during the predetermined pose. The robot presses together mating pairs of load cells to form the poses. The host machine executes an algorithm to process the joint angles and strain values, and from the set of all calibration matrices that minimize error in force balance equations, selects the set of calibration matrices that is closest in a value to a pre-specified value. A method for calibrating the load cells via the algorithm is also provided.

Wampler, II, Charles W.↗
DOE OSTI2021

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗
NASA NTRS2015

NASA's Functional Task Test: Providing Information for an Integrated Countermeasure System

Exposure to the microgravity conditions of spaceflight causes astronauts to experience alterations in multiple physiological systems. These physiological changes include sensorimotor disturbances, cardiovascular deconditioning, and loss of muscle mass and strength. Some or all of these changes might affect the ability of crewmembers to perform critical mission tasks immediately after landing on a planetary surface. The goals of the Functional Task Test (FTT) study were to determine the effects of spaceflight on functional tests that are representative of critical exploration mission tasks and to identify the key physiological factors that contribute to decrements in performance. The FTT was comprised of seven functional tests and a corresponding set of interdisciplinary physiological measures targeting the sensorimotor, cardiovascular and muscular changes associated with exposure to spaceflight. Both Shuttle and ISS crewmembers participated in this study. Additionally, we conducted a supporting study using the FTT protocol on subjects before and after 70 days of 6 head-down bed rest. The bed rest analog allowed us to investigate the impact of body unloading in isolation on both functional tasks and on the underlying physiological factors that lead to decrements in performance, and then to compare them with the results obtained in our spaceflight study. Spaceflight data were collected on three sessions before flight, on landing day (Shuttle only) and 1, 6 and 30 days after landing. Bed rest subjects were tested three times before bed rest and immediately after getting up from bed rest as well as 1, 6, and 12 days after reambulation. We have shown that for Shuttle, ISS and bed rest subjects, functional tasks requiring a greater demand for dynamic control of postural equilibrium (i.e. fall recovery, seat egress/obstacle avoidance during walking, object translation, jump down) showed the greatest decrement in performance. Functional tests with reduced requirements for postural stability (i.e. hatch opening, ladder climb, manual manipulation of objects and tool use) showed little reduction in performance. These changes in functional performance were paralleled by similar decrements in sensorimotor tests designed to specifically assess postural equilibrium and dynamic gait control. Bed rest subjects experienced similar deficits both in functional tests with balance challenges and in sensorimotor tests designed to evaluate postural and gait control as spaceflight subjects indicating that body support unloading experienced during spaceflight plays a central role in post-flight alteration of functional task performance. To determine how differences in body-support loading experienced during in-flight treadmill exercise affect postflight functional performance, the loading history for each subject during in-flight treadmill (T2) exercise was correlated with postflight measures of performance. ISS crewmembers who walked on the treadmill with higher pull-down loads had enhanced post-flight performance on tests requiring mobility. Taken together the spaceflight and bed rest data point to the importance of supplementing inflight exercise countermeasures with balance and sensorimotor adaptability training. These data also support the notion that inflight treadmill exercise performed with higher body loading provides sensorimotor benefits leading to improved performance on functional tasks that require dynamic postural stability and mobility.

Bloomberg, J. J.↗
NASA NTRS1979

Analysis of graphite/polyimide rail shear specimens subjected to mechanical and thermal loading

A two-dimensional, linear-elastic, finite element analysis of selected graphite/polyimide rail shear test specimens was made to determine the mechanical loading and the effect of heating the specimen to a uniform temperature. The presence of specimen free edges and their influence on the accuracy of the rail shear test is discussed. Parameters include the length-to-width ratio of the specimen and the ply layup for symmetric, balanced laminates. Results presented include shear and normal stress distributions and the deflection behavior of various specimens caused by the mechanical loading and elevated temperature.

Weisshaar, T. A.↗
NASA NTRS2004

TIGER: Development of Thermal Gradient Compensation Algorithms and Techniques

In a wind tunnel facility, the direct measurement of forces and moments induced on the model are performed by a force measurement balance. The measurement balance is a precision-machined device that has strain gages at strategic locations to measure the strain (i.e., deformations) due to applied forces and moments. The strain gages convert the strain (and hence the applied force) to an electrical voltage that is measured by external instruments. To address the problem of thermal gradients on the force measurement balance NASA-LaRC has initiated a research program called TIGER - Thermally-Induced Gradients Effects Research. The ultimate goals of the TIGER program are to: (a) understand the physics of the thermally-induced strain and its subsequent impact on load measurements and (b) develop a robust thermal gradient compensation technique. This paper will discuss the impact of thermal gradients on force measurement balances, specific aspects of the TIGER program (the design of a special-purpose balance, data acquisition and data analysis challenges), and give an overall summary.

Hereford, James↗
DOE OSTI2020

Water and Ammonia Desorption from 5A Zeolite

Demonstrate adsorption and desorption characteristics of water and ammonia on 5A zeolite during regeneration conditions using a Thermogravimetric analyzer (TGA) on samples previously evaluated by residual gas analyzer (RGA)/mass balance. Molecular sieve (zeolite) adsorbents have the following characteristics: Crystalline alumino-silicates containing pores or 'cages' that adsorb water or other molecules. Polar compound are adsorbed with high loading even at very low concentrations of the fluid. A 5A molecular sieve was chosen for its ability to adsorb both water and ammonia (NH{sub 3}) from a carrier gas stream. Preliminary RGA/mass balance testing indicated: 5A zeolite captured both NH{sub 3} and water as anticipated based on molecular size; Reloading showed limited success after zeolite heated beyond manufacturer recommended operating conditions: Steam dealumination theorized cause; Tests were reprioritized to focus on NH{sub 3} removal and end of life potential holdup of NH{sub 3} and water on 5A zeolite material. TGA measures a sample's weight and volatile composition as it is heated or cooled in a furnace. TGA heats sample to release volatile materials, (change in mass is measured). MS detects/measures low levels of impurities. Perform TGA desorption of zeolite samples taken at the following conditions tested with RGA (RGA results not shown here): Initial Bakeout conditions: hydrogen carrier gas, slowly raise temp to approximately 300 deg. C until desired moisture content <<100 ppm is achieved. Water loading (re-loading): argon carrier gas through bubbler until breach is observed. Ammonia loading (re-loading): hydrogen carrier gas through system. Regenerations/End of life conditions: hydrogen carrier gas, raise temp to approximately 300 deg. C, then slowly to 450 deg. C (end of life). After end of life testing less than 4% of the total mass was residual ammonia or water at bakeout conditions. Peak water and ammonia removal occurred around 275 deg. C and 150 deg. C respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Ensemble voting-based fault classification and location identification for a distribution system with microgrids using smart meter measurements

This study presents an ensemble learning approach for fault classification and location identification in a smart distribution network containing photovoltaics (PV)-based microgrid. Lack of available data points and the unbalanced nature of the distribution system make fault handling a challenging task for utilities. The proposed method uses event-driven voltage data from smart meters to classify and locate faults. The ensemble voting classifier is composed of three base learners; random forest, k-nearest neighbours, and artificial neural network. The fault location (FL) task has been formulated as a classification problem where the fault type is classified in the first step and based on the fault type, the faulty bus is identified. The method is tested on IEEE-123 bus system modified with added PV-based microgrid along with dynamic loading conditions and varying fault resistances from 0 to 20 Ω for both unbalanced and balanced fault types. A further sensitivity analysis has been done to test the robustness of the proposed method under various noise levels and data loss errors in the smart meter measurements. The ensemble method shows improved performance and robustness compared to some previously proposed FL methods. Finally, the proposed method has been experimentally validated on a real-time simulation-based testbed using a state-of-the-art digital real-time simulator, industry standard DNP3 communication protocol and a cpu-based control centre running the FL algorithm.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Optimization of District Heating Network Parameters in Steady-State Operation

Here we examine the modeling, simulation, and optimization of district heating systems, which are widely used for thermal transport using steam or hot water as a carrier. We propose a generalizable framework to specify network models and scenario parameters, and develop an optimization method for evaluating system states including pressures, fluid flowrates, and temperatures throughout the network. The network modeling includes pipes, thermal plants, pumps, and passive or controllable loads as system components. We propose basic models for thermodynamic fluid transport and enforce the balance of physical quantities in steady-state flow over co-located outgoing and return networks. We formulate an optimization problem with steam and hot water as the outgoing and return carriers, as in legacy twentieth century systems. The physical laws and engineering limitations are specified for each component type, and the thermal network flow optimization problem is formulated and solved for a realistic test network under several scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1977

The vehicle design evaluation program - A computer-aided design procedure for transport aircraft

The vehicle design evaluation program is described. This program is a computer-aided design procedure that provides a vehicle synthesis capability for vehicle sizing, external load analysis, structural analysis, and cost evaluation. The vehicle sizing subprogram provides geometry, weight, and balance data for aircraft using JP, hydrogen, or methane fuels. The structural synthesis subprogram uses a multistation analysis for aerodynamic surfaces and fuselages to develop theoretical weights and geometric dimensions. The parts definition subprogram uses the geometric data from the structural analysis and develops the predicted fabrication dimensions, parts material raw stock buy requirements, and predicted actual weights. The cost analysis subprogram uses detail part data in conjunction with standard hours, realization factors, labor rates, and material data to develop the manufacturing costs. The program is used to evaluate overall design effects on subsonic commercial type aircraft due to parameter variations.

Oman, B. H.↗
DOE OSTI2020

Provision of Grid Services by PV Plants with Integrated Battery Energy Storage System: Preprint

Battery energy storage systems (BESS), due to their tremendous range of uses and configurations, may assist PV integration in any number of ways by increasing power system flexibility. In this paper we describe results of a research project conducted by NREL and First Solar for developing controls and demonstrating many use cases for PV-BESS systems including (1) matching generation to loads through time shifting, reducing PV curtailment,; (2) promoting higher levels of PV penetrations by balancing the grid through ancillary services; (3) use of PV-BESS systems to provide wide-area stability services in the form of oscillations damping controls; and (r) use of gird forming BESS for enabling black start and islanded applications for PV-BESS systems. In the paper we will also describe the unique multi-MW test and validation platform developed at NREL for conducting research on fielded utility-scale PV-BESS systems. The platform consists of First Solar 0.43 MW PV power plant, NREL’s 1MW/1MW BESS, 2MW PV power supplies and 7MVA power electronic grid simulator interfaced with industrial plant controllers and power-hardware-in-the-loop (PHIL) capability.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2025

A cross-dimensional analysis of data-driven short-term load forecasting methods with large-scale smart meter data

Electricity load forecasting is essential to utility operation and power grid stability. A wide spectrum of data-driven methods, ranging from linear regression models to more recent deep learning models have been adopted to forecast electric load over the years. However, there still lacks a holistic evaluation of the applicability of conventional statistical and machine learning based algorithms with respect to different temporal and spatial scopes, computational requirements, and sensitivity of model-tuning. Enabled by a large-scale electricity load profile dataset of over 40,000 residential customers in a utility region, we conducted a cross-dimensional analysis of data-driven load forecasting methods. Three regression-based and seven deep learning algorithms with different model configurations were evaluated in terms of their overall and peak load prediction accuracy, and training burdens, across spatial aggregation levels ranging from the transformer, feeder, substation, to neighborhood. We found, first, the load forecasting accuracy is constrained by a predictability boundary, influenced by the forecasting horizon and spatial aggregation level. Specifically, RandomForest, XGBoost, TFT, TSMixer, and TiDE models achieved less than 10 % prediction error for up to 96-h ahead forecasting for district, substation, and feeder levels, while other models struggle at long-horizon predictions; Second, for winter and summer peak load dates, most models were able to predict the peak demand timing within ± 1 h, but the prediction percentage error varied by models, with TFT and TiDE models being the top performers; Third, models with similar prediction accuracy can differ in training burden by an order of magnitude. Therefore, choosing model configurations that balance prediction performance and computational resource is an important practical consideration for large-scale deployment of the machine learning based load forecasting. The outcome of this study can guide researchers and practitioners to choose the proper load forecasting algorithms based on their problem scope, required accuracy, and available resources. The predictability boundary can serve as a benchmark for electricity load forecasting problems with new algorithms and datasets.

Li, Han↗
DOE OSTI2023

Modeling a Gas-Cooled Microreactor Balance of Plant for the Virtual Test Bed

High Temperature Gas-cooled Reactors (HTGRs) are one of the technology considered for microreactor designs because of their high performance and technological maturity. Several designs are being developed. These microreactor cores are connected to power conversion system (PCS) through a heat exchanger. For transient analysis, the feedback of the PCS or of the primary loop can be important, therefore, it is necessary to develop robust models for the balance of plant that can be coupled to a core model. In this work, a balance of plant model using the MOOSE Thermal Hydraulics module (THM) is presented and demonstrated for startup and load-follow transients. This model can be seamlessly coupled with any MOOSE-based multi-physics core model using the MOOSE multi-app approach.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2019

Aerodynamic Characterization and Improved Testing Methods for the Space Launch System Liftoff and Transition Environment

Low-speed wind tunnel testing for the liftoff and transition environment of the Space Launch System (SLS) was recently completed in the NASA Langley Research Center 14- by 22-Foot Subsonic Tunnel using 1.75%-scale models of three SLS vehicle configurations. During the liftoff testing, the primary objective was to evaluate the aerodynamic forces and moments on the SLS launch vehicles, as the vehicle, launch tower, and mobile launch platform were subjected to ground winds from all directions at varying heights for the vehicle off the launch pad. Additionally, aerodynamic forces and moments were acquired for all three SLS vehicles during the transition phase from liftoff to ascent that covered a wide range of angles of attack and angles of side slip. Details of the experimental setup including improved testing methods and a stiffer sting-balance system based on lessons learned from previous test entries are presented. Also, a new force measurement technique was applied during the test where two subminiature six-component load cells were installed in each Solid Rocket Booster (SRB) to acquire forces and moments for each SRB separately from the full vehicle forces and moments measured by the main strain gauge balance. Finally, sample results from the experiment are presented including improved overall data coverage, evaluation of the new SRB data, and smoke flow visualization photos.

Chan, David T.↗
DOE OSTI2025

Sensitivity analysis of numerical modeling input parameters on floating offshore wind turbine loads in extreme idling conditions

Abstract. Floating offshore wind turbine (FOWT) systems are subject to complex environmental loads, with significant potential for damage in extreme storm conditions. Design simulations in these conditions are required to assess the survivability of the device with some level of confidence. Aero-hydro-servo-elastic engineering tools can be used with a reasonable balance of accuracy and computational efficiency. The models require many input parameters to describe the air and water conditions, the system properties, and the load calculations. Each of these parameters has some possible range, due to either statistical uncertainty or variations with time. Variation in the input parameters can have important effects on the uncertainty in the resulting loads, but it is not practical to perform detailed assessments of the impact of this uncertainty for every input parameter. This work demonstrates a method to identify the input parameters that have the most impact on the loads to focus further inspection. The process is done specifically for extreme storm load cases defined in the International Electrotechnical Commission design requirements for floating offshore wind turbines. The analysis was performed using the International Energy Agency Wind 15 MW offshore reference wind turbine atop the University of Maine VolturnUS-S reference platform in two US offshore wind regions, the Gulf of Maine and Humboldt Bay. It was found that the direction of incident waves and current, yaw misalignment, and the length of mooring line sections were among the primary sensitivities.

17 WIND ENERGY↗
DOE OSTI2025

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗