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DOE OSTI2024

The National Climate Data Base (NCDB): A Bias-Corrected High-Resolution Climate Dataset

Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.

climate data↗

NASA NTRS2016

TEM Analyses of Itokawa Regolith Grains and Lunar Soil Grains to Directly Determine Space Weathering Rates on Airless Bodies

Samples returned from the moon and Asteroid Itokawa by NASA's Apollo Missions and JAXA's Hayabusa Mission, respectively, provide a unique record of their interaction with the space environment. Space weathering effects result from micrometeorite impact activity and interactions with the solar wind. While the effects of solar wind interactions, ion implantation and solar flare particle track accumulation, have been studied extensively, the rate at which these effects accumulate in samples on airless bodies has not been conclusively determined. Results of numerical modeling and experimental simulations do not converge with observations from natural samples. We measured track densities and rim thicknesses of three olivine grains from Itokawa and multiple olivine and anorthite grains from lunar soils of varying exposure ages. Samples were prepared for analysis using a Leica EM UC6 ultramicrotome and an FEI Quanta 3D dual beam focused ion beam scanning electron microscope (FIB-SEM). Transmission electron microscope (TEM) analyses were performed on the JEOL 2500SE 200kV field emission STEM. The solar wind damaged rims on lunar anorthite grains are amorphous, lack inclusions, and are compositionally similar to the host grain. The rim width increases as a smooth function of exposure age until it levels off at approximately 180 nm after approximately 20 My (Fig. 1). While solar wind ion damage can only accumulate while the grain is in a direct line of sight to the Sun, solar flare particles can penetrate to mm-depths. To assess whether the track density accurately predicts surface exposure, we measured the rim width and track density in olivine and anorthite from the surface of rock 64455, which was never buried and has a surface exposure age of 2 My based on isotopic measurements. The rim width from 64455 (60-70nm) plots within error of the well-defined trend for solar wind amorphized rims in Fig. 1. Measured solar flare track densities are accurately reflecting the surface exposure of the grains. Track densities correlate with the amorphous rim thicknesses. While the space-weathered rims of anorthite grains are amorphous, the space-weathered rims on both Itokawa and lunar olivine grains show solar wind damaged rims that are not amorphous. Instead, the rims are nanocrystalline with high dislocation densities and sparse inclusions of nanophase Fe metal. The rim thicknesses on the olivine grains also correlate with track density. The Itokawa olivine grains have track densities that indicate surface exposures of approximately 10(exp 5) years. Longer exposures (up to approximately 10(exp 7) years) do not amorphize the rims, as evidenced by lunar soil olivines with high track densities (approximately 10(exp 11) cm(exp -2)). From the combined data, shown in Fig. 1, it is clear that olivine is damaged (but not amorphized) more rapidly by the solar wind compared to anorthite. The olivine damaged rim forms quickly (in approximately 10(exp 6) y) and saturates at approximately 120nm with longer exposure time. The anorthite damaged rims form more slowly, amorphize, and grow thicker than the olivine rims. This is in agreement with numerical modeling data which predicts that solar wind damaged rims on anorthite will be thicker than olivine. However, the models predict that both olivine and anorthite rims will amorphize and reach equilibrium widths in less than 10(exp 3) y, in contrast to what is observed for natural samples. Laboratory irradiation experiments, which show rapid formation of fully amorphous and blistered surfaces from simulated solar wind exposures are also in contrast to observations of natural samples. These results suggest that there is a flux dependence on the type and extent of irradiation damage that develops in olivine. This flux dependence suggests that great caution be used in extrapolating between high-flux laboratory experiments and the natural case, as demonstrated by. We constrain the space weathering rate through analysis of returned samples. Provided that the track densities and the solar wind damaged rim widths exhibited by the Itokawa grains are typical of the fine-grained regions of Itokawa, then the space weathering rate is on the order of 10(exp 5) y. Space weathering effects in lunar soils saturate within a few My of exposure while those in Itokawa regolith grains formed in approximately 10(exp 5) y. Olivine and anorthite respond differently to solar wind irradiation. The space weathering effects in olivine are particularly difficult to reconcile with laboratory irradiation studies and numerical models. Additional measurements, experiments, and modeling are required to resolve the discrepancies among the observations and calculations involving solar wind amorphization of different minerals on airless bodies.

Berger, Eve L.↗

DOE OSTI2022

Improving tide-estuary representation in MPAS-Ocean (Final Report)

The overarching goal of this research is to produce a skill-assessed tide-estuary representation, including BGC (biogeochemistry) components of the ecosystem, into the MPAS-O global climate modeling system. Specifically, in the original proposal we proposed one-way nesting, into global MPAS-O, of a high-resolution model for TES (tidal and estuary systems) including the coupling of the BGC components. We have completed the proposed tasks during the past 4 years. Specifically, after extensive consultation with the MPAS-O group during the first year, we have decided to go beyond the original proposal and to two-way nest SCHISM into MPAS-O. As a result, SCHISM-CoSiNE (with CoSiNE being the BGC model) is now fully integrated into MPAS-O as a subroutine (more precisely, an analysis member) and can be invoked as MPAS-O is running with two-way exchange of information between the TES and global models (with proper spatial interpolation done on the fly). As originally proposed, we have also developed the new finite-volume (FV) model MPAS-OI (aka ELCIRC-sub) for TES. We have conducted several tests using the coupled MPAS-SCHISM- CoSiNE model and also MPAS-OI for Columbia River, San Francisco Bay and Chesapeake Bay. Four journal publications have been produced so far as the result of the project and 1 is under review (cf. Publication section). With these achievements, we will be ready to conduct fully coupled simulations of TES and global ocean anywhere, as soon as some missing capabilities in MPAS-O (e.g. tides, improved ability to handle the boundary conditions, and streamlining of the global BGC model) are worked out. The significance of the outcome of this project cannot be overstated. It marks the first time, as far as we know, that a global climate model is tightly coupled to a bona fide nearshore and terrestrial model (SCHISM system); in fact SCHISM is the first bona fide compound flooding model that seamlessly covers the coastal ocean, estuaries, rivers and watersheds (Ye et al. 2020; Zhang et al. 2020). The coupled model will reduce the errors and uncertainties of the MPAS-O global climate model system. It also complements and extends on-going E3SM project, as the latter seeks in the long-term to include components required to simulate impacts of sea-level change and storm surge on coastal regions, including wave models and focusing resolution in coastal and storm-track regions, as an important component of the Cryosphere-ocean system. Note that a spectral wave model (the unstructured-grid version of Wave Watch III, aka Wind Wave Model) is already incorporated inside the SCHISM system and is therefore directly accessible in the coupled system.

58 GEOSCIENCES↗

DOE OSTI2024

Recovered supernova Ia rate from simulated LSST images

Aims.TheVera C. RubinObservatory’s Legacy Survey of Space and Time (LSST) will revolutionize time-domain astronomy by detecting millions of different transients. In particular, it is expected to increase the number of known type Ia supernovae (SN Ia) by a factor of 100 compared to existing samples up to redshift ∼1.2. Such a high number of events will dramatically reduce statistical uncertainties in the analysis of the properties and rates of these objects. However, the impact of all other sources of uncertainty on the measurement of the SN Ia rate must still be evaluated. The comprehension and reduction of such uncertainties will be fundamental both for cosmology and stellar evolution studies, as measuring the SN Ia rate can put constraints on the evolutionary scenarios of different SN Ia progenitors. Methods.We used simulated data from the Dark Energy Science Collaboration (DESC) Data Challenge 2 (DC2) and LSST Data Preview 0 to measure the SN Ia rate on a 15 deg 2 region of the “wide-fast-deep” area. We selected a sample of SN candidates detected in difference images, associated them to the host galaxy with a specially developed algorithm, and retrieved their photometric redshifts. We then tested different light-curve classification methods, with and without redshift priors (albeit ignoring contamination from other transients, as DC2 contains only SN Ia). We discuss how the distribution in redshift measured for the SN candidates changes according to the selected host galaxy and redshift estimate. Results.We measured the SN Ia rate, analyzing the impact of uncertainties due to photometric redshift, host-galaxy association and classification on the distribution in redshift of the starting sample. We find that we are missing 17% of the SN Ia, on average, with respect to the simulated sample. As 10% of the mismatch is due to the uncertainty on the photometric redshift alone (which also affects classification when used as a prior), we conclude that this parameter is the major source of uncertainty. We discuss possible reduction of the errors in the measurement of the SN Ia rate, including synergies with other surveys, which may help us to use the rate to discriminate different progenitor models.

Astronomy & Astrophysics↗

NASA NTRS2007

The Effect of Acoustic Disturbances on the Operation of the Space Shuttle Main Engine Fuel Flowmeter

The Space Shuttle Main Engine (SSME) uses a turbine fuel flowmeter (FFM) in its Low Pressure Fuel Duct (LPFD) to measure liquid hydrogen flowrates during engine operation. The flowmeter is required to provide accurate and robust measurements of flow rates ranging from 10000 to 18000 GPM in an environment contaminated by duct vibration and duct internal acoustic disturbances. Errors exceeding 0.5% can have a significant impact on engine operation and mission completion. The accuracy of each sensor is monitored during hot-fire engine tests on the ground. Flow meters which do not meet requirements are not flown. Among other parameters, the device is screened for a specific behavior in which a small shift in the flow rate reading is registered during a period in which the actual fuel flow as measured by a facility meter does not change. Such behavior has been observed over the years for specific builds of the FFM and must be avoided or limited in magnitude in flight. Various analyses of the recorded data have been made prior to this report in an effort to understand the cause of the phenomenon; however, no conclusive cause for the shift in the instrument behavior has been found. The present report proposes an explanation of the phenomenon based on interactions between acoustic pressure disturbances in the duct and the wakes produced by the FFM flow straightener. Physical insight into the effects of acoustic plane wave disturbances was obtained using a simple analytical model. Based on that model, a series of three-dimensional unsteady viscous flow computational fluid dynamics (CFD) simulations were performed using the MSFC PHANTOM turbomachinery code. The code was customized to allow the FFM rotor speed to change at every time step according to the instantaneous fluid forces on the rotor, that, in turn, are affected by acoustic plane pressure waves propagating through the device. The results of the simulations show the variation in the rotation rate of the flowmeter due to the interaction of the flow straightener wakes and the upstream propagating acoustic waves. A detailed analysis of the acoustic disturbance effects is presented along with an assessment of the impact on measurement accuracy.

Marcu, Bogdan↗

DOE OSTI2021

Analysis of Loss-of-Offsite-Power Events: Update

Loss-of-offsite power (LOOP) can have a negative impact on a nuclear power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study were based on the operating experience during calendar years 1987–2020, while the most recent 15-year data (i.e., from 2006–2020) were used for most analyses in this report. LOOP events during critical operation that did not result in a reactor trip are not included. Frequencies and durations were determined for four LOOP event categories: plant-centered, switchyard-centered, grid-related, and weather related. Highly significant decreasing trends in the LOOP occurrence rates were identified for All-LOOPs during critical operation (p-value = 0.001) and switchyard-centered LOOPs during critical operation (p-value = 0.002) for the most recent 10-year period (2011–2020). Adverse trends in LOOP durations continue for switchyard-centered LOOPs (p-value = 0.005), All-LOOPs (p-value = 0.019), as well as All-LOOPs during shutdown operation (p-value = 0.003). Statistical tests show the LOOP counts are not uniformly distributed across the 12 months, and variation among the months exists for plant-centered LOOPs (p-value = 0.028), grid-related LOOPs (p-value = 0.021), All-LOOPs (p-value = 0.003), and All-LOOPs during critical operation (p-value = 0.008). The engineering analysis of LOOP data showed for the period of 2006–2020, the equipment failure events were dominated by failures of circuits and relay; human errors have been less frequent and occurred primarily in maintenance; and weather events were dominated by tornadoes and lightning.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS2001

The Vertical Error Characteristics of GOES-derived Winds: Description and Impact on Numerical Weather Prediction

Errors in the height assignment of some satellite-derived winds exist because the satellites sense radiation emitted from a finite layer of the atmosphere rather than a specific level. Potential problems in data assimilation may arise because the motion of a measured layer is often represented by a single-level value. In this research, cloud and water vapor motion winds that are derived from the Geostationary Operational Environmental Satellites (GOES winds) are compared to collocated rawinsonde observations (RAOBs). An important aspect of this work is that in addition to comparisons at each assigned height, the GOES winds are compared to the entire profile of the collocated RAOB data to determine the vertical error characteristics of the GOES winds. The impact of these results on numerical weather prediction is then investigated. The comparisons at individual vector height assignments indicate that the error of the GOES winds range from approx. 3 to 10 m/s and generally increase with height. However, if taken as a percentage of the total wind speed, accuracy is better at upper levels. As expected, comparisons with the entire profile of the collocated RAOBs indicate that clear-air water vapor winds represent deeper layers than do either infrared or water vapor cloud-tracked winds. This is because in cloud-free regions the signal from water vapor features may result from emittance over a thicker layer. To further investigate characteristics of the clear-air water vapor winds, they are stratified into two categories that are dependent on the depth of the layer represented by the vector. It is found that if the vertical gradient of moisture is smooth and uniform from near the height assignment upwards, the clear-air water vapor wind tends to represent a relatively deep layer. The information from the comparisons is then used in numerical model simulations of two separate events to determine the forecast impacts. Four simulations are performed for each case: 1) A control simulation that assimilates no satellite wind data, 2) assimilation of all GOES winds according to their assigned single level height, 3) assimilation of all GOES winds spread over multiple levels, and 4) assimilation of all GOES winds spread over multiple levels, but with variations in the vertical influence of clear-air water vapor winds based on the moisture profile in the model. In the first case, a strong mid-latitude cyclone is present and the use of the satellite data results in improved storm tracks during the initial approx. 36 h forecast period. This is because the satellite data improves the analysis of the environment into which the storm progresses. Statistics for mean wind vector and height differences show that, with the exception of the height field at later times in the first case, the use of GOES winds improves the simulation with time. The simulation results suggest that it is beneficial to spread the GOES wind information over multiple levels, particularly when the moisture profile is used to define the vertical influence.

Rao, P. Anil↗

DOE OSTI2026

Describing Point Defect Topology in 2D Energy Materials Through Computer Vision

Point defects such as vacancies and impurity atoms strongly impact the performance of 2D materials. Traditional efforts often rely on manual detection, a process that is time-intensive, prone to human error, and challenging to scale. Here we leverage machine learning (ML) methods to identify and quantify vacancies within 2D transition metal carbides (Ti3C2, MXenes), aiming to expedite detection while improving accuracy. MXenes exhibit valuable defect-defined electrochemical properties, but we currently lack statistical understanding of defect topology needed to fully harness these materials. Here we employ a convolutional neural network for semantic segmentation of experimental MXene images, opening an opportunity to conduct a rigorous statistical study on defect hierarchy while investigating local relaxation in the lattice. We show how the integration of ML can yield fundamental insight into point defects, providing a powerful tool that will play an increasingly crucial role in the future of materials science. ML is often not just a matter of straightforward application, and pretrained models proved ineffective in this case. Instead, we trained our own neural network (NN) and applied data augmentation techniques and fine-tuning to the training dataset. Since labeled microscopy data is often scarce, we developed training data from a previously published wide-frame MXene image, using customized Gaussian fitting to locate atomic positions. Our trained model was then applied to a large dataset of experimental images, enabling a statistical study of defect configurations across three samples prepared with different HF etchant concentrations (5%, 9.1%, and 12.5%), as shown in Fig. 1. This also allowed us to investigate local strain around vacancies, though we find that we are limited by the precision of measurements using high-angle annular dark field (HAADF) images, as shown in Fig. 2. This study demonstrates how ML enables large-scale, quantitative analysis of atomic defects - an otherwise infeasible task with traditional methods. While our NN was specialized for Ti3C2 MXenes, the pipeline we developed provides a foundation for future ML models tailored to other materials. Ultimately, we envision embedding the NN onto the microscope to give real-time feedback to the user. To make this a reality, continued work is necessary to fully understand the NN's capabilities and limitations. This study gets one step closer to our goals of automated experimentation moving away from traditional methods of manual labeling. As ML capabilities advance, we hope to continue adapting and applying these techniques in microscopy.

2D materials↗

NASA NTRS2021

The Temporal and Spatial Development of dB/dt for Substorms

Ground induced currents (GICs) due to space weather are a threat to high voltage power transmission systems. However, knowledge of ground conductivity is the largest source of errors in the determination of GICs. A good proxy for GICs is dB/dt obtained from the Bx and By components of the magnetic field fluctuations. It is known that dB/dt values associated with magnetic storms can reach dangerous levels for power transmission systems. On the other hand, it is not uncommon for dB/dt values associated with substorms to exceed prior Pulkkinen and Molinski critical thresholds of 1.5 nT/s and 5 nT/s, respectively, and the temporal and spatial changes of the dB/dt associated with substorms, unlike storms, are not well understood. Using two dimensional maps of dB/dt over North America and Greenland derived from the spherical elementary currents, we investigate the temporal and spatial change of dB/dt for both a single substorm event and a two dimensional superposed epoch analysis of many substorms. Both the single event and the statistical analysis shows a sudden increase of dB/dt at substorm onset followed by an expansion poleward, westward, and eastward after the onset during the expansion phase. The area of dB/dt values exceeding the two critical thresholds from the initial onset dB/dt values showed little to no expansion equatorward. The temporal and spatial development of the dB/dt resembles the temporal and spatial change of the auroral emissions. Substorm values of dB/dt peak shortly after the auroral onset time and in at least one event exceeded 35 nT/s for a non-storm time substorm. In many of our 81 cases the area that exceeds the threshold of 1.5 nT/s is over several million square kilometers and after about 30 minutes the dB/dt values fall below the threshold level. These results address one of goals of the Space Weather Action Plan, which are to establish benchmarks for space weather events and improve modeling and prediction of their impacts on infrastructure. Plain language: The change in the ground magnetic field with respect to time (dB/dt) associated with magnetic storms (a large disturbance of the magnetic field of the earth) can reach dangerous levels for power transmission systems. On the other hand, substorms, which are a smaller more localized disturbance of the Earth’s magnetic field, are more common. It is not uncommon for substorm dB/dt values to also exceed dangerous levels and the temporal and spatial changes of the dB/dt associated with substorms, unlike storms, are not well understood. Our analysis shows a sudden increase of dB/dt at substorm onset, which peaks shortly after the start of the substorm, followed shortly after by an expansion northward, westward, and eastward after the onset.

ionospheric currents↗

DOE OSTI2023

How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?

Cropland carbon budget depicts the amount of carbon flowing in and out of agroecosystems and the changes in carbon stocks of soil and living biomass during the same period. Soil carbon credit is the additional change in soil carbon stock under certain farming practices compared with the business-as-usual practices. Accurately calculating cropland carbon budget and soil carbon credit is critical to assessing climate change mitigation potential in agroecosystems. The calculation of cropland carbon budget and soil carbon credit is sensitive to local soil and climatic conditions, especially initial soil organic carbon (SOC) stock, which is determined by both SOC concentration (SOC%) and bulk density (Bulk_Density). SOC stock data are either from soil sampling or gridded public survey data. In agroecosystem models, SOC stock data are a key model input for quantifying cropland carbon budget and soil carbon credit. However, various types and degrees of uncertainties exist in SOC stock datasets, which propagate to the quantification of SOC stock change. In particular, a large discrepancy is found in two widely used SOC stock datasets — Rapid Carbon Assessment dataset (RaCA) and Gridded Soil Survey Geographic Database (gSSURGO) — in the U.S. Midwest, with a relative difference (quantified using Normalized Root Mean Square Error, NRMSE) of 48.0% for 0–30 cm SOC stock between the two datasets. It remains largely unclear how uncertainty in SOC stocks affects the calculation of cropland carbon budget and soil carbon credit. To address this question, we used a well-validated process-based agroecosystem model, ecosys, to assess the impacts of SOC stock uncertainty on carbon budget and soil carbon credit calculation in the U.S. Midwestern corn-soybean rotation systems. Our results reveal the following findings: (1) A sizable discrepancy exists in simulated cropland carbon budget between using gSSURGO and using RaCA for their SOC% and Bulk_Density as model inputs, with a Pearson correlation coefficient (r) of only 0.4 for simulated change of SOC stock (ΔSOC) using these two different soil datasets. (2) Simulated cropland carbon budget components were more sensitive to initial SOC% than to Bulk_Density. For example, the upper and lower quartiles of multi-year averaged ΔSOC were –29.8 and 4.8 gC/m 2 /year for the selected counties respectively, with an uncertainty of 13.7 and 0.7 gC/m 2 /year induced by uncertainties in initial SOC% and Bulk_Density, respectively. (3) Both simulated ΔSOC and its uncertainty were negatively correlated with initial SOC%, whereas ΔSOC was negatively correlated with air temperature, and ΔSOC uncertainty was positively correlated with air temperature. (4) The uncertainty of calculated soil carbon credits was much smaller compared with the uncertainty of calculated absolute carbon budgets assuming the same SOC stock uncertainty level in the inputs. Specifically, in our assessment comparing planting cover crops vs no cover crop, the uncertainty of calculated soil carbon credits induced by initial SOC% uncertainty was less than 4% (relative to the quantified value of the soil carbon credits) for 90% of the cases. Our analysis highlights that high accuracy measurement of SOC% as inputs is needed for the calculation of cropland carbon budgets; however, soil carbon credit quantification is much less sensitive to the initial SOC% inputs, and the current publicly available soil datasets (e.g., gSSURGO) are largely suitable for the calculation of soil

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Assessment of the Impact of Realistic Sensor Physics and the Integration of Ex-Core Sensors on Reactor Power Synthesis

In the work documented in this report, a weighting function–based core power synthesis method was applied to multiple Monte Carlo N-Particle (MCNP) reactor models, which are informed based on simulated self-powered neutron detector (SPND) responses. The weighting function method used has been coined the point-based iterative (PBI) method. The goal of this application is to assess the impact of considering realistic sensor physics in the generation of the simulated SPND outputs as well as to consider how the synthesis is impacted based on the inclusion of ex-core detectors in the model. The NuScale small modular reactor (SMR) and Westinghouse AP1000 pressurized water reactor (PWR) are the models that served as the testbeds for the assessment of realistic sensor physics; this was achieved by using Geant4 SPND models in comparison with analytical models, such that the effect of electron transport in realistic SPND geometries in the Geant4 model can be understood in terms of synthesis error and convergence time. The comparison was considered for fuel burnup–induced perturbations, for a range of sensor string densities and synthesized power distribution axial fidelities. The Texas A&M Testing, Research, Isotopes, General Atomics Reactor (TAMU TRIGA) reactor MCNP model was used to assess the impact of ex-core sensors; this was done by performing synthesis with and without the ex-core detectors and by quantifying the synthesis error and number of iterations associated with Gaussian-type perturbations in many locations in the core. The TAMU TRIGA model was particularly pertinent for this study because of the interest in future experimental tests with SPNDs in this reactor, as well as the ease of modifying the MCNP model to include ex-core detectors with heterogeneously described response functions. Results from the comparison between the Geant4 and analytical SPND models indicate that similar average and maximum synthesis errors were obtained for burnup-induced perturbations in both the NuScale SMR and the AP1000. This was true for a range of sensor string densities and axial fidelities. However, there were marked differences between both the Geant4 and analytically informed models in terms of the iterations required to converge on the synthesized power distribution. Namely, the Geant4-informed models tended to lead to fewer iterations, except for a few sensor–core configurations that had particularly numerous iterations. Results from the ex-core sensor assessment with the TAMU TRIGA model indicate that the inclusion of ex-core sensors drastically reduces the synthesis error of Gaussian-type perturbations close to the edge of the core, and it slightly reduces synthesis errors for perturbations closer to the center of the core. This was achieved with a minimal increase in computational cost—that is, the number of iterations required for convergence. The errors were identified to be in the same location as the perturbation in the core, indicating that the methodology remains robust for unperturbed regions of the core. A secondary result from this study with the TAMU TRIGA was yielded by analysis of the neutron flux levels in the in-core and ex-core sensor locations of the core; these flux levels indicate that SPNDs could be used as both in-core and ex-core sensors, so long as the emitter material is sensitive to thermal neutrons. The results from these studies provide a quantitative understanding of the importance of considering realistic sensor physics and including ex-core sensors to perform accurate and timely power distribution synthesis of a reactor core.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Performance assessment of a real water source heat pump within a hardware-in-the-loop (HIL) testing environment

Over the last decade, the global fight against climate change through electrification has led to an increase in research on building heating, ventilation, and air conditioning (HVAC) systems that utilize intelligent control algorithms to provide demand-side grid service while also maintaining the thermal comfort of building occupants. As the pivotal point between building electricity consumption and indoor thermal comfort, high-efficiency electrical vapor-compression heat pumps are at the center of these emerging studies, and various grid-interactive and occupant-comfort control algorithms have been developed for them. The impact of these algorithms on heat pump operation and performance when subjected to different weather conditions, building loads, and grid requests calls for investigation and verification via experimental testing with actual heat pumps integrated with real-time building and grid responses. This study introduces a Water-Source Heat Pump (WSHP) Hardware-in-The-Loop (HIL) Test Facility that is the first of its kind. This testbed utilizes a 2-ton variable speed water-to-air heat pump that is capable of interacting with a virtual environment currently comprised of an EnergyPlus (E+) building simulation, an agent-based occupant behavioral model, and a single U-tube ground-loop heat exchanger (GLHE) model. Detailed descriptions of the testbed’s physical design and operation, virtual environment, as well as their mutual communication is provided. An uncertainty analysis is also performed under manufacturer specified heating and cooling design conditions. This analysis shows that the total load across the WSHP’s demand side heat exchanger, i.e., the sum of its latent and sensible components, can be measured with a relative uncertainty of ± 10.4% and ± 3.6% in cooling and heating mode respectively. The WSHP’s coefficient of performance (COP) can be measured with relative uncertainties of ± 10.4% in cooling mode, and ± 3.7% in heating mode. A preliminary 24-h experimental demonstration is then performed utilizing the DOE prototype small commercial office building model in E+. The simulation takes place in Atlanta, GA on the date of 08/26/15 from 12:00 AM to 11:59 PM using TMY3 weather data. Here, the results from this demonstration show that over the course of this experiment the simulated outputs of zone dry-bulb temperature, zone humidity ratio, and WSHP inlet water temperature can be tracked by testbed emulators up to a root mean squared error (RMSE) of ± 0.27 °C, ± 0.376 g/kg, and ± 0.85 °C respectively. The WSHP’s dynamic behavioral characteristics and performance are also captured, and correspond well with the authors’ previous understanding of heat pump efficiency as a function of evaporator and condenser fluid inlet conditions respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRSDate not supplied

The Cognition Battery: Developing a Normative Database for Spaceflight and Examining the Impact of Prolonged Isolation and Confinement on Cognitive Performance

INTRODUCTION: Astronauts on future long duration space exploration will be required to execute complex tasks in which even minor errors could have devastating consequences. Intact cognition is critical to maintain exceptional performance standards and it is possible that variability even at the highest ends of the performance spectrum will impact operational tasks. Exposure to spaceflight hazards could compromise cognitive performance, and decrements have been documented under conditions of altered gravity and radiation exposure. The cognitive impacts of prolonged isolation and confinement remain relatively unknown. Traditional neuropsychological assessments cannot support earth independent monitoring, do not have normative comparisons for high functioning individuals, and most are not sensitive enough to detect small performance decrements. The Cognition Battery was developed to address these limitations but currently lacks comprehensive normative data. In this project, we aimed to 1) develop a preliminary normative database for astronauts and astronaut surrogates using the Cognition Battery, and 2) characterize differences in cognitive performance after short and long duration analog missions. PARTICIPANTS & METHODS: We assessed baseline cognitive performance by administering the Cognition Battery to 97 astronaut and astronaut surrogates recruited to approximate astronaut demographics (mean age: 39.38, SD=7.62; 35.1% female; 91.7% advanced degrees). For aim 1, we calculated speed and accuracy outcomes for each subtest and summarized the data with descriptive statistics. We examined the relationship between age and performance with Pearsons’s correlations and the relationship between gender and performance with independent samples t-tests. A subset of individuals on short duration (n=48; mean age: 38.18, SD=7.14; 37.5% female; 91.7% advanced degrees) missions of 45 days and long duration (n=34; mean age: 42.12, SD=8.39; 38.2% female; 94.1% advanced degrees) missions ranging from 4-8 months were administered the Cognition Battery during and after their respective missions. For aim 2, we accounted for practice effects using published corrections, and z-transformed post-mission scores using the full sample’s baseline scores. One-way analysis of covariance tests determined the main effect of analog duration on post-mission performance, after accounting for age and gender. The False Discovery Rate method was applied to adjust for multiple comparisons. RESULTS: In the full normative sample, older age was associated with slower reaction times on a processing speed task (r=.39, p=.02), and men were more accurate on processing speed (t=-2.19, p=.03) and faster on sustained attention (t=2.02, p=.049) and risk-taking tasks (t=2.49, p=.02). We observed a main effect of duration on performance on tasks of visual memory (f(1)=5.62, p=.04), processing speed (f(1)=5.48, p=.03), and sensorimotor functioning (f(1)=39.52, p < .001), such that slower performance was observed after long duration missions relative to short. Only sensorimotor functioning was significant after adjustments for multiple comparisons (adjusted p<.001). DISCUSSION: The full sample represents the largest dataset of cognitive performance assessed by the Cognition Battery available and can be used for further research in spaceflight and high-performance populations. Relationships between performance and key demographic variables suggest future research that include age and gender stratification is needed. Our results also show minimal changes in cognitive performance between longer and shorter periods of isolation and confinement.

S I Dev↗

DOE OSTI2022

A Multi-Scale Computational Platform for Predictive Modeling of Corrosion in Al-Steel Joints (Final Report)

The research team proposed to develop innovative multi-scale models to predict corrosion and the resulting mechanical performances in aluminum-steel joints. The methods of joining considered are resistance spot welding, self-piercing riveting, and rivet-welding, all suitable for mass production applications. The multi-scale models integrate high throughput first-principle calculations based on density functional theory (DFT), high throughput calculation of phase diagrams (CALPHAD) modeling, and finite element method (FEM) simulations. These models are to be validated through laboratory experiments. Furthermore, the models are available as open source so as to enable scientists and engineers in the community to adapt and contribute to the development and application. The approaches rely on the research team’s extensive experience on the prediction of properties of individual phases at finite temperatures and variable compositions through DFT calculations, and our broad expertise on dissimilar material joining and their corrosion. The proposed computational framework enables high throughput computations for improved predictions of corrosion and the associated mechanical performance in dissimilar material joints, resulting in significant reduction in computational time needed by the current state-of-the-art methods. With the participation of researchers from three universities, an auto manufacturer, two manufacturing technology/equipment suppliers, and a software developer/vendor, the interdisciplinary research team applies the technical development on both phase-based modeling and laboratory experiments into the automobile body joining processes for validation and technology demonstration. The global cost of corrosion was estimated at about 3.4% of the global GDP in 2013. By using available corrosion control practices, it is estimated a saving between 15-35% of the cost of corrosion. In the U.S., more than $276 billion is spent repairing corrosion damage. Prediction of the corrosion and its impact on performance of the dissimilar material joints is critical for reducing the massive number of the current corrosion-based recalls for automobiles. Thus, the project goal is to develop models to enable predictive maintenance and end-of-life planning of multi-metal joints with risk of corrosion under different conditions such as exposure to high temperatures in summer and salt solutions in winter, quantified through its pH. An academia-industry consortium led by the University of Michigan and including Pennsylvania State University, University of Illinois Urbana-Champaign, University of Georgia, General Motors Company, Livermore Software Technology Corporation, and Optimal Process Technologies, LLC. created multi-scale models for prediction of corrosion in aluminum-steel joint structures such of them used in vehicle subassemblies – chassis and transmission systems. Starting from the first principle calculations, the team developed mathematical and data-driven models to predict the metallic components, which are formed during joining of two metals, for example aluminum and steel - a lightweight multilateral system which is currently used in more than 60% car bodies. These models were used for simulating chemical reactions that are happening when the joining metallic components are exposed to high temperatures and different pH values. The team was able to predict how the corrosion installs on the metallic components and how they lead to a sudden failure of components in cars. Newly developed machine learning algorithms combining Science, Technology, Engineering and Math disciplines, advanced finite element simulation and experimental validations have been integrated in a platform for prediction of the corrosion evolution and prediction the failure of joints under mechanical loadings and fatigue. Moreover, based on machine learning and inverse analysis, the team proposed solutions for designing new metallic alloys less susceptible to corrosion when joining multi-material assembles. An average of 4% error compared with experiments was achieved for the most common joints that are used in vehicle subassemblies.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Investigating Low-Altitude Constellations of Ad-Hoc Lunar PNT System for Distributed Spacecraft Autonomy

In this study, we examine a low-altitude Lunar Position, Navigation, and Timing (LPNT) constellations and the localization performance of Centralized Extended Kalman Filter (CEKF) and Decentralized Extended Kalman Filter (DEKF) algorithms. The primary investigation involves a 100-node swarm operating at a 100 km altitude, in contrast to previous studies that examined a 21-node asset in a frozen-orbit at 5,500 km. The autonomous operation of large-scale swarm is based on two-way Inter-Satellite Link (ISL) measurements, which involve pseudoranges and relative velocities among swarm nodes. We perform a numerical assessment of the two filtering approaches, utilizing ‘fully sampled’ measurements from all available assets as well as ‘two ISL’ measurements where each spacecraft is restricted to only two antennas. This research includes an analysis of CEKF under 2-ISL constraints and evaluates the performance of DEKF in a 100-node swarm, which has not been explored in previous studies. In addition, we examine the impact of increasing the sampling frequency for DEKF, showing that the update cycle can be shortened from a 10-minute interval. A novel approach for ‘2-ISL limited’ DEKF will also be introduced, using a matching formulation that exhaustively enumerates all potential matches. This study provides valuable insights into large-scale distributed swarm operations, considering various filter configurations, sampling frequencies, matching strategies, and scalability of CEKF and DEKF for low-altitude LPNT applications. The Lunar PNT technology plays a key role in providing reliable and robust navigation services on the Moon's surface and the South pole, where the primary Lunar missions are planned. To support upcoming Lunar missions, including small satellites from NASA's Commercial Lunar Payload Services program, the Lunar PNT system must be adaptable to smaller platforms like CubeSats. Driven by the growing involvement of public and private exploration partnerships, the traditional low Earth orbit missions are shifting to beyond geosynchronous orbit [1]. These upcoming missions aim to foster a sustainable and innovative exploration program, in collaboration with commercial and international partners, to facilitate human expansion throughout the solar system and return new knowledge and opportunities to Earth [2]. As part of this trend, there are increasing efforts to utilize science missions in Lunar orbit to develop a non-dedicated and ad-hoc PNT network system. Two traditional approaches, the Deep Space Network (DSN) and the weak signal Global Positioning System (GPS), are established deep-space navigation technologies for missions beyond the geosynchronous orbit. Beginning in 1958, the DSN was developed to communicate with the Explorer 1 spacecraft based on the use of radiometric tracking in spacecraft navigation [3]. The DSN is capable of providing nearly unfettered coverage to spacecraft beyond low-Earth orbit (LEO), however, increased space mission volume has created concerns about future expectations of DSN usage for spacecraft navigation [4]. For cislunar mission applications, the position accuracy using DSN achieves 100 m (3σ) with at least three geometrically diverse ground stations when using radiometric tracking alone [5]. The DSN's dependence on Earth-based ground stations restricts its operational capabilities to periods of Earth visibility. This limitation, coupled with its poor localization performance, renders the DSN unsuitable for future lunar missions that demand continuous tracking and precise positioning. To satisfy the increasing requirements of DSN in Lunar applications, spacecrafts are also required to improve their onboard antenna power and efficiency of the transmission. However, there is an important aggregate cost trade between adding capabilities to every spacecraft and adding to a capacity on the ground that serves multiple spacecraft [6]. A weak GPS system can provide PNT service while the user spacecraft is bound to the Moon, leveraging a single, steerable high gain antenna with the relatively narrow beam which includes all the sources in its field of view [7]. However, the higher the altitude the receiver is above the GPS constellations, the poorer and the weaker are the relative geometry and the received signal powers, respectively, leading to a significant navigation accuracy reduction [8]. The transmitted power becomes weaker with increasing distance from the Earth as well as signals tracked from one of the side lobes of the GPS antenna pattern. As a results, the number of visible satellites and relative geometric condition of the GPS satellites at very high altitude drops dramatically and reduces the navigation solution accuracy. Therefore, the weak GPS system is also not an ideal way to provide PNT service to upcoming Lunar missions when considering its limited geometric condition and the recued navigation accuracy. Another navigation approach on the Moon is being developed, similar to the Global Navigation Satellite System (GNSS) on Earth, aiming to offer navigation service with continuous 24/7 coverage across the entire Lunar surface. For example, lunar communications relay and navigation systems (LCRNS) by NASA and Lunar navigation satellite systems (LNSS) by JAXA are designed to serve as dedicated Position, Navigation, and Timing (PNT) systems for the Moon. However, designing a dedicated LNSS and PNT service involves additional challenges, which are unique to the lunar environment, including limited payload capacity for the CubeSat platform, i.e., the size, weight, and power (SWaP) of the onboard clock, limited lunar ground monitoring stations, and limited financial investment as compared to the legacy Earth-GPS [9]. NASA’s focus on utilizing CubeSat platforms on the Moon leads to an alternative Lunar navigation platform that leverages the existing Lunar science and exploration assets. The small satellites used in Lunar missions can be used to create a low-cost, autonomous, ad-hoc, and on-demand mission-centric Lunar PNT swarm capable of providing PNT services to these low-cost lunar missions [10]. As upcoming Lunar missions will often operate at low-altitude about 30 km to 100 km for scientific observations and mapping purposes, the low-altitude orbital constellations could be employed to create an ad-hoc Lunar PNT system. However, several issues must be addressed, such as the instability of these orbits, which often require maintenance or are only suitable for short-duration missions, operating for fewer than 90 days. Additionally, at an altitude of 100 km, the satellites have a limited period during which they are above the horizon and capable of providing PNT service to users. The implementation of a non-dedicated, ad-hoc Lunar navigation constellation facilitates on-demand PNT services. A preliminary study of ad-hoc Lunar PNT system was conducted using 21 spacecraft in 5,5000 km altitude frozen orbits to test its feasibility and a basic performance of orbital asset localization among ad-hoc Lunar constellations in small satellites format [10]. These swarm assets are designed for autonomous localization with minimal Earth interaction, reducing dependency on bandwidth and ground resources. The design in [10] demonstrated the feasibility of a decentralized PNT approach, specifically employing a DEKF approach for state estimation, which helps minimize onboard operating costs. The DEKF method distributes computation across individual satellites, which lightens the computational load while maintaining accuracy in orbit ephemeris and clock offsets, similar to centralized systems [11]. In a follow-on study [12], each spacecraft was limited to 2 communications antennae, forcing the selection of measurements and scheduling spacecraft activities to perform the measurements. A matching algorithm is implemented to select the best measurements and schedule position estimation updates. The decentralized localization performance is also investigated with increasing levels of network degradation for swarm assets considering the impact of intermittent and permanent communication failure, to demonstrate the robustness and fidelity of the decentralized Lunar PNT service [13]. This study confirmed that the ad-hoc PNT constellations in frozen orbit are highly robust and resilient to communication failures. However, unlike frozen orbit swarm assets, the low-altitude satellites have a limited ground view at an altitude of 100 km, where the ad-hoc Lunar constellation consists of 98 low-altitude satellites, evenly distributed across seven circular polar orbital planes, alongside two satellites in a frozen orbit at an altitude of 5,500 km (Figure 1). Therefore, the number of satellites visible to ground users is significantly limited in low-altitude orbit constellations. As each visibility of a spacecraft remains intact for only a few ticks before it moves out of the field of view, the ground user encounters challenges in maintaining continuous navigation service, resulting in sparse availability and provision of Lunar PNT system. Consequently, service availability is primarily restricted to the Lunar South Pole region (Figure 2). Given these limitations and concerns, the localization performance of low-altitude swarm assets will be assessed in this study. We focus on the investigation of the localization performance of low-altitude swarm assets and ground users near the Lunar South Pole. The overall flow of the Lunar PNT simulation incorporates the DEKF approach of asset localization and the weighted least-squares approach in user localization (Figure 3). The autonomous Lunar PNT simulation is primarily implemented in MATLAB, where the DEKF based on the matching scheduler is implemented with Google’s OR-tools as a model builder and Gurobi optimization tool as a backend solver. The General Mission Analysis Tool (GMAT) is utilized to generate ephemeris data for swarm assets, and accounts for satellite orbital details, mass, and perturbations like solar radiation pressure and drag coefficients. Each ephemeris dataset is produced in the Moon International Celestial Reference Frame (ICRF) inertial coordinate system. For state estimation, the distributed swarm assets rely on two-way Inter-Satellite Link (ISL) measurements, which involve tracking pseudoranges and relative velocities between visible satellites and anchor nodes during each observation. Numerical evaluations of the decentralized localization process are conducted to demonstrate the feasibility of the low-altitude PNT system in providing reliable navigation services. The main approach involves using DEKF and CEKF to localize 100 satellites in low-altitude constellations, where the CEKF is implemented to serve as a baseline for comparing the performance of distributed algorithms. In both cases, we evaluate ‘fully sampled’ measurements from all available assets, and ‘two ISL’ measurements when spacecraft are constrained to have only two antennas. We test four estimation techniques: CEKF fully sampled, CEKF two ISL, DEKF fully sampled, and DEKF two ISL filters. As the DEKF update cycle is comprised of network setup, communication, and computations, a global broadcast network and 2-way ISL network setup will take from 4 to 6 minutes as maximum [12]. In this simulation, the DEKF update cycle is set to 10 minutes, including a 4-minute latency for obtaining and computing the actual measurement updates. We experiment an increased update cycle to demonstrate the feasibility and evaluate the impact on localization performance using various tuning values for measurement noise covariances (Figures 4 and 5). By comparing centralized and decentralized approaches using a matching algorithm, we analyze the influence of cross-correlation factors in the covariance matrix, assuming 100% reliability of all assets and measurements. The increased frequency and the adjustments of tuning parameters reveal distinct error patterns between the two scenarios. The localization accuracy of the swarm assets and ground users is assessed by taking the median error across 100 assets and one ground user (84.9°S, 137.5°E) over 7-day simulation period (Table 1). Since the user localization accuracy is significantly affected by the performance of the swarm assets, it is crucial to maintain high localization accuracy within the swarm. This study will continue to explore decentralized filtering for autonomous LPNT operations, with further investigation of an 'iterative' matching approach which enumerates every valid matching pair, planned for the following month.

Yeji Kim↗

DOE OSTI2022

Analysis of Loss-of-Offsite-Power Events: 2021 Update

Loss-of-offsite power (LOOP) can have a negative impact on a nuclear power plant’s ability to achieve and maintain safe shutdown conditions. LOOP event frequencies and times required for subsequent restoration of offsite power are important inputs to plant probabilistic risk assessments. This report presents a statistical and engineering analysis of LOOP frequencies and durations at U.S. commercial nuclear power plants. The data used in this study were based on the operating experience during calendar years 1987–2021, while the most recent 15-year data (i.e., from 2007–2021) were used for most analyses in this report. LOOP events during critical operation that did not result in a reactor trip are not included. Frequencies and durations were determined for four LOOP event categories: plant-centered, switchyard-centered, grid-related, and weather-related. These categories (and the All-LOOPs group which contains all LOOPs without regarding of the four categories) could be further grouped by whether a LOOP event occurred during critical operation, during shutdown operation, or during all operations. The following decreasing trends in the LOOP occurrence rates were identified for the most recent 10-year period (2012–2021): All-LOOPs during critical operation, switchyard-centered LOOPs during critical operation, and grid-related LOOPs during critical operation. Adverse trends in LOOP durations continue for switchyard-centered LOOPs during all operations, All-LOOPs during all operations, and All-LOOPs during shutdown operation for the 1997–2021 period. Statistical tests show the LOOP counts for the period of 2007–2021 are not uniformly distributed across the 12 months, and variation among the months exists for grid-related LOOPs during all operations, All-LOOPs during all operations, and All-LOOPs during critical operation. The engineering analysis of LOOP data showed for the period of 2007–2021, the equipment failure events were dominated by failures of relay and other; human errors have been less frequent and occurred primarily in maintenance and switching; and weather were dominated by tornadoes then by lightning and hurricane. Weather was the cause for 45% of LOOPs for the last fifteen years (2007– 2021) but only for 20% of LOOPs for the previous 20 years (1987–2006) .

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2026

Representativity error scaling of models of the high temperature test facility

Error scaling is a critical step toward the validation of modeling capabilities for high-temperature gas-cooled reactors (HTGRs). Extensive effort is being made to bring HTGRs into the validation basis of numerous thermal-hydraulics codes. Here, this paper demonstrates how systems-level codes can be leveraged to perform error scaling analyses between an experimental facility and a plant-to-be facility. Specifically, we focus on two conduction cooldown experiments from the High Temperature Test Facility (HTTF) and the General Atomics 350 MW th modular high-temperature gas-cooled reactor (MHTGR-350). The error scaling methodology employed in this study is representativity, which in the context of this work was used to quantify how well experiments captured the physics of the plant facility by comparing sensitivity vectors between the two facilities. In addition, two different RELAP5–3D models of the HTTF were included in the comparison to determine if modeling methodologies notably impact the representativity results. The key figures of merit are the maximum block temperature and the coolant outlet temperature. The time-dependent maximum block temperature had a low representativity of below 0.1 for both models across both transients. The coolant outlet temperature had a higher representativity of around 0.6 for both models during the pressurized conduction cooldown, but it was below 0.2 for the depressurized conduction cooldown. Overall, the HTTF experiments were not representative of the transients in the MHTGR-350. However, these results can play a significant role in informing future potential experiments for HTGR systems that iterate on what the HTTF accomplished.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1993

Analytic Theory and Control of the Motion of Spinning Rigid Bodies

Numerical simulations are often resorted to, in order to understand the attitude response and control characteristics of a rigid body. However, this approach in performing sensitivity and/or error analyses may be prohibitively expensive and time consuming, especially when a large number of problem parameters are involved. Thus, there is an important role for analytical models in obtaining an understanding of the complex dynamical behavior. In this dissertation, new analytic solutions are derived for the complete attitude motion of spinning rigid bodies, under minimal assumptions. Hence, we obtain the most general solutions reported in the literature so far. Specifically, large external torques and large asymmetries are included in the problem statement. Moreover, problems involving large angular excursions are treated in detail. A new tractable formulation of the kinematics is introduced which proves to be extremely helpful in the search for analytic solutions of the attitude history of such kinds of problems. The main utility of the new formulation becomes apparent however, when searching for feedback control laws for stabilization and/or reorientation of spinning spacecraft. This is an inherently nonlinear problem, where standard linear control techniques fail. We derive a class of control laws for spin axis stabilization of symmetric spacecraft using only two pairs of gas jet actuators. Practically, this could correspond to a spacecraft operating in failure mode, for example. Theoretically, it is also an important control problem which, because of its difficulty, has received little, if any, attention in the literature. The proposed control laws are especially simple and elegant. A feedback control law that achieves arbitrary reorientation of the spacecraft is also derived, using ideas from invariant manifold theory. The significance of this research is twofold. First, it provides a deeper understanding of the fundamental behavior of rigid bodies subject to body-fixed torques. Assessment of the analytic solutions reveals that they are very accurate; for symmetric bodies the solutions of Euler's equations of motion are, in fact, exact. Second, the results of this research have a fundamental impact on practical scientific and mechanical applications in terms of the analysis and control of all finite-sized rigid bodies ranging from nanomachines to very large bodies, both man made and natural. After all, Euler's equations of motion apply to all physical bodies, barring only the extreme limits of quantum mechanics and relativity.

Tsiotras, Panagiotis↗