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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Lunar Pole Illumination and Communications Maps Computed from GSSR Elevation Data

A Digital Elevation Model of the lunar south pole was produced using Goldstone Solar System RADAR (GSSR) data obtained in 2006.12 This model has 40-meter horizontal resolution and about 5-meter relative vertical accuracy. This Digital Elevation Model was used to compute average solar illumination and Earth visibility with 100 kilometers of the lunar south pole. The elevation data were converted into local terrain horizon masks, then converted into lunar-centric latitude and longitude coordinates. The horizon masks were compared to latitude, longitude regions bounding the maximum Sun and Earth motions relative to the moon. Estimates of Earth visibility were computed by integrating the area of the region bounding the Earth's motion that was below the horizon mask. Solar illumination and other metrics were computed similarly. Proposed lunar south pole base sites were examined in detail, with the best site showing yearly solar power availability of 92 percent and Direct-To-Earth (DTE) communication availability of about 50 percent. Similar analysis of the lunar south pole used an older GSSR Digital Elevation Model with 600-meter horizontal resolution. The paper also explores using a heliostat to reduce the photovoltaic power system mass and complexity.

lunar base↗
NASA NTRS2010

Lunar Pole Illumination and Communications Statistics Computed from GSSR Elevation Data

The Goldstone Solar System RADAR (GSSR) group at JPL produced a Digital Elevation Model (DEM) of the lunar south pole using data obtained in 2006. This model has 40-meter horizontal resolution and about 5-meter relative vertical accuracy. This paper uses that Digital Elevation Model to compute average solar illumination and Earth visibility near the lunar south pole. This data quantifies solar power and Earth communications resources at proposed lunar base locations. The elevation data were converted into local terrain horizon masks, then converted into selenographic latitude and longitude coordinates. The horizon masks were compared to latitude, longitude regions bounding the maximum Sun and Earth motions relative to the moon. Proposed lunar south pole base sites were examined in detail, with the best site showing multi-year averages of solar power availability of 92% and Direct-To-Earth (DTE) communication availability of about 50%. Results are compared with a theoretical model, and with actual sun and Earth visibility averaged over the years 2009 to 2028. Results for the lunar North pole were computed using the GSSR DEM of the lunar North pole produced in 1997. The paper also explores using a heliostat to reduce the photovoltaic power system mass and complexity.

Lunar base↗
NASA NTRS2004

Orbit Design Based on the Global Maps of Telecom Metrics

In this paper we describe an orbit design aide tool, called Telecom Orbit Analysis and Simulation Tool(TOAST). Although it can be used for studying and selecting orbits for any planet, we solely concentrate on its use for Mars. By specifying the six orbital elements for an orbit, a time frame of interest, a horizon mask angle, and some telecom parameters such as the transmitting power, frequency, antenna gains, antenna losses, link margin, received threshold powers for the rates, etc. this tool enables the user to view the animation of the orbit in two and three-dimensional different telecom metrics at any point on the Mars, namely the global planetary map.

Mars orbiter↗
NASA NTRS1994

Arctic sea ice albedo from AVHRR

The seasonal cycle of surface albedo of sea ice in the Arctic is estimated from measurements made with the Advanced Very High Resolution Radiometer (AVHRR) on the polar-orbiting satellites NOAA-10 and NOAA-11. The albedos of 145 200-km-square cells are analyzed. The cells are from March through September 1989 and include only those for which the sun is more than 10 deg above the horizon. Cloud masking is performed manually. Corrections are applied for instrument calibration, nonisotropic reflection, atmospheric interference, narrowband to broadband conversion, and normalization to a common solar zenith angle. The estimated albedos are relative, with the instrument gain set to give an albedo of 0.80 for ice floes in March and April. The mean values for the cloud-free portions of individual cells range from 0.18 to 0.91. Monthly averages of cells in the central Arctic range from 0.76 in April to 0.47 in August. The monthly averages of the within-cell standard deviations in the central Arctic are 0.04 in April and 0.06 in September. The surface albedo and surface temperature are correlated most strongly in March (R = -0.77) with little correlation in the summer. The monthly average lead fraction is determined from the mean potential open water, a scaled representation of the temperature or albedo between 0.0 (for ice) and 1.0 (for water); in the central Arctic it rises from an average 0.025 in the spring to 0.06 in September. Sparse data on aerosols, ozone, and water vapor in the atmospheric column contribute uncertainties to instantaneous, area-average albedos of 0.13, 0.04, and 0.08. Uncertainties in monthly average albedos are not this large. Contemporaneous estimation of these variables could reduce the uncertainty in the estimated albedo considerably. The poor calibration of AVHRR channels 1 and 2 is another large impediment to making accurate albedo estimates.

Lindsay, R. W.↗
NASA NTRS1994

A GPS coverage model

The results of several case studies using the Global Positioning System coverage model developed at Ohio University are summarized. Presented are results pertaining to outage area, outage dynamics, and availability. Input parameters to the model include the satellite orbit data, service area of interest, geometry requirements, and horizon and antenna mask angles. It is shown for precision-landing Category 1 requirements that the planned GPS 21 Primary Satellite Constellation produces significant outage area and unavailability. It is also shown that a decrease in the user equivalent range error dramatically decreases outage area and improves the service availability.

Skidmore, Trent A.↗
DOE OSTI2025

Uncertainty-Guided Prediction Horizon of Phase-Resolved Ocean Wave Forecasting Under Data Sparsity: Experimental and Numerical Evaluation

Accurate short-term wave forecasting is critical for the safe and efficient operation of marine structures that rely on real-time, phase-resolved ocean wave information for control and monitoring purposes (e.g., digital twins). These systems often depend on environmental sensors (e.g., waverider buoys, wave-sensing LIDAR). Challenges arise when upstream sensor data are missing, sparse, or phase-shifted due to drift. This study investigates the performance of two machine learning models, time-series dense encoder (TiDE) and long short-term memory (LSTM), for forecasting phase-resolved ocean surface elevations under varying degrees of data degradation. We introduce the τ-trimming algorithm, which adapts the prediction horizon based on uncertainty thresholds derived from historical forecasts. Numerical wave tank (NWT) and wave basin experiments are used to benchmark model performance under short- and long-term data masking, spatially coarse sensor grids, and upstream phase shifts. Results show under a 50% probability of upstream data loss, the τ-trimmed TiDE model achieves a 46% reduction in error at the most upstream target, compared to 22% for LSTM. Furthermore, phase misalignment in upstream data introduces a near-linear increase in forecast error. Under moderate model settings, a ±3 s misalignment increases the mean absolute error by approximately 0.5 m, while the same error is accumulated at ±4 s using the more conservative approach. These findings inform the design of resilient, uncertainty-aware wave forecasting systems suited for realistic offshore sensing environments.

42 ENGINEERING↗
DOE OSTI2022

Anomalies in the topology of the temperature fluctuations in the cosmic microwave background: An analysis of the NPIPE and FFP10 data releases

We present a topological analysis of the temperature fluctuation maps from the Planck 2020 Data Release 4 NPIPE dataset and the Planck 2018 Data Release 3 FFP10 dataset. We performed a multiscale analysis in terms of the homology characteristics of the maps, invoking relative homology to account for the analysis in the presence of masks. We performed our analysis for a range of smoothing scales spanning sub- and super-horizon scales corresponding to a full width at half maximum (FWHM) of 5',10',20',40',80',160',320', and 640', and employed simulations based on the standard model for comparison, which assumes the initial fluctuation field to be an isotropic and homogeneous Gaussian random field. Examining the behavior of topological components, represented by the 0D homology group, we find the observations to be approximately 2σ or less deviant from the simulations for all resolutions and scales for the NPIPE dataset. For the FFP10 dataset, we detect a 2.96σ deviation between the observations and simulations at N = 128, FWHM = 80'. For the topological loops, represented by the first homology group, the simulations and observations are consistent within 2σ for most resolutions and scales for both the datasets. However, for the NPIPE dataset, we observe a high deviation between the observation and simulations in the number of loops at FWHM = 320', but at a low dimensionless threshold ν = –2.5. Under a Gaussian assumption, this would amount to a deviation of ~4σ. However, the distribution in this bin is manifestly non-Gaussian and does not obey Poisson statistics either. In the absence of a true theoretical understanding, we simply note that the significance is higher than what may be resolved by 600 simulations, yielding an empirical p-value of at most 0.0016. Specifically in this case, our tests indicate that the numbers arise from a statistically stable regime, despite being based on small numbers. For the FFP10 dataset, the differences are not as strong as for the NPIPE dataset, indicating a 2.77σ deviation at this resolution and threshold. The Euler characteristic, which is the alternating sum of the ranks of relative homology groups, reflects the deviations in the components and loops. To assess the significance of combined levels for a given scale, we employed the empirical and theoretical versions of the χ 2 test as well as the nonparametric Tukey depth test. Although all statistics exhibit a stable distribution, we favor the empirical version of the χ 2 test in the final interpretation, as it indicates the most conservative differences. For the NPIPE dataset, we find that the components and loops differ at more than 95%, but agree within the 99% confidence level with respect to the base model at N = 32, FWHM = 320'. The Euler characteristic at this resolution displays a per mil deviation. In contrast, the FFP10 dataset shows that the observations are consistent with the base model within the 95% confidence level, at this and smaller scales. This is consistent with the observations of the Planck analysis pipeline via Minkowski functionals. For the largest smoothing scale, N = 16, FWHM = 640', both datasets exhibit an anomalous behavior of the loops, where FFP10 data exhibit a deviation that is larger by an order of magnitude than that of the NPIPE dataset. In contrast, the values for the topological components and the Euler characteristic agree between observations and model to within a confidence level of 99%. However, for the largest scales, the statistics are based on low numbers and may have to be regarded with caution. Even though both datasets exhibit mild to significant discrepancies, they also exhibit contrasting behaviors at various instances. Therefore, we do not find it feasible to convincingly accept or reject the null hypothesis. Disregarding the large-scale anomalies that persist at similar scales in WMAP and Planck, observations of the cosmic microwave background are largely consistent with the standard cosmological model within 2σ.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

Elemental abundance anomalies in the late Cenomanian extinction interval - A search for the source(s)

Measurements of elemental abundances by neutron activation methods across the Cenomanian-Turonian extinction interval in samples collected from 16 sites in the Western Interior Basin of North America from 12 widely separated locations around the globe, including six ODP/DSDP sites, are reported. In most Western Interior Basin sites, in Colombia, and in Western Europe, two closely spaced elemental abundance peaks occur in the upper Cenomanian (about 92 m.y.), spanning the ammonite zones of Sciponoceras gracile through Neocardioceras juddii. Elements with anomalously high concentrations include Sc, Ti, V, Cr, Mn, Co, Ni, Ir, Pt, and Au. The lower peak coincides with the disappearance (extinction) of the foraminifer Rotalipora cushmani. In North American sections R. greenhornensis also disappears at or just below this horizon, but in Europe it disappears considerably earlier than R. cushmani. Although the weak geochemical signal from comet impact(s) could be masked by the strong terrestrial-like overprint, these anomalies more likely resulted in the large late Cenomanian through early Turonian eustatic rise and deep-water opening of the South Atlantic.

Orth, Charles J.↗
NASA NTRS2026

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona↗
DOE OSTI2019

Support for Reactor Operators in Case of Cyber-Security Threats (NEUP Final Report)

Increasing use of digital technology in nuclear power plants (NPPs) poses cyber-security as a crucial threat to public safety and to continuous energy production. Cyber-security risks are comprised of complex known and unknown interactions between various entities, system vulnerabilities, network protocols, human users and malicious attacks. There is little understanding or research geared towards plant operators’ response under cyber-security threats and operational procedures to cope with such threats. This is particularly critical when a cyber-security event masquerades as a safety incident or an evolving accident. Instead of leading operators to the remediation of the accident, the masked cyber event may lead them to circumvent the safety mechanisms of the plant. Given these challenges, the objective of this project is to develop a tool to characterize abnormal NPP events as “cyber” or “safety” incidents, and to further develop this tool as a real-time operator aid to assist in response to the incident. This NEUP Final Report summarizes the research efforts towards the above goals and the results in the following three aspects. First, a methodology for classifying abnormal NPP events as cyber-attacks or safety incidents was developed. This provides the basis for responding to potential cyber-attacks. In this methodology, the causal relationships between various variables (i.e., physical variables, network variables, and control variables) for a nuclear system under consideration are modeled using dynamic Bayesian networks. Based on observations of certain variables (i.e., the evidence), inference is performed to identify the state of hidden variables, which helps indicate the occurrence of cyber-attacks or safety incidents. The proposed methodology was applied to the full scope NPP simulator system at The Ohio State University as a case study. The result shows that the proposed methodology is capable of distinguishing between cyber-attacks and safety incidents. Second, a game-theoretic approach for responding to cyber-attacks on nuclear power plants was developed. This is the second major goal of the project, and the method is used to recommend optimal responses to reactor operators in the case of cyber-attacks. We consider two cases in this research. In the first case, the interaction between the defender (i.e., the reactor operator) and the attacker is modeled as a two-player, nonzero-sum, Markov game with an infinite time horizon. In the second case, we consider a semi-Markov game between the defender and the attacker within a finite time horizon. The model in the second case enables us to consider the time sensitive response of the defender. In each case, the method for deriving the Nash equilibrium is developed. The Nash Equilibrium of the game provides the valid prediction of both players’ actions because no single player can benefit from unilaterally deviating from the equilibrium policy if the other player adheres to his/hers, hence it provides the best response of the defender to cyber-attacks. The proposed method in each case is demonstrated through a simplified benchmark digital feedwater control system. Third, a prototype display is developed to integrate the above information. The prototype display depicts the communication information to the operator and incorporates the cyber-security tool developed by the team into the interface. It consists of the regular display in current control rooms, as well as a panel used to indicate the occurrence of cyber-attacks or safety events and a panel used to guide the operator’s response to detected cyber-attacks.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗