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NASA NTRS2026

Space Mission Options for Reconnaissance and Mitigation of Asteroid 2024 YR4

Near-Earth asteroid 2024 YR 4 was discovered on 2024-12-27 and its probability of Earth impact in December 2032 peaked at about 3% on 2025-02-18. Additional observations ruled out Earth impact by 2025-02-23. However, the probability of lunar impact in December 2032 then rose, reaching about 4% by the end of the apparition in May 2025. James Webb Space Telescope (JWST) observations on 2025-03-26 estimated the asteroid's diameter at 60 +/- 7 m. Studies of 2024 YR 4 's potential lunar impact effects suggest lunar ejecta could increase micrometeoroid debris flux in low Earth orbit up to 1000 times above background levels over just a few days, possibly threatening astronauts and spacecraft. In this work, we present options for space missions to 2024 YR 4 that could be utilized if lunar impact is confirmed. We cover flyby & rendezvous reconnaissance, deflection, and robust disruption of the asteroid. We examine both rapid-response and delayed launch options through 2032. We evaluate chemical and solar electric propulsion, various launch vehicles, optimized deep space maneuvers, and gravity assists. Re-tasking extant spacecraft and using built spacecraft not yet launched are also considered. The best reconnaissance mission options launch in late 2028, leaving only approximately three years for development at the time of this writing in August 2025. Deflection missions were assessed and appear impractical. However, kinetic robust disruption missions are available with launches between April 2030 and April 2032. Nuclear robust disruption missions are also available with launches between late 2029 and late 2031. Finally, even if lunar impact is ruled out there is significant potential utility in deploying a reconnaissance mission to characterize the asteroid.

Asteroid Disruption↗

NASA NTRS2004

Microphysics of Pyrocumulonimbus Clouds

The intense heat from forest fires can generate explosive deep convective cloud systems that inject pollutants to high altitudes. Both satellite and high-altitude aircraft measurements have documented cases in which these pyrocumulonimbus clouds inject large amounts of smoke well into the stratosphere (Fromm and Servranckx 2003; Jost et al. 2004). This smoke can remain in the stratosphere, be transported large distances, and affect lower stratospheric chemistry. In addition recent in situ measurements in pyrocumulus updrafts have shown that the high concentrations of smoke particles have significant impacts on cloud microphysical properties. Very high droplet number densities result in delayed precipitation and may enhance lightning (Andrew et al. 2004). Presumably, the smoke particles will also lead to changes in the properties of anvil cirrus produces by the deep convection, with resulting influences on cloud radiative forcing. In situ sampling near the tops of mature pyrocumulonimbus is difficult due to the high altitude and violence of the storms. In this study, we use large eddy simulations (LES) with size-resolved microphysics to elucidate physical processes in pyrocumulonimbus clouds.

Jensen, Eric↗

DOE OSTI2026

Developing a Deep Learning-Computer Vision Framework to Monitor Avian Interactions with Solar Energy Facility Infrastructure (Final Technical Report)

The project addressed an inability to monitor avian interactions with photovoltaic (PV) solar energy facilities necessary for understanding PV solar impacts on birds. In the project, machine-vision technology that continuously monitors avian activities at PV solar facilities was developed. The technology includes four machine-learning (ML) models, each of which accomplishes a specific task in detecting birds and classifying their activities in live or recorded videos—detecting and tracking moving objects, differentiating birds from other objects, detecting bird collisions with solar panels, and classifying non-collision bird activities around PV facilities. Major project outcomes include adoption by two of DOE SETO’s SolWEB projects, providing novel observational data on birds to promote co-location of PV solar development and habitat conservation, known as ecovoltaics.

14 SOLAR ENERGY↗

NASA NTRS1999

Impact of Track Structure Effects on Shielding and Dosimetry

Galactic cosmic rays (GCR) consisting of nuclei of all the known elements with kinetic energies extending from tens to millions of MeV pose a significant health hazard to future deep space operations. Even half of the radiation exposures expected in ISS will result from GCR components. The biological actions of these radiations are known to depend on the details of the energy deposition (not just linear energy transfer, LET, but the lateral dispersion of energy deposition about the particle track). Energy deposits in tissues are dominated by the transfer of tens to hundreds of eV to the tissue's atomic electrons. In the case of low LET radiations, the collisions are separated by large dimensions compared to the size of important biomolecular structures. If such events are also separated in time, then the radiation adds little to the background of radicals occurring from ordinary metabolic processes and causes little or no biological injury. Hence, dose rate is a strong determinant of the action of low LET exposures. The GCR exposures are dominated by ions of high charge and energy (HZE) characterized by many collisions with atomic electrons over biomolecular dimensions, resulting in high radical- density events associated with a few isolated ion paths through the cell and minimal dose rate dependence at ordinary exposure levels. The HZE energy deposit declines quickly laterally and merges with the background radical density in the track periphery for which the exact lateral distribution of the energy deposit is the determinant of the biological injury. Although little data exists on human exposures from HZE radiations, limited studies in mice and mammalian cell cultures allow evaluation of the effects of track structure on shield attenuation properties and evaluation of implications for dosimetry. The most complete mammalian cell HZE exposure data sets have been modeled including the C3H10T1/2 survival and transformation data of Yang et al., the V79 survival and mutation data of various groups, and the Harderian gland tumor data of Alpen et al. Model results for the Harderian gland tumor data in comparison with data from Alpen et al. The Harderian target cell initiation cross section compares closely with the transformation cross section found for the C3H10T1/2 cell transformation data of Yang et al. The most notable feature of the cross sections are the multivalued cross sections for a given LET which implies the corresponding relative biological effectiveness (RBE) is dependent not only on the LET but also the ion type. This fact is at variance with the latest ICRP recommended quality factor which is a defined function of only the LET.

Wilson, J. W.↗

NASA NTRSDate not supplied

Deep Space Habitat Primary Structure - A Comparison between Metallic, Inflatable, and Composite Materials

This paper presents a comprehensive trade study comparing metallic, inflatable, and composite primary structure materials for a Mars Transit Habitat module. The study evaluates the impact of these materials on the overall mass, outfitting, and mission complexity of the habitat. The results show that the composite module outperforms the other options in terms of minimum mass, being 33% lighter than the metallic configurations and 41% lighter than the inflatable option. The study highlights the potential of composite habitats for future space missions and emphasizes the need for further development and testing to increase the Technology Readiness Level.

Matthew T. Ziglar↗

NASA NTRS2024

Microstructural Evolution of the Civet Cat Norite (72255)

The ‘Civet Cat Norite’ is a ~ 2.5 cm clast within the Apollo impact melt breccia sample 72255 collected during Apollo 17 EVA 2 at Boulder 1. The norite is primarily composed of plagioclase and orthopyroxene with fine-scale exsolution lamellae of augite. The plagioclase and orthopyroxene (OPX) coexist with minor quartz and augitic clinopyroxene (CPX), and accessory apatite, baddeleyite, chromite, ilmenite, loveringite, merrillite, rutile and zircon. The major minerals range from 1 to 4 mm in size and show a cataclastic texture indicated by banding of the light and dark phases]. The chemical composition of the orthopyroxene, augitic exsolution lamellae, and exsolved oxides suggest the norite crystallized in the lower crust of the Moon (10 – 70 km depth) and was subsequently excavated by impact(s). Shock pressure estimates for the norite range from 15 – 35 GPa based on maskeleynite formation within the plagioclase, kink banding in pyroxenes, and granular recrystallization in the accessory phosphates. Previous Rb-Sr and 40 Ar/ 39 Ar analyses recalculated with modern decay constants yield relatively young ages of 4.16 ± 0.05 Ga and 3.99 ± 0.03 Ga, respectively. However, recent U-Pb analyses of some zircon grains from within the Civet Cat yield an age of 4.45 ± 0.03 Ga. While this is the oldest age for any rock recovered from the Moon, the full age spread of zircon from the Civet Cat range from ca. 4.46 to 4.02 Ga, indicating variable Pb-loss and complicating interpretation of the primary age. Recent atom probe analyses indicate minimal Pb mobilization within the oldest zircon grain from Civet Cat, supporting the interpretation that these ancient zircon ages reflect the age of the norite, rather than an apparent antiquity caused by reverse discordance. To investigate the potential antiquity and deep crustal origin of the Civet Cat norite, we have undertaken high resolution microstructural analyses of the major, minor, and accessory minerals to characterize the primary igneous textures and secondary overprinting by impact and metamorphism. The employed analytical techniques include scanning electron microscope-based electron backscatter diffraction (EBSD) analyses, electron probe microanalyzer (EPMA) chemical analyses, and transmission electron microscopy (TEM) of pyroxene, plagioclase, quartz, zircon, and phosphates.

T M Erickson↗

DOE OSTI2026

Space Mission Options for Reconnaissance and Mitigation of Asteroid 2024 YR4

Near-Earth asteroid 2024 YR 4 was discovered on 2024-12-27 and its probability of Earth impact in December 2032 peaked at ~3% on 2025-02-18. Additional observations ruled out Earth impact by 2025-02-23. However, the probability of lunar impact in December 2032 then rose, reaching ~4% by the end of the apparition in May 2025. James Webb Space Telescope (JWST) observations on 2025-03-26 estimated the asteroid’s diameter at 60 ± 7 m. Studies of 2024 YR 4 ’s potential lunar impact effects suggest lunar ejecta could increase micrometeoroid debris flux in low Earth orbit up to 1000 times above background levels over just a few days, possibly threatening astronauts and spacecraft. In this work, we present options for space missions to 2024 YR 4 that could be utilized if lunar impact is confirmed. Here, we cover flyby & rendezvous reconnaissance, deflection, and robust disruption of the asteroid. We examine both rapid-response and delayed launch options through 2032. We evaluate chemical and solar electric propulsion, various launch vehicles, optimized deep space maneuvers, and gravity assists. Re-tasking extant spacecraft and using built spacecraft not yet launched are also considered. The best reconnaissance mission options launch in late 2028, leaving only approximately three years for development at the time of this writing in August 2025. Deflection missions were assessed and appear impractical. However, kinetic robust disruption missions are available with launches between April 2030 and April 2032. Nuclear robust disruption missions are also available with launches between late 2029 and late 2031. Finally, even if lunar impact is ruled out there is significant potential utility in deploying a reconnaissance mission to characterize the asteroid.

Asteroid deflection↗

DOE OSTI2025

Revealing the Moon's Taurus‐Littrow Landslide via Integrated Analysis of Pristine Apollo 17 Soil Core 73001/2

The “light mantle” deposit at the base of South Massif in the Moon's Taurus‐Littrow Valley was a primary science target for the Apollo 17 exploration. The possibility that it was a landslide triggered by ejecta from Tycho Crater is critical for establishing the age of Tycho and constraining recent lunar impact chronology; however, the mechanism of emplacement of the deposit has recently been questioned. The newly opened 73001/73002 double drive tube from Station 3 sampled 70.6 cm deep into the regolith and represents the first stratigraphic section of an extraterrestrial landslide deposit returned to Earth. Here we provide an overview of the stratigraphy of the 73001/73002 core based on top to bottom variations revealed by coordinated laboratory analyses and explore constraints on the emplacement of the light mantle deposit. Briefly, the upper ∼10 cm of 73002 contains a disturbed zone from space weathering and emplacement of ejecta from a nearby crater that excavated and ejected basaltic material. Below 10 cm is a nearly uniform unit of immature regolith. These data support a single event for the emplacement of the deposit at this location, followed by weathering and mixing of materials from nearby crater ejecta in the upper 10 cm. Slight variations in chemistry and clast components may reflect the relative stratigraphy of the South Massif slope, with material toward the bottom of 73001 originating from lower slopes and material from higher up in the core representing regolith from higher up the South Massif slopes.

58 GEOSCIENCES↗

DOE OSTI2026

Understanding Biases in Simulated Cloud Radiative Effects in E3SMv3

This study systematically investigates biases in cloud radiative effects (CREs) within the recently released Energy Exascale Earth System Model version 3 (E3SMv3). Compared to its previous version (E3SMv2), E3SMv3 shows excessively strong shortwave CRE over tropical and subtropical oceans, the Southern Ocean, and the Northern Hemisphere storm tracks, which is primarily caused by an overestimation of optically intermediate low clouds. The model also displays excessive longwave CRE over the Maritime Continent and other tropical deep convection regions, resulting from an overestimation of optically thick high clouds. Implementing the Predicted Particle Properties (P3) scheme for stratiform clouds played the most significant role in these cloud changes. In addition, using a double-moment scheme for convective clouds contributed to the increase in intermediate low clouds and optically thick clouds in tropical deep convection regions. Error metrics for total cloud amount (E TCA ), cloud properties (E ctp-τ ), and cloud properties weighted by their SW and LW radiative impacts (E SW and E LW ) indicate that E3SMv3's ability to reproduce observed cloud radiative effect of low, middle, and high clouds has not been improved compared to E3SMv2. Nevertheless, the performance of E3SMv3 remains well within the spread of CMIP6 models, with E SW and E LW values smaller than those in most CMIP6 models. This study underscores the importance of integrating diverse satellite observations for robust cloud evaluation and using cloud-radiation relationships as consistency check for model errors. It suggests that further model developments focus on improving cloud microphysics and their interactions with radiation.

Environmental sciences↗

DOE OSTI2024

Enhancing Electron Microscopy Image Classification Using Data Augmentation

Manual labeling for machine learning tasks such as image classification is tedious and labor-intensive; as a result, scientific datasets suitable for deep learning applications are scarce and limited. While data augmentation techniques have shown promise for extending image datasets, very little work has been done to understand the impact of combining multiple augmentation methods sequentially or the limits of their effectiveness when combined. Our work addresses this gap by examining how standard and combinatorial data augmentation affects the performance of machine learning models when trained on small datasets for label classification tasks. For our analysis, we generate single, double and quadruple-augmented datasets for a microscopy image classification task using six standard augmentation methods, and compare the resultant improvements observed in binary classification accuracy with three standard image classification models (DenseNet169, MobileNetV2, ResNet101V2). Our experiments show a non-monotonic relationship between the number of simultaneous augmentation methods and classification accuracy, indicating that there is a trade-off between the degree of augmentation and the model performance. These findings suggest that the optimal number of augmentation methods will vary by domain and use case. We also find that the order in which augmentation methods are applied to a limited dataset matters when combining augmentation schemes, with our use case showing performance differences up to 2.6% when the augmentation order is reversed for double-augmented datasets. Our work offers insights to the limits of data augmentation when working on image classification tasks with limited datasets.

Welsman, Jordan A↗

DOE OSTI2026

Building MCP-native hierarchical AI scientist ecosystems: a perspective on scaling multi-agent scientific discovery

Large language models (LLMs) are evolving from chatbots with limited tool-using capabilities to agentic AI systems that can perform deep research, assist in proposing hypotheses, help design experiments, automate data analysis, and draft scientific reports. However, there are currently two bottlenecks limiting LLMs' real-world impact on the broader scientific research community beyond academic demonstrations: lack of interoperability (repetitive manual tool-integration is required across scenarios) and the need for scalable coordination (unstructured communication and memory become brittle as the number of agents grows). In this Perspective, we argue that the next phase of agentic scientific discovery requires the development of an ecosystem of protocol-native agents and tools organized through hierarchies inspired by human society, beyond the current paradigm of a single monolithic “AI scientist”. We use Model Context Protocol (MCP) as a concrete example of an emerging interoperability layer for scientific tool and context exchange, and we propose three complementary pathways to increase the scaling capabilities of an MCP-native scientific ecosystem by addressing the composability issues: (1) MCP servers for high-value scientific tools maintained by domain experts, (2) automated transformation of existing code repositories into MCP services, and (3) autonomous invention and evolution of new agents and workflows. Finally, we provide a practical roadmap for scaling AI-driven scientific discovery by expanding tool supply and coordination in MCP-native scientific ecosystems.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2016

Nuclear Thermal Rocket - Arc Jet Integrated System Model

In the post-shuttle era, space exploration is moving into a new regime. Commercial space flight is in development and is planned to take on much of the low earth orbit space flight missions. With the development of a heavy lift launch vehicle, the Space Launch, System, NASA has become focused on deep space exploration. Exploration into deep space has traditionally been done with robotic probes. More ambitious missions such as manned missions to asteroids and Mars will require significant technology development. Propulsion system performance is tied to the achievability of these missions and the requirements of other developing technologies that will be required. Nuclear thermal propulsion offers a significant improvement over chemical propulsion while still achieving high levels of thrust. Opportunities exist; however, to build upon what would be considered a standard nuclear thermal engine to attain improved performance, thus further enabling deep space missions. This paper discuss the modeling of a nuclear thermal system integrated with an arc jet to further augment performance. The performance predictions and systems impacts are discussed.

Taylor, Brian D.↗

NASA NTRS2019

Spaceflight Hazards of Escape-Velocity-Domain Impact Ejecta in the CR3BP

As a consequence of planned/proposed human lunar activity, the long-term effects of lunar debris and ejecta resulting from large-body (> 1000 kg) impacts on the lunar surface is investigated. The Escape-Velocity-Domain (EVD) ejecta behavior is characterized in terms of destination, duration in lunar orbit, and total displaced mass. Likewise, the amount of mass sent into geosynchronous orbit is also characterized and assessed as a function of impact location in terms of Sun-Earth-Moon angle, lunar latitude and longitude, and impact angle. Finally, a threat analysis is performed on critical assets in Earth and Lunar orbit such as the I.S.S., geosynchronous satellites, prospective lunar base, and the Deep Space Gateway now under construction.

Wittal, M. M.↗

NASA NTRS2020

Saharan Dust Aerosols Change Deep Convective Cloud Prevalence, Possibly by Inhibiting Marine New Particle Formation

Deep convective clouds (DCCs) are important to global climate, atmospheric chemistry, and precipitation. Dust, a dominant aerosol type over the tropical North Atlantic, has potentially large microphysical impacts on DCCs over this region. However, dust effects are difficult to identify, being confounded by co-varying meteorology and other factors. Here, a method is developed to quantify DCC responses to dust and other aerosols at large spatial and temporal scales despite these uncertainties. Over 7 million tropical North Atlantic cloud, aerosol, and meteorological profiles from CloudSat satellite data and MERRA-2 reanalysis products are used to stratify cloud observations into meteorological regimes, objectively select a priori assumptions, and iteratively test uncertainty sensitivity. Dust is robustly associated with a 54% increase in DCC prevalence. However, marine aerosol proxy concentrations are five times more predictive of dust-associated increases in DCC prevalence than the dust itself, or any other aerosol or meteorological factor. Marine aerosols are also the most predictive factor for the even larger increases in DCC prevalence (61-87%) associated with enhanced dimethyl sulfide and combustion and sulfate aerosols. Dust-associated increases in DCC prevalence are smaller at high dust concentrations than at low concentrations. These observations suggest that not only is dust a comparatively ineffective CCN source, but it may also act as a condensation/coagulation sink for chemical precursors to CCN, reducing total CCN availability over large spatial scales by inhibiting new particle formation from marine emissions. These observations represent the first time this rocess, previously predicted by models, is supported and quantified by measurements.

Aerosol-cloud interactions↗

NASA NTRSDate not supplied

Early Radiometric Performance of Landsat-9 Thermal Infrared Sensor

Landsat-9, launched on September 27, 2021, carries the Thermal Infrared Sensor (TIRS). The Landsat-9 TIRS is a close copy of the Landsat-8 TIRS instrument; it is a two spectral-band, pushbroom sensor with three Sensor Chip Assemblies (SCAs) that cover the 15-degree field-of-view. The primary radiometric change between the instruments is the addition of baffling in the Landsat-9 TIRS telescope to mitigate the stray light issue that has impacted the radiometric quality of Landsat-8 TIRS. The on-orbit radiometric performance is monitored using the on-board variable temperature blackbody and views of deep space. Maneuvers to look at and around the moon have provided an assessment of the stray light. The absolute calibration is monitored by vicarious calibration techniques by teams at NASA/Jet Propulsion Lab and the Rochester Institute of Technology. Landsat-9 completed a three-month commissioning phase in January 2022 and has been operational since February 2022. The instrument has demonstrated excellent radiometric performance, as assessed from the on-orbit measurements. The TIRS instrument is radiometrically stable to 0.1% within a power cycle, and has noise levels below 0.1K. The lunar scans and the vicarious calibration data provide evidence that the stray light has been effectively mitigated.

Landsat-9↗

NASA NTRSDate not supplied

Quantifying Medical Risk on a Long Duration Lunar Mission: A Demonstration of NASA’s IMPACT Tradespace Analysis Tool

Background NASA’s human exploration spaceflight missions to the Moon and Mars present unprecedented challenges for in-mission medical care. The distance from Earth will mean increased mission durations, communication delays, limited to no resupply opportunities, and constraints on the medical evacuation of astronauts. Mass, volume, power, and data will be limited while higher demands will be placed on the crew to manage medical care. NASA’s Moon to Mars exploration strategy lays out increasingly complex Artemis missions both in terms of duration and operations. In these more challenging deep space missions, it is important to quantitatively estimate the human medical risk to inform a traditional heuristic approach to medical risk. Prior tools have been developed for missions in low Earth orbit, but a new tool is required to plan for future exploration missions. Methods IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) is a risk assessment tool developed by NASA to advance exploration mission medical system design by quantitatively estimating mission medical risk. IMPACT v1.0 includes a novel evidence library baselined to exploration environments; an expanded list of 119 medical conditions; the addition of medical resources; and the ability for rapid and iterative analysis. Medical system risk estimates include loss of crew life, consideration of the need for return to definitive care (medical evacuation), and an estimate of crew time affected due to medical conditions. A notional long duration lunar orbit and lunar surface design reference mission (DRM) was chosen with a 4-astronaut crew to represent a sustained exploration Artemis mission. Results/Discussion Overall, IMPACT successfully quantified medical risk and derived an optimized medical system to support crew on a long duration lunar mission. In this DRM, the calculated loss of crew life from a medical event was 0.008 events per mission, risk of potential need for evacuation was 0.30 events per mission, and cumulative crew time affected by medical conditions was 103 days. The medical conditions that most contributed to overall medical risk were decompression sickness, trauma conditions, and respiratory failure. The conditions that had the largest effects on crew performance included musculoskeletal injuries and lunar dust exposure. The IMPACT-generated medical system included resources that target the most common and highest risk conditions. This systematic analysis demonstrates the value of the IMPACT tool in medical system design for human exploration spaceflight missions.

Missions to Mars↗

NASA NTRS2024

Quantifying Medical Risk on a Long Duration Lunar Mission: A Demonstration of NASA’s IMPACT Tradespace Analysis Tool

Missions to Mars↗

DOE OSTI2025

Environmental Thermodynamic Effects on Future Changes of Mesoscale Convective Systems and Isolated Deep Convection Over the US: A Case Study

Mesoscale convective systems (MCSs) and isolated deep convection (IDC) significantly influence local weather conditions and the hydrological cycle across the United States. Their future changes under warming is critical to the society. However, the exact impacts of thermodynamic environmental changes on them are difficult to resolve using climate model simulations which integrate both dynamic and thermodynamic factors. This study explores a theoretical modeling approach to isolate environmental thermodynamic effects on their future changes through a case study. For a 50-day period during the 2020 summer, a pair of convection-permitting model simulations indicate contrasting changes in MCSs and IDC between inland and coastal regions under pseudo global warming. Driven by the thermodynamic environments of these simulations, a single-column parcel model indicates a decrease in the frequency of IDC occurrences, along with increases in duration and precipitation amount under warming, attributable to rising most unstable convective available potential energy (MUCAPE), convective inhibition (MUCIN), and precipitable water (PW). A multi-column parcel model reveals contrasting changes in the frequency and mean area of MCSs between inland and coastal regions, underscoring the increase in mean MUCIN over inland regions and increases in mean MUCAPE and PW over coastal regions. The increase in mean MCS area over inland regions is linked to the interplay between accelerated gust fronts and enhanced subsidence strength, which is further traced to the unchanged mean MUCIN but increased mean MUCAPE in large-scale environments. In conclusion, these case study results suggest a major role of thermodynamic environmental changes in controlling characteristics of MCSs and IDC under warming.

Mesoscale convective system↗