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Multi-Agent Swarm State of the Art Report

The Next-Generation Multi-Agent Swarm (NGS) Study conducted by NASA’s Ames Research Center for NASA’s Space Technology Mission Directorate (STMD) will develop a comprehensive understanding of emerging multi-agent swarm capabilities. The study aims to identify existing swarm capabilities and asses their potential for persistent lunar space situational awareness, surface monitoring, and distributed autonomy demonstrations. A key objective is to inform the design of a next-generation multi-agent swarm that can perform autonomous distributed remote sensing, position, navigation, and timing (PNT) services, automated deployment that leverages autonomy, edge computing, and interoperable networking to enable cooperative operations without the need for immediate human operation. This study will address specific shortfalls identified by STMD, including intelligent multi-agent constellations, autonomy, edge computation, position, navigation, and timing for small spacecraft, small spacecraft propulsion, and space situational awareness (1625, 1438, 1433, 1557, 1431, 1430, 1589). The NASA Ames Mission Design Center (MDC) will provide subject matter expertise to support systems engineering trades, while experts in autonomy and spacecraft swarms in NASA’s Intelligent Systems Division will lead the study and focus on identifying emerging next-generation swarm capabilities. The study objectives include: capturing the current state-of-the-art for multi-agent swarm capabilities, evaluating technologies and creating technology roadmaps, and developing at least one new technology demonstration mission concept. This initial NGS study report surveys the current state of the art in technology areas relevant for the next-generation multi-agent swarm design. Our primary focus is on surveying relevant deployed space systems1, supplemented with selective analysis of relevant proposed missions and technology developments that have yet to fly.

agent

Vapor Transport Crystal Growth of Mercury-Cadmium-Telluride in Microgravity

Two epitaxial growth experiments of Hg 1-x Cd x Te layers on (100) CdTe substrates in closed ampoules using HgI 2 as a transport agent have been performed during the USML-1 mission. The characterization results to date demonstrate a considerable improvement of the space-grown epitaxial layers relative to ground-control specimens in terms of morphology, compositional uniformity, and structural micro homogeneity. These results show the effects of microgravity and fluid dynamic disturbances on-ground on the deposition and growth processes. The continued analysis of this technologically important system is designed to further elucidate the observed crystallographic improvements and their relation to mass flow.

Heribert Wiedemeier

Hydrology Copilot: A Cloud-Native Ai System for Hydrological Data Analysis

The emergence of AI-driven Earth observation systems promises to broaden access to petabyte-scale geospatial data beyond domain specialists. However, translating this vision into operational scientific infrastructure requires addressing fundamental challenges in data virtualization, code transparency, and domain-specific reasoning. We present Hydrology Copilot, a cloud-native AI framework for natural-language-driven analysis of Earth observation data. To demonstrate operational capabilities at scale, we implement the system using NASA's North American Land Data Assimilation System version 3 (NLDAS-3), which provides surface meteorological forcing and land-surface model output across North and Central America at 1-km resolution, from which drought diagnostics are derived. The system integrates five core contributions: (1) scalable data virtualization using Kerchunk-based cloud optimized access, achieving a 1.5 to 4.6 times improvement in I/O latency across benchmark queries spanning regional single-day extractions (4.6 times speedup) to continental monthly aggregations (1.5 times speedup); (2) transparent code generation through Microsoft Azure AI Foundry agents that expose executable Python workflows for scientific verification; (3) persistent conversational memory enabling multi-turn analytical discourse across sessions; (4) intelligent query validation that enforces dataset boundaries and resolves ambiguous requests before execution; and (5) a multi-agent architecture coordinating query parsing, code generation, and visualization. We evaluate the system through drought-monitoring workflows, demonstrating reliable code generation, accurate results validated against reference computations and the operational U.S. Drought Monitor, and efficient operation across increasingly complex tasks. By bridging natural-language interfaces with rigorous hydrological analysis, Hydrology Copilot advances beyond proof-of-concept demonstrations to provide a deployable framework for operational Earth science applications.

Data virtualization

Developments in Fibrous Refractory Composite Insulation

The development of a new insulation material for heat-shielding advanced reusable entry vehicles is reported. The material, called fibrous refractory composite insulation, is a composite of two ceramic fibers with no additional additives to bond the fibers together; it also includes silicon carbide, an emmittance agent, to improve its optical properties at high temperature. One fiber is a drawn 11-micron-diameter aluminoborosilicate fiber, the other fiber is the silica fiber (microquartz) used in producing silica RSI (reusable surface insulation for the Space Shuttle), which is a blown fiber of 1-3 micron diameter and variable length. A composition containing 20%, with a thermal shock resistance of 1.8 that of all silica insulation, has been successfully produced in a pilot plant.

D B Leiser

Raman and Infrared Spectroscopy of Yttrium Aluminum Borate Glasses and Glass-ceramics

Raman spectra of glasses and glass-ceramics in the Y2O3-Al2O3-B2O3 system are reported. Glasses with B2O3 contents ranging from 40 to 60 mole percent were prepared by melting 20 g of the appropriate oxide or carbonate powders in alumina crucibles at 1400 C for 45 minutes. Subsequent heat treatments of the glasses at temperatures ranging from 600 to 800 C were performed in order to induce nucleation and crystallization. It was found that Na2CO3 added to the melt served as a nucleating agent and resulted in uniform bulk crystallization. The Raman spectra of the glasses are interpreted primarily in terms of vibrations of boron - oxygen structural groups. Comparison of the Raman spectra of the glass-ceramic samples with spectra of aluminate and borate crystalline materials reveal that these glasses crystallize primarily as yttrium aluminum borate, YAl3(BO3)4.

J Bradley

NASA POWER: Providing Analysis-Ready, Cloud-Optimized Data for AI /ML Training and Applications in Earth Science

As global demand for sustainable development grows, the integration of Earth Observation (EO) data into decision making frameworks has become a primary objective for the scientific community. The NASA Prediction of Worldwide Energy Resources (POWER) project serves as a bridge between NASA EO data and the specialized needs of the renewable energy, sustainable infrastructure and agroclimatology communities. In this poster presentation we will present an overview of POWER data products and services along with its use in diverse research to decision-making workflows. By providing over 40 years of high-resolution historical, hourly and daily solar and meteorological data, POWER transforms satellite observations and global model reanalysis into actionable, Analysis-Ready Dataset (ARD). Currently, the project delivers over 250 industry-friendly parameters to the users from different NASA datasets like CERES SYN1Deg, MERRA-2, and IMERG alongside downscaled CMIP6 climate model data, fulfilling over 16 million requests from 50,000 unique users monthly. To ensure data quality and traceability, these parameters are rigorously validated against the ground-based observations from the Baseline Surface Radiation Network (BSRN) and the Global Surface Summary of the Day (GSOD) – these results will be discussed in the presentation. A newly introduced web-based PaRameter Uncertainty ViEwer (PRUVE) tool will be presented that provides an online validation platform to the users that benchmarks satellite-based and assimilation data products against these surface measurements. To reduce technical barriers to data adoption, POWER data is accessible through RESTful APIs, ESRI ArcGIS Image Services, a web-based Data Access Viewer tool, allowing users to visualize, validate and apply the dataset. For efficient data delivery POWER data is cloud-optimized into Zarr datastore accessible through NASA managed Amazon S3 ensures high-performance allowing users to integrate EO directly into operational pipelines. These customized services will be presented. Use cases from application will be presented from the energy sector - such as for design of generation systems, performance monitoring of solar power plants, in infrastructure sector- optimizing building energy efficiency and thermal comfort, in agriculture – such as driving crop simulation and yield forecasting models to enable climate resilient farming. Furthermore, the shift toward machine learning (ML) in EO research that has positioned POWER as a key provider for training datasets which will be discussed. Use-cases will be presented to showcase how NASA data is enabling the development of predictive tools for climate variability and resource management. The poster will present POWER’s future plans including technology development to enhance data traceability and reproducibility and improving I/O performance to support the rapid integration of new EO products, ensuring that POWER remains a robust scalable backend for the evolving landscape of AI-driven Earth Science. Additionally, POWER is developing an AI Agent and an MCP-Server to enable industry AI-Agentic workflows.

Neha Khadka

Colors of Jupiter's large anticyclones and the interaction of a Tropical Red Oval with the Great Red Spot in 2008

The nature and mechanisms producing the chromophore agents that provide color to the upper clouds and hazes of the atmospheres of the giant planets are largely unknown. In recent times, the changes in red coloration that have occurred in large- and medium-scale Jovian anticyclones have been particularly interesting. In late June and early July 2008, a particularly color-intense red tropical oval interacted with the Great Red Spot (GRS) leading to the destruction of the red tropical oval and cloud dispersion. We present a detailed study of the tropical vortices, usually white but sometimes red, and a characterization of their color spectral signatures and dynamics. From the spectral reflectivity in methane bands we study their vertical cloud structure compared to that of the GRS and BA. Using two spectral indices we found a near-correlation between anticyclones cloud top altitudes and red color. We present detailed observations of the interaction of the red oval with the GRS and model simulations of the phenomena that allow us to constrain the relative vertical extent of the vortices. We conclude that the vertical cloud structure, vertical extent and dynamics of Jovian anticyclones are not the causes of their coloration. We propose that the red chromophore forms when background material (a compound or particles) is entrained by the vortex, transforming into red once inside the vortex due to internal conditions, exposure to ultraviolet radiation or to the mixing of two chemical compounds that react inside the vortex, confined by a potential vorticity ring barrier.

red color

Engineering the Interface: Advanced Surface Technologies for Lunar Dust Management and Equipment Longevity

Through the Artemis program, NASA intends to develop a sustainable human foothold on the Moon, ultimately paving the way for crewed exploration of Mars. The Moon's hostile environment poses numerous obstacles, including exposure to radiation, temperature extremes, micrometeoroid threats, and particularly the persistent problem of lunar dust. Lunar dust impacts nearly every aspect of surface operations through adhesion and abrasion mechanisms, with contamination from anthropogenic activities (landing, rovers) far outweighing natural phenomena. Multiple adhesion pathways contribute to surface contamination in the lunar environment, including van der Waals forces, electrostatic forces, chemical reaction, and magnetic forces from elemental iron deposits. Sharp asperities from micrometeoroid bombardment and atmospheric absence increase interaction potential and enable mechanical interlocking. Low cohesion between dust particles exacerbates these challenges, as minimal interaction potential between dust and nearby surfaces overcomes particle cohesion, causing contamination. Lunar dust adhesion mitigation technologies can be categorized as either active, requiring external energy, or passive, relying on intrinsic material properties. Ultrasonic and electrodynamic technologies have been developed to the highest technology readiness level for active approaches. Passive strategies primarily focus on surface chemistry and topography modifications. At NASA Langley Research Center, approaches include surface migration agents to reduce surface energy, topographical modification using laser ablation patterning, and tailored surface conductivity to reduce intrinsic adhesion force. Performance has been evaluated using custom-built ultrasonic and centrifuge instruments. Plume-surface interactions from lunar landers can propel micrometer-sized particles at velocities up to 1000 m s-1.8 These particles pose risks to landers, habitats and infrastructure, leading to erosion, degradation, and reduced component lifespan. A panel recovered from Surveyor III was determined to have been severely abraded because of lunar dust displaced from the Apollo 12 lunar module that landed 160 m away. The performance of metallic surfaces has been evaluated via high velocity single particle impact using the laser-induced project impact test (LIPIT) facility at the University of Utah. Peridynamics modeling, a form of continuum mechanics that uses a nonlocal approach enabling greater simulation capabilities of crack initiation and fracture, has also been utilized to gain greater insight into material response during impact events. Lunar dust contamination challenges extend to power generation systems and moving equipment. Cables, rotation stages, and other mechanisms may experience limited range of motion and reduced lifetime due to dust infiltration. NASA Langley Research Center has evaluated traditional aerospace alloys, softgoods, wear resistant ceramics, and several polymer and polymer composite materials. Test methods have included traditional techniques like Taber abrasion testing, as well as designed test configurations developed in the DUSTE (dust, ultraviolet radiation, and space thermal environmental) chamber that reproduce mechanism functions in operational environment. Beyond laboratory experiments, several flight experiments have been conducted. Materials were exposed to the low Earth orbit environment on the Materials International Space Station Experiment (MISSE) and to the lunar surface environment through the Aegis Aerospace Regolith Adherence Characterization (RAC) payload and the Honeybee Robotics PlanetVac payload. Determining lunar dust's impact on surface exploration and habitation requires comprehensive experimental and computational capabilities combined with lessons learned from initial lunar activities. Identifying the greatest environmental challenges and developing mitigation technologies provides the clearest path toward successfully, expeditiously, and efficaciously completing NASA's mission. This presentation will discuss ongoing efforts at NASA Langley Research Center and collaborator contributions to these critical objectives.

Surface Engineering