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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

An Efficient and Effective Light Gas Gun Design for Millimeter-scale Hypervelocity Testing

This paper serves to document a design for a light gas gun that was used for 3 decades at NASA’s Langley Research Center. By adapting readily-available equipment and supplies, this apparatus was capable of accelerating projectiles at up to 9 kilometers per second (when new). The lack of a projectile-carrying sabot sacrifices some adaptability in projectile size, but results in a design that can be cleaned and cycled with far less labor input. Overall limitation on the projectile impact energies attainable effectively limit the applications to assessing the relatively thin shields employed for robotic spacecraft (less useful for those used for manned missions). The original gun has been decommissioned, but it is believed that this design has application for robotic spacecraft shield testing in the modern world, allowing cost-effective generation of larger sample sizes than with conventional sabot-based light gas guns.

Scott Hull↗
NASA NTRSDate not supplied

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗
NASA NTRSDate not supplied

Use NASA Earthdata in the Cloud

With the impending arrival of new, high-data-volume Earth observation missions, NASA’s ability to effectively ingest, process, and archive large amounts of data requires the most cost-effective, flexible, and scalable data-management architectures and technologies. To meet these demands, NASA's Earth Science Data Systems (ESDS) Program is implementing a strategic vision to develop and operate multiple components of NASA's Earth Observing System Data and Information System (EOSDIS) in a commercial cloud environment. As more earth observing data is moved into the cloud, NASA EOSDIS wants to share our reasoning for moving data into the commercial cloud, as well as demonstrate how end-users can take advantage of both data in the cloud and cloud-deployed services. This presentation explains the enterprise reasons for moving data into the cloud, specifically the scalability of cloud systems, the flexibility to pivot to the most optimal language/system/architecture, and the reduced redundancy of a common architecture. Then we primarily focus on the user-driven reasons for moving to the cloud. Equal access to high performance computing helps all parties, especially users that don't have access to their own on-premise computing infrastructure. Rapid deployment allows users to spin up their own systems without needing the extensive platform previously required for large scale development. Cost effectiveness allows users a wide breadth of computing options, from super computer ability to small scale development, which can help underserved communities. Finally we link to internal resources that users can utilize to begin their cloud based development journey without having to be an expert in the field.

Nicholas Doty↗
NASA NTRSDate not supplied

Total Variation Majorization Minimization (TV-MM) Approach to Radiometer Brightness Temperature Gridding and Reconstruction

This paper presents the implementation of an algorithm to enhance the image resolution of the Earth's surface brightness temperature (T B ) data measured by radiometers such as the one onboard of the Soil Moisture Active Passive (SMAP) mission. A key step in radiometer T B processing is the conversion of the swath-based calibrated antenna temperature (T A ) measurements to the Level 3 Earth-centered grid. The simplest algorithm to transform this data from swath to gridded format is called drop-in-the-bucket which simply averages surrounding noisy T A samples to form a T B value at the gridded location. This method reduces noise, however produces low resolution products. To obtain a higher resolution product, SMAP uses other techniques such the Backus-Gilbert (BG) algorithm, which is the conventional method used in microwave radiometry. Although this method performs the required interpolation, it is not effective in denoising and removing blurring effects due to antenna filtering of the radiometer image data. Our motivation for this development is to further improve the resolution through post-processing of the radiometer T B image, a highly cost-effective method of image enhancement. The approach adapted in this work is based on the minimization of the Total Variation (TV) regularized objective function that is used extensively in solving general ill-posed linear inverse problems in image processing. Since the TV-based objective function is convex but not everywhere differentiable, there exists many numerical algorithms that can estimate the solution and the one selected for this work is called Majorization- Minimization (MM). By applying this algorithm, simulation experiments were performed based on synthetic data from the Geophysical model as well as real SMAP data to demonstrate the effectiveness of the technique. Results were then compared against the BG method.

Wing Lee↗
NASA NTRSDate not supplied

Airspace Research and Development Portfolio Assessment of Urban Air Mobility using Knowledge Graph Data Science

National Aeronautics and Space Administration (NASA) is spearheading an innovative digital engineering approach to integrate, communicate, and facilitate the research of Urban Air Mobility (UAM) operations. The UAM vision is one in which advanced technologies and new operational procedures enable practical and cost-effective air transport as an integrated mode of movement of people and goods throughout metropolitan areas. To safely support UAM operations at scale in the National Airspace System (NAS), NASA’s Air Traffic Management-Exploration (ATM-X) project has been conducting research that evolves the UAM air traffic management system towards a highly automated and operationally flexible system of the future. The complexity of UAM airspace evolution to accommodate the increasing tempo of UAM operations over time is managed through the UAM airspace research roadmap, which is a system engineering approach to the R&D of complex system-of-systems, where system’s interdependencies make it nearly impossible to define requirements for individual elements of the system in isolation. These interdependencies form a knowledge graph (node-link network) with a highly complex structure far beyond the human user’s ability to extract insights for project management’s research portfolio assessment. This study applies advanced data analytics in knowledge graph to the UAM knowledge graph to facilitate the portfolio assessment.

ATM↗
NASA NTRSDate not supplied

Role of PHM in Autonomous Decision-Making: Aerospace applications

There is an increased need for onboard decision-making capabilities in cyber-physical systems be it in energy, automotive, aviation, space, or other industries as they aim for increased efficiency, resiliency, and mission assurance capabilities. Emerging next-gen technologies such as multi-rover planetary missions, distributed satellites, unmanned ground and aerial vehicle operations and smart grid systems rely on in-time risk assessment and autonomous decision-making. One critical piece of the autonomy puzzle is reliable prediction of system behavior under time-varying and potentially uncertain environmental conditions. Further, if agent states change during operation such as initiation of faults or degradation, reliable diagnostic tools need to be investigated. In this tutorial, we will revise approaches that integrates existing physics-based and data-driven models of agents interacting with probability models of the environment and component operation state. Role of existing PHM methodologies as they feed into decision-making under uncertainty will be studied. Balancing critical trade-offs between high-fidelity prognostic models, prediction time-horizons and the computational requirements for in-time cost-effective decision-making will be discussed through the implementation of surrogate models. Finally, the audience will be introduced to a real-time application of in-time trajectory planning of an unmanned aerial system (UAS) based on its PHM assessments under uncertain and varying wind conditions.

decision-making↗
NASA NTRS2024

South Africa Ecological Conservation: Identifying and Mapping Riparian Areas in South Africa with Earth Observations

Riparian zones are thin strips of wetland that occur along the edges of rivers, lakes, and other water bodies. They provide many ecosystem and societal benefits such as stream bank stabilization, flood control, and habitat stability, making these zones very important areas to preserve and protect. Recognizing the need to accurately map these ecosystems in a cost-effective way, we partnered with the South African National Biodiversity Institute (SANBI) and the Biodiversity Survey of the Cape(BioSCape) to develop a GI methodology using Esri's ArcGIS Pro and data from Landsat 9 Operational Land Imager-2, Sentinel-2 Multispectral Instrument, and the Shuttle Radar Topography Mission to identify potential riparian zones (PRZ) and observed riparian vegetation(ORV) in the Southern Cape and the North West Province of South Africa to estimate the actual riparian vegetation (ARV) within those areas. Potential riparian ecosystems were calculated by utilizing a Topographic Wetness Index (TWI) and a water feature layer, while observed riparian vegetation were calculated by overlaying a Normalized Difference Vegetation Index (NDVI) and TWI. Actual Riparian Vegetation is determined by the overlap of ORV with PRZ and is done with conditional statements; ORV within PRZ is ARV. This method significantly improved a current riparian land cover classification since it combined high resolution optical imagery and topographic data. We anticipate such maps will be used by conservationists and practitioners interested in riparian monitoring and management.

Remote Sensing↗
NASA NTRSDate not supplied

Atlas: Navigating NASA’s Knowledge Universe with AI-Powered Natural Language Queries

NASA has a vast archive of engineering guidelines, standards, and best practices collected over decades. This encompasses a breadth of topics from rocketry and engineering standards to risk management and space-related health issues. This wealth of information, while invaluable to NASA engineers, staff, and the public, is too extensive for any individual to fully comprehend. To address this challenge, we have developed Atlas, a tool within NASA's Mission Cloud Platform that enables users to query these diverse sources effectively. Atlas allows users to ask natural language questions and receive answers grounded in factual information from source documents. The tool provides responses with direct quotations and links to original documents, ensuring transparency and accuracy. It can address a wide range of queries, from specific technical details like safe distances for rocket launches from lightning to broader topics such as crew health requirements for long-duration space missions, corrosion protection in low Earth orbit, and NASA's agreements with various entities. In developing Atlas, we encountered and overcame several technical challenges. Large Language Models often struggle with consistently providing accurate information, especially for highly specialized topics. We implemented strategies to prevent hallucinations and ensure the reliability of responses, even for complex questions on topics ranging from NASA Mission Classes to intricate rocket science concepts. Additionally, we addressed the challenges of delivering quick responses while maintaining cost-effectiveness. Our presentation will detail the innovative approaches we employed to optimize performance and efficiency, making Atlas a powerful and practical tool for accessing NASA's extensive knowledge base.

Artificial Intelligence↗
NASA NTRS2025

Airports as Energy Nodes Activity Summary

Advanced aircraft concepts that use non-traditional aviation energy storage methods such as batteries or cryogenic hydrogen are in development and expected to enter regular service at airports worldwide within the next decade. The energy needs for these aircraft may quickly overwhelm the existing energy infrastructure at airports, particularly at smaller and more remote facilities. Without energy upgrades, these airports will not be able to host these advanced vehicles, but without the advanced vehicle traffic, these airports will not have the rationale or funding to build up their energy infrastructure. The Airports as Energy Nodes (ÆNodes) activity, a collaboration between the National Aeronautics and Space Administration (NASA) and the National Renewable Energy Laboratory (NREL), was executed to understand and model the energy needs that advanced aircraft concepts may levy on these smaller airports, determine cost-effective approaches to enhance the airport energy infrastructure, and demonstrate the enhanced resilience of these energy infrastructure upgrades to the airport and surrounding community via “digital twin” simulation at relevant energy and dynamic time scales. The ÆNodes team also investigated future reference aircraft designs and materials to enable cryogenic hydrogen storage for aircraft. The ÆNodes team conducted analysis at two U.S. airport partner sites — Winchester Regional Airport in Winchester, Virginia, and Tweed/New Haven Airport in New Haven, Connecticut. The goal of this partnership was to develop data and reference infrastructure designs that could accommodate advanced aircraft in the future at these airports while also enhancing the resiliency of the energy supply to the surrounding airport community, which could be used to capture funding to enable the infrastructure upgrades. Over the course of the study, a method was developed to estimate air traffic requiring advanced energy services over the course of a year using a mix of historical data and companion studies on advanced aircraft transportation networks. The study has concluded at NASA but continues at NREL, who will develop a final report discussing the energy infrastructure upgrades and digital twin results. Preliminary results indicate that unrestricted adoption of advanced battery-electric aircraft may double traffic at these airports and increase peak daily power usage by an order of magnitude, while increase electricity energy needs by a factor of two to four. The infrastructure upgrades necessary to accommodate these increased energy needs could be used to provide enhanced energy services to the airport community to offset the cost and increase the utility of the upgrades, which will be described in the NREL final report.

Airports↗
NASA NTRS2026

Remote Sensing-Driven Hydrodynamic Modeling in Data-Scarce Regions: Integrating ICESat-2, Sentinel-2, SWOT and Re-analysis Models for Coastal Monitoring

Hydrodynamic models in coastal and estuarine systems are typically constrained by sparse bathymetry, boundary, and validation data, especially in regions where field campaigns are costly or impractical. Here we develop and test a fully satellite-driven framework for hydrodynamic modeling in South Africa’s Langebaan Lagoon without using any local in situ measurements. Bathymetry is derived by training multispectral Sentinel-2 reflectance against ICESat-2 ATL24 photon-derived depths using an XGBoost model optimized with Bayesian search. The final satellite-derived bathymetry reproduces independent ATL24 points with RMSE = 0.45 m and R 2 = 0.97. This bathymetry was used in a depth-averaged Delft3D Flexible Mesh model driven at the open boundary by TPXO tidal harmonics and by ERA5 winds. We validate modeled water surface elevation against 16 SWOT low-rate (250 m, unsmoothed) passes in 2023. SWOT–model comparisons yield an overall RMSE of 0.11 m and R 2 = 0.61, with typical point differences <0.10 m (∼7% of the 1.5 m tidal range), and showed consistent spatial gradients in water level from the offshore boundary, through Saldanha Bay, and into the lagoon. At the offshore boundary, TPXO and SWOT sea surface heights agree closely (R 2 = 0.86). A simple phase adjustment of ∼26,min between TPXO and SWOT lowers the RMSE from 0.18,m to 0.11,m, showing that phase offset accounts for some of the discrepancy, with additional errors likely linked to non-tidal signals. Our results demonstrate that combining passive optical, photon-counting LiDAR, radar interferometry, and global tidal/atmospheric models enables robust, transferrable hydrodynamic modeling in data-scarce coastal systems, offering a cost-effective pathway for monitoring.

ICESat-2↗
NASA NTRS2026

Hybrid Modeling Study on Grain Evolution in the Metal Welding Process and Its Potential Lunar Application

Metal is most commonly used structural material in a wide range of spacecraft, and welding is the principal method for joining metal components into functional systems. However, conducting welding experiments under extreme environments—such as microgravity or vacuum conditions in space—is prohibitively expensive and experimentally challenging. To overcome these limitations, multi-physics computational welding models provide a cost-effective and versatile alternative. In this work, the authors have developed a coupled thermal (fluid) microstructure simulation framework to model metal welding under varying gravity conditions. The framework integrates a mixed-mode heat transfer formulation (conduction, convection, and radiation) with molten pool fluid dynamics, enabling accurate prediction of temperature fields and weld-pool geometry. A grain growth model is further incorporated to capture the spatial and temporal evolution of microstructure, including grain size distribution and morphological transitions during solidification. This approach provides detailed insight into molten pool evolution and grain-level microstructure development throughout the welding process. By explicitly parameterizing environmental conditions, the model supports extrapolation to off-Earth manufacturing scenarios such as welding on the lunar surface. Tantalum—chosen in this study due to its high melting point, oxidation resistance, and mechanical stability at elevated temperatures—serves as the material system for model demonstration. Beyond Tantalum, the integrated multi-physics framework offers broad applicability for predictive welding simulations of various structural and refractory metals or alloys used in extreme terrestrial or extraterrestrial environments.

kinetic Monte Carlo (SPPARKS)↗
NASA NTRSDate not supplied

Assembly and Integration Status of a High Fidelity Ground Test Bed for the Water Processor Assembly

The Water Recovery System (WRS) is a critical component of life support aboard the International Space Station (ISS) and will play an essential role in future missions beyond Low Earth Orbit (LEO). Its primary functional units – the Urine Processor Assembly (UPA), Brine Processor Assembly (BPA), and Water Processor Assembly (WPA) – must be evaluated for extended operation, dormancy resilience, material obsolescence, and reliability under exploration-driven constraints. Ground testing is vital for developing these technologies and generating statistically relevant reliability assessments, which requires extended runtime under integrated, Flight-like conditions. Currently, no high-fidelity, fully integrated WPA ground test bed exists to support these objectives. To address this gap, NASA is developing a WPA test bed at Marshall Space Flight Center (MSFC) that combines downgraded ISS flight hardware with functionally flight-like components in a cost-effective configuration while maintaining priority hardware investigations. This paper describes the current status of hardware assembly and integration, outlines key challenges such as simulating microgravity effects and mitigating obsolescence, and presents future test objectives including software development, reliability assessments, dormancy studies, and exploration-oriented upgrades.

Mary-Elizabeth Davis↗
NASA NTRS2026

Smart Process Planning for Automated Fiber Placement

Many industries, including aerospace, automotive, wind energy, maritime, and sporting goods, rely on strong, lightweight materials called composites. These materials are made by layering fibers, which can come in the form of narrow strips or wider sheets, and setting them in a polymer matrix. One of the most advanced ways to make these parts is through automated fiber placement, where a machine lays down the fibers in precise patterns. This method can create very efficient and strong designs, but it is complex, expensive, and often depends heavily on the experience of skilled engineers. Today, the design, manufacturing, and inspection stages of composite production are usually handled separately. This separation means that important information, such as how a part will be built or what defects might occur, is not always shared between stages. As a result, parts may not be as lightweight, strong, or defect-free as possible, and the process can take longer and cost more. This research develops a smart process planning system that connects design, manufacturing, and inspection into one continuous process. Built as software that works with existing tools, the system can automatically plan how the fibers are placed, predicting and reducing defects while improving both manufacturability and strength. The system optimizes not only individual layers but also how defects are distributed across all layers, preventing them from stacking up in ways that weaken the final part. It also uses inspection results from completed parts to improve future designs, creating a feedback loop where each stage informs the others. The system was tested by designing a composite panel using this new approach and comparing it to a panel made with state-of-the-art manual planning methods. The results showed that the system could intentionally control where defects appeared and increase the efficiency of the planning process. By unifying design, manufacturing, and inspection, this research shows a way to make advanced composite manufacturing more efficient, consistent, and cost-effective. This approach lowers the barrier to using automated fiber placement and opens the door for its wider adoption not only in aerospace but also in industries such as automotive, wind energy, maritime, and sporting goods, where strong and lightweight structures are essential.

Computer-Aided Process Planning↗
NASA NTRSDate not supplied

Assembly and Integration Status of a High Fidelity Ground Test Bed for the Water Processor Assembly

The Water Recovery System (WRS) is a critical component of life support aboard the International Space Station (ISS) and will play an essential role in future missions beyond Low Earth Orbit (LEO). Its primary functional units – the Urine Processor Assembly (UPA), Brine Processor Assembly (BPA), and Water Processor Assembly (WPA) – must be evaluated for extended operation, dormancy resilience, material obsolescence, and reliability under exploration-driven constraints. Ground testing is vital for developing these technologies and generating statistically relevant reliability assessments, which requires extended runtime under integrated, Flight-like conditions. Currently, no high-fidelity, fully integrated WPA ground test bed exists to support these objectives. To address this gap, NASA is developing a WPA test bed at Marshall Space Flight Center (MSFC) that combines downgraded ISS flight hardware with functionally flight-like components in a cost-effective configuration while maintaining priority hardware investigations. This paper describes the current status of hardware assembly and integration, outlines key challenges such as simulating microgravity effects and mitigating obsolescence, and presents future test objectives including software development, reliability assessments, dormancy studies, and exploration-oriented upgrades.

Water Processor Assembly↗
NASA NTRSDate not supplied

Characterization of Quicksounder ATMS at Instrument Level TVAC

QuickSounder (QS) is the pathfinder space mission for the next generation of NOAA LEO environmental satellites in the NEON program, follow-on to the JPSS program. It is a collaborative initiative between NASA and NOAA to verify rapid and cost-effective delivery of small Earth observation satellites. QuickSounder is focusing on mission elements other than science performance. In this context, an existing sensor, the refurbished ATMS EDU (Advanced Technology Microwave Sounder, Engineering Development Unit) was chosen as the QuickSounder payload. This poster discusses the performances of QuickSounder ATMS during thermal vacuum (TVAC) calibration to ensure that QS ATMS is characterized and calibrated in the same manner as JPSS ATMS units, even though science performance attributes are not the priority of this mission.

Saji Abraham↗
NASA NTRS2025

A Review of Direct Ink Writing of Polymer Derived Ceramics

With the growing demand for materials capable of withstanding extreme temperatures and pressures, ceramic components with exceptional corrosion resistance and reliable mechanical properties have experienced a significant surge in demand. However, traditional ceramic forming methods involve high-temperatures and energy-intensive processes that often struggle to produce complex parts or composites efficiently. Polymer-Derived Ceramics (PDCs) offer a transformative solution by using polymeric precursors that can be converted into a wide variety of silicon-based and non-silicon-based ceramics through heat treatment. The polymeric nature of PDC precursors enables the fabrication of geometrically intricate components using conventional polymer-forming techniques at significantly lower processing temperatures. Furthermore, PDCs are well-suited for additive manufacturing (AM), allowing the production of complex structural and functional components through cost-effective, low-temperature processes. By leveraging the diverse properties of PDC materials – each with unique advantages and limitations – manufacturers can optimise performance for specific applications. This review provides an overview of the types of PDCs developed to date and their broad range of applications. Specifically, it delves into the Direct Ink Writing (DIW) process, exploring its rheological requirements and the critical role of fillers in tailoring the rheological properties of polymeric precursors to meet the specific demands of DIW.

Victoria Bishop↗
NASA NTRS1995

Functions Performed by Mission Operations

We propose the series of three presentations described above for inclusion in your symposium. These presentations are similar to those we presented last November in plenary session at the Third International Symposium on Space Mission Operations and Ground Data Systems. Each presentation lasts 40 minutes and the presentations are designed to be given in order. The information in our presentations is extracted from a book of the same title scheduled for publication in August, 1995. Please note that since we have a book covering this topic, we will not prepare separate papers. An overview of each presentation is shown below.

Cost-Effective Mission↗