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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 NTRS2012

Space Weather Forecasting at NASA GSFC Space Weather Research Center

The NASA GSFC Space Weather Research Center (http://swrc.gsfc.nasa.gov) is committed to providing research forecasts and notifications to address NASA's space weather needs - in addition to its critical role in space weather education. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, weekly summaries and reports, and most recently - video casts. In this presentation, we will focus on how near real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), enable space weather forecasting and quality space weather products provided by our Center. A few critical near real-time data streams for space weather forecasting will be identified and discussed.

CMEs↗
NASA NTRS1988

The need for a comprehensive expert system development methodology

In a traditional software development environment, the introduction of standardized approaches has led to higher quality, maintainable products on the technical side and greater visibility into the status of the effort on the management side. This study examined expert system development to determine whether it differed enough from traditional systems to warrant a reevaluation of current software development methodologies. Its purpose was to identify areas of similarity with traditional software development and areas requiring tailoring to the unique needs of expert systems. A second purpose was to determine whether existing expert system development methodologies meet the needs of expert system development, management, and maintenance personnel. The study consisted of a literature search and personal interviews. It was determined that existing methodologies and approaches to developing expert systems are not comprehensive nor are they easily applied, especially to cradle to grave system development. As a result, requirements were derived for an expert system development methodology and an initial annotated outline derived for such a methodology.

Baumert, John↗
NASA NTRS2004

Gardosian Patterns in Tribology

The following paper is a memorial retrospective on selected research of Dr. Michael N. Gardos. Dr. Gardos spent his professional career engaged in tribological research which often extended the scientific boundaries of the field. Several of the concepts he put forth into the tribology community were initially met with grave skepticism but over time his views have been largely embraced but not widely acknowledged. His approach to new research topics was often characterized by these qualities: 1) pioneering points of view, 2) the use of the model experiment, and 3) the presence of multiple research agendas for each single experiment. I have chosen to name his research approach as "Gardosian Patterns" in honor of his contributions to Tribology. Three specific examples of these patterns will be reviewed. One is the concept of atomic level tailoring of materials to control macroscopic properties. A second is the use of a model ball polishing experiment to identify high fracture toughness ceramics for use in rolling element bearings. A third Gardosian Pattern example is his pioneering work with the tribology of diamond and diamond films in which he proposed controlling friction via surface bond tailoring. In these examples, Gardos utilized conventional research tools in unconventional ways and, at times, even developed new tools which have become part of the mainstream. His remarkable career has left a positive and lasting mark on Tribology.

DellaCorte, Christopher↗
NASA NTRS2007

Feasibility of Turing-Style Tests for Autonomous Aerial Vehicle "Intelligence"

A new approach is suggested to define and evaluate key metrics as to autonomous aerial vehicle performance. This approach entails the conceptual definition of a "Turing Test" for UAVs. Such a "UAV Turing test" would be conducted by means of mission simulations and/or tailored flight demonstrations of vehicles under the guidance of their autonomous system software. These autonomous vehicle mission simulations and flight demonstrations would also have to be benchmarked against missions "flown" with pilots/human-operators in the loop. In turn, scoring criteria for such testing could be based upon both quantitative mission success metrics (unique to each mission) and by turning to analog "handling quality" metrics similar to the well-known Cooper-Harper pilot ratings used for manned aircraft. Autonomous aerial vehicles would be considered to have successfully passed this "UAV Turing Test" if the aggregate mission success metrics and handling qualities for the autonomous aerial vehicle matched or exceeded the equivalent metrics for missions conducted with pilots/human-operators in the loop. Alternatively, an independent, knowledgeable observer could provide the "UAV Turing Test" ratings of whether a vehicle is autonomous or "piloted." This observer ideally would, in the more sophisticated mission simulations, also have the enhanced capability of being able to override the scripted mission scenario and instigate failure modes and change of flight profile/plans. If a majority of mission tasks are rated as "piloted" by the observer, when in reality the vehicle/simulation is fully- or semi- autonomously controlled, then the vehicle/simulation "passes" the "UAV Turing Test." In this regards, this second "UAV Turing Test" approach is more consistent with Turing s original "imitation game" proposal. The overall feasibility, and important considerations and limitations, of such an approach for judging/evaluating autonomous aerial vehicle "intelligence" will be discussed from a theoretical perspective.

Young, Larry A.↗
NASA NTRS2011

Holographic Weapons Sight as Crew Optical Alignment Sight

Crew Optical Alignment Sights (COAS) are used by spacecraft pilots to provide a visual reference to a target spacecraft for lateral relative position during rendezvous and docking operations. NASA s Orion vehicle, which is currently under development, has not included a COAS in favor of automated sensors, but the crew office has requested such a device be added for situational awareness and contingency support. The current Space Shuttle COAS was adopted from Apollo heritage, weighs several pounds, and is no longer available for procurement which would make re-use difficult. In response, a study was conducted to examine the possibility of converting a commercially available weapons sight to a COAS for the Orion spacecraft. The device used in this study was the XPS series Holographic Weapon Sight (HWS) procured from L-3 EOTech. This device was selected because the targeting reticule can subtend several degrees, and display a graphic pattern tailored to rendezvous and docking operations. Evaluations of the COAS were performed in both the Orion low-fidelity mockup and rendezvous simulations in the Reconfigurable Operational Cockpit (ROC) by crewmembers, rendezvous engineering experts, and flight controllers at Johnson Space Center. These evaluations determined that this unit s size and mounting options can support proper operation and that the reticule visual qualities are as good as or better than the current Space Shuttle COAS. The results positively indicate that the device could be used as a functional COAS and supports a low-cost technology conversion solution.

Merancy, Nujoud↗
NASA NTRS2017

Scenario Development Process at the Vertical Motion Simulator

There has been a significant effort within the simulation community to standardize many aspects of flight simulation. More recently, an effort has begun to develop a formal scenario definition language for aviation. A working group within the AIAA Modeling and Simulation Technical Committee has been created to develop a standard aviation scenario definition language, though much of the initial effort has been tailored to training simulators. Research and development (R&D) simulators, like the Vertical Motion Simulator (VMS), and training simulators have different missions and thus have different scenario requirements. The purpose of this paper is to highlight some of the unique tasks and scenario elements used at the VMS so they may be captured by scenario standardization efforts. The VMS most often performs handling qualities studies and transfer of training studies. Three representative handling qualities simulation studies and two transfer of training simulation studies are described in this paper. Unique scenario elements discussed in this paper included special out-the-window (OTW) targets and environmental conditions, motion system parameters, active inceptor parameters, and configurable vehicle math model parameters.

Vertical Motion Simulator↗
NASA NTRS2006

Integrated Modeling and Simulation Verification, Validation, and Accreditation Strategy for Exploration Systems Mission Directorate

Models and simulations (M&S) are critical resources in the exploration of space. They support program management, systems engineering, integration, analysis, test, and operations and provide critical information and data supporting key analyses and decisions (technical, cost and schedule). Consequently, there is a clear need to establish a solid understanding of M&S strengths and weaknesses, and the bounds within which they can credibly support decision-making. Their usage requires the implementation of a rigorous approach to verification, validation and accreditation (W&A) and establishment of formal process and practices associated with their application. To ensure decision-making is suitably supported by information (data, models, test beds) from activities (studies, exercises) from M&S applications that are understood and characterized, ESMD is establishing formal, tailored W&A processes and practices. In addition, to ensure the successful application of M&S within ESMD, a formal process for the certification of analysts that use M&S is being implemented. This presentation will highlight NASA's Exploration Systems Mission Directorate (ESMD) management approach for M&S W&A to ensure decision-makers receive timely information on the model's fidelity, credibility, and quality.

Hale, Joseph P.↗
DOE OSTI2026

Leveraging large language models to address data scarcity in machine learning for graphene synthesis

Machine learning in experimental materials science faces significant challenges due to the scarcity of data, which are costly and time-consuming to generate, particularly when relying on in-house experiments. Literature data mining offers a potential solution but introduces issues like mixed data quality, inconsistent formats, and non-uniform reporting of synthesis parameters, resulting in partially missing and heterogeneous features across the dataset. Here, we propose data imputation and feature engineering methods that employ pre-trained large language models (LLMs) to enhance machine learning performance on scarce, heterogeneous datasets, demonstrated on graphene CVD synthesis data and the ML-HydPARK hydrogen storage dataset. GPT models perform data imputation via tailored prompting and semantic normalization of inconsistently reported features through embeddings, for example, to harmonize the complex nomenclature of CVD substrates. Beyond yielding more diverse and richer feature representations than traditional methods such as K-nearest neighbors (KNN) and Multivariate Imputation by Chained Equations (MICE), LLM-based data imputation is evaluated against dataset characteristics and prompting strategies. We vary the level of autonomy granted to the LLM, from generic prompting that leverages pre-trained knowledge for autonomous data generation to data-informed prompting that constrains outputs using target-specific information, and demonstrate which level of autonomy yields superior imputation performance across datasets and feature types. The proposed data engineering methods markedly improve downstream performance; for example, in graphene layer number classification using a support vector machine (SVM), binary accuracy increases from 39% to 65% and ternary accuracy from 52% to 72%. Fine-tuning experiments on both datasets show that combining our proposed LLM-based data imputation and feature encoding methods with numerical machine learning predictors outperforms standalone fine-tuned LLM predictors in data-scarce settings. The proposed strategies emphasize data enhancement techniques rather than refining learning architectures or regularizing loss functions, offering a broadly applicable framework for improving machine learning performance on scarce, inhomogeneous datasets.

Chemical vapor deposition↗
NASA NTRSDate not supplied

Enhancing Air Quality Applications in the Hindu Kush-Himalayan Region Using Satellite, Model, and Machine Learning Techniques

Air pollution in the Hindu Kush Himalayan (HKH) region of South Asia is a severe issue, as increases in emissions over the past two decades have degraded air quality (AQ) across the region, which poses major threats to human health, the ecosystem, climate, and agriculture. A diversity of anthropogenic and natural emission sources including transportation, power plants, industries, open biomass burning of crop residue, forest fires, cooking and heating fires, and dust storms contribute to unhealthy AQ and transboundary pollution issues in the region. Further complicating matters is the importance of meteorology and terrain on AQ, especially in the Kathmandu Valley where extreme haze episodes frequently develop from the atmospherically stable weather conditions during the winter monsoon. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with machine learning techniques to develop a comprehensive toolkit for enhancing AQ monitoring and forecasting in HKH. The toolkit incorporates new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager (AMI), which provide unprecedented resolution on aerosols and trace gases, including nitrogen dioxide (NO 2 ), formaldehyde (CH2O), sulfur dioxide (SO 2 ), carbon monoxide (CO), and ozone (O 3 ), and aerosol optical depth (AOD). Value-added products [e.g., Particulate matter with diameters less than 2.5 micrometers (PM2.5)] are developed from the suite of satellite observations to further improve AQ monitoring capabilities in the region. The satellite products are also used to assimilate a high-resolution chemical transport model tailored for the HKH region, which is providing daily, 54-hour AQ forecasts with horizontal grid spacings of 12- and 4-km. This presentation will provide an overview of the suite of satellite- and model-based products in the AQ toolkit and application and performance of the toolkit for AQ monitoring and forecasting in HKH.

Air Quality↗
DOE OSTI2025

Preserving the Josephson Coupling of Twisted Cuprate Junctions via Tailored Silicon Nitride Circuits Boards

Controlled fabrication of twisted van der Waals heterostructures is essential to unlock the full potential of moiré materials. However, achieving reproducibility remains a major challenge, particularly for air-sensitive materials such as Bi 2 Sr 2 CaCu 2 O 8 + δ (BSCCO), where it is crucial to preserve the intrinsic and delicate superconducting properties of the interface throughout the entire fabrication process. Here, a dry, inert and cryogenic assembly method is presented that combines silicon nitride nanomembranes (NMBs) with pre-patterned electrodes and the cryogenic stacking technique (CST) to fabricate high-quality twisted BSCCO Josephson junctions (JJs). This protocol prevents thermal and chemical degradation during both interface formation and electrical contact integration. It is also found that asymmetric membrane designs, such as a double cantilever, effectively suppress vibration-induced disorder due to wire bonding, resulting in sharp and hysteretic current–voltage characteristics. The junctions exhibit a twist-angle-dependent Josephson coupling with magnitudes comparable to the highest-performing devices reported to date, but achieved through a straightforward and versatile contact method, offering a scalable and adaptable platform for future applications. These findings highlight the importance of both interface and contact engineering in addressing reproducibility in superconducting van der Waals heterostructures.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2009

Review of the Constellation Level II Safety, Reliability, and Quality Assurance (SR&QA) Requirements Documents during Participation in the Constellation Level II SR&QA Forum

At the request of the Exploration Systems Mission Directorate (ESMD) and the Constellation Program (CxP) Safety, Reliability; and Quality Assurance (SR&QA) Requirements Director, the NASA Engineering and Safety Center (NESC) participated in the Cx SR&QA Requirements forum. The Requirements Forum was held June 24-26; 2008, at GRC's Plum Brook Facility. The forums purpose was to gather all stakeholders into a focused meeting to help complete the process of refining the CxP to refine its Level II SR&QA requirements or defining project-specific requirements tailoring. Element prime contractors had raised specific questions about the wording and intent of many requirements in areas they felt were driving costs without adding commensurate value. NESC was asked to provide an independent and thorough review of requirements that contractors believed were driving Program costs, by active participation in the forum. This document contains information from the forum.

Cameron, Kenneth D.↗
DOE OSTI2024

Connected Thermostat Alternatives for Room Air Conditioners and Minisplit Heat Pumps

The availability of smart, connected thermostats has improved climate control, energy efficiency, and grid demand-response programs for central HVAC systems. However, a significant gap exists in addressing integrated control systems for point-source heating and cooling systems such as window air-conditioners (window ACs) and mini-split heat pumps (MSHPs). This report examines the emerging market of third-party connected thermostats tailored for these systems, focusing on their effectiveness, reliability, and potential barriers to adoption.This study evaluates several commercially available products designed for room ACs and MSHPs through a series of laboratory tests. While these infrared-based (IR-based) thermostats offer remote temperature control and scheduling via mobile apps, our findings reveal that none are seamless, with reliability of basic functions being a critical factor. Promising features include integration of indoor air quality metrics and time-of-use pricing, but the latter are not yet available in the U.S. Barriers to broad user acceptance include non-seamless setup processes, challenges in thermostat placement, and unclear product differentiation. There is a pressing need for research and development in enabling MSHPs and central thermostats to coordinate, enhancing energy savings and comfort in retrofit applications. This study underscores the importance of further innovation in connected thermostat technology to address the diverse needs of single-zone HVAC systems and promote efficient energy management in households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1986

Wright Brothers Lectureship in Aeronautics: Experience with HiMAT remotely piloted research vehicle - An alternate flight test approach

The highly maneuverable aircraft technology (HiMAT) program explored the various and complex interactions of advanced technologies, such as aeroelastic tailoring, close-coupled canard, and relaxed static stability. A 0.44-subscale remotely piloted research vehicle (RPRV) of a hypothetical fighter airplane was designed and flight-tested to determine the effects of these interactions and to define the design techniques appropriate for advanced fighter technologies. Flexibility and high maneuverability were provided by flight control laws implemented in ground-based computers and telemetered to the vehicle control system during flight tests. The high quality of the flight-measured data and their close correlation with the analytical design modeling proved that the RPRV is a viable and cost-effective tool for developing aerodynamic, structure, and control law requirements for highly maneuverable fighter airplanes of the future.

Deets, D. A.↗
NASA NTRS1986

The pultrusion process for structures on advanced aerospace transportation systems

The pultrusion process, which has the potential for use in the manufacture of structures for aerospace hardware, is described. In this process, reinforcing fibers are pulled continuously through a resin system for wetting and subsequently through a heated die for polymerization. By using this process, fabrication of very long lengths of high strength, lightweight structures with consistently high quality for aerospace applications is possible. The more conventional processes involve hand lay-up, vacuum bagging, autoclaving or oven curing techniques such that lengths of structural elements produced are limited by the lengths of autoclaves or curing ovens. Several types of developmental structural elements are described in which fiberglass, aramid, graphite, and hybrid fiber systems have been used as reinforcements in an epoxy matrix and their flexural properties compared. Reinforcement fibers having tailor-made orientations which achieve tailor-made strength in the pultrusions are described. The potential aerospace applications for the pultruded products are described with advantages cited over conventional hand lay-up methods.

Wilson, Maywood L.↗
DOE OSTI2026

Uncertainty-Aware Machine Learning for Small-Angle X-ray Scattering Analysis in Autonomous Experimentation

Small-angle X-ray scattering (SAXS) is a powerful high-throughput characterization tool for probing nanoscale structure in native sample environments, providing real-time morphological information such as nanoparticle size and shape during synthesis. However, automated SAXS data analysis for extracting meaningful structural parameters is non-trivial and remains a bottleneck in closed-loop experimentation towards autonomous materials discovery, which demands fast, reliable, and uncertainty-aware data analysis. Here, we develop a machine-learning approach for automated SAXS analysis tailored to closed-loop nanoparticle synthesis. A Random Forest (RF) regression model is trained on 100,000 synthetic SAXS curves generated from polydisperse spherical nanoparticles with realistic background contributions. Using normalized one-dimensional SAXS intensity profiles as input, the RF model directly predicts nanoparticle radius, size polydispersity, and background parameters, while the ensemble standard deviation across trees provides built-in uncertainty quantification (UQ). On synthetic data, we show that combining fit-quality metrics (R 2 , MAE) with thresholds on prediction uncertainty reliably identifies accurate parameter estimates without access to ground truth. We then apply the trained model to 365 experimental SAXS profiles of citrate-reduced gold nanoparticles synthesized using an automated droplet-flow microreactor with in situ SAXS at a synchrotron beamline, classifying the results into high- and low-confidence subsets based on UQ metrics. Finally, we integrate RF-based SAXS analysis into a simulated closed-loop optimization campaign using Gaussian process Bayesian optimization to minimize nanoparticle polydispersity, benchmarking against conventional automated Levenberg–Marquardt fitting. The RF-guided campaign exhibits substantially faster convergence and lower relative opportunity cost (∼0.07 vs ∼0.3), demonstrating that uncertainty-aware machine-learning SAXS analysis significantly enhances the efficiency and robustness of autonomous nanomaterials synthesis workflows.

Bayesian optimization↗
NASA NTRS2010

The ICARE Method

The ICARE method is a flexible, widely applicable method for systems engineers to solve problems and resolve issues in a complete and comprehensive manner. The method can be tailored by diverse users for direct application to their function (e.g. system integrators, design engineers, technical discipline leads, analysts, etc.). The clever acronym, ICARE, instills the attitude of accountability, safety, technical rigor and engagement in the problem resolution: Identify, Communicate, Assess, Report, Execute (ICARE). This method was developed through observation of Space Shuttle Propulsion Systems Engineering and Integration (PSE&I) office personnel approach in an attempt to succinctly describe the actions of an effective systems engineer. Additionally it evolved from an effort to make a broadly-defined checklist for a PSE&I worker to perform their responsibilities in an iterative and recursive manner. The National Aeronautics and Space Administration (NASA) Systems Engineering Handbook states, engineering of NASA systems requires a systematic and disciplined set of processes that are applied recursively and iteratively for the design, development, operation, maintenance, and closeout of systems throughout the life cycle of the programs and projects. ICARE is a method that can be applied within the boundaries and requirements of NASA s systems engineering set of processes to provide an elevated sense of duty and responsibility to crew and vehicle safety. The importance of a disciplined set of processes and a safety-conscious mindset increases with the complexity of the system. Moreover, the larger the system and the larger the workforce, the more important it is to encourage the usage of the ICARE method as widely as possible. According to the NASA Systems Engineering Handbook, elements of a system can include people, hardware, software, facilities, policies and documents; all things required to produce system-level results, qualities, properties, characteristics, functions, behavior and performance. The ICARE method can be used to improve all elements of a system and, consequently, the system-level functional, physical and operational performance. Even though ICARE was specifically designed for a systems engineer, any person whose job is to examine another person, product, or process can use the ICARE method to improve effectiveness, implementation, usefulness, value, capability, efficiency, integration, design, and/or marketability. This paper provides the details of the ICARE method, emphasizing the method s application to systems engineering. In addition, a sample of other, non-systems engineering applications are briefly discussed to demonstrate how ICARE can be tailored to a variety of diverse jobs (from project management to parenting).

Henke, Luke↗
NASA NTRSDate not supplied

Enhancing Air Quality Applications in the Hindu Kush-Himalayan Region Using Satellite, Model, and Machine Learning Techniques

Air pollution in the Hindu Kush Himalayan (HKH) region of South Asia is a severe issue, as increases in emissions over the past two decades have degraded air quality (AQ) across the region, which poses major threats to human health, the ecosystem, climate, and agriculture. A diversity of anthropogenic and natural emission sources including transportation, power plants, industries, open biomass burning of crop residue, forest fires, cooking and heating fires, and dust storms contribute to unhealthy AQ and transboundary pollution issues in the region. Further complicating matters is the importance of meteorology and terrain on AQ, especially in the Kathmandu Valley where extreme haze episodes frequently develop from the atmospherically stable weather conditions during the winter monsoon. This study uses state-of-the-art satellite observations and modeling capabilities in conjunction with machine learning techniques to develop a comprehensive toolkit for enhancing AQ monitoring and forecasting in HKH. The toolkit incorporates new generation satellite observations from the TROPOspheric Monitoring Instrument (TROPOMI), Geostationary Environment Monitoring Spectrometer (GEMS), and Advanced Meteorological Imager (AMI), which provide unprecedented resolution on aerosols and trace gases, including nitrogen dioxide, formaldehyde, sulfur dioxide, carbon monoxide, and ozone, and aerosol optical depth. Value-added products, such as level 4 PM2.5 products, are developed from the suite of satellite observations to further improve AQ monitoring capabilities in the region. The satellite products are also used to assimilate a high-resolution chemical transport model tailored for the HKH region, which is providing daily, 54-hour AQ forecasts with horizontal grid spacings of 12- and 4-km. This presentation will provide an overview of the suite of satellite- and model-based products in the AQ toolkit and application and performance of the toolkit for AQ monitoring and forecasting in HKH.

Forecasting↗
NASA NTRS2015

In-Flight Calibration Processes for the MMS Fluxgate Magnetometers

The calibration effort for the Magnetospheric Multiscale Mission (MMS) Analog Fluxgate (AFG) and DigitalFluxgate (DFG) magnetometers is a coordinated effort between three primary institutions: University of California, LosAngeles (UCLA); Space Research Institute, Graz, Austria (IWF); and Goddard Space Flight Center (GSFC). Since thesuccessful deployment of all 8 magnetometers on 17 March 2015, the effort to confirm and update the groundcalibrations has been underway during the MMS commissioning phase. The in-flight calibration processes evaluatetwelve parameters that determine the alignment, orthogonalization, offsets, and gains for all 8 magnetometers usingalgorithms originally developed by UCLA and the Technical University of Braunschweig and tailored to MMS by IWF,UCLA, and GSFC. We focus on the processes run at GSFC to determine the eight parameters associated with spin tonesand harmonics. We will also discuss the processing flow and interchange of parameters between GSFC, IWF, and UCLA.IWF determines the low range spin axis offsets using the Electron Drift Instrument (EDI). UCLA determines the absolutegains and sensor azimuth orientation using Earth field comparisons. We evaluate the performance achieved for MMS andgive examples of the quality of the resulting calibrations.

Electromagnetic field Measurements↗