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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Human Reliability Assessments: Using the Past (Shuttle) to Predict the Future (ORION)

NASA uses two HRA assessment methodologies. The first is a simplified method which is based on how much time is available to complete the action, with consideration included for environmental and personal factors that could influence the human's reliability. This method is expected to provide a conservative value or placeholder as a preliminary estimate. This preliminary estimate is used to determine which placeholder needs a more detailed assessment. The second methodology is used to develop a more detailed human reliability assessment on the performance of critical human actions. This assessment needs to consider more than the time available, this would include factors such as: the importance of the action, the context, environmental factors, potential human stresses, previous experience, training, physical design interfaces, available procedures/checklists and internal human stresses. The more detailed assessment is still expected to be more realistic than that based primarily on time available. When performing an HRA on a system or process that has an operational history, we have information specific to the task based on this history and experience. In the case of a PRA model that is based on a new design and has no operational history, providing a "reasonable" assessment of potential crew actions becomes more problematic. In order to determine what is expected of future operational parameters, the experience from individuals who had relevant experience and were familiar with the system and process previously implemented by NASA was used to provide the "best" available data. Personnel from Flight Operations, Flight Directors, Launch Test Directors, Control Room Console Operators and Astronauts were all interviewed to provide a comprehensive picture of previous NASA operations. Verification of the assumptions and expectations expressed in the assessments will be needed when the procedures, flight rules and operational requirements are developed and then finalized.

DeMott, Diana L.↗
NASA NTRS2016

Human Reliability Assessments: Using the Past (Shuttle) to Predict the Future (Orion)

NASA (National Aeronautics and Space Administration) Johnson Space Center (JSC) Safety and Mission Assurance (S&MA) uses two human reliability analysis (HRA) methodologies. The first is a simplified method which is based on how much time is available to complete the action, with consideration included for environmental and personal factors that could influence the human's reliability. This method is expected to provide a conservative value or placeholder as a preliminary estimate. This preliminary estimate or screening value is used to determine which placeholder needs a more detailed assessment. The second methodology is used to develop a more detailed human reliability assessment on the performance of critical human actions. This assessment needs to consider more than the time available, this would include factors such as: the importance of the action, the context, environmental factors, potential human stresses, previous experience, training, physical design interfaces, available procedures/checklists and internal human stresses. The more detailed assessment is expected to be more realistic than that based primarily on time available. When performing an HRA on a system or process that has an operational history, we have information specific to the task based on this history and experience. In the case of a Probabilistic Risk Assessment (PRA) that is based on a new design and has no operational history, providing a "reasonable" assessment of potential crew actions becomes more challenging. In order to determine what is expected of future operational parameters, the experience from individuals who had relevant experience and were familiar with the system and process previously implemented by NASA was used to provide the "best" available data. Personnel from Flight Operations, Flight Directors, Launch Test Directors, Control Room Console Operators and Astronauts were all interviewed to provide a comprehensive picture of previous NASA operations. Verification of the assumptions and expectations expressed in the assessments will be needed when the procedures, flight rules and operational requirements are developed and then finalized.

DeMott, Diana↗
NASA NTRS2017

Human Reliability Assessments: Using the Past (Shuttle) to Predict the Future (Orion)

NASA (National Aeronautics and Space Administration) Johnson Space Center (JSC) Safety and Mission Assurance (S&MA) uses two human reliability analysis (HRA) methodologies. The first is a simplified method which is based on how much time is available to complete the action, with consideration included for environmental and personal factors that could influence the human's reliability. This method is expected to provide a conservative value or placeholder as a preliminary estimate. This preliminary estimate or screening value is used to determine which placeholder needs a more detailed assessment. The second methodology is used to develop a more detailed human reliability assessment on the performance of critical human actions. This assessment needs to consider more than the time available, this would include factors such as: the importance of the action, the context, environmental factors, potential human stresses, previous experience, training, physical design interfaces, available procedures/checklists and internal human stresses. The more detailed assessment is expected to be more realistic than that based primarily on time available. When performing an HRA on a system or process that has an operational history, we have information specific to the task based on this history and experience. In the case of a Probabilistic Risk Assessment (PRA) that is based on a new design and has no operational history, providing a "reasonable" assessment of potential crew actions becomes more challenging. To determine what is expected of future operational parameters, the experience from individuals who had relevant experience and were familiar with the system and process previously implemented by NASA was used to provide the "best" available data. Personnel from Flight Operations, Flight Directors, Launch Test Directors, Control Room Console Operators, and Astronauts were all interviewed to provide a comprehensive picture of previous NASA operations. Verification of the assumptions and expectations expressed in the assessments will be needed when the procedures, flight rules, and operational requirements are developed and then finalized.

DeMott, Diana L.↗
NASA NTRS2011

Next Steps in the Evolution of Human Spaceflight Training

Train before you fly has always been a watchword at NASA, and consequently, NASA has been conducting training for human spaceflight missions for longer than it has been involved in the actual conduct of human spaceflight missions. Throughout that time, NASA s approach to human spaceflight training has continuously evolved to keep pace with the technology of the modern world, but the approach to training itself has not changed significantly. Today, there are more tools and technologies that enable learning than ever before. This paper intends to review the challenges of human spaceflight training and how modern technology and an updated approach could improve that training. The Spaceflight Training Management Office (DA7) within the Mission Operations Directorate (MOD) has been investigating the current training of instructors, flight controllers and astronauts in order to identify where a new approach to training and training management may be necessary to improve the efficacy of the training provided. Through this investigation, the DA7 team has identified potential areas of improvement within International Space Station (ISS) training in a wide range of areas, including the delivery of training, the structure of the training program, the concept of what is considered training, and the management of that training. The ISS is an operational program with an established training paradigm. As such, the implementation of these concepts will be met with several challenges that may prevent or preclude them from being adopted. These challenges include demonstrating return-on-investment (ROI) and overcoming cultural or technological obstacles. This report will delve into the possible improvement areas for training, the future training concepts that are being considered, and the challenges associated with implementation. The paper will include concepts for utilization of Web 2.0 technologies, electronic learning, digital media, and other technologies in the development, management, and conduct of human spaceflight training.

Balmain, Clint↗
NASA NTRS2010

Smart Ultrasound Remote Guidance Experiment (SURGE)- Concept of Operations Evaluation for Using Remote Guidance Ultrasound for Planetary Space Flight

Introduction Use of remote guidance (RG) techniques aboard the International Space Station (ISS) has enabled astronauts to collect diagnostic-level ultrasound images. Exploration class missions will require this cohort of (typically) non-formally trained sonographers to operate with greater autonomy given the longer communication delays (2 seconds for ISS vs. >6 seconds for missions beyond the Moon) and communication blackouts. To determine the feasibility and training requirements for autonomous ultrasound image collection by non-expert ultrasound operators, ultrasound images were collected from a similar cohort using three different image collection protocols: RG only, RG with a computer-based learning tool (LT), and autonomous image collection with LT. The groups were assessed for both image quality and time to collect the images. Methods Subjects were randomized into three groups: RG only, RG with LT, and autonomous with LT. Each subject received 10 minutes of standardized training before the experiment. The subjects were tasked with making the following ultrasound assessments: 1) bone fracture and 2) focused assessment with sonography in trauma (FAST) to assess a patient s abdomen. Human factors-related questionnaire data were collected immediately after the assessments. Results The autonomous group did not out-perform the two groups that received RG. The mean time for the autonomous group to collect images was less than the RG groups, however the mean image quality for the autonomous group was less compared to both RG groups. Discussion Remote guidance continues to produce higher quality ultrasound images than autonomous ultrasound operation. This is likely due to near-instant feedback on image quality from the remote guider. Expansion in communication time delays, however, diminishes the capability to provide this feedback, thus requiring more autonomous ultrasound operation. The LT has the potential to be an excellent training and coaching component for autonomous ultrasound image collection during exploration missions.

Hurst, Victor, IV↗
DOE OSTI2024

Modeling graphene sheet growth and dynamical matrix calculations using molecular dynamics

Molecular dynamics (MD) has been an incredibly useful tool to model physical processes that were synthesized experimentally but not fully understood. MD, through the use of semi-empirical inter-atomic potentials, has allowed understanding of different physical processes in materials science. Yet as well as providing useful insights into materials science, molecular dynamics has a wider range of usability. In this report, I will be detailing how MD can be used to study graphene formation from a carbon liquid which requires high temperatures and pressures. Beyond this, I will describe the usefulness of MD for understanding the physics for phonon transport quantum sensors. To do this, MD was employed to determine the dynamical matrix by treating atoms as coupled oscillators. An accurate understanding of the dynamical matrix of a system is required to calculate the non-equilibrium Green’s function used to describe the phonon transport within phonon wave-guides. I found that, across multiple pressures and temperatures, randomly placed carbon atoms will show evidence of pent-first formation with semi-empirical models. Density functional theory (DFT), on the other hand, was too computationally expensive to use for full scale MD simulations, but we have the possibility of training a machine learned interatomic potential to approximate DFT for carbon in the environments being studied for pent-first graphene sheet formation.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Detecting and diagnosing SSME faults using an autoassociative neural network topology

An effort is underway at the University of Tennessee Space Institute to develop diagnostic expert system methodologies based on the analysis of patterns of behavior of physical mechanisms. In this approach, fault diagnosis is conceptualized as the mapping or association of patterns of sensor data to patterns representing fault conditions. Neural networks are being investigated as a means of storing and retrieving fault scenarios. Neural networks offer several powerful features in fault diagnosis, including (1) general pattern matching capabilities, (2) resistance to noisy input data, (3) the ability to be trained by example, and (4) the potential for implementation on parallel computer architectures. This paper presents (1) an autoassociative neural network topology, i.e. the network input and output is identical when properly trained, and hence learning is unsupervised; (2) the training regimen used; and (3) the response of the system to inputs representing both previously observed and unkown fault scenarios. The effects of noise on the integrity of the diagnosis are also evaluated.

Ali, M.↗
DOE OSTI2025

Bridging material models across scales: An integrated approach to equation of state and molecular dynamics modeling of copper

New uncertainty-aware equation of state (EOS) and electrical conductivity (EC) models for copper have been developed. The multiphase EOS/EC models are fit to experimental solid/liquid EC isobar measurements as well as density-functional theory molecular dynamics (DFT-MD) EC calculations in both expanded and compressed regimes (0.1–16 g/ cm 3 ⁠). The liquid and solid EOS phases were fit to available experimental data along with additional DFT-MD data over the same range as the EC. Leveraging the DFT-MD data, a corresponding machine-learned interatomic potential (MLIAP) for copper was trained using genetic-algorithm optimization. The copper MLIAP was constrained by EOS shock points at high compressions. The final EOS bounded MLIAP proves to be stable over a large density range (approximately 0.1–20 g/ cm 3 ) with good agreement to an isothermal compression curve, shock Hugoniot, and liquid speed of sound measurements at high pressures (100s of GPa).

Acoustic measurements and instrumentation↗
DOE OSTI2025

Differential Seismic Phase Detection Probability as a Potential Discriminant of Explosions and Earthquakes

Deep learning models trained to estimate the probability of seismic P and S phases are rapidly expanding the scale of local event detections. Here, we evaluate the potential for deep learning model output phase detection probabilities to contribute to event‐type classification, particularly discrimination of single‐fired borehole explosions and earthquakes at local distances (<300 km). Motivated by the empirical success of P/S amplitude ratios, we consider the difference between P and S pick probability output from previously developed phase detection models, P prob −S prob ⁠, as a discriminant. Test data include M L ∼1–4 earthquakes and explosions observed by common seismographs in ten geologically diverse localities. Depending on the picking model and training data, binary classification using P prob −S prob with at least three stations can achieve approximately equivalent classification accuracy as P/S amplitude ratios without requiring any customization. Joint classification with P/S and P prob −S prob improves accuracy for most quality control scenarios. Pick probabilities are an efficient attribute to consider in explosion discrimination because they can be automated byproducts of event detection. They avoid the binary choice of picking or not picking weakly visible S waves common to explosions.

Duan, Chenglong [Rice Univ., Houston, TX (United S↗
NASA NTRS2007

A Study to Estimate the Effectiveness of Visual Testing Training for Aviation Maintenance Management

The Air Commerce Act of 1926 set the beginning for standards in aviation maintenance. Even after deregulation in the late l970s, maintenance standards and requirements still have not changed far from their initial criteria. After a potential candidate completes Federal Aviation Administration training prerequisites, they may test for their Airframe and Powerplant (A&P) certificate. Performing maintenance in the aviation industry for a minimum of three years, the technician may then test for their Inspection Authorization (IA). After receiving their Airframe and Powerplant certificate, a technician is said to have a license to perform. At no time within the three years to eligibility for Inspection Authorization are they required to attend higher-level inspection training. What a technician learns in the aviation maintenance industry is handed down from a seasoned technician to the new hire or is developed from lessons learned on the job. Only in Europe has the Joint Aviation Authorities (JAA) required higher-level training for their aviation maintenance technicians in order to control maintenance related accidents (Lu, 2005). Throughout the 1990s both the General Accounting Office (GAO) and the National Transportation Safety Board (NTSB) made public that the FAA is historically understaffed (GAO, 1996). In a safety recommendation the NTSB stated "The Safety Board continues to lack confidence in the FAA's commitment to provide effective quality assurance and safety oversight of the ATC system (NTSB, 1990)." The Federal Aviation Administration (FAA) has been known to be proactive in creating safer skies. With such reports you would suspect the FAA to also be proactive in developing more stringent inspection training for aviation maintenance technicians. The purpose of this study is to estimate the effectiveness of higher-level inspection training, such as Visual Testing (VT) for aviation maintenance technicians, to improve the safety of aircraft and to make recommendations to management with regard to the value of such training.

Law, Lewis Lyle↗
DOE OSTI2025

A systematic review of machine learning in groundwater monitoring

With increasing concerns about water scarcity, groundwater has become crucial since this resource provides most of the freshwater needs. However, various human and natural activities often contaminate the groundwater, making it unsuitable for use. Over the years, scientists and engineers have used many methods to predict and track groundwater contamination as part of environmental monitoring. Consequently, there is an urgent need for improved methods, particularly in the face of increasing contamination. Machine learning has sometimes been used to monitor groundwater, air quality, and climate. Traditional methods must be improved due to the complexity and large amount of environmental data. This includes using hybrid models that combine traditional and new techniques. Despite the use of machine learning in many scientific areas, there is a lack of comprehensive reviews focusing on its use in environmental monitoring, especially groundwater monitoring. We aim to fill this gap by exploring machine-learning applications in groundwater monitoring. We discuss relevant methods, their limitations, and future potential. We summarize research on automating data processing and model training using groundwater sensor data. Our research underscores the transformative potential of machine learning to revolutionize long-term groundwater monitoring and contamination detection, providing valuable insights for future research and practical applications.

AI/ML↗
DOE OSTI2025

Thermal disorder and phonon softening in the ferroelectric phase transition of lead titanate

We report a molecular dynamics study of ab initio quality of the ferroelectric phase transition in crystalline PbTi⁢O3. We model anharmonicity accurately in terms of potential energy and polarization surfaces trained on density functional theory data with modern machine learning techniques. Our simulations demonstrate that the transition has a strong order-disorder character, in agreement with diffraction experiments, and provide fresh insight into the approach to equilibrium across the phase transition. We find that the emergence and disappearance of the macroscopic polarization is driven by dipolar switching at the nanometer scale. We also computed the infrared optical absorption spectra in both the ferroelectric and the paraelectric phases, finding good agreement with the experimental Raman frequencies. Often, the almost ideal displacive character of the soft mode detected by Raman scattering in the paraelectric phase has been contrasted with the order-disorder character of the transition suggested by diffraction experiments. We settle this issue by showing that the soft mode coexists with a strong Debye relaxation associated with thermal disordering of the dipoles. The Debye relaxation feature is centered at zero frequency and appears near the transition temperature in both the ferroelectric and the paraelectric phases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

CuXASNet: Rapid and accurate prediction of copper L-edge x-ray absorption spectra using machine learning

In this work, we have developed CuXASNet, a dense neural network that predicts simulated Cu -edge x-ray absorption spectra (XAS) from atomic structures. Featurization of the Cu local environment is performed using a component of M3GNet, a graph neural network developed for predicting the potential energy surface. CuXASNet is trained on simulated spectra from FEFF9 at the multiple scattering level of theory, and can predict the and edges for Cu sites to quantitative accuracy. To validate our approach, we compare 14 experimental spectra extracted from the literature with the predictions of CuXASNet. The agreement of CuXASNet with experiments is shown by an average mean absolute error of 0.125 and an average Spearman's correlation coefficient of 0.891, which is comparable to FEFF9's values of 0.131 and 0.898 for the same metrics. As such, CuXASNet can rapidly predict a large number of -edge XAS spectra at the same accuracy as FEFF9 simulations. This can be used as a drop-in replacement for multiple scattering codes for fast screening of candidate atomic structure models of a measured system. This model establishes a general framework for Cu XAS prediction, and can be extended to more computationally expensive levels of theory and to other transition metal edges.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Securing Federated Learning Against Active Reconstruction Attacks

Federated Learning (FL) has amassed notable attention for its ability to preserve user privacy while emphasizing the retainment of model training efficiency. Due to this potential, FL has been integrated in many domains, such as healthcare, finance, law, and industrial engineering, where data cannot be easily exchanged due to sensitive information and strict privacy laws. However, current research has indicated that FL protocols are easily compromised by active data reconstruction attacks employed by actively dishonest servers. The malicious modification of global model parameters allows an actively dishonest server to obtain a direct copy of users’ private data via gradient inversion. Here, this class of attacks is highly underexplored and continues to be a major challenge due to the intense threat model. In this paper, we propose OASIS as a scalable and modality-agnostic defense based on data augmentation that counteracts active data reconstruction attacks while preserving model performance. To generalize our defense, we uncover the intuition behind gradient inversion that enables these attacks and theoretically establish the conditions by which the defense can be considered robust regardless of attack design. From this, we formulate our defense with data augmentation that illustrates its ability to undermine the attack principle. We evaluate OASIS on five real-world datasets–two image-based (ImageNet and CIFAR100) and three text-based (Wikitext, Stack Overflow, and Shakespeare)–which span diverse uses cases such as vision tasks and language modeling. Comprehensive evaluations on these datasets exhibit the efficacy of OASIS and highlight its feasibility as a solution.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) towards CMIP7

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. Consequently, the role of enhanced horizontal resolution in improved process representation in all components of the climate system continues to be of great interest. Recent simulations suggest the possibility of significant changes in both large-scale aspects of the ocean and atmospheric circulations and in the regional responses to climate change, as well as improvements in representations of small-scale processes and extremes, when resolution is enhanced. The first phase of the High-Resolution Model Intercomparison Project (HighResMIP1) was successful at producing a baseline multi-model assessment of global simulations with model grid spacings of 25–50 km in the atmosphere and 10–25 km in the ocean, a significant increase when compared to models with standard resolutions on the order of 1° that are typically used as part of the Coupled Model Intercomparison Project (CMIP) experiments. In addition to over 250 peer-reviewed manuscripts using the published HighResMIP1 datasets, the results were widely cited in the Intergovernmental Panel on Climate Change report and were the basis of a variety of derived datasets, including tracked cyclones (both tropical and extratropical), river discharge, storm surge, and impact studies. There were also suggestions from the few ocean eddy-rich coupled simulations that aspects of climate variability and change might be significantly influenced by improved process representation in such models. The compromises that HighResMIP1 made should now be revisited, given the recent major advances in modelling and computing resources. Aspects that will be reconsidered include experimental design and simulation length, complexity, and resolution. In addition, larger ensemble sizes and a wider range of future scenarios would enhance the applicability of HighResMIP. Therefore, we propose the High-Resolution Model Intercomparison Project phase 2 (HighResMIP2) to improve and extend the previous work, to address new science questions, and to further advance our understanding of the role of horizontal resolution (and hence process representation) in state-of-the-art climate simulations. With further increases in high-performance computing resources and modelling advances, along with the ability to take full advantage of these computational resources, an enhanced investigation of the drivers and consequences of variability and change in both large- and synoptic-scale weather and climate is now possible. With the arrival of global cloud-resolving models (currently run for relatively short timescales), there is also an opportunity to improve links between such models and more traditional CMIP models, with HighResMIP providing a bridge to link understanding between these domains. HighResMIP also aims to link to other CMIP projects and international efforts such as the World Climate Research Program lighthouse activities and various digital twin initiatives. It also has the potential to be used as training and validation data for the fast-evolving machine learning climate models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

History and future of remote sensing technology and education

A historical overview of the discovery and development of photography, related sciences, and remote sensing technology is presented. The role of education to date in the development of remote sensing is discussed. The probable future and potential of remote sensing and training is described.

Colwell, R. N.↗
NASA NTRS1980

Field verification of lateral-torsional coupling effects on rotor instabilities in centrifugal compressors

Lateral and torsional vibration data obtained on a centrifugal compressor train which had shaft instabilities and gear failures is examined. The field data verifies that the stability of centrifugal compressors can be adversely affected by coincidence of torsional natural frequencies with lateral instability frequencies. The data also indicates that excitation energy from gear boxes can reduce stability margins if energy is transmitted either laterally or torsionally to the compressors. The lateral and torsional coupling mechanisms of shaft systems is discussed. The coupling mechanisms in a large industrial compressor train are documented and the potential effect on rotor stability is demonstrated. Guidelines are set forth to eliminate these potential problems by minimizing the interaction of torsional and lateral responses and their effect on rotor stability.

Wachel, J. C.↗
NASA NTRS1992

Analyst variability in labeling of unsupervised classifications

Analyst variability in the labeling of unsupervised classifications is tested for Landsat 5 Thematic Mapper image products covering two test sites in southern California. The accuracy of results are tested using samples from a photo interpreted base map of the area. The significance of differences between analysts is indicated by comparing Kappa statistics derived from error matrices. Analyst variability is found to be statistically significant in most cases. Certain analysts provided consistently better results for a given study area or degree of training. This work demonstrates the potential influence of analyst bias on what would otherwise seem to be a fairly objective method and suggests that controls for this subjectivity should be factored into experimental designs.

Mcgwire, Kenneth C.↗