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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO 2 Emissions

Satellite data provides essential insights into the spatiotemporal distribution of CO 2 concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and often lack rigorous methods for estimating parameters like spatial length scales. We introduce an inference model that processes the spatiotemporal covariance in satellite data and estimates hyperparameters such as covariance length scales. Our approach uses the Gaussian process (GP) machine learning (ML) and modern probabilistic programming languages (PPLs) to perform atmospheric inversions of emissions from satellite data. We develop a GP ML inversion system based on modern PPLs and the GEOS-Chem chemical transport model, simulating atmospheric CO 2 concentrations corresponding to the Orbiting Carbon Observatory-2/3 (OCO-2/3) data for July 2020. In our supervised learning framework, we treat the GEOS-Chem simulated data set as the target, with predictors derived by scaling the target with sector-specific factors hidden from the GP machine. Our results show that the GP model, combined with GPU-enabled PPLs, effectively retrieves true emission scaling factors and infers noise levels concealed within the data. This suggests that our method could be applied over larger areas with more complex covariance structures, enabling comprehensive analysis of the spatiotemporal patterns observed in OCO-2/3 and similar satellite data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Observational benchmarks inform representation of soil organic carbon dynamics in land surface models

Abstract. Representing soil organic carbon (SOC) dynamics in Earth system models (ESMs) is a key source of uncertainty in predicting carbon–climate feedbacks. Machine learning models can help identify dominant environmental controllers and establish their functional relationships with SOC stocks. The resulting knowledge can be integrated into ESMs to reduce uncertainty and improve predictions of SOC dynamics over space and time. In this study, we used a large number of SOC field observations (n=54 000), geospatial datasets of environmental factors (n=46), and two machine learning approaches (namely random forest, RF, and generalized additive modeling, GAM) to (1) identify dominant environmental controllers of global and biome-specific SOC stocks, (2) derive functional relationships between environmental controllers and SOC stocks, and (3) compare the identified environmental controllers and predictive relationships with those in models used in Phase 6 of the Coupled Model Intercomparison Project (CMIP6). Our results showed that the diurnal temperature, drought index, cation exchange capacity, and precipitation were important observed environmental predictors of global SOC stocks. While the RF model identified 14 environmental factors that describe climatic, vegetation, and edaphic conditions as important predictors of global SOC stocks (R2=0.61, RMSE = 0.46 kg m−2), current ESMs oversimplify the relationships between environmental factors and SOC, with precipitation, temperature, and net primary productivity explaining > 96 % of the variability in ESM-modeled SOC stocks. Further, our study revealed notable disparities among the functional relationships between environmental factors and SOC stocks simulated by ESMs compared with observed relationships. To improve SOC representations in ESMs, it is imperative to incorporate additional environmental controls, such as the cation exchange capacity, and refine the functional relationships to align more closely with observations.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Considerations for human-machine interfaces in tele-operations

Numerous factors impact on the efficiency of tele-operative manipulative work. Generally, these are related to the physical environment of the tele-operator and how he interfaces with robotic control consoles. The capabilities of the operator can be influenced by considerations such as temperature, eye strain, body fatigue, and boredom created by repetitive work tasks. In addition, the successful combination of man and machine will, in part, be determined by the configuration of the visual and physical interfaces available to the teleoperator. The design and operation of system components such as full-scale and mini-master manipulator controllers, servo joysticks, and video monitors will have a direct impact on operational efficiency. As a result, the local environment and the interaction of the operator with the robotic control console have a substantial effect on mission productivity.

Newport, Curt↗
NASA NTRS1998

Some Formal Aspects of Human-Machine Interaction

While automated control systems such as autopilots and medical devices are introduced at a rapid pace, it is widely recognized that user interaction with these machines is problematic (Abbott, Slotte, & Stimson, 1996). One factor commonly cited in the literature is the discrepancy between the machine's behavior and the user's expectations. Design guidelines to reduce this discrepancy focus on two elements: (1) improvement of the "feedback" about what the automation is actually doing, and (2) improvement of the user's "mental model" of the automation (Norman, 1990; Sarter and Woods, 1995). This presentation describes a methodology for investigating these two elements via a formal (Le., mathematical) approach. The method involves two representations: (1) a finite state model of the machine's behavior (2) a finite state model of the user's knowledge and expectations about the machine's behavior. In the analysis phase we compare these two models and identify discrepancies. Such discrepancies can be compensated by augmenting the display and/or the user's model. A taxonomy of these discrepancies will be discussed using examples from automated Eight control systems of modern "glass cockpit" jetliners.

Degani, Asaf↗
NASA NTRS1989

Telerobotic Architecture for an on-Orbit Servicer

An on-orbit servicer system has unique functional and human factors requirements. The servicing, whether it be teleoperation task, a supervised control task or an autonomous robotic task, the man-machine interface function is likely to be a bottleneck to the operation of the whole system. The man-machine interface system for a space servicer, namely the operator control station, includes several subsystems with a hierarchical architecture. Those subsystems include a reasoning and planning subsystem (also known as the artificial intelligence planner), a run-time control subsystem, a manipulator control and mechanization subsystem, and a sensing and perception subsystem. Indicative of these potentials, certain generic tasks, suggestive of space assembly, maintenance and repair, were performed in a testbed environment. Through performance in several modes: direct teleoperation, shared control, traded control, and robotic operation, the benefits of the individual technology contributions to the operation were quantized and recommendations for use in telerobotic systems were established.

Operator Control Station↗
NASA NTRSDate not supplied

Resilience Modeling in Complex Engineered Systems with Human-Machine Interactions

In recent times, there has been a growing interest in resilience-based design. Resilience-based design operates on the concept that failures and unexpected events will happen, and when they occur, complex engineered systems should be able to operate within acceptable bounds and recover reasonably. Humans can contribute to the resilience of a system by quickly detecting unforeseen events and taking corrective measures. To this effect, researchers have proposed guidelines and design approaches that can help promote human-system resilience. However, there is no early design stage tool to validate if a system is indeed resilient after applying these guidelines and design methods. In this research, we integrate the Human Error and Functional Failure Reasoning (HEFFR) framework into the fmdtools toolkit to enable designers to model the combined (machine, human, and joint) failures, including their propagation and dynamic effects, during early design stages. This integrated tool also allows designers to model the effects of performance shaping factors, team dynamics, and human-machine interactions in systems of systems. A demonstrative example of a remotely operated rover is explored to demonstrate how this approach can be applied to understand resilience in complex engineered systems with human interactions.

Lukman Irshad↗
NASA NTRS1963

HABITABILITY IN SPACE STATIONS

What does habitability mean? This word is commonly used and is bandied about as a thing which is necessary and desirable for all manned flight vehicles. But what does it really mean? A serious examination of the meaning of the term soon leads to attempts at definition into discussions of the interplay of such factors as the mission, the size and makeup of the crew, the jobs within the mission, the flight duration, the stress loads, the vehicle to be used, the comfort, and the deprivations inherent in the mission, the flight environment, et cetera. In other words, habitability might be considered the resultant of the interplay of all of the factors related to the man, his machine, his environment, and the mission to be accomplished. It is more easily visualized as the state of being at the completion of the interaction of all of the-factors rather than a discrete entity itself. Therefore, the provisions made to meet the habitability requirements can contribute to or be detrimental in meeting the program objectives. The requirement placed upon the space vehicle may be eased if necessary through the proper selection and training of the crewmen, The motivation of the crew may be an additional aid in providing a satisfactory solution to the habitability needs. The design and development of the space vehicle should avoid depending upon special selection and unusual training to meet the basic provisions needed to support the men in the space environment. The vehicle provisions should stand upon their own merit. Difficult and hazardous missions can he made more tolerable through augmentation of the provisions for habitability. For the sake of this discussion of habitability in a space station, this concept will be considered. This paper will emphasize a discussion of the interplay of some of these broader and little discussed factors as they reflect themselves in the development and operation of the space stations, rather than represent a list of items which have been established as essential for crew provisions. Ignoring these allied factors can lead to a successful mechanical system that will operate in space, yet a complete failure in providing the working, relaxing, and living areas so necessary for man if he is to maintain his productivity.

Space station↗
NASA NTRS1978

CAVE3: A general transient heat transfer computer code utilizing eigenvectors and eigenvalues

The method of solution is a hybrid analytical numerical technique which utilizes eigenvalues and eigenvectors. The method is inherently stable, permitting large time steps even with the best of conductors with the finest of mesh sizes which can provide a factor of five reduction in machine time compared to conventional explicit finite difference methods when structures with small time constants are analyzed over long time periods. This code will find utility in analyzing hypersonic missile and aircraft structures which fall naturally into this class. The code is a completely general one in that problems involving any geometry, boundary conditions and materials can be analyzed. This is made possible by requiring the user to establish the thermal network conductances between nodes. Dynamic storage allocation is used to minimize core storage requirements. This report is primarily a user's manual for CAVE3 code. Input and output formats are presented and explained. Sample problems are included which illustrate the usage of the code as well as establish the validity and accuracy of the method.

Palmieri, J. V.↗
NASA NTRS1979

Considerations for design of future research and development interactive image analysis systems

Future interactive image analysis systems must provide for the increased processing requirements imposed by a thermal channel to LANDSAT-3 and the increased number of spectral channels with significantly higher spatial resolution provided by the LANDSAT-D thematic mapper. Other design considerations must include the rapidly changing technology in memories and special purpose processors, as well as the analyst-machine interface and the human factors involved. The centralized and distributed system approaches are examined in relation to the optimum design configuration of future systems.

Wilkinson, T. B.↗
NASA NTRS1984

A system-level approach to automation research

Automation is the application of self-regulating mechanical and electronic devices to processes that can be accomplished with the human organs of perception, decision, and actuation. The successful application of automation to a system process should reduce man/system interaction and the perceived complexity of the system, or should increase affordability, productivity, quality control, and safety. The expense, time constraints, and risk factors associated with extravehicular activities have led the Automation Technology Branch (ATB), as part of the NASA Automation Research and Technology Program, to investigate the use of robots and teleoperators as automation aids in the context of space operations. The ATB program addresses three major areas: (1) basic research in autonomous operations, (2) human factors research on man-machine interfaces with remote systems, and (3) the integration and analysis of automated systems. This paper reviews the current ATB research in the area of robotics and teleoperators.

Harrison, F. W.↗
NASA NTRS1993

Design and cost drivers in 2-D braiding

Fundamentally, the braiding process is a highly efficient, low cost method for combining single yarns into circumferential shapes, as evidenced by the number of applications for continuous sleeving. However, this braiding approach cannot fully demonstrate that it can drastically reduce the cost of complex shape structural preforms. Factors such as part geometry, machine design and configuration, materials used, and operating parameters are described as key cost drivers and what is needed to minimize their effect on elevating the cost of structural braided preforms.

Morales, Alberto↗
NASA NTRS1992

Review of performance, medical, and operational data on pilot aging issues

An extensive review of the literature and studies relating to performance, medical, operational, and legal data regarding pilot aging issues was performed in order to determine what evidence there is, if any, to support mandatory pilot retirement. Popular misconceptions about aging, including the failure to distinguish between the normal aging process and disease processes that occur more frequently in older individuals, continue to contribute to much of the misunderstanding and controversy that surround this issue. Results: Review of medical data related to the pilot aging issue indicate that recent improvement in medical diagnostics and treatment technology have made it possible to identify to a high degree individuals who are at risk for developing sudden incapacitating illness and for treating those with disqualifying medical conditions. Performance studies revealed that after controlling for the presence of disease states, older pilots are able to perform as well as younger pilots on many performance tasks. Review of accident data showed that older, healthy pilots do not have higher accident rates than younger pilots, and indeeed, evidence suggests that older pilots have an advantage in the cockpit due to higher experience levels. The Man-Machine-Mission-Environment interface of factors can be managed through structured, supervised, and enhanced operations, maintenance, flight reviews, and safety procedures in order to ensure safe and productive operations by reducing the margin of error and by increasing the margin of safety. Conclusions: There is no evidence indicating any specific age as an arbitrary cut-off point for pilots to perform their fight duties. A combination of regular medical screening, performance evaluation, enhanced operational maintenance, and safety procedures can most effectively ensure a safe pilot population than can a mandatory retirement policy based on arbitrary age restrictions.

Stoklosa, J. H.↗
DOE OSTI2023

Hybrid Data‐Driven Discovery of High‐Performance Silver Selenide‐Based Thermoelectric Composites

Optimizing material compositions often enhances thermoelectric performances. However, the large selection of possible base elements and dopants results in a vast composition design space that is too large to systematically search using solely domain knowledge. To address this challenge, a hybrid data-driven strategy that integrates Bayesian optimization (BO) and Gaussian process regression (GPR) is proposed to optimize the composition of five elements (Ag, Se, S, Cu, and Te) in AgSe-based thermoelectric materials. Data is collected from the literature to provide prior knowledge for the initial GPR model, which is updated by actively collected experimental data during the iteration between BO and experiments. Within seven iterations, the optimized AgSe-based materials prepared using a simple high-throughput ink mixing and blade coating method deliver a high power factor of 2100 µW m −1 K −2 , which is a 75% improvement from the baseline composite (nominal composition of Ag 2 Se 1 ). In conclusion, the success of this study provides opportunities to generalize the demonstrated active machine learning technique to accelerate the development and optimization of a wide range of material systems with reduced experimental trials.

36 MATERIALS SCIENCE↗
NASA NTRS2004

Improving Search Algorithms by Using Intelligent Coordinates

We consider algorithms that maximize a global function G in a distributed manner, using a different adaptive computational agent to set each variable of the underlying space. Each agent eta is self-interested; it sets its variable to maximize its own function g (sub eta). Three factors govern such a distributed algorithm's performance, related to exploration/exploitation, game theory, and machine learning. We demonstrate how to exploit alI three factors by modifying a search algorithm's exploration stage: rather than random exploration, each coordinate of the search space is now controlled by a separate machine-learning-based player engaged in a noncooperative game. Experiments demonstrate that this modification improves simulated annealing (SA) by up to an order of magnitude for bin packing and for a model of an economic process run over an underlying network. These experiments also reveal interesting small-world phenomena.

Wolpert, David H.↗
DOE OSTI2024

Anomaly detection in collider physics via factorized observables

To maximize the discovery potential of high-energy colliders, experimental searches should be sensitive to unforeseen new physics scenarios. This goal has motivated the use of machine learning for unsupervised anomaly detection. In this paper, we introduce a new anomaly detection strategy called : factorized observables for regressing conditional expectations. Our approach is based on the inductive bias of factorization, which is the idea that the physics governing different energy scales can be treated as approximately independent. Assuming factorization holds separately for signal and background processes, the appearance of nontrivial correlations between low- and high-energy observables is a robust indicator of new physics. Under the most restrictive form of factorization, a machine-learned model trained to identify such correlations will in fact converge to the optimal new physics classifier. We test on a benchmark anomaly detection task for the Large Hadron Collider involving collimated sprays of particles called jets. By teasing out correlations between the kinematics and substructure of jets, our method can reliably extract percent-level signal fractions. This strategy for uncovering new physics adds to the growing toolbox of anomaly detection methods for collider physics with a complementary set of assumptions. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

Learning the factors controlling mineral dissolution in three-dimensional fracture networks: applications in geologic carbon sequestration

We perform a set of high-fidelity simulations of geochemical reactions within three-dimensional discrete fracture networks (DFN) and use various machine learning techniques to determine the primary factors controlling mineral dissolution. The DFN are partially filled with quartz that gradually dissolves until quasi-steady state conditions are reached. At this point, we measure the quartz remaining in each fracture within the domain as our primary quantity of interest. We observe that a primary sub-network of fractures exists, where the quartz has been fully dissolved out. This reduction in resistance to flow leads to increased flow channelization and reduced solute travel times. However, depending on the DFN topology and the rate of dissolution, we observe substantial variability in the volume of quartz remaining within fractures outside of the primary subnetwork. This variability indicates an interplay between the fracture network structure and geochemical reactions. We characterize the features controlling these processes by developing a machine learning framework to extract their relevant impact. Specifically, we use a combination of high-fidelity simulations with a graph-based approach to study geochemical reactive transport in a complex fracture network to determine the key features that control dissolution. We consider topological, geometric and hydrological features of the fracture network to predict the remaining quartz in quasi-steady state. We found that the dissolution reaction rate constant of quartz and the distance to the primary sub-network in the fracture network are the two most important features controlling the amount of quartz remaining. This study is a first step towards characterizing the parameters that control carbon mineralization using an approach with integrates computational physics and machine learning.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1983

NASA research in teleoperation and robotics

Increased automation is necessary in future NASA missions. Drivers for automation include constrained funding and physical resources as well as mission capabilities not achievable through conventional means. The application of emerging technology in manipulators and machine intelligence will enable the development of robotic devices remotely commanded by human operators to increase man's productivity in space. The Office of Aeronautics and Space Technology (OAST) has established a program for research in teleoperation and robotics. The program's near-term focus is a Remote Orbital Servicing System (ROSS). The longer range goals include: (1) basic research in autonomous operations, (2) human factors research on the man-machine interface to remote systems, and (3) system integration and analysis of advanced concepts. This paper reviews the current NASA research and technology and considers future work needed to meet the OAST goals.

Meintel, A. J., Jr.↗