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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 217 records · Page 12

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NASA NTRS1984

NASA: Model development for human factors interfacing

The results of an intensive literature review in the general topics of human error analysis, stress and job performance, and accident and safety analysis revealed no usable techniques or approaches for analyzing human error in ground or space operations tasks. A task review model is described and proposed to be developed in order to reduce the degree of labor intensiveness in ground and space operations tasks. An extensive number of annotated references are provided.

Smith, L. L.↗

DOE OSTI2024

Machine learning at the edge to improve in-field safeguards inspections

Artificial intelligence (AI) and machine learning (ML) are near-ubiquitous in day-to-day life; from cars with automated driver-assistance, recommender systems, generative content platforms, and large language chatbots. Implementing AI as a tool for international safeguards could significantly decrease the burden on safeguards inspectors and nuclear facility operators. The use of AI would allow inspectors to complete their in-field activities quicker, while identifying patterns and anomalies and freeing inspectors to focus on the uniquely human component of inspections. Sandia National Laboratories has spent the past two and a half years developing on-device machine learning to develop both a digital and robotic assistant. This combined platform, which we term inspecta, has numerous on-device machine learning capabilities that have been demonstrated at the laboratory scale. Here this work describes early successes implementing AI/ML capabilities to reduce the burden of tedious inspector tasks such as seal examination, information recall, note taking, and more.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2019

Parallel streaming between heterogeneous HPC resources for real-time analysis

Performing analysis or generating visualizations concurrently with high performance simulations can yield great benefits compared to post-processing data. Writing and reading large volumes of data can be reduced or eliminated, thereby producing an I/O cost savings. One such method for concurrent simulation and analysis is in transit - streaming data from the resource running the simulation to a separate resource running the analysis. In transit analysis can be beneficial since computational resources may not have certain resources needed for visualization and analysis (e.g. GPUs) and to reduce the impact of performing analysis tasks to the run time of the simulation. When sending and receiving data in transit, data redistribution mechanisms are needed in order to support heterogeneous data layouts that may be required by the simulation and analysis applications. The work described in this paper compares two mechanisms for on-the-fly data redistribution when streaming data in parallel between two distributed memory applications. Finally, our results show that it is often more advantageous to stream data in the same layout as the sender and redistribute data amongst processes on the receiving end than to stream data in the final layout needed by the receiver.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

A Machine Learning Framework for Predicting Microphysical Properties of Ice Crystals From Cloud Particle Imagery

The microphysical properties of ice crystals are important because they significantly alter the radiative properties and spatiotemporal distributions of clouds, which in turn strongly affect Earth's climate. However, it is challenging to measure key properties of ice crystals, such as mass or morphological features. Here, we present a proof-of-concept framework for predicting three-dimensional (3D) microphysical properties of ice crystals from in situ two-dimensional (2D) imagery. First, we computationally generated synthetic ice crystals using 3D modeling software along with geometric parameters estimated from the 2021 Ice Cryo-Encapsulation Balloon (ICEBall) field campaign. Then, we used synthetic crystals to train machine learning (ML) models to predict effective density ($ρ_e$), effective surface area ($A_e$), and number of bullets ($N_b$) from synthetic rosette imagery. On unseen synthetic images, our ML models accurately predicted ice crystal properties. ResNet-18 performed best, achieving $R^2$ values of 0.99 and 0.98 for $ρ_e$ and $A_e$, respectively, and MAE of 0.10 for mathematical equation in single view tasks. Stereo view ResNet-18 further reduced RMSE by 40% for $ρ_e$ and $A_e$ and reduced MAE by 0.08 for $N_b$. This work provides a novel ML-driven framework for estimating ice microphysical properties from in situ imagery, which will allow for downstream constraints on microphysical parameterizations, such as the mass-size relationship.

Ko, J. [Columbia Univ., New York, NY (United State↗

DOE OSTI2025

Solving tricky quantum optics problems with assistance from large language models

The capabilities of modern artificial intelligence (AI) as a “scientific collaborator” are explored by engaging it with three nuanced problems in quantum optics: state populations in optical pumping, resonant transitions between decaying states (the Burshtein effect), and degenerate mirrorless lasing. Through iterative dialogue, the authors observe that AI models–when prompted and corrected–can reason through complex scenarios, refine their answers, and provide expert-level guidance, closely resembling the interaction with an adept colleague. The findings highlight that AI can democratize access to sophisticated modeling and analysis, shifting the focus in scientific practice from technical mastery to the generation and testing of ideas, and reducing the time for completing research tasks from days to minutes.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2026

Data-driven Mori–Zwanzig modeling of Lagrangian particle dynamics in turbulent flows

The dynamics of Lagrangian particles in turbulence play a crucial role in mixing, transport, and dispersion in complex flows. Their trajectories exhibit highly nontrivial statistical behavior, motivating the development of surrogate models that can reproduce these trajectories without incurring the high computational cost of direct numerical simulations of the full Eulerian field. This task is particularly challenging because reduced-order models typically lack access to the full set of interactions with the underlying turbulent field. Novel data-driven machine learning techniques can be powerful in capturing and reproducing complex statistics of the reduced-order/surrogate dynamics. In this work, we show how one can learn a surrogate dynamical system that is able to evolve a turbulent Lagrangian trajectory in a way that is point-wise accurate for short-time predictions (with respect to Kolmogorov time) and stable and statistically accurate at long times. This approach is based on the Mori–Zwanzig formalism, which prescribes a mathematical decomposition of the full dynamical system into resolved dynamics that depend on the current state and the past history of a reduced set of observables, and the unresolved orthogonal dynamics due to unresolved degrees of freedom of the initial state. We show how by training this reduced order model on a point-wise error metric on short time-prediction, we are able to correctly learn the dynamics of Lagrangian turbulence, such that also the long-time statistical behavior is stably recovered at test time. This opens up a range of applications, for example, for the control of active Lagrangian agents in turbulence.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1977

Coordinated NASA nickel-cadmium battery technology program

This paper describes the NASA nickel-cadmium (Ni-Cd) battery technology program which is being coordinated by JPL to provide NASA and other users with lighter and/or longer-lived Ni-Cd cells for low-earth-orbit, geosynchronous-orbit, and planetary spacecraft missions in the 1980s. The goal is to double the energy density and/or life of the system. Failure modes and mechanisms are differentiated and discussed to point out the critical design variables which affect Ni-Cd cell life. Cell component weights are listed, approaches for reducing weight are discussed, and program tasks and schedules are presented. The nine major tasks being worked on by various organizations are described. Progress has been made in weight reduction, understanding of life reliability mechanisms, and development of a process for manufacturing more stable electrodes. An accelerated and predictive life test program is approximately 30% complete. It appears feasible to double the life and/or usable energy density of the Ni-Cd cell.

Bogner, R. S.↗

NASA NTRS1978

Solar cell workshop

The workshop addressed three issues in respect to the NASA solar cell technology requirements for future orbital missions. First, technology areas were identified that were considered most significant and the deficiencies and concerns that were had with each area are indicated. Second, the tasks that should be undertaken to reduce the costs and risks of future orbital power systems are recommended. Third, an attempt to identify the lowest priority items in the present program in terms of content and timing are made.

Ralph, E. L.↗

NASA NTRS1980

Parallel processing implementations of a contextual classifier for multispectral remote sensing data

Contextual classifiers are being developed as a method to exploit the spatial/spectral context of a pixel to achieve accurate classification. Classification algorithms such as the contextual classifier typically require large amounts of computation time. One way to reduce the execution time of these tasks is through the use of parallelism. The applicability of the CDC flexible processor system and of a proposed multimicroprocessor system (PASM) for implementing contextual classifiers is examined.

Siegel, H. J.↗

NASA NTRS1985

Active control technology experience with the Space Shuttle in the landing regime

An interesting description was provided of the development of the shuttle flight control systems. Of particular concern was a tendency to excite PIO during the landing phase. Both ground based and in-flight simulation were used to study the problem. It was found that in-flight simulation was the only reliable method to use in the study of PIO. Two of the major contributions to the PIO problem were found to be system time delay and the lack of a clear motion cue at the pilot's location following a pitch up command. The PIO problem was solved by reducing the demands of the piloting task and introducing an adaptive stick gain limiter.

Powers, B. G.↗

NASA NTRS1987

Asteroid families, dynamics and astrometry

The proper elements and family assignments for the 1227 Palomar-Leiden Survey asteroids of high quality were tabulated. In addition to the large table, there are also auxiliary tables of Mars crossers and commensurate objects, histograms of the proper element distributions, and a discussion. Probably the most important part of the discussion describes the Mars crossing boundary, how the closest distances of approach to Mars and Jupiter are calculated, and why the observed population of Mars crossers should bombard that planet episodically rather than uniformly. Analytical work was done to derive velocity distributions of family forming events from proper element distributions subject to assumptions which may be appropriate for cratering events. Software was developed for a microcomputer to permit plotting of the proper elements. Three orthogonal views are generated and stereo pairs can be printed when desired. This program was created for the study of asteroid families. The astrometry task is directed toward measuring and reducing positions on faint comets and the minor planets with less common orbits. The observational material is CCD frames taken with the Palomar 1.5 m telescope. Positions of 10 comets and 16 different asteroids were published on the Minor Planet Circulars.

Williams, J. G.↗

NASA NTRS1990

Effect of shaping sensor data on pilot response

The pilot of a modern jet aircraft is subjected to varying workloads while being responsible for multiple, ongoing tasks. The ability to associate the pilot's responses with the task/situation, by modifying the way information is presented relative to the task, could provide a means of reducing workload. To examine the feasibility of this concept, a real time simulation study was undertaken to determine whether preprocessing of sensor data would affect pilot response. Results indicated that preprocessing could be an effective way to tailor the pilot's response to displayed data. The effects of three transformations or shaping functions were evaluated with respect to the pilot's ability to predict and detect out-of-tolerance conditions while monitoring an electronic engine display. Two nonlinear transformations, on being the inverse of the other, were compared to a linear transformation. Results indicate that a nonlinear transformation that increases the rate-or-change of output relative to input tends to advance the prediction response and improve the detection response, while a nonlinear transformation that decreases the rate-of-change of output relative to input tends to lengthen the prediction response and make detection more difficult.

Bailey, Roger M.↗

NASA NTRS1991

Cockpit task management: A preliminary, normative theory

Cockpit task management (CTM) involves the initiation, monitoring, prioritizing, and allocation of resources to concurrent tasks as well as termination of multiple concurrent tasks. As aircrews have more tasks to attend to due to reduced crew sizes and the increased complexity of aircraft and the air transportation system, CTM will become a more critical factor in aviation safety. It is clear that many aviation accidents and incidents can be satisfactorily explained in terms of CTM errors, and it is likely that more accidents induced by poor CTM practice will occur in the future unless the issue is properly addressed. The first step in understanding and facilitating CTM behavior was the development of a preliminary, normative theory of CTM which identifies several important CTM functions. From this theory, some requirements for pilot-vehicle interfaces were developed which are believed to facilitate CTM. A prototype PVI was developed which improves CTM performance and currently, a research program is under way that is aimed at developing a better understanding of CTM and facilitating CTM performance through better equipment and procedures.

Funk, Ken↗

NASA NTRS1993

Operations automation using the Link Monitor and Control Operator Assistant

The Link Monitor and Control Operator Assistant (LMC OA) is a knowledge-based prototype system which uses AI techniques to provide semiautomated monitor and control functions to support operations of the Deep Space Network (DSN) 70-m antenna at the Goldstone Deep Space Communications Complex (DSCC). The manual and time-consuming process of configuring the 70-m antenna and its associated communications and processing equipment, known as precalibration, is an overhead activity; the time spent in precalibration is time which cannot be spent supporting actual mission operations. Therefore, the major goal of the LMC OA task is to demonstrate techniques that reduce precalibration time, decrease operations overhead, and increase the availability of this valuable and oversubscribed NASA resource. The LMC OA prototype was tested in a parallel, experimental mode at the Goldstone DSCC performing semiautomated precalibration using the actual operational equipment. This test demonstrated that a reduction of 40 percent in precalibration time can be achieved with the LMC OA prototype.

Lee, Lorrine F.↗

NASA NTRS1996

Mower/Litter Removal

The Burg Corporation needed to get more power out of the suction system in their Vac 'N Bag grass mower/litter remover. The president submitted a problem statement to the Marshall Space Flight Center Technology Transfer Office, which devised a way to guide heavier items of trash to a point where suction was greatest, and made changes to the impeller and the exhaust port, based on rocket propulsion technology. The improved system is used by highway departments, city governments and park authorities, reducing work time by combining the tasks of grass cutting and vacuuming trash and grass clippings.

Source record↗

NASA NTRS1994

Robotic Vehicle

A commercially available ANDROS Mark V-A robot was used by Jet Propulsion Laboratory (JPL) as the departure point in the development of the HAZBOT III, a prototype teleoperated mobile robot designed for response to emergencies. Teleoperated robots contribute significantly to reducing human injury levels by performing tasks too hazardous for humans. ANDROS' manufacturer, REMOTEC, Inc., in turn, adopted some of the JPL concepts, particularly the control panel. HAZBOT III has exceptional mobility, employs solid state electronics and brushless DC motors for safer operation, and is designed so combustible gases cannot penetrate areas containing electronics and motors. Other features include the six-degree-of-freedom manipulator, the 30-pound squeeze force parallel jaw gripper and two video cameras, one for general viewing and navigation and the other for manipulation/grasping.

Source record↗

NASA NTRS2009

High-Performance Algorithm for Solving the Diagnosis Problem

An improved method of model-based diagnosis of a complex engineering system is embodied in an algorithm that involves considerably less computation than do prior such algorithms. This method and algorithm are based largely on developments reported in several NASA Tech Briefs articles: The Complexity of the Diagnosis Problem (NPO-30315), Vol. 26, No. 4 (April 2002), page 20; Fast Algorithms for Model-Based Diagnosis (NPO-30582), Vol. 29, No. 3 (March 2005), page 69; Two Methods of Efficient Solution of the Hitting-Set Problem (NPO-30584), Vol. 29, No. 3 (March 2005), page 73; and Efficient Model-Based Diagnosis Engine (NPO-40544), on the following page. Some background information from the cited articles is prerequisite to a meaningful summary of the innovative aspects of the present method and algorithm. In model-based diagnosis, the function of each component and the relationships among all the components of the engineering system to be diagnosed are represented as a logical system denoted the system description (SD). Hence, the expected normal behavior of the engineering system is the set of logical consequences of the SD. Faulty components lead to inconsistencies between the observed behaviors of the system and the SD. Diagnosis the task of finding faulty components is reduced to finding those components, the abnormalities of which could explain all the inconsistencies. The solution of the diagnosis problem should be a minimal diagnosis, which is a minimal set of faulty components. The calculation of a minimal diagnosis is inherently a hard problem, the solution of which requires amounts of computation time and memory that increase exponentially with the number of components of the engineering system. Among the developments to reduce the computational burden, as reported in the cited articles, is the mapping of the diagnosis problem onto the integer-programming (IP) problem. This mapping makes it possible to utilize a variety of algorithms developed previously for IP to solve the diagnosis problem. In the IP approach, the diagnosis problem can be formulated as a linear integer optimization problem, which can be solved by use of well-developed integer-programming algorithms. This concludes the background information.

Fijany, Amir↗

NASA NTRS2005

Biased Randomized Algorithm for Fast Model-Based Diagnosis

A biased randomized algorithm has been developed to enable the rapid computational solution of a propositional- satisfiability (SAT) problem equivalent to a diagnosis problem. The closest competing methods of automated diagnosis are described in the preceding article "Fast Algorithms for Model-Based Diagnosis" and "Two Methods of Efficient Solution of the Hitting-Set Problem" (NPO-30584), which appears elsewhere in this issue. It is necessary to recapitulate some of the information from the cited articles as a prerequisite to a description of the present method. As used here, "diagnosis" signifies, more precisely, a type of model-based diagnosis in which one explores any logical inconsistencies between the observed and expected behaviors of an engineering system. The function of each component and the interconnections among all the components of the engineering system are represented as a logical system. Hence, the expected behavior of the engineering system is represented as a set of logical consequences. Faulty components lead to inconsistency between the observed and expected behaviors of the system, represented by logical inconsistencies. Diagnosis - the task of finding the faulty components - reduces to finding the components, the abnormalities of which could explain all the logical inconsistencies. One seeks a minimal set of faulty components (denoted a minimal diagnosis), because the trivial solution, in which all components are deemed to be faulty, always explains all inconsistencies. In the methods of the cited articles, the minimal-diagnosis problem is treated as equivalent to a minimal-hitting-set problem, which is translated from a combinatorial to a computational problem by mapping it onto the Boolean-satisfiability and integer-programming problems. The integer-programming approach taken in one of the prior methods is complete (in the sense that it is guaranteed to find a solution if one exists) and slow and yields a lower bound on the size of the minimal diagnosis. In contrast, the present approach is incomplete and fast and yields an upper bound on the size of the minimal diagnosis.

Williams, Colin↗