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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
NASA NTRS1954

Flight Tests of a Man Standing on a Platform Supported by a Teetering Rotor

Because previous flight tests of a man standing on a jet-supported platform were very successful, a series of flight tests were made to determine the flying qualities of a man standing on a platform supported by a teetering rotor. The rotor was 7 feet in diameter and was driven by air jets at the rotor tips fed by hollow blades and air hoses connected to an external air supply. The machine was tested with a free-teetering rotor and with a spring-restrained rotor, and, as an alternate arrangement, with the rotor and foot platform isolated from the framework by rubber connections to reduce the inertia of the moving parts. The machine was tested indoors in hovering and in limited translational flight and outdoors in light and in strong gusty winds. The stability and controllability with the spring-restrained rotor were uniformly good. The stability with the free-teetering rotor was marginal, but, when an experienced flyer placed his hands on a hand rail, the stability and controllability were good. The stability and controllability with the rubber-isolated frame and spring-restrained teetering rotor were very good and quite like the jet-supported platform.

Paul R Hill↗
NASA NTRS2019

Seeker Free-Flying Inspector GNC System Overview

Seeker is an ultra-low cost approach to highly automated extravehicular inspection of crewed or uncrewed spacecraft that has been designed and built in-house at the NASA Johnson Space Center (JSC). The first version of Seeker is intended to be an incremental development towards an advanced inspection capability. This effort builds on past free-flying inspector development efforts such as the Autonomous Extravehicular Activity Robotic Camera Sprint (AERCam Sprint) and Mini AERCam. Seeker was funded as an International Space Station (ISS) "X-by" Project, which required delivery of the vehicle approximately one year after authority to proceed and within the budget of $1.8 million. Seeker will fly onboard the NG-11 Cygnus mission in 2019 and will deploy after Cygnus' primary mission is completed. Seeker will perform inspection-like maneuvers within 50 meters of the target vehicle (Cygnus) and then dispose itself. The Seeker Guidance, Navigation, and Control (GNC) system is composed entirely of commercial off-the-shelf (COTS) and space-rated COTS items, an inertial-relative Multiplicative Extended Kalman Filter (MEKF), point-to-point guidance (with various additional modes such as stationkeeping), proportional-integral translational control, phase plane rotational control, and a state machine for automated mission moding with minimal ground input.

Navigation↗
NASA NTRS2000

New Web Server - the Java Version of Tempest - Produced

A new software design and development effort has produced a Java (Sun Microsystems, Inc.) version of the award-winning Tempest software (refs. 1 and 2). In 1999, the Embedded Web Technology (EWT) team received a prestigious R&D 100 Award for Tempest, Java Version. In this article, "Tempest" will refer to the Java version of Tempest, a World Wide Web server for desktop or embedded systems. Tempest was designed at the NASA Glenn Research Center at Lewis Field to run on any platform for which a Java Virtual Machine (JVM, Sun Microsystems, Inc.) exists. The JVM acts as a translator between the native code of the platform and the byte code of Tempest, which is compiled in Java. These byte code files are Java executables with a ".class" extension. Multiple byte code files can be zipped together as a "*.jar" file for more efficient transmission over the Internet. Today's popular browsers, such as Netscape (Netscape Communications Corporation) and Internet Explorer (Microsoft Corporation) have built-in Virtual Machines to display Java applets.

York, David W.↗
DOE OSTI2025

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗
NASA NTRS1991

Automated implementation of rule-based expert systems with neural networks for time-critical applications

In fault diagnosis, control and real-time monitoring, both timing and accuracy are critical for operators or machines to reach proper solutions or appropriate actions. Expert systems are becoming more popular in the manufacturing community for dealing with such problems. In recent years, neural networks have revived and their applications have spread to many areas of science and engineering. A method of using neural networks to implement rule-based expert systems for time-critical applications is discussed here. This method can convert a given rule-based system into a neural network with fixed weights and thresholds. The rules governing the translation are presented along with some examples. We also present the results of automated machine implementation of such networks from the given rule-base. This significantly simplifies the translation process to neural network expert systems from conventional rule-based systems. Results comparing the performance of the proposed approach based on neural networks vs. the classical approach are given. The possibility of very large scale integration (VLSI) realization of such neural network expert systems is also discussed.

Ramamoorthy, P. A.↗
NASA NTRS2001

Aspect-Oriented Programming

Computer science has experienced an evolution in programming languages and systems from the crude assembly and machine codes of the earliest computers through concepts such as formula translation, procedural programming, structured programming, functional programming, logic programming, and programming with abstract data types. Each of these steps in programming technology has advanced our ability to achieve clear separation of concerns at the source code level. Currently, the dominant programming paradigm is object-oriented programming - the idea that one builds a software system by decomposing a problem into objects and then writing the code of those objects. Such objects abstract together behavior and data into a single conceptual and physical entity. Object-orientation is reflected in the entire spectrum of current software development methodologies and tools - we have OO methodologies, analysis and design tools, and OO programming languages. Writing complex applications such as graphical user interfaces, operating systems, and distributed applications while maintaining comprehensible source code has been made possible with OOP. Success at developing simpler systems leads to aspirations for greater complexity. Object orientation is a clever idea, but has certain limitations. We are now seeing that many requirements do not decompose neatly into behavior centered on a single locus. Object technology has difficulty localizing concerns invoking global constraints and pandemic behaviors, appropriately segregating concerns, and applying domain-specific knowledge. Post-object programming (POP) mechanisms that look to increase the expressiveness of the OO paradigm are a fertile arena for current research. Examples of POP technologies include domain-specific languages, generative programming, generic programming, constraint languages, reflection and metaprogramming, feature-oriented development, views/viewpoints, and asynchronous message brokering. (Czarneclu and Eisenecker s book includes a good survey of many of these technologies).

Elrad, Tzilla↗
DOE OSTI2026

Cross-domain digital twin architecture for predictive maintenance via machine learning and Large Language Models

This research introduces a comprehensive framework for creating and deploying a digital twin platform for continuous monitoring and predictive maintenance within industrial settings. Through utilizing advanced technologies, including Unreal Engine 5, Unity 3D, the Message Queue Telemetry Transport protocol, Random Forest machine learning algorithms, and Large Language Models (LLMs), we establish a platform that digitally reproduces physical equipment and translates digital controls into real-world actions. This facilitates preventive maintenance approaches and improves operational effectiveness. The digital twin platform gathers sensor data from operational equipment, analyzes it using machine learning, and delivers practical insights to prevent potential malfunctions and enhance equipment performance. Furthermore, the incorporation of a web portal enables efficient monitoring and access to historical data, educational materials, and equipment status information. Preliminary findings indicate that digital twins can transform industrial equipment management and maintenance methodologies.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1988

Implementation of a hypersonic rarefied flow particle simulation on the Connection Machine

A very efficient direct particle simulation algorithm for hypersonic rarefied flows is presented and its implmentation on a Connection Machine is described. The implementation simulates ideal diatomic Maxwell molecules with three translational and two rotational degrees of freedom. Results for a 2-D simulation of supersonic flow over a 30 deg wedge are presented and used for validation.

Dagum, Leonardo↗
NASA NTRS1988

Symbolic derivation of material property matrices in finite element analysis

The principles and operation of MMAX, a symbolic-computation program which automates the process of generating property matrices for structural materials, are briefly described and illustrated with sample analyses of a rubberlike material and an elastoplastic material. MMAX is written in LISP under the symbolic finite-element generator FINGER and the general symbolic manipulator MACSYMA; it first derives the formulas required by mathematical manipulation, and then translates the formulas into FORTRAN code, adapted to the particular type of machine to be used for the numerical calculations. This approach is shown to combine efficiently the advantages of symbolic and numerical computation for engineering applications.

Tan, H. Q.↗
NASA NTRS1989

OMV mission simulator

The Orbital Maneuvering Vehicle (OMV) will be remotely piloted during rendezvous, docking, or proximity operations with target spacecraft from a ground control console (GCC). The real-time mission simulator and graphics being used to design a console pilot-machine interface are discussed. A real-time orbital dynamics simulator drives the visual displays. The dynamics simulator includes a J2 oblate earth gravity model and a generalized 1962 rotating atmospheric and drag model. The simulator also provides a variable-length communication delay to represent use of the Tracking and Data Relay Satellite System (TDRSS) and NASA Communications (NASCOM). Input parameter files determine the graphics display. This feature allows rapid prototyping since displays can be easily modified from pilot recommendations. A series of pilot reviews are being held to determine an effective pilot-machine interface. Pilots fly missions with nominal to 3-sigma dispersions in translational or rotational axes. Console dimensions, switch type and layout, hand controllers, and graphic interfaces are evaluated by the pilots and the GCC simulator is modified for subsequent runs. Initial results indicate a pilot preference for analog versus digital displays and for two 3-degree-of-freedom hand controllers.

Cok, Keith E.↗
NASA NTRS1989

Implementation of a hypersonic rarefied flow particle simulation on the Connection Machine

A very efficient direct particle simulation algorithm for hypersonic rarefied flows is presented and its implementation on a Connection Machine is described. The implementation simulates ideal diatomic Maxwell molecules with three translational and two rotational degrees of freedom. Results for a 2-D simulation of supersonic flow over a 30 deg wedge are presented and used for validation.

Dagum, Leonardo↗
NASA NTRSDate not supplied

Communication Network Awareness Machine System Phase I Development: The Intelligent Party-Line Schema

As NextGen continues toward the full implementation of a Net-Centric Architecture (N-CA)it will inherently provide a continuous increase to the Three-Vs components (Volume, Velocity, and Variety) of big data . This will create an insurmountable environment for direct-action aviation personnel (DAAP)as the DAAP’s natural abilities to manage and process data into actionable information will be overmatched by the Three-Vs. Therefore, conducting operations within a N-CA requires that new tools and applications be researched and developed to aid the DAAP’s ability to understand and manage data, mitigate non-normals, create contingency plans and actions. This paper will describe a research area at NASA Langley Research Center known as the Intelligent Party-Line (IPL).

Intelligent Party-Line↗
NASA NTRS2004

Using Ontologies to Formalize Services Specifications in Multi-Agent Systems

One key issue in multi-agent systems (MAS) is their ability to interact and exchange information autonomously across applications. To secure agent interoperability, designers must rely on a communication protocol that allows software agents to exchange meaningful information. In this paper we propose using ontologies as such communication protocol. Ontologies capture the semantics of the operations and services provided by agents, allowing interoperability and information exchange in a MAS. Ontologies are a formal, machine processable, representation that allows to capture the semantics of a domain and, to derive meaningful information by way of logical inference. In our proposal we use a formal knowledge representation language (OWL) that translates into Description Logics (a subset of first order logic), thus eliminating ambiguities and providing a solid base for machine based inference. The main contribution of this approach is to make the requirements explicit, centralize the specification in a single document (the ontology itself), at the same that it provides a formal, unambiguous representation that can be processed by automated inference machines.

Breitman, Karin Koogan↗
NASA NTRS2018

Towards Informing an Intuitive Mission Planning Interface for Autonomous Multi-Asset Teams via Image Descriptions

Establishing a basis for certification of autonomous systems using trust and trustworthiness is the focus of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Human-Machine Interface (HMI) team is working to capture and utilize the multitude of ways in which humans are already comfortable communicating mission goals and translate that into an intuitive mission planning interface. Several input/output modalities (speech/audio, typing/text, touch, and gesture) are being considered and investigated in the context human-machine teaming for the ATTRACTOR design reference mission (DRM) of Search and Rescue or (more generally) intelligence, surveillance, and reconnaissance (ISR). The first of these investigations, the Human Informed Natural-language GANs Evaluation (HINGE) data collection effort, is aimed at building an image description database to train a Generative Adversarial Network (GAN). In addition to building an image description database, the HMI team was interested if, and how, modality (spoken vs. written) affects different aspects of the image description given. The results will be analyzed to better inform the designing of an interface for mission planning.

Generative Adversarial Network (GAN)↗
DOE OSTI2025

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Machine learning for domain transfer between simulated and experimental 2D X-ray diffraction patterns using generative adversarial networks

X-ray diffraction (XRD) is a well-established technique for analyzing materials at an atomic level. Dynamic compression experiments (DCE), in which materials are subject to extreme pressures, can provide fundamental understanding to pressure-induced phase transitions and compression of the crystal lattice. The analysis of XRD patterns from highly compressed samples is non-trivial given the sparsity of data, high experimental costs, and the fact that the data is often marred with X-ray background and other artifacts. While accurate computational frameworks exist, they solve the forward problem—from structures and orientations to XRD patterns. Solving the inverse problem for 2D experimental diffraction patterns is currently a complex manual process of matching and comparing experimentally observed patterns to computationally generated ones. Machine learning is a promising tool for automating the matching process but often requires data-intensive architectures. Here, in this study, we use a CycleGAN to translate the domain of limited experimental data to a domain in which there is readily available simulated data. This domain shift allows data-intensive machine learning models that have only been trained on simulated XRD patterns to be used in the analysis of experiments.

Brozak, Samantha Jean [Sandia National Laboratorie↗
NASA NTRS1983

Retractable Rotating Door Latch

New mechanism turns door latch, latching or unlatching door, then retracts until latch is flush with surface of door frame. Concentric cylinders have cam grooves machined in surfaces. When rotated relative to each other cylinders impart rotation and translation to shaft of door latch. Motions may proceed separately or simultaneously.

Carsley, R. B.↗
NASA NTRS1993

Mechanical properties of composite materials

A composite material incorporates high strength, high modulus fibers in a matrix (polymer, metal, or ceramic). The fibers may be oriented in a manner to give varying in-plane properties (longitudinal, transverse-stress, strain, and modulus of elasticity). The lay-up of the composite laminates is such that a center line of symmetry and no bending moment exist through the thickness. The laminates are tabbed, with either aluminum or fiberglass, and are ready for tensile testing. The determination of the tensile properties of resin matrix composites, reinforced by continuous fibers, is outlined in ASTM standard D 3039, Tensile Properties of Oriented Fiber Composites. The tabbed flat tensile coupons are placed into the grips of a tensile machine and load-deformation curves plotted. The load-deformation data are translated into stress-strain curves for determination of mechanical properties (ultimate tensile strength and modulus of elasticity).

Thornton, H. Richard↗