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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1978

Geothermal systems

Several tasks of JPL related to geothermal energy are discussed. The major task is the procurement and test and evaluation of a helical screw drive (wellhead unit). A general review of geothermal energy systems is given. The presentation focuses attention on geothermal reservoirs in California, with graphs and charts to support the discussion. Included are discussions on cost analysis, systems maintenance, and a comparison of geothermal and conventional heating and cooling systems.

Mohl, C.↗
NASA NTRS1983

The dynamics and control of large flexible space structures, 6

The controls analysis based on a truncated finite element model of the 122m. Hoop/Column Antenna System focuses on an analysis of the controllability as well as the synthesis of control laws. Graph theoretic techniques are employed to consider controllability for different combinations of number and locations of actuators. Control law synthesis is based on an application of the linear regulator theory as well as pole placement techniques. Placement of an actuator on the hoop can result in a noticeable improvement in the transient characteristics. The problem of orientation and shape control of an orbiting flexible beam, previously examined, is now extended to include the influence of solar radiation environmental forces. For extremely flexible thin structures modification of control laws may be required and techniques for accomplishing this are explained. Effects of environmental torques are also included in previously developed models of orbiting flexible thin platforms.

Bainum, P. M.↗
NASA NTRS1983

Seismicity, fault plane solutions, depth of faulting, and active tectonics of the Andes of Peru, Ecuador, and southern Colombia

The long-period P waveforms observed for 17 earthquakes in the Peruvian Andes during 1963-1976 are compared with synthetic waveforms to obtain fault-plane solutions and focal depths. The morphological units of the Peruvian Andes are characterized: coastal plains, Cordillera Occidental, altiplano and central high plateau, Cordillera Oriental, and sub-Andes. The data base and analysis methodology are discussed, and the results are presented in tables, diagrams, graphs, maps, and photographs illustrating typical formations. Most of the earthquakes are shown to occur in the transition zone from the sub-Andes to the Cordillera Oriental under formations of about 1 km elevation at focal depths of 10-38 km. It is suggested that the sub-Andean earthquakes reflect hinterland deformation of a detached fold and thrust belt, perhaps like that which occurred in parts of the Canadian Rockies. From the total crustal shortening evident in Andean morphology and the shortening rate of the recent earthquakes it is estimated that the topography and crustal root of the Andes have been formed during the last 90-135 Myr.

Suarez, G.↗
NASA NTRS1986

Modeling of multi-rotor torsional vibrations in rotating machinery using substructuring

The application of FEM modeling techniques to the analysis of torsional vibrations in complex rotating systems is described and demonstrated, summarizing results reported by Soares (1985). A substructuring approach is used for determination of torsional natural frequencies and resonant-mode shapes, steady-state frequency-sweep analysis, identification of dynamically unstable speed ranges, and characterization of transient linear and nonlinear systems. Results for several sample problems are presented in diagrams, graphs, and tables. STORV, a computer code based on this approach, is in use as a preliminary design tool for drive-train torsional analysis in the High Altitude Wind Tunnel at NASA Lewis.

Soares, Fola R.↗
NASA NTRS1988

Wide binary stars at the Galactic poles

Results are reported from a search for high-Galactic-latitude wide binaries down to visual magnitude 14 on five digitized Schmidt-telescope plates. The data-reduction and analysis techniques are described in detail, and the results are presented in graphs and briefly characterized. The number of wide binaries and the estimated wide-binary number density are both three times smaller than those found by Bahcall and Soneira (1981), but still too large to be consistent with the predictions of physical models. Possible explanations for this discrepancy are explored.

Garnavich, Peter M.↗
NASA NTRS1991

Results from 13-cm absorptivity and H2SO4 abundance profiles from the Season 10 (1986) Pioneer Venus Orbiter radio occultation experiment

Results are reported from 13-cm radio-occultation absorptivity measurements of H2SO4 in the northern-hemisphere atmosphere of Venus, obtained by the Pioneer Venus Orbiter on 23 orbits during late 1986 and early 1987. The theoretical basis of the occultation measurements is explained; the error-analysis procedures are outlined; and the data are presented in tables and graphs. The abundance and distribution of gaseous H2SO4 in the equatorial zone (11-25 deg N) are found to be significantly different from those at latitudes above 36 deg N, and evidence for a reduction in H2SO4 abundance since the 1979 measurements is detected.

Jenkins, Jon M.↗
NASA NTRS1994

From conditional oughts to qualitative decision theory

The primary theme of this investigation is a decision theoretic account of conditional ought statements (e.g., 'You ought to do A, if C') that rectifies glaring deficiencies in classical deontic logic. The resulting account forms a sound basis for qualitative decision theory, thus providing a framework for qualitative planning under uncertainty. In particular, we show that adding causal relationships (in the form of a single graph) as part of an epistemic state is sufficient to facilitate the analysis of action sequences, their consequences, their interaction with observations, their expected utilities, and the synthesis of plans and strategies under uncertainty.

Pearl, Judea↗
NASA NTRS2003

Analysis of Return and Forward Links from STARS' Flight Demonstration 1

Space-based Telemetry And Range Safety (STARS) is a Kennedy Space Center (KSC) led proof-of-concept demonstration, which utilizes NASA's space network of Tracking and Data Relay Satellites (TDRS) as a pathway for launch and mission related information streams. Flight Demonstration 1 concluded on July 15,2003 with the seventh flight of a Low Power Transmitter (LPT) a Command and Data Handler (C&DH), a twelve channel GPS receiver and associated power supplies and amplifiers. The equipment flew on NASA's F-I5 aircraft at the Dryden Flight Research Center located at Edwards Air Force Base in California. During this NASA-ASEE Faculty Fellowship, the author participated in the collection and analysis of data from the seven flights comprising Flight Demonstration 1. Specifically, the author examined the forward and return links bit energy E(sub B) (in Watt-seconds) divided by the ambient radio frequency noise N(sub 0) (in Watts / Hertz). E(sub b)/N(sub 0) is commonly thought of as a signal-to-noise parameter, which characterizes a particular received radio frequency (RF) link. Outputs from the data analysis include the construction of time lines for all flights, production of graphs of range safety values for all seven flights, histograms of range safety E(sub b)/N(sub 0) values in five dB increments, calculation of associated averages and standard deviations, production of graphs of range user E(sub b)/N(sub 0) values for the all flights, production of graphs of AGC's and E(sub b)/N(sub 0) estimates for flight 1, recorded onboard, transmitted directly to the launch head and transmitted through TDRS. The data and graphs are being used to draw conclusions related to a lower than expected signal strength seen in the range safety return link.

Gering, James A.↗
NASA NTRS2011

Software Users Manual (SUM): Extended Testability Analysis (ETA) Tool

This software user manual describes the implementation and use the Extended Testability Analysis (ETA) Tool. The ETA Tool is a software program that augments the analysis and reporting capabilities of a commercial-off-the-shelf (COTS) testability analysis software package called the Testability Engineering And Maintenance System (TEAMS) Designer. An initial diagnostic assessment is performed by the TEAMS Designer software using a qualitative, directed-graph model of the system being analyzed. The ETA Tool utilizes system design information captured within the diagnostic model and testability analysis output from the TEAMS Designer software to create a series of six reports for various system engineering needs. The ETA Tool allows the user to perform additional studies on the testability analysis results by determining the detection sensitivity to the loss of certain sensors or tests. The ETA Tool was developed to support design and development of the NASA Ares I Crew Launch Vehicle. The diagnostic analysis provided by the ETA Tool was proven to be valuable system engineering output that provided consistency in the verification of system engineering requirements. This software user manual provides a description of each output report generated by the ETA Tool. The manual also describes the example diagnostic model and supporting documentation - also provided with the ETA Tool software release package - that were used to generate the reports presented in the manual

Maul, William A.↗
DOE OSTI2023

End-to-End Pipeline for Trigger Detection on Hit and Track Graphs

There has been a surge of interest in applying deep learning in particle and nuclear physics to replace labor-intensive offline data analysis with automated online machine learning tasks. This paper details a novel AI-enabled triggering solution for physics experiments in Relativistic Heavy Ion Collider and future Electron-Ion Collider. The triggering system consists of a comprehensive end-to-end pipeline based on Graph Neural Networks that classifies trigger events versus background events, makes online decisions to retain signal data, and enables efficient data acquisition. Here, the triggering system first starts with the coordinates of pixel hits lit up by passing particles in the detector, applies three stages of event processing (hits clustering, track reconstruction, and trigger detection), and labels all processed events with the binary tag of trigger versus background events. By switching among different objective functions, we train the Graph Neural Networks in the pipeline to solve multiple tasks: the edge-level track reconstruction problem, the edge-level track adjacency matrix prediction, and the graph-level trigger detection problem. We propose a novel method to treat the events as track-graphs instead of hit-graphs. This method focuses on intertrack relations and is driven by underlying physics processing. As a result, it attains a solid performance (around 72% accuracy) for trigger detection and outperforms the baseline method using hit-graphs by 2% higher accuracy.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Spatio-Temporal Denoising Graph Autoencoders with Data Augmentation for Missing Photovoltaic Data Imputation

The integration of the global Photovoltaic (PV) market with real time data-loggers has enabled large scale PV data analytical pipelines for power forecasting and long-term reliability assessment of PV fleets. Nevertheless, the performance of PV data analysis heavily depends on the quality of PV timeseries data. This paper proposes a novel Spatio-Temporal Denoising Graph Autoencoder (STD-GAE) framework to impute missing PV Power Data. STDGAE exploits temporal correlation, spatial coherence, and value dependencies from domain knowledge to recover missing data. It is empowered by two modules. (1) To cope with sparse yet various scenarios of missing data, STD-GAE incorporates a domain-knowledge aware data augmentation module that creates plausible variations of missing data patterns. This generalizes STD-GAE to robust imputation over different seasons and environment. (2) STD-GAE nontrivially integrates spatiotemporal graph convolution layers (to recover local missing data by observed “neighboring” PV plants) and denoising autoencoder (to recover corrupted data from augmented counterpart) to improve the accuracy of imputation accuracy at PV fleet level. We have evaluated our proposed model on two realworld PV datasets. Experimental results show that STD-GAE can achieve a gain of 43.14% in imputation accuracy and remains less sensitive to missing rate, different seasons, and missing scenarios, compared with state-of-the-art data imputation methods such as MIDA and LRTC-TNN.

Fan, Yangxin↗
NASA NTRS2013

Software Tools to Support the Assessment of System Health

This presentation provides an overview of three software tools that were developed by the NASA Glenn Research Center to support the assessment of system health: the Propulsion Diagnostic Method Evaluation Strategy (ProDIMES), the Systematic Sensor Selection Strategy (S4), and the Extended Testability Analysis (ETA) tool. Originally developed to support specific NASA projects in aeronautics and space, these software tools are currently available to U.S. citizens through the NASA Glenn Software Catalog. The ProDiMES software tool was developed to support a uniform comparison of propulsion gas path diagnostic methods. Methods published in the open literature are typically applied to dissimilar platforms with different levels of complexity. They often address different diagnostic problems and use inconsistent metrics for evaluating performance. As a result, it is difficult to perform a one ]to ]one comparison of the various diagnostic methods. ProDIMES solves this problem by serving as a theme problem to aid in propulsion gas path diagnostic technology development and evaluation. The overall goal is to provide a tool that will serve as an industry standard, and will truly facilitate the development and evaluation of significant Engine Health Management (EHM) capabilities. ProDiMES has been developed under a collaborative project of The Technical Cooperation Program (TTCP) based on feedback provided by individuals within the aircraft engine health management community. The S4 software tool provides a framework that supports the optimal selection of sensors for health management assessments. S4 is structured to accommodate user ]defined applications, diagnostic systems, search techniques, and system requirements/constraints. One or more sensor suites that maximize this performance while meeting other user ]defined system requirements that are presumed to exist. S4 provides a systematic approach for evaluating combinations of sensors to determine the set or sets of sensors that optimally meet the performance goals and the constraints. It identifies optimal sensor suite solutions by utilizing a merit (i.e., cost) function with one of several available optimization approaches. As part of its analysis, S4 can expose fault conditions that are difficult to diagnose due to an incomplete diagnostic philosophy and/or a lack of sensors. S4 was originally developed and applied to liquid rocket engines. It was subsequently used to study the optimized selection of sensors for a simulation ]based aircraft engine diagnostic system. The ETA Tool is a software ]based analysis tool that augments the testability analysis and reporting capabilities of a commercial ]off ]the ]shelf (COTS) package. An initial diagnostic assessment is performed by the COTS software using a user ]developed, qualitative, directed ]graph model of the system being analyzed. The ETA Tool accesses system design information captured within the model and the associated testability analysis output to create a series of six reports for various system engineering needs. These reports are highlighted in the presentation. The ETA Tool was developed by NASA to support the verification of fault management requirements early in the Launch Vehicle process. Due to their early development during the design process, the TEAMS ]based diagnostic model and the ETA Tool were able to positively influence the system design by highlighting gaps in failure detection, fault isolation, and failure recovery.

Melcher, Kevin J.↗
DOE OSTI2026

Vulcan-Forge: Architecture and Design of a Multi-Modal Forensic Analysis Plugin for CALDERA

Forge and VULCAN together describe an open-architecture cybersecurity analysis ecosystem that unifies forensic artifact processing, detection engineering, and vulnerability intelligence within integrated platforms. Forge operates as a plugin for MITRE CALDERA, ingesting diverse evidence formats—including EVTX, PCAP/PCAPNG, CSV, JSON, YAML, XML, binaries, and archives—to construct a unified artifact graph enriched with severity scoring, TLP classification, and audit trails. It provides subsystems for artifact parsing, streaming structured-data visualization, NetworkMiner-based packet inspection, PE/.NET binary analysis, and LLM-assisted triage and rule generation, with outputs validated against CCCS-YARA and pySigma schemas. VULCAN complements this by serving as a cybersecurity analyst platform that integrates a Neo4j knowledge graph, Qdrant vector retrieval, SSVC-based triage, and a local LLM to deliver CVE intelligence and forensic analysis through a multi-source ingest pipeline drawing from NVD, CISA KEV, EPSS, MITRE ATT&CK, and CAPEC. Together, they bridge structured threat intelligence with automated forensic analysis and detection workflows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Differentially Private Generation of Social Networks via Exponential Random Graph Models

Many social networks contain sensitive relational information. One approach to protect the sensitive relational information while offering flexibility for social network research and analysis is to release synthetic social networks at a pre-specified privacy risk level, given the original observed network. In this work, we propose the DP-ERGM procedure that synthesizes networks that satisfy the differential privacy (DP) via the exponential random graph model (EGRM). We apply DP-ERGM to a college student friendship network and compare its original network information preservation in the generated private networks with two other approaches: differentially private DyadWise Randomized Response (DWRR) and Sanitization of the Conditional probability of Edge given Attribute classes (SCEA). The results suggest that DP-EGRM preserves the original information significantly better than DWRR and SCEA in both network statistics and inferences from ERGMs and latent space models. In addition, DP-ERGM satisfies the node DP, a stronger notion of privacy than the edge DP that DWRR and SCEA satisfy.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

The dynamics and control of large flexible space structures-V

A general survey of the progress made in the areas of mathematical modelling of the system dynamics, structural analysis, development of control algorithms, and simulation of environmental disturbances is presented. The use of graph theory techniques is employed to examine the effects of inherent damping associated with LSST systems on the number and locations of the required control actuators. A mathematical model of the forces and moments induced on a flexible orbiting beam due to solar radiation pressure is developed and typical steady state open loop responses obtained for the case when rotations and vibrations are limited to occur within the orbit plane. A preliminary controls analysis based on a truncated (13 mode) finite element model of the 122m. Hoop/Column antenna indicates that a minimum of six appropriately placed actuators is required for controllability. An algorithm to evaluate the coefficients which describe coupling between the rigid rotational and flexible modes and also intramodal coupling was developed and numerical evaluation based on the finite element model of Hoop/Column system is currently in progress.

Bainum, P. M.↗
DOE OSTI2026

Classification of dynamical Lie algebras generated by spin interactions on undirected graphs

Dynamical Lie algebras (DLAs) are a versatile tool for various topics that span from the expressibility-trainability of variational quantum algorithms (VQAs), to simulation of many body Hamiltonians. Quantum gates and most of the Hamiltonians of interest consist of local interactions; therefore, the analysis of all possible DLAs generated by 1- and 2-local operators is crucial for quantum simulation and VQAs on current hardware. Previously in [R. Wiersema et al ., npj Quantum Inf. 10 , 110 (2024)], we analyzed the DLAs on linear, circular and all-to-all topologies, and obtained results about their dimensions and algebraic structure. Here, in this work, we extend our analysis into any possible hardware topology and provide a classification of all DLAs generated by Pauli strings on any undirected interaction graph. Our results indicate that the DLAs depend solely on whether the connectivity or interaction graph is bipartite or not. In addition, we find that the non-trivial polynomially scaling DLAs appear only on 1D line or circle topologies, and all other DLAs have dimensions scaling exponentially with the system size. Together with the current VQA literature, our results imply that either the majority of VQAs are non-trainable, or we are yet to understand the role of DLAs on the trainability of VQAs.

Algebraic structures↗
NASA NTRS1976

An analysis of the errors associated with the determination of atmospheric temperature from atmospheric pressure and density data

A graph was developed for relating delta T/T, the relative uncertainty in atmospheric temperature T, to delta p/p, the relative uncertainty in the atmospheric pressure p, for situations, when T is derived from the slope of the pressure-height profile. A similar graph relates delta T/T to delta roh/rho, the relative uncertainty in the atmospheric density rho, for those cases when T is derived from the downward integration of the density-height profile. A comparison of these two graphs shows that for equal uncertainties in the respective basic parameters, p or rho, smaller uncertainties in the derived temperatures are associated with density-height rather than with pressure-height data. The value of delta T/T is seen to depend not only upon delta p or delta rho, and to a small extent upon the value of T or the related scale height H, but also upon the inverse of delta h, the height increment between successive observations of p or rho. In the case of pressure-height data, delta T/T is dominated by 1/delta h for all values of delta h; for density-height data, delta T/T is dominated by delta rho/rho for delta h smaller than about 5 km. In the case of T derived from density-height data, this inverse relationship between delta T/T and delta h applies only for large values of delta h, that is, for delta h 35 km. No limit exists in the fineness of usable height resolution of T which may be derived from densities, while a fine height resolution in pressure-height data leads to temperature with unacceptably large uncertainties.

Minzner, R. A.↗
DOE OSTI2026

Phenomena-based graph representations and applications to chemical process simulation

Rapid and robust simulation of chemical processes is critical to conduct process design, optimization, techno-economic analysis, and sustainability analysis. Yet, efficiently solving simulation models remains a challenge due to the highly coupled and nonlinear nature of the underlying algebraic equations that capture the physical phenomena taking place in the process (e.g., material and energy conservation, phase equilibrium, reactions). In this work, we show that graph-theoretic representations of the physical phenomena within unit operations can help navigate and decompose equations to systematically identify alternative approaches for fast and robust numerical solutions. Specifically, we present a graph-theoretic abstraction that captures the connectivity between the model variables/equations and use this abstraction to group variables/equations into fundamental phenomena. We show that phenomena-based decomposition of the underlying equations can help decouple nonlinearities and enforce material/energy conservation at the process level to accelerate convergence. The proposed decomposition approach differs from the more traditional sequential modular simulation approach, in which equations are grouped and decomposed by unit operations. We implemented the phenomena-based decomposition in BioSTEAM—an open-source process simulation platform in Python—and demonstrated that this approach can converge a variety of separation process models. Compared to sequential modular simulation, the phenomena-based approach can converge idealized systems faster, but it can be slower for (or even fail to converge) highly coupled and nonideal process systems.

Convergence↗