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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Understanding the effect of density functional choice and van der Waals treatment on predicting the binding configuration, loading, and stability of amine-grafted metal organic frameworks

Metal organic frameworks (MOFs) are crystalline, three-dimensional structures with high surface areas and tunable porosities. Made from metal nodes connected by organic linkers, the exact properties of a given MOF are determined by node and linker choice. MOFs hold promise for numerous applications, including gas capture and storage. M2(4,4′-dioxidobiphenyl-3,3′-dicarboxylate)—henceforth simply M2(dobpdc), with M = Mg, Mn, Fe, Co, Ni, Cu, or Zn—is regarded as one of the most promising structures for CO2 capture applications. Further modification of the MOF with diamines or tetramines can significantly boost gas species selectivity, a necessity for the ultra-dilute CO2 concentrations in the direct-air capture of CO2. There are countless potential diamines and tetramines, paving the way for a vast number of potential sorbents to be probed for CO2 adsorption properties. The number of amines and their configuration in the MOF pore are key drivers of CO2 adsorption capacity and kinetics, and so a validation of computational prediction of these quantities is required to suitably use computational methods in the discovery and screening of amine-functionalized sorbents. In this work, we study the predictive accuracy of density functional theory and related calculations on amine loading and configuration for one diamine and two tetramines. In particular, we explore the Perdew–Burke–Ernzerhof (PBE) functional and its formulation for solids (PBEsol) with and without the Grimme-D2 and Grimme-D3 pairwise corrections (PBE+D2/3 and PBEsol+D2/3), two revised PBE functionals with the Grimme-D2 and Grimme-D3 pairwise corrections (RPBE+D2/3 and revPBE+D2/3), and the nonlocal van der Waals correlation (vdW-DF2) functional. We also investigate a universal graph deep learning interatomic potential’s (M3GNet) predictive accuracy for loading and configuration. These results allow us to identify a useful screening procedure for configuration prediction that has a coarse component for quick evaluation and a higher accuracy component for detailed analysis. Our general observation is that the neural network-based potential can be used as a high-level and rapid screening tool, whereas PBEsol+D3 gives a completely qualitatively predictive picture across all systems studied, and can thus be used for high accuracy motif predictions. We close by briefly exploring the predictions of relative thermal stability for the different functionals and dispersion corrections.

Chemistry↗
NASA NTRS1985

X-ray emission from cataclysmic variables with accretion disks. I - Hard X-rays. II - EUV/soft X-ray radiation

Theoretical models explaining the hard-X-ray, soft-X-ray, and EUV emission of accretion-disk cataclysmic variables in terms of the disk boundary layer (DBL) are developed on the basis of a survey of the published observational data. The data are compared with model predictions in graphs for systems with high or low (greater than or less than 10-Pg/s) accretion rates. Good agreement is obtained both at low accretion rates, where an optically thin rarefied hot (Te = 10 to the 8th K) DBL radiates most of its energy as hard X-rays, and at high accretion rates, where an optically thick 100,000-K DBL radiates most of its energy in the EUV and as soft X-rays. Detailed analysis of the old nova V603 Aql suggests that previous models predicting more detections of soft-X-ray/EUV emissions from thick-DBL objects (Ferland et al., 1982) used inappropriate dwarf masses, interstellar column densities, or classical-nova space densities.

Patterson, J.↗
DOE OSTI2019

Evaluating Time Varying Connectivities and System Throughput in Opportunistic Networks for Smart Grid Applications

With increasing proliferation of smart phones, there is an opportunity to employ mobile ad hoc networks to connect to distributed energy assets located in remote areas. With embedded intelligence and edge computing capabilities, autonomous ‘edge control nodes’ can enable a decentralized energy nexus, without the need for on-demand communications. Authors have developed an opportunistic networking framework using Bluetooth Low Energy and a specialized mobile phone application that enables delay tolerant networking for the above framework. Here, this paper presents the analysis of time varying graph connectivity for such an opportunistic mobile ad hoc network. Dependence of connectivity on different network parameters such as radio characteristics, the mobility of data mules and parameters governing how connections are established are explored. Simulation results showing the variation of above trends have been presented.

Bluetooth↗
NASA NTRS1996

Computational and Experimental Efforts in Gravity Probe B Microthruster Analysis

Gravity Probe B, an experiment to test the theory of relativity, will be launched near the turn of the millennium. Due to the precise pointing requirements need to successfully carry out this experiment, the satellite will use sixteen proportionally controlled microthrusters as a main component of the attitude control system. These microthrusters use the helium boil-off from the on-board dewar as propellant. Marshall Space Flight Center, verified the design of the thruster flow path by both computational and experimental methods. The flow performance of the thruster has been adequately characterized. Graphs show specific impulse, thrust coefficient, discharge coefficient, and mass flow rate trends. Value was added to the program through gained confidence in the design of the thruster and through valuation of some design trade-offs.

Droege, Alan↗
DOE OSTI2026

Designing the Protocols for Programmable Ammonia Catalysis

Programmable catalysis can provide a more energy-efficient and cost-effective route to enhancing commercial ammonia production, a key process in the advancement of renewable energy technologies and the manufacture of fertilizers and basic chemicals. This work explores the computational discovery of optimal forcing protocols to drive such dynamic catalysis models. By employing matrix-free time-stepper methods, coupled with an optimization approach, that integrates Bayesian optimization with a Bayesian continuation strategy to efficiently discover the periodic steady states of such periodically forced systems, we enable the discovery of complex optimal catalyst strain waveforms, while ensuring robust solver convergence. We demonstrate the flexibility of our approach to discover optimized forcing protocols under varying physical constraints on strain modulation or other catalyst operating parameters. We show that these can have a temporal structure more complex than simple step functions. In order to detect undesirable catalytic loops that may correlate with overall reduced performance, we perform a study using graph-theoretical analysis to investigate the dynamics of catalytic kinetic networks formed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Continuous Integration Service at Fermilab

This paper describes the current architecture of Continuous Integration (CI) service developed at Fermilab, encountered successes and difficulties, as well as future development plans. The current experiment code has hundreds of contributors that provide new features, bug fixes, and other improvements. Version control systems help developers to collaborate in contributing software for their experiments, while the CI system helps developers keep their code healthy. The Fermilab CI service allows experiments and projects to test and validate their offline production and analysis code on the supported platforms. It is built on top of Jenkins, designed to be set up from a configuration file that provides implementation for each phase of the CI workflow, and able to validate experiment code through grid jobs. This CI service provides a dashboard for easy access to logs and statistical graphs. Since the CI service has been adopted by Fermilab experiments/projects, it proved to be very useful to intercept issues in their code early on and get them fixed before running it in production. Currently the CI service is in use by the ArgoNeuT, DUNE, g-2, LArIAT, MINERvA, mu2e, NOvA, SBND and uBooNE experiments and by the following projects: ART and LArSoft software suites, GENIE, and Glidein-WMS. The CI service is under active development and planning to support code profiling.

Di benedetto, Vito↗
NASA NTRSDate not supplied

Machine Learning for the Validation of Expert-Elicited Causal Risk Diagrams

Exposure to spaceflight poses risk to human health in complex ways. To help manage this risk, the Human Systems Risk Board (HSRB) at the National Aeronautics and Space Administration (NASA) maintains a set of causal diagrams that attempt to explain how spaceflight hazards generate health risks and lead to adverse outcomes both in-mission, immediately post-mission, and over the long term. These causal risk diagrams are formulated as directed acyclic graphs (DAGs) and can function as knowledge graphs of connected risks and outcomes. These DAGs have proven useful for communication, and, through network analysis, have allowed for the identification of structurally important factors in the risk network. However, the utility these DAGs provide is directly proportional to their verisimilitude, making assessment of this trait using empirical data – whether from actual human spaceflight or various spaceflight analogue exposures and model organisms – a high priority. In this research we explore the use of machine learning algorithms to learn DAG structure from empirical data as a means of evaluating human-elicited DAG structures. To do so, we test several different graph structure-learning algorithms on data concerning changes in the bones of rats and mice after exposure to either spaceflight or a spaceflight analogue. We explore potential methods for indexing the similarity between each algorithm’s output DAG with all the others and with that of the expert-elicited DAG. We discuss next steps in this ongoing line of research and open science initiatives underway to complete them.

directed acyclic graphs↗
DOE OSTI2023

Causal interaction in high frequency turbulence at the biosphere–atmosphere interface: Structure–function coupling

At the biosphere–atmosphere interface, nonlinear interdependencies among components of an ecohydrological complex system can be inferred using multivariate high frequency time series observations. Information flow among these interacting variables allows us to represent the causal dependencies in the form of a directed acyclic graph (DAG). Here, we use high frequency multivariate data at 10 Hz from an eddy covariance instrument located at 25 m above agricultural land in the Midwestern US to quantify the evolutionary dynamics of this complex system using a sequence of DAGs by examining the structural dependency of information flow and the associated functional response. We investigate whether functional differences correspond to structural differences or if there are no functional variations despite the structural differences. We base our analysis on the hypothesis that causal dependencies are instigated through information flow, and the resulting interactions sustain the dynamics and its functionality. To test our hypothesis, we build upon causal structure analysis in the companion paper to characterize the information flow in similarly clustered DAGs from 3-min non-overlapping contiguous windows in the observational data. We characterize functionality as the nature of interactions as discerned through redundant, unique, and synergistic components of information flow. Through this analysis, we find that in turbulence at the biosphere–atmosphere interface, the variables that control the dynamic character of the atmosphere as well as the thermodynamics are driven by non-local conditions, while the scalar transport associated with CO and H 2 O is mainly driven by short-term local conditions.

58 GEOSCIENCES↗
DOE OSTI2015

Newberry Well 55-29 Stimulation Data 2014

The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to run for weeks and deliver large volumes of water at moderate well-head pressure. Second, to stimulate multiple zones, AltaRock developed thermo-degradable zonal isolation materials (TZIMs) to seal off fractures in a geothermal well to stimulate secondary and tertiary fracture zones. The TZIMs degrade within weeks, resulting in an optimized injection/ production profile of the entire well. Third, the project followed a project-specific Induced Seismicity Mitigation Plan (ISMP) to evaluate, monitor for, and mitigate felt induced seismicity. An initial stimulation was conducted in 2012 and continued for 7 weeks, with over 41,000 m3 of water injected. Further analysis indicated a shallow casing leak and an unstable formation in the open hole. The well was repaired with a shallow casing tieback and perforated liner in the open hole and re-stimulated in 2014. The second stimulation started September 23rd, 2014 and continued for 3 weeks with over 9,500 m3 of water injected. The well was treated with several batches of newly tested TZIM diverter materials and a newly designed Diverter Injection Vessel Assembly (DIVA), which was the main modification to the original injection system design used in 2012. A second round of stimulation that included two perforation shots and additional batches of TZIM was conducted on November 11th, 2014 for 9 days with an additional 4,000 m3 of water injected. The stimulations resulted in a 3-4 fold increase in injectivity, and PTS data indicates partial blocking and creation of flow zones near the bottom of the well. This submission includes all of the files and reports associated with the stimulation, pressure testing, and monitoring included in the scope of the project.

15 GEOTHERMAL ENERGY↗
DOE OSTI2013

Redeye: A Digital Library for Forensic Document Triage

Forensic document analysis has become an important aspect of investigation of many different kinds of crimes from money laundering to fraud and from cybercrime to smuggling. The current workflow for analysts includes powerful tools, such as Palantir and Analyst s Notebook, for moving from evidence to actionable intelligence and tools for finding documents among the millions of files on a hard disk, such as FTK. However, the analysts often leave the process of sorting through collections of seized documents to filter out the noise from the actual evidence to a highly labor-intensive manual effort. This paper presents the Redeye Analysis Workbench, a tool to help analysts move from manual sorting of a collection of documents to performing intelligent document triage over a digital library. We will discuss the tools and techniques we build upon in addition to an in-depth discussion of our tool and how it addresses two major use cases we observed analysts performing. Finally, we also include a new layout algorithm for radial graphs that is used to visualize clusters of documents in our system.

Bogen, Paul Logasa↗
NASA NTRS1973

Frequency modulation television analysis: Distortion analysis

Computer simulation is used to calculate the time-domain waveform of standard T-pulse-and-bar test signal distorted in passing through an FM television system. The simulator includes flat or preemphasized systems and requires specification of the RF predetection filter characteristics. The predetection filters are modeled with frequency-symmetric Chebyshev (0.1-db ripple) and Butterworth filters. The computer was used to calculate distorted output signals for sixty-four different specified systems, and the output waveforms are plotted for all sixty-four. Comparison of the plotted graphs indicates that a Chebyshev predetection filter of four poles causes slightly more signal distortion than a corresponding Butterworth filter and the signal distortion increases as the number of poles increases. An increase in the peak deviation also increases signal distortion. Distortion also increases with the addition of preemphasis.

Hodge, W. H.↗
DOE OSTI2022

Randomized Cholesky Preconditioning for Graph Partitioning Applications

A graph is a mathematical representation of a network; we say it consists of a set of vertices, which are connected by edges. Graphs have numerous applications in various fields, as they can model all sorts of connections, processes, or relations. For example, graphs can model intricate transit systems or the human nervous system. However, graphs that are large or complicated become difficult to analyze. This is why there is an increased interest in the area of graph partitioning, reducing the size of the graph into multiple partitions. For example, partitions of a graph representing a social network might help identify clusters of friends or colleagues. Graph partitioning is also a widely used approach to load balancing in parallel computing. The partitioning of a graph is extremely useful to decompose the graph into smaller parts and allow for easier analysis. There are different ways to solve graph partitioning problems. For this work, we focus on a spectral partitioning method which forms a partition based upon the eigenvectors of the graph Laplacian (details presented in Acer, et. al.). This method uses the LOBPCG algorithm to compute these eigenvectors. LOBPCG can be accelerated by an operator called a preconditioner. For this internship, we evaluate a randomized Cholesky (rchol) preconditioner for its effectiveness on graph partitioning problems with LOBPCG. We compare it with two standard preconditioners: Jacobi and Incomplete Cholesky (ichol). This research was conducted from August to December 2021 in conjunction with Sandia National Laboratories.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Probing solar system objects at infrared wavelengths

The instruments, techniques, and analysis methods employed in IR observations of solar-system objects are discussed and illustrated with sample data. Particular attention is given to (1) high-resolution (Doppler-limited) spectra of H2O in Comet Halley and Comet Wilson (1986l), obtained with the NASA Kuiper Airborne Observatory in 1985-1986, and (2) scanning observations of Jovian thermal emission, obtained with the NASA IRTF in 1987 and subjected to detailed time-series analysis to investigate atmospheric motion. The data are presented in spectra, energy-level diagrams, maps, and graphs and briefly characterized.

Mumma, M. J.↗
NASA NTRS1999

User's Manual for LINER: FORTRAN Code for the Numerical Simulation of Plane Wave Propagation in a Lined Two-Dimensional Channel

LINER is a system of Fortran 77 codes which performs a 2D analysis of acoustic wave propagation and noise suppression in a rectangular channel with a continuous liner at the top wall. This new implementation is designed to streamline the usage of the several codes making up LINER, resulting in a useful design tool. Major input parameters are placed in two main data files, input.inc and nurn.prm. Output data appear in the form of ASCII files as well as a choice of GNUPLOT graphs. Section 2 briefly describes the physical model. Section 3 discusses the numerical methods; Section 4 gives a detailed account of program usage, including input formats and graphical options. A sample run is also provided. Finally, Section 5 briefly describes the individual program files.

Reichert, R, S.↗
DOE OSTI2012

Network Intrusion Detection and Visualization using Aggregations in a Cyber Security Data Warehouse

The challenge of achieving situational understanding is a limiting factor in effective, timely, and adaptive cyber-security analysis. Anomaly detection fills a critical role in network assessment and trend analysis, both of which underlie the establishment of comprehensive situational understanding. To that end, we propose a cyber security data warehouse implemented as a hierarchical graph of aggregations that captures anomalies at multiple scales. Each node of our pro-posed graph is a summarization table of cyber event aggregations, and the edges are aggregation operators. The cyber security data warehouse enables domain experts to quickly traverse a multi-scale aggregation space systematically. We describe the architecture of a test bed system and a summary of results on the IEEE VAST 2012 Cyber Forensics data.

anomaly detection↗
NASA NTRS1990

Manned Mars System Study (MMSS): Mars transportation and facility infrastructure study. Volume 2: Technical report

The Manned Mars System Study (MMSS) was conducted for the Marshall Space Flight Center (MSFC) over the 35 month period between May 15, 1987 and April 30, 1990. During the course of the study, the NASA Office of Exploration (OEXP; Code Z) was created and MSFC was subsequently designated the Transportation Integration Agent (TIA) for support of the OEXP Mission Analysis and Systems Engineering (MASE) team. As a result of this action, modifications to the contract redirected the efforts to be consistent with NASA's overall objectives, including lunar transportation system design. A large number of written submittals were required in order to provide TIA support to MASE. A list summarizing the documents which have been prepared and delivered by Martin Marietta under this contract during the course of this work is presented. In nearly all cases, full sets of view-graphs were also provided to the MSFC COTR, and in several cases magnetic media were provided as well. To incorporate all of these materials (more than 2,000 pages) into the present report would obviously produce an extremely unwieldy and confusing document. Therefore, a summary of key findings are presented in this final report, supplemented by other material produced under this contract but not already available in the widespread literature.

Source record↗
DOE OSTI2025

Entropy-based feature selection for capturing impacts in Earth system models with abrupt forcing

This paper presents the development of a new entropy-based feature selection method for identifying and quantifying impacts. Here, impacts are defined as statistically significant differences in spatio-temporal fields when comparing datasets with and without an external forcing in an Earth system model. Temporal feature selection is performed by first computing the cross-fuzzy entropy to quantify similarity of patterns between two datasets and then applying changepoint detection to identify regions of statistically constant entropy. The method is used to capture temperate north surface cooling from a 9-member simulation ensemble of the Mt. Pinatubo volcanic eruption, which injected 10 Tg of SO 2 into the stratosphere. The results estimate a mean difference decrease in near surface air temperature of -0.560 K with a 99% confidence interval between -0.864 K and -0.257 K between April and November of 1992, one year following the eruption. A sensitivity analysis with decreasing SO 2 injection revealed that the impact is statistically significant at 5 Tg but not at 3 Tg. Using identified features, a dependency graph model based on a 9-day lag had significantly fewer nodes than a graph based on monthly means. Furthermore, this demonstrates our method’s ability to perform dimension reduction while still uncovering source-to-impact pathways.

Changepoint detection↗