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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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16 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

The Distributed Space Exploration Simulation (DSES)

The paper describes the Distributed Space Exploration Simulation (DSES) Project, a research and development collaboration between NASA centers which focuses on the investigation and development of technologies, processes and integrated simulations related to the collaborative distributed simulation of complex space systems in support of NASA's Exploration Initiative. This paper describes the three major components of DSES: network infrastructure, software infrastructure and simulation development. In the network work area, DSES is developing a Distributed Simulation Network that will provide agency wide support for distributed simulation between all NASA centers. In the software work area, DSES is developing a collection of software models, tool and procedures that ease the burden of developing distributed simulations and provides a consistent interoperability infrastructure for agency wide participation in integrated simulation. Finally, for simulation development, DSES is developing an integrated end-to-end simulation capability to support NASA development of new exploration spacecraft and missions. This paper will present current status and plans for each of these work areas with specific examples of simulations that support NASA's exploration initiatives.

Crues, Edwin Z.↗
NASA NTRS2007

An Overview of the Distributed Space Exploration Simulation (DSES) Project

This paper describes the Distributed Space Exploration Simulation (DSES) Project, a research and development collaboration between NASA centers which investigates technologies, and processes related to integrated, distributed simulation of complex space systems in support of NASA's Exploration Initiative. In particular, it describes the three major components of DSES: network infrastructure, software infrastructure and simulation development. With regard to network infrastructure, DSES is developing a Distributed Simulation Network for use by all NASA centers. With regard to software, DSES is developing software models, tools and procedures that streamline distributed simulation development and provide an interoperable infrastructure for agency-wide integrated simulation. Finally, with regard to simulation development, DSES is developing an integrated end-to-end simulation capability to support NASA development of new exploration spacecraft and missions. This paper presents the current status and plans for these three areas, including examples of specific simulations.

Crues, Edwin Z.↗
NASA NTRS2007

An Orion/Ares I Launch and Ascent Simulation: One Segment of the Distributed Space Exploration Simulation (DSES)

This paper describes the architecture and implementation of a distributed launch and ascent simulation of NASA's Orion spacecraft and Ares I launch vehicle. This simulation is one segment of the Distributed Space Exploration Simulation (DSES) Project. The DSES project is a research and development collaboration between NASA centers which investigates technologies and processes for distributed simulation of complex space systems in support of NASA's Exploration Initiative. DSES is developing an integrated end-to-end simulation capability to support NASA development and deployment of new exploration spacecraft and missions. This paper describes the first in a collection of simulation capabilities that DSES will support.

Chung, Victoria I.↗
NASA NTRS2007

A Coordinated Initialization Process for the Distributed Space Exploration Simulation (DSES)

This document describes the federate initialization process that was developed at the NASA Johnson Space Center with the HIIA Transfer Vehicle Flight Controller Trainer (HTV FCT) simulations and refined in the Distributed Space Exploration Simulation (DSES). These simulations use the High Level Architecture (HLA) IEEE 1516 to provide the communication and coordination between the distributed parts of the simulation. The purpose of the paper is to describe a generic initialization sequence that can be used to create a federate that can: 1. Properly initialize all HLA objects, object instances, interactions, and time management 2. Check for the presence of all federates 3. Coordinate startup with other federates 4. Robustly initialize and share initial object instance data with other federates.

Phillips, Robert↗
DOE OSTI2026

Hyaloscypha finlandica Metabolome Repository

This repository provides the curated data tables, manuscript figure and table exports, dependency records, and workflow scripts supporting an integrated comparative genomics and untargeted LC-MS/MS metabolomics analysis of Hyaloscypha finlandica strain PMI 746, a root-associated dark septate endophyte of poplar. The repository includes genome-mining summaries from antiSMASH, FunBGCeX, BGC-Prophet, and BiG-SCAPE; processed metabolomics inputs; metabolite annotation evidence; statistical outputs; and publication-facing figures and tables. Raw LC-MS/MS spectra, full genome/protein downloads, and large generated tool outputs are referenced through public archive/accession records and are not stored in Git.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Insight into a highly polymorphic endophyte isolated from the roots of the halophytic seepweed Suaeda salsa: Laburnicola rhizohalophila sp. nov. (Didymosphaeriaceae, Pleosporales)

In this work, we surveyed root endophytic fungi of the coastal halophyte Suaeda salsa and detected a population of a novel species that we described here as Laburnicola rhizohalophila sp. nov. No sexual sporulating structure was observed. Instead, it produced a large amount of thalloconidia, 0–1 transverse septa, hyaline to darkly pigmented, often peanut-shaped and sometimes dumbbell-shaped, both ends enlarged with numerous oil droplets inside the hyphal cells. Surprisingly, a high degree of phenotypic and physiological intraspecific variation (e.g., salinity tolerance, growth under different carbon:nitrogen ratios, and carbon utilization pattern) was recorded. The inoculation test indicated that the isolates could successfully infect host roots and form microsclerotia-like structures in cortical cells, a typical trait of dark septate endophytes (DSEs). Furthermore, most isolates were shown to promote host seedling growth. To evaluate conspecificity and infer its phylogenetic affinity, multiloci data including nuclear rRNA loci (ITS1 and 2, partial 28S), partial RNA Polymerase II second-largest subunit ( rpb2 ), and partial translation elongation factor-1α ( tef1 ) were characterized. Genealogical concordance phylogenetic species recognition (GCPSR) detected a genetically isolated clade of L. rhizohalophila within the Pleosporales in the Didymosphaeriaceae. Maximum likelihood phylogenetic reconstruction revealed that the endophytic fungus was genetically close to L aburnicola dactylidis but separated by a relatively long genetic distance. Our work highlights that the pleosporalean taxa might represent an underexplored reservoir of root DSEs.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2007

A Coordinated Initialization Process for the Distributed Space Exploration Simulation

A viewgraph presentation on the federate initialization process for the Distributed Space Exploration Simulation (DSES) is described. The topics include: 1) Background: DSES; 2) Simulation requirements; 3) Nine Step Initialization; 4) Step 1: Create the Federation; 5) Step 2: Publish and Subscribe; 6) Step 3: Create Object Instances; 7) Step 4: Confirm All Federates Have Joined; 8) Step 5: Achieve initialize Synchronization Point; 9) Step 6: Update Object Instances With Initial Data; 10) Step 7: Wait for Object Reflections; 11) Step 8: Set Up Time Management; 12) Step 9: Achieve startup Synchronization Point; and 13) Conclusions

Crues, Edwin Z.↗
NASA NTRS2007

Middleware Trade Study for NASA Domain

This presentation presents preliminary results of a trade study designed to assess three distributed simulation middleware technologies for support of the NASA Constellation Distributed Space Exploration Simulation (DSES) project and Test and Verification Distributed System Integration Laboratory (DSIL). The technologies are: the High Level Architecture (HLA), the Test and Training Enabling Architecture (TENA), and an XML-based variant of Distributed Interactive Simulation (DIS-XML) coupled with the Extensible Messaging and Presence Protocol (XMPP). According to the criteria and weights determined in this study, HLA scores better than the other two for DSES as well as the DSIL

Bowman, Dan↗
NASA NTRS2008

NASA Constellation Distributed Simulation Middleware Trade Study

This paper presents the results of a trade study designed to assess three distributed simulation middleware technologies for support of the NASA Constellation Distributed Space Exploration Simulation (DSES) project and Test and Verification Distributed System Integration Laboratory (DSIL). The technologies are the High Level Architecture (HLA), the Test and Training Enabling Architecture (TENA), and an XML-based variant of Distributed Interactive Simulation (DIS-XML) coupled with the Extensible Messaging and Presence Protocol (XMPP). According to the criteria and weights determined in this study, HLA scores better than the other two for DSES as well as the DSIL.

Hasan, David↗
DOE OSTI2020

Distinguishing Quarks and Gluons in Pion and Kaon PDFs

The leading-twist parton distribution functions of the pion and kwon are calculated for the first time using a rainbow-ladder truncation of QCD's Dyson-Schwinger equations (DSEs) that self-consistently sums all planar diagrams. The nonperturbative gluon dressing of the quarks is thereby correctly accounted for, which in practice means solving the inhomogeneous Bethe-Salpeter equation (BSE) for the quark operator that defines the spin-independent quark distribution functions. An immediate consequence of using this dressed vertex is that gluons carry 35% of the pion's and 30% of the kaon's light-cone momentum, with the remaining momentum carried by the quarks. The scale associated with these DSE results is μ 0 = 0.78 GeV. The gluon effects generated by the inhomogeneous BSE are inherently nonperturbative and cannot be mimicked by the perturbative QCD evolution equations. A key consequence of this gluon dressing is that the valence quarks have reduced support at low-to-intermediate x, where the gluons dominate, and increased support at large x. As a result, our DSE calculation of the pion's valence quark distribution is in excellent agreement with the Conway et al. pion-induced Drell-Yan data, but nevertheless exhibits the q π (x) similar or equal to (1 - x) 2 behavior as x -> 1 predicted by perturbative QCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation

This paper combines model-based and data-driven methods to develop a hierarchical, decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level and hence significantly speed up the computational time. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system, and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2006

Distributed Simulation for Space Exploration

This viewgraph presentation reviews the use of simulation and modeling in preparation for the planned exploration initiatives. The Exploration Systems Mission Directorate (EMSD) Integrated Modeling and Simulation (IM&S) team strategy encompasses a wide spectrum of simulation and modeling policies and technologies. One prominent technology is distributed simulation. The DIstributed Simulation (DIS),a collaborative simulation project with international participation (US and Japan) is reviewed as an example of distributed simulation development. The Distributed Space Exploration Simulation (DSES) is another example of distributed simulation that is described

Crues, Edwin Z.↗
NASA NTRS2009

A Process for Comparing Dynamics of Distributed Space Systems Simulations

The paper describes a process that was developed for comparing the primary orbital dynamics behavior between space systems distributed simulations. This process is used to characterize and understand the fundamental fidelities and compatibilities of the modeling of orbital dynamics between spacecraft simulations. This is required for high-latency distributed simulations such as NASA s Integrated Mission Simulation and must be understood when reporting results from simulation executions. This paper presents 10 principal comparison tests along with their rationale and examples of the results. The Integrated Mission Simulation (IMSim) (formerly know as the Distributed Space Exploration Simulation (DSES)) is a NASA research and development project focusing on the technologies and processes that are related to the collaborative simulation of complex space systems involved in the exploration of our solar system. Currently, the NASA centers that are actively participating in the IMSim project are the Ames Research Center, the Jet Propulsion Laboratory (JPL), the Johnson Space Center (JSC), the Kennedy Space Center, the Langley Research Center and the Marshall Space Flight Center. In concept, each center participating in IMSim has its own set of simulation models and environment(s). These simulation tools are used to build the various simulation products that are used for scientific investigation, engineering analysis, system design, training, planning, operations and more. Working individually, these production simulations provide important data to various NASA projects.

Cures, Edwin Z.↗
DOE OSTI2019

Application of the Koopman Operator-Theoretic Framework to Power System Dynamic State Estimation

Model-based and data-driven methods are combined to develop a hierarchical decentralized, robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level consists of robust, model-based, decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data-driven DSE. The proposed hybrid framework does not depend on the centralized infrastructure of the control centers; thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator locations. Also, the network model is not necessary; thus, a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on the 2,000-bus synthetic Texas system and shown to be capable of reconstructing the dynamic states of the generators with high accuracy, and of forecasting in the advent of missing data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A Hybrid Framework Combining Model-Based and Data-Driven Methods for Hierarchical Decentralized Robust Dynamic State Estimation: Preprint

This paper combines model-based and data-driven methods to develop a hierarchical decentralized robust dynamic state estimator (DSE). A two-level hierarchy is proposed, where the lower level is comprised of robust model-based decentralized DSEs. The state estimates sent from the lower level are received at the upper level, where they are filtered by a robust data- driven DSE, after a principled sparse selection. This selection allows us to shrink the dimension of the problem at the upper level, and hence to speed up the computational time significantly. The proposed hybrid framework does not depend upon the centralized infrastructure of the control centers, thus it can be completely embedded into the wide-area measurement systems. This feature will ultimately facilitate the placement of hierarchical decentralized control schemes at the phasor data concentrator (PDC) locations. Also, the network model is not necessary, thus a topology processor is not required. Finally, there is no assumption on the dynamics of the electric loads. The proposed framework is tested on a 2000-bus network.

24 POWER TRANSMISSION AND DISTRIBUTION↗