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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Fault-Tree Compiler Program

FTC, Fault-Tree Compiler program, is reliability-analysis software tool used to calculate probability of top event of fault tree. Five different types of gates allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language of FTC easy to understand and use. Program supports hierarchical fault-tree-definition feature simplifying process of description of tree and reduces execution time. Solution technique implemented in FORTRAN, and user interface in Pascal. Written to run on DEC VAX computer operating under VMS operating system.

Butler, Ricky W.↗
DOE OSTI2025

AmeriFlux US-TLR Timberlake Observatory for Wetland Restoration (TOWeR)

This is the AmeriFlux version of the carbon flux data for the site US-TLR Timberlake Observatory for Wetland Restoration (TOWeR). Site Description - This tower is located in Timberlake Forest, a restored forested wetland located 4 km from Albermarle Sound on the North Carolina coast. The forest to the south of the tower had historically been ditched, drained and converted to agricultural land, and subsequently reforested with Black Gum and Cypress trees and naturally re-wetted in 2006. This southern region has a bottomland forest ecosystem which saw a large-scale succession event of pine trees following the reforestation efforts. The northern part of the forest had been ditched, but never drained or converted for other land uses. It is much wetter and more sparsely vegetated when compared to the southern region, and has a mixed bottomland forest and swamp ecosystem.

Rey-Sanchez, Camilo [North Carolina State Universi↗
DOE OSTI2026

AmeriFlux FLUXNET-1F US-TLR Timberlake Observatory for Wetland Restoration (TOWeR)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-TLR Timberlake Observatory for Wetland Restoration (TOWeR). This is the FLUXNET version of the carbon flux data for the site US-TLR Timberlake Observatory for Wetland Restoration (TOWeR) produced by applying the standard ONEFlux (1F) software. Site Description - This tower is located in Timberlake Forest, a restored forested wetland located 4 km from Albermarle Sound on the North Carolina coast. The forest to the south of the tower had historically been ditched, drained and converted to agricultural land, and subsequently reforested with Black Gum and Cypress trees and naturally re-wetted in 2006. This southern region has a bottomland forest ecosystem which saw a large-scale succession event of pine trees following the reforestation efforts. The northern part of the forest had been ditched, but never drained or converted for other land uses. It is much wetter and more sparsely vegetated when compared to the southern region, and has a mixed bottomland forest and swamp ecosystem.

Rey-Sanchez, Camilo [North Carolina State Universi↗
DOE OSTI2024

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v1-2

This is the version 1-2 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments.L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds and out-of-service flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project**This dataset includes:- An overall dataset README file that describes the current version, gives citation and contact information, etc.- Site- and year-specific folders, each holding up to 12 CSV (comma separated value) data files for each site and plot in that year.- Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site.- Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes.Please see v1-2 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning.The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods.* Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021* TEMPEST 1: June 22, 2022* TEMPEST 2: June 6-7, 2023* TEMPEST 3: June 11-13, 2024

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 1 Sensor Data v2-1

This is the version 2-1 Level 1 (L1) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. L1 data are close to raw, but are units-transformed and have out-of-instrument-bounds, out-of-service, and outlier flags added. Duplicates and missing data are removed but otherwise these data are not filtered, and have not been subject to any additional algorithmic or human QA/QC. Any scientific analyses of L1 data should be performed with care. **This dataset will be updated quarterly with new data for the duration of the project** This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific CSV (comma separated value) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are normally logged every 15 minutes. Please see v2-1 TEMPEST L1 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024 This dataset was updated 2026-03-12: (i) data now go through 2025-12-31 (previous end was 2025-06-30) and (ii) dataset and file names updated to “…v2-1” (previously was “v2-0”).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Tree Inventory

This is the tree inventory (diameter, species, and live/dead status) data from the Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment is part of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field Measurements and Experiments; see https://compass.pnnl.gov/FME/COMPASSFME) project. It addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in eastern Maryland, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments.This dataset includes:- An overall dataset README file.- The tree inventory data in both "wide" and "long" forms. These contain the same information but are structured differently, with the former more useful for human viewers and the latter more amenable for programmatic analyses.- A key to the species/genus codes used, which follow the U.S. Department of Agriculture's PLANTS schema (https://plants.usda.gov/).- A copy of the R code used to generate the wide- and long-form data files.All files are comma-separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1971

Reliability computation using fault tree analysis

A method is presented for calculating event probabilities from an arbitrary fault tree. The method includes an analytical derivation of the system equation and is not a simulation program. The method can handle systems that incorporate standby redundancy and it uses conditional probabilities for computing fault trees where the same basic failure appears in more than one fault path.

Chelson, P. O.↗
DOE OSTI2026

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Level 2 Sensor Data v2-1

This is the version v2-1 Level 2 (L2) data release for COMPASS-FME environmental sensors located at our Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Level 2 (L2) data consist of sensor observations from the COMPASS-FME synoptic sites, TEMPEST, and DELUGE. Compared to the L1 data, these are more consistent (always 15-minute timestamps for the entire year); better QA/QC’d (out of bounds, out of service, and extreme outlier values are removed); and more complete, with a gap-filled time series available alongside the main observations, and additional derived (calculated) variables. L2 data are intended to be rapidly and easily usable in analyses and simulations. However, algorithmic outlier identification always carries the risk of removing valid data, and Level 1 data may be more suitable for analyses that focus on variability or extreme events. This dataset includes: - An overall dataset README file that describes the current version, gives citation and contact information, etc. - Site- and year-specific folders, each holding variable-specific Parquet (a high performance, space efficient format; see https://parquet.apache.org) data files for each site and plot in that year. - Metadata files within each site-year folder provide full information on data units, expected ranges, contact information, detailed flood times, as well as a general description of the site. - Environmental sensor types that appear in the data files include weather (ClimaVUE50, CS, RM Young, and LI instruments in the graphs below); soil conditions (TEROS12); soil redox state (Redox); groundwater variables (AquaTROLL200 and AquaTROLL600); open water sondes (Exo); tree sap velocity (Sapflow); and system voltage and state (Datalogger). Data are reported every 15 minutes. Please see v2-1 TEMPEST L2 Sensor Package Quick Start.pdf for detailed information on data package structure, temporal coverage, and versioning. Data files are in Apache Parquet, a high performance, space efficient format for tabular data. These files can be read using R's `arrow` package (https://arrow.apache.org/docs/r/), with similar tools available in other languages. The TEMPEST flood events occurred on the following dates. They lasted for ~10 hours each day and delivered ~80,000 gallons to each plot; many data streams are available at 1 or 5 minute frequency during these periods. * Tests: Aug 25 (fresh plot) and Sep 9 (salt plot), 2021 * TEMPEST 1: June 22, 2022 * TEMPEST 2: June 6-7, 2023 * TEMPEST 3: June 11-13, 2024

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATU↗
DOE OSTI2022

Search for flavor-changing neutral current interactions of the top quark and the Higgs boson decaying to a bottom quark-antiquark pair at $ \sqrt{s} $ = 13 TeV

A search for flavor-changing neutral current interactions of the top quark (t) and the Higgs boson (H) is presented. The search is based on a data sample corresponding to an integrated luminosity of 137 fb-1 recorded by the CMS experiment at the LHC in proton-proton collisions at √s = 13 TeV. Events containing exactly one lepton (muon or electron) and at least three jets, among which at least two are identified as originating from the hadronization of a bottom quark, are analyzed. A set of deep neural networks is used for kinematic event reconstruction, while boosted decision trees distinguish the signal from the background events. No significant excess over the background predictions is observed, and upper limits on the signal production cross sections are extracted. These limits are interpreted in terms of top quark decay branching fractions (B) to the Higgs boson and an up (u) or a charm quark (c). Assuming one nonvanishing extra coupling at a time, the observed (expected) upper limits at 95% confidence level are B(t → Hu) < 0.079 (0.11)% and B(t → Hc) < 0.094 (0.086)%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Attaining freshwater and estuarine-water soil saturation in an ecosystem-scale coastal flooding experiment

Abstract Coastal upland forests are facing widespread mortality as sea-level rise accelerates and precipitation and storm regimes change. The loss of coastal forests has significant implications for the coastal carbon cycle; yet, predicting mortality likelihood is difficult due to our limited understanding of disturbance impacts on coastal forests. The manipulative, ecosystem-scale Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in MD, USA. The experiment uses a large-unit (2000 m 2 ), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments. Transient saturation (5 h) of the entire soil rooting zone (0–30 cm) across a 2000 m 2 coastal forest was attained by delivering 300 m 3 of water through a spatially distributed irrigation network at a rate just above the soil infiltration rate. Our water delivery approach also elevated the water table (typically ~ 2 m belowground) and achieved extensive, low-level inundation (~ 8 cm standing water). A TEMPEST simulation approximated a 15-cm rainfall event and based on historic records, was of comparable intensity to a 10-year storm for the area. This characterization was supported by showing that Hurricane Ida’s (~ 5 cm rainfall) hydrologic impacts were shorter (40% lower duration) and less expansive (80% less coverage) than those generated through experimental manipulation. Future work will apply TEMPEST treatments to evaluate coastal forest resilience to changing hydrologic disturbance regimes and identify conditions that initiate ecosystem state transitions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Vermont & New Hampshire Ecological Forecasting: Monitoring Trends in Tree Defoliation Due to Lymantria dispar Outbreaks to Predict Future Hardwood Tree Mortality and Health Impacts

The invasive, herbivorous insect Lymantria dispar is a major defoliator of hardwood trees in the northeastern United States. Established populations of L. dispar typically rest at low levels but undergo recurring outbreaks that cause tree mortality if they occur in quick succession or are combined with other stressors on tree health. Widespread defoliation events disrupt local wildlife, economies, and livelihoods. Accurate monitoring of defoliation events is necessary to implement effective land management practices that support tree health. There are challenges to accurately monitoring L. dispar outbreaks that include the ephemeral character of defoliation disturbances and the difficulties of conducting large-scale surveys of L. dispar populations using existing aerial and ground-based data collection methods. To better monitor the impact of L. dispar on forests in Vermont and New Hampshire, the NASA DEVELOP team partnered with organizations responsible for supporting land and invasive species management including the Forest Ecosystem Monitoring Cooperative, the Vermont Agency of Agriculture, Food and Markets, the University of New Hampshire Cooperative Extension, and the New Hampshire Division of Forests and Lands, Forest Health Program. The team used NASA Earth observations collected by the Terra, Soil Moisture Active Passive (SMAP), Shuttle Radar Topography Mission (SRTM), Landsat 7, and Landsat 8 satellites along with ancillary datasets to map historical tree defoliation from 2012 to 2021. In support of partners’ future land management efforts, the team created a Google Earth Engine tool that displays annual defoliation extent.

Seamore Zhu↗
DOE OSTI2024

SULI Peer Review

Daniel Xing is a SULI intern whose project was titled: “An Improved Boosted Decision Tree Framework for Event Classification MicroBooNE” This is a physical subject that helps us understand how we can better model neutrinos. I do not study neutrinos, so listening to this talk was very formal.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1992

Object-Oriented Algorithm For Evaluation Of Fault Trees

Algorithm for direct evaluation of fault trees incorporates techniques of object-oriented programming. Reduces number of calls needed to solve trees with repeated events. Provides significantly improved software environment for such computations as quantitative analyses of safety and reliability of complicated systems of equipment (e.g., spacecraft or factories).

Patterson-Hine, F. A.↗
NASA NTRS2004

Managing Risk to Ensure a Successful Cassini/Huygens Saturn Orbit Insertion (SOI)

I. Design: a) S/C designed to be largely single fault tolerant; b) Operate in flight demonstrated envelope, with margin; and c) Strict compliance with requirements & flight rules. II. Test: a) Baseline, fault & stress testing using flight system testbeds (H/W & S/W); b) In-flight checkout & demos to remove first time events. III. Failure Analysis: a) Critical event driven fault tree analysis; b) Risk mitigation & development of contingencies. IV) Residual Risks: a) Accepted pre-launch waivers to Single Point Failures; b) Unavoidable risks (e.g. natural disaster). V) Mission Assurance: a) Strict process for characterization of variances (ISAs, PFRs & Waivers; b) Full time Mission Assurance Manager reports to Program Manager: 1) Independent assessment of compliance with institutional standards; 2) Oversight & risk assessment of ISAs, PFRs & Waivers etc.; and 3) Risk Management Process facilitator.

risk managment↗
DOE OSTI2024

Development and Validation of a Probabilistic Risk Assessment Model for a Generic Modular High Temperature Gas-Cooled Reactor

This study looks to develop and validate a probabilistic risk assessment (PRA) model for the modular high temperature gas-cooled reactor (MHTGR) using INL’s Systems Analysis Programs for Hands-on Integrated Reliability Evaluations (SAPHIRE) software. Validation against a General Atomics design involves matching event and fault trees to historical frequencies, with a goal of under 15% difference. The research aims to deliver a reliable PRA model to assess the safety of MHTGRs for use within high-temperature industrial applications.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Advancing Multi-Hazard Risk and Safety Considerations for Aging Nuclear Facilities

While probabilistic risk assessment (PRA) of nuclear facilities is expected to include internal and external hazards for a risk-informed and performance-based design, the current state of practice treats each hazard independently. However, such an independent treatment of hazards may not account for the correlations between different hazards and their response of and damage to the structures, systems, and components (SSCs) in a plant resulting in underestimating the overall risk. This project proposes to advance the multi-hazard PRA of nuclear facilities to more adequately evaluate concurrent hazards and contribute to an increased safety of nuclear plants. A framework for multi-hazard PRA will be developed by identifying concurrent hazard events (both internal and external) and event sequences that include interdependencies through the response of SSCs. An example application of the multi-hazard PRA framework will be demonstrated by considering a generic pressurized water reactor (PWR) subjected to seismic and internal flooding hazards. Computational models for the response of components will be developed to generated multi-hazard fragility surfaces under seismic and flooding loads. A PRA model consisting of event and fault trees will also be developed to quantify the multi-hazard risk profile and compare it with the independent hazard risk profile. Overall, by advancing the multi-hazard PRA of nuclear facilities, this project enhances nuclear safety and reduces costs by mitigating unforeseen consequences caused by correlations between concurrent hazards.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2022

SNAD transient miner: Finding missed transient events in ZTF DR4 using k-D trees

Here we report the automatic detection of 11 transients (7 possible supernovae and 4 active galactic nuclei candidates) within the Zwicky Transient Facility fourth data release (ZTF DR4), all of them observed in 2018 and absent from public catalogs. Among these, three were not part of the ZTF alert stream. Our transient mining strategy employs 41 physically motivated features extracted from both real light curves and four simulated light curve models (SN Ia, SN II, TDE, SLSN-I). These features are input to a k-D tree algorithm, from which we calculate the 15 nearest neighbors. After pre-processing and selection cuts, our dataset contained approximately a million objects among which we visually inspected the 105 closest neighbors from seven of our brightest, most well-sampled simulations, comprising 89 unique ZTF DR4 sources. Our result illustrates the potential of coherently incorporating domain knowledge and automatic learning algorithms, which is one of the guiding principles directing the SNAD team. It also demonstrates that the ZTF DR is a suitable testing ground for data mining algorithms aiming to prepare for the next generation of astronomical data.

79 ASTRONOMY AND ASTROPHYSICS↗