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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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-D-9A-01: Listmode-Driven Optimal Gating (OG) Respiratory Motion Management: Potential Impact On Quantitative PET Imaging

Purpose: To evaluate the potential impact of listmode-driven amplitude based optimal gating (OG) respiratory motion management technique on quantitative PET imaging. Methods: During the PET acquisitions, an optical camera tracked and recorded the motion of a tool placed on top of patients' torso. PET event data were utilized to detect and derive a motion signal that is directly coupled with a specific internal organ. A radioactivity-trace was generated from listmode data by accumulating all prompt counts in temporal bins matching the sampling rate of the external tracking device. Decay correction for 18F was performed. The image reconstructions using OG respiratory motion management technique that uses 35% of total radioactivity counts within limited motion amplitudes were performed with external motion and radioactivity traces separately with ordered subset expectation maximization (OSEM) with 2 iterations and 21 subsets. Standard uptake values (SUVs) in a tumor region were calculated to measure the effect of using radioactivity trace for motion compensation. Motion-blurred 3D static PET image was also reconstructed with all counts and the SUVs derived from OG images were compared with SUVs from 3D images. Results: A 5.7 % increase of the maximum SUV in the lesion was found for optimal gating image reconstruction with radioactivity trace when compared to a static 3D image. The mean and maximum SUVs on the image that was reconstructed with radioactivity trace were found comparable (0.4 % and 4.5 % increase, respectively) to the values derived from the image that was reconstructed with external trace. Conclusion: The image reconstructed using radioactivity trace showed that the blurring due to the motion was reduced with impact on derived SUVs. The resolution and contrast of the images reconstructed with radioactivity trace were comparable to the resolution and contrast of the images reconstructed with external respiratory traces. Research supported by Siemens.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1991

Gamma-ray bursts from colliding strange stars

The rate of collisions between the neutron stars is about 0.0001/yr in the galaxy and about 0.00001/yr within the Hubble distance. The collisions are the final phases of binary orbit decay driven by gravitational radiation and may produce gamma-ray bursts detectable at extragalactic distances. If strange stars exist then their collisions must release about 10 to the 50th ergs in gamma rays over 0.2 s. Such events should be detectable out to 1 Gpc with the current instruments. The distance to the majority of gamma-ray bursts is not known at this time. The Burst and Transient Source Experiment (BATSE) on Gamma Ray Observatory should determine the distance scale by determining the angular distribution of very weak bursts. If the majority of gamma-ray bursts turn out to be extragalactic, and if their distances are about 1 Gpc, then the collisions between strange stars may be the least speculative events that might account for so energetic bursts.

Haensel, P.↗
NASA NTRS1995

Radio jet propagation and wide-angle tailed radio sources in merging galaxy cluster environments

The intracluster medium (ICM) within merging clusters of galaxies is likely to be in a violent or turbulent dynamical state which may have a significant effect on the evolution of cluster radio sources. We present results from a recent gas + N-body simulation of a cluster merger, suggesting that mergers can result in long-lived, supersonic bulk flows, as well as shocks, within a few hundred kiloparsecs of the core of the dominant cluster. These results have motivated our new two-dimensional and three-dimensional simulations of jet propagation in such environments. The first set of simulations models the ISM/ICM transition as a contact discontinuity with a strong velocity shear. A supersonic (M(sub j) = 6) jet crossing this discontinuity into an ICM with a transverse, supersonic wind bends continuously, becomes 'naked' on the upwind side, and forms a distended cocoon on the downwind side. In the case of a mildly supersonic jet (M(sub j) = 3), however, a shock is driven into the ISM and ISM material is pulled along with the jet into the ICM. Instabilities excited at the ISM/ICM interface result in the jet repeatedly pinching off and reestablishing itself in a series of 'disconnection events.' The second set of simulations deals with a jet encountering a shock in the merging cluster environment. A series of relatively high-resolution two-dimensional calculations is used to confirm earlier analysis predicting that the jet will not disrupt when the jet Mach number is greater than the shock Mach number. A jet which survives the encounter with the shock will decrease in radius and disrupt shortly thereafter as a result of the growth of Kelvin-Helmholtz instabilities. We also find, in disagreement with predictions, that the jet flaring angle decreases with increasing jet density. Finally, a three-dimensional simulation of a jet crossing an oblique shock gives rise to a morphology which resembles a wide-angle tailed radio source with the jet flaring at the shock and disrupting to form a long, turbulent tail which is dragged downstream by the preshock wind.

Loken, Chris↗
NASA NTRS2000

The Precambrian Biogeochemical Carbon Isotopic Record: Contributions of Thermal Versus Biological Processes

Superplumes offer a new approach for understanding global C cycles. Isotopes help to discern the impacts of geological, environmental and biological processes ujpun the evolution of these cycles. For example, C-13/C-12 values of coeval sedimentary organics and carbonates give global estimates of the fraction of C buried as organics (Forg), which today lies near 0.2. Before Oxygenic photosynthesis arose, our biosphere obtained reducing power for biosynthesis solely from thermal volatiles and rock alteration. Thus Forg was dominated by the mantle redox state, which has remained remarkably constant for greater than Gy. Recent data confirm that the long-term change in Forg had been small, indicating that the mantle redox buffer remains important even today. Oxygenic photosynthesis enabled life to obtain additional reducing power by splitting the water molecule. Accordingly, biological organic production rose above the level constrained by the mantle-derived flux of reduced species. For example, today, chemoautotrophs harvesting energy from hydrothermal emanations can synthesize at most between 0.2 x 10(exp 12) and 2x 10(exp 12) mol C yr-1 of organic C globally. In contrast, global photosynthetic productivity is estimated at 9000 x 10(exp 12) mol C yr-1. Occasionally photosynthetic productivity did contribute to dramatically -elevated Forg values (to 0.4 or more) as evidenced by very high carbonate C-13/C-12. The interplay between biological, tectonic and other environmental factors is illustrated by the mid-Archean to mid-Proterozoic isotopic record. The relatively constant C-13/C-12 values of Archean carbonates support the view that photosynthetically-driven Forg increases were not yet possible. In contrast, major excursions in C-13/C-12, and thus also in Forg, during the early Proterozoic confirmed the global importance of oxygenic photosynthesis by that time. Remarkably, the superplume event at 1.9 Ga did not trigger another major Forg increase, despite the favorable conditions for organic burial that were evidenced by elevated sea levels and higher black shale abundances. Perhaps those superplume-rated processes that favored enhanced organic burial were offset by the ability of mantle-derived redox buffering, which was enhanced during the superplume event, to limit excursions in Forg.

DesMarais, David J.↗
NASA NTRS2002

Tensile stress stimulates microtubule outgrowth in living cells

Cell motility is driven by the sum of asymmetric traction forces exerted on the substrate through adhesion foci that interface with the actin cytoskeleton. Establishment of this asymmetry involves microtubules, which exert a destabilising effect on adhesion foci via targeting events. Here, we demonstrate the existence of a mechano-sensing mechanism that signals microtubule polymerisation and guidance of the microtubules towards adhesion sites under increased stress. Stress was applied either by manipulating the body of cells moving on glass with a microneedle or by stretching a flexible substrate that cells were migrating on. We propose a model for this mechano-sensing phenomenon whereby microtubule polymerisation is stimulated and guided through the interaction of a microtubule tip complex with actin filaments under tension.

NASA Discipline Cell Biology↗
NASA NTRS2006

Agent-Based Simulations of Malaria Transmissions with Applications to a Study Site in Thailand

The dynamics of malaria transmission are driven by environmental, biotic and socioeconomic factors. Because of the geographic dependency of these factors and the complex interactions among them, it is difficult to generalize the key factors that perpetuate or intensify malaria transmission. Methods: Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. Meteorological and environmental parameters may be derived from satellite data. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. Results: Three years of transmissions of vivax and falciparum malaria were simulated for a hypothetical hamlet with approximately 1/7 of the study site population. The model generated results for a number of scenarios, including applications of larvicide and insecticide, asymptomatic cases receiving or not receiving treatment, blocking malaria transmission in mosquito vectors, and increasing the density of farm (host) animals in the hamlet. Transmission characteristics and trends in the simulated results are comparable to actual data collected at the study site.

Kiang, Richard K.↗
NASA NTRS2018

NU-WRF Development and Support at NASA GSFC

The NASA Unified WRF modeling system (NU-WRF) is an observation driven framework that combines WRF-ARW with Goddard developed radiation, microphysics, aerosols and land information system (LIS) packages. NU-WRF can be used for simulating aerosols and land use effects on a variety of weather events. This poster will present a description of the modeling system including updates and future plans.

Cruz, Carlos A.↗
DOE OSTI2019

Using Machine Learning to Discern Eruption in Noisy Environments: A Case Study Using CO2-Driven Cold-Water Geyser in Chimayó, New Mexico

In this paper, we present an approach based on machine learning (ML) to distinguish eruption and precursory signals of Chimayó geyser (New Mexico, U.S.A.) under noisy environmental conditions. This geyser can be considered a natural analog of CO 2 intrusion into shallow water aquifers. By studying this geyser, we can understand upwelling of CO 2 -rich fluids from depth, which has relevance to leak monitoring in a CO 2 sequestration project. ML methods such as random forests (RFs) are known to be robust multiclass classifiers and perform well under unfavorable, noisy conditions. However, the extent of the RF method’s accuracy is poorly understood for this CO 2 -driven geysering application. The current study aims to quantify the performance of RF classifiers to discern the geyser state. Toward this goal, we first present the data collected from the seismometer that is installed near the Chimayó geyser. The seismic signals collected at this site contain different types of noises such as daily temperature variations, animal movement near the geyser, and human activity. First, we filter the signals from these noises by combining the Butterworth high-pass (BH) filter and an autoregressive (AR) method in a multilevel fashion. We show that by combining these filtering techniques in a hierarchical fashion leads to a reduction in noise in the seismic data without removing the precursors and eruption event signals. We then use RF on the filtered data to classify the state of geyser into three classes: remnant noise, precursor, and eruption states. RF classifier is constructed based on the comprehensive features extracted using the Tsfresh Python package. We show that the classification accuracy using RF on the filtered data is greater than 90%. We also evaluate the accuracy of other classical time-series methods such as dynamic time warping (DTW) on filtered data along with RF on partially filtered data in which we remove the daily trends. Classification accuracy shows that DTW performs poorly (44%) and RF on partially filtered data performs decently (87%). Denoising seismic signals from both daily trends and human activity enhances RF classifier performance by 7%. Finally, these aspects make the proposed ML framework attractive for event discrimination and signal enhancement under noisy conditions, with strong potential for application to monitor leaks in CO 2 sequestration.

58 GEOSCIENCES↗
DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Climatology and surface impacts of atmospheric rivers on West Antarctica

Abstract. Atmospheric rivers (ARs) transport large amounts of moisture from the mid- to high-latitudes and they are a primary driver of the most extreme snowfall events, along with surface melting, in Antarctica. In this study, we characterize the climatology and surface impacts of ARs on West Antarctica, focusing on the Amundsen Sea Embayment and Marie Byrd Land. First, we develop a climatology of ARs in this region, using an Antarctic-specific AR detection tool combined with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) atmospheric reanalyses. We find that while ARs are infrequent (occurring 3 % of the time), they cause intense precipitation in short periods of time and account for 11 % of the annual surface accumulation. They are driven by the coupling of a blocking high over the Antarctic Peninsula with a low-pressure system known as the Amundsen Sea Low. Next, we use observations from automatic weather stations on Thwaites Eastern Ice Shelf with the firn model SNOWPACK and interferometric reflectometry (IR) to examine a case study of three ARs that made landfall in rapid succession from 2 to 8 February 2020, known as an AR family event. While accumulation dominates the surface impacts of the event on Thwaites Eastern Ice Shelf (> 100 kg m−2 or millimeters water equivalent), we find small amounts of surface melt as well (< 5 kg m−2). The results presented here enable us to quantify the past impacts of ARs on West Antarctica's surface mass balance (SMB) and characterize their interannual variability and trends, enabling a better assessment of future AR-driven changes in the SMB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Bulk cloud microphysical properties as seen from numerical simulation and remote sensing products: case study of a hailstorm event over the La Plata Basin

Hailstorms develop over the La Plata Basin, in south-eastern South America, more often during later winter and early austral spring, between September and October. These systems have significant socioeconomic impacts over the region. Thus, a better understanding of how atmospheric drivers modulate the formation of hailstorms is important to improve the forecast of such phenomena. In this study, we selected a hailstorm event observed over the eastern La Plata Basin during 14–15 July 2016 to evaluate the performance of the Brazilian developments on the Regional Atmospheric Modelling System (BRAMS) model. The ability of the model in simulating cloud microphysical properties was evaluated by comparing simulations driven by different global forcings against in situ and remote sensing observations. The model results showed good skill in capturing the basic characteristics of the thunderstorm, particularly in terms of the spatial distribution of hydrometeors. The simulated spatial distribution of hail covers locations where hail fall was reported. The BRAMS simulations suggest that, despite relatively low values of the convective available potential energy (CAPE) (700–1000 J kg -1 ), environments with strong 0–8-km bulk shear (60–70 kt, ~30.9–36.0 m s –1 ) can promote the formation of ice clouds and hail fall over the eastern La Plata Basin. To be more conclusive, however, further research is needed to understand how different combinations of CAPE and shear affect hail formation over the region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Rapid Evaluation and Response to Impacts on Critical End-Use Loads Following Natural Hazard-Driven Power Outages: A Modular and Responsive Geospatial Technology

The disparate nature of data for electric power utilities complicates the emergency recovery and response process. The reduced efficiency of response to natural hazards and disasters can extend the time that electrical service is not available for critical end-use loads, and in extreme events, leave the public without power for extended periods. This article presents a methodology for the development of a semantic data model for power systems and the integration of electrical grid topology, population, and electric distribution line reliability indices into a unified, cloud-based, serverless framework that supports power system operations in response to extreme events. An iterative and pragmatic approach to working with large and disparate datasets of different formats and types resulted in improved application runtime and efficiency, which is important to consider in real time decision-making processes during hurricanes and similar catastrophic events. This technology was developed initially for Puerto Rico, following extreme hurricane and earthquake events in 2017 and 2020, but is applicable to utilities around the world. Given the highly abstract and modular design approach, this technology is equally applicable to any geographic region and similar natural hazard events. In addition to a review of the requirements, development, and deployment of this framework, technical aspects related to application performance and response time are highlighted.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Task Decomposition in Human Reliability Analysis

In the probabilistic safety assessments (PSAs) used in the nuclear industry, human failure events (HFEs) are determined as a subset of hardware failures, namely those hardware failures that could be triggered by human action or inaction. This approach is top-down, starting with hardware faults and deducing human contributions to those faults. Elsewhere, more traditionally human factors driven approaches would tend to look at opportunities for human errors first in a task analysis and then identify which of those errors is risk significant. The intersection of top-down and bottom-up approaches to defining HFEs has not been carefully studied. Ideally, both approaches should arrive at the same set of HFEs. This question remains central as human reliability analysis (HRA) methods are generalized to new domains like oil and gas. The HFEs used in nuclear PSAs tend to be top-down— defined as a subset of the PSA—whereas the HFEs used in petroleum quantitative risk assessments (QRAs) are more likely to be bottom-up—derived from a task analysis conducted by human factors experts. The marriage of these approaches is necessary in order to ensure that HRA methods developed for top-down HFEs are also sufficient for bottom-up applications.

error of commission↗
DOE OSTI2015

SU-D-BRD-06: Creating a Safety Net for a Fully Automated, Script Driven Electronic Medical Record

Purpose: Demonstrate the effectiveness of in-house software in ensuring EMR workflow efficiency and safety. Methods: A web-based dashboard system (WBDS) was developed to monitor clinical workflow in real time using web technology (WAMP) through ODBC (Open Database Connectivity). Within Mosaiq (Elekta Inc), operational workflow is driven and indicated by Quality Check Lists (QCLs), which is triggered by automation software IQ Scripts (Elekta Inc); QCLs rely on user completion to propagate. The WBDS retrieves data directly from the Mosaig SQL database and tracks clinical events in real time. For example, the necessity of a physics initial chart check can be determined by screening all patients on treatment who have received their first fraction and who have not yet had their first chart check. Monitoring similar “real” events with our in-house software creates a safety net as its propagation does not rely on individual users input. Results: The WBDS monitors the following: patient care workflow (initial consult to end of treatment), daily treatment consistency (scheduling, technique, charges), physics chart checks (initial, EOT, weekly), new starts, missing treatments (>3 warning/>5 fractions, action required), and machine overrides. The WBDS can be launched from any web browser which allows the end user complete transparency and timely information. Since the creation of the dashboards, workflow interruptions due to accidental deletion or completion of QCLs were eliminated. Additionally, all physics chart checks were completed timely. Prompt notifications of treatment record inconsistency and machine overrides have decreased the amount of time between occurrence and execution of corrective action. Conclusion: Our clinical workflow relies primarily on QCLs and IQ Scripts; however, this functionality is not the panacea of safety and efficiency. The WBDS creates a more thorough system of checks to provide a safer and near error-less working environment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Sea Ice and Cloud Processes Mediating Compensation between Atmospheric and Oceanic Meridional Heat Transports across the CMIP6 Preindustrial Control Experiment

Abstract Bjerknes compensation (BJC) refers to the anticorrelation observed between atmospheric and oceanic heat transport (AHT/OHT) variability, particularly on decadal to longer time scales that may be important to the predictability of the climate system. This study investigates the spread in BJC across fully coupled simulations of phase 6 of the Coupled Model Intercomparison Project (CMIP6) and critical processes (particularly related to sea ice and clouds) that may contribute to that spread. BJC on decadal to longer time scales is confirmed across all the simulations evaluated, and it is strongest in the Northern Hemisphere (NH) between 60° and 70°N. At these latitudes, BJC appears to be primarily driven by the exchange of turbulent fluxes (sensible and latent) in the Greenland, Iceland, and Barents Seas. Metrics to break down how sea ice and clouds uniquely modify the radiative balance of the polar atmosphere during anomalous OHT events are presented. These metrics quantify the impacts of sea ice and clouds on surface and top of atmosphere (latent, sensible, longwave, and shortwave radiative) energy fluxes. Cloud responses tend to counter the clear sky impacts over the Marginal Ice Zone (MIZ). It is further shown that the degree of BJC present in a simulation at high latitudes is heavily influenced by the sensitivity of the sea ice to OHT, which is most influential over the MIZ. These results are qualitatively robust across models and explain the intermodel spread in NH BJC in the preindustrial control experiment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Detecting the undetected: Dealing with non-routine events using advanced M&V meter-based savings approaches

In a rapidly evolving energy industry, utilities are dealing with new challenges like integrating distributed energy resources and market saturation for advanced lighting retrofits. Demand-side management programs require new approaches to meet aggressive carbon reduction goals. Advanced measurement & verification (M&V) is an energy data analysis method using smart meter data in combination with analytics to quantify energy efficiency project savings. Advanced M&V shows great promise for supporting next generation commercial programs including retro commissioning, multi-measure retrofits, and behavior change programs. Advanced M&V captures real project impacts at the meter, but sometimes non-project events can also impact consumption (so-called “non-routine events” [NREs]). Accurately detecting and accounting for NREs is important for reducing uncertainty of savings estimates and helps manage investment risk for different stakeholders (e.g., utilities, building owners, ESCOs). Recent research has shown promise in establishing data-driven techniques to identify and adjust for NREs, but fundamental questions still remain, such as: how can you distinguish NREs from acceptable noise in energy consumption profiles? What is the frequency and magnitude of NREs? Can their detection and adjustment be automated and streamlined? This paper documents the state of the art in NRE quantification and analysis. The results of research to quantify the frequency, nature and direction of NREs, and methods and metrics for determining a trigger threshold for taking action on NREs are presented. The paper also documents the latest technical guidance on application of NRE detection and adjustment methods.

Fernandes, Samuel↗
DOE OSTI2026

Toward a microscopic picture of hadronization and multi-parton processes

This project advanced the understanding of how quarks and gluons produced in high-energy collisions transform into the hadrons observed in particle detectors, a fundamental process known as quantum chromodynamics (QCD) hadronization. By combining theoretical calculations, quantum simulation methods, and modern AI techniques, the research developed new tools to study multi-parton dynamics and nonperturbative effects that are essential for interpreting data from current and future nuclear physics experiments. Key outcomes include new theoretical frameworks for jet and hadron measurements, pioneering quantum simulation algorithms for real-time dynamics in field theories, and the development of advanced machine-learning models, such as diffusion models and explainable classifiers, to simulate and analyze collider events. These results are directly relevant to experiments at Jefferson Lab, Brookhaven National Laboratory, and the future Electron-Ion Collider, and they also have a broader impact in areas such as quantum information science and data-driven modeling of complex systems. The project supported the training of graduate students and postdoctoral fellows and contributed to the broader scientific community through publications, workshops, and collaborative activities. Overall, this work provides new insights into the microscopic mechanisms of hadron formation and establishes a foundation for future studies at the intersection of nuclear physics, artificial intelligence, and quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Waveform Simulation Framework: User Manual with Tutorials

This manuscript describes the Waveform Simulation Framework (WSF), a Python-based framework that provides a unified, programmable interface for generating synthetic seismograms for applications such as seismic array design, method development, and special event analysis. WSF standardizes how users define sources, receivers, and velocity models while abstracting simulator-specific configuration details, enabling workflows that are largely independent of the underlying numerical engine. The document provides installation guidance and tutorial-driven examples for three WSF simulator wrappers—WSF PyFK, WSF SW4, and WSF SPECFEM2D—illustrating end-to-end workflows from forward waveform simulation to common post-processing tasks (e.g., visualization and backprojection) using consistent data products (e.g., ObsPy Stream objects and SAC files).

97 MATHEMATICS AND COMPUTING↗