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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 1,801 records · Page 100
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Relationship of the time course of venous gas bubbles to altitude decompression illness

The correlation is low between the occurrence of gas bubbles in the pulmonary artery, called venous gas emboli (VGE), and subsequent decompression illness (DCI). The correlation improves when a "grade" of VGE is considered; a zero to four categorical classification based on the intensity and duration of the VGE signal from a Doppler bubble detector. Additional insight about DCI might come from an analysis of the time course of the occurrence of VGE. Using the NASA Hypobaric Decompression Sickness Databank, we compared the time course of the VGE outcome between 322 subjects who exercised and 133 Doppler technicians who did not exercise to evaluate the role of physical activity on the VGE outcome and incidence of DCI. We also compared 61 subjects with VGE and DCI with 110 subjects with VGE but without DCI to identify unique characteristics about the time course of the VGE outcome to try to discriminate between DCI and no-DCI cases. The VGE outcome as a function of time showed a characteristic short lag, rapid response, and gradual recovery phase that was related to physical activity at altitude and the presence or absence of DCI. The average time for DCI symptoms in a limb occurred just before the time of the highest fraction of VGE in the pulmonary artery. It is likely, but not certain, that an individual will report a DCI symptom if VGE are detected early in the altitude exposure, the intensity or grade of VGE rapidly increases from a limb region, and the intensity or grade of VGE remains high.

NASA Discipline Environmental Health↗
NASA NTRS2015

Enhancing the Traffic Management Advisor's Schedule by Time Advance

A time advance algorithm associated with the scheduling functionalities of the Traffic Management Advisor (TMA) for arrival flights is presented and evaluated. The algorithm enhances TMA's meter fix schedule by advancing the flights' Scheduled Time of Arrival (STA) by an amount that minimizes their systemic operating cost. The systemic operating cost leverages the inherent trade-off of time and fuel efficiency resident in the cost index of modern flight management systems. The resulting STAs are achievable by speeding up the leading flights from their desired nominal speed profiles. A key advantage of this approach is that it reduces systemic delay to tight groupings of arriving aircraft as well as increases sustained throughput of the operation. A fast-time, Monte Carlo simulation that emulates TMA's scheduling functionalities is performed for arrival flights to the Phoenix Airport to quantify the benefit of the time advance algorithm. Results show consistent time saving benefits, ranging from 3 to 50 minutes for 112 flights with varying levels of traffic congestion.

arrival traffic management↗
NASA NTRS2019

The Value of Near Real-Time Earth Observations for Improved Flood Disaster Response

Information is a critical resource in disaster response scenarios. Data regarding the geographic extent, severity, and socioeconomic impacts of a disaster event can help guide emergency responders and relief operations, particularly when delivered within hours of data acquisition. Information from remote observations provides a valuable tool for assessing conditions "on the ground" more quickly and efficiently. Here, we evaluate the social value of a near real-time flood impact system using a disaster response case study, and quantify the Value of Information (VOI) of satellite-based observations for rapid response using a hypothetical flooding disaster in Bangkok, Thailand. MODIS imagery from NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) system is used to produce operational estimates of inundation depths and economic damages.These rapid Earth observations are coupled with a decision-analytical model to inform decisions on emergency vehicle routing. Emergency response times from vehicles routed using flood damage data are compared with baseline routes without the benefit of advance information on road conditions. Our results illustrate how the application of near real-time Earth observations can improve the response time and reduce potential encounters with flood hazards when compared with baseline routing strategies. Results indicate a potential significant economic benefit (i.e.,millions of dollars) from applying near real-time Earth observations for improved flood disaster response and management.

emergency response↗
NASA NTRS2018

A Higher-Order Space-Time Finite-Element Method for Moving-Body and Fluid-Structure Interaction Problems

We present a high-order finite-element method for moving body and fluid/structure interaction problems. Our solution strategy is based on a space-time discontinuous Galerkin (DG) spectral-element discretization which extends to arbitrary order of accuracy. The space-time DG discretization is a natural choice for moving body and fluid-structure interaction problems as moving surfaces are incorporated simply by considering curved space-time elements whose space-time faces align with the moving body. We present a discontinuous-Galerkin in time discretization for six-degree of motion modeling of rigid bodies, and a continuous-Galerkin discretization for equations of linear elasticity to generate curved space-time meshes. Numerical results for several simple 2D test cases are presented in order to verify the implementation of the different models. Finally we present a preliminary dynamic simulation of a parachute.

High-Order↗
NASA NTRS2021

Real-time Unimpeded Taxi Out Machine Learning Service

This paper describes a study on the estimation of the unimpeded taxi out time using Machine Learning (ML) tools and proposes an implementation that can be used to make real-time predictions at any airport in the National Airspace System. Kedro, an open-source pipeline framework, is used to develop the model definition and training. Models are stored in scikit-learn containers on a MLFlow server where they can be retrieved and served to make predictions in the live system. These open source frameworks provide common structures between ML services, allow for easier maintenance and updates, and overall deliver an easier CI/CD (Continuous Integration/Continuous Deployment) process. The current models were trained on data acquired at KCLT and KDFW from June 1st to December 31st, 2019 and compute taxi time in the ramp, airport movement area (AMA) and total (from gates to runways). The current versions of the models achieve relatively low uncertainties of about 10 to 15% for the total and AMA taxi times and about 20% for the ramp taxi time at both KCLT and KDFW. Initial tests on offline data from 2020 and 2021 show a small degradation (10 to 15%) in accuracy performance indicating the model’s resilience to operational changes over time.

machine learning↗
NASA NTRS2021

Real-time Unimpeded Taxi Out Machine Learning Service

This presentation describes a study on the estimation of the unimpeded taxi out time using Machine Learning (ML) tools and proposes an implementation that can be used to make real-time predictions at any airport in the National Airspace System. Kedro, an open-source pipeline framework, is used to develop the model definition and training. Models are stored in scikit-learn containers on a MLFlow server where they can be retrieved and served to make predictions in the live system. These open source frameworks provide common structures between ML services, allow for easier maintenance and updates, and overall deliver an easier CI/CD (Continuous Integration/Continuous Deployment) process. The current models were trained on data acquired at KCLT and KDFW from June 1st to December 31st, 2019 and compute taxi time in the ramp, airport movement area (AMA) and total (from gates to runways). The current versions of the models achieve relatively low uncertainties of about 10 to 15% for the total and AMA taxi times and about 20% for the ramp taxi time at both KCLT and KDFW. Initial tests on offline data from 2020 and 2021 show a small degradation (10 to 15%) in accuracy performance indicating the model’s resilience to operational changes over time.

Machine Learning↗
NASA NTRSDate not supplied

Flight Testing of In-Time Safety Assurance Technologies for UAS Operations

Ongoing research at NASA is driven by a strategic plan defined by the Aeronautics Research Mission Directorate and a vision for future In-Time Aviation Safety Management Systems (IASMS) as described by the National Academies. In both visions, system safety awareness and provision are expanded through increased access to relevant data; integrated analysis and predictive capabilities; improved real-time detection and alerting of domain-specific hazards; decision support, and in some cases, automated risk mitigation strategies. One primary research focus is to develop means by which more timely (i.e., “in-time”) actions may be taken to mitigate precursors, anomalies, or trends that are observed during operations. In this paper, we describe such means as a collection of Services, Functions, and Capabilities (SFCs) that are supported by an underlying information system. For example, an integrated risk assessment capability is envisioned that continuously monitors safety-related metrics and margins and recommends timely operational changes. Assessment functions and/or services can be based on data analytics and predictive models derived from heterogeneous data sets that span relevant indicator metrics and their time histories. Likewise, on-board functions can identify and reduce susceptibility to precursor conditions that have led (and can lead) to aircraft loss-of-control or out-of-control accidents. This paper summarizes development and testing of such an information system tailored to hazards anticipated for future highly autonomous flight missions near and over densely populated areas. Testing is accomplished via simulation and by using small, unmanned aircraft operating over a test range at NASA’s Langley Research Center. Flight plans and test scenarios are defined to emulate several use-cases, including package delivery; reconnaissance; fire management; and urban air taxi vertiport operations. Two test phases are summarized with Phase 1 occurring in (2019-2020) and Phase 2 ongoing (2021-present). Results focus on SFC performance, technology readiness level assessment, and requirements discovery/validation. Companion papers are cited throughout for additional details on the recent testing.

safety management↗
DOE OSTI2023

A Reproducible Validation of Algorithms for Estimating Array Tilt and Azimuth from Photovoltaic Power Time Series

In this research, we assess the viability of four different, publicly available algorithms for estimating the azimuth and tilt parameters of solar photovoltaic systems using only the associated AC power time series data and site latitude-longitude coordinates. In this work, we curated a benchmarking data set of 44 fixed-tilt systems, comprising 275 measured AC power inverter data streams, with known azimuth and tilt parameters. Additionally, we isolated test cases in the data set with real-world issues, including shading and clipping, to determine how algorithm performance varies based on the presence of these phenomena. Using this data set for benchmarking, we evaluated the estimated vs. actual system characteristics for each algorithm, as well as the associated algorithm execution time using a standardized benchmarking process. The two highest performing algorithms were the Solar Data Tools and the PVWatts 5-based methods, which both achieved a median absolute error of approximately 5 and 1 degrees for azimuth and tilt, respectively. During run time analysis, the SDT method was approximately 5 times faster than the PVWatts 5-based method, with the median execution time for a stream varying between 6 and 8 seconds vs. a median run time of 31 seconds for the PVWatts 5-based method.

algorithm validation↗
DOE OSTI2023

On Soft Mathematical Models of Subjective Time Acceleration with Age

It is a commonplace perception that speed of time subjectively experienced by humans significantly differs from chronological (objective) time and shows a great deal of variability. An often cited example is the phenomenon of the time acceleration with age - subjectively, the time passes faster as we get older. While the exact mechanisms behind it are not yet fully established, here we consider three 'soft' (conceptual) mathematical models that might be applicable to the speeding time phenomenon: two proportionality theories widely discussed in the past and the original model that takes into account the novelty of experience effect. Furthermore, the latter is found the most plausible, as not only it satisfactorily describes the decadal subjective time acceleration, but also offers a reasonable explanation of the human life experience accumulation with age.

acceleration↗
DOE OSTI2012

Burst wait time simulation of CALIBAN reactor at delayed super-critical state

In the past, the super prompt critical wait time probability distribution was measured on CALIBAN fast burst reactor [4]. Afterwards, these experiments were simulated with a very good agreement by solving the non-extinction probability equation [5]. Recently, the burst wait time probability distribution has been measured at CEA-Valduc on CALIBAN at different delayed super-critical states [6]. However, in the delayed super-critical case the non-extinction probability does not give access to the wait time distribution. In this case it is necessary to compute the time dependent evolution of the full neutron count number probability distribution. In this paper we present the point model deterministic method used to calculate the probability distribution of the wait time before a prescribed count level taking into account prompt neutrons and delayed neutron precursors. This method is based on the solution of the time dependent adjoint Kolmogorov master equations for the number of detections using the generating function methodology [8,9,10] and inverse discrete Fourier transforms. The obtained results are then compared to the measurements and Monte-Carlo calculations based on the algorithm presented in [7]. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2012

Effects of cooling time on a closed LWR fuel cycle

In this study, the effects of cooling time prior to reprocessing spent LWR fuel has on the reactor physics characteristics of a PWR fully loaded with homogeneously mixed U-Pu or U-TRU oxide (MOX) fuel is examined. A reactor physics analysis was completed using the CASM04e code. A void reactivity feedback coefficient analysis was also completed for an infinite lattice of fresh fuel assemblies. Some useful conclusions can be made regarding the effect that cooling time prior to reprocessing spent LWR fuel has on a closed homogeneous MOX fuel cycle. The computational analysis shows that it is more neutronically efficient to reprocess cooled spent fuel into homogeneous MOX fuel rods earlier rather than later as the fissile fuel content decreases with time. Also, the number of spent fuel rods needed to fabricate one MOX fuel rod increases as cooling time increases. In the case of TRU MOX fuel, with time, there is an economic tradeoff between fuel handling difficulty and higher throughput of fuel to be reprocessed. The void coefficient analysis shows that the void coefficient becomes progressively more restrictive on fuel Pu content with increasing spent fuel cooling time before reprocessing. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2012

Model for Correlating Real-Time Survey Results to Contaminant Concentrations - 12183

The U.S. Environmental Protection Agency (EPA) Superfund program is developing a new Counts Per Minute (CPM) calculator to correlate real-time survey results, which are often expressed as counts per minute, to contaminant concentrations that are more typically provided in risk assessments or for cleanup levels, usually expressed in pCi/g or pCi/m{sup 2}. Currently there is no EPA guidance for Superfund sites on correlating count per minute field survey readings back to risk, dose, or other ARAR based concentrations. The CPM calculator is a web-based model that estimates a gamma detector response for a given level of contamination. The intent of the CPM calculator is to facilitate more real-time measurements within a Superfund response framework. The draft of the CPM calculator is still undergoing internal EPA review. This will be followed by external peer review. It is expected that the CPM calculator will at least be in peer review by the time of WM2012 and possibly finalized at that time. The CPM calculator should facilitate greater use of real-time measurement at Superfund sites. The CPM calculator may also standardize the process of converting lab data to real time measurements. It will thus lessen the amount of lab sampling that is needed for site characterization and confirmation surveys, but it will not remove the need for sampling. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2017

Time Analysis on a Steam Condensation Jet

The time dependence of a steam bubble entering a water pool was measured for this experiment. The temperature of the water tank at the nozzle exit was 75 deg. C ± 5 deg. C. The experiment will focus on how the bubble changes its size through time for future experimental analysis concerning the heat transfer coefficient. The study focuses at different steam flow velocities approaching the water tank. The area of the steam bubble was measured using a high-speed camera to obtain the heat transfer coefficients. The region of interest is illuminated with a laser or a halogen lamp depending on the experiment. Calculating the rate at which the bubbles are created and condensed, will help obtain a better understanding of the energy transfer between the bubble and the water. The study of steam condensation is important due to its application on nuclear plants, heat exchangers, geothermal power plants and steam ejectors. Recently, more experiments have been performed and studied due to its high heat transfer rate. The results obtained in this experiment will be used to validate CFD models. This primary experimental report focuses on the steam bubble's time dependence; the same system will be used for future experiments concerning the heat transfer coefficient. In previous work done by Chun using only steam, the average heat transfer coefficient of direct contact condensation reported was in the range of 1.0-3.5 MW/m{sup 2} deg. C. He proposes an empirical correlation to predict the average heat transfer coefficients. The experimental data agrees with the empirical correlation within ± 30%. On a different experiment performed by Gulawani using a hot film anemometer on a steam condensation jet. The reported heat transfer coefficient for the vapor liquid interface varies between 0.1-4 MW/m{sup 2}-K. The nozzle diameter used during this experiment varied between 1-2 mm, and the velocity ranged between 286-304 m/s. Aya and Nariai reported three different heat transfer coefficients for direct contact condensation. They reported a heat transfer coefficient at chugging of 2*10{sup 6} W/m{sup 2}-K, at condensation oscillation of 10{sup 5} - 10{sup 6} W/m{sup 2}-K, and at the surface of stratified flow of 3*10{sup 3} - 3*10{sup 4} W/m{sup 2}-K. With steam and air mixture, a heat transfer coefficient relating the bubble average area was reported by Qu. He reported that the heat transfer coefficient decreased with the increase of the bubble diameter. The relation is time dependant and can be used to the transient analysis of the heat transfer. For this experiment, a set of images was obtained of a steam jet. The pictures were analyzed to obtained the time dependence of the steam bubble with time, and the rate of its condensation. A frequency of 20 Hz was calculated when the steam had a flow rate of 2.5 grams per second. The first result obtained for this experiment. In the future, more flow rates will be analyzed to obtain a relationship between the frequency of the bubbles and the flow rate of the steam. Eventually, this information will aid with the calculation of the heat transfer coefficient of the steam jet in a water pool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

High carrier mobility in ultrapure diamond measured by time-resolved cyclotron resonance

We have performed time-resolved cyclotron resonance measurements in ultrapure diamond crystals for the temperature range of T=7.3–40 K and obtained the temperature-dependent momentum relaxation times based on the cyclotron resonance widths for optically generated electrons and holes. The relaxation time follows a T{sup −3/2} law down to 12 K, which is expected for acoustic-phonon scattering without impurity effect because of the high purity of our samples. The deviation from the law at lower temperatures is explained by the impurity scattering and the breakdown of the high-temperature approximation for the phonon scattering. We extract the carrier drift mobility by using the directly measured effective masses and the relaxation times. The mobility at 10 K for 600 ns delay time after optical injection is found to be μ{sub e}=1.5×10{sup 6} cm{sup 2}/V s for the electrons, and μ{sub lh}=2.3×10{sup 6} cm{sup 2}/V s and μ{sub hh}=2.4×10{sup 5} cm{sup 2}/V s for the light and heavy holes, respectively. These high values are achieved by our high-sensitivity detection for low-density carriers (at <10{sup 11} cm{sup −3}) free from the carrier-carrier scattering as well as by the suppression of the impurity scattering in the high-purity samples.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Data and scripts associated with “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” (v3)

This data package is associated with the publication “Sequential Precipitation Input Tagging (SPIT) to Estimate Water Transit Times and Hydrologic Tracer Dynamics within Water-Tagging Enabled Hydrologic Models” submitted to Journal of Advances in Modeling Earth Systems (Butler et al. 2025). This study developed the Sequential Precipitation Input Tagging (SPIT) framework to tag input precipitation and estimate water transit times and hydrologic tracers. SPIT tags all precipitation events at regular intervals over an extended period (monthly tags over seven years) in a hydrologic model from 2016-2022. SPIT is applied at six National Ecological Observatory Network (NEON) sites across the continental United States to calculate transit time distributions (TTD) and derive from these mean transit times (MTT), fractions of young water (Fyw), and hydrologic tracer concentrations in stream water (δ18O) within a water-tagging enabled version of the Weather Research and Forecast (WT-WRF-Hydro) model with national water model (NWM) configurations. We go on to validate WT-WRF-Hydro estimates against Butler et al. (2023), who analyzed the same NEON sites using stable water isotope data to estimate water transit times. This new tracking method provides a detailed picture of water movement and helps improve predictions about water availability in the future. This data package was originally published in January 2025. It was updated May 2025 (v2; new and modified files) and October 2025 (v3; new and modified files). File and folder names were not revised to indicate changes. See the change history section in the readme for more details. This data package contains the data and scripts used to develop the SPIT framework WT-WRF-Hydro (Water Tagging Weather Research and Forecasting Hydrologic) model and is associated with the following GitHub repository: https://github.com/zbutler33/SPIT-Framework. This data package contains five parent folders: (1) “Manipulated_outputs”, (2) “Metadata”, (3) “Observed”, (4) “Outputs”, and (5) “Scripts”. Each of these parent folders contains additional subfolders and files. Please see the FLMD (“v*_Butler_2024_WT_WRF_Hydro_flmd.csv”) for a list of all the files contained in this data package and descriptions for each. See the data dictionary (“v*_Butler_2024_WT_WRF_Hydro_dd.csv”) for definitions and units of all of the tabular (files ending in “.csv” and ".tsv") column headers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey

In modern smart grids, accurate and synchronized time signals are essential for effective monitoring, protection, and control. Various time synchronization methods exist, each tailored to specific application needs. Widely adopted solutions, such as GPS, however, are vulnerable to challenges such as signal loss and cyber-attacks, underscoring the need for reliable backup or supplementary solutions. This paper examines the timing requirements across different power grid applications and provides a comprehensive review of available time synchronization mechanisms. Through a comparative analysis of timing methods based on accuracy, flexibility, reliability, and security, this study offers insights to guide the selection of optimal solutions for seamless grid integration.

comparison↗
DOE OSTI2024

Energy and Carbon Payback Times for Modern U.S. Utility Photovoltaic Systems

Manufacturing and operating a PV system consumes non-renewable energy and produces carbon emissions, as does end-of-life handling when PV systems are eventually decommissioned. To fully account for PV's contribution toward decarbonization, these life cycle impacts must be quantified. A 2023 NREL LCA of utility PV systems in the United States Study show energy payback times between 0.5 and 1.2 years and carbon payback times between 0.8 to 20 years, depending on the system install location. Payback times are affected by the amount of local solar radiation, and carbon payback time is significantly affected by the carbon-intensity of the local grid it offsets, as well as the future projected grid mix for the location it is installed. In an average U.S. location, carbon payback times are less than 2 years.

carbon payback time↗
DOE OSTI2017

Contribution of storm time substorms to the prompt electric field disturbances in the equatorial ionosphere

This study tries to bring out the fact that storm time substorms can compete and at times significantly contribute to the geomagnetically disturbed time prompt penetration electric field effects on low and equatorial latitudes. Observations of unusual equatorial plasma drift data from Jicamarca Unattended Long-term Investigations of the Ionosphere and Atmosphere during two space weather events show that substorms can induce both eastward and westward penetration electric fields under steady southward interplanetary magnetic field (IMF B z ) conditions. During the first event on 2 January 2005, the enhancement of the daytime eastward electric field over Jicamarca due to substorm is found to be comparable with the Sq and interplanetary electric field (IEFy) generated electric fields combined. During the second event on 19 August 2006, the substorm is seen to weaken the daytime eastward field thereby inducing a westward field in spite of the absence of northward turning of IMF B z (overshielding). The westward electric field perturbation in the absence of any overshielding events is observationally sparse and contrary to the earlier results. Further, the substorm-induced field is found to be strong enough to compete or almost nullify the effects of storm time IEFy fields. This study also shows quantitatively that at times substorm contribution to the disturbed time prompt electric fields can be significant and thus should be taken into consideration in evaluating penetration events over low latitudes.

79 ASTRONOMY AND ASTROPHYSICS↗

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