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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study

# 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction Study The 2023 University of Puerto Rico at Mayagüez National Institute for Congestion Reduction (NCIR) Study provided insight into the travel patterns and associated energy consumption of participants. Study results helped researchers identify opportunities for the development of policies that could incentivize the use of alternative modes of travel such as transit and micromobility. Such travel modes reduce congestion by reducing the miles traveled by privately owned vehicles in urban and rural areas. The [National Institute for Congestion Reduction](https://nicr.usf.edu/) provides multimodal congestion reduction strategies through real-world deployments that leverage advances in technology, big data science, and innovative transportation options to optimize the efficiency and reliability of the transportation system for all users. ## Data Collection Agency The University of Puerto Rico at Mayagüez conducted the study. ## Survey Methodology The study was conducted in Spanish. Data collection was enabled via the open-source [NREL OpenPATH platform](https://www.nrel.gov/transportation/openpath). The resulting dataset consists of partially automated travel diaries—combining sensed and surveyed data reflecting patterns of multimodal, end-to-end, individual human mobility—as well as demographic and socioeconomic information from the 17 participants. ## Survey Records, Data, and Documentation Study records include 17 participants. The total number of trips was 458 and total non-air-miles traveled was approximately 1,469.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2011

Causal Factors and Adverse Events of Aviation Accidents and Incidents Related to Integrated Vehicle Health Management

Causal factors in aviation accidents and incidents related to system/component failure/malfunction (SCFM) were examined for Federal Aviation Regulation Parts 121 and 135 operations to establish future requirements for the NASA Aviation Safety Program s Integrated Vehicle Health Management (IVHM) Project. Data analyzed includes National Transportation Safety Board (NSTB) accident data (1988 to 2003), Federal Aviation Administration (FAA) incident data (1988 to 2003), and Aviation Safety Reporting System (ASRS) incident data (1993 to 2008). Failure modes and effects analyses were examined to identify possible modes of SCFM. A table of potential adverse conditions was developed to help evaluate IVHM research technologies. Tables present details of specific SCFM for the incidents and accidents. Of the 370 NTSB accidents affected by SCFM, 48 percent involved the engine or fuel system, and 31 percent involved landing gear or hydraulic failure and malfunctions. A total of 35 percent of all SCFM accidents were caused by improper maintenance. Of the 7732 FAA database incidents affected by SCFM, 33 percent involved landing gear or hydraulics, and 33 percent involved the engine and fuel system. The most frequent SCFM found in ASRS were turbine engine, pressurization system, hydraulic main system, flight management system/flight management computer, and engine. Because the IVHM Project does not address maintenance issues, and landing gear and hydraulic systems accidents are usually not fatal, the focus of research should be those SCFMs that occur in the engine/fuel and flight control/structures systems as well as power systems.

Reveley, Mary S.↗
NASA NTRS1977

Comparative vibration environments of transportation vehicles

Measured vibration data are presented for a number of air and surface vehicles. Consideration is given to the importance of direction effects; of vehicle operating modes such as takeoff, cruise, and landing; and of measurement location on the level and frequency of the measurements. Various physical measurement units or descriptors are used to quantify and compare the data. Results suggest the range of vibration associated with a particular mode of transportation and illustrate the comparative levels in terms of each of the descriptors. Collectively, the results form a data base which may be useful in assessing the ride of existing or future systems relative to vehicles in current operation. In addition, subjective response data obtained from vibration simulator studies are presented to illustrate human response characteristics as well as to indicate a laboratory approach for the development of ride-quality criteria.

Stephens, D. G.↗
DOE OSTI2020

UNESE Data Analysis-Disko Elm Gas Transport Characteristics (NA-22 Quarterly Report)

Recently published papers have demonstrated the impact of sorption mechanisms on gas transport in the subsurface following an underground nuclear explosion. To include sorption processes in the multi-physics models of noble gas production and transport, researchers have conducted experiments of gas sorption in geologic materials and calibrated a linear (Henry’s law) sorption model for all gases in various geologic materials. As a part of Task #4, we requested the experimental data from Sandia Laboratories and derived a dual-mode (Henry’s absorption and Langmuir adsorption) sorption model. The derived model better describes the nonlinear sorption mechanism with much higher fitness with the experimental data. When gas concentrations are relatively low (in the conditions of field experiments or underground nuclear explosions) compared to those used sorption experiments, the nonlinear sorption model can be approximated as a linear sorption model. The equivalent Henry’s constant, which equals the product of Langmuir capacity and affinity, is systematically higher than the literature values. Further analyses and comparison of sorption models are planned in FY2020 Q4 and the sorption model will be coupled in models of nonisothermal multiphase transport for studying noble gas detectability.

58 GEOSCIENCES↗
NASA NTRS1956

An analysis of airspeed, altitude, and acceleration data obtained from a twin-engine transport airplane operated over a feeder-line route in the Rocky Mountains

Time-history data of airspeed, altitude, and acceleration obtained with the NACA VGH recorder from a twin-engine airplane operated by a regional feeder airline in the Rocky Mountains are evaluated to determine the magnitude and frequency of occurrence of gusts and gust accelerations and the operating airspeeds and altitudes. The results obtained are compared with the results previously obtained from a representative short-haul and long-haul operation.

OPERATING PROBLEMS↗
NASA NTRS1988

The eddy transport of nonconserved trace species derived from satellite data

Using the approach of the Garcia and Solomon (1983) model and data obtained by the LIMS instrument on Nimbus 7, the chemical eddy transport matrix for planetary waves was calculated, and the chemical eddy contribution to the components of the matrix obtained from the LIMS satellite observations was computed using specified photochemical damping time scales. The dominant component of the transport matrices for several winter months were obtained for ozone, nitric acid, and quasi-geostrophic potential vorticity (PV), and the parameterized transports of these were compared with the 'exact' transports, computed directly from the eddy LIMS data. The results indicate that the chemical eddy effect can account for most of the observed ozone transport in early winter, decreasing to less than half in late winter. The agreement between the parameterized and observed nitric acid and PV was not as good. Reasons for this are discussed.

Smith, Anne K.↗
DOE OSTI2021

TNSL Overview

Thermal neutron scattering law (TNSL) data describe low-energy neutrons scattering off of bound materials, and can have a significant impact on modeling any system with slow neutrons, including nuclear reactors. Previous work to introduce TNSL data to neutron transport codes at LLNL focused on COG and TART [1], with the limitation that these codes require highly specialized data processing and formatting. We have recently increased efforts to process TNSL data with the central LLNL nuclear data processing code FUDGE, to be stored in the generalized nuclear database structure (GNDS) for use in any general transport code with the ability to read GNDS data. The first step in this effort is to verify that the TNSL processing with FUDGE yields results comparable to results obtained using the LANL nuclear data processing code NJOY. The next step is to verify the transport of thermal neutrons in Mercury (a Monte Carlo code) and Ardra (a deterministic code) against one another, as well as against the LANL Monte Carlo neutron transport code MCNP. This verification step has not been completed, due to a number of discrepancies between results obtained using differently processed data. There is ongoing effort to understand differences between FUDGE and NJOY. Finally, we map out our current capability to validate TNSL data against benchmark systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2017

Daily Ambient Air Pollution Metrics for Five Cities: Evaluation of Data Fusion-Based Estimates and Uncertainties

Spatiotemporal characterization of ambient air pollutant concentrations is increasingly relying on the combination of observations and air quality models to provide well-constrained, spatially and temporally complete pollutant concentration fields. Air quality models, in particular, are attractive, as they characterize the emissions, meteorological, and physiochemical process linkages explicitly while providing continuous spatial structure. However, such modeling is computationally intensive and has biases. The limitations of spatially sparse and temporally incomplete observations can be overcome by blending the data with estimates from a physically and chemically coherent model, driven by emissions and meteorological inputs. We recently developed a data fusion method that blends ambient ground observations and chemical transport-modeled (CTM) data to estimate daily, spatially resolved pollutant concentrations and associatedcorrelations. In this study, we assess the ability of the data fusion method to produce daily metrics (i.e., 1-hr max, 8-hr max, and 24-hr average) of ambient air pollution that capture spatiotemporal air pollution trends for 12 pollutants (CO, NO2, NOx, O3, SO2, PM (sub10), PM (sub 2.5), and five PM (sub 2.5) components) across five metropolitan areas (Atlanta, Birmingham, Dallas, Pittsburgh, and St. Louis), from 2002 to 2008. Three sets of comparisons are performed: (1) the CTM concentrations are evaluated for each pollutant and metropolitan domain, (2) the data fusion concentrations are compared with the monitor data, (3) a comprehensive cross-validation analysis against observed data evaluates the quality of the data fusion model simulations across multiple metropolitan domains. The resulting daily spatial field estimates of air pollutant concentrations and uncertainties are not only consistent with observations, emissions, andmeteorology, but substantially improve CTM-derived results for nearly all pollutants and all cities, with the exception of NO2 for Birmingham. The greatest improvements occur for O3 and PM (sub 2.5). Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R-squared equal to 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM (sub 2.5)), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM (sub 10)). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

spatiotemporal fusion↗
DOE OSTI2016

Error Detection and Correction LDMS Plugin Version 1.0

Sandia's Lightweight Distributed Metric Service (LDMS) is a data collection and transport system used at Livermore Computing to gather performance data across the center. While Sandia has a set of plugins available, they do not include all the data we need to capture. The ECAC plugin that we have developed enables collection of the Error Detection and Correction (EDAC) counters.

Shoga, Kathleen↗
DOE OSTI2012

Quantifying Feedbacks from Abrupt Changes in High-Latitude Trace-Gas Emissions

During the three-year project period, Purdue University has specifically accomplished the following: revised the existing Methane Dynamics Model (MDM) to consider the effects of changes of atmospheric pressure; applied the methane dynamics model (MDM) to Siberian region to demonstrate that ebullition estimates could increase previous estimates of regional terrestrial CH 4 emissions 3- to 7-fold in Siberia; Conducted an analysis of the carbon balance of the Arctic Basin from 1997 to 2006 to show that terrestrial areas of the Arctic were a net source of 41.5 Tg CH 4 yr 1 that increased by 0.6 Tg CH 4 yr 1 during the decade of analysis, a magnitude that is comparable with an atmospheric inversion of CH 4 ; improved the quantification of CH 4 fluxes in the Arctic with inversion methods; evaluated AIRS CH4 retrieval data with a transport and inversion model and surface flux and aircraft data; to better quantify methane emissions from wetlands, we extended the MDM within a biogeochemistry model, the Terrestrial Ecosystem Model (TEM), to include a large-scale hydrology model, the variable infiltration capacity (VIC) model; more recently, we developed a single box atmospheric chemistry model involving atmospheric methane (CH 4 ), carbon monoxide (CO) and radical hydroxyl (OH) to analyze atmospheric CH 4 concentrations from 1984 to 2008.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Error Detection and Correction LDMS Plugin Version 1.0

Sandia's Lightweight Distributed Metric Service (LDMS) is a data collection and transport system used at Livermore Computing to gather performance data across the center. While Sandia has a set of plugins available, they do not include all the data we need to capture. The ECAC plugin that we have developed enables collection of the Error Detection and Correction (EDAC) counters.

Shoga, Kathleen↗
NASA NTRS2012

Near real-time traffic routing

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Yang, Chaowei↗
DOE OSTI2024

A traffic accident dataset for Chattanooga, Tennessee

This publication presents an annotated accident dataset which fuses traffic data from radar detection sensors, weather condition data, and light condition data with traffic accident data (as illustrated in Fig. 1) in a format that is easy to process using machine learning tools, databases, or data workflows. The purpose of this data is to analyze, predict, and detect traffic patterns when accidents occur. Each file contains a timeseries of traffic speeds, flows, and occupancies at the sensor nearest to the accident, as well as 5 neighboring sensors upstream and downstream. It also contains information about the accident type, date, and time. In addition to the accident data, we provide baseline data for typical traffic patterns during a given time of day. Overall, the dataset contains 6 months of annotated traffic data from November 2020 to April 2021. During this timeframe, and 361 accidents occurred in the monitored area around Chattanooga, Tennessee. This dataset served as the basis for a study on topology-aware automated accident detection for a companion publication [1].

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1986

Crash response data system for the controlled impact demonstration (CID) of a full scale transport aircraft

NASA Langley's Crash Response Data System (CRDS) which is designed to acquire aircraft structural and anthropomorphic dummy responses during the full-scale transport CID test is described. Included in the discussion are the system design approach, details on key instrumentation subsystems and operations, overall instrumentation crash performance, and data recovery results. Two autonomous high-environment digital flight instrumentation systems, DAS 1 and DAS 2, were employed to obtain research data from various strain gage, accelerometer, and tensiometric sensors installed in the B-720 test aircraft. The CRDS successfully acquired 343 out of 352 measurements of dynamic crash data.

Calloway, Raymond S.↗