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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 NTRS2014

Building a Database for a Quantitative Model

A database can greatly benefit a quantitative analysis. The defining characteristic of a quantitative risk, or reliability, model is the use of failure estimate data. Models can easily contain a thousand Basic Events, relying on hundreds of individual data sources. Obviously, entering so much data by hand will eventually lead to errors. Not so obviously entering data this way does not aid linking the Basic Events to the data sources. The best way to organize large amounts of data on a computer is with a database. But a model does not require a large, enterprise-level database with dedicated developers and administrators. A database built in Excel can be quite sufficient. A simple spreadsheet database can link every Basic Event to the individual data source selected for them. This database can also contain the manipulations appropriate for how the data is used in the model. These manipulations include stressing factors based on use and maintenance cycles, dormancy, unique failure modes, the modeling of multiple items as a single "Super component" Basic Event, and Bayesian Updating based on flight and testing experience. A simple, unique metadata field in both the model and database provides a link from any Basic Event in the model to its data source and all relevant calculations. The credibility for the entire model often rests on the credibility and traceability of the data.

Kahn, C. Joseph↗
DOE OSTI2026

Cooperative Agreement To Analyze variabiLity, change and predictabilitY in the earth SysTem (CATALYST)

CATALYST proposes to perform foundational coordinated research in a team-oriented collaborative effort aimed at advancing a robust understanding of modes of Earth system variability and change using models, observations and process studies. The proposed research will address the DOE/BER mission by exploring the limits to predictability, identifying fundamental underlying mechanisms, quantifying interactions among modes of variability, and discovering tipping points in the Earth system to understand the current and future impacts of these phenomena on regional and global climate. Four fundamental gaps are identified in our knowledge of the Earth system: 1) What are the limits to predictability on various timescales? 2) What are the interactions among modes of Earth system variability? 3) How may modes of Earth system variability change in response to changes in external forcing, and what are the tipping points involved with those changes? 4) How are high impact events connected to modes of Earth system variability and how may they change in the future? Related to those gaps in our knowledge, we formulate four research objectives to address those gaps using a combination of Earth system models (ESMs) and machine learning (ML) methods. Research Objective 1 (RO1) addresses the first gap above and proposes to understand modes of variability and their limits of predictability on subseasonal to decadal timescales using ESMs and ML. Research Objective 2 (RO2) addresses the second gap and proposes to use a hierarchy of models to understand relevant processes and feedbacks related to how modes of variability interact with each other. Research Objective 3 (RO3) is designed to study the third gap and proposes to examine the role of external forcings in changes of modes of Earth system variability and their interactions, and the likelihood and predictability of tipping points and irreversible changes. Research Objective 4 (RO4) will address the fourth gap and proposes to use high resolution ESMs, regionally refined models (RRMs), and ML methods to investigate the relationships between high impact events (e.g. flash droughts and precipitation extremes, atmospheric rivers (ARs), tropical cyclones (TCs), storm surge/sea level rise), the synoptic systems that produce them, and their changes related to modes of Earth system variability. The research will involve the use of the Community Earth System Model (CESM), Energy Exascale Earth System Model (E3SM), CMIP multi-model data sets, a hierarchy of simpler models, and numerous observational data sets. In the course of the proposed research, CATALYST will contribute to metrics and diagnostics that will be integrated in Coordinated Model Evaluation Capabilities (CMEC), particularly with regards to the Quasi-biennial Oscillation (QBO) and its interactions with the Madden-Julian Oscillation (MJO), high atmospheric pressure blocking, and new precipitation metrics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Quantitative magnetospheric models derived from spacecraft magnetometer data

Quantitative models of the external magnetospheric field were derived by making least-squares fits to magnetic field measurements from four IMP satellites. The data were fit to a power series expansion in the solar magnetic coordinates and the solar wind-dipole tilt angle, and thus the models contain the effects of seasonal north-south asymmetries. The expansions are divergence-free, but unlike the usual scalar potential expansions, the models contain a nonzero curl representing currents distributed within the magnetosphere. Characteristics of four models are presented, representing different degrees of magnetic disturbance as determined by the range of Kp values. The latitude at the earth separating open polar cap field lines from field lines closing on the dayside is about 5 deg lower than that determined by previous theoretically-derived models. At times of high Kp, additional high latitude field lines are drawn back into the tail.

Mead, G. D.↗
NASA NTRS2006

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes the recently awarded ACCESS project to provide data management of NASA remote sensing data for the Northern Eurasia Earth Science Partnership Initiative (NEESPI). The project targets integration of remote sensing data from MODIS, and other NASA instruments on board US-satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEP/NCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗
NASA NTRS2003

Estimation of Model Error Variances During Data Assimilation

Data assimilation is all about understanding the error characteristics of the data and models that are used in the assimilation process. Reliable error estimates are needed to implement observational quality control, bias correction of observations and model fields, and intelligent data selection. Meaningful covariance specifications are obviously required for the analysis as well, since the impact of any single observation strongly depends on the assumed structure of the background errors. Operational atmospheric data assimilation systems still rely primarily on climatological background error covariances. To obtain error estimates that reflect both the character of the flow and the current state of the observing system, it is necessary to solve three problems: (1) how to account for the short-term evolution of errors in the initial conditions; (2) how to estimate the additional component of error caused by model defects; and (3) how to compute the error reduction in the analysis due to observational information. Various approaches are now available that provide approximate solutions to the first and third of these problems. However, the useful accuracy of these solutions very much depends on the size and character of the model errors and the ability to account for them. Model errors represent the real-world forcing of the error evolution in a data assimilation system. Clearly, meaningful model error estimates and/or statistics must be based on information external to the model itself. The most obvious information source is observational, and since the volume of available geophysical data is growing rapidly, there is some hope that a purely statistical approach to model error estimation can be viable. This requires that the observation errors themselves are well understood and quantifiable. We will discuss some of these challenges and present a new sequential scheme for estimating model error variances from observations in the context of an atmospheric data assimilation system.

Dee, Dick↗
NASA NTRS2017

Enabling NLDAS-2 Anomaly Analysis Using Giovanni

A newly implemented feature in Giovanni (GES DISC Interactive Online Visualization and Analysis Interface) allows users to explore and visualize anomaly data from the NLDAS-2 Primary Forcing and Noah model data sets. For a given measurement and location, an anomaly describes how conditions for a particular time period compare to normal conditions, based on long-term averages. Analyzing anomalies is important for monitoring droughts, determining weather trends, and studying land surface processes relevant for meteorology, hydrology, and climate. Using Giovanni to analyze anomalies for NLDAS-2 data allows for these studies to be efficiently conducted for the central North American region. Phase 2 of NLDAS (NLDAS-2) currently runs at an 1/8th degree resolution, in near-real time, with data sets extending back to January 1979. NLDAS-2 provides data for soil moisture, precipitation, temperature, and other hydrology measurements. Hourly, monthly, and 30-year (1980-2009) monthly climatology data are available for several land surface models and forcing data sets. The Giovanni anomaly tool calculates monthly anomalies, for a given user-defined variable, as the difference between the NLDAS-2 monthly climatology data and the monthly data. The resulting anomaly describes how a chosen month compares to the 30-year monthly average. The presentation will demonstrate the capabilities and usefulness of Giovanni's anomaly tool, detail the recently added NLDAS-2 variables for which anomalies are available, and show how users can access the data.

drough↗
NASA NTRSDate not supplied

Analysis of Atmospheric Conditions Responsible for an Ozone Exceedance Event in Southeast Virginia on June 15, 2022

On June 15, 2022, the Virginia Department of Environmental Quality monitoring site at Suffolk/Holland, a rural site in southeast Virginia, recorded its first ozone exceedance since 2016. An ozone exceedance day occurs when the daily maximum 8-hour average surface ozone concentration is greater than 70 ppb. On this day, it was 75 ppb. This event is also noteworthy due to the rapid increase in surface ozone between 6 am and 9 am EDT as well as the hourly maximum ozone concentration of 82 ppb that was measured at 1 pm EDT. In this analysis, we utilize various observational and model data to determine the atmospheric conditions responsible for this ozone exceedance event. The analysis is conducted in two parts: (1) an evaluation of the accuracy of the GEOS-CF and WRF-Chem model forecasts and (2) an investigation of the mechanisms responsible for the high surface ozone at the Virginia DEQ Suffolk/Holland monitoring site. Comparisons of model forecasted ozone time-height cross sections with measured ozone by lidars from the Tropospheric Ozone Lidar Network (TOLNet) at NASA Langley and NASA Goddard reveal that both models forecasted ozone reasonably well near the surface. Model and observational data reveal that an upper-level ridge was present over much of the eastern United States, with a broad anticyclonic circulation near the surface, resulting in north-northeasterly flow over southeast Virginia. Back trajectory calculations using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) and model data suggest that a low-level plume rich in ozone and precursor species originating from the New York City and New Jersey region was transported along the east coast between June 14 and June 15, arriving in southeast Virginia around 6 am EDT on June 15. In the early morning hours, this plume mixed down to the surface, elevating the background ozone mixing ratio as well as the mixing ratios of several precursor species. Other potential contributions are also explored and discussed. Lastly, the authors note that this work represents the analysis of the authors and not the Virginia Department of Environmental Quality.

Daniel B Phoenix↗
NASA NTRS1975

A quantitative magnetospheric model derived from spacecraft magnetometer data

The model is derived by making least squares fits to magnetic field measurements from four Imp satellites. It includes four sets of coefficients, representing different degrees of magnetic disturbance as determined by the range of Kp values. The data are fit to a power series expansion in the solar magnetic coordinates and the solar wind-dipole tilt angle, and thus the effects of seasonal north-south asymmetries are contained. The expansion is divergence-free, but unlike the usual scalar potential expansion, the model contains a nonzero curl representing currents distributed within the magnetosphere. The latitude at the earth separating open polar cap field lines from field lines closing on the day side is about 5 deg lower than that determined by previous theoretically derived models. At times of high Kp, additional high-latitude field lines extend back into the tail. Near solstice, the separation latitude can be as low as 75 deg in the winter hemisphere. The average northward component of the external field is much smaller than that predicted by theoretical models; this finding indicates the important effects of distributed currents in the magnetosphere.

Mead, G. D.↗
NASA NTRSDate not supplied

Global Reference Atmospheric Model (GRAM) Advancements and Additions

Introduction:The Global Reference Atmospheric Model (GRAM) is one of the most widely used engineering models of the atmosphere. GRAM development and maintenance has been led by NASA Marshall Space Flight Center (MSFC). The NASA Science Mission Directorate (SMD) has provided funding support to upgrade the GRAMs since Fiscal Year 2018. NASA Langley Research Center has been working with MSFC on the upgrades.This presentation will provide details regarding the upgrades that have been made to the existing GRAMs, the development of new GRAMs, as well as the ongoing objectives, tasks, and milestones re-lated to the GRAM upgrades funded by NASA SMD. GRAM: The GRAMs are engineering-oriented atmospheric models that estimate mean values and statistical variations of the atmospheric properties for numerous planetary destinations.They provide mean values and variability for any point in the atmosphere as well as seasonal, geographic, and altitude variations. GRAM outputs include atmospheric density, temperature, pressure, winds, and chemical composition along a user-defined path.Theyhave been widely used by the engineering community because of their ability to create realistic dispersions. GRAMs have been integrated into high fidelity flight dynamic simulations of launch, entry, descent and landing (EDL), aerobraking and aerocapture. MSFC has been developing and updating GRAMs since 1974; GRAMs are currently available for Earth, Mars, Venus, Neptune, and Titan. GRAM Upgrade Status: Code Moderization.The planetary GRAMs are being rearchitected from Fortran to a common object-ori-entedC++ framework called the GRAM Suite. This new architecture creates a common GRAM library of data models and utilities. The first C++ releases of the existing planetary GRAMs (Mars, Venus, Neptune, and Titan-GRAM) in the GRAM Suite are straight conversions from the latest Fortran version. Model Upgrades.The focus of the model upgrade task is to improve the atmosphere models in the existing GRAMs and to establish a foundation for developing GRAMs for additional destinations. The GRAM ephemerishas been upgraded to the NASA Navigation and Ancillary Information Facility (NAIF) SPICE toolkit (version N0066). The calculation of the speed of sound has also been improved in the GRAMs. The GRAM team has received updated Mars General Circulation Model (MGCM) datasets from NASA Ames Research Center. Mars Global Ionosphere-Thermosphere Model (M-GITM) data is being obtained toreplace the Mars Thermospheric General Circulation Model (MTGCM) data in legacy Mars-GRAM. M-GITM and updated MGCM data will be incorporated into a future GRAM Suite release.Twoprojects that will improve the atmospheric model data in the GRAMs have been funded by the GRAM team since Fiscal Year 2020. Sanjay Limaye and Patrick Fry at the University of Wisconsin are reanalyzing the Venus Express radio occultation observations and analyzing the Akatsukiradio occultation observations.This will lead tothe calculation of number density, temperature, and pressure profiles for the 40-90 km altitude range. Kunio Sayanagi, Justin Garland, and Ryan McCabeat Hampton University are developing empirical global models for Venus,Jupiter, Saturn, Uranus, Neptune, and Titan that incorporates the latest data available for each of these planetary destinations. Upgraded GRAM Releases. GRAM Suite Version 1.0 was released in May 2020 and contains the rearchitected Neptune-GRAM, including the common GRAM framework and planet–specific code. GRAM Suite Version 1.1 was released in September 2020 and addedthe rearchitected Titan-GRAM to the GRAM Suite. A User Guide and Programmer’s Manualarereleased with all GRAMs. The rearchitected Mars and Venus-GRAMs will be released in upcomingversions of the GRAM Suite. New GRAM Releases. New GRAMs have been de-veloped for Uranus and Jupiter. Uranus-GRAM is based on an individual profile generated by Gary Allen (ARC) from Voyager 2 occultation data and will be released in GRAM Suite Version 1.2. Jupiter-GRAM is based on individual profile produced from Al Seiff’s Ju-piter model[1].Jupiter-GRAM will be released in GRAM Suite Version 1.3. Saturn-GRAM is currently under development and will be released in a future version of the GRAM Suite. Conclusions: GRAMs are vital and frequently used toolsets. Releases of the GRAM Suite, upgrades of the existing planetary GRAMs, and development of new planetary GRAMs are ongoing. NASA SMD funding has been essential to addressing current limitations and accomplishing GRAM developmental goals. Continua-tion ofSMD fundingwill ensure the development, up-grades, and maintenance of the GRAMs. References: [1] Seiff, A., et al. (1998) JGR, 103, 22,857-22,889. Acknowledgments: The authors gratefully acknowledge support from the NASA SMD

atmospheric models↗
NASA NTRS1994

Performance of BLAS 3, FFTs and NAS Parallel Benchmarks on Cray T3D

Recently, a Cray T3D Emulator has been made available on the Cray Y-MP and C90 computers. The Pittsburgh Supercomputer Center has acquired a CRAY T3D system and many other centers like Jet Propulsion Laboratory (JPL) will have it by the end of 1994. The Cray T3D system is the firstphase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's ALPHA microprocessors and CRI's parallel-vector technology, i.e. the Cray Y-MP and Cray C90. The Cray T3D Emulator will give prospective users a valuable experience in developing high performance applications on the MPP system. This emulator runs programs written in CRI's MPP Fortran programming model (data sharing and work sharing) or Parallel Virtual Machine (PVM) programming model. It will help the users to study data layout, data locality, and data reference patterns thereby providing feedback which will enable one to write more efficient parallel codes. An overview of the Cray T3D hardware, software, and three of its available programming models is presented.The Cray Fortran Programming Model comprising (a) Data Sharing, (b) Worksharing and (c) Message Passing, will be discussed with examples. We have also implemented distributed BLAS 3 (matrix-matrix multiplication) in data parallel model (using only CSHIFT); worksharing model using block distribution and collapsed distribution; and message passing model using PVM. We have also implemented 2D and 3D FFTs for radix-2 using PVM. The performance of NAS Parallel 'Benchmarks (NPB) on CRAY T3D will be compared with other highly parallel systems such as CM-5, Paragon, C90 etc.

Saini, Subhash↗
NASA NTRS2012

Identifying and Addressing Land Surface Model Deficiencies with Data Assimilation

Land surface models (LSMs) encapsulate our understanding of terrestrial water and energy cycle physics and provide estimates of land surface states and fluxes when and where measurement gaps exist. Gaps in our understanding of the physics are a different issue. Data assimilation can address that issue both directly, through updating of prognostic model variables, or indirectly, when the simulated world conflicts with observation, necessitating adjustment of the model. Here we will focus on the latter case and present several examples, including (1) depth to bedrock adjustment to accommodate assimilated GRACE terrestrial water storage data; (2) steps to prevent immediate melting of assimilated snow cover; (3) irrigation's contribution to evapotranspiration; (4) lessons learned from soil moisture data assimilation; (5) the potential impact of satellite based runoff observation

Rodell, Matthew↗
NASA NTRS1990

A comprehensive cost model for NASA data archiving

A simple archive cost model has been developed to help predict NASA's archiving costs. The model covers data management activities from the beginning of the mission through launch, acquisition, and support of retrospective users by the long-term archive; it is capable of determining the life cycle costs for archived data depending on how the data need to be managed to meet user requirements. The model, which currently contains 48 equations with a menu-driven user interface, is available for use on an IBM PC or AT.

Green, J. L.↗
NASA NTRS1993

Simultaneous laboratory measurements of CO2 and H2O adsorption on palagonite: Implications for the Martian climate and volatile reservoir

We are measuring the simultaneous adsorption of H2O and CO2 on palagonite materials in order to improve the formulation of climate models for Mars. We report on the initial co-adsorption data. Models of the Martian climate and volatile inventory indicate that the regolith serves as one of the primary reservoirs of outgassed volatiles and that it exchanges H2O and CO2 with the atmosphere in response to changes in insolation associated with astronomical cycles. Physical adsorbate must exist on the surfaces of the cold particulates that constitute the regolith, and the size of that reservoir can be assessed through laboratory measurements of adsorption on terrestrial analogs. Many studies of the independent adsorption of H2O and CO2 on Mars analog were made and appear in the literature. Empirical expressions that relate the adsorptive coverage of each gas to the temperature of the soil and partial pressure have been derived based on the laboratory data. Numerical models incorporate these adsorption isotherms into climatic models, which predict how the adsorptive coverage of the regolith and hence, the pressure of each gas in the atmosphere will vary as the planet moves through its orbit. These models suggest that the regolith holds several tens to hundreds of millibars of CO2 and that during periods of high obliquity warming of the high-latitude regolith will result in desorption of the CO2, and a consequent increase in atmospheric pressure. At lower obliquities, the caps cool and the equator warms forcing the desorption of several tens of millibars of CO2, which is trapped into quasipermanent CO2 caps.

Zent, A. P.↗
NASA NTRSDate not supplied

Open Science Practices at the Community Coordinated Modeling Center

Open Science is defined as “the principle and practice of making research products and processes available to all, while respecting diverse cultures, maintaining security and privacy, and fostering collaborations, reproducibility, and equity” by Federal Agencies. The CCMC has been practicing open science based on FAIR (Findable, Accessible, Interoperable and Reusable) principle by providing access to the state-of -the art space science and space weather models to users around the world through various simulation services such as Runs-on-Request, Instant Runs, Real time runs on iSWA system. The CCMC also provides a wide range of tools and framework to help users easily utilize modeled data. One of the tools is the official NASA open-sourced software called Kamodo. Kamodo allows users to work with complex space weather models and data with little or no coding experience. Additionally, to support transparent model validation efforts, the CCMC is providing an integrated and flexible framework called CAMEL. CAMEL allows users to seamlessly compare model outputs with observational data sets. Currently, we are working on a user-friendly database of the papers and research that used CCMC services, so that the future users will have open access to previously performed research by other users and its details. In this presentation, we will show the open tools and resources provided by the CCMC. Furthermore, we will share our new efforts to support open data and open science results.

Ja Soon Shim↗
NASA NTRS2018

Improving the Performance of the OMPS Limb Profiling Instrument in Monitoring Aerosols in the Post-Pinatubo Stratosphere

The OMPS Limb Profiling (LP) instrument was launched on NOAA's Suomi NPP (SNPP) weather satellite in October 2011. The instrument measures limb-scattered radiation in the ultraviolet, visible and NIR wavelengths with high vertical resolution (~2 km) and relatively dense spatial and temporal sampling (several thousand measurements/day covering the entire sunlit globe). These measurements have very high sensitivity to stratospheric aerosols due to long path of the incoming solar photons through the aerosol layer. However, unlike the recently launched ISS/SAGE III that directly measures extinction of solar/lunar radiation by gases and particles along the line of sight (LOS) of the instrument, information content of OMPS LP measurements is complex. It consists of solar radiation singly scattered and attenuated by aerosols, air, and trace gases along the LOS of the instrument, as well as diffuse upwelling radiation from the lower atmosphere that also gets scattered and attenuated into the LOS. To unscramble this complex signal one needs to have good knowledge of aerosol size distribution (ASD) and their complex refractive index. We will describe our recent efforts in constraining the ASD parameters by analyzing in-situ balloon data from Laramie, Wyoming; aerosol microphysical model data from CARMA; and spectral information provided by OMPS LP. We will also discuss our proposed methodology to refine this information by adjusting the microphysical properties of the aerosols to make data from various occultation and scattering instruments internally consistent. This is a generalized version of the technique employed by AERONET in which solar extinction data are combined with scattered radiation measured by the almucantar technique to determine aerosol particle shape, complex refractive index and size distribution. We suggest that such closure studies are essential to develop confidence in space-based data to validate aerosol microphysical models, such as CARMA, and aerosol chemistry- transport models, such as GOCART, and for estimating radiative forcing due to stratospheric aerosols in both volcanic and quiescent time periods.

Bhartia, P. K.↗
NASA NTRS2012

Microwave Satellite Data for Hydrologic Modeling in Ungauged Basins

An innovative flood-prediction framework is developed using Tropical Rainfall Measuring Mission precipitation forcing and a proxy for river discharge from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) onboard the National Aeronautics and Space Administration's Aqua satellite. The AMSR-E-detected water surface signal was correlated with in situ measurements of streamflow in the Okavango Basin in Southern Africa as indicated by a Pearson correlation coefficient of 0.90. A distributed hydrologic model, with structural data sets derived from remote-sensing data, was calibrated to yield simulations matching the flood frequencies from the AMSR-E-detected water surface signal. Model performance during a validation period yielded a Nash-Sutcliffe efficiency of 0.84. We concluded that remote-sensing data from microwave sensors could be used to supplement stream gauges in large sparsely gauged or ungauged basins to calibrate hydrologic models. Given the global availability of all required data sets, this approach can be potentially expanded to improve flood monitoring and prediction in sparsely gauged basins throughout the world

Distributed hydrologic modeling↗
DOE OSTI2026

TSDC: Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

The Transportation Secure Data Center is a centralized repository for high-resolution transportation data from hundreds of travel and transit surveys and studies. It makes vital transportation data broadly available to users while preserving the privacy of survey participants. It houses surveys and studies conducted by state departments of transportation, metropolitan planning organizations, transit agencies, cities, and other public agencies. Meanwhile, the Livewire Data Platform empowers research, industry, and academic partners to easily and securely preserve, maintain, share, discover, and gain access to transportation and mobility data. Livewire accommodates a range of datasets, including behavioral, experimental, model, analytical, and raw data at the vehicle, traveler, and system levels. Datasets support mobility research and planning spanning urban science, connected and automated vehicles, fueling and charging infrastructure, mobility decision science, multimodal transportation, vehicle efficiency, and more.

33 ADVANCED PROPULSION SYSTEMS↗