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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
DOE OSTI2016

Enhancements to the RAVEN code in FY16

The RAVEN code has been under development at the Idaho National Laboratory since 2012. Its main goal is to create a multi-purpose platform for the deploying of all the capabilities needed for Probabilistic Risk Assessment, uncertainty quantification, data mining analysis and optimization studies. RAVEN has currently reached a good level of maturity in terms of deployed state-of-art and advanced capabilities. The main subject of this report is to show the activities that have been recently accomplished: • Implementation of ensemble modeling for time-series, and • initial implementation of model validation for surrogate models, and • advanced visualization capability for topology based data analysis The development of ensemble modeling for time-series has been performed in order to begin tackling the needs of those RISMC applications that need to communicate 1-Dimensional information (e.g. power histories, etc.) among different models. In this document the implementation details and an application example is reported. The second subject of this report is about the initial development of methods, within the RAVEN framework, to assess the validity of the predictive capabilities of surrogate models. Indeed, after the construction of a surrogate tight to a certain physical model, it is crucial to assess the goodness of its representation, in order to be confident with its prediction. In this initial activity, a cross-validation technique has been employed. This report will highlight the implementation details and proof its correct implementation by an application example. The final subject of this report is about the implementation of advanced visualization capability in RAVEN, for interactive data analysis. Indeed, RAVEN offers several post-processing capabilities that can structurally decompose data extracted from experimental results offering both data clustering/partitioning and dimensionality reduction techniques. A disadvantage of the workflow available in RAVEN is that it treats these as black box operations and the user is expected to know specific information about their data including the number of partitions to expect in some cases or the “correct” parameter settings for a particular algorithm. In order to overcome this limitation, it has been added an interactive user interface that can be run in RAVEN to explore different parameter settings on the fly specifically for the topological post-processor and allows the user to explore the data interactively. The design of this user interface is generalizable to other algorithms and can be used as a model to generate more dynamic and user-friendly visualization capabilities within RAVEN.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Estimation of M 1 scissors mode strength for deformed nuclei in the medium- to heavy-mass region by statistical Hauser-Feshbach model calculations

Radiative neutron capture is an important nuclear reaction whose accurate description is needed for many applications ranging from nuclear technology to nuclear astrophysics. The description of such a process relies on the Hauser-Feshbach theory which requires the nuclear optical potential, level density, and γ-strength function as model inputs. It has recently been suggested that the M 1 scissors mode may explain discrepancies between theoretical calculations and evaluated data. We explore statistical model calculations with the strength of the M 1 scissors mode estimated to be dependent on the nuclear deformation of the compound system. We show that the form of the M 1 scissors mode improves the theoretical description of evaluated data and the match to experiment in both the fission product and actinide regions. Since the scissors mode occurs in the range of a few keV to a few MeV, it may also impact the neutron capture cross sections of neutron-rich nuclei that participate in the rapid neutron capture process of nucleosynthesis. As a result, we comment on the possible impact to nucleosynthesis by evaluating neutron capture rates for neutron-rich nuclei with the M 1 scissors mode active.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

Determination of interstellar O parameters using the first two years of data from the Interstellar Boundary Explorer

The direct measurements of interstellar matter by the Interstellar Boundary Explorer (IBEX) mission have opened a new and important chapter in our study of the interactions that control the boundaries of our heliosphere. Here we derive for the quantitative information about interstellar O flow parameters from IBEX low-energy neutral atom data for the first time. Specifically, we derive a relatively narrow four-dimensional parameter tube along which interstellar O flow parameters must lie. Along the parameter tube, we find a large uncertainty in interstellar O flow longitude, 76.°0 ± 3.°4 from χ {sup 2} analysis and 76.°5 ± 6.°2 from a maximum likelihood fit, which is statistically consistent with the flow longitude derived for interstellar He, 75.°6 ± 1.°4. The best-fit O and He temperatures are almost identical at a reference flow longitude of 76°, which provides a strong indication that the local interstellar plasma near the Sun is relatively unaffected by turbulent heating. However, key differences include an oxygen parameter tube for the interstellar speed (relation between speed and longitude) that has higher speeds than those in the corresponding parameter tube for He, and an upstream flow latitude for oxygen that is southward of the upstream flow latitude for helium. Both of these differences are likely the result of enhanced filtration of interstellar oxygen due to its charge-exchange ionization rate, which is higher than that for helium. Furthermore, we derive an interstellar O density near the termination shock of 5.8{sub −0.8}{sup +0.9}×10{sup −5} cm{sup −3} that, within uncertainties, is consistent with previous estimates. Thus, we use IBEX data to probe the interstellar properties of oxygen.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Evaluation of wetland methane emissions across North America using atmospheric data and inverse modeling

Existing estimates of methane (CH 4 ) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH 4 observations from the US and Canada to analyze seven different bottom-up, wetland CH 4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH 4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. Lastly, these models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Shallow (2-meter) Temperature Surveys in Colorado

Shallow temperature surveys are useful in early-stage geothermal exploration to delineate surface outflow zones, with the intent to identify the source of upwelling, usually a fault. Detailed descriptions of the 2-meter survey method and equipment design can be found in Coolbaugh et al. (2007) and Sladek et al. (2007), and are summarized here. The survey method was devised to measure temperature as far below the zone of solar influence as possible, have minimal equilibration time, and yet be portable enough to fit on the back of an all-terrain vehicle (ATV); Figure 2). This method utilizes a direct push technology (DPT) technique where 2.3 m long, 0.54" outer diameter hollow steel rods are pounded into the ground using a demolition hammer. Resistance temperature devices (RTD) are then inserted into the rods at 2-meter depths, and allowed to equilibrate for one hour. The temperatures are then measured and recorded, the rods pulled out of the ground, and re-used at future sites. Usually multiple rods are planted over the course of an hour, and then the sampler returns back to the first station, measures the temperatures, pulls the rods, and so on, to eliminate waiting time. At Wagon Wheel Gap, 32 rods were planted around the hot springs between June 20 and July 1, 2012. The purpose was to determine the direction of a possible upflow fault or other structure. Temperatures at 1.5m and 2m depths were measured and recorded in the attribute table of this point shapefile. Several anomalous temperatures suggest that outflow is coming from a ~N60W striking fault or shear zone that contains the quartz-fluorite-barite veins of the adjacent patented mining claims. It should be noted that temperatures at 2m depth vary according to the amount of solar heating from above, as well as possible geothermal heating from below.

15 GEOTHERMAL ENERGY↗
NASA NTRS2025

Rolling DICE to Advance Knowledge of Land-Atmosphere Interactions

The Diurnal Land-Atmosphere Coupling Experiment (DICE) aims to explore the complex interactions between the land surface and atmospheric boundary layer, which are generally not well understood and difficult to isolate in models. The project involves over 10 different models, combining expertise from both land surface and atmospheric boundary-layer modelling groups. A simple three-stage methodology is designed to assess land-atmosphere feedbacks. Stage 1: the individual components are assessed in isolation, driven and evaluated against observational data; stage 2: the impact of coupling is investigated; stage 3: the sensitivity of the stand-alone models to variations in driving data is explored. For this initial study, a three-day clear-sky period in the mid-west USA over, an assumed simple, predominantly grass surface was simulated using data from the CASES-99 field campaign. Key conclusions from the study include: (1) the memory of vegetation state within Land Surface Models (LSMs) needs attention; (2) the height of atmospheric forcing for LSMs is important, particularly for the nocturnal boundary layer, and this has implications for both observations and vertical resolution for atmospheric models; (3) land-atmosphere feedbacks reduce errors in simulated surface fluxes at the expense of the accuracy of the variables that the models are designed to simulate (e.g., temperature, humidity and wind speed); (4) problems remain in representing the stable boundary layer in atmospheric models; (5) the mixing of temperature and humidity within the boundary layer may need to be represented separately; (6) differences in daytime profiles of heat, moisture and momentum between models are mainly due to the way the models erode the inversion at the top of the boundary layer, rather than differences in the surface fluxes. Resultant variations in modelled boundary layer heights have a substantial impact on relative humidity and could partially explain variations in coupling strength between models in the GLACE experiment.

Martin Best↗
DOE OSTI2023

SAS4A/SASSYS-1 Validation with EBR-II Tests Performed During the SHRT Testing Program (Rev. 2)

The EBR-II sodium-cooled fast reactor supported a wide range of fast reactor research activities. The final fifteen years of operations at EBR-II were used for experiments and tests to demonstrate the importance of passive safety in liquid metal reactors and the capability of such systems to provide strong passive responses during off-normal conditions. The Shutdown Heat Removal Test program at EBR-II provided test data supporting the validation of computer codes for design, licensing, and operation of LMRs, among other objectives. The program included nearly sixty tests, most of which were protected and unprotected loss of flow and loss of heat sink tests run at various initial powers and flow rates. This report documents the results of modeling and simulation of tests from the Shutdown Heat Removal Test program to support validation of Argonne’s SAS4A/SASSYS-1 fast reactor safety analysis code. SHRT-17 and SHRT-6 were protected loss of flow tests where a loss of electrical power to all sodium coolant pumps was simulated to demonstrate the effectiveness of natural circulation cooling characteristics. SHRT-45R, SHRT-39, and SHRT-43R were unprotected loss of flow tests where the control rod scram function of the plant protection system was disabled to demonstrate the effectiveness of EBR-II’s passive reactivity feedbacks. BOP-301 and BOP-302R were unprotected loss of heat sink tests that demonstrated how reactivity feedback effects driven by changes to the core inlet temperature can shut down the fission process. PICT-5/6 demonstrated how core power could be increased and decreased via changes in the intermediate sodium and feedwater flow rates. This validation activity leverages modeling and simulation efforts that originated under an International Atomic Energy Agency Coordinated Research Project for benchmark analysis of the EBR-II Shutdown Heat Removal Tests. The SAS4A/SASSYS-1 models originally developed for the CRP have been modernized to utilize new code features and modeling practices. Differences between the predicted and measured test data were explored and the causes of these differences were identified as being due to modeling approximations, uncertainty in transient component behavior, and instrumentation uncertainties. Overall, it was concluded that for all tests simulated there was good agreement between the flow, power, and temperature predictions and the measured data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1972

Ionosphere total electron measurements as extracted from satellite tracking data

The Goddard Range and Range Rate System (GRARR) determines the range of a spacecraft by measuring the group delay of a modulated wave and the range rate by measuring the Doppler phase shift of the carrier. An analytical technique is presented for obtaining corrections and equivalent total electron content along the vertical, using VHF GRARR data and a radial model of the ionosphere. The results of computation for a representative pass are given, and estimated accuracy is discussed from a statistical view point. Using VHF GRARR data and a radial model of the ionosphere. The results of computation for a representative pass are given, and estimated accuracy is discussed from a statistical view point. Using GRARR range, range rate, and angle tracking data from Explorer 41, values of total electron content on the order of 10 to the 17th to 10 to the 18th power (electrons/sq m) were obtained. These values agree with estimates of the total electron content from ionospheric profiles using f sub o F sub 2 predict data.

Murray, C. W., Jr.↗
NASA NTRS1978

Interplanetary magnetic field variations and the electromagnetic state of the equatorial ionosphere

The Esq phenomena were selected in order to examine the effect of the interplanetary magnetic field (IMF) on the ionospheric plasma and to obtain insight into the interplanetary ionospheric coupling processes. January-March 1973 interplanetary magnetic field data of Explorer 43, Huancayo ionograms, and surface equatorial magnetograms were used. The IMF observations from Explorer 43 in the form of 15-sec averages were examined around the time of disappearance of the Esq. The IMF z-component was observed to change from a negative to a positive value before the disappearance of the Esq in four events where simultaneous data were available. The general explanation is that the induced electric field becomes westward from a previous eastward direction, coinciding with the IMF z-component reversal. Thus, just before the Esq disappears, the magnetosphere is subjected to the westward electric field. If this field is impressed to the low-latitude ionosphere, the resultant electric field in the equatorial ionosphere changes from eastward (westward) to westward (eastward) in the daytime (nighttime).

Patel, V. L.↗
DOE OSTI2018

Uncertainty quantification in ToxCast high throughput screening

High throughput screening (HTS) projects like the U.S. Environmental Protection Agency’s ToxCast program are required to address the large and rapidly increasing number of chemicals for which we have little to no toxicity measurements. Concentration-response parameters such as potency and efficacy are extracted from HTS data using nonlinear regression, and models and analyses built from these parameters are used to predict in vivo and in vitro toxicity of thousands of chemicals. How these predictions are impacted by uncertainties that stem from parameter estimation and propagated through the models and analyses has not been well explored. While data size and complexity makes uncertainty quantification computationally expensive for HTS datasets, continued advancements in computational resources have allowed these computational challenges to be met. This study uses nonparametric bootstrap resampling to calculate uncertainties in concentration-response parameters from a variety of HTS assays. Using the ToxCast estrogen receptor model for bioactivity as a case study, we highlight how these uncertainties can be propagated through models to quantify the uncertainty in model outputs. Uncertainty quantification in model outputs is used to identify potential false positives and false negatives and to determine the distribution of model values around semi-arbitrary activity cutoffs, increasing confidence in model predictions. At the individual chemical-assay level, curves with high variability are flagged for manual inspection or retesting, focusing subject-matter-expert time on results that need further input. This work improves the confidence of predictions made using HTS data, increasing the ability to use this data in risk assessment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Can we safely go to 200 °C? An integrated approach to assessing impacts to the engineered barrier system in a high-temperature repository

Abstract. This presentation gives on overview of the complex thermo-hydro-mechanical-chemical (THMC) processes occurring during the disposal of heat-producing high-level radioactive waste in geologic repositories. A specific focus is on the role of compacted bentonite, which is commonly used as an engineered backfill material for emplacement tunnels because of its low permeability, high swelling pressure, and radionuclide retention capacity. Laboratory and field tests integrated with THMC modeling have provided an effective way to deepen our understanding of temperature-related perturbations in the engineered barrier system; however, most of this work has been conducted for maximum temperatures around 100 ∘C. In contrast, some international disposal programs have recently started investigations to understand whether local temperatures in the bentonite of up to 200 ∘C could be tolerated with no significant changes to safety relevant properties. Raising the maximum temperature is attractive for economical and safety reasons but faces the challenge of exposing the bentonite to significant temperature increases. Strong thermal gradients may induce complex moisture transport processes while geochemical processes, such as cementation and perhaps also illitization effects may occur, all of which could strongly affect the bentonite and near-field rock properties. Here, we present initial investigations of repository behavior exposed to strongly elevated temperatures. We will start discussing our current knowledge base for temperature effects in repositories exposed to a maximum temperature of 100 ∘C, based on data and related modeling analysis from a large heater experiment conducted for over 18 years in the Grimsel Test Site in Switzerland. We then show results from coupled THMC simulations of a nuclear waste repository in a clay formation exposed to a maximum temperature of 200 ∘C. We also explore preliminary data from a bench-scale laboratory mock-up experiment, which was designed to represent the strong THMC gradients occurring in a “hot” repository, and we finally touch on a full-scale field heater test to be conducted soon in the Grimsel Test Site underground research laboratory in Switzerland (referred to as HotBENT).

Birkholzer, Jens T. (ORCID:0000000279891912)↗
DOE OSTI2025

Investigating Kinetic Mechanisms of Soot Formation in Plasma Pyrolysis of Methane via Active Learning (Final Technical Report)

Plasma pyrolysis of methane is an effective route for zero-carbon hydrogen production. Yet, soot generated from pyrolysis of hydrocarbons is detrimental to the climate and human health. There is ample experimental and theoretical evidence that suggests polycyclic aromatic hydrocarbons (PAHs) are the molecular precursors to soot particles. The reaction pathways of PAH formation are intricately dependent on a multitude of process parameters, whose kinetic mechanisms are not well-understood in plasma pyrolysis. This project aims to leverage advances in the kinetic modeling of soot formation in combustion, as well as in surrogate modeling and active learning, to systematically investigate the effects of process parameter on the kinetics of PAH formation in plasma pyrolysis of methane. To this end, we propose to use the PAH formation kinetics model developed by the PPPL/PU group based on the well-established ABF and HACA mechanisms, coupled with low-temperature plasma models. We will develop an active learning (AL) framework based on Bayesian optimization to systematically and data-efficiently explore the complex and multivariable parameter space of plasma pyrolysis in order to quantify the effects of plasma and feed parameters on the ABF and HACA kinetic pathways. AL is the branch of machine learning concerned with systematically querying samples from a system (experimental or computational) to train a data-driven model that maps design parameters to a performance criterion. We will use the data generated via AL to perform global sensitivity analysis, combined with uncertainty quantification, to elucidate the impact of different reaction pathways on minimizing formation of soot precursors. This study will result in an improved understanding of kinetics of PAH formation in plasma pyrolysis and can pave the way for more advanced mechanistic studies (e.g., soot nucleation mechanisms). Additionally, the findings will be useful for establishing practical strategies for increasing the pyrolysis efficiency and producing high-grade carbon for synthesis of nanomaterials.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Machine-learned closure of URANS for stably stratified turbulence: connecting physical timescales & data hyperparameters of deep time-series models

Stably stratified turbulence (SST), a model that is representative of the turbulence found in the oceans and atmosphere, is strongly affected by fine balances between forces and becomes more anisotropic in time for decaying scenarios. Moreover, there is a limited understanding of the physical phenomena described by some of the terms in the Unsteady Reynolds-Averaged Navier–Stokes (URANS) equations—used to numerically simulate approximate solutions for such turbulent flows. Rather than attempting to model each term in URANS separately, it is attractive to explore the capability of machine learning (ML) to model groups of terms, i.e. to directly model the force balances. We develop deep time-series ML for closure modeling of the URANS equations applied to SST. We consider decaying SST which are homogeneous and stably stratified by a uniform density gradient, enabling dimensionality reduction. We consider two time-series ML models: long short-term memory and neural ordinary differential equation. Both models perform accurately and are numerically stable in a posteriori (online) tests. Furthermore, we explore the data requirements of the time-series ML models by extracting physically relevant timescales of the complex system. We find that the ratio of the timescales of the minimum information required by the ML models to accurately capture the dynamics of the SST corresponds to the Reynolds number of the flow. The current framework provides the backbone to explore the capability of such models to capture the dynamics of high-dimensional complex dynamical system like SST flows.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

The 1% concordance Hubble constant

The determination of the Hubble constant has been a central goal in observational astrophysics for nearly a hundred years. Extraordinary progress has occurred in recent years on two fronts: the cosmic distance ladder measurements at low redshift and cosmic microwave background (CMB) measurements at high redshift. The CMB is used to predict the current expansion rate through a best-fit cosmological model. Complementary progress has been made with baryon acoustic oscillation (BAO) measurements at relatively low redshifts. While BAO data do not independently determine a Hubble constant, they are important for constraints on possible solutions and checks on cosmic consistency. A precise determination of the Hubble constant is of great value, but it is more important to compare the high and low redshift measurements to test our cosmological model. Significant tension would suggest either uncertainties not accounted for in the experimental estimates or the discovery of new physics beyond the standard model of cosmology. In this paper we examine in detail the tension between the CMB, BAO, and cosmic distance ladder data sets. We find that these measurements are consistent within reasonable statistical expectations and we combine them to determine a best-fit Hubble constant of 69.6 ± 0.7 km s{sup –1} Mpc{sup –1}. This value is based upon WMAP9+SPT+ACT+6dFGS+BOSS/DR11+H {sub 0}/Riess; we explore alternate data combinations in the text. The combined data constrain the Hubble constant to 1%, with no compelling evidence for new physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Improving Cosmological Constraints from Galaxy Cluster Number Counts with CMB-cluster-lensing Data: Results from the SPT-SZ Survey and Forecasts for the Future

Abstract We show the improvement to cosmological constraints from galaxy cluster surveys with the addition of cosmic microwave background (CMB)-cluster lensing data. We explore the cosmological implications of adding mass information from the 3.1 σ detection of gravitational lensing of the CMB by galaxy clusters to the Sunyaev–Zel’dovich (SZ) selected galaxy cluster sample from the 2500 deg 2 SPT-SZ survey and targeted optical and X-ray follow-up data. In the ΛCDM model, the combination of the cluster sample with the Planck power spectrum measurements prefers σ 8 Ω m / 0.3 0.5 = 0.831 ± 0.020 . Adding the cluster data reduces the uncertainty on this quantity by a factor of 1.4, which is unchanged whether the 3.1 σ CMB-cluster lensing measurement is included or not. We then forecast the impact of CMB-cluster lensing measurements with future cluster catalogs. Adding CMB-cluster lensing measurements to the SZ cluster catalog of the ongoing SPT-3G survey is expected to improve the expected constraint on the dark energy equation of state w by a factor of 1.3 to σ ( w ) = 0.19. We find the largest improvements from CMB-cluster lensing measurements to be for σ 8 , where adding CMB-cluster lensing data to the cluster number counts reduces the expected uncertainty on σ 8 by respective factors of 2.4 and 3.6 for SPT-3G and CMB-S4.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1997

Lunar and Planetary Science XXVIII

The present conference discusses such topics as density crossovers in lunar picrites, the geology of the Cassini impact basin, Mars, nanobacteria in carbonates, the properties of shocked aerogels, a chemical model of Comet Halley, lunar mascons, the impact evolution of icy regoliths, the geology of the Venera 8 landing site, the photogeologic mapping of northern Venus, HST observations of Mars, observational constraints on the rotational dynamics of Mars, and primordial magnetic field measurements from the moon. Also discussed are models of the S2 fluorescence spectra of comets, Martian crater ejecta, the heights of Venusian steep-sided domes, cloud-climate interactions on Venus, the Humorum basin geology from Clementine data, an early Amazonian lake in the Gale crater of Mars, nebular fractionations and Mn-Cr systematics, the Rock Chipper planetary surface sample collection, Mariner 10 stereo images of Mercury, remote and local stresses and Calderas on Mars, the electrostatic charging of saltating particles, SO2 detected on Callisto, the Mars Explorer Planetary Data System, an assessment of explosive venting on Europa, the sequential faulting history of the Mars Valles Marineris, a search for Martian sediments, the composition and internal structure of Europa, long-term and 'diurnal' tidal stresses on Europa, and episodic greenhouse climates on Mars.

Source record↗
NASA NTRSDate not supplied

Data Integrity Challenges in NASA Giovanni

The Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) is an online tool developed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA Science Mission Directorate Data Centers (DAACs) to analyze and visualize NASA remote sensing and model data without downloading data and software. As of this writing, over 2000 Earth satellite and model variables are available in Giovanni, including several well-known NASA satellite missions (e.g., TRMM, GPM) and projects (e.g., MERRA-2, GPCP). There are twenty-two plots provided by Giovanni that can be used to analyze, compare, and explore Earth data across disciplines. Results can be shared with colleagues and downloaded for further analysis. Giovanni has helped publish over 3000 referral papers over the years. As open science policies roll in, data integrity has become a major challenge for Giovanni and other tools. For integrity, both data and workflows must be transparent. FAIR-compliant data, including input, intermediate, and result products, as well as their associated statistics, metadata, and information, are needed. The NASA Data Product Development Guide for Data Producers provides a key resource on how to develop FAIR-compliant data products. Data quality information is also needed from data producers and analysis services like Giovanni. The workflow part is quite challenging and requires workflow management improvements, such as recording workflows and making them available to users. In this presentation, we will discuss the data integrity challenges in Giovanni.

data analysis, visualization↗
DOE OSTI2025

Unlocking nighttime mobility: Land use and accessibility in public transit for night commuters

Night commuters are integral to urban transportation systems. Essential services such as healthcare and manufacturing rely on workers who travel at night, and reliable mobility options are crucial for them. A gap exists in understanding how land use and accessibility influence public transportation use among night commuters. This study addresses this gap by using public data to explore land use and accessibility factors that affect night commuters' public transportation use in New York State. We investigated (1) the demographic characteristics of night commuters; (2) the influence of land use and accessibility on nighttime public transportation use; and (3) potential improvements to increase public transportation use and their impact. We combined data from the National Household Travel Survey with the Smart Location Database to link home locations with land use characteristics. Using logistic regression, we found that although females are generally less likely to be night commuters, they are more likely to use public transportation. Longer commute distances are associated with higher use of public transportation. Increasing job density along fixed-guideway transit routes and improving overall job accessibility via public transportation significantly enhances public transportation use among night commuters. In conclusion, this research provides actionable insights for public transportation agencies and urban planners to support night commuters, improving access and encouraging nighttime employment.

Job accessibility↗