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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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Pathfinder Networks for Measuring Operator Mental Model Structure with a Simple Autopilot System

Pathfinder networks are a method to represent mental models from empirically generated pairwise relatedness ratings. This study examined the effects of training exposure on mental model structures based on relatedness ratings collected using the Target Rating method. Forty-eight participants read instruction slides with or without explicit information on the functionality of an autopilot system (Advanced Mental Model or Basic Mental Model groups, respectively). Participants provided relatedness ratings and completed a comprehension test. The Advanced Mental Model group had more common links with the expected model, higher within-group network similarity scores, and higher mental model assessment questionnaire scores than the Basic Mental Model group. Both groups had coherence scores above the minimum threshold for internal consistency. Pathfinder network analysis was sensitive to changes produced by a simple exposure training intervention. In practice, a simple training program may effectively influence operator mental models in novel technological environments such as Advanced Air Mobility.

Mental Models↗
DOE OSTI2025

Comparison of removal and spatial mark‐resight models for estimating wild pig density

Density estimation is critical to effectively manage invasive species and elucidate areas of highest concern. For wild pigs (Sus scrofa), the ability to estimate density is complicated because of their variable home range sizes and social structure. Common methods for estimating density (e.g., mark-recapture) may be unsuitable in management applications because additional data needs to be collected before and after management. Removal models offer a suitable alternative to estimate density changes following management and can be applied broadly across areas where management of wild pigs is ongoing. We collected wild pig removal and camera trap data from 25 private properties ranging in size from approximately 0.5 km 2 to 95 km 2 across 3 ecoregions in South Carolina, USA, from 2020–2023. We compared factors affecting consistency and precision of property-level density estimates between removal and spatial mark-resight (SMR) models. In general, excluding 1 large outlier, density estimates from removal models were between 0.60 and 15.85 wild pigs/km 2 (median = 5.34) with a median coefficient of variation (CV) of 0.76 and 95% confidence intervals for the CV between 0.70 and 0.94. Similarly, excluding 1 large outlier, density estimates from SMR were between 0.22 and 30.97 wild pigs/km 2 (median = 5.48) with a median CV of 0.39 and 95% confidence intervals for the CV between 0.38 and 1.20. We found the precision of removal models was affected primarily by the number of wild pigs dispatched in the removal period (3 months) and the ecoregion in which they were removed. None of the covariates, including the number of recaptures (a corresponding measure of sample size), influenced precision of the SMR models, although recaptures did influence the density estimates. At the individual property level, density estimates from our 2 estimators were dissimilar from each other in approximately 80% of instances, although none of the covariates we examined influenced dissimilarity. Our results provide unique insight into how sample size affects density estimates using 2 common methods and into novel SMR models that incorporate both marked and unmarked detections. In addition, the density estimates in this study can be used as a reference for wild pig densities in common land cover types throughout the southeastern United States.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

An information-matching approach to optimal experimental design and active learning

The efficacy of mathematical models heavily depends on the quality of the training data, yet collecting sufficient data is often expensive and challenging. Many modeling applications require inferring parameters only as a means to predict other quantities of interest (QoI). Because models often contain many unidentifiable (sloppy) parameters, QoIs often depend on a relatively small number of parameter combinations. Therefore, we introduce an information-matching criterion based on the Fisher information matrix to select the most informative training data from a candidate pool. This method ensures that the selected data contain sufficient information to learn only those parameters that are needed to constrain downstream QoIs. It is formulated as a convex optimization problem, making it scalable to large models and datasets. Here, we demonstrate the effectiveness of this approach across various modeling problems in diverse scientific fields, including power systems and underwater acoustics. Finally, we use information-matching as a query function within an active learning (AL) loop for materials science applications. In all these applications, we find that a relatively small set of optimal training data can provide the necessary information for achieving precise predictions. These results are encouraging for diverse future applications, particularly AL in large machine-learning models.

Materials science↗
NASA NTRS1995

Mars Pathfinder Project: Planetary Constants and Models

This document provides a common set of astrodynamic constants and planetary models for use by the Mars Pathfinder Project. It attempts to collect in a single reference all the quantities and models in use across the project during development and for mission operations. These models are central to the navigation and mission design functions, but they are also used in other aspects of the project such as science observation planning and data reduction.

Vaughan, Robin↗
NASA NTRS1999

Mars Pathfinder Project: Planetary Constants and Models

This document provides a common set of astrodynamic constants and planetary models for use by the Mars pathfinder Project. It attempts to collect in a single reference all the quantities and models in use across the project during development and for mission operations.

Mars Pathfinder Planetary Constants↗
NASA NTRS2012

Spatial and Temporal Variations in Titan's Surface Temperatures from Cassini CIRS Observations

We report a wide-ranging study of Titan's surface temperatures by analysis of the Moon's outgoing radiance through a spectral window in the thermal infrared at 19 mm (530/cm) characterized by lower atmospheric opacity. We begin by modeling Cassini Composite Infrared Spectrometer (CIRS) far infrared spectra collected in the period 2004-2010, using a radiative transfer forward model combined with a non-linear optimal estimation inversion method. At low-latitudes, we agree with the HASI near-surface temperature of about 94 K at 101S (Fulchignoni et al., 2005). We find a systematic decrease from the equator toward the poles, hemispherically asymmetric, of approx. 1 K at 60 deg. south and approx. 3 K at 60 deg. north, in general agreement with a previous analysis of CIRS data and with Voyager results from the previous northern winter. Subdividing the available database, corresponding to about one Titan season, into 3 consecutive periods, small seasonal changes of up to 2 K at 60 deg N became noticeable in the results. In addition, clear evidence of diurnal variations of the surface temperatures near the equator are observed for the first time: we find a trend of slowly increasing temperature from the morning to the early afternoon and a faster decrease during the night. The diurnal change is approx. 1.5 K, in agreement with model predictions for a surface with a thermal inertia between 300 and 600 J/ sq. m s (exp -1/2) / K. These results provide important constraints on coupled surface-atmosphere models of Titan's meteorology and atmospheric dynamic.

titan↗
DOE OSTI2024

Bayesian analysis of (3 +1)⁢D relativistic nuclear dynamics with the RHIC beam energy scan data

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the beam energy scan program at the BNL Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)-dimensional [(3+1)⁢D] collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the quark-gluon plasma's transport properties and various aspects of (3+1)⁢D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for p T -differential observables and estimate their systematic theory uncertainty. Here, a sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1982

Radiation effects studies for the high-resolution spectrograph

The generation and collection of charge carriers created during the passage of energetic protons through a silicon photodiode array are modeled. Pulse height distributions of noise charge collected during exposure of a digicon type diode array to 21 and 75 MeV protons were obtained. The magnitude of charge collected by a diode from each proton event is determined not only by diffusion, but by statistical considerations involving the ionization process itself. Utilizing analytical solutions to the diffusion equation for transport of minority carriers, together with the Vavilov theory of energy loss fluctuations in thin absorbers, simulations of the pulse height spectra which follow the experimental distributions fairly well are presented and an estimate for the minority carrier diffusion length L sub d is provided.

Smith, L. C.↗
NASA NTRS2010

The Value of Biomedical Simulation Environments to Future Human Space Flight Missions

With the ambitious goals to send manned missions to asteroids and onto Mars, substantial work will be required to ensure the well being of the men and women who will undertake these difficult missions. Unlike current International Space Station or Shuttle missions, astronauts will be required to endure long-term exposure to higher levels of radiation, isolation and reduced gravity. These new operation conditions will pose health risks that are currently not well understood and perhaps unanticipated. Therefore, it is essential to develop and apply advanced tools to predict, assess and mitigate potential hazards to astronaut health. NASA s Digital Astronaut Project (DAP) is working to develop and apply computational models of physiologic response to space flight operation conditions over various time periods and environmental circumstances. The collective application and integration of well vetted models assessing the physiology, biomechanics and anatomy is referred to as the Digital Astronaut. The Digital Astronaut simulation environment will serve as a practical working tool for use by NASA in operational activities such as the prediction of biomedical risks and functional capabilities of astronauts. In additional to space flight operation conditions, DAP s work has direct applicability to terrestrial biomedical research by providing virtual environments for hypothesis testing, experiment design, and to reduce animal/human testing. A practical application of the DA to assess pre and post flight responses to exercise is illustrated and the difficulty in matching true physiological responses is discussed.

Mulugeta, Lealem↗
NASA NTRS2012

Light Curve Observations of Upper Stages in the Low Earth Orbit Environment

Active debris removal (ADR) is a potential means to remediate the orbital debris environment in low Earth orbit (LEO). Massive intact objects, including spent upper stages and retired payloads, with high collision probabilities have been suggested as potential targets for ADR. The challenges to remove such objects on a routine basis are truly monumental. A key piece of information needed for any ADR operations is the tumble motion of the targets. Rapid tumble motion (in excess of one degree per second) of a multiple-ton intact object could be a major problem for proximity and docking operations. Therefore, there is a need to characterize the general tumble motion of the potential ADR targets for future ADR planning. The NASA Orbital Debris Program Office has initiated an effort to identify the global tumble behavior of potential ADR targets in LEO. The activities include optical light curve observations, imaging radar data collection, and laboratory light curve simulations and modeling. This paper provides a preliminary summary of light curve data of more than 100 upper stages collected by two telescope facilities in Colorado and New Mexico between 2011 and 2012. Analyses of the data and implications for the tumble motions of the objects are also discussed in the paper.

Liou, J.-C.↗
NASA NTRSDate not supplied

Microbial Pigments and Their Degradation Products as Biosignatures

Carotenoids are a class of vibrant biological pigments that have a characteristic chemical structure centered around a polyene core (Lu et al. 2018). Carotenoids and their derivatives are candidate biosignatures because they can persist in the terrestrial geologic record for up to 1.73 billion years (Vinnichenko et al. 2020), have specific structures that are likely the result of complex pathways, mediate the survival of many microorganisms in Mars and Ocean Worlds analog environments, and are detectable with multiple techniques, including Raman spectroscopy. In this project, we aim to investigate the detectability of carotenoid pigments with different spectroscopic methods to inform future instrument selection. We compare the spectra of five unaltered carotenoids, two model compounds, and carotenoid-forming archaeon with visible and deep UV Raman spectroscopy and UVVis absorption spectrophotometry. We then use one model pigment, beta-carotene, to evaluate the likelihood that unique spectral properties of carotenoids, or their refractory byproducts, would be preserved and detectable on a remote planetary surface by exposing it to simulated conditions for Mars. Sample Acquisition. Pigments betacarotene, lutein, zeaxanthin, astaxanthin, and lycopene were purchased from Sigma Aldrich. Halobacterium salinarum NRC-1 was acquired from Carlina Biological and grown in Halobacterium media. Mineral salts including sodium sulfate, sodium carbonate, and halite were used to form matrices in which the beta-carotene was embedded before exposure. Pigment-mineral mixes were at a 1:10 ratio in water. Analytical Techniques. Deep UV Raman data were collected on a custom laboratory mapping spectrometer called MOBIUS (Mineral and Organic Based Investigations using Ultraviolet Spectroscopy), which is an analog to the SHERLOC instrument on the Mars 2020 Perseverance rover (Bhartia et al. 2021). It features a 248.56 nm NeCu pulsed laser, liquid nitrogen-cooled detector, and tunable optical setup. Visible Raman data were collected using a Horiba Jobin Yvon LabRam HR spectrometer with a frequencydoubled Nd:YAG laser (532 nm) and a HeNe laser (633 nm). A VWR 6300 PC UV/Visible Spectrophotometer was used to collect absorption data for carotenoid solutions, model compounds, and solvents in UVpermissible capped cuvettes. Data were collected from 190-1100 nm at 1 nm increments. All spectral data were analyzed using Igor Pro 9 (Wavemetrics). Irradiation. We used a vacuum chamber equipped with a cryostat and a flood electron gun to simulate Martian surface temperatures, low pressures, and ionizing radiation (10keV, 10μA for 6h at 200K for our initial tests). The samples were prepared by drying the pigment-mineral mix onto polished metal tabs, then mounted on the cryostat for processing. Samples were then analyzed directly on the tabs after exposure. Results: In comparing the visible and deep UV Raman spectra of unaltered pigments, we found that they differed drastically. Carotenoids are often studied with visible Raman and typically have peaks at 1525 cm-1 and 1157 cm-1, due to the stretching of the C=C and C-C bonds in the polyene structure. However, in deep UV, the strongest feature is at ~1630 cm-1 and is broad, possibly indicating that multiple peaks are forming this feature. This stark difference is likely due to different preresonant enhancement effects. The UV-Vis results show that there is an absorption band in the deep UV <300 nm, which supports the hypothesis that the 248.6 nm excitation is interrogating another aspect of carotenoids than visible Raman. Our preliminary exposure tests indicated that pigments – even without minerals present - were largely unaltered in the applied conditions, with only a slight broadening in the primary polyene peaks apparent in the visible Raman data. Figure 1. A) Visible vs. deep UV Raman spectra of unaltered beta carotene. B) Schematic of exposure. Conclusions: Our results to date indicate that deep UV and visible Raman spectroscopy, both techniques with planetary mission heritage from Mars 2020 (Wiens et al. 2021, Bhartia et al. 2021), may be used in a complementary manner to observe carotenoids. In addition, we find that beta-carotene is largely resistant to our current exposure conditions, though there may be some amount of amorphization of the material which could cause the broadening of the peaks at 1525 and 1157 cm-1. As a next step, we aim to increase the dosage and duration of exposure to observe degradation of the parent pigment, possibly add UV as a factor via an Ar mini-arc UV lamp and use GC-MS to characterize possible degradation products.

pigments↗
NASA NTRS1991

An experimental investigation of hollow cathode-based plasma contactors

Experimental results are presented which describe operation of the plasma environment associated with a hollow cathod-based plasma contactor collecting electrons from or emitting them to an ambient, low density Maxwellian plasma. A one-dimensional, phenomenological model of the near-field electron collection process, which was formulated from experimental observations, is presented. It considers three regions, namely, a plasma cloud adjacent to the contactor, an ambient plasma from which electrons are collected, and a double layer region that develops between the contactor plasma cloud and the ambient plasma regions. Results of the electron emission experiments are also presented. An important observation is made using a retarding potential analyzer (RPA) which shows that high energy ions generally stream from a contactor along with the electrons being emitted. A mechanism for this phenomenon is presented and it involves a high rate of ionization induced between electrons and atoms flowing together from the hollow cathode orifice. This can result in the development of a region of high positive potential. Langmuir and RPA probe data suggest that both electrons and ions expand spherically from this hill region. In addition to experimental observations, a one-dimensional model which describes the electron emission process and predicts the phenomena just mentioned is presented and shown to agree qualitatively with these observations.

Williams, John D.↗
NASA NTRS2021

Spectrophotometric Modeling and Mapping of (101955) Bennu

Using hyperspectral data collected by OVIRS, the visible and infrared spectrometer onboard the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security–Regolith Explorer) spacecraft, we modeled the global average spectrophotometric properties of the carbonaceous asteroid (101955) Bennu and mapped their variations. We restricted our analysis to 0.4–2.5 µm to avoid the wavelengths where thermal emission from the asteroid dominates (>2.5 µm). Bennu has global photometric properties typical of dark asteroids; we found a geometric albedo of 0.046 ± 0.007 and a linear phase slope of 0.024 ± 0.007 mag deg–1 at 0.55 µm. The average spectral slope of Bennu’s normal albedo is –0.0030 µm–1, and the phase reddening parameter is 4.3´10–4 µm–1 deg–1, both over the spectral range of 0.5–2.0 µm. We produced normal albedo maps and phase slope maps at all spectral channels, from which we derived spectral slope and phase reddening maps. Correlation analysis suggests that phase slope variations on Bennu are likely due to photometric roughness variation. A correlation between photometric roughness and thermal roughness is evident, implying that the roughness of Bennu is self-similar on scales from tens of microns to meters. Our analysis reveals latitudinal trends in the spectral color slope and phase reddening on Bennu. The equatorial region appears to be redder than the global average, and the spectral slope decreases towards higher latitudes. Phase reddening on Bennu is relatively weak in the equatorial region and shows an asymmetry between the northern and southern hemispheres. We attributed the latitudinal trend to the geophysical conditions on Bennu that result in a global pattern of mass flow towards the equator.

Jian-Yang Li (李荐扬)↗
DOE OSTI2026

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗
DOE OSTI2025

Informed Investments in Clean Energy Technologies

Governments and companies face consequential decisions about allocating resources to the research, development, demonstration and deployment of energy technologies to meet environmental, economic and social goals. Here we discuss how research insights can inform and potentially improve these decisions to make effective use of limited resources and time in shaping the next-generation energy infrastructure. We outline three key research steps: forecasting technological change, relating investments to economic, social and environmental outcomes and informing decision-making processes. We recommend advances to address uncertainty as well as to make methods and results more practicable, emphasizing the importance of model validation, streamlining and interactivity. Progress has been made, yet further work is needed-for example, in the development of reduced-order, testable models and more comprehensive data collection. Overall, this research is beginning to inform decisions but could be adopted more widely by governments and the private sector to help support technological progress for energy affordability, equitable climate change mitigation, health benefits and other objectives.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

A compendium of multi-omics data illuminating host responses to lethal human virus infections

Human infections caused by viral pathogens trigger a complex gamut of host responses that limit disease, resolve infection, generate immunity, and contribute to severe disease or death. Here, we present experimental methods and multi-omics data capture approaches representing the global host response to infection generated from 45 individual experiments involving human viruses from the Orthomyxoviridae, Filoviridae, Flaviviridae, and Coronaviridae families. Analogous experimental designs were implemented across human or mouse host model systems, longitudinal samples were collected over defined time courses, and global multi-omics data (transcriptomics, proteomics, metabolomics, and lipidomics) were acquired by microarray, RNA sequencing, or mass spectrometry analyses. For comparison, we have included transcriptomics datasets from cells treated with type I and type II human interferon. Raw multi-omics data and metadata were deposited in public repositories, and we provide a central location linking the raw data with experimental metadata and ready-to-use, quality-controlled, statistically processed multi-omics datasets not previously available in any public repository. This compendium of infection-induced host response data for reuse will be useful for those endeavouring to understand viral disease pathophysiology and network biology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Shared Use Travel Behavior for Improving Rural Mobility: Insights from Greene County, Pennsylvania

Rural communities are considered disadvantaged communities as they suffer from a lack of transport options. Thus, rural regionsprovide less accessibility for commuters to reach their destination as opposed to urban regions. However, the issues of transport disadvantageand shared use mobility in rural areas within the United States (US) have not been well investigated. Furthermore, transport disadvantagediffers between communities and regions across the globe; thus, there is a need to study the behavioral choices of rural commuters within theUS context. This study contributes by analyzing the behavioral choices of rural communities within the US through a case study site ofWaynesburg, Pennsylvania, for adopting a shared use shuttle service. K-means clusters showed that trips from the survey data were a goodrepresentation of real trips from Ecolane. Furthermore, random parameter-based binary logit models were calibrated using data collected fromstudents, faculty, and residents in Waynesburg, Greene County, to study the behavioral choices of commuters. The findings for the faculty andstudents group revealed that prior experience with shared services increases the likelihood of using a shared shuttle. An important personalcharacteristic of inconvenience showed a higher propensity toward using existing modes as opposed to a shared shuttle. Such commutersvalue personal vehicles as more convenient as they have childcare responsibilities and varying schedules for work that require them to moveback and forth across locations, thus making a shared shuttle less attractive for them. The socioeconomic factors of age and gender show ahigher propensity for using shared shuttles. Furthermore, the findings from this study could be helpful for agencies in improving rural mobility andconsidering such shared mobility services for rural communities

42 ENGINEERING↗
DOE OSTI2024

Machine learning analysis of high-repetition-rate two-dimensional Thomson scattering spectra from laser-produced plasmas

With the emergence of high-repetition-rate two-dimensional Thomson scattering (TS) measurements, improving spectral data analysis is a key area of interest. Here, we present a new way to derive the electron temperature and density of laser-driven blast waves in plasmas from their TS spectra with machine learning (ML). This analysis occurs in both the non-collective (α < 1) and collective (α > 1) scattering regimes with the goal of autonomously and more accurately determining T c and n e both where spectral data has been collected and to give the ability to predict these attributes in regions where data has not been collected. We introduce three ML models, one trained only on experimental data, one only on synthetic data, and one using transfer learning, and compare their speed and accuracy with the conventional TS inversion algorithms in the open source PlasmaPy python package.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗