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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Synthetic perspective optical flow: Influence on pilot control tasks

One approach used to better understand the impact of visual flow on control tasks has been to use synthetic perspective flow patterns. Such patterns are the result of apparent motion across a grid or random dot display. Unfortunately, the optical flow so generated is based on a subset of the flow information that exists in the real world. The danger is that the resulting optical motions may not generate the visual flow patterns useful for actual flight control. Researchers conducted a series of studies directed at understanding the characteristics of synthetic perspective flow that support various pilot tasks. In the first of these, they examined the control of altitude over various perspective grid textures (Johnson et al., 1987). Another set of studies was directed at studying the head tracking of targets moving in a 3-D coordinate system. These studies, parametric in nature, utilized both impoverished and complex virtual worlds represented by simple perspective grids at one extreme, and computer-generated terrain at the other. These studies are part of an applied visual research program directed at understanding the design principles required for the development of instruments displaying spatial orientation information. The experiments also highlight the need for modeling the impact of spatial displays on pilot control tasks.

Bennett, C. Thomas↗
DOE OSTI2024

Development and Evaluation of Ensemble Learning-based Environmental Methane Detection and Intensity Prediction Models

The environmental impacts of global warming driven by methane (CH 4 ) emissions have catalyzed significant research initiatives in developing novel technologies that enable proactive and rapid detection of CH 4 . Several data-driven machine learning (ML) models were tested to determine how well they identified fugitive CH 4 and its related intensity in the affected areas. Various meteorological characteristics, including wind speed, temperature, pressure, relative humidity, water vapor, and heat flux, were included in the simulation. We used the ensemble learning method to determine the best-performing weighted ensemble ML models built upon several weaker lower-layer ML models to (i) detect the presence of CH 4 as a classification problem and (ii) predict the intensity of CH 4 as a regression problem. The classification model performance for CH 4 detection was evaluated using accuracy, F1 score, Matthew’s Correlation Coefficient (MCC), and the area under the receiver operating characteristic curve (AUC ROC), with the top-performing model being 97.2%, 0.972, 0.945 and 0.995, respectively. The R 2 score was used to evaluate the regression model performance for CH 4 intensity prediction, with the R 2 score of the best-performing model being 0.858. The ML models developed in this study for fugitive CH 4 detection and intensity prediction can be used with fixed environmental sensors deployed on the ground or with sensors mounted on unmanned aerial vehicles (UAVs) for mobile detection.

Majumder, Reek↗
DOE OSTI2020

Regulatory Decision-Making Process Using 'Weight of Evidence: An Evidence Integration Approach' by the State of Washington at the Hanford Site - 20163

Performance Assessment and Environmental Impact Statement Modeling, Human and Ecological Risk Assessments are the tools used by the Washington State Department of Ecology (Ecology) to make regulatory decisions for permitting and cleanup. These efforts all inherently have large amounts of uncertainty no matter how many alternative approaches are attempted. Professional feedback from tribal governments, stakeholders, federal and state regulators, the public and independent peer review groups are taken into account in this process of informed decision making. The process also includes full evaluation of the comments and the associated reviews made by the various peer review groups such as the Low -Level Waste Disposal Facility Federal Review Group (DOE order 435.1) and the Nuclear Regulatory Commission (NRC). The evolution of technology has produced quicker and more efficient fate and transport modeling tools with related quantification of uncertainties and their significance. Groundwater and vadose zone models have been expanded across the entire Hanford site. Many of the technical approaches identified in the Washington State Regulations are updated using current knowledge to better understand the complexities of the Hanford Site using the latest state of the art tools for risk assessment and modeling. More emphasis and time are directed on defining uncertainty and then managing the uncertainty. One added tool is to run sensitivity cases based on informed decision making. The weight of evidence approach considers all relevant information in an integrative assessment that takes into account the kinds of evidence available, the quality and quantity, the uncertainty and error associated with each type, and how they fit together. Evidence of integration involves looking at systematic reviews and evaluating their strengths and weaknesses. In conclusion, Ecology, Washington State's lead regulatory agency at the Hanford site, has had to modify its site closure approach compared to the rest of the state. A more holistic approach dealing with the Hanford site as an integrated system has evolved leading to a defensible informed approach for regulatory closure decisions. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Ice‐Nucleating Particles That Impact Clouds and Climate: Observational and Modeling Research Needs

Abstract Atmospheric ice‐nucleating particles (INPs) play a critical role in cloud freezing processes, with important implications for precipitation formation and cloud radiative properties, and thus for weather and climate. Additionally, INP emissions respond to changes in the Earth System and climate, for example, desertification, agricultural practices, and fires, and therefore may introduce climate feedbacks that are still poorly understood. As knowledge of the nature and origins of INPs has advanced, regional and global weather, climate, and Earth system models have increasingly begun to link cloud ice processes to model‐simulated aerosol abundance and types. While these recent advances are exciting, coupling cloud processes to simulated aerosol also makes cloud physics simulations increasingly susceptible to uncertainties in simulation of INPs, which are still poorly constrained by observations. Advancing the predictability of INP abundance with reasonable spatiotemporal resolution will require an increased focus on research that bridges the measurement and modeling communities. This review summarizes the current state of knowledge and identifies critical knowledge gaps from both observational and modeling perspectives. In particular, we emphasize needs in two key areas: (a) observational closure between aerosol and INP quantities and (b) skillful simulation of INPs within existing weather and climate models. We discuss the state of knowledge on various INP particle types and briefly discuss the challenges faced in understanding the cloud impacts of INPs with present‐day models. Finally, we identify priority research directions for both observations and models to improve understanding of INPs and their interactions with the Earth System.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2010

Secondary Impacts on Structures on the Lunar Surface

The Altair Lunar Lander is being designed for the planned return to the Moon by 2020. Since it is hoped that lander components will be re-used by later missions, studies are underway to examine the exposure threat to the lander sitting on the Lunar surface for extended periods. These threats involve both direct strikes of meteoroids on the vehicle as well as strikes from Lunar regolith and rock thrown by nearby meteorite strikes. Currently, the lander design is comprised of up to 10 different types of pressure vessels. These vessels included the manned habitation module, fuel, cryogenic fuel and gas storage containers, and instrument bays. These pressure vessels have various wall designs, including various aluminum alloys, honeycomb, and carbon-fiber composite materials. For some of the vessels, shielding is being considered. This program involved the test and analysis of six pressure vessel designs, one of which included a Whipple bumper shield. In addition to the pressure vessel walls, all the pressure vessels are wrapped in multi-layer insulation (MLI). Two variants were tested without the MLI to better understand the role of the MLI in the impact performance. The tests of performed were to examine the secondary impacts on these structures as they rested on the Lunar surface. If a hypervelocity meteor were to strike the surface nearby, it would throw regolith and rock debris into the structure at a much lower velocity. Also, when the manned module departs for the return to Earth, its rocket engines throw up debris that can impact the remaining lander components and cause damage. Glass spheres were used as a stimulant for the regolith material. Impact tests were performed with a gas gun to find the V50 of various sized spheres striking the pressure vessels. The impacts were then modeled and a fast-running approximate model for the V50 data was developed. This model was for performing risk analysis to assist in the vessel design and in the identification of ideal long-term mission sites. This paper reviews the impact tests and analysis and modeling examining the impact threat to various components in the lander design.

Christiansen, Eric↗
DOE OSTI2022

Assimilation of a Coordinated Fleet of Uncrewed Aircraft System Observations in Complex Terrain: Observing System Experiments

Uncrewed aircraft system (UAS) observations from the Lower Atmospheric Profiling Studies at Elevation–A Remotely-Piloted Aircraft Team Experiment (LAPSE-RATE) field campaign were assimilated into a high-resolution configuration of the Weather Research and Forecasting (WRF) Model. The impact of assimilating targeted UAS observations in addition to surface observations was compared to that obtained when assimilating surface observations alone using observing system experiments (OSEs) for a terrain-driven flow case and a convection initiation (CI) case observed within Colorado’s San Luis Valley (SLV). The assimilation of UAS observations in addition to surface observations results in a clear increase in skill for both flow regimes over that obtained when assimilating surface observations alone. For the terrain-driven flow case, the UAS observations improved the representation of thermal stratification across the northern SLV, which produced stronger upvalley flow over the eastern half of the SLV that better matched the observations. For the CI case, the UAS observations improved the representation of the pre-convective environment by reducing dry biases across the SLV and over the surrounding terrain. This led to earlier CI and more organized convection over the foothills that spilled outflows into the SLV, ultimately helping to increase low-level convergence and CI there. In addition, the importance of UAS capturing an outflow that originated over the Sangre de Cristo Mountains and triggered CI is discussed. These outflows and subsequent CI were not well captured in the simulation that assimilated surface observations alone. We report that observations obtained with a fleet of UAS are shown to notably improve high-resolution analyses and short-term predictions of two very different mesogamma-scale weather events.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Land Surface Modeling 2.0 for agricultural climate change impact assessments

Focus Area: This white paper addresses DOE AI4ESP focus area #2 by providing a sketch blueprint for a next generation, hybrid AI/process-based global Land Surface Modeling (LSM) framework to improve projections of climate change impacts on the land surface system including agriculture and the hydrological cycle. Science Challenge: Climate change impacts on agriculture are highly uncertain: -50% to +150% global production changes for major grains under high-end climate change, for example. The core challenge in land surface system predictability is the large gap between the scale at which the relevant biological processes act and the scale at which the risks need to be assessed. Conventional empirical and process-based modeling approaches are insufficient. A new multi-scale modeling paradigm which employs AI/ML to learn from new streams of remote sensing data and targeted ’gene-to-global’ simulations is needed.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2004

The Seismic Effect of Impacts on Asteroid Surface Morphology: Early Modeling Results

In recent years, spacecraft observations of asteroids 951 Gaspra, 243 Ida, 253 Mathilde, and 433 Eros have shown the overriding dominance of impact processes with regard to the structure and appearance of these small, irregular bodies. One currently unanswered question is: to what degree does seismic shaking from impacts affect the surface morphology of these bodies? Through detailed modeling, we begin to address this question.

Richardson, J. E.↗
DOE OSTI2021

Atomic understanding of structural deformations upon ablation of graphene

We investigate the atomic rearrangement in graphene under femtosecond pulse illumination with reactive molecular dynamics simulations and compare with ultra-fast laser ablation experiments. To model the impact of the laser pulse irradiation, heat is locally applied to a selected area of the graphene layer and the resulting structural deformation is simulated as a function of time, providing a detailed understanding of the bond breaking process under laser illumination and subsequent re-equilibration afterAQ3 the pulse is turned off. Analysis of the atomic dynamics indicates that the types of defects formed depend on the pulse energy and exposure duration. By varying the exposed area, we determine that the shape of the ablated area is not only a function of the pulse energy, but also of the beam spot size and pulse repetition. Furthermore, we apply a machine learning approach to extrapolate our simulated data to experimental length scales and reproduce the trends in ablated area as a function of temperature. Furthermore, our study provides a first step towards understanding the design parameters for graphene nano-patterning.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Comparative studies of 2HDMs under the Higgs boson precision measurements

We perform comparative studies for four types of the two Higgs Doublet Models (2HDMs) under the precision measurements of the Standard Model (SM) Higgs observables at the proposed Higgs factories. We explore the discovery potential based on the hypothetical deviations in the precision data for the 2HDMs up to one-loop level. We find 5σ observability from the χ2 fitting in a significant theory parameter space at future Higgs factories. For the Type-I 2HDM, regions with cos(β - α) ≲ -0.1 or cos(β - α) ≳ 0.08 are discoverable at more than 5σ level. For the other three types of 2HDMs, the 5σ region is even bigger: | cos(β - α)| ≳ 0.02 for tan β ~ 1. At small and large values of tan β, the region in cos(β - α) is further tightened. We examine the extent to which the different 2HDM theories may be distinguishable from one to the other at the 95% Confidence Level with four benchmark points as case studies. We show that a large part of the parameter space of the other types of 2HDMs can be distinguished from the benchmark points of the target model. The impacts of loop corrections are found to be significant in certain parameter regions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Toward engineering lattice structures with the material point method (MPM)

This study examines the potential of two variants of the material point method—the generalized interpolation material point (GIMP) and dual domain material point (DDMP) methods—in developing a robust computational framework for engineering lattice structures under different loading conditions. The study begins with assessing the ability of the two methods in predicting elastic buckling phenomena using column geometries with and without initial geometric imperfections. The results indicate that both methods effectively capture buckling phenomena when initial geometric imperfections are introduced. After this verification step, we create several models of tetrahedral lattice structures with varying strut diameter and orientation and subject them to quasi-static loading. We then validate the numerical results using laboratory test results. The results show that, while both methods accurately predict load–displacement curves in the pre-buckling regime, their predictive capabilities diminish in the post-buckling regime. Through visual comparison between the numerical and experimental deformed shapes, it appears that the discrepancies between model and experimental results are attributed to initial geometric imperfections in the lattices that occurred during 3D printing. We then establish a second set of lattice models where different types of initial geometric imperfections are considered. The results from these models show that imperfections have a negligible influence in the pre-buckling regime but affect the behavior considerably in the post-buckling regime. As a final step in this work, we subject the lattice models to impact loading and employ hypothetical soft and stiff materials. These results show that the lattice stiffness, which depends on material stiffness, strut diameter, and orientation, significantly influences the ability of a lattice structure to resist impact. In particular, we find that a stiffer lattice (i.e., one made with a stiff material and thicker struts) is capable of absorbing more energy than a softer one during impact. Although material nonlinearities, inelasticity, and detailed contact formulations are not considered in this study, the findings obtained herein lay the groundwork for engineering lattice structures under extreme loading conditions through a simulation-driven framework based on particle-based methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Uncertainties in estimating global potential yields and their impacts for long-term modeling

Estimating realistic potential yields by crop type and region is challenging; such yields depend on both biophysical characteristics (e.g., soil characteristics, climate, etc.), and the crop management practices available in any site or region (e.g., mechanization, irrigation, crop cultivars). A broad body of literature has assessed potential yields for selected crops and regions, using several strategies. In this study we first analyze future potential yields of major crop types globally by two different estimation methods, one of which is based on historical observed yields (“Empirical”), while the other is based on biophysical conditions (“Simulated”). Potential yields by major crop and region are quite different between the two methods; in particular, Simulated potential yields are typically 200% higher than Empirical potential yields in tropical regions for major crops. Applying both of these potential yields in yield gap closure scenarios in a global agro-economic model, GCAM, the two estimates of future potential yields lead to very different outcomes for the agricultural sector globally. In the Simulated potential yield closure scenario, Africa, Asia, and South America see comparatively favorable outcomes for agricultural sustainability over time: low land use change emissions, low crop prices, and high levels of self-sufficiency. In contrast, the Empirical potential yield scenario is characterized by a heavy reliance on production and exports in temperate regions that currently practice industrial agriculture. At the global level, this scenario has comparatively high crop commodity prices, and more land allocated to crop production (and associated land use change emissions) than either the baseline or Simulated potential yield scenarios. This study highlights the importance of the choice of methods of estimating potential yields for agro-economic modeling.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Physical model and experimental validation of a high temperature proton exchange membrane electrochemical hydrogen pump cell for efficient single-stage extraction of low concentration hydrogen gas

There is interest in valorization of existing natural gas infrastructure to facilitate the co-transportation of hydrogen via blending of hydrogen gas initially at limited concentrations of 1–20 vol% H2 and to subsequently extract hydrogen at fuel cell quality standards (SAE J2719/ISO14687-2). High temperature proton exchange membrane electrochemical hydrogen pump (HT-PEM EHP) based on phosphoric acid doped polybenzimidazole (PA-PBI) exhibits good performance at elevated temperatures (>120 °C), which provides desirable tolerance to non-methane natural gas constituents that are problematic for lower temperature based EHP. To better understand the suitability of the HT-PEM EHP for such gas separation processes, a two-dimensional model of EHP based on PA-PBI was developed. The model is validated for several relevant operating conditions and across cells with differing amounts of phosphoric acid content in the electrodes. Operando micro x-ray computed tomography (CT) imaging of an HT-PEM EHP was used to further validate physical parameters and assumptions of the model. The impacts of pressure, relative humidity of the anode feed, and concentration of feed gases on separation performance are investigated. This study shows that a specific energy of separation of 5.1 kWh/kg H2 at a hydrogen recovery factor (HRF) of 50 vol% can be achieved in a single stage with the EHP, producing fuel cell quality hydrogen purity of 99.99 vol% H2 from a 2 vol% H2/CH4 feed blend, while pressurizing the product H2 at a pressure ratio of 1.3 relative to feed pressure.

Stansberry, John M↗
DOE OSTI2025

Dehumidification energy storage using a stratified liquid desiccant tank

Liquid desiccants can play an important role in reducing dehumidification energy requirements in the built environment. Because they are in a liquid state, the desiccant can be easily stored and then used to dehumidify buildings during peak energy consumption periods. By maintaining stratification between concentrated and diluted desiccant solutions, a single tank can be used to store liquid desiccant for energy storage purposes. Using a stratified tank instead of separate tanks for dilute and concentrated solutions will reduce storage costs and increase energy storage densities for liquid desiccant systems. This paper describes the experimental validation and one-dimensional modeling of a stratified liquid desiccant tank. The stratified tank prototype developed achieved 80 % of the theoretical energy storage density based on an imposed desiccant concentration change. Here, the stratified tank model was able to reasonably reproduce the experimental results. Using this model, the impact of varying operational conditions on the energy density of the stratified liquid desiccant energy storage was evaluated. Depending on the operating conditions, stratified liquid desiccant energy storage using aqueous LiCl up to 40 wt% can achieve energy storage densities in excess of 330 kWh/m 3 .

25 ENERGY STORAGE↗
DOE OSTI2025

Assessing the fidelity of shallow-water carbonates as records of the Ni isotope composition of surface seawater

Nickel is a bioessential metal that is used in enzymes important to the C, N, and O cycles, and changes in its marine abundance and bioavailability may have affected the evolutionary trajectory of early life. Changes over time in the Ni isotope composition (δ 60 Ni) of surface seawater, which reflects biological demand for Ni, could allow for the reconstruction of the dynamics of Ni demand over Earth’s history, but this approach would require geologic records of surface seawater. Here, we investigate the fidelity of shallow-water carbonates as a record of the Ni isotope composition of surface seawater by determining how Ni is first partitioned into natural carbonates and then how post-depositional processes influence the Ni signal. Our samples come from the Great Bahama Bank, which is a well-studied, modern carbonate platform often used to study ancient platforms. We found that Ni is fractionated from seawater upon incorporation into carbonates capturing shallow (<18 cm), recent deposition (0.1 ‰–0.4 ‰ lighter than seawater). Variation among these [Ni] and δ 60 Ni values may be controlled by variation in mineral proportions. Meteoric diagenesis shifts δ 60 Ni to lower values, which we attribute to isotopically light meteoric fluids. In contrast, carbonates that experienced sediment-buffered marine diagenesis with respect to Ca isotopes and Sr/Ca ratios do not appear to differ in δ 60 Ni values from sediments generally representative of their initial deposition. The sensitivity of δ 60 Ni to diagenetic reset in these samples appears comparable to the sensitivities of Ca isotopes and Sr/Ca ratios, to first order. Thus, in general, carbonates that experienced sediment-buffered marine diagenesis with respect to these elements may hold the most promise as a record of the δ 60 Ni of coeval surface seawater. Additionally, we use our results to infer that the fraction of Ni removed from seawater into carbonates is less than 10 % of the total Ni output from the global oceans and incorporation of this Ni sink into global biogeochemical models will only have a minor impact on the modeled modern Ni budget.

Great Bahama Bank carbonates↗
DOE OSTI2023

Dynamical responses of constrained pipe conveying fluids and its dependence on the modeling of the contact force

Accurately modeling the impact force used in the analysis of loosely constrained cantilevered pipes conveying fluid is imperative. If little information is known of the motion-limiting constraints used in experiments, the analysis of the system may yield inaccurate predictions. Here in this work, multiple forcing representations of the impact force are defined and analyzed for a cantilevered pipe that conveys fluid. Depending on the representation of the impact force, the dynamics of the pipe can vary greatly when only the stiffness of the constraints is known from experiments. Three gap sizes of the constraints are analyzed, and the representation of the impact force used to analyze the system is found to significantly affect the response of the pipe at each gap size. An investigation on the effects of the vibro-impact force representation is performed through using basin of attraction analysis and nonlinear characterization of the system’s response.

42 ENGINEERING↗
DOE OSTI2024

Epitopes recognition of SARS-CoV-2 nucleocapsid RNA binding domain by human monoclonal antibodies

Coronavirus nucleocapsid protein (NP) of SARS-CoV-2 plays a central role in many functions important for virus proliferation including packaging and protecting genomic RNA. The protein shares sequence, structure, and architecture with nucleocapsid proteins from betacoronaviruses. The N-terminal domain (NP RBD ) binds RNA and the C-terminal domain is responsible for dimerization. After infection, NP is highly expressed and triggers robust host immune response. The anti-NP antibodies are not protective and not neutralizing but can effectively detect viral proliferation soon after infection. Two structures of SARS-CoV-2 NP RBD were determined providing a continuous model from residue 48 to 173, including RNA binding region and key epitopes. Five structures of NP RBD complexes with human mAbs were isolated using an antigen-bait sorting. Complexes revealed a distinct complement-determining regions and unique sets of epitope recognition. This may assist in the early detection of pathogens and designing peptide-based vaccines. Mutations that significantly increase viral load were mapped on developed, full length NP model, likely impacting interactions with host proteins and viral RNA.

59 BASIC BIOLOGICAL SCIENCES↗