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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

The ν -process with Fully Time-dependent Supernova Neutrino Emission Spectra

The neutrino process that occurs in the outer stellar shells during a supernova explosion and involves neutrino–nucleus reactions produces a range of rare, stable, and radioactive isotopes. We improve previous ν-process studies by using, for the first time, the time-dependent neutrino emission spectra, as predicted from supernova simulations, rather than a simplified parametric description modeled after the neutron star cooling phase. In particular, our calculations use time-dependent neutrino spectra for all neutrino species, consider their deviation from a Fermi–Dirac distribution, and account for the neutrino emission from the neutrino burst and accretion phases. We find that the time-dependent treatment of the neutrino emission spectra results in higher yields for the selected nuclei produced by the ν process as compared to previous studies and to the approximation of assuming constant neutrino energies corresponding to the time-averaged mean energy radiated in each species. The effect is largest for nuclides produced by charged-current reactions. Our results reflect the dynamical competition between neutrino-induced reactions and the effect of the shock passage through the star. By varying the neutrino burst luminosity and the duration of the accretion phase, we study the impact of these early emission phases and their uncertainties on the ν-process nucleosynthesis. We find that the deviation of the neutrino spectra from a Fermi–Dirac distribution calculated in supernova simulations has a negligible effect on the ν-process yields.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1983

Space station needs, attributes and architectural options study. Briefing material: Final review and executive summary

Advantages and disadvantages were assessed for configuration options for a modular 14' diameter space station, a modular aft cargo carrier and a shuttle derived vehicle. Early, intermediate, and mature configurations were defined as well as power requirements, heat rejection, hydrazine usage, and the external scavenging concept. Subsystems were analyzed for propulsion, attitude control, data processing, and communications. Areas of uncertainties, associated costs and benefits, and the cost by phase of the modular and shuttle derived vehicle configurations were identified. Technologies assessed included solar vs nuclear; gravity gradient vs active control; heat pipe radiators vs fluid loops; distributed processors vs centralized, and modular vs shuttle derived configuration. It was determined that the early space station architecture should include: (1) reusable OTV with aerobraking; (2) TMS with telepresence services; (3) OTV/TMS refueling and servicing capability; and (4) attached research laboratories for life sciences and materials processing.

Source record↗
DOE OSTI2021

Determination of the 60 Zn level density from neutron evaporation spectra

Nuclear reactions of interest for astrophysics and applications often rely on statistical model calculations for nuclear reaction rates, particularly for nuclei far from β stability. However, statistical model parameters are often poorly constrained, where experimental constraints are particularly sparse for exotic nuclides. For example, our understanding of the breakout from the NiCu cycle in the astrophysical rp-process is currently limited by uncertainties in the statistical properties of the proton-rich nucleus 60 Zn. We have determined the nuclear level density of 60 Zn using neutron evaporation spectra from 58 Ni( 3 He,n) measured at the Edwards Accelerator Laboratory. We compare our results to a number of theoretical predictions, including phenomenological, microscopic, and shell-model-based approaches. Notably, we find the 60 Zn level density is somewhat lower than expected for excitation energies populated in the 59 Cu(p,γ) 60 Zn reaction under rp-process conditions. This includes a level density plateau from roughly 5 to 6 MeV excitation energy, which is counter to the usual expectation of exponential growth and all theoretical predictions that we explore. Here, a determination of the spin distribution at the relevant excitation energies in 60 Zn is needed to confirm that the Hauser-Feshbach formalism is appropriate for the 59 Cu(p,γ) 60 Zn reaction rate at x-ray burst temperatures

59 ≤ A ≤ 89↗
NASA NTRS2011

The Role of Uncertainty in Aerospace Vehicle Analysis and Design

Effective uncertainty quantification (UQ) begins at the earliest phase in the design phase for which there are adequate models and continues tightly integrated to the analysis and design cycles as the refinement of the models and the fidelity of the tools increase. It is essential that uncertainty quantification strategies provide objective information to support the processes of identifying, analyzing and accommodating for the effects of uncertainty. Assessments of uncertainty should never render the results more difficult for engineers and decision makers to comprehend, but instead provide them with critical information to assist with resource utilization decisions and risk mitigation strategies. Success would be measured by the tools to enable engineers and decision makers to effectively balance critical project resources against system requirements while accounting for the impact of uncertainty.

Kenny, Sean P.↗
NASA NTRS2020

OMI Measurements of Bromine Monoxide and Implications for Missing Sources of Polar Bromine in GEOS-Chem

The OMI satellite instrument provides total column measurements of bromine monoxide (BrO) with daily global coverage. Reactive bromine compounds (Br and BrO) catalytically destroy ozone in both the stratosphere and troposphere. The current emission scheme of brominated source gases in the GEOS-Chem chemical transport model well represents the stratospheric burden of bromine. However, halogen research in GEOS-Chem has largely focused on the influence of halogens on the tropospheric oxidative capacity. In the troposphere, the distribution of brominated compounds is more variable and significant uncertainties remain in the chemical processes governing the sources and sinks of reactive bromine compounds. In this study, we use GEOS-Chem simulated stratospheric columns of BrO to separate the tropospheric signal of BrO from the OMI total column measurements. The resulting tropospheric BrO columns are used to identify seasonal and regional anomalies in tropospheric BrO not currently represented in GEOS-Chem. In particular, periods of elevated tropospheric BrO during polar spring are observable by OMI, and past studies have connected these so-called "bromine explosion" events to near complete removal of surface ozone. Due to significant uncertainties in the springtime polar source of reactive bromine, many global models, including GEOS-Chem, do not simulate these tropospheric ozone depletion events. Consequently, OMI-based tropospheric columns of BrO are useful tool for investigating the impact of bromine explosion events on tropospheric ozone depletion episodes as well as background air quality.

Wales, Pamela↗
DOE OSTI2021

Simulation of hardened cement degradation and estimation of uncertainty in predicted failure times with peridynamics

Modeling the degradation of cement-based infrastructure due to aqueous environmental conditions continues to be a challenge. In order to develop a capability to predict concrete infrastructure failure due to chemical degradation, here we created a chemomechanical model of the effects of long-term water exposure on cement paste. The model couples the mechanical static equilibrium balance with reactive–diffusive transport and incorporates fracture and failure via peridynamics (a meshless simulation method). The model includes fundamental aspects of degradation of ordinary Portland cement (OPC) paste, including the observed softening, reduced toughness, and shrinkage of the cement paste, and increased reactivity and transport with water induced degradation. This version of the model focuses on the first stage of cement paste decalcification, the dissolution of portlandite. Given unknowns in the cement paste degradation process and the cost of uncertainty quantification (UQ), we adopt a minimally complex model in two dimensions (2D) in order to perform sensitivity analysis and UQ. We calibrate the model to existing experimental data using simulations of common tests such as flexure, compression and diffusion. Then we calculate the global sensitivity and uncertainty of predicted failure times based on variation of eleven unique and fundamental material properties. We observed particularly strong sensitivities to the diffusion coefficient, the reaction rate, and the shrinkage with degradation. Also, the predicted time of first fracture is highly correlated with the time to total failure in compression, which implies fracture can indicate impending degradation induced failure; however, the distributions of the two events overlap so the lead time may be minimal. Extension of the model to include the multiple reactions that describe complete degradation, viscous relaxation, post-peak load mechanisms, and to three dimensions to explore the interactions of complex fracture patterns evoked by more realistic geometry is straightforward and ongoing.

36 MATERIALS SCIENCE↗
NASA NTRS2022

Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations

Flight testing has been the historical standard for determining aircraft airworthiness - however, increases in the cost of flight testing and the accuracy of inexpensive CFD promote certification by analysis to reduce or replace flight testing. A framework is introduced to predict the performance in the special case of a modification to an existing, previously certified aircraft. This framework uses a combination of existing flight test or high fidelity data of the original aircraft as well as lower fidelity data of the original and modified configurations. Two methods are presented which estimate the model form uncertainty of the modified configuration, which is then used to conduct non-deterministic simulations. The framework is applied to an example aircraft system with simulated flight test data to demonstrate the ability to predict the performance and associated uncertainty of modified aircraft configurations. However, it is important that the models and methods used are applicable and accurate throughout the intended use domain. The factors and limitations of the framework are explored to determine the range of applicability of the framework. The effects of these factors on the performance and uncertainty results are demonstrated using the example aircraft system. The framework is then applied to NASA’s X-57 Maxwell and each of its modifications. The estimated performance and associated uncertainties are then compared to the airworthiness criteria to evaluate the potential of the framework as a component to the certification by analysis process.

Uncertainty Quantification↗
DOE OSTI2021

Phase Separation in Ultramassive White Dwarfs

We report ultramassive white dwarfs are extreme endpoints of stellar evolution. Recent findings, such as a missing multi-Gyr cooling delay for a number of ultramassive white dwarfs and a white dwarf with a quasi-Chandrasekhar mass, motivate a better understanding of their evolution. A key process still subject to important uncertainties is the crystallization of their dense cores, which are generally assumed to be constituted of 16 O, 20 Ne, and a mixture of several trace elements (most notably 23 Na and 24 Mg). In this work, we use our recently developed Clapeyron integration technique to compute accurate phase diagrams of three-component mixtures relevant to the modeling of O/Ne ultramassive white dwarfs. We show that, unlike the phase separation of 22 Ne impurities in C/O cores, the phase separation of 23 Na impurities in O/Ne white dwarfs cannot lead to the enrichment of their cores in 23 Na via a distillation process. This severely limits the prospect of transporting large quantities of 23 Na toward the center of the star, as needed in the white dwarf core-collapse mechanism recently proposed by Caiazzo et al. We also show that despite representing ≈10% of the ionic mixture, 23 Na and 24 Mg impurities only have a negligible impact on the O/Ne phase diagram, and the two-component O/Ne phase diagram can be safely used in white dwarf evolution codes. We provide analytic fits to our high-accuracy O/Ne phase diagram for implementation in white dwarf models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Modular hybrid modeling to increase efficiency, explore structural uncertainty, and allow multidimensional complexity scaling in land surface models

Land surface models (LSMs) are indispensable tools for predicting hydrologic extremes, as well as a particularly uncertain component of Earth system models that has stubbornly resisted the convergence in projections over several successive generations of model intercomparisons. This uncertainty in LSMs is poorly quantified and poorly attributed to specific processes, which has hampered efforts to focus research in reducing uncertainty. This has resulted from sparse sampling of the possible uncertainty space—which is high-dimensional and has contributions from parametric, structural, initial, and boundary condition uncertainties—as an artifact of CMIP-type ensembles of opportunity and limitations inherent in observational benchmarks. A new approach is needed to understand and reduce this uncertainty, based around individual LSMs that can represent the breadth of assumptions represented in current CMIP-type efforts, while at the same time exploring that uncertainty in a systematic way, confronting multiple types of observations, and where justified, replacing process representations with ML-driven emulators. We propose an approach of modular hybrid modeling to address these challenges.

58 GEOSCIENCES↗
NASA NTRS2010

Lidar Measurements of Methane and Applications for Aircraft and Spacecraft

Atmospheric methane levels have remained relatively constant over the last decade around 1.78 parts per million (ppm) but observations since 2007 show that levels may be increasing. This trend may be caused by increased fossil fuel production, rice farming, livestock and landfills, but the underlying causes are quite uncertain. One hypothesis is that reservoirs of carbon trapped in the permafrost regions of northern Canada, Europe, and Siberia thaw as global temperatures rise and are releasing increasing amounts of methane. Another hypothesis points to increased production of methane by microbes as the permafrost warms. Currently most observations of greenhouse gases are limited to in-situ (surface and tower sites) and limited airborne in-situ measurements. Space column density measurements are starting to become available from the GOSAT mission. Although methane survives for a shorter time in the atmosphere than CO2, its impact on climate change per molecule is about 23 times than that of CO2. Accurate global observations of several greenhouse gases, including methane, are urgently needed in order to better understand climate change processes and to reduce the uncertainty in the carbon budget. Differential absorption lidar is a well-established technique to measure atmospheric gases, and methane has optical absorption bands near 1.65,2.2,3.4 and 7.8 micron. The near infrared overtones lines of CH4 near 1650 nm are relatively free of interference from other species. There are absorption lines near 1651 nm which are both temperature insensitive and have line strengths well suited for lidar measurements. We have developed a laser and demonstrated lidar measurements of CH4 using lines in this band. Our laser uses a narrow linewidth 1064 nm laser pulse passing through a nonlinear crystal. We generate the tunable laser signals near 1651 nm by using the optical parametric amplification (OPA) process. Inside the crystal the 1064 nm beam overlaps with an injection seed laser near 1651 nm from a wavelength tunable diode laser. Incident photons from the pump laser pulse are converted into two photons, with one at the wavelength of the injection seeder. The wavelength of the OPA output is tuned via the wavelength of diode laser. Our laser is tunable, operates near 1651 nm and generates approximately 4 uJ/pulse at 6 KHz. We vary the emission wavelengths within this band by tuning the diode laser's wavelength. We have used this OPA transmitter to make measurements of CH4 at various pressures in a gas cell and over open outdoor horizontal paths. We have measured the lineshape of methane in a 6 cm long cell at various energy levels with this transmitter, with excellent agreement with the lineshape calculated by HITRAN. We have also measured the absorption lineshape of atmospheric methane in an open 3 km outdoor path. The agreement between the measurements and HITRAN, for 1746 ppb and 760 Torr was quite good. We have also made pulsed two wavelength lidar measurements of methane line absorption in the column to a tower at 1.5 km range. These used on- and off-line wavelengths of 1650.957 nm, and 1651.072 nm, and a 20 cm diameter receiver telescope with an infrared PMT detector. The absorption of the on-line photons was 30%. The methane column absorption was estimated via HITRAN, and was in good agreement with the expected methane absorption for a concentration of 1750 ppm. Finally we have calculated the measurement performance of an airborne methane lidar using this transmitter, as well as the energy and telescope scaling needed for a lidar for space. These results, and more details of our experiments will be described in the presentation.

Riris, Haris↗
DOE OSTI2022

The uncertain role of rising atmospheric CO 2 on global plant transpiration

As CO 2 concentration in the atmosphere rises, there is a need for improved physical understanding of its impact on global plant transpiration. This knowledge gap poses a major hurdle in robustly projecting changes in the global hydrologic cycle. For this reason, here we review the different processes by which atmospheric CO 2 concentration affects plant transpiration, the several uncertainties related to the complex physiological and radiative processes involved, and the knowledge gaps which need to be filled in order to improve predictions of plant transpiration. Additionally, although there is a high degree of certainty that rising CO 2 will impact plant transpiration, the exact nature of this impact remains unclear due to complex interactions between CO 2 and climate, and key aspects of plant morphology and physiology. The interplay between these factors has substantial consequences not only for future climate and global vegetation, but also for water availability needed for sustaining the productivity of terrestrial ecosystems. Future changes in global plant transpiration in response to enhanced CO 2 are expected to be driven by water availability, atmospheric evaporative demand, plant physiological processes, emergent plant disturbances related to increasing temperatures, and the modification of plant physiology and coverage. Considering the universal sensitivity of natural and agricultural systems to terrestrial water availability we argue that reliable future projections of transpiration is an issue of the highest priority, which can only be achieved by integrating monitoring and modeling efforts to improve the representation of CO 2 effects on plant transpiration in the next generation of earth system models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Effective Uncertainty Quantification for Multi-Angle Polarimetric Aerosol Remote Sensing Over Ocean

Multi-angle polarimetric (MAP) measurements can enable detailed characterization of aerosol microphysical and optical properties and improve atmospheric correction in ocean color remote sensing. Advanced retrieval algorithms have been developed to obtain multiple geophysical parameters in the atmosphere–ocean system. Theoretical pixel-wise retrieval uncertainties based on error propagation have been used to quantify retrieval performance and determine the quality of data products. However, standard error propagation techniques in high-dimensional retrievals may not always represent true retrieval errors well due to issues such as local minima and the nonlinear dependence of the forward model on the retrieved parameters near the solution. In this work, we analyze these theoretical uncertainty estimates and validate them using a flexible Monte Carlo approach. The Fast Multi-Angular Polarimetric Ocean coLor (FastMAPOL) retrieval algorithm, based on efficient neural network forward models, is used to conduct the retrievals and uncertainty quantification on both synthetic HARP2 (Hyper-Angular Rainbow Polarimeter 2) and AirHARP (airborne version of HARP2) datasets. In addition, for practical application of the uncertainty evaluation technique in operational data processing, we use the automatic differentiation method to calculate derivatives analytically based on the neural network models. Both the speed and accuracy associated with uncertainty quantification for MAP retrievals are addressed in this study. Pixel-wise retrieval uncertainties are further evaluated for the real AirHARP field campaign data. The uncertainty quantification methods and results can be used to evaluate the quality of data products, as well as guide MAP algorithm development for current and future satellite systems such as NASA’s Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission.

PACE↗
DOE OSTI2026

Improving unfolding and systematic uncertainty estimation using generative diffusion networks (Final Technical Report)

This final technical report summarizes the key accomplishments on the unfolding using diffusion model project, a DOE award received by PI Pierre-Hugues Beauchemin at Tufts University. This project main goal was to investigate the potential of diffusion models for unfolding experimental High Energy Physics data from detector effects while controlling systematics uncertainties. The project accomplished its goals by completing the following objectives: 1) Performing an object-by-object, event-by-event unfolding of various kinematic distributions reconstructed from detector data in HEP in a way that keeps correlations between unfolded observables while demonstrating competitive performance compared to standard algorithms used in the field; 2) Address the generalization problem by developing an unfolding algorithm capable to correctly infer the underlying distributions of observables and processes never seen before, while controlling the dominant theoretical uncertainties affecting the process, therefore increasing the effectiveness, the precision, and the applicability of the developed algorithm; 3) Understand the theoretical foundations between the developed algorithm so to extend it to applications beyond experimental HEP, for broader benefits to the society. This report provides an overview of the accomplishments related to each of these key objectives.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production

Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects.

17 WIND ENERGY↗
DOE OSTI2021

A functional modeling approach for quality assurance in metal additive manufacturing

Purpose: Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. Here, a systematically integrated holistic view is proposed to achieve QA for AM. Design/methodology/approach: A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling. Findings: The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility. Research limitations/implications: A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study. Social implications: This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system. Originality/value: This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Role of Secondary Ice Processes in Midlatitude Continental Clouds

Clouds contribute very large uncertainties to our understanding of Earth's climate system. This is partly attributed to the insufficient predictive abilities of ice formation processes in clouds and the ramifications for the hydrological cycle and climate. To improve predictions of ice particle concentrations in clouds, a better understanding of the relative contributions of ice nucleating particles and secondary ice processes (SIPs) is needed. To address this challenging question, we combine ice nucleation measurements via immersion freezing of particles filtered from rainwater, with satellite-retrieved cloud top glaciation temperatures of the same clouds, while considering the chemical composition of the rainwater, the particles, and the particles' mass loads. In addition, laboratory-derived ice nucleation parameterization of K-feldspar was implemented in an ice nucleation model in order to reconstruct cloud glaciation temperatures considering primary ice nucleation only. Our laboratory and modeling results suggest that SIPs play a major role in glaciating the investigated clouds system. Furthermore, we show that SIP is controlled by cloud droplet sizes. In summary, our results suggest that the effect of SIP on cloud glaciation temperatures and therefore on Earth's radiation budget, may be significant.

54 ENVIRONMENTAL SCIENCES↗