Search NASA⌕ Search

SEARCH · Search NASA

Results for “water temperature”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The effect of cerium, neodymium, and ytterbium doping on UO 2 dissolution

Here, the dissolution rate of spent nuclear fuel has been studied heavily to understand the impacts of a failed waste package scenario on potential radionuclide release from a geologic repository. Multiple countries have evaluated these scenarios in oxidizing and reducing environments respective to their relevant repository conditions. The repository environment (e.g., water chemistry, temperature, oxygen content) and the fuel itself (e.g., chemical content of the fuel) both heavily impact the dissolution rate of the spent fuel. This work examined the impact that rare earth element dopants (Ce, Nd, Yb) have on the fuel dissolution under repository relevant conditions with decreasing oxidizing conditions using a single pass flowthrough system. UO 2 samples were doped with Ce, Nd, or Yb with concentrations between 1 and 5 at%. The addition of dopants to the samples reduced the dissolution rates on most samples relative to pure UO 2 samples. Scoping experiments that occurred in a less oxidizing environment showed a reduction in dissolution rate compared to fully oxidizing conditions. The results within highlight the importance of dopant behavior in used fuel dissolution modeling.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Cluster mediated conversion of amorphous Al(OH) 3 to γ-AlOOH

In this work, we report a synthetic pathway by which amorphous Al(OH) 3 is converted to γ-AlOOH through hydrothermal reaction in the presence of water at temperature T = 473 K. X-ray pair distribution function measurements reveal that the initially amorphous Al(OH) 3 possesses a locally γ-Al(OH) 3 -like structure, while nanocrystalline γ-AlOOH precipitates within 1 h of continuous hydrothermal exposure. Solid state nuclear magnetic resonance measurements show that resonant features associated with four- and five-member Al clusters persist through 20 min of hydrothermal treatment, and ultraviolet (UV) spectra mark the onset of UV-induced photoluminescent features characteristic to γ-AlOOH with 10 min of exposure, indicating a coexistence region of γ-Al(OH) 3 -like and γ-AlOOH-like amorphous species. Furthermore, powder x-ray diffraction measurements of desiccated powders reveal that the conversion process takes place in distinct, power law-defined stages with initial γ-AlOOH nucleation occurring within the first 20 min, followed by a ~ 1 h period of rapid grain coarsening and the subsequent onset of Lifshitz-Slyozov-Wagner-like coalescence.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Modeling aqueous association constants and mineral solubilities at subcritical and supercritical temperatures

The need for sustainable power generation has increased interest in the use of hydrothermal fluids for industrial applications. New high-enthalpy geothermal systems and biowaste-to-fuel processes are two relevant examples that employ supercritical fluids which require an in-depth understanding of complex chemical reactions occurring near the supercritical temperature of water (374 °C). As these processes operate in thermodynamic regimes that are not currently covered by a standard molar Gibbs energy of formation model, only empirical fits for single reaction systems are available which limit the use of multi-component phase equilibria calculations that are standard practice for less extreme environments. Here, in this paper, we advance a standard molar Gibbs energy of formation model able to operate in these otherwise inaccessible thermodynamic states to include species needed for key mineral solubility systems and ion association reactions. This work extends a model based on molecular statistical thermodynamics (MST) into four new systems (Na 3 PO 4 -H 2 O, LiOH-H 2 O, KOH-H 2 O, and BaSO 4 -H 2 O) by extending the model to cover 10 new species. For each of these systems, model predictions were consistently within the experimental uncertainties for the new systems covered. A breakdown of MST contributions to the model revealed that electrostatic and hard sphere contributions were key to reproducing density dependencies of standard molar Gibbs energy of formation values around the critical point of water.

42 ENGINEERING↗
DOE OSTI2021

Thin Water Films Enable Low-Temperature Magnesite Growth Under Conditions Relevant to Geologic Carbon Sequestration

Injecting supercritical CO2 (scCO2) into basalt formations for long-term storage is a promising strategy for mitigating CO2 emissions. Mineral carbonation can result in permanent entrapment of CO2; however, carbonation kinetics in thin H2O films in humidified scCO2 is not well understood. We investigated forsterite (Mg2SiO4) carbonation to magnesite (MgCO3) via amorphous magnesium carbonate (AMC; MgCO3·xH2O, 0.5 < x < 1), with the goal to establish the fundamental controls on magnesite growth rates at low H2O activity and temperature. Experiments were conducted at 25, 40, and 50 °C in 90 bar CO2 with a H2O film thickness on forsterite that averaged 1.78 ± 0.05 monolayers. In situ infrared spectroscopy was used to monitor forsterite dissolution and the growth of AMC, magnesite, and amorphous SiO2 as a function of time. Geochemical kinetic modeling showed that magnesite was supersaturated by two to three orders of magnitude and grew according to a zero-order rate law. The results indicate that the main drivers for magnesite growth are sustained high supersaturation coupled with low H2O activity, a combination of thermodynamic conditions not attainable in bulk aqueous solution. This improved understanding of reaction kinetics can inform subsurface reactive transport models for better predictions of CO2 fate and transport.

Kerisit, Sebastien N.↗
DOE OSTI2026

A Quantum Mechanical Study of Quartz (101) Interfacial Boundaries

Density functional theory (DFT) calculations were performed on periodic and molecular models to explore the energetics of bonding modes at quartz–quartz interfaces, common grain contacts in sandstones. Four interface types were modeled: H 2 O-mediated, silanol H-bond mediated, O–O peroxide bonds, and siloxane bonds. Each type of interface may exist in the subsurface of the Earth, depending upon water activity, temperature, and pressure, as interfacial structures are stable within DFT molecular dynamics simulations up to 473 K. The results predict interfacial energies SiOSi > SiOOSi > SiOH-6H 2 O > 2SiOH, as expected based on similar bond strengths in other systems. The proposed SiOOSi interface is not generally accounted for in chemomechanical models but could be important in sandstones at depth in the Earth. The implications for intergrain fracturing and H2 generation are discussed.

Hydrogen↗
DOE OSTI2021

Notable Contributions of Aerosols to the Predictability of Hail Precipitation

There is an increasing concern of the uncertainty produced by aerosols in forecasting precipitation including hail precipitation. This study provides an assessment of the uncertainties in hail and total precipitation by varying initial cloud condensation nuclei (CCN) number concentration (CCNC) and meteorological conditions based on 1200 cloud-resolving simulations of an idealized hailstorm. Although the meteorological perturbations produce large uncertainties in hail precipitation (including rate and maximum hail size) as well as total precipitation, varying CCNC by an order of magnitude can cause even larger uncertainties, especially pairing with the thermodynamics perturbation (i.e., potential temperature and water vapor). Changing CCNC modifies the predictability of hail precipitation, with a higher predictability in moderate polluted environments compared with the very clean and polluted environments. Increasing CCNC consistently leads a non-monotonic response of ensemble mean with an optimal CCNC for hail precipitation but a monotonic decreasing response of total precipitation with the various meteorological perturbations, meaning the initial meteorological perturbations does not qualitatively change the aerosol effects. Investigation with 10-fold reduced initial perturbation further supports the large CCN effects are not dependent of metrological perturbations. The findings suggest the importance of considering CCN effects in severe weather simulations and forecasting.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Aerosol Direct Radiative Effects at the ARM SGP and TWP Sites: Clear Skies

The clear-sky aerosol direct radiative effect (DRE) was estimated at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) and Tropical Western Pacific (TWP) sites. The NASA Langley Fu-Liou radiation model was used with observed inputs including aerosol vertical extinction profile from the Raman lidar; spectral aerosol optical depth (AOD), single-scattering albedo and asymmetry factor from Aerosol Robotic Network; temperature and water vapor profiles from radiosondes; and surface shortwave (SW) spectral albedo from radiometers. A radiative closure experiment was conducted for clear-sky conditions. The mean differences of modeled and observed surface downwelling SW total fluxes were 1 W m-2 at SGP and 2 W m -2 at TWP, which are within observational uncertainty. At SGP, the estimated annual mean clear-sky aerosol DRE is -3.00 W m -2 at the top of atmosphere (TOA) and -6.85 W m -2 at the surface. The strongest aerosol DRE of -4.81 (-10.77) W m -2 at the TOA (surface) are in the summer when AODs are largest. The weakest aerosol DRE of -.28 (-2.77) W m -2 at the TOA (surface) are in November–January when AODs and single-scattering albedos are lowest. At TWP, the annual mean clear-sky DRE is -2.82 W m-2 at the TOA and -10.34 W m -2 at the surface. The strongest aerosol DRE of -5.95 (-22.20) W m -2 at the TOA (surface) are in November (October) due to the biomass burning season’s peak. The weakest aerosol DRE of -0.96 (-4.16) W m -2 at the TOA (surface) are in March (April) when AODs are smallest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Dependence of Aerosol-Droplet Partitioning on Turbulence in a Laboratory Cloud

Activation is the first step in aerosol-cloud interactions, which have been identified as one of the principal uncertainties in Earth's climate system. Aerosol particles become cloud droplets, or activate, when the ambient saturation ratio exceeds a threshold, which depends on the particle's size and hygroscopicity. In the traditional formulation of the process, only average, uniform saturation ratios are considered. Furthermore, turbulent environments like clouds intrinsically have fluctuations around mean values in the scalar fields of temperature and water vapor concentration, which determine the saturation ratio. Through laboratory measurements, we show that these fluctuations are an important parameter that needs to be addressed to fully describe activation. Our results show, even for single-sized, chemically homogeneous aerosols, that fluctuations blur the correspondence between activation and a particle's size and chemical composition, that turbulence can increase the fraction of aerosol particles which activate, and that the activated fraction decreases monotonically as the concentration of aerosol increases. Taken together, our data demonstrate that fluctuations can have effects equivalent to the aerosol limited and updraft limited regimes, known from adiabatic parcel theory.

58 GEOSCIENCES↗
DOE OSTI2021

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Machine‐Learning‐Assisted Stochastic Cloud Population Model as a Parameterization of Cumulus Convection

Abstract A machine‐learning‐assisted stochastic cloud population model is coupled with the Advanced Research Weather Research and Forecasting (WRF) model to represent fluctuations in the cloud‐base mass flux associated with the life cycles and interactions among cumulus convection cells. In this cloud population model, the size distribution and the associated cloud‐base mass flux of the convective cells are related to their previous state and to the change in the total convective area via a transition function. The convective area tendency in turn is assumed to depend on the cloud‐base mass flux that is resolved by the host WRF model. The transition function is represented by a single hidden‐layer neural network trained by the evolution of convective cell size distributions in a 1‐km grid‐spacing WRF simulation run over the Australian Monsoon region. At every grid point of the host model, the cloud population model predicts the cell size and cloud‐base mass flux distributions from which a random sample of cells is fed to an entraining parcel model that calculates precipitation as well as the associated liquid water potential temperature and total moisture tendencies. These tendencies are averaged over the cells and provided to the host model. Several regional simulations are performed over tropical and midlatitude domains to test this as a potential approach to scale‐aware parameterization. It is shown that such an approach could be a new promising path to simulating realistic precipitation statistics and propagation of precipitation associated with the Madden‐Julian Oscillation while maintaining realistic depictions of the diurnal cycle over both land and ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Investigation of Isobaric Mixing as a Mechanism for Boundary‐Layer Cloud Formation

This study investigates the potential role of isobaric mixing in the formation of marine boundary layer clouds. Cloud formation theory emphasizes uplift and adiabatic cooling, but recent observations support the existence of small clouds forming at various altitudes, even below the lifting condensation level. Isobaric mixing of air with different thermodynamic properties can generate localized supersaturation. A Gaussian mixing model is employed to simulate this process, considering the correlation between temperature and water vapor. Cloud droplet size distributions from aircraft measurements show a persistent and prominent mode of small droplets at 9 m, and the size of this mode compares favorably with predictions from the model. The results suggests that isobaric mixing plausibly contributes to the formation of clouds, particularly those observed at multiple altitudes with narrow droplet size distributions. This finding highlights the importance of considering isobaric mixing processes in understanding and modeling cloud formation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Constraining composition and temperature variations in the mantle transition zone

The mantle transition zone connects two major layers of Earth’s interior that may be compositionally distinct: the upper mantle and the lower mantle. Wadsleyite is a major mineral in the upper mantle transition zone. Here, we measure the single-crystal elastic properties of hydrous Fe-bearing wadsleyite at high pressure-temperature conditions by Brillouin spectroscopy. Our results are then used to model the global distribution of wadsleyite proportion, temperature, and water content in the upper mantle transition zone by integrating mineral physics data with global seismic observations. Our models show that the upper mantle transition zone near subducted slabs is relatively cold, enriched in wadsleyite, and slightly more hydrated compared to regions where plumes are expected. This study provides direct evidence for the thermochemical heterogeneities in the upper mantle transition zone which is important for understanding the material exchange processes between the upper and lower mantle.

58 GEOSCIENCES↗
DOE OSTI2024

Unveiling the effect of composition on nuclear waste immobilization glasses’ durability by nonparametric machine learning

Abstract Ensuring the long-term chemical durability of glasses is critical for nuclear waste immobilization operations. Durable glasses usually undergo qualification for disposal based on their response to standardized tests such as the product consistency test or the vapor hydration test (VHT). The VHT uses elevated temperature and water vapor to accelerate glass alteration and the formation of secondary phases. Understanding the relationship between glass composition and VHT response is of fundamental and practical interest. However, this relationship is complex, non-linear, and sometimes fairly variable, posing challenges in identifying the distinct effect of individual oxides on VHT response. Here, we leverage a dataset comprising 654 Hanford low-activity waste (LAW) glasses across a wide compositional envelope and employ various machine learning techniques to explore this relationship. We find that Gaussian process regression (GPR), a nonparametric regression method, yields the highest predictive accuracy. By utilizing the trained model, we discern the influence of each oxide on the glasses’ VHT response. Moreover, we discuss the trade-off between underfitting and overfitting for extrapolating the material performance in the context of sparse and heterogeneous datasets.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Root traits explain plant species distributions along climatic gradients yet challenge the nature of ecological trade-offs

Ecological theory is built on trade-offs, where trait differences among species evolved as adaptations to different environments. Trade-offs are often assumed to be bidirectional, where opposite ends of a gradient in trait values confer advantages in different environments. However, unidirectional benefits could be widespread if extreme trait values confer advantages at one end of an environmental gradient, whereas a wide range of trait values are equally beneficial at the other end. Here, we show that root traits explain species occurrences along broad gradients of temperature and water availability, but model predictions only resembled trade-offs in two out of 24 models. Forest species with low specific root length and high root tissue density (RTD) were more likely to occur in warm climates but species with high specific root length and low RTD were more likely to occur in cold climates. Unidirectional benefits were more prevalent than trade-offs: for example, species with large-diameter roots and high RTD were more commonly associated with dry climates, but species with the opposite trait values were not associated with wet climates. Directional selection for traits consistently occurred in cold or dry climates, whereas a diversity of root trait values were equally viable in warm or wet climates. Explicit integration of unidirectional benefits into ecological theory is needed to advance our understanding of the consequences of trait variation on species responses to environmental change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Covalently integrated silica nanoparticles in poly(ethylene glycol)-based acrylate resins: thermomechanical, swelling, and morphological behavior

Nanocomposites integrate functional nanofillers into viscoelastic matrices for electronics, lightweight structural materials, and tissue engineering. Herein, the effect of methacrylate-functionalized (MA-SiO 2 ) and vinyl-functionalized (V-SiO 2 ) silica nanoparticles on the thermal, mechanical, physical, and morphological characteristics of poly(ethylene glycol) (PEG) nanocomposites was investigated. The gel fraction of V-SiO 2 composites decreases upon addition of 3.8 wt% but increases with further addition (>7.4 wt%) until it reaches a plateau at 10.7 wt%. The MA-SiO 2 induced no significant changes in gel fraction and both V-SiO 2 and MA-SiO 2 nanoparticles had a negligible impact on the nanocomposite glass transition temperature and water absorption. The Young's modulus and ultimate compressive stress increased with increasing nanoparticle concentration for both nanoparticles. Due to the higher crosslink density, MA-SiO 2 composites reached a maximum mechanical stress at a concentration of 7.4 wt%, while V-SiO 2 composites reached a maximum at a concentration of 10.7 wt%. Scanning electron microscopy, transmission electron microscopy, and small-angle X-ray scattering revealed a bimodal size distribution for V-SiO 2 and a monomodal size distribution for MA-SiO 2 . Although aggregates were observed for both nanoparticle surface treatments, V-SiO 2 dispersion was poor while MA-SiO 2 were generally well-dispersed. Finally, these findings lay the framework for silica nanofillers in PEG-based nanocomposites for advanced manufacturing applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Direct numerical simulations of activation and deactivation in turbulent atmospheric clouds

Significant knowledge gaps remain in our understanding of turbulence–cloud–aerosol interactions in the Earth's atmosphere, and direct numerical simulation (DNS) has increasingly become an indispensable tool to fill such critical knowledge gaps. Here, this study is an extension of our previous DNS model [Gao et al., J. Geophys. Res.: Atmos., 123(4), 2194–2214 (2018)], with a focus on the activation of aerosol particles into cloud droplets and deactivation of cloud droplets into aerosol particles in a microscale cloud environment. The effects of turbulence intensity, particle curvature, and solute, as well as the initial distributions of the aerosol particles (monodisperse or polydisperse) are investigated. The governing equations for the flow of air, temperature, and water vapor mixing ratio are solved numerically in the Eulerian fashion, assuming homogeneous and isotropic turbulence. The dynamics of the aerosol and cloud particles are calculated with the Lagrangian particle tracking method. The results show that the deviations of the thermodynamic variables from their respective means are significantly reduced, the activation process appears to be delayed, and the deactivation process occurs more rapidly, as the turbulence intensity is increased. The inclusion of particle curvature and solute effects, as well as polydispersity, tends to retard the activation of aerosols into cloud droplets. It is also observed that fluctuations in supersaturation broaden the spread of particle radii, and the broadening is followed by a narrowing as turbulent homogenization reduces thermodynamic fluctuations over time.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Topology Optimization Framework to Facilitate Adoption of Advanced District Thermal Energy Systems

Advanced district thermal energy systems, which circulate water at temperatures near ambient conditions, and facilitate the utilization of waste heat and renewable thermal sources, can lower the carbon-intensity of urban districts, advancing the U.N. Sustainable Development Goals. Optimization of the network topology — the selection of the best subset of buildings and the best network to connect them, to minimize life cycle cost — can increase adoption of these system in appropriate applications. The potential "solution space" of the topology optimization problem grows factorially with the number of buildings in the district, motivating the consideration of a design heuristic. In this study, a heuristic for the network selection was evaluated with an exhaustive search, for a prototypical four-building district. For the prototypical district considered, the heuristic was effective in selecting an optimal network topology. Additionally, it was found that, in this case, the selection of the subset of buildings was more influential on the life cycle cost than the selection of the network topology. This work is part of a larger effort to develop a topology optimization framework for district thermal energy systems, which is anticipated to address barriers to adoption of ambient-temperature systems.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2026

Compilation and utilization of a sorghum transcriptome compendium for gene regulatory network analysis and crop trait engineering

Sorghum bicolor (Sorghum) is a drought and heat tolerant C4 grass crop used to produce grain, forage, biofuels, and other bioproducts. Genetic improvement of sorghum hybrid crops is aided by a large and diverse germplasm, sorghum's diploid inbreeding genetics, and a relatively small genome that has facilitated genomic research. Over the past 20 years, the sorghum research community characterized the cytogenetic and recombinant landscapes of sorghum's 10 chromosomes, sequenced and annotated the sorghum genome, and used that information to identify genes/alleles that modulate flowering time, plant height, seed shattering, and other important traits. More recently, >1000 RNA-seq transcriptome profiles were collected from 15 sorghum genotypes to help understand the genetic basis of variation in growth and development of sorghum stems, tillers, roots, and leaves, and the regulation of biosynthetic pathways that produce epicuticular wax, dhurrin, and RFOs, compounds that contribute to sorghum's resilience. Transcriptome studies were designed to identify differentially expressed genes that are co-expressed during development or in response to a treatment to enable construction of gene regulatory networks. Co-expression and network analysis identified transcription factors and their cognate binding sites in target gene promoters and signaling pathways that modulate gene regulatory networks providing gene editing targets for further trait optimization. RNA-seq data from >20 experiments targeting sorghum organs, tissues, cell types, developmental stages, and responses to environmental conditions (i.e., diel, day-length, shading, water-deficit, temperature) has been compiled in a sorghum transcriptome compendium. The goal of this resource paper is to describe compendium content, accessibility, and a compendium data analysis pipeline and to illustrate the types of information that can be derived from the compendium with a focus on the elucidation of gene regulatory networks useful for guiding the improvement of sorghum traits through gene editing.

RNA-seq↗