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At least 343 records · Page 19

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NASA NTRS2021

Carolina Coastal Plain Ecological Forecasting: Utilizing NASA Earth Observations to Map Suitable Venus Flytrap Habitat in an Effort to Inform Conservation, Seed Banking, and Reintroduction in the Carolina Coastal Plain and Sandhills Regions

Although the carnivorous plant Venus flytrap (Dionaea muscipula) is recognized globally, its native range is restricted to a small portion of the North and South Carolina Coastal Plain and Sandhills. Within this limited range, Venus flytrap populations are threatened by habitat loss, fire suppression, and poaching. NASA DEVELOP partnered with the North Carolina Botanical Garden (NCBG), the University of North Carolina Herbarium (NCU), and the North Carolina Natural Heritage Program (NCNHP) to support Venus flytrap conservation. The team developed models based on species presence data and environmental variables using the Software for Assisted Habitat Modeling (SAHM) to create a 2021 habitat suitability map for Venus flytrap. These models incorporated Earth observations collected by Landsat 8 Thermal Infrared Sensor (TIRS), Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Land Observation Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), and Sentinel-2 Multispectral Instrument (MSI). To predict areas at high risk of development, the team produced a 2050 land-use change map using TerrSet Land Change Modeler. The team found potential areas of conflict between predicted habitat and forecasted future development. Many areas of suitable habitat were concentrated along the coast where development was likely to occur, placing populations there at risk of extirpation. Overlaying suitable habitat with forecasted land change also identified suitable habitats with minimal risk of development, which may serve as lasting Venus flytrap habitat. These results can inform the NCBG and NCNHP’s conservation decision-making, including targeted seed banking, reintroduction, and prioritization of enduring habitats for protection and management.

Monika Rock↗

NASA NTRS2022

Carolina Coastal Plain Ecological Forecasting

Monika Rock↗

DOE OSTI2024

Carbon-13 Radiofrequency Amplification by Stimulated Emission of Radiation of the Hyperpolarized Ketone and Hemiketal Forms of Allyl [1- 13 C]Pyruvate

13 C hyperpolarized pyruvate is an emerging MRI contrast agent for sensing molecular events in cancer and other diseases with aberrant metabolic pathways. This metabolic contrast agent can be produced via several hyperpolarization techniques. Despite remarkable success in research settings, widespread clinical adoption faces substantial roadblocks because the current sensing technology utilized to sense this contrast agent requires the excitation of 13 C nuclear spins that also need to be synchronized with MRI field gradient pulses. Here, we demonstrate sensing of hyperpolarized allyl [1- 13 C]pyruvate via the stimulated emission of radiation that mitigates the requirements currently blocking broader adoption. Specifically, 13 C Radiofrequency Amplification by Stimulated Emission of Radiation ( 13 C RASER) was obtained after pairwise addition of parahydrogen to a pyruvate precursor, detected in a commercial inductive detector with a quality factor (Q) of 32 for sample concentrations as low as 0.125 M with 13 C polarization of 4%. Moreover, parahydrogen-induced polarization allowed for the preparation of a mixture of ketone and hemiketal forms of hyperpolarized allyl [1- 13 C]pyruvate, which are separated by 10 ppm in 13 C NMR spectra. This is a good model system to study the simultaneous 13 C RASER signals of multiple 13 C species. This system models the metabolic production of hyperpolarized [1- 13 C]lactate from hyperpolarized [1- 13 C]pyruvate, which has a similar chemical shift difference. Our results show that 13 C RASER signals can be obtained from both species simultaneously when the emission threshold is exceeded for both species. On the other hand, when the emission threshold is exceeded only for one of the hyperpolarized species, 13 C stimulated emission is confined to this species only, therefore enabling the background-free detection of individual hyperpolarized 13 C signals. Furthermore, the reported results pave the way to novel sensing approaches of 13 C hyperpolarized pyruvate, potentially unlocking hyperpolarized 13 C MRI on virtually any MRI system–an attractive vision for the future molecular imaging and diagnostics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Coupled chemical–CFD modeling of unsealed dry storage of advanced test reactor spent fuel

We report given the current lack of long-term disposal for spent nuclear fuel storage in the United States, the current inventory of advanced test reactor (ATR) fuel at Idaho National Laboratory (INL) is expected to be stored in a dry storage facility for an extended storage period. As part of an effort to understand the conditions during a 50-year period, a three-dimensional computational fluid dynamics (CFD) of the unsealed canisters packed with spent fuel in the storage facility was constructed, this CFD model is coupled with radiolytic chemical reactions associated with water vapor and other species. The coupled model is simulated over a range of sensitivity parameters for the fuel decay heat, relative humidity, and oxyhydroxide film thickness for undried and fully-dried fuel. The most important parameter was the initial fuel decay heat. Over the range of cases, the hydrogen and nitric acid concentrations are low enough no significant impact is expected.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1974

Development of a second order closure model for computation of turbulent diffusion flames

A typical eddy box model for the second-order closure of turbulent, multispecies, reacting flows developed. The model structure was quite general and was valid for an arbitrary number of species. For the case of a reaction involving three species, the nine model parameters were determined from equations for nine independent first- and second-order correlations. The model enabled calculation of any higher-order correlation involving mass fractions, temperatures, and reaction rates in terms of first- and second-order correlations. Model predictions for the reaction rate were in very good agreement with exact solutions of the reaction rate equations for a number of assumed flow distributions.

Varma, A. K.↗

NASA NTRS1992

The chemical effects of auroral oxygen precipitation at Jupiter

A numerical model of the auroral ionosphere and thermosphere of Jupiter, which includes odd oxygen species, is presented. Density profiles of neutral species O, OH, and H2O and the ion species H2(+), H3(+), H(+), H2O(+), H3O(+), O(+), and OH(+) are calculated. The total neutral odd oxygen density is found to be about 10 exp 5/cu cm near the auroral ionosphere peak. The major ionospheric ion, H(+) reacts rapidly with both O and H2O and the presence of these species in the model calculations significantly reduces the H(+) density and thus the electron density. The chemical lifetime against reaction of H(+) with odd oxygen is about 1000 s near the peak, whereas the radiative recombination lifetime is roughly 10,000 s.

Cravens, T. E.↗

NASA NTRSDate not supplied

Atmospheric Variability and Measurement Uncertainty: Pitfalls in Averaging in situ Data

Satellite measurements and atmospheric models, two essential components of the integrated global observing system, provide crucial tools for monitoring and predicting regional and global foci, spanning numerous Earth Science fields. Unfortunately, models can lack the spatial and temporal resolution needed to resolve finer scale structure. Satellite measurements also have similar tempo-spatial restriction issues, but additionally can only measure certain species and can have biases that must be evaluated. Ground measurement networks are critical components of this system, by providing both independent inputs of species needed by models (including those that satellites do not provide) and assisting with investigation of biases in satellite products. Similarly, aircraft measurements play a vital role in closing the gaps between satellite measurements, model products, and ground monitoring networks by providing high accuracy, high-resolution data on local to regional spatial scales. Therefore, both ground-based and airborne observations are widely used to assess model predictions and satellite observations. One of the great challenges in using both ground and aircraft data in this fashion is matching the data temporally and spatially to the model/satellite data. A meaningful comparison with model or satellite requires a solid assessment of the variability of the in-situ measurements, which include both the instrument uncertainty and the statistical uncertainty due to atmospheric variability. While instrument uncertainty is generally more straightforwardly characterized, it can be challenging to accurately capture this variability uncertainty as it often presents in a non-Gaussian manner (e.g. emission plumes, frontal passages). We will present results examining spatial and temporal variability over a selection of scales relevant to satellite measurements and models of several in situ measurement species spanning both airborne and ground measurements. The extent of non-Gaussian variability will be quantified, and we will discuss additional statistical parameters that help assess the fitness of gaussian variability assumption when temporally or spatially averaging.

satellite validation↗

NASA NTRS1988

The effect of random precipitation times on the scavenging rate for tropospheric nitric acid

A model for the effective scavenging rate of a soluble species has been developed. The model takes into account the possibility of positive as well as negative correlations between departures from the mean of the scavenging rate and species concentration. The model is demonstrated for the case of late afternoon rainout of nitric acid occurring just prior to the nighttime cessation of its chemical production. The calculations give effective scavenging rates which are about a factor of 2 to 3 greater than those calculated using the models of Rodhe and Grandell (1972) and Giorgi and Chameides (1985).

Stewart, Richard W.↗

DOE OSTI2022

Extension of the energetic particle transport kick model in TRANSP to multiple fast ion species

Abstract Alfvénic instabilities (AEs) are well known to cause enhanced transport of energetic particles (EPs) in fusion devices. Most studies until now have focused on characterizing and understanding AE stability in single-species plasmas heated by neutral beams (NB), where deuterium is typically used as both main plasma species and NB fuel. As the fusion community moves toward fusion reactors that target burning plasma conditions, such as ITER, the single-species picture breaks down. Burning plasmas, which will use a mix of deuterium and tritium (DT) as main fuel, also feature the presence of several supra-thermal fusion products such as alpha particles, protons, helium isotopes and high-energy tritium ions. This work presents the extension of the EP transport kick model implemented in the TRANSP time-dependent tokamak transport code to study the combined effect of multiple EP species on AE stability and, in turn, the response of different EP species to plasma instabilities in terms of their redistribution and losses. Further validation of the enhanced model is planned based on experimental results expected from the JET DT campaign scheduled for 2021, in preparation for ITER plasmas and beyond.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Python Group Additivity (pGrAdd) software for estimating species thermochemical properties

ncreasingly complex chemistry models require thermochemical data for many species often estimated from costly first-principles DFT computations. Here we introduce the Python Group Additivity software (pGrAdd) that implements comprehensive group additivity in a simple, modular, lightweight Python package that is extensible and easy to implement. It includes 6 group additivity databases for gas species and Pt(111) adsorbates allowing users to immediately compute thermochemical properties for a wide range of molecules and build new databases.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2004

Computational Ion Optics Design Evaluations

Ion optics computational models are invaluable tools in the design of ion optics systems. In this study a new computational model developed by an outside vendor for use at the NASA Glenn Research Center (GRC) is presented. This computational model is a gun code that has been modified to model the plasma sheaths both upstream and downstream of the ion optics. The model handles multiple species (e.g. singly and doubly-charged ions) and includes a charge-exchange model to support erosion estimations. The model uses commercially developed solid design and meshing software to allow high flexibility in ion optics geometric configurations. The results from this computational model are applied to the NEXT project to investigate the effects of crossover impingement erosion seen during the 2000-hour wear test.

Malone, Shane P.↗

NASA NTRS2004

Computational Modeling of NEXT 2000-Hour Wear Test Results

Ion optics computational models are invaluable tools for the design of ion optics systems. In this study, a new computational model developed by an outside vendor for NASA Glenn Research Center (GRC) is presented. This model is a gun code which has been modified to model the plasma sheaths both upstream and downstream of the ion optics. The model handles multiple species (e.g. singly and doubly-charged ions) and includes a charge-exchange model for erosion estimates. The model uses commercially available solid design and meshing software, allowing high flexibility in ion optics geometric configurations. This computational model is compared to experimental results from the NASA Evolutionary Xenon Thruster (NEXT) 2000-hour wear test, including over-focusing along the edge apertures, pit-and-groove erosion due to charge exchange, and beamlet distortion at the edge of the hole pattern.

Malone, Shane P.↗

DOE OSTI2024

Photosynthetic responses to temperature across the tropics: a meta-analytic approach

Background and Aims Tropical forests exchange more carbon dioxide (CO 2 ) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three times greater for the tropics than other for ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink. Methods Here, we used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light-saturated photosynthetic (A sat ) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (J max ) and Rubisco carboxylation (V cmax ). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity and elevation, as well as also how responses differed among successional strategy, leaf habit and light environment. Key Results Optimum temperatures for A sat (T optA ) and J max (T optJ ) increased with MAT but not for V cmax (T optV ). Although photosynthetic rates were higher for ‘light’ than ‘shaded’ leaves, light conditions did not generate differences in temperature response parameters. T optA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher T optA than broadleaf evergreen species. Most global modelling efforts consider all tropical forests as a single ‘broadleaf evergreen’ functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modelling efforts. Conclusions This novel research will inform modelling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

Carter, Kelsey R. [Oak Ridge National Laboratory (↗

DOE OSTI2021

Biological Response Models: Predicting Injury and Mortality of Fish During Downstream Passage through Hydropower Facilities

This report describes the U.S. Department of Energy’s HydroPASSAGE project efforts to develop and collect biological response models for integration into the Biological Performance Assessment (BioPA) toolset and the Hydropower Biological Evaluation Toolset (HBET). These models help understand how fish are likely to respond during dam passage when exposed to hydraulic and physical stressors associated with turbines and other hydropower structures. When fish pass through hydropower facilities, they may encounter several stressors, of which the three most common are collision, rapid decompression, and fluid shear. Specialized equipment has been used to develop 99 biological response models for exposure to blade strike, rapid decompression, or fluid shear. The models were gathered from the literature or developed as part of this effort and include models for 31 different species of fish that have various predicted endpoints (i.e., injury or mortality). Among these models, considerable variation in susceptibility to the stressors has been observed from one species to another, and a species’ susceptibility to one stressor does not necessarily indicate similar susceptibility to another. Although several species have been examined, it is still unclear how many other species, which may have different morphological traits, may respond to these stressors, so further examination of the different species is needed. These models can and have been applied in several different cases, often using the BioPA toolset and HBET, to better understand the potential for injury and mortality that may occur during fish passage at hydropower facilities, including specific applications, such as turbine replacement, the installation of new turbines, or changing operations of currently installed turbines. As hydropower is continually developed to meet the electricity needs of society, tools such as HBET and BioPA, used with the integrated biological response models, will aid in the development of technologies and strategies that avoid, minimize, mitigate, or manage environmental effects.

13 HYDRO ENERGY↗

DOE OSTI2023

First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis

Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2000

A Solution Methodology and Computer Program to Efficiently Model Thermodynamic and Transport Coefficients of Mixtures

A solution methodology has been developed to efficiently model multi-specie, chemically frozen, thermally perfect gas mixtures. The method relies on the ability to generate a single (composite) set of thermodynamic and transport coefficients prior to beginning a CFD solution. While not fundamentally a new concept, many applied CFD users are not aware of this capability nor have a mechanism to easily and confidently generate new coefficients. A database of individual specie property coefficients has been created for 48 species. The seven coefficient form of the thermodynamic functions is currently used rather then the ten coefficient form due to the similarity of the calculated properties, low temperature behavior and reduced CPU requirements. Sutherland laminar viscosity and thermal conductivity coefficients were computed in a consistent manner from available reference curves. A computer program has been written to provide CFD users with a convenient method to generate composite specie coefficients for any mixture. Mach 7 forebody/inlet calculations demonstrated nearly equivalent results and significant CPU time savings compared to a multi-specie solution approach. Results from high-speed combustor analysis also illustrate the ability to model inert test gas contaminants without additional computational expense.

Ferlemann, Paul G.↗

DOE OSTI2023

Nested solitons in two-field fuzzy dark matter

ABSTRACT Dark matter as scalar particles consisting of multiple species is well motivated in string theory where axion fields are ubiquitous. A two-field fuzzy dark matter (FDM) model features two species of ultralight axion particles with different masses, m1 ≠ m2, which is extended from the standard one-field model with $m_a \sim 10^{-22} \, {\rm eV}$. Here we perform numerical simulations to explore the properties of two-field FDM haloes. We find that the central soliton has a nested structure when m2 ≫ m1, which is distinguishable from the generic flat-core soliton in one-field haloes. However, the formation of this nested soliton is subject to many factors, including the density fraction and mass ratio of the two fields. Finally, we study non-linear structure formation in two-field cosmological simulations with self-consistent initial conditions and find that the small-scale structure in two-field cosmology is also distinct from the one-field model in terms of DM halo counts and soliton formation time.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Overcoming genetic paucity of Camelina sativa : possibilities for interspecific hybridization conditioned by the genus evolution pathway

Camelina or false flax (Camelina sativa) is an emerging oilseed crop and a feedstock for biofuel production. This species is believed to originate from Western Asian and Eastern European regions, where the center of diversity of the Camelina genus is located. Cultivated Camelina species arose via a series of polyploidization events, serving as bottlenecks narrowing genetic diversity of the species. The genetic paucity of C. sativa is foreseen as the most crucial limitation for successful breeding and improvement of this crop. A potential solution to this challenge could be gene introgression from Camelina wild species or from resynthesized allohexaploid C. sativa. However, both approaches would require a complete comprehension of the evolutionary trajectories that led to the C. sativa origin. Although there are some studies discussing the origin and evolution of Camelina hexaploid species, final conclusions have not been made yet. Here, we propose the most complete integrated evolutionary model for the Camelina genus based on the most recently described findings, which enables efficient improvement of C. sativa via the interspecific hybridization with its wild relatives. We also discuss issues of interspecific and intergeneric hybridization, aimed on improving C. sativa and overcoming the genetic paucity of this crop. The proposed comprehensive evolutionary model of Camelina species indicates that a newly described species Camelina neglecta has a key role in origin of tetra- and hexaploids, all of which have two C. neglecta-based subgenomes. Understanding of species evolution within the Camelina genus provides insights into further research on C. sativa improvements via gene introgression from wild species, and a potential resynthesis of this emerging oilseed crop.

09 BIOMASS FUELS↗