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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 163 records · Page 9

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Mineral Database and Dashboard

The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.

produced water management↗

Acceleration of Graph Neural Network-Based Prediction Models in Chemistry via Co-Design Optimization on Intelligence Processing Units

Atomic structure prediction and associated property calculations are the bedrock of chemical physics. Since high-fidelity ab initio modeling techniques for computing the structure and properties can be prohibitively expensive, this motivates the development of machine-learning (ML) models that make these predictions more efficiently. Training graph neural networks over large atomistic databases introduces unique computational challenges such as the need to process millions of small graphs with variable size and support communication patterns that are distinct from learning over large graphs such as social networks. We demonstrate a novel hardware-software co-design approach to scale up the training of atomistic graph neural networks (GNN) for structure and property prediction. First, to eliminate redundant computation and memory associated with alternative padding techniques and to improve throughput via minimizing communication, we formulate the effective coalescing of the batches of variable-size atomistic graphs as the bin packing problem and introduce a hardware-agnostic algorithm to pack these batches. In addition, we propose hardware-specific optimizations including a planner and vectorization for the gather-scatter operations targeted for Graphcore’s Intelligence Processing Unit (IPU), as well as model-specific optimizations such as merged communication collectives and optimized softplus. Putting these all together, we demonstrate the effectiveness of the proposed co-design approach by providing an implementation of a well-established atomistic GNN on the Graphcore IPUs. We evaluate the training performance on multiple atomistic graph databases with varying degrees of graph counts, sizes and sparsity. Here, we demonstrate that such a co-design approach can reduce the training time of atomistic GNNs and can improve the performance by up to 1.5× compared to the baseline implementation of the model on the IPUs. Additionally, we compare our IPU implementation with a Nvidia GPU-based implementation and show that our atomistic GNN implementation on the IPUs can run 1.8× faster on average compared to the execution time on the GPUs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chemistry on the mesoscale: Modeling and measurement issues

The topics covered include the following: Regional Acid Deposition Model (RADM) -- a coupled chemistry/mesoscale model; convection in RADM; unresolved issues for mesoscale modeling with chemistry -- nonprecipitating clouds; unresolved issues for mesoscale modeling with chemistry -- aerosols; tracer studies with Goddard Cumulus Ensemble Model (GCEM); field observations of trace gas transport in convection; and photochemical consequences of convection.

Thompson, Anne↗

A parameter sensitivity study for simulating DNA damage after proton irradiation using TOPAS-nBio

Monte Carlo (MC) track structure simulation tools are commonly used for predicting radiation induced DNA damage by modeling the physical and chemical reactions at the nanometer scale. However, the outcome of these MC simulations is particularly sensitive to the adopted parameters which vary significantly across studies. In this study, a previously developed full model of nuclear DNA was used to describe the DNA geometry. The TOPAS-nBio MC toolkit was used to investigate the impact of physics and chemistry models as well as three key parameters (the energy threshold for direct damage, the chemical stage time length, and the probability of damage between hydroxyl radical reactions with DNA) on the induction of DNA damage. Our results show that the difference in physics and chemistry models alone can cause differences up to 34% and 16% in the DNA double strand break (DSB) yield, respectively. Additionally, changing the direct damage threshold, chemical stage length, and hydroxyl damage probability can cause differences of up to 28%, 51%, and 71% in predicted DSB yields, respectively, for the configurations in this study.

60 APPLIED LIFE SCIENCES↗

Anthropogenic Sulfate, Clouds, and Climate Forcing

This research work is a joint effort between research groups at the Battelle Pacific Northwest Laboratory, Virginia Tech University, Georgia Institute of Technology, Brookhaven National Laboratory, and Texas A&M University. It has been jointly sponsored by the National Aeronautics and Space Administration, the U.S. Department of Energy, and the U.S. Environmental Protection Agency. In this research, a detailed tropospheric aerosol-chemistry model that predicts oxidant concentrations as well as concentrations of sulfur dioxide and sulfate aerosols has been coupled to a general circulation model that distinguishes between cloud water mass and cloud droplet number. The coupled model system has been first validated and then used to estimate the radiative impact of anthropogenic sulfur emissions. Both the direct radiative impact of the aerosols and their indirect impact through their influence on cloud droplet number are represented by distinguishing between sulfuric acid vapor and fresh and aged sulfate aerosols, and by parameterizing cloud droplet nucleation in terms of vertical velocity and the number concentration of aged sulfur aerosols. Natural sulfate aerosols, dust, and carbonaceous and nitrate aerosols and their influence on the radiative impact of anthropogenic sulfate aerosols, through competition as cloud condensation nuclei, will also be simulated. Parallel simulations with and without anthropogenic sulfur emissions are performed for a global domain. The objectives of the research are: To couple a state-of-the-art tropospheric aerosol-chemistry model with a global climate model. To use field and satellite measurements to evaluate the treatment of tropospheric chemistry and aerosol physics in the coupled model. To use the coupled model to simulate the radiative (and ultimately climatic) impacts of anthropogenic sulfur emissions.

Ghan, Steven J.↗

Tropospheric Ozone in the NASA GEOS Model: Effects of Satellite NO2 Data Assimilation and Improvements in Background NOx Chemistry

Tropospheric ozone is a major atmospheric oxidant, the primary source of the hydroxyl radical, and a greenhouse gas. In the troposphere, it is produced from the oxidation of carbon monoxide and volatile organic compounds in the presence of nitrogen oxides (NOx=NO+NO2) or has its origins in the stratosphere. The tropospheric ozone burdens in global atmospheric chemistry models disagree by a factor of 1.5, indicating an incomplete understanding of ozone sources and sinks. Here we examine the tropospheric ozone simulation in NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS model with the GEOS-Chem chemistry mechanism (version 14.2), using observations from satellites, aircraft, ozonesondes, and surface sites. This modeling framework is used to produce GMAO’s GEOS Composition Forecasts (GEOS-CF), and it has been updated extensively with new emission inventories, improved model physics, satellite data assimilation capability, and an up-to-date chemical mechanism that includes tropospheric halogen chemistry and NOx recycling from particulate nitrate. Earlier versions of the model using GEOS-Chem version 12.0 showed an underestimate in tropospheric ozone in the northern hemisphere. We evaluate the ozone simulation in the updated model, focusing on the effects of assimilating satellite NO2 data from the Ozone Monitoring Instrument (OMI), constraining stratospheric ozone to satellite data, and updates to the NOx chemistry. We will examine changes in the vertical profiles of tropospheric ozone over the US in support of the Tropospheric Emissions: Monitoring of Pollution (TEMPO), and discuss implications for the tropospheric ozone budget.

V. Shah↗

Tropospheric Ozone in the NASA GEOS Model: Effects of Satellite Data Assimilation and Improvements in Background NO x Chemistry

Tropospheric ozone is a major atmospheric oxidant, the primary source of the hydroxyl radical, and a greenhouse gas. In the troposphere, it is produced from the oxidation of carbon monoxide and volatile organic compounds in the presence of nitrogen oxides (NO x =NO+NO 2 ) or has its origins in the stratosphere. The tropospheric ozone burdens in global atmospheric chemistry models disagree by a factor of 1.5, indicating an incomplete understanding of ozone sources and sinks. Here we examine the tropospheric ozone simulation in NASA Global Modeling and Assimilation Office’s (GMAO’s) GEOS model with the GEOS-Chem chemistry mechanism (version 14.2), using observations from satellites, aircraft, ozonesondes, and surface sites. This modeling framework is used to produce GMAO’s GEOS Composition Forecasts (GEOS-CF), and it has been updated extensively with new emission inventories, improved model physics, satellite data assimilation capability, and an up-to-date chemical mechanism that includes tropospheric halogen chemistry and NOx recycling from particulate nitrate. Earlier versions of the model using GEOS-Chem version 12.0 showed an underestimate in tropospheric ozone in the northern hemisphere. We evaluate the ozone simulation in the updated model, focusing on the effects of assimilating satellite NO 2 data from the Ozone Monitoring Instrument (OMI), constraining stratospheric ozone to satellite data, and updates to the NOx chemistry. We will examine changes in the vertical profiles of tropospheric ozone over the US in support of the Tropospheric Emissions: Monitoring of Pollution (TEMPO), and discuss implications for the tropospheric ozone budget.

Viral Shah↗

On the modelling of non-reactive and reactive turbulent combustor flows

A study of non-reactive and reactive axisymmetric combustor flows with and without swirl is presented. Closure of the Reynolds equations is achieved by three models: kappa-epsilon, algebraic stress and Reynolds stress closure. Performance of two locally nonequilibrium and one equilibrium algebraic stress models is analyzed assuming four pressure strain models. A comparison is also made of the performance of a high and a low Reynolds number model for combustor flow calculations using Reynolds stress closures. Effects of diffusion and pressure-strain models on these closures are also investigated. Two models for the scalar transport are presented. One employs the second-moment closure which solves the transport equations for the scalar fluxes, while the other solves the algebraic equations for the scalar fluxes. In addition, two cases of non-premixed and one case of premixed combustion are considered. Fast- and finite-rate chemistry models are applied to non-premixed combustion. Both show promise for application in gas turbine combustors. However, finite rate chemistry models need to be examined to establish a suitable coupling of the heat release effects on turbulence field and rate constants.

Nikjooy, Mohammad↗

Modeling prebiotic chemistries with quantum accuracy at classical costs

Molecular Dynamics (MD) simulations using classical force-fields are commonly employed in numerous scientific investigations. However, many natural processes involve bond breaking and quantum forces. This complexity is compounded by the presence of multiple competing length and timescales. For example, accurately modeling the thermodynamics and dynamics of a chemical reaction requires accounting for the concerted movements of numerous solvent molecules and ions with their own fast or slow timescales. While widely used static Density Functional Theory (DFT) calculations at 0 temperature can be beneficial for such investigations, they do not account for dynamics, and lack precision in describing the molecular environments. They particularly fail at correct, rigorous treatments of finite-temperature fluctuations, and thus generalization to experimentally relevant conditions. In PNAS Benayad et al develop a scalable, generalizable approach for designing Neural Network Potentials (NNPs) that can handle chemical reactivity in solvated systems with quantum accuracy at classical costs. Specifically, they study phosphoester bond formation and rupture, which is fundamentally relevant to the Phosphorus-Oxygen bond formation central to life, and especially for the RNA world hypothesis. The framework developed here has the potential to generalize to different chemical reactions of energy and biological relevance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Analysis of North Atlantic Aircraft Data on Oxygenated Intermediate Species Using an Adapted Regional Chemistry-Transport Model

Our study is on the interaction of nitrogen oxides with organics as they are exported from their complex sources in Eastern North America. Both urban and specific industrial emissions contribute the nitrogen of the C-H-O-N compounds that affect the global atmosphere, helping determine both ozone and the self-cleaning radical chemistry of the troposphere mediated by the OH radical. Different industrial sources, urban, and natural emissions contribute the organic C. Peroxyacetyl nitrate, CH3C(double bonds O)OONO2 is the most interesting compound for which we can measure the outflow to the full depth of the Atlantic troposphere. As we adapt the 3-d chemical model to describe outflow for specific periods with sufficient accuracy, we are analyzing some valuable information in the NARE-97 complete airborne dataset. (NARE: North Atlantic Regional Experiment). Ames researchers find that there are substantial puzzles in the ratios of PAN/NO2. Peroxy acetyl nitrate provides one of the major long-distance export pathways for active nitrogen from Eastern North America. It should be closely linked with NO, (defined as the sum NO + NO2) by simple thermal association and decomposition reactions, at least when the ambient temperature is substantially above 5 C.

Chatfield, Robert↗

Utilization of STRAT Data

One of the goals of the STRAT mission was to improve our understanding of transport in the stratosphere. We have used our coupled 2-D model to analyse transport between the tropics and midlatitudes using aircraft measurements of (CO2) and (N2O) made during the SPADE and ASHOE/MAESA campaigns (Boering et al. 1994) for model validation. We have further used the model to estimate errors in the experimental determination of the age of stratospheric air that arise from nonlinear increases of real tracers such as (CO2) and (SF6). The interpretation of measurements made during STRAT is still in progress. Most of the work performed under this contract has been described in the second year progress report, submitted in April of 1996. In the following, the research is summarized and some additional work that has become relevant in the meantime is described. We have developed an interactive model of the dynamics, chemistry and radiation of the stratosphere with partial support from this contract. The dynamics module integrates the primitive equations on a sphere. Lower boundary zonal winds and eddy geopotential heights are specified from observations. Chemistry and tracer transport are done in two dimensions. The chemistry model is a family model. Long lived species are transported and short lived species are determined in intervals of 5 to 10 days by assuming photochemical steady state. Full diurnal integrations with the fast species are performed periodically and diurnal coefficients, derived from the explicit integration are used to determine the steady state solution. Heating rates in the stratosphere are calculated from model ozone and the model temperatures and circulation fields are used in the chemistry transport module.

Source record↗

Hypersonic Aerodynamic Characteristics of a Proposed Single-Stage-To-Orbit Vehicle

The hypersonic aerodynamic characteristics of a winged body concept representing a candidate single- stage-to-orbit vehicle which features wing tip fin controllers and elevon/body flap control surfa'Fs are predicted at points along a nominal trajectory for Mach numbers from 5 to 27 and angles of attack from 19 to 32 degrees. Predictions are derived from surface properties based on flow solvers for inviscid and viscous, laminar flows acting as a perfect gas, as a gas in chemical equilibrium and as a gas in chemical non- equilibrium. At a Mach number of 22, the lateral aerodynamic characteristics of the vehicle are determined based on an inviscid analysis at side slip angles of 2 and 4 degrees and 32 degrees angle of attack; a viscous analysis was carried out to determine the effect of gas chemistry model on surface pressure and to determine the incremental aerodynamics for control surface deflections. The results show that the longitudinal pitch characteristics of the baseline configuration, i.e., zero control surface deflections, are significantly altered by real gas chemistry at angles of attack greater than 30 degrees and Mach numbers greater than 9; and, that aerodynamics derived from inviscid solutions are of sufficient accuracy for preliminary analysis. Also, it is shown that a Mach number of 22, the choice of gas chemistry model has a large impact on surface pressure levels at highly localized regions on the vehicle and that the vehicle can be trimmed at control surface deflections less than 11 degrees.

Weilmuenster, K. James↗

Satellite observation and mapping of wintertime ozone variability in the lower stratosphere

Comparison is made between 30 mbar ozone fields that are generated by a transport chemistry model utilizing the winds from the Goddard Space Flight Center stratospheric data assimilation system (STRATAN), observations from the LIMS instrument on Nimbus-7, and the ozone fields that result from 'flying a mathematical simulation of LIMS observations through the transport chemistry model ozone fields. The modeled ozone fields were found to resemble the LIMS observations, but the model fields show much more temporal and spatial structure than do the LIMS observations. The 'satellite mapped' model results resemble the LIMS observations much more closely. These results are very consistent with the earlier discussions of satellite space-time sampling by Salby.

Geller, Marvin A.↗

Satellite observation and mapping of wintertime ozone variability in the lower stratosphere

Comparison is made between 30 mbar ozone fields that are generated by a transport chemistry model utilizing the winds from the Goddard Space Flight Center stratospheric data assimilation system (STRATAN), observations from the LIMS instrument on Nimbus-7, and the ozone fields that result from 'flying' a mathematical simulation of LIMS observations through the transport chemistry model ozone fields. The modeled ozone fields were found to resemble the LIMS observations, but the model fields show much more temporal and spatial structure than do the LIMS observations. The 'satellite mapped' model results resemble the LIMS observations much more closely. These results are very consistent with the earlier discussions of satellite space-time sampling by Salby.

Geller, M. A.↗

Evolutionary models of interstellar chemistry

The goal of evolutionary models of interstellar chemistry is to understand how interstellar clouds came to be the way they are, how they will change with time, and to place them in an evolutionary sequence with other celestial objects such as stars. An improved Mark II version of an earlier model of chemistry in dynamically evolving clouds is presented. The Mark II model suggests that the conventional elemental C/O ratio less than one can explain the observed abundances of CI and the nondetection of O2 in dense clouds. Coupled chemical-dynamical models seem to have the potential to generate many observable discriminators of the evolutionary tracks. This is exciting, because, in general, purely dynamical models do not yield enough verifiable discriminators of the predicted tracks.

Prasad, Sheo S.↗

Theoretical estimates of flammability bounds for thin condensed fuel diffusion flames in microgravity using detailed models of chemistry and radiation

Recently, U-shape flammability maps have been constructed showing minimal oxygen vs. flame strain for opposed flame spread in micro-gravity by Olson and Ferkul. The U-shape defines the limiting flammability bounds from radiative extinction and flame blow-off. Here, the minimum of the U corresponds to the minimum possible oxidizer concentration where burning can occur, and is an important quantity of interest for fire safety. While high strain extinction bounds have been well analyzed, low strain radiative extinction has not. To estimate low strain extinction, in this study an analytical theory is developed based on thin flame theory coupled with a heat and mass transfer model for solid fuels. A reaction progress variable based on the Damköhler number is adapted in the theory to account for incomplete combustion at high strain rates and enable the capturing of the full flammability map. The analytical model is compared to a one dimensional numerical model w/ detailed chemical kinetics and coupled radiation heat transfer in planar and spherical geometries. The flammability maps are then qualitatively compared to experimental extinguishment data compiled by Olson and Ferkul for cylindrical rods of PMMA showing similar trends. The results show the newly developed analytics capture the radiative extinction bound compared to the numerical model and qualitatively agrees with microgravity data.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Active Site Engineering via Optimizing the Heterogeneous Support Structure for Single-Atom Catalysis

Supported single-atom catalysts show a large range of activities and selectivities that depend on the local environment of the catalytic sites. Here a theory-based optimization strategy is presented that is based on a density functional theory determination of the transition states and intermediates for a low-dimensional coordinate representation of the heterogeneity of the active sites. The approach is applied to a vanadium catalyst on an amorphous SiO 2 support that involves a large kinetic network described using a full chemistry model. Without assuming a priori scaling relations or mechanism reduction, the optimal state of heterogeneity is found to lie at atomic configurations where the activation energies for two distinct key chemical processes are equal. It is found a posteriori that the behavior of the system is consistent with linear free energy scaling relations in the randomness parameters. The energetic span theory proves quite useful in reducing the full chemistry model to a small number of key reactions. The use of a nonlinear optimization algorithm in combination with energetic span theory provides significant simplification in treating disordered systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Use of Laboratory Data to Model Interstellar Chemistry

Our laboratory research program is about the formation of molecules on dust grains analogues in conditions mimicking interstellar medium environments. Using surface science techniques, in the last ten years we have investigated the formation of molecular hydrogen and other molecules on different types of dust grain analogues. We analyzed the results to extract quantitative information on the processes of molecule formation on and ejection from dust grain analogues. The usefulness of these data lies in the fact that these results have been employed by theoreticians in models of the chemical evolution of ISM environments.

Vidali, Gianfranco↗