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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
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Pressure Effects on the Relaxation of an Excited Ethane Molecule in High-Pressure Bath Gases

Here, we use molecular dynamics to calculate the rotational and vibrational energy relaxation of C 2 H 6 in Ar, Kr, and Xe bath gases over a pressure range of 10 to 400 atm and at temperatures of 300 K and 800 K. The C 2 H 6 is instantaneously excited by 80 kcal/mol randomly distributed into both vibrational and rotational modes. The computed relaxation rates show little sensitivity to the identity of the noble gas in the bath. Vibrational relaxation rates show a non-linear pressure dependence at 300 K. At 800 K the reduced range of bath gas densities covered by the range of pressures do not yet show any non-linearity in the pressure dependence. Rotational relaxation is characterized with two relaxation rates. The slower rate is comparable to the vibrational relaxation rate. The faster rate has a linear pressure dependence at 300 K but an irregular, nonlinear pressure dependence at 800 K. To understand this, a model was developed based on approximating the periodic box used in the molecular dynamics simulations by an equal-volume collection of cubes where each cube is sized to allow only single occupancy by the noble gas or the molecule. Combinatorial statistics then leads to a pressure and temperature dependent analytic distribution of the bath gas species the molecule encounters in a collision. This distribution, the dissociation energy of molecule/bath gas complexes and bath gas clusters, and the computed energy release per collision combine to show that only at 300 K is the energy release sufficient to dissociate likely complexes and clusters. This suggests that persistent and pressure-dependent clusters and complexes at 800 K may be responsible for the non-linear pressure dependence of rotational relaxation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Observation and rationalization of nitrogen oxidation enabled only by coupled plasma and catalyst

Abstract Heterogeneous catalysts coupled with non-thermal plasmas (NTP) are known to achieve reaction yields that exceed the contributions of the individual components. Rationalization of the enhancing potential of catalysts, however, remains challenging because the background contributions from NTP or catalysts are often non-negligible. Here, we first demonstrate platinum (Pt)-catalyzed nitrogen (N 2 ) oxidation in a radio frequency plasma afterglow at conditions at which neither catalyst nor plasma alone produces significant concentrations of nitric oxide (NO). We then develop reactor models based on reduced NTP- and surface-microkinetic mechanisms to identify the features of each that lead to the synergy between NTP and Pt. At experimental conditions, NTP and thermal catalytic NO production are suppressed by radical reactions and high N 2 dissociation barrier, respectively. Pt catalyzes NTP-generated radicals and vibrationally excited molecules to produce NO. The model construction further illustrates that the optimization of productivity and energy efficiency involves tuning of plasma species, catalysts properties, and the reactor configurations to couple plasma and catalysts. These results provide unambiguous evidence of synergism between plasma and catalyst, the origins of that synergy for N 2 oxidation, and a modeling approach to guide material selection and system optimization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Investigation of carbon incorporation in laser-assisted MOCVD of GaN

Background carbon (C) impurity incorporation in metalorganic chemical vapor deposition (MOCVD) grown gallium nitride (GaN) represents one of the major issues in further improving GaN vertical power device performance. This work presents a laser-assisted MOCVD (LA-MOCVD) technique to address the high-C issue in MOCVD homoepitaxial GaN under different growth rate (Rg) regimes and studies the correlations between [C] and Rg. [C] in LA-MOCVD GaN is reduced by 50%–90% as compared to the conventional MOCVD GaN for a wide growth rate range between 1 and 16 μm/h. A mass-transport based model is developed to understand the C incorporation at different Rg regimes. The results obtained from the developed model are in good agreement with experimental data. The model further reveals that LA-MOCVD effectively suppresses C incorporation by reducing the active C species in the gas phase. Moreover, high step velocity in step flow growth mode can facilitate C incorporation at fast Rg, exhibiting steeper C increase. The theoretical model indicates that [C] can be suppressed below 1016 cm−3 with a fast growth rate (Rg) of 10 μm/h by utilizing higher power LA-MOCVD and freestanding GaN substrates with larger off-cut angles.

Physics↗
DOE OSTI2020

Modeling Water Electrolysis in Bipolar Membranes

Bipolar membranes (BPMs) have proven useful in numerous electrochemical energy conversion and storage applications, including fuel cells and electrolyzers. However, water dissociation in bipolar membrane electrolysis cells (BPMECs) is a complicated phenomenon that occurs via several different pathways. In this work, we develop a model based on the Poisson-Nernst-Planck system that includes a multistep water-dissociation mechanism to observe the fundamental processes that contribute to BPMEC performance. The model, which is validated to in-house experimental data, demonstrates that the junction potential is the most significant contributor to the total electrolysis voltage. We investigated the effects of water-dissociation catalysts and found that the optimal catalyst $p{K}_{a}$ depends on how the catalyst is integrated into the BPM (although values near 7 are typically best, in accordance with conventional wisdom). We also simulated the water content across the BPM and found that dry-out is not a significant issue when the membrane is in contact with liquid water on both sides. The species conservation approach taken here leads to a physical understanding of the system without using any fitting parameters.

25 ENERGY STORAGE↗
DOE OSTI2019

Modeling Coupled Durability and Performance in Polymer-Electrolyte Fuel Cells: Membrane Effects

During operation, proton-exchange-membrane fuel cells (PEMFCs) are subjected to mechanical and chemical stressors that contribute to membrane degradation, performance loss, and eventual failure. Together, synergistic effects between mechanical and chemical degradation mechanisms lead to accelerated degradation. A physics-based model is developed to understand the synergistic effects of chemical and mechanical degradation and the coupled nature of performance and durability in PEMFCs. The model includes pinhole existence and growth in the membrane, which increases crossover of reactant gases as well as subsequent formation of chemical degradation agents that impact both transport and mechanical properties of the membrane. The fuel-cell model is fully coupled with a mechanical model to determine the stresses on the membrane and subsequent growth of pinholes during transient operation. Simulation results demonstrate pinhole growth under relative-humidity cycling and the resultant increased gas-crossover fluxes and decrease in polarization performance. Furthermore, the model results highlight nonlinearities and the importance of coupling mechanical and chemical degradation models in order to explain membrane degradation under various cycles, and serves as a foundation for examining coupled durability and performance.

25 ENERGY STORAGE↗
DOE OSTI2022

Planning decentralized urban renewable energy systems using algal cultivation for closed-loop and resilient communities

To tackle climate challenges, communities need to harvest renewable energy and resources on site locally to close the loops for enhancing the resilience of communities facing unpredictable and uncertain future changes. A decentralization planning of urban renewable energy systems is proposed by treating urban waste streams and producing biomass through applying algal biotechnology. When applying algal technology as a renewable and decentralized energy source in urban systems, the overall performance can vary by levels of urban nutrients, solar and CO 2 resources, and the transportation cost when considering its application to different urban densities, urban form, and the spatial scale of urban settings. This research explores three potential impacts on the algal system’s energy performance: (1) urban density, (2) urban form in different contexts, and (3) spatial scale. The research examines the impacts by testing urban settings given in actual contexts in Atlanta, Georgia, USA. Four neighborhoods representing the high-density urban, mid-density urban, mixed suburban, and typical suburban areas are investigated. The density-scale–performance relationships are explored through testing different urban forms of neighborhoods in both hypothetical and actual neighborhood settings. A GIS-based model is developed to estimate the overall energy performance of the decentralized renewable energy system in urban environments. Results show that the energy performance is positive mainly for high-density urban neighborhoods with small-to-medium scales, up to 0.36 MJ per ton of municipal solid wastes for actual settings and 0.37 MJ for hypothetical cases. Neighborhoods with higher density have higher energy performance while up scaling has negative effects on the energy performance with a low degree of significance. Optimal scales are found as a 1-km radius in real test beds and 1.3 km in hypothetical settings, in which the results show trade-offs between scaling effects in the system efficiency gain and the transportation cost increase.

Quan, Steven Jige↗
DOE OSTI2021

Light transport with weak angular dependence in fog

Random scattering and absorption of light by tiny particles in aerosols, like fog, reduce situational awareness and cause unacceptable down-time for critical systems or operations. Computationally efficient light transport models are desired for computational imaging to improve remote sensing capabilities in degraded optical environments. To this end, we have developed a model based on a weak angular dependence approximation to the Boltzmann or radiative transfer equation that appears to be applicable in both the moderate and highly scattering regimes, thereby covering the applicability domain of both the small angle and diffusion approximations. An analytic solution was derived and validated using experimental data acquired at the Sandia National Laboratory Fog Chamber facility. The evolution of the fog particle density and size distribution were measured and used to determine macroscopic absorption and scattering properties using Mie theory. A three-band (0.532, 1.55, and 9.68 µ m) transmissometer with lock-in amplifiers enabled changes in fog density of over an order of magnitude to be measured due to the increased transmission at higher wavelengths, covering both the moderate and highly scattering regimes. The meteorological optical range parameter is shown to be about 0.6 times the transport mean free path length, suggesting an improved physical interpretation of this parameter.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

A DYNAMIC ENERGY MODEL FOR DISPLAY CASES CONSIDERING FAULTS IN SUPERMARKETS FOR LOW GWP REFRIGERANTION

Display cases are widely used in supermarkets to demonstrate commercial goods for customers, like milk, frozen food, ice-cream, etc. There are two types of display case: open case and closed case. The goods inside display cases need to stay within a stable temperature range to meet the quality standards. However, due to variety of faults (e.g., leaving door opening), it is hard to maintain a stable temperature. The associated energy consumption from display cases is extremely high due to faults. There is a need for a dynamic energy model to accurately predict the good temperature and energy consumption under faults. A dynamic model is developed based on operation data collected through field tests in a low global warming potential (GWP) refrigeration system, at Oak Ridge National Laboratory.

Li, Yanfei↗
DOE OSTI2018

Thermochemical and transport properties important to molten salt reactor operation: Off-gas performance and the fission product mechanistic source term

The source term used in reactor performance and safety analysis requires understanding the chemical speciation and transport behavior of fission and activation products in the primary heat transport system (PHTS) and containment. As a starting condition, the transport models will use the isotopic compositions determined through ORIGEN (Bell 1973) calculations and thermochemistry that describes the speciation of the fuel, the salt, activation products and fission products. However, as changes in phase will be under non-equilibrium conditions, the source terms will also need models for the transport behavior of key compounds in the PHTS under various scenarios: normal operation with and without an off-gas system, maintenance, off-normal events, and severe reactor accidents. This document highlights those mechanistic behaviors for which models are needed. Simulations of reactor behavior require these models to be developed for molten salt reactors (MSRs), especially if not part of the suite used in describing LWR behavior. The document concludes with recommendations how to develop these models based on what is already known about reactor safety and fission product behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

The objective of this project is to improve the prediction of engine knock by developing a new combustion modeling framework. Engine knock is a limiting factor to constrain the increase of fuel efficiency for spark ignition (SI) engines in most passenger cars. Efforts to increase fuel efficiency, increasing the compression ratio or downsizing, lead to the increase in the tendency of the knock occurrence. The knock is an undesired ignition of the end-gas, unburned fuel/air mixture ahead of the spark-ignited premixed flame, resulting in rapid in-cylinder pressure rises and engine damages. The combustion modeling framework developed in this project can consider turbulence-chemistry interactions during end-gas ignition, while using a reasonably detailed chemical mechanism developed for ignition and combustion reactions under engine relevant conditions, and the subtle characteristics of spark-ignited flame propagation. It is developed in the context of large eddy simulation (LES), which can capture stochastic in-cylinder processes. The developed model is incorporated into a commercial software for engine simulation, CONVERGE CFD, as a user defined function, and validated. Engine knock and knock-free experiments as well as direct numerical simulation (DNS) of end-gas ignition in homogeneous turbulence are performed to help model development and provide data sets for model validation. With further validation, the developed model is expected to advance the predictive capability for engine knock simulations and thus contribute to improving the fuel efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

CO2 hydrate crystal thickening, morphology, and Raman spectroscopy in a microfluidic device

Gas hydrates are a solid, crystalline form of water that often form at low temperatures and high pressures. Carbon dioxide (CO2) hydrates may form during carbon dioxide capture and storage (CCS) processes. These solid compounds may form in CO2 pipelines, potentially leading to a full blockage and process shutdown for plug removal. On the other hand, formation of CO2 hydrates may be desired for CO2 capture and separation. In either case, understanding the growth behavior and nature of the hydrates is vital to managing these CCS processes. Using a high-pressure, transparent microfluidic reactor, the crystalline film thickening of CO2 hydrates was observed and measured through visual microscopy and Raman spectroscopy. The impact of subcooling, pressure, and CO2 flow rate was investigated, and only CO2 flow rate was found to have a significant impact on the overall thickness of the film. Visual observations and Raman spectroscopy measurements confirmed that two distinct hydrate layers formed during thickening, one which was more porous than the other. The capillary-like channels in the porous layer indicated a mechanism for mass transfer of water through the hydrate layer. A model was developed based on this observation, and it was fit to the thickening data in order to obtain mass transfer coefficients. Results of this study can be applied to CO2 hydrate formation in pipelines and near porous media used for CO2 capture.

Wadsworth, Lindsey [Colorado School of Mines, Gold↗
DOE OSTI2022

Scalable deep learning for watershed model calibration

Watershed models such as the Soil and Water Assessment Tool (SWAT) consist of high-dimensional physical and empirical parameters. These parameters often need to be estimated/calibrated through inverse modeling to produce reliable predictions on hydrological fluxes and states. Existing parameter estimation methods can be time consuming, inefficient, and computationally expensive for high-dimensional problems. In this paper, we present an accurate and robust method to calibrate the SWAT model (i.e., 20 parameters) using scalable deep learning (DL). We developed inverse models based on convolutional neural networks (CNN) to assimilate observed streamflow data and estimate the SWAT model parameters. Scalable hyperparameter tuning is performed using high-performance computing resources to identify the top 50 optimal neural network architectures. We used ensemble SWAT simulations to train, validate, and test the CNN models. We estimated the parameters of the SWAT model using observed streamflow data and assessed the impact of measurement errors on SWAT model calibration. We tested and validated the proposed scalable DL methodology on the American River Watershed, located in the Pacific Northwest-based Yakima River basin. Our results show that the CNN-based calibration is better than two popular parameter estimation methods (i.e., the generalized likelihood uncertainty estimation [GLUE] and the dynamically dimensioned search [DDS], which is a global optimization algorithm). For the set of parameters that are sensitive to the observations, our proposed method yields narrower ranges than the GLUE method but broader ranges than values produced using the DDS method within the sampling range even under high relative observational errors. The SWAT model calibration performance using the CNNs, GLUE, and DDS methods are compared using R 2 and a set of efficiency metrics, including Nash-Sutcliffe, logarithmic Nash-Sutcliffe, Kling-Gupta, modified Kling-Gupta, and non-parametric Kling-Gupta scores, computed on the observed and simulated watershed responses. The best CNN-based calibrated set has scores of 0.71, 0.75, 0.85, 0.85, 0.86, and 0.91. The best DDS-based calibrated set has scores of 0.62, 0.69, 0.8, 0.77, 0.79, and 0.82. The best GLUE-based calibrated set has scores of 0.56, 0.58, 0.71, 0.7, 0.71, and 0.8. The scores above show that the CNN-based calibration leads to more accurate low and high streamflow predictions than the GLUE and DDS sets. Our research demonstrates that the proposed method has high potential to improve our current practice in calibrating large-scale integrated hydrologic models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Properties of Hot Nuclear Matter

A fully quantitative description of the equilibrium and dynamical properties of hot nuclear matter will be needed for the interpretation of the available and forthcoming astrophysical data, providing information on the post-merger phase of a neutron star coalescence. We discuss the results of a recently developed theoretical model, based on a phenomenological nuclear Hamiltonian including two- and three-nucleon potentials, to study the temperature dependence of average and single-particle properties of nuclear matter relevant to astrophysical applications. The potential of the proposed approach for describing dissipative processes leading to the appearance of bulk viscosity in neutron star matter is also outlined.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Development of a Physics-Based Combustion Model for Engine Knock Prediction

The objective of this project is to improve the prediction of engine knock by developing a new combustion modeling framework. Engine knock is a limiting factor to constrain the increase of fuel efficiency for spark ignition (SI) engines in most passenger cars. Efforts to increase fuel efficiency, increasing the compression ratio or downsizing, lead to the increase in the tendency of the knock occurrence. The knock is an undesired ignition of the end-gas, unburned fuel/air mixture ahead of the spark-ignited premixed flame, resulting in rapid in-cylinder pressure rises and engine damages. The combustion modeling framework developed in this project can consider turbulence-chemistry interactions during end-gas ignition, while using a reasonably detailed chemical mechanism developed for ignition and combustion reactions under engine relevant conditions, and the subtle characteristics of spark-ignited flame propagation. It is developed in the context of large eddy simulation (LES), which can capture stochastic in-cylinder processes. The developed model is incorporated into a commercial software for engine simulation, CONVERGE CFD, as a user defined function, and validated. Engine knock and knock-free experiments as well as direct numerical simulation (DNS) of end-gas ignition in homogeneous turbulence are performed to help model development and provide data sets for model validation. With further validation, the developed model is expected to advance the predictive capability for engine knock simulations and thus contribute to improving the fuel efficiency.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Ab Initio Study of Atomic and Electronic Structure of Promising Ba4XMn3O12 (X = Nb, Ce, Pr) Oxides for Solar Thermochemical Hydrogen Production

The two-step metal oxide water-splitting cycle is one of the most viable approach for Solar Thermochemical Hydrogen (STCH) production. Challenges exist in finding suitable oxides that can satisfy thermodynamics of the STCH redox cycle under viable range of temperatures and partial pressures. Recently, BXM family members, i.e., Ba4NbMn3O12 (BNM), Ba4CeMn3O12 (BCM), Ba4PrMn3O12 (BPM) are discovered to exhibit promising STCH performance. However, the magnetic degrees of freedom of their experimental crystal structures is not characterized, and only hypothetical models exist for their electronic structure. We performed Monte-Carlo sampling for the magnetic spin arrangement of Mn atoms to provide explicit atomic structure models for their ground state 12R polytype and determined the most stable spin configuration for each member after structure relaxation using density functional theory (DFT) calculations. We also elucidate the most stable charge configuration (Mn3+/Mn4+ arrangement) for BNM among the existing hypothesis in literature. We investigate these strongly correlated oxides using different levels of theory (DFT+U, Hybrid-DFT) to develop better understanding of their electronic structure. These calculations allowed us to develop a model based on molecular orbital interactions that help explain the observed changes in their experimental x-ray spectroscopy measurements. Thereby, help link differences in electronic structure of BXM family members to their varying water-splitting behavior. These structure models will further facilitate future in-depth defect studies to model STCH redox cycle of these oxides.

atomic and magnetic structure↗
DOE OSTI2023

Energy Model of an Air Source Heat Pump to Explore Performance Improvements under Cold Conditions: A Python Framework: Preprint

Replacing combustion appliances with heat pumps can be part of a strategy to electrify buildings. When their electricity is supplied by renewables, the adoption of heat pumps for space heating may help curb the carbon dioxide emissions inherent to traditional heating systems that burn natural gas or coal. When operating in very cold climates, however, heat pump performance deteriorates, sometimes requiring backup heating supplied by electric resistances or other sources to continue to function. To avoid the use of electric resistances, complementary technologies, like thermal energy storage, solar collectors, or alternative refrigerants, have been explored in recent years. In this study, we present an open-source Python-based numerical model developed to evaluate the annual hourly performance of an air source heat pump (ASHP) operating in the USA. Simulation results include coefficient of performance and heating capacity. The model, validated with experimental results, will be employed in the future to investigate the feasibility of integrating thermal energy storage and other technologies into ASHPs operating in cold climates.

cold climate↗