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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 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Investigating the effect of oxy-fuel combustion and light coal volatiles interaction: A mass spectrometric study

Given the multi-physical nature of coal combustion, the development and validation of detailed chemical models reproducing coal volatiles combustion under oxy-fuel conditions is a crucial step towards the advancement of predictive full-scale simulations. During the devolatilization process, a large variety of gases is released and undergoes secondary pyrolysis and oxidation reactions. Therefore, the ability to capture their interactions is a prerequisite for each chemical model used in its detailed or reduced form to simulate these processes. In this work, a high-resolution time-of-flight molecular-beam mass spectrometer was employed to enable fast and simultaneous detection of stable and unstable species in counterflow flames of typical light volatiles. Following an approach of increasing complexity, carbon dioxide and methane were progressively added to an argon diluted acetylene base flame. For the three flames investigated here, results showed a significant increase in the concentration of C 2 and C 3 hydrocarbons and oxygenated compounds caused by methane addition to the acetylene flame. By hindering the production of the butadienyl radical, the addition of methane induces the reduction of benzene which triggers the decrease of aromatic species. Conversely, CO 2 addition did not have significant effects on intermediates. To guide and interpret the measurements, numerical simulations with two existing chemical models were performed and the results were found to be consistent with the experimental data for small hydrocarbons. Some discrepancies were found between the two model predictions and between simulations and experiments for C 4 and C 5 species. In addition, numerical simulations were found to overestimate the role of the methyl radical in aromatics formation.

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

YAHFC: A Code Framework to Model Nuclear Reactions and Estimate Correlated Uncertainties

Reaction modeling is a key ingredient in designing experiments and interpreting their results, and is an essential component in the process of evaluating nuclear data and assembling nuclear data libraries used in nuclear technology applications. Typically, experimental data are available only for a handful of reaction channels and theory models are used to fill in the gaps. In addition, theory is often called upon as the arbitrator between discrepant data. Most importantly, theory and modeling are required for an accurate determination of uncertainties in the evaluated data and the correlations between the multiple channels. A fast, accurate, and flexible modeling capability has been developed at LLNL with the code system YAHFC (Yet Another Hauser-Feshbach Code). YAHFC is a Monte Carlo, Hauser-Feshbach code framework, making full use of dynamic memory allocation, derived types, and parallel computing. YAHFC can generate events to simulate experiments and is guiding experiments designed to measure inelastic neutron scattering from actinide targets. YAHFC is also being used to analyze decays from surrogate experiments, thereby enabling the inference of reaction cross sections inaccessible by direct measurement. Finally, by modeling nuclear reactions with constraints from experimental data, YAHFC can deliver complete nuclear data libraries, with evaluated uncertainties, using the modernized Generalized Nuclear Data Structure (GNDS).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1991

The use of transition heights for the representation of ion composition

Several characteristic transition heights can be found in ionospheric ion-composition profiles. These are the boundaries between the regions dominated by light ions, atomic oxygen ions, molecular ions, and cluster ions, respectively. Ion-composition modeling can benefit from the use of these transition heights. Special emphasis is given to the 'upper' transition height H sub T (light ions to atomic oxygen) and to the 'lower' transition height h sub t (atomic oxygen to molecular ions). Transition-height models deduced from rocket and satellite measurements are compared with the heights predicted by the International Reference Ionosphere. Considerable discrepancies are found between the different models as well as between the models and independent measurements.

Bilitza, Dieter↗
NASA NTRS1994

A critical evaluation of semianalytic methods in the study of centrally heated, unresolved, infrared sources

We critically evaluate current methods of analysis in infrared (IR) astronomy and investigate the conditions under which these semianalytic methods are reliable. Specifically we examine the usual assumptions of homogeneities in dust density and temperature, and neglect of opacity effects when applied to internally heated, unresolved IR sources. To accomplish this, a series of radiation transport models for these sources have been constructed. The model results are treated as observed quantities and analyzed to derive the source parameters, using simple semianalytic methods. The discrepancies between the derived and actual model parameters can then be attributed to the limitations of the analysis methods and provide a measure of their reliability. Applying this approach to centrally heated, unresolved IR sources, we have studied in detail the following diagnostic problems: (1) determination of dust mass from monochromatic and integrated luminosities; (2) estimation of dust temperature distribution from color temperatures derived from the flux spectrum; and (3) determination of the empirical grain emissivity law (opacity function) for both continuum and spectral features.

Doty, Steven D.↗
DOE OSTI2024

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify, and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles, it is known as a directed acyclic graph. A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts can identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification

The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper presents the Advanced ACC-Micro (AA-Micro) model, a new energy consumption model based on micro trajectory data, calibrated and verified by empirical data. Utilizing a commercial AV equipped with the ACC system as the test platform, experiments were conducted at the Columbus 151 Speedway, capturing data from multiple ACC and Human-Driven (HV) test runs. The calibrated AA-Micro model integrates features from traditional energy consumption models and demonstrates superior goodness of fit, achieving an impressive 90% accuracy in predicting ACC system energy consumption without overfitting. A comprehensive statistical evaluation of the AA-Micro model's applicability and adaptability in predicting energy consumption and vehicle trajectories indicated strong model consistency and reliability for ACC vehicles, evidenced by minimal variance in RMSE values and uniform RSS distributions. Conversely, significant discrepancies were observed when applying the model to HV data, underscoring the necessity for specialized models to accurately predict energy consumption for HV and ACC systems, potentially due to their distinct energy consumption characteristics.

Ma, Ke↗
NASA NTRS1990

Boundary layer roll circulations during FIRE

The probable mechanism underlying the development of boundary layer roll circulations are studied using wind and temperature profiles measured by the National Center for Atmospheric Research (NCAR) Electra during the stratocumulus phase of the First ISCCP Regional Experiment (FIRE). The expected, or preferred, roll orientations, horizontal wavelengths, and propagation periods are determined by finding the minimum values of the dynamic and thermodynamic forcing parameters, which here are the eddy Reynolds number (Re) and moist Rayleigh number (Ra sub m). These minimum values depend on the height z sub T of the capping temperature inversion and on the values of the Fourier coefficients of the background height-dependent vector wind profile. As input to our nonlinear spectral model, descent and ascent runs by the Electra provide for initial estimates of the inversion height and the wind profiles. In the first phase of the investigation presented here, a mechanism is said to be a probable contributor to the development of roll circulations within the stratocumulus-topped boundary layer if the modeled roll orientation and wavelengths agree with their observed values. Preliminary results using the 14-coefficient model of Haack-Hirschberg (1988) are discussed for the 7 July 1987 Electra Mission 188-A (Flight 5). This mission was flown across a sharp cloud boundary that was within a LANDSAT/SPOT scene. The stratocumulus deck was relatively solid in the eastern part of the scene, while there was a rapid decrease in cloud cover to scattered cumulus clouds aligned in streets to the west. These cloud streets were oriented nearly parallel to the mean wind direction in the layer, which was approximately 340 degrees. The hypothesis that roll circulations occurred in both the relatively clear and the cloudy regions is investigated using as model input a descent profile obtained in the relatively clear air and an ascent profile obtained in the cloudy air. Initial results for the clear air case are that the pure inflection point mode is not possible and the pure thermal mode was oriented 35 degrees to the right of the mean wind direction. The origin of this unacceptably large discrepancy between the observed and modeled results will be investigated further and the conclusions reported at the next FIRE workshop.

Shirer, Hampton N.↗
NASA NTRS2015

Numerical Modeling of the Transient Chilldown Process of a Cryogenic Propellant Transfer Line

Before cryogenic fuel depots can be fully realized, efficient methods with which to chill down the spacecraft transfer line and receiver tank are required. This paper presents numerical modeling of the chilldown of a liquid hydrogen tank-to-tank propellant transfer line using the Generalized Fluid System Simulation Program (GFSSP). To compare with data from recently concluded turbulent LH2 chill down experiments, seven different cases were run across a range of inlet liquid temperatures and mass flow rates. Both trickle and pulse chill down methods were simulated. The GFSSP model qualitatively matches external skin mounted temperature readings, but large differences are shown between measured and predicted internal stream temperatures. Discrepancies are attributed to the simplified model correlation used to compute two-phase flow boiling heat transfer. Flow visualization from testing shows that the initial bottoming out of skin mounted sensors corresponds to annular flow, but that considerable time is required for the stream sensor to achieve steady state as the system moves through annular, churn, and bubbly flow. The GFSSP model does adequately well in tracking trends in the data but further work is needed to refine the two-phase flow modeling to better match observed test data.

Chilldown↗
NASA NTRSDate not supplied

Validation Experiments for Turbulent Separation over an Axisymmetric Body of Revolution

Historically, the flow physics involved with most turbulent separated flows have presented fundamental challenges to validating numerical approaches. As recognized by the CFD Vision 2030 study commissioned by NASA, validation of Reynolds-averaged Navier-Stokes (RANS) models and other scale-resolving methods for turbulent separated flow requires data from advanced, high-fidelity experiments designed specifically for CFD implementation. In accordance with this effort, a new test platform, referred to as the NASA Axisymmetric Afterbody, was designed to obtain detailed measurements of the flow field undergoing a smooth, adverse pressure gradient induced separation for a fixed Reynolds number, Re = 180,000. The parametric body offers a range of flow states progressing from fully attached, to incipient separation, and finally to small-scale separated flow based on variable afterbody geometries. In an initial effort to evaluate RANS turbulence model capabilities, the present configurations of the axisymmetric model host a mild adverse pressure gradient over the contoured boattail section, inducing incipient turbulent separation, as well as a slightly larger adverse pressure gradient, inducing a small-scale region of turbulent separation. Experiments include steady pressure measurements and 2-D PIV to provide the preliminary dataset for simulation studies, which examine the effect of variable grid domains and RANS turbulence models. This is done in an effort to understand and evaluate the critical variability between solutions for the present model configurations. Results indicate potential discrepancies may be due to the effect of the square tunnel test section walls, relatively large blockage ratio, and slight variability in reference parameters. Ongoing work will focus on higher fidelity experimental campaigns to obtain surface flow visualizations and Stereo-Particle Image Velocimetry (SPIV) to deliver higher spatial resolution of the three-dimensional flow field to aid turbulence modelers.

Validation↗
DOE OSTI2019

Modeling the Altitude Distribution of Meteor Head Echoes Observed with HPLA Radars: Implications for the Radar Detectability of Meteoroid Populations

The altitude distribution of meteors detected by a radar is sensitive to the instrument’s response function and can thus provide insight into the physical processes involved in radar measurements. This, in turn, can be used to determine the rate of ablation and ionization of the meteoroids and ultimately the input flux on Earth. In this work, we model the radar meteor head echo altitude distribution for three High Power and Large Aperture radar systems, by considering meteoroid populations from the main cometary family sources. In this simulation, we first use the results of a dynamical model of small meteoroids impacting Earth’s upper atmosphere to model the incoming mass, velocity, and entry angular distributions. We then combine these with the Chemical Ablation Model and establish the meteoroid ionization rates as a function of mass, velocity, and entry angle in order to determine the altitude at which these radars should detect the produced meteors and the portion of produced meteors from each population that are detected by these radars. We explore different sizes of head plasma as well as the possible effects on radar scattering of the head echo aspect sensitivity. We find that the modeled altitude distributions are generally in good agreement with measurements, particularly for ultra-high-frequency radars. In addition, our results indicate that the number of particles from Jupiter Family Comets (JFCs) required to fit the observations is lower than predicted by astronomical models. It is not clear yet if this discrepancy is due to the overprediction of JFC meteoroids by dynamical models or due to unaccounted physical processes in the treatment of ablation, ionization, and detections of meteoroids as they pass through Earth’s atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2009

Modeling of the 22 July 2009 Storm

The magnetic storm on 22 July 2009 is the greatest storm observed since the summer of 2008 when TWINS began its stereo imaging of the magnetosphere, On 22 July 2009, the Dst dropped to nearly -80 nT at 07:00 and 10:00 UT. During the main phase and at the peak of the storm, TWINS 1 and 2 were near apogee and moving from pre-dawn to post-dawn local time. The energetic neutral atom (ENA) Imagers on the 2 spacecraft captured the storm intensification and the formation of the partial ring current. The development of this storm has been simulated using the Comprehensive Ring Current Model (CRCM) to understand and interpret the observed signatures. The CRCM reproduced the double-dip in the Dst index and the simulated ENA flux intensities agree very well with the TWINS images. However, the peak of ion flux predicted by the model is always eastward of the observed maximum by TWINS. This discrepancy posts a challenge to reexamine the physical models employed in the CRCM.

Fok, Mei-Ching↗
DOE OSTI2025

Permafrost, Peatland, and Cropland Regions Are Key to Reconciling North American Carbon Sink Estimates

Persistent discrepancies between bottom-up, terrestrial biosphere models (TBMs), and top-down, atmospheric inversions, have made it difficult to quantify the magnitude of the North American terrestrial carbon sink. Previous studies have compared aggregated continent-scale estimates of carbon fluxes from TBMs and inversions for all of North America, but this provides limited insights into finer-scale mismatches that contribute to the overall discrepancies. Here we evaluate agreement between TBM and inversion carbon flux estimates at 1° × 1° resolution to provide more direct insights into where models disagree and what underlying factors drive discrepancies. We find that the additional carbon uptake estimated by inversions, in just 16% of the area of North America, is large enough to account for the discrepancy between TBMs and inversions across the whole continent. The majority of these differences occur in permafrost, peatland, and cropland regions. In these regions, we find a higher likelihood of potential biases in the weaker sink estimates from TBMs, suggesting that the stronger sink implied by inversions is more likely to be realistic. However, the current observational coverage is insufficient for fully assessing the causes of discrepancies or the magnitude of biases in either approach. Encouragingly, improved representation of agricultural processes in a TBM led to better agreement with inversions in croplands. Efforts to accurately model cropland dynamics will help improve agreement between TBMs and inversions. Overall, this work presents a clear path for reconciling the discrepancies between inversion and TBM estimates of the North American carbon sink that have persisted for two decades.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Lagrangian displacement field estimators in cosmology

The late-time nonlinear Lagrangian displacement field is highly correlated with the initial field, so reconstructing it could enable us to extract primordial cosmological information. Our previous work carefully studied the displacement field reconstructed from the late-time density field using the iterative method proposed and found that it does not fully converge to the true, underlying displacement field (e.g., ~8 % offset at k ~ 0.2 h Mpc –1 at z = 0.6 ). We also constructed the Lagrangian perturbation theory model for the reconstructed field, but the model could not explain the discrepancy between the true and the reconstructed fields in the previous work. Here, the main sources of the discrepancy were speculated to be a numerical artifact in the displacement estimator due to the discreteness of the sample. In this paper, we develop two new estimators of the displacement fields to reduce such a numerical discreteness effect, the normalized momentum estimator and the rescaled resumed estimator. We show that the discrepancy reported is not due to the numerical artifacts. We conclude that the method cannot fully reconstruct the shape of the nonlinear displacement field at the redshift we studied, while it is still an efficient baryon acoustic oscillation reconstruction method. In parallel, by properly accounting for the UV-sensitive term in a reconstruction procedure with an effective field theory approach, we improve the theoretical model for the reconstructed displacement field, by almost 5 times, from ~15% to the level of a few percent at k ~ 0.2 h Mpc –1 at the redshift z = 0.6.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Validating compositional fluid flow simulations using 4D seismic interpretation and vice versa in the SECARB Early Test—A critical review

We report on strengths and weaknesses of 4D seismic interpretation as a technique for monitoring carbon dioxide that was injected as part of a large scale test associated with commercial enhanced oil recovery (EOR) at Cranfield Field, Mississippi, USA. The goals of the monitoring effort are 1) to make measurements to verify that the CO 2 is contained in the reservoir according to operational designs and model predictions, and 2) that if there are deviations, to provide data which can be used to update the earth models and determine if any mitigation is needed. Our work uses a compositional numerical simulation to model CO 2 flow in the reservoir and compares the results with estimates of changes in seismic properties between a pre-injection and a survey after more than 2 million metric tons injected. The complicated physics of the problem in Cranfield field present challenges to seismic interpretations. These findings reflect partial agreement between the results of the numerical simulation and the seismic interpretations. Possible causes of discrepancies among the fluid flow model and multiple interpretations of the same seismic data sets performed with different work flows illuminates the types of uncertainties that should be considered to achieve the goals of monitoring.

4D seismic↗
DOE OSTI2023

Discrete element simulation of Pebble Bed Reactors on graphics processing units

Prediction of pebble positions in a Pebble Bed Reactor (PBR) is necessary for both reactor physics and thermal hydraulics simulations as the arrangement of pebbles has a significant impact on the resulting core power, coolant flow, and fuel temperature. Knowledge of pebble movement as the fuel is cycled through the core is also critical for predicting the fuel residence time and subsequently, the fuel burnup. Simulation with the Discrete Element Method (DEM) can provide knowledge of both the fuel packing and the fuel movement during cycling. Previous works that have performed 3D full-core DEM simulation of PBRs have used simplified models that neglect reflector wall features. This work employs a graphics processing unit (GPU)-enabled DEM code, Project Chrono, to analyze the differences in pebble packing and pebble velocities between a simplified smooth PBR reflector and a more realistic reflector that includes circular wall features. Additionally, a sensitivity study is performed on the depth of the wall features to ensure that crystallization is prevented. Project Chrono is also validated for PBR cycling applications using experimental data. It is found that wall features with a depth of at least 0.5 pebble diameters significantly reduce crystallization in the near-wall region, leading to discrepancies in both packing fraction and pebble velocity in this region compared to the simplified reflector models. These discrepancies are found to lead to roughly a 5–10% difference in the prediction of the near-wall porosity and a 10% difference in the prediction of the velocity of pebbles near the wall. As a result of these discrepancies, it is suggested that future DEM simulations of PBRs include wall features to reduce modeling errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1978

Quantitative calculations of helium ion escape fluxes from the polar ionospheres

An attempt is made to reduce the discrepancy between the earlier theoretical model and the recent experimental observations of H(+) outward fluxes for winter and summer hemispheres by improving the theoretical model. The helium photoionization cross sections used are accurate to 10%, the latest solar EUV fluxes measured by the Atmosphere Explorer satellites are incorporated, and the most recent MSIS model of the neutral atmosphere is contained in the model. A range of conditions covering solar cycle, seasonal, and geomagnetic conditions are studied. The results show a maximum H(+) escape flux of 1.4 times 10 to the 7th per sq cm per sec for solar maximum, winter, low magnetic activity conditions, which is within the scatter of the measured fluxes. The computed summer H(+) escape flux is a factor of 20 lower than the winter value. Possible reasons for the slight discrepancy between theory and experiment in summer are discussed.

Raitt, W. J.↗
DOE OSTI2023

Domain Adaptive Graph Neural Networks for Constraining Cosmological Parameters Across Multiple Data Sets

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross-dataset tasks. Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗