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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Global Mass Flux Solutions from GRACE: A Comparison of Parameter Estimation Strategies - Mass Concentrations Versus Stokes Coefficients

The differences between mass concentration (mas con) parameters and standard Stokes coefficient parameters in the recovery of gravity infonnation from gravity recovery and climate experiment (GRACE) intersatellite K-band range rate data are investigated. First, mascons are decomposed into their Stokes coefficient representations to gauge the range of solutions available using each of the two types of parameters. Next, a direct comparison is made between two time series of unconstrained gravity solutions, one based on a set of global equal area mascon parameters (equivalent to 4deg x 4deg at the equator), and the other based on standard Stokes coefficients with each time series using the same fundamental processing of the GRACE tracking data. It is shown that in unconstrained solutions, the type of gravity parameter being estimated does not qualitatively affect the estimated gravity field. It is also shown that many of the differences in mass flux derivations from GRACE gravity solutions arise from the type of smoothing being used and that the type of smoothing that can be embedded in mas con solutions has distinct advantages over postsolution smoothing. Finally, a 1 year time series based on global 2deg equal area mascons estimated every 10 days is presented.

Rowlands, D. D.↗
DOE OSTI2023

Optimization under uncertainty of a hybrid waste tire and natural gas feedstock flexible polygeneration system using a decomposition algorithm

Market uncertainties motivate the development of flexible polygeneration systems that are able to adjust operating conditions to favor production of the most profitable product portfolio. However, this operational flexibility comes at the cost of higher capital expenditure. A scenario-based two-stage stochastic nonconvex Mixed-Integer Nonlinear Programming (MINLP) approach lends itself naturally to optimizing these trade-offs. This work studies the optimal design and operation under uncertainty of a hybrid feedstock flexible polygeneration system producing electricity, methanol, dimethyl ether, olefins or liquefied (synthetic) natural gas. A recently developed C++ based software framework (named GOSSIP) is used for modeling the optimization problem as well as its efficient solution using the Nonconvex Generalized Benders Decomposition (NGBD) algorithm. Two different cases are studied: The first uses estimates of the means and variances of the uncertain parameters from historical data, whereas the second assesses the impact of increased uncertain parameter volatility. The value of implementing flexible designs characterized by the value of the stochastic solution (VSS) is in the range of 260–405 M$ for a scale of approximately 893 MW of thermal input. Increased price volatility around the same mean results in higher expected net present value and VSS as operational flexibility allows for asymmetric exploitation of price peaks.

42 ENGINEERING↗
DOE OSTI2025

Automatic Generation of Chemical Mechanisms for Electrochemical Systems: Solid Electrolyte Interphase Formation in Lithium Batteries

Electrolytes in many lithium ion batteries decompose at the low potentials near the anode. The decomposition products form a layer termed the solid electrolyte interphase (SEI). The composition and growth of the SEI layer significantly affect both the capacity fade and safety of lithium ion batteries. However, SEI formation and growth kinetics are not well understood. In this work, we present an extension of the Reaction Mechanism Generator (RMG) software to automatically generate mechanisms for SEI formation. We extend RMG’s solvation correction framework to account for kinetic solvent effects and demonstrate the accuracy of our technique. We calculate thermochemical parameters for 252 species and rate coefficients for 69 reactions, most with associated solvation corrections. This and additional quantum chemistry data are used to extend RMG’s thermodynamic group additivity and solute parameter estimation schemes to handle lithiated species and add 14 new reaction families to RMG. RMG is additionally extended to simulate electrocatalytic systems. Lastly, we demonstrate RMG on the decomposition of acetonitrile and ethylene carbonate near a battery anode. Furthermore, while this framework does not yet resolve individual ions, as appropriate thermochemistry estimators are not available, and thus, cannot yet resolve more complex electrochemical pathways, RMG is able to generate reasonable pathways for SEI formation that match literature pathways and products. In particular, RMG identifies a new important reaction pathway that is not present in literature.

Chemical reactions↗
DOE OSTI2023

Quantification of early nonpharmaceutical interventions aimed at slowing transmission of Coronavirus Disease 2019 in the Navajo Nation and surrounding states (Arizona, Colorado, New Mexico, and Utah)

During an early period of the Coronavirus Disease 2019 (COVID-19) pandemic, the Navajo Nation, much like New York City, experienced a relatively high rate of disease transmission. Yet, between January and October 2020, it experienced only a single period of growth in new COVID-19 cases, which ended when cases peaked in May 2020. The daily number of new cases slowly decayed in the summer of 2020 until late September 2020. In contrast, the surrounding states of Arizona, Colorado, New Mexico, and Utah all experienced at least two periods of growth in the same time frame, with second surges beginning in late May to early June. Here, we investigated these differences in disease transmission dynamics with the objective of quantifying the contributions of non-pharmaceutical interventions (NPIs) (e.g., behaviors that limit disease transmission). We considered a compartmental model accounting for distinct periods of NPIs to analyze the epidemic in each of the five regions. We used Bayesian inference to estimate region-specific model parameters from regional surveillance data (daily reports of new COVID-19 cases) and to quantify uncertainty in parameter estimates and model predictions. Our results suggest that NPIs in the Navajo Nation were sustained over the period of interest, whereas in the surrounding states, NPIs were relaxed, which allowed for subsequent surges in cases. Our region-specific model parameterizations allow us to quantify the impacts of NPIs on disease incidence in the regions of interest.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Fast and Flexible Inference Framework for Continuum Reverberation Mapping Using Simulation-based Inference with Deep Learning

Continuum reverberation mapping (CRM) of active galactic nuclei (AGN) monitors multiwavelength variability signatures to constrain accretion disk structure and supermassive black hole (SMBH) properties. The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time will survey tens of millions of AGN over the next decade, with thousands of AGN monitored with almost daily cadence in the deep drilling fields. However, existing CRM methodologies often require long computation time and are not designed to handle such large amounts of data. In this paper, we present a fast and flexible inference framework for CRM using simulation-based inference (SBI) with deep learning to estimate SMBH properties from AGN light curves. We use a long short-term memory summary network to reduce the high dimensionality of the light curve data and then use a neural density estimator to estimate the posterior of SMBH parameters. Using simulated light curves, we find SBI can produce more accurate SMBH parameter estimation with 10 3 –10 5 times speed up in inference efficiency compared to traditional methods. The SBI framework is particularly suitable for wide-field CRM surveys as the light curves will have identical observing patterns, which can be incorporated into the SBI simulation. We explore the performance of our SBI model on light curves with irregular-sampled, realistic observing cadence and alternative variability characteristics to demonstrate the flexibility and limitation of the SBI framework.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Extraction of longitudinal aerodynamic coefficients from forward-flight conditions of a tilt-wing V/STOL airplane

A parameter-estimation algorithm was used to extract the longitudinal aerodynamic derivatives from flight data for the XC-142A airplane in a cruise condition. The flight data were the response to a tail-plane doublet input. Results of this study showed that a set of derivatives were determined which yielded a calculated aircraft response in close agreement with the measured response. This calculated response was in much closer agreement with the flight data than the response obtained by using derivatives which were calculated from empirical methods. There were large differences between some of the important derivatives extracted from flight data and those calculated from empirical methods. The reasons for these differences were not identified.

Williams, J. L.↗
NASA NTRS1976

Solar heating in the Mars dusty atmosphere

The complex refractive index in the solar spectral region is estimated. With this index and the size distribution estimated from the UVS data Mie theory is used to compute the radiative parameters required for including radiative scattering in simplified radiative transfer approximations. These approximations then enable the wavelength-integrated solar heating to be computed for various dust-laden Martian atmospheres. The calculations presented in the main body of the paper were computer using the delta-Eddington approximation.

Zurek, R. W.↗
NASA NTRS1996

Multifrequency, Multipolarization External Calibration of the SIR-C/X-SAR Radars

Progress and the future plans for the following objectives are discussed: (1) Assess the accuracy at which the SIR-C/X-SAR standard data products can be calibrated through the use of ground calibrators to estimate the end-to-end system polarization calibration constants (or distortion parameters) and incorporate the constants into the data processing; (2) Study the cross-calibration between three multipolarization systems: SIR-C, the National Aeronautics and Space Administration/Jet Propulsion Laboratory (NASA/JPL) DC-8 SAR, and the University of Michigan ground-based polarimetric scatterometer; (3) Evaluate the calibration "stability" of SIR-C/X-SAR (measured by variations in the calibration constants) over the range swath width and over a specified distance in azimuth. Variations over a 12-hour period (between ascending and descending passes) will also be studied; and (4) Develop a cost-effective calibration plan including development of inexpensive polarimetric active calibrators.

Freeman, Anthony↗
NASA NTRS1999

CARES/Life Ceramics Durability Evaluation Software Enhanced for Cyclic Fatigue

The CARES/Life computer program predicts the probability of a monolithic ceramic component's failure as a function of time in service. The program has many features and options for materials evaluation and component design. It couples commercial finite element programs--which resolve a component's temperature and stress distribution--to reliability evaluation and fracture mechanics routines for modeling strength-limiting defects. The capability, flexibility, and uniqueness of CARES/Life have attracted many users representing a broad range of interests and has resulted in numerous awards for technological achievements and technology transfer. Recent work with CARES/Life was directed at enhancing the program s capabilities with regards to cyclic fatigue. Only in the last few years have ceramics been recognized to be susceptible to enhanced degradation from cyclic loading. To account for cyclic loads, researchers at the NASA Lewis Research Center developed a crack growth model that combines the Power Law (time-dependent) and the Walker Law (cycle-dependent) crack growth models. This combined model has the characteristics of Power Law behavior (decreased damage) at high R ratios (minimum load/maximum load) and of Walker law behavior (increased damage) at low R ratios. In addition, a parameter estimation methodology for constant-amplitude, steady-state cyclic fatigue experiments was developed using nonlinear least squares and a modified Levenberg-Marquardt algorithm. This methodology is used to give best estimates of parameter values from cyclic fatigue specimen rupture data (usually tensile or flexure bar specimens) for a relatively small number of specimens. Methodology to account for runout data (unfailed specimens over the duration of the experiment) was also included.

Nemeth, Noel N.↗
NASA NTRS2012

Top-of-the-Atmosphere Shortwave Flux Estimation from UV Observations: An Empirical Approach

Measurements of top of the atmosphere (TOA) radiation are essential to the understanding of Earth's climate. Clouds, aerosols, and ozone (0,) are among the most important agents impacting the Earth's short-wave (SW) radiation budget. There are several sensors in orbit that provide independent information related to the Earth's SW radiation budget. Having coincident information from these sensors is important for understanding their potential contributions. The A-train constellation of satellites provides a unique opportunity to analyze near-simultaneous data from several of these sensors. They include the Ozone Monitoring Instrument (OMI), on the NASA Aura satellite, that makes TOA hyper-spectral measurements from ultraviolet (UV) to visible wavelengths, and Clouds and the Earth's Radiant Energy System (CERES) instrument, on the NASA Aqua satellite, that makes broadband measurements in both the long- and short-wave. OMI measurements have been successfully utilized to derive the information on trace gases (e.g., 0 1, NO" and SO,), clouds, and absorbing aerosols. TOA SW fluxes are estimated using a combination of data from CERES and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS). In this paper, OMI retrievals of cloud/aerosol parameters and 0 1 have been collocated with CERES TOA SW flux retrievals. We use this collocated data to develop a neural network that estimates TOA shortwave flux globally over ocean using data from OMI and meteorological analyses. This input data include the effective cloud fraction, cloud optical centroid pressure (OCP), total-column 0" and sun-satellite viewing geometry from OMI as well as wind speed and water vapor from the Goddard Earth Observing System 5 Modern Era Retrospective-analysis for Research and Applications (GEOS-5 MERRA) along with a climatology of chlorophyll content. We train the neural network using a subset of CERES retrievals of TOA SW flux as the target output (truth) and withhold a different subset of the CERES data to be used for validation.

Gupta, P.↗
NASA NTRS2016

Photon Counting Detector Array Algorithms for Deep Space Optical Communications

For deep-space optical communications systems utilizing an uplink optical beacon, a single-photon-counting detector array on the flight terminal can be used to simultaneously perform uplink tracking and communications as well as accurate downlink pointing at photon-starved (pW/sq. m) power levels. In this paper, we discuss concepts and algorithms for uplink signal acquisition, tracking, and parameter estimation using a photon-counting camera. Statistical models of detector output data and signal processing algorithms are presented, incorporating realistic effects such as Earth background and detector/readout blocking. Analysis and simulation results are validated against measured laboratory data using state-of-the-art commercial photon-counting detector arrays, demonstrating sub-microradian tracking errors under channel conditions representative of deep space optical links.

beacon tracking↗
DOE OSTI2024

Steam Condensation Scaled Experiment in the Presence of Non-condensable Gas for Reactor Containment Passive Safety Analysis

This study presents scaled experiments using steam condensation with non-condensable gas (NCG)—helium, simulating hydrogen—as these experiments are pivotal for water-cooled reactor passive containment cooling system (PCCS) design and analysis. Research into PCCSs for small modular reactors (SMRs) is especially important in light of SMR system design; however, studies in the literature reflect limitations due to test geometry and operational condition variations, without considering SMR prototypic design. To address these challenges, a scaled test facility was developed to accurately replicate SMR PCCSs. This facility includes vertical down-flow condensing test sections with 1-, 2-, and 4-in.-diameter condensing tubes, accompanied by annular water cooling. Experiments were conducted using both superheated and saturated steam, with steam mass flow rates varying from 55 to 66 kg/hr., in the presence of helium as the NCG mass flow rate ranges from 1.8 to 22 kg/hr. Test data were collected on (a) the axial temperatures of the annular cooling water; (b) the outer wall temperature of the condensers; and (c) the mass flow rate, temperature, and pressure at the test section inlets and outlets. These primary test data were used in conjunction with a standard data reduction methodology to estimate essential thermal parameters such as heat fluxes, heat transfer coefficients, and condensation rates. The effects of NCGs on steam condensation within the geometry of the scaled test sections were then presented in regard to various testing conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Presentation: Steam Condensation Scaled Experiment in the Presence of Non-condensable Gas for Reactor Containment Passive Safety Analysis

This study presents scaled experiments using steam condensation with non-condensable gas (NCG)—helium, simulating hydrogen—as these experiments are pivotal for water-cooled reactor passive containment cooling system (PCCS) design and analysis. Research into PCCSs for small modular reactors (SMRs) is especially important in light of SMR system design; however, studies in the literature reflect limitations due to test geometry and operational condition variations, without considering SMR prototypic design. To address these challenges, a scaled test facility was developed to accurately replicate SMR PCCSs. This facility includes vertical down-flow condensing test sections with 1-, 2-, and 4-in.-diameter condensing tubes, accompanied by annular water cooling. Experiments were conducted using both superheated and saturated steam, with steam mass flow rates varying from 55 to 66 kg/hr., in the presence of helium as the NCG mass flow rate ranges from 1.8 to 22 kg/hr. Test data were collected on (a) the axial temperatures of the annular cooling water; (b) the outer wall temperature of the condensers; and (c) the mass flow rate, temperature, and pressure at the test section inlets and outlets. These primary test data were used in conjunction with a standard data reduction methodology to estimate essential thermal parameters such as heat fluxes, heat transfer coefficients, and condensation rates. The effects of NCGs on steam condensation within the geometry of the scaled test sections were then presented in regard to various testing conditions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Tightly-coupled camera/LiDAR integration for point cloud generation from GNSS/INS-assisted UAV mapping systems

Unmanned aerial vehicles (UAVs) equipped with integrated global navigation satellite systems/inertial navigation systems (GNSS/INS) together with cameras and/or LiDAR sensors are being widely used for topographic mapping in a variety of applications such as precision agriculture, coastal monitoring, and archaeological documentation. Integration of image-based and LiDAR point clouds can provide a comprehensive 3D model of the area of interest. For such integration, ensuring a good alignment between data from the different sources is critical. Although many works have been conducted on this topic, there is still a need for a rigorous integration approach that minimizes the discrepancy between camera and LiDAR data caused by inaccurate system calibration parameters and/or trajectory artifacts. This study proposes an automated tightly-coupled camera/LiDAR integration workflow for GNSS/INS-assisted UAV systems. The proposed strategy is conducted in three main steps. First, an image-based point cloud is generated using a LiDAR/GNSS/INS-assisted structure from motion (SfM) strategy. Then, feature correspondences between image-based and LiDAR point clouds are automatically identified. Finally, an integrated-bundle adjustment procedure including image points, LiDAR raw measurements, and GNSS/INS information is conducted to minimize the discrepancy between point clouds from different sensors while estimating system calibration parameters and refining the trajectory information. The proposed SfM strategy and integration framework are evaluated using five datasets. The SfM results show that using LiDAR data can facilitate feature matching and further increase the number of reconstructed 3D points. The experimental results also illustrate that the developed automated camera/LiDAR integration strategy is capable of accurately estimating system calibration parameters to achieve good alignment among camera/LiDAR data from single/multiple systems. Finally, an absolute accuracy in the range of 3–5 cm is achieved for the image/LiDAR point clouds after the integration process.

42 ENGINEERING↗
DOE OSTI2022

Synthesis of observed and simulated rain microphysics to inform a new Bayesian statistical framework for microphysical parameterization in climate models (Final Scientific Report)

This project aimed to investigate a new approach to bulk microphysics schemes. We identified the need to move beyond the fixed structural assumptions and approximation of existing schemes. For example, most schemes assume some functional form for the rain drop size distribution (e.g. a gamma or exponential distribution). Most schemes then evolve some number of statistical moments of that distribution via various processes, such as evaporation, sedimentation, collision-coalescence, and collisional breakup. These microphysical processes, in turn, are typically some fixed functional form derived from either some other (more detailed) model, or using some single-particle rates that are then integrated over the size distribution. While these process rate functions may have some free parameters to adjust, in other cases doing so is impossible (e.g. when the process rates are analytical or piecewise solutions to some target function). Our goal was to build and test a scheme that assumed no size distribution form, and used a series of power laws as the basis for the process rates. Moments of the size distribution would be predicted, but no underlying size distribution would be specified. Any number or choice of size distribution moments could be used, and any number of power laws could be employed to model the process rates. Thus, our approach is flexible, and can seamlessly scale across levels of complexity, as demanded by the data. Bayesian inference then would provide the formalism to estimate the model parameters and structure, allowing for robust uncertainty quantification. We proposed testing this framework in idealized simulations using bin microphysical schemes as a data source. We also proposed using real data to inform our microphysics scheme, and also that we would integrate our scheme into WRF.

58 GEOSCIENCES↗
DOE OSTI2023

Kinetics of simultaneous hydrodesulfurization and hydrodenitrogenation reactions using CoMoP/Al 2 O 3 and NiMoP/Al 2 O 3

Hydrodesulfurization (HDS) is a key reaction to achieve diesel production at the specified low sulfur levels and is highly affected by a competing reaction involving nitrogen removal through hydrodenitrogenation (HDN). This work evaluated kinetic parameters of simultaneous reactions of HDS of dibenzothiophene (DBT) and HDN of quinoline (Q) using CoMoP/Al 2 O 3 and NiMoP/Al 2 O 3 catalysts under operational conditions that allow a wide range of reagent conversions. Estimated parameters were evaluated using rigorous statistical 2 analysis. Good fits for the evaluated experimental data were provided by both power-law and Langmuir-Hinshelwood models. Further, turnover frequency values highlight adsorption and competition effects between nitrogen-containing compounds and sulfur-containing compounds. NiMoP catalyst showed higher hydrogenating power than CoMoP, with larger absolute value of the estimated adsorption enthalpy (-120 kJ.mol -1 for NiMoP and -75 kJ.mol -1 for CoMoP), suggesting strong adsorption of nitrogen compounds. A catalyst with more hydrogenating power is also more capable of performing both HDN and HDS reactions simultaneously.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

MEDLI2: MISP Inferred Aerothermal Environment and Flow Transition Assessment

The Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) sensor suite on the Mars2020 mission contained multiple sensors on the aeroshell to measure the aerothermal environment during entry into the Martian atmosphere. These sensors performed superbly and successfully returned forebody and aftbody heating measurements. Analysis of MEDLI2 data indicated flow transitioning from a laminar to turbulent state on the heatshield. No evidence of flow transition was observed on the backshell. Two methods were used to estimate flow transition times on the heatshield: (1) temperature gradient of near-surface thermocouple data and (2) heat flux gradient from an inverse reconstruction approach using thermocouple data and material response modeling. Both methods produced similar transition times with an estimated accuracy of ±1 s. To assess various transition criteria, transition parameters were evaluated at each sensor location using flow field solutions from computational fluid dynamics (CFD) simulations. The idea was to use conservative values inferred from MEDLI2 data as transition criteria for other Mars missions. To test this hypothesis, MEDLI data from the Mars Science Laboratory (MSL) mission was used to compare predicted vs. actual flow transition times. The comparisons suggest smooth wall transition criteria are not well-suited in modeling the rapid progression of a turbulent transition front. Transition criteria containing a roughness element parameter agreed better with the flight data. In summary, critical transition values derived from MEDLI2 data may be used as a starting point in constructing a flow transition model for future Mars missions.

Chun Y Tang↗
DOE OSTI2024

Convergence in simulating global soil organic carbon by structurally different models after data assimilation

Abstract Current biogeochemical models produce carbon–climate feedback projections with large uncertainties, often attributed to their structural differences when simulating soil organic carbon (SOC) dynamics worldwide. However, choices of model parameter values that quantify the strength and represent properties of different soil carbon cycle processes could also contribute to model simulation uncertainties. Here, we demonstrate the critical role of using common observational data in reducing model uncertainty in estimates of global SOC storage. Two structurally different models featuring distinctive carbon pools, decomposition kinetics, and carbon transfer pathways simulate opposite global SOC distributions with their customary parameter values yet converge to similar results after being informed by the same global SOC database using a data assimilation approach. The converged spatial SOC simulations result from similar simulations in key model components such as carbon transfer efficiency, baseline decomposition rate, and environmental effects on carbon fluxes by these two models after data assimilation. Moreover, data assimilation results suggest equally effective simulations of SOC using models following either first‐order or Michaelis–Menten kinetics at the global scale. Nevertheless, a wider range of data with high‐quality control and assurance are needed to further constrain SOC dynamics simulations and reduce unconstrained parameters. New sets of data, such as microbial genomics‐function relationships, may also suggest novel structures to account for in future model development. Overall, our results highlight the importance of observational data in informing model development and constraining model predictions.

54 ENVIRONMENTAL SCIENCES↗