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DOE OSTI2020

Modeling the Sources and Transport Processes During Extreme Ammonia Episodes in the U.S. Corn Belt

Abstract Atmospheric ammonia (NH 3 ) is the primary form of reactive nitrogen (N r ) and a precursor of ammonium (NH 4 + ) aerosols. Ammonia has been linked to adverse impacts on human health, the loss of ecosystem biodiversity, and plays a key role in aerosol radiative forcing. The midwestern United States is the major NH 3 source in North America because of dense livestock operations and the high use of synthetic nitrogen fertilizers. Here, we combine tall‐tower (100 m) observations in Minnesota and Weather Research and Forecasting model coupled with Chemistry (WRF‐Chem) modeling to investigate high and low NH 3 emission episodes within the U.S. Corn Belt to improve our understanding of the distribution of emission sources and transport processes. We examined observations and performed model simulations for cases in February through November of 2017 and 2018. The results showed the following: (1) Peak emissions in November 2017 were enhanced by above‐normal air temperatures, implying a Q 10 (i.e., the change in NH 3 emissions for a temperature increase of 10°C) of 2.5 for emissions. (2) The intensive livestock emissions rom northern Iowa, approximately 400 km away from the tall tower, accounted for 17.6% of the abundance in tall‐tower NH 3 mixing ratios. (3) Ammonia mixing ratios in the innermost domain 3 frequently (i.e., 336 hr, 48% of November 2017) exceeded 5.3 ppb, an important air quality health standard. (4) In November 2017, simulated NH 3 net ecosystem exchange (the difference between NH 3 emissions and dry deposition) accounted for 60–65% of gross NH 3 emissions for agricultural areas and was 2.8–3.1 times the emissions of forested areas. (5) We estimated a mean annual NH 3 net ecosystem exchange of 1.60 ± 0.06 nmol · m −2 · s −1 for agricultural lands and −0.07 ± 0.02 nmol · m −2 · s −1 for forested lands. These results imply that future warmer fall temperatures will enhance agricultural NH 3 emissions, increase the frequency of dangerous NH 3 episodes, and enhance dry NH 3 deposition in adjacent forested lands.

Hu, Cheng↗

NASA NTRS1989

A discussion of observation model, error sources and signal size for spaceborne gravitational gradiometry

Various space concepts were discussed during the past 20 years for a global improvement of the knowledge of the earth's gravity field. The concepts reach from high-low and low-low satellite-to-satellite tracking via tethered satellite gradiometers to sophisticated superconducting gradiometers. The purpose is to show that starting from one basic equation three criteria are sufficient to typify the various concepts and define the underlying observation model. Furthermore the different error sources, in particular, the time varying part of self-gravitation, and the expected signal size of all six gravity gradient components shall be discussed.

Rummel, R.↗

DOE OSTI2021

DEPRECATED AI-Batt-OS (Autonomous Identification of Battery Life Models - Open Source) [SWR 21-17]

DEPRECATED. This repository was archived by the owner on Jun 30, 2026. It is now read-only. Open source implementation of some of the methods utilized by AI-Batt, a battery lifetime modeling and analysis toolkit provided by the National Laboratory of the Rockies (NLR). This software demonstrates the use of bi-level optimization and symbolic regression techniques to semi-autonomously identify algebraic models predicting the capacity fade of lithium-ion batteries during calendar aging. Modeling the degradation of batteries is a complex task, due to the difficulty in separating the time-dependent and time-independent factors impacting cell level degradation, across multiple data series with different numbers of measurements and/or data quality. Bi-level optimization enables model parameters to be optimized to either the entire data set or to individual data series, allowing statistical disambiguation of global behaviors (data series independent) and local behaviors (data series dependent). Symbolic regression is used to automatically search for optimal low-dimesional models predicting the variation of locally optimized parameters versus time-independent experimental variables from millions of possible models, resulting in a more accurate and repeatable model identification process than is possible by a manual search. The provided tools also implement cross-validation and bootstrap resampling schemes, empowering statistical model comparison/selection and quantification of model uncertainties. An example script replicates the results from the manuscript "Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning", submitted to ECS. All code is written in MATLAB. Requires the Statistics and Machine Learning Toolbox. Contact Dr. Paul Gasper at Paul.Gasper@nlr.gov for any questions.

Gasper, Paul↗

NASA NTRS2019

Lens Model and Source Reconstruction Reveal the Morphology and Star Formation Distribution in the Cool Spiral LIRG SGAS J143845.1+145407

We present Hubble Space Telescope (HST) imaging and grism spectroscopy of a strongly lensed LIRG at z = 0.816, SGAS 143845.1+145407, and use the magnification boost of gravitational lensing to study the distribution of star formation throughout this galaxy. Based on the HST imaging data, we create a lens model for this system; we compute the mass distribution and magnification map of the z = 0.237 foreground lens. We find that the magnification of the lensed galaxy ranges between 2 and 10, with a total magnification (measured over all the images of the source) of μ = ${11.8}_{-2.4}^{+4.6}$. We find that the total projected mass density within ∼34 kpc of the brightest cluster galaxy is 6.0(+0.3,-0.7) x 10^(12)Mꙩ. Using the lens model we create a source reconstruction for SGAS 143845.1+145407, which, paired with a faint detection of Hα in the grism spectroscopy, allows us to finally comment directly on the distribution of star formation in a z ∼ 1 LIRG. We find widespread star formation across this galaxy, in agreement with the current understanding of these objects. However, we note a deficit of Hα emission in the nucleus of SGAS 143845.1+145407, likely due to dust extinction.

Samuel J. Dunham↗

NASA NTRS2003

Tagging Water Sources in Atmospheric Models

Tagging of water sources in atmospheric models allows for quantitative diagnostics of how water is transported from its source region to its sink region. In this presentation, we review how this methodology is applied to global atmospheric models. We will present several applications of the methodology. In one example, the regional sources of water for the North American Monsoon system are evaluated by tagging the surface evaporation. In another example, the tagged water is used to quantify the global water cycling rate and residence time. We will also discuss the need for more research and the importance of these diagnostics in water cycle studies.

Bosilovich, M.↗

DOE OSTI2024

Applied radiation tags for warhead dismantlement transparency

Here, this study explores the feasibility of applying radiation tags as a Chain of Custody tool to confirm the dismantlement of individual warheads by investigating time dependent emissions from special nuclear material. Precedents of photon and neutron sources that have been used to irradiate warhead components are presented. Measurements of irradiated Highly Enriched Uranium (HEU) are used to benchmark simulations with the CINDER90 library for MCNP. Delayed gamma emissions are simulated as a function of time since irradiation of moderated HEU and Weapons Grade Plutonium with photon and neutron sources. Models of commercial 9 MV and 15 MV linacs were found to induce ~10 9 fissions/g and ~10 11 fissions/g, respectively, creating 3 to 4 orders of magnitude more delayed gammas than neutron sources, modeled at 10 10 n/s. However, a DT neutron source was found to induce sufficient fissions, ~10 7 fissions/g, to create quantifiable signatures relative to intrinsic emissions. Applied radiation tagging is determined to be technically feasible, but its operational context and practical implementation requires significant development.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2025

Factors That Influence Variability in Stress-Drop Measurements Using Spectral Decomposition and Spectral-Ratio Methods for the 2019 Ridgecrest Earthquake Sequence

Stress drop is a fundamental parameter related to earthquake source physics, but is hard to measure accurately. To better understand how different factors influence stress-drop measurements, we compare two different methods using the Ridgecrest stress-drop validation data set: spectral decomposition (SD) and spectral ratio (SR), each with different processing options. Here, we also examine the influence of spectral complexity on source parameter measurement. Applying the SD method, we find that frequency bandwidth and time-window length could influence spectral magnitude calibration, while depth-dependent attenuation is important to correctly map stress-drop variations. For the SR method, we find that the selected source model has limited influence on the measurements; however, the Boatwright model tends to produce smaller standard deviation and larger magnitude dependence than the Brune model. Variance reduction threshold, frequency bandwidth, and time-window length, if chosen within an appropriate parameter range, have limited influence on source parameter measurement. For both methods, wave type, attenuation correction, and spectral complexity strongly influence the result. The scale factor that quantifies the magnitude dependence of stress drop show large variations with different processing options, and earthquakes with complex source spectra deviating from the Brune-type source models tend to have larger scale factor than earthquakes without complexity. Based on these detailed comparisons, we make a few specific suggestions for data processing workflows that could help future studies of source parameters and interpretations.

58 GEOSCIENCES↗

DOE OSTI2024

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗

NASA NTRS1980

Alternate symbol inversion for improved symbol synchronization in convolutionally coded systems

Inverting alternate symbols of the encoder output of a convolutionally coded system provides sufficient density of symbol transitions to guarantee adequate symbol synchronizer performance, a guarantee otherwise lacking. Although alternate symbol inversion may increase or decrease the average transition density, depending on the data source model, it produces a maximum number of contiguous symbols without transition for a particular class of convolutional codes, independent of the data source model. Further, this maximum is sufficiently small to guarantee acceptable symbol synchronizer performance for typical applications. Subsequent inversion of alternate detected symbols permits proper decoding.

Simon, M. K.↗

DOE OSTI2024

Cognitive Grid Optimization

This project laid the foundation to include a security constrained economic dispatch (SCED) within one of the leading simulators which is used to train system operators who keep the lights on for over 150 million people in USA. The SCED is designed to handle very high penetrations of renewable generation as well as battery storage. As a follow on the this project, a Trusted Source Model of the North American Electric Interconnections will be built from public GIS data. The various North American Markets will be emulated. This Trusted Source Model will grow the software developers for the next generation of power applications that are needed to transition to all green generation while everything is electrified.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2003

Sound Radiated by a Wave-Like Structure in a Compressible Jet

This paper extends the analysis of acoustic radiation from the source model representing spatially-growing instability waves in a round jet at high speeds. Compared to previous work, a modified approach to the sound source modeling is examined that employs a set of solutions to linearized Euler equations. The sound radiation is then calculated using an integral surface method.

Golubev, V. V.↗

NASA NTRS1977

The structure of cometary ionospheres. II - CO-rich comets

The structure of the ionosphere of a CO-rich comet is computed using two different models. The first one, the photochemical model, assumes that the dissociation and ionization of cometary neutrals and ions are due to photoionization, and photodissociation by solar UV radiation together with dissociative recombinations and ion-neutral reactions. The second one, the internal source model, also incorporates the ionization and dissociation effects of an electric current discharging through the inner coma. The generation of this current has been discussed in earlier papers. It is concluded that the internal source model can explain qualitatively the basic morphology of the ionospheres of CO-rich comets such as Humason (1962, VIII) and Morehouse (1908, III), whereas the photochemical model cannot. The main aim of this paper is not so much to provide accurate numerical estimates as to draw attention to a process which may very well dominate the structures of cometary ionospheres.

Ip, W.-H.↗

NASA NTRS2006

Source Noise Modeling Efforts for Fan Noise in NASA Research Programs

There has been considerable progress made in fan noise prediction over the past 15 years. NASA has conducted and sponsored research that has improved both tone and broadband fan noise prediction methods. This presentation highlights progress in these areas with emphasis on rotor/stator interaction noise sources. Tone noise predictions are presented for an advanced prediction code called "LINFLUX". Comparisons with data are" included for individual fan duct modes. There has also been considerable work developing new fan broadband noise prediction codes and validation data from wind tunnel model tests. Results from several code validation exercises are presented that show improvement of predicted sound power levels. A summary is included with recommendations for future work.

Huff, Dennis L.↗

NASA NTRSDate not supplied

Predictions of the Azimuthal Variation of the Noise from Chevron Jets using an Acoustic Analogy

An existing acoustic analogy formulation is used to make predictions of the turbulent mixing noise from a series of chevron jets tested at NASA Glenn Research Center. Reynolds-averaged Navier-Stokes solutions are used as input to provide the mean flow and turbulence quantities needed to compute the Green’s function and parameterize the source model. The Green’s function for the non-axisymmetric mean flows generated by these nozzles is computed using a second-order finite volume method. A slightly modified version of an existing source model originally developed for round jets is used to assess its capability in these non-axisymmetric flows. Prediction results are compared with experimental data for a range of azimuthal orders of the nozzle geometry and flow speeds. The results show that the RANS-based acoustic analogy prediction method is able to capture the observed azimuthal variation of the sound field fairly well at relatively low jet exit velocities. At higher speeds, the prediction method still captures the observed trends in azimuthal directivity but not the absolute levels, particularly at higher frequencies. Areas for potential improvement of the method are suggested.

Jet Noise↗

NASA NTRSDate not supplied

Predictions of the Azimuthal Variation of the Noise from Chevron Jets using an Acoustic Analogy

Jet Noise↗

NASA NTRSDate not supplied

Inlet Radiated Noise Predictions for the NASA Source Diagnostic Test Fan Using Physics-Based Simulations

Commercial supersonic aircraft are expected to produce considerably more noise during landing and take-off operations than existing subsonic aircraft. Establishing noise regulation is challenging because no examples of this aircraft type are currently flying. Existing aircraft noise prediction tools can be used, but the noise source models for these empirical tools are typically based on data from subsonic aircraft components. The present work documents a procedure for using physics-based computational tools to generate the propagating sound field radiating out the nacelle inlet. Although no analytical source modeling is demonstrated, these tools utilize measured data to compare the complex pressure for various propagating modes. The discrepancies found in applying the propagation tools to the subsonic inlet will be ascribed to calculations of supersonic inlets being used to update current empirical noise prediction tools.

Noise Predictions↗

NASA NTRS2012

Broadband Liner Optimization for the Source Diagnostic Test Fan

The broadband component of fan noise has grown in relevance with the utilization of increased bypass ratio and advanced fan designs. Thus, while the attenuation of fan tones remains paramount, the ability to simultaneously reduce broadband fan noise levels has become more appealing. This paper describes a broadband acoustic liner optimization study for the scale model Source Diagnostic Test fan. Specifically, in-duct attenuation predictions with a statistical fan source model are used to obtain optimum impedance spectra over a number of flow conditions for three liner locations in the bypass duct. The predicted optimum impedance information is then used with acoustic liner modeling tools to design liners aimed at producing impedance spectra that most closely match the predicted optimum values. Design selection is based on an acceptance criterion that provides the ability to apply increased weighting to specific frequencies and/or operating conditions. Typical tonal liner designs targeting single frequencies at one operating condition are first produced to provide baseline performance information. These are followed by multiple broadband design approaches culminating in a broadband liner targeting the full range of frequencies and operating conditions. The broadband liner is found to satisfy the optimum impedance objectives much better than the tonal liner designs. In addition, the broadband liner is found to provide better attenuation than the tonal designs over the full range of frequencies and operating conditions considered. Thus, the current study successfully establishes a process for the initial design and evaluation of novel broadband liner concepts for complex engine configurations.

Nark, Douglas M.↗

NASA NTRS1980

Iron and titanium distribution on the moon from orbital gamma ray spectrometry with implications for crustal evolutionary models

A set of Fe and Ti maps and regional values are obtained from the Apollo 15 and 16 orbital gamma ray data by energy band analysis. High-Ti basalts predominate the early and late stages of mare volcanism with high-Fe basaltic volcanism in the interim. The first evidence of a high-Ti-KREEP basalt association is found in the Aristarchus region. A N-S asymmetry for Fe and Ti in the east limb and farside highlands complicates the E-W asymmetry for Th but substantiates crustal inhomogeneity. The observed crustal inhomogeneity adds an additional objection to the primitive source model for crustal evolution. The high-Ti-KREEP basalt association and the general trend of decreasing mare basalt Ti with time lend support to the cumulate source model; however, this model cannot account for young, high-Ti maria. The dynamic assimilation model better accounts for chemical variations observed on the moon.

Davis, P. A., Jr.↗