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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CTF Validation and Verification (V.4.2)

Coolant-Boiling in Rod Arrays- Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for Light Water Reactor (LWR) analysis. It uses a two-fluid, three-field (i.e. fluid film, fluid drops, and vapor) modeling approach. Both sub-channel and 3D Cartesian forms of nine conservation equations are available for LWR modeling. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last several decades. COBRA-TF is also used at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently became the PSU RDFMG version of COBRA-TF (CTF). One part of the improvement process includes validating the methods in CTF. This document seeks to provide a certain level of certainty and confidence in the predictive capabilities of the code for the scenarios it was designed to model-rod bundle geometries with operating conditions that are representative of prototypical Pressurized Water Reactor (PWR)s and Boiling Water Reactor (BWR)s in both normal and accident conditions. This is done by modeling a variety of experiments that simulate these scenarios and then presenting a qualitative and quantitative analysis of the results that demonstrates the accuracy to which CTF is capable of capturing specific quantities of interest.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2025

Parallel diffusion operator for magnetized plasmas with improved spectral fidelity

Diffusive transport processes in magnetized plasmas are highly anisotropic, with fast parallel transport along the magnetic field lines sometimes faster than perpendicular transport by orders of magnitude. This constitutes a major challenge for describing non-grid-aligned magnetic structures in Eulerian (grid-based) simulations. Here, the present paper describes and validates a new method for parallel diffusion in magnetized plasmas based on the anti-symmetry representation [Halpern and Waltz, Phys. Plasmas 25, 060703 (2018)]. In the anti-symmetry formalism, diffusion manifests as a flow operator involving the logarithmic derivative of the transported quantity. Qualitative plane wave analysis shows that the new operator naturally yields better discrete spectral resolution compared to its conventional counterpart. Numerical simulations comparing the new method against existing finite difference methods are carried out, showing significant improvement. In particular, we find that combining anti-symmetry with finite differences in diagonally staggered grids essentially eliminates the so-called “artificial numerical diffusion” that affects conventional finite difference and finite volume methods.

Anisotropic diffusion↗
DOE OSTI2024

What to expect when you're expecting engagement: Delivering procedural justice in large-scale solar energy deployment

Community engagement in the planning process to build large-scale solar (LSS) projects can win local support and advance procedural justice. However, an understanding of community engagement in current LSS development is lacking. Using responses from a U.S. nationwide survey (n = 979) of residential neighbors living within 3 miles (4.8 km) of completed LSS projects (i.e. “solar neighbors”) and project details from the U.S. Large-Scale Solar Photovoltaic Database (USPVDB), this study seeks to answer the following questions: How are solar neighbors' perceptions of community engagement associated with their attitudes toward their LSS projects? How do solar neighbors' perceptions of community engagement compare to their expectations? And, how do neighbors explain what they perceived about the planning process? We answer these questions using mixed methods, including regression modeling, a new gap analysis technique, and qualitative coding. We find that higher perceived engagement is associated with more positive attitudes toward the project, even when controlling for respondents who acted in opposition. Supporters and opponents alike expect more engagement than they perceived and information about projects both before construction and after operation is lacking. Awareness and engagement expectations increase at certain project size and proximity thresholds. However, most neighbors expect the public to offer input during engagement, but not make decisions. We contextualize these findings with explanatory comments from respondents.

14 SOLAR ENERGY↗
DOE OSTI2020

Deep learning interfacial momentum closures in coarse-mesh CFD two-phase flow simulation using validation data

Multiphase flow phenomena have been widely observed in the industrial applications while it remains a challenging yet unsolved problems. Three-dimensional computational fluid dynamics (CFD) approaches resolve the flow fields on a finer special and temporal scales which can complement the dedicated experimental study. However, closures have to be introduced to reflect the underlying physics in multiphase flow. Among them, the interfacial forces, including drag, lift, turbulent dispersion and wall lubrication forces, play in important role on the bubble’s distribution and migration in liquid-vapor two-phase flow. Development of those closures traditionally rely on the experimental data and analytical derivation with simplified assumptions which usually cannot deliver a universal solution across wide range of flow conditions. In this paper, a data-driven approach, named as Feature Similarity Measurement (FSM), is developed and applied to improve the simulation capability of two-phase flow with coarse-mesh CFD approach. Interfacial momentum transfer in adiabatic bubbly flow serves as the focus of the present study. Both a mature and a simplified set of interfacial closures are taken as the low fidelity data. Experimental data and fine mesh CFD simulations results are adopted as high-fidelity data. Qualitative and quantitative analysis are performed in this paper which reveals that FSM can substantially improve the prediction of coarse mesh CFD model regardless of the choice of interfacial closures and it provides scalability and consistency across discontinuous flow regimes. Furthermore, it demonstrates that data-driven method can aid the multiphase flow modeling by exploring the connections between local physical features and simulation errors.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Simplification of the purification of heat stable recombinant low molecular weight proteins and peptides from GST-fusion products

The synthesis and purification of peptides of importance in the fields of research and medicine continue to be a challenging task. Chemical synthesis of oligopeptides, especially those greater than 25 amino acids, is cost prohibitive. On the other hand, several bottlenecks exist in the production of recombinant short peptides in heterologous expression hosts such as Escherichia coli (E. coli). In this paper, a rapid, cost-effective, and reliable method for the production and singlestep-purification of peptides and small proteins was developed. Five peptides and small proteins were overexpressed in E. coli as GST-fusion products in high yields. The recombinant peptides or proteins were successfully purified after enzymatic cleavage with selective heat-induced precipitation of the GST-affinity tag. Qualitative and quantitative analysis using SDS-PAGE and mass spectrometric methods suggest that the recombinant peptides/ proteins were purified to >95% homogeneity. Results of biophysical experiments, including multi-dimensional NMR spectroscopy, show that the purified proteins/ peptides retain their native conformation. Isothermal titration calorimetry studies indicate no significant change in the binding affinity of the heattreated purified product to their interacting partner(s) compared to the recombinant peptides purified by conventional chromatographic procedures without subjecting to heat treatment. In our opinion, the results reported render the purification of recombinant proteins/ peptides of biomedical relevance using our proposed method easy and reliable.

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

Microstructure of irradiated AGR TRISO particle buffer layers as measured by X-ray computed tomography

Shrinkage of the initially low-density buffer layer in tristructural isotropic (TRISO) coated fuel particles during irradiation is a well-known phenomenon with potential implications for fission product and actinide transport, as well as potential pyrocarbon fracture that in some cases has been observed to impact particle performance. During post-irradiation examination, the buffer layer's structure is commonly determined using 2D microscopy of a particle cross section or a series of particle cross sections at staggered depths. Although these methods provide a general idea of the irradiated buffer microstructure, they do not provide a full picture of the TRISO coating microstructure. By contrast, x-ray computed tomography (XCT) provides full 3D imaging of the TRISO particle. Particles from various compacts irradiated for the Advanced Gas Reactor Fuel Development and Qualification Program were imaged using XCT. Some of these particles were selected because of abnormal fission product inventories (e.g., low 137 Cs), whereas others were randomly selected from the center of the fission product inventory distribution. Qualitative and quantitative analysis techniques were applied to the randomly selected particles as representatives of typical TRISO behavior to study the post-irradiation structure of the buffer layer. These results showed that, while separation of the buffer and inner pyrolytic carbon layers was a common behavior during the radiation-induced shrinkage of the buffer, a portion of the original buffer/inner pyrolytic carbon interface remained intact throughout irradiation in nearly all cases. Furthermore, these results also indicated clear trends in the degree of buffer densification with irradiation temperature and fluence.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bridging cognitive gaps between user and model in interactive dimension reduction

Interactive machine learning (ML) systems are difficult to design because of the "Two Black Boxes" problem that exists at the interface between human and machine. Many algorithms that are used in interactive ML systems are black boxes that are presented to users, while the human cognition represents a second black box that can be difficult for the algorithm to interpret. These two black boxes create cognitive gaps between the user and the interactive ML model when a user interacts with the system. In this paper, we identify several cognitive gaps that exist in a previously-developed interactive visual analytics (VA) system, Andromeda. These cognitive gaps that we are addressing in Andromeda are representative of common problems in other VA systems. Our goal with this work is to open both black boxes and bridge these cognitive gaps by making improvements to the original Andromeda system, including designing new visual features to help people better understand how Andromeda processes and interacts with data and improving the underlying algorithm so that the Andromeda system can better understand the intent of the user during the data exploration process. We evaluate our designs through both qualitative and quantitative analysis (i.e., user study and simulation analysis), and the results confirm that the improved Andromeda system outperforms the original version significantly in a series of high-dimensional data understanding tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Large-Scale Interlaboratory DI-FT-ICR MS Comparability Study Employing Various Systems

We report ultra-high resolution mass spectrometry (UHR-MS) coupled with direct infusion (DI) electrospray ionization offers a fast solution for accurate untargeted profiling. Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometers have been shown to produce a wealth of insights into complex chemical systems because they enable unambiguous molecular formula assignment even if the vast majority of signals is of unknown identity. Inter-laboratory comparisons are required to apply this type of instrumentation in quality control (for food industry or pharmaceutics), large-scale environmental studies or clinical diagnostics. Extended comparisons employing different FT-ICR MS instruments with qualitative direct infusion analysis are scarce since the majority of detected compounds cannot be quantified. The extent to which observations can be reproduced by different laboratories remains unknown. We set up a preliminary study which encompassed a set of seventeen laboratories around the globe, diverse in instrumental characteristics and applications, to analyze the same sets of extracts from commercially available standard human blood plasma and Standard Reference Material (SRM) for blood plasma (SRM1950), which were delivered at different dilutions or spiked with different concentrations of pesticides. The aim of this study was to assess the extent to which the outputs of differently tuned FTICR mass spectrometers, with different technical specifications, are comparable for setting the frames of a future DI-FT-ICR MS ring trial. We concluded that a cluster of five laboratories, with diverse instrumental characteristics showed comparable and representative performance across all experiments, setting a reference to be used in a future ring trial on blood plasma.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Polysulfide entrapment and retardation in gel electrolyte Li–S batteries: experiments and modeling

Gelling the electrolyte in lithium–sulfur (Li–S) batteries provides advantages in terms of safety and mitigating polysulfide shuttling leading to reduced side reactions and dendrite growth on the anode side. In the current study, organic and ceramic crosslinkers have been used to improve the entrapment of polysulfides and prevent them from shuttling to the anode side. However, the performance of gel electrolytes is still far from being on par with liquid electrolytes in terms of raw capacity. The discharge curves exhibit an extended first plateau for gel electrolyte batteries compared to liquid electrolytes, showing that polysulfides are better trapped in the gel system. Yet, in the conversion of soluble polysulfides into insoluble polysulfides, the second plateau was delayed. Qualitative and quantitative analysis of the polysulfide diffusion in the liquid electrolyte and gel electrolyte systems were also conducted to predict the relative diffusivity ratio between the liquid electrolyte and gel electrolyte for simulation. To probe what happens at the end of the discharge, where the mass transport in the gel electrolyte appears to be slow, a modified discharge procedure was used where the cell is first paused after discharge and then discharged a second time before recharging normally. Coin cell tests for two gel electrolytes in addition to liquid electrolyte show up to 7% capacity recovery after the pause, which indicates that the diffusion of species during the pause is responsible for the failure recovery. Additionally, the recovery is higher for gel electrolytes compared to liquid, for higher C-rates, and for longer pause times. To better understand this behavior, a Li–S numerical model with mass transport limited reactions was used to examine the polysulfide diffusion coefficients expected in different electrolyte systems. The model is able to reproduce the trends seen in experiments and yields a higher recovery for smaller Li 2 S 4 diffusion coefficients, suggesting that insufficient Li 2 S 4 mass transport is responsible for failure at the end of discharge. By identifying the effect that gel electrolytes have on the state of the battery during discharge using both experimental and simulation methods, this work is a step towards leveraging the advantages of gel electrolytes and mitigating their weaknesses.

25 ENERGY STORAGE↗
DOE OSTI2025

Incubating advances in integrated photonics with emerging sensing and computational capabilities

As photonic technologies grow in multidimensional aspects, integrated photonics holds a unique position and continuously presents enormous possibilities for research communities. Applications include data centers, environmental monitoring, medical diagnosis, and highly compact communication components, with further possibilities continuously growing. Herein, we review state-of-the-art integrated photonic on-chip sensors that operate in the visible to mid-infrared wavelength region on various material platforms. Among the different materials, architectures, and technologies leading the way for on-chip sensors, we discuss the optical sensing principles that are commonly applied to biochemical and gas sensing. Our focus is on passive optical waveguides, including dispersion-engineered metamaterial-based structures, which are essential for enhancing the interaction between light and analytes in chip-scale sensors. We harness a diverse array of cutting-edge sensing technologies, heralding a revolutionary on-chip sensing paradigm. Our arsenal includes refractive-index-based sensing, plasmonics, and spectroscopy, which forge an unparalleled foundation for innovation and precision. Furthermore, we include a brief discussion of recent trends and computational concepts, incorporating Artificial Intelligence & Machine Learning (AI/ML) and deep learning approaches over the past few years to improve the qualitative and quantitative analysis of sensor measurements.

Jain, Sourabh (ORCID:0000000279923275)↗
DOE OSTI2021

Application of molecular convergent close-coupling cross sections in a collisional radiative model for the triplet system of molecular hydrogen

Collisional radiative (CR) models for molecular hydrogen are of high relevance for performing qualitative and quantitative analysis of excited-state population densities measured in plasmas or predicting the dependence of plasma emission on parameter variations. Although the development of such models for H 2 started decades ago, major uncertainties still exist regarding the most important set of input parameters, namely the cross sections for electron-impact excitation. The deviations between cross sections from different datasets are particularly pronounced in the energy region close to the threshold energy, strongly increasing the uncertainty of CR models applied to low-temperature plasmas. This paper presents experimental validation of a set of newly calculated non ro-vibrationally resolved electron-impact cross sections calculated for the triplet system of H 2 using the molecular convergent close-coupling method in the adiabatic-nuclei formulation. These cross sections are implemented into a CR model based on the flexible solver Yacora. A first comparison of CR calculations with the different datasets to experimentally-determined population densities is performed at a planar ICP discharge for varying pressure (between 1 and 10 Pa) and RF power (between 700 and 1100 W). For the experimentally-accessible electron temperature and density range (2.5–10 eV and 1.8–3.3 × 10 16 m –3 , respectively), very good agreement between the model and experiment is obtained using the new data set, in contrast to previously used cross sections.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Effects of overlapping sources on cosmic shear estimation: Statistical sensitivity and pixel-noise bias

The next generation of dark-energy imaging surveys — so called “Stage-IV” surveys, such as that of the Rubin Observatory Legacy Survey of Space and Time (LSST) — will cross a threshold in the number density of detected sources on the sky that requires qualitatively different image analysis and measurement techniques compared to the current generation of Stage-III surveys. In Stage-IV surveys, a significant amount of the cosmologically useful information is due to sources whose images overlap with those of other sources on the sky. Here, we focus on the weak gravitational lensing probe, for which we expect the largest impact since the cosmic shear signal is primarily encoded in the estimated shapes of observed galaxies and thus directly impacted by overlaps. We introduce a framework based on the Fisher formalism to analyze the effect of the overlapping sources (“blending”) on the estimation of cosmic shear. This method gives concrete predictions for the minimum loss of information due to noise and blending for any choice of “deblending” scheme and shape-measurement algorithm. Our studies account for undetected sources but do not address their full effects and biases they may introduce. We use simulated images and predict this impact of blending for three surveys: the Dark Energy Survey (DES), the Hyper-Suprime Cam Subaru Strategic Program (HSC-SSP), and the Rubin LSST. Our methodology successfully estimates the statistical sensitivity to weak lensing for DES and HSC early results. For LSST, we present the expected loss in statistical sensitivity for the ten-year survey due to blending. We find that for approximately 62% of galaxies that are likely to be detected in full-depth LSST images, at least 1% of the flux in their pixels is from overlapping sources. We also find that the statistical correlations between measures of overlapping galaxies and, to a much lesser extent (0.2%) the higher shot noise level due to their presence, decrease the effective number density of galaxies, N eff , by ~ 18%. We calculate an upper limit on N eff of 39.4 galaxies per arcmin 2 in r band. We study the impact of stars on as a function of stellar density and illustrate the diminishing returns of extending the survey into lower Galactic latitudes. We extend the simulation-based Fisher formalism to predict the expected increase in pixel-noise bias due to blending for maximum-likelihood (ML) shape estimators. We find that noise bias depends sensitively on the particular shape estimator and measure of ensemble-average shape that is used, and properties of the galaxy that include redshift-dependent quantities such as size and luminosity. The source code for these studies is available online.[The documented software developed for the catalog-level studies are available in the open-source LSST DESC github repository https://github.com/LSSTDESC/WeakLensingDeblending. The software for analyzing one or two galaxies with user-defined parameters is in the open-source github repository https://github.com/ismael-mendoza/ShapeMeasurementFisherFormalism.]

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Distributed Coordination of Networked Microgrids for Voltage Support in Bulk Power Grids

The increasing deployment of distributed energy resources (DERs) and microgrids (MGs) in power distribution systems has enabled the adjustment of reactive power consumption as seen at the substation, which can be used to provide voltage support for the bulk power system (BPS). Leveraging this new capability will provide greater resiliency to the power system as a whole. Here, the goal of this paper is to develop and compare three different algorithms, namely distributed optimal power flow, distributed consensus algorithm, and fully decentralized collaborative autonomy for unbalanced distribution systems for microgrid coordination. These algorithms use networked MGs to support the BPS voltage when a contingency at the bulk grid results in abnormally low voltages, which may be a precursor to voltage collapse. Our comparative analysis includes both qualitative and quantitative assessments of the three algorithms and a discussion of the trade-offs between the decentralized and distributed methods in normal and disrupted conditions. Each algorithm was evaluated on the modified IEEE 13-bus system and a real power distribution system at Chattanooga, Tennessee, that encompasses more than 4500 buses. Each algorithms excels differently and may be suited for different scenarios depending on the condition, operations, and priorities of the power and communication systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

DPC Cement Filler Development (Progress Report)

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The following cement filler compositions were selected for experimental development work and accelerated testing in FY20: Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with H 3 PO 4 ; Calcium phosphate cements (CPCs); more specifically composed of pure or nearly pure hydroxyapatite or HAP (Ca 5 (PO 4 ) 3 (OH)); Wollastonite phosphate cements (WPC), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material and the phosphate serves as the binder. The FY20 effort focused on the optimization of compositions and subsequent processing of these three materials to achieve dense and well-consolidated monolithic samples with 30 to 40% porosity and permeabilities of 1 millidarcy. At the close of this progress report the aluminum phosphate cements (APCs) and the wollastonite phosphate cements (WPCs) appear to show the most promise for continued development. Less progress has been made with the calcium phosphate cements (CPCs); their slurry viscosities are high (and difficult to measure) and they exhibit relatively short cure times of 2 to 3 hours with concomitant and excessive volatile (e.g. CO 2 ) generation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Development and Advanced Testing of DPC Cement Fillers

The fillers research and development (R&D) program, mostly experimental, is part of a broader R&D program that includes new process modeling and performance assessment of criticality effects and the overall importance of criticality to repository performance (consequence screening). A literature research and consultation effort with experts by Hardin and Brady (2018) identified several potentially effective and workable filler materials including cements (primarily phosphate based), moltenmetal alloys, and low-temperature glasses. Filler attributes were defined, and the preliminary lists were compared qualitatively. Further comparative analysis will be done (e.g., cost estimates) after experimental screening has narrowed the list of alternatives. The research presented here is focused Sandia’s efforts for the development of phosphate-based cement fillers. Molten metal filler research is an ongoing activity at Oak Ridge National Laboratories and is not discussed herein. After the completion of the FY20 research effort the following cement filler compositions were selected for further experimental development work and advanced testing in FY21: 1. Aluminum phosphate cements (APCs); more specifically aluminum oxide / aluminum phosphate (Al 2 O 3 / AlPO 4 ) cements in which Al 2 O 3 serves as the filler material bound by an AlPO 4 binder formed by the reaction of Al 2 O 3 with various phosphate sources; 2. Wollastonite phosphate cements (WPCs), specifically wollastonite and aluminum or calcium aluminum phosphates in which CaSiO 3 serves as the filler material bound by a calcium phosphate that serves as the binder; and 3. Calcium aluminate phosphate cements (CAPCs) specifically grossite (CaAl 4 O 7 ) and hibonite (CaAl 11 O 18 ) fillers bound by an aluminum phosphate that serves as the binder. This effort focused on the optimization and subsequent processing of these three cements to achieve dense and well-consolidated monolithic samples. Upon completion of the FY21 effort the aluminum phosphate cements (APCs) and the calcium aluminate phosphate cements (CAPCs) show the most promise for advanced testing and scale up. We will begin the work in FY22 focused on testing the performance of these two cements in small scale DPCs as well as advanced materials testing to evaluate cement performance under expected radiation doses and representative post-closure geochemical environments.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

“Shoulda, Coulda, Woulda”: Conceptualizing the Differences in Trust Between Human-Human Teaming and Human-Machine Teaming

Intelligent decision support systems (IDSSs) are machine teammates designed to facilitate better human decision-making in high-consequence domains such as health care, power grid operations, and fraud detection. IDSSs identify patterns in datasets and provide intelligent decision-making recommendations to human teammates. However, previous research indicates that humans often trust IDSS recommendations less than the recommendations from their human teammates, even when the machine teammate is more accurate. To conceptualize why trust differs, we review the literature surrounding trust, error, and predictability. Then, we compile and compare participant trust ratings and decision-making in an abridged systematic review of previous studies manipulating teammate type, error rate, and error type. Finally, we conduct a content analysis of participants’ qualitative responses to trust queries from a survey on generative language models. Results suggest that humans may trust IDSS teammates less than other human teammates because of differences in (1) interaction complexity, (2) blame attribution, and (3) swift trust. We conclude that human factors practitioners should collaborate with data scientists and domain experts to build and maintain trust in IDSSs by anthropomorphizing algorithms, matching mental models, and considering individual differences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Pathways for Agricultural Decarbonization in the United States

In the United States, agricultural production is both a significant source of greenhouse gases (GHGs) (Environmental Protection Agency (EPA), 2022) and uniquely susceptible to climate change impacts (Vermeulen et al., 2012). Decarbonization solutions have been proposed for addressing agricultural GHGs; however, research has been limited in synthesizing qualitative and quantitative analysis of potential GHG mitigation solutions in the United States. In this report, we review U.S. agricultural GHG sources by activity and quantify potential mitigation solutions based on a comprehensive data and literature analysis. We also discuss agricultural carbon sequestration options to offset GHG emissions. In our analysis, we identified two significant and hard-to-abate GHG sources (N 2 O from soil management, and CH 4 from enteric fermentation from livestock) as well as high-impact GHG mitigation solutions (e.g. agroforestry, reforestation, and biochar application) and cross-cutting GHG mitigation solutions (renewable energy production, precision agriculture, no-till, integrated nutrient management, and biochar). This report is meant to provide initial analysis and establish a foundation for future agricultural decarbonization research - it is not an exhaustive analysis of all available studies. However, to our knowledge this report is the most comprehensive assessment of agricultural GHG emissions and associated mitigation opportunities in the United States to date. Future empirical research is recommended to close research gaps in different climates, soils, and agricultural systems. Meta-analyses for all mitigation solutions would increase confidence in the estimated GHG mitigation potentials. To conclude this report, we discuss short-term and long-term pathways for agricultural decarbonization in the United States, the importance of accounting for total GHG fluxes, potential co-benefits of agricultural decarbonization, analysis of study data confidence, and research gaps.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1964

Sonic Booms from Aircraft in Maneuvers

Superboom measurements and calculated pressure patterns have been made for fighter aircraft in level accelerated flight and in turn maneuvers. A summary of the main findings of these superboom studies, qualitative comparisons with analysis, and a physical explanation of some of the observed phenomena are presented. From 2 to 6 booms were observed (compared with normally overserved 2 booms for steady flight), and pressure-buildup factors of from 2 to 4 were measured (depending on the type of maneuver and the location of the observer).The relative positions of the multiple shocks were predicted within 1,000 feet, and the location of the initial superboom impact was found to be predictable within about ±2 miles when the temperature profile and airplane position information were available.

SONIC BOOM↗