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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 1,081 records · Page 60
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Unpolarized transverse momentum distributions from a global fit of Drell-Yan and semi-inclusive deep-inelastic scattering data

We present an extraction of unpolarized transverse-momentum-dependent parton distribution and fragmentation functions based on more than two thousand data points from several experiments for two different processes: semi-inclusive deep-inelastic scattering and Drell-Yan production. The baseline analysis is performed using the Monte Carlo replica method and resumming large logarithms at N 3 LL accuracy. The resulting description of the data is very good (χ 2 /N dat = 1.06). For semi-inclusive deep-inelastic scattering, predictions for multiplicities are normalized by factors that cure the discrepancy with data introduced by higher-order perturbative corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Global Sensitivity Analysis of a Reactive Transport Model for Mineral Scale Formation During Hydraulic Fracturing

Injection of water-based hydraulic fracturing fluid (HFF) into tight shale gas/oil formations can increase formation permeability and enhance production rates, but this process frequently causes mineral scale formation that can occlude pore space and hinder flow. To identify the most important factors that control the formation of mineral scales, we applied a novel global sensitivity analysis method—distance-based generalized sensitivity analysis (DGSA)—to a reactive transport model (RTM) that was previously built and calibrated to simulate precipitation of barite [BaSO4] and iron (hydr)oxide [Fe(OH) 3 ] in shale matrices and on fracture surfaces. Reactive transport simulations were run with model parameters randomly sampled based on assigned uncertainties. Modeling results for barite and Fe(OH)3 formation were clustered using machine-learning algorithms. A list of ranked critical input parameters was obtained after statistical quantification of cumulative distribution functions of input parameters. We found that barite formation is most sensitive to the rate of sulfate ion generation, which is determined by the pyrite dissolution rate coefficient and oxidant availability. In addition, barite formation is sensitive to the initial amounts of barite in HFF and shale, followed by barite thermodynamics/kinetics. For Fe(OH) 3 formation, the ranked factors are Fe(OH)3 precipitation rate coefficients, initial HFF pH, initial Fe(OH) 3 amount in HFF, and oxidant availability. Overall, our results provide insights into managing mineral scale formation during hydraulic fracturing to enhance production. Meanwhile, this study serves as an example of global sensitivity analysis of RTMs using the efficient, straightforward, and open-source DGSA method.

58 GEOSCIENCES↗
DOE OSTI2020

Comparison of improved TMD and CGC frameworks in forward quark dijet production

For studying small- x gluon saturation in forward dijet production in high-energy dilute-dense collisions, the improved TMD (ITMD) factorization formula was recently proposed. In the Color Glass Condensate (CGC) framework, it represents the leading term of an expansion in inverse powers of the hard scale. It contains the leading-twist TMD factorization formula relevant for small gluon’s transverse momentum k t , but also incorporates an all-order resummation of kinematical twists, resulting in a proper matching to high-energy factorization at large k t . In this paper, we evaluate the accuracy of the ITMD formula quantitatively, for the case of quark dijet production in high-energy proton-proton( p + p ) and proton-nucleus ( p + A ) collisions at LHC energies. We do so by comparing the quark-antiquark azimuthal angle Δ ϕ distribution to that obtained with the CGC formula. For a dijet with each quark momentum p t much larger than the target saturation scale, Q s , the ITMD formula is a good approximation to the CGC formula in a wide range of azimuthal angle. It becomes less accurate as the jet p t ’s are lowered, as expected, due to the presence of genuine higher-twists contributions in the CGC framework, which represent multi-body scattering effects absent in the ITMD formula. We find that, as the hard jet momenta are lowered, the accuracy of ITMD start by deteriorating at small angles, in the high-energy-factorization regime, while in the TMD regime near Δ ϕ = π , very low values of p t are needed to see differences between the CGC and the ITMD formula. In addition, the genuine twists corrections to ITMD become visible for higher values of p t in p + A collisions, compared to p + p collisions, signaling that they are enhanced by the target saturation scale.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

The soil health assessment protocol and evaluation applied to soil organic carbon

The concept of soil health has evolved over the past several decades, recognizing that dynamic soil property response to management and land use is highly dependent on site-specific factors that must be considered when interpreting soil health measurements. Initially, the Soil Management Assessment Framework (SMAF) and Comprehensive Assessment of Soil Health (CASH) were developed and used globally for scoring soil health indicators. However, both SMAF and CASH frameworks were developed using a relatively small dataset and their interpretation curves were not validated at the nationwide scale. Expanding upon these concepts, we propose the Soil Health Assessment Protocol and Evaluation (SHAPE) tool. The SHAPE was developed using 14,680 soil organic C (SOC) observations from across the United States, and accounts for edaphic and climate factors at the continental scale. Data were compiled from the literature, the Cornell Soil Health Laboratory, and the Kellogg Soil Survey Laboratory. In this approach, scoring curves are Bayesian model-based estimates of the conditional cumulative distribution function (CDF) for defined soil peer groups reflecting five soil texture and five soil suborder classes adjusted for mean annual temperature and precipitation. Specifically, SHAPE produces scores between 0 and 1 (0–100%) for measured SOC values that reflect the quantile or position within the conditional CDF along with measures of uncertainty. Herein, we focus on development of the SHAPE scoring curve for SOC with our case studies. SHAPE is a flexible, quantitative tool that provides a regionally relevant interpretation of this key soil health indicator.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Wormhole calculus, replicas, and entropies

We investigate contributions of spacetime wormholes, describing baby universe emission and absorption, to calculations of entropies and correlation functions, for example those based on the replica method. We find that the rules of the “wormhole calculus”, developed in the 1980s, together with standard quantum mechanical prescriptions for computing entropies and correlators, imply definite rules for limited patterns of connection between replica factors in simple calculations. These results stand in contrast with assumptions that all topologies connecting replicas should be summed over, and call into question the explanation for the latter. In a “free” approximation baby universes introduce probability distributions for coupling constants, and we review and extend arguments that successive experiments in a “parent” universe increasingly precisely fix such couplings, resulting in ultimately pure evolution. Once this has happened, the nontrivial question remains of how topology-changing effects can modify the standard description of black hole information loss.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Novel Rosenbluth extraction framework for Compton form factors from deeply virtual exclusive experiments

We use a generalization of the Rosenbluth separation method for a model independent simultaneous extraction of the Compton Form Factors $\mathscr{H}$ and $\mathscr{E}$ from virtual Compton scattering data on an unpolarized target. A precise evaluation of $\mathscr{H}$ and $\mathscr{E}$ enabled by the proposed method, is the first step towards pinning down the distribution of angular momentum inside the proton.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Correlated mechanochemical maps of Arabidopsis thaliana primary cell walls using atomic force microscope infrared spectroscopy

Spatial heterogeneity in composition and organisation of the primary cell wall affects the mechanics of cellular morphogenesis. However, directly correlating cell wall composition, organisation and mechanics has been challenging. To overcome this barrier, we applied atomic force microscopy coupled with infrared (AFM-IR) spectroscopy to generate spatially correlated maps of chemical and mechanical properties for paraformaldehyde-fixed, intact Arabidopsis thaliana epidermal cell walls. AFM-IR spectra were deconvoluted by non-negative matrix factorisation (NMF) into a linear combination of IR spectral factors representing sets of chemical groups comprising different cell wall components. This approach enables quantification of chemical composition from IR spectral signatures and visualisation of chemical heterogeneity at nanometer resolution. Cross-correlation analysis of the spatial distribution of NMFs and mechanical properties suggests that the carbohydrate composition of cell wall junctions correlates with increased local stiffness. Together, our work establishes new methodology to use AFM-IR for the mechanochemical analysis of intact plant primary cell walls.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Large Scale Study of Ligand–Protein Relative Binding Free Energy Calculations: Actionable Predictions from Statistically Robust Protocols

The accurate and reliable prediction of protein–ligand binding affinities can play a central role in the drug discovery process as well as in personalized medicine. Of considerable importance during lead optimization are the alchemical free energy methods that furnish an estimation of relative binding free energies (RBFE) of similar molecules. Recent advances in these methods have increased their speed, accuracy, and precision. This is evident from the increasing number of retrospective as well as prospective studies employing them. However, such methods still have limited applicability in real-world scenarios due to a number of important yet unresolved issues. Here, we report the findings from a large data set comprising over 500 ligand transformations spanning over 300 ligands binding to a diverse set of 14 different protein targets which furnish statistically robust results on the accuracy, precision, and reproducibility of RBFE calculations. We use ensemble-based methods which are the only way to provide reliable uncertainty quantification given that the underlying molecular dynamics is chaotic. These are implemented using TIES (Thermodynamic Integration with Enhanced Sampling). Results achieve chemical accuracy in all cases. Ensemble simulations also furnish information on the statistical distributions of the free energy calculations which exhibit non-normal behavior. We find that the “enhanced sampling” method known as replica exchange with solute tempering degrades RBFE predictions. We also report definitively on numerous associated alchemical factors including the choice of ligand charge method, flexibility in ligand structure, and the size of the alchemical region including the number of atoms involved in transforming one ligand into another. Our findings provide a key set of recommendations that should be adopted for the reliable application of RBFE methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Strong Negative Thermal Expansion in a Low-Cost and Facile Oxide of Cu 2 P 2 O 7

Negative thermal expansion (NTE) behaviors have been observed in various types of compounds. The achievement in the merits of promising low-cost and facile NTE oxides remains challenging. In the present work, a simple and low-cost Cu 2 P 2 O 7 has been found to exhibit the strongest NTE among the oxides (alpha(v) similar to -27.69 X 10 -6 K -1 , 5-375 K). The complex NTE mechanism has been investigated by the combined methods of high-resolution synchrotron X-ray diffraction, neutron powder diffraction, X-ray pair distribution function, extended X-ray absorption fine structure spectroscopy, and density functional theory calculations. Interesting, the direct experimental evidence reveals that the coupling twist and rotation of PO 4 and CuO 5 polyhedra are the inherent factors for the NTE nature of Cu 2 P 2 O 7 , which is triggered by the transverse vibrations of oxygen atoms. The present new NTE material of Cu 2 P 2 O 7 also has been verified for the practical application.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Time Series Dimension Reduction for Surrogate Models of Port Scanning Cyber Emulations

Surrogate model development is a key resource in the scientific modeling community for providing computational expedience when simulating complex systems without loss of great fidelity. The initial step to development of a surrogate model is identification of the primary governing components of the system. Principal component analysis (PCA) is a widely used data science technique that provides inspection of such driving factors, when the objective for modeling is to capture the greatest sources of variance inherent to a dataset. Although an efficient linear dimension reduction tool, PCA makes the fundamental assumption that the data is continuous and normally distributed. Thus, it provides ideal performance when these conditions are met. In the case for which cyber emulations provide realizations of a port scanning scenario, the data to be modeled follows a discrete time series function comprised of monotonically increasing piece-wise constant steps. The sources of variance are related to the timing and magnitude of these steps. Therefore, we consider using XPCA, an extension to PCA for continuous and discrete random variates. This report provides the documentation of the trade-offs between the PCA and XPCA linear dimension reduction algorithms, for the intended purpose to identify key components of greatest variance in our time series data. These components will ultimately provide the basis for future surrogate models of port scanning cyber emulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Assessing the drivers of Isoprene SOA: laboratory studies, field observations and modeling (Final Technical Report)

This report describes the research results and products stemming from the funding award DE-SC0018221. The main goals of this project were to develop a quantitative understanding of the factors driving secondary organic aerosol (SOA) formation from biogenic volatile organic compounds, namely isoprene and monoterpenes, using a combination of laboratory measurements, field data analysis, and modeling. Specifically, we aimed to: 1) develop an observationally constrained volatility distribution of trace gases produced from the oxidation of biogenic hydrocarbons that can explain the formation of SOA from in situ observations made during DOE ASR/ARM field campaigns such as HI-SCALE and BAECC 2) use new and existing (e.g. DOE ASR funded SOAFFEE experiments) laboratory chamber experiments to develop detailed parameterizations of isoprene-derived epxoy diol (IEPOX) reactive uptake, including product branching, product volatility, and solubility constants, as well as SOA formation generally from the formation of highly oxygenated organic molecules (HOM) formed from isoprene and monoterpene photo-oxidation that can be directly incorporated into models. 3) collaborate with PNNL modeling teams to incorporate new parameterizations into detailed box models, such as MOSAIC, and regional or Earth System models such as WRF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Implementation Aspects of Smart Grids Cyber-Security Cross-Layered Framework for Critical Infrastructure Operation

Communication networks in power systems are a major part of the smart grid paradigm. It enables and facilitates the automation of power grid operation as well as self-healing in contingencies. Such dependencies on communication networks, though, create a roam for cyber-threats. An adversary can launch an attack on the communication network, which in turn reflects on power grid operation. Attacks could be in the form of false data injection into system measurements, flooding the communication channels with unnecessary data, or intercepting messages. Using machine learning-based processing on data gathered from communication networks and the power grid is a promising solution for detecting cyber threats. In this paper, a co-simulation of cyber-security for cross-layer strategy is presented. The advantage of such a framework is the augmentation of valuable data that enhances the detection as well as identification of anomalies in the operation of the power grid. The framework is implemented on the IEEE 118-bus system. The system is constructed in Mininet to simulate a communication network and obtain data for analysis. A distributed three controller software-defined networking (SDN) framework is proposed that utilizes the Open Network Operating System (ONOS) cluster. According to the findings of our suggested architecture, it outperforms a single SDN controller framework by a factor of more than ten times the throughput. This provides for a higher flow of data throughout the network while decreasing congestion caused by a single controller’s processing restrictions. Furthermore, our CECD-AS approach outperforms state-of-the-art physics and machine learning-based techniques in terms of attack classification. The performance of the framework is investigated under various types of communication attacks.

cross-layered↗
DOE OSTI2022

Effects of Impact and Target Parameters on the Results of a Kinetic Impactor: Predictions for the Double Asteroid Redirection Test (DART) Mission

Abstract The Double Asteroid Redirection Test (DART) spacecraft will impact into the asteroid Dimorphos on 2022 September 26 as a test of the kinetic impactor technique for planetary defense. The efficiency of the deflection following a kinetic impactor can be represented using the momentum enhancement factor, β , which is dependent on factors such as impact geometry and the specific target material properties. Currently, very little is known about Dimorphos and its material properties, which introduces uncertainty in the results of the deflection efficiency observables, including crater formation, ejecta distribution, and β . The DART Impact Modeling Working Group (IWG) is responsible for using impact simulations to better understand the results of the DART impact. Pre-impact simulation studies also provide considerable insight into how different properties and impact scenarios affect momentum enhancement following a kinetic impact. This insight provides a basis for predicting the effects of the DART impact and the first understanding of how to interpret results following the encounter. Following the DART impact, the knowledge gained from these studies will inform the initial simulations that will recreate the impact conditions, including providing estimates for potential material properties of Dimorphos and β resulting from DART’s impact. This paper summarizes, at a high level, what has been learned from the IWG simulations and experiments in preparation for the DART impact. While unknown, estimates for reasonable potential material properties of Dimorphos provide predictions for β of 1–5, depending on end-member cases in the strength regime.

58 GEOSCIENCES↗
DOE OSTI2022

MSW Variability Mapping and Conversion to Biofuel

MSW (Municipal Solid Waste) is a form of biomass which consists of categorized components of waste/trash. The general categories are paper, yard trash, construction & debris, appliances, tires, glass, metals, aluminum & steel cans, plastics, organics, inorganics, and HHW (Household Hazardous Waste). This project focuses on the factors within a region or population that contribute to variability in the composition of MSW and in turn MSW’s convertibility to biofuel. A list of contributors was determined (Social Vulnerability Index, Access to Public Transportation, Racial Distribution, GDP, Personal Income) and then JMP was used to perform a Multivariate analysis to determine correlations and a Partial Least-Squares regression to determine Variable Importance Plots for each MSW category. In addition to data analysis, the convertibility of MSW to biofuel was studied via microwave pyrolysis system in order to separate and characterize the various gaseous and bio-oil products.

09 BIOMASS FUELS↗
DOE OSTI2026

Subsurface mechanical damage of fused silica glass during grinding by various sub-aperture tools with and without ultrasonics

The subsurface mechanical damage (SSD) depth after grinding fused silica glass with a comprehensive set of sub-aperture fixed abrasive grinding tools [cup, wheel, belt, pad, and rotary face mill (with and without ultrasonics)] and process parameters has been statistically measured using the taper wedge technique and evaluated. Consistent with a previously reported grinding model [J. Non-Cryst. Solids 352, 5601–5617 (2006) Crossref , Materials Science and Technology of Optical Fabrication (Wiley & Sons, 2018)], based on the sliding indentation fracture by sliding particles or asperities where the normal load per particle determines the depth of the fracture (and ultimately the overall SSD depth), the dominant factor controlling SSD depth was found to be the abrasive size regardless of the tool type and process conditions. Compared to full aperture grinding methods, the overall SSD depth was higher using the sub-aperture tools, likely due to the higher effective pressure and higher load per particle distribution. Here, in addition to abrasive size, a significant reduction in SSD depth was achieved by: (1) reducing the load distribution on the abrasive particles via increase in contact area and/or decrease in mechanical loading; (2) using a more compliant host tool medium; and (3) in what we believe is a more novel way, using ultrasonics. Combining low abrasive size, larger contact area, and a compliant host, the 6 µm diamond in a resin matrix (Trizact) on a foam pad led to very low SSD depth (~ 4.6 µm), relatively fast grinding rate (186 mm 3 /h), and little or no figure degradation. This grinding tool/process is an attractive choice for final grind, resulting in significantly reduced polish out (i.e., “grey out”) times. With the rotary face mill tool, the use of ultrasonics consistently led to a SSD depth reduction (ranging from 17%–34%). A new fracture mechanics-based model, to the best of our knowledge, where the relevant normal load is parallel to the feed direction, has been developed to explain how ultrasonics leads to lower SSD depth. The key factors, supported by finite element stress analysis and load measurements, are (1) the initiation of fractures at higher z heights during the tool’s ultrasonic vertical oscillations, thus propagating less deep into workpiece; (2) reduction in load (and therefore reduction in fracture propagation distance) due to smaller tool-workpiece feed direction contact area (again caused by higher heights relative to depth of cut); (3) upward movement of the tool during oscillation leads to fracturing toward the surface instead into the depth; and finally (4) at tool’s lowest point of oscillation cycle, there may not be enough time for the fracture to propagate to its full length.

Optics and optical instruments↗
DOE OSTI2020

Development of interatomic potential for Al–Tb alloys using a deep neural network learning method

An interatomic potential for the Al–Tb alloy around the composition of Al 90 Tb 10 is developed using the deep neural network (DNN) learning method. The atomic configurations and the corresponding total potential energies and forces on each atom obtained from ab initio molecular dynamics (AIMD) simulations are collected to train a DNN model to construct the interatomic potential for the Al–Tb alloy. Here we show that the obtained DNN model can well reproduce the energies and forces calculated by AIMD simulations. Molecular dynamics (MD) simulations using the DNN interatomic potential also accurately describe the structural properties of the Al 90 Tb 10 liquid, such as partial pair correlation functions (PPCFs) and bond angle distributions, in comparison with the results from AIMD simulations. Furthermore, the developed DNN interatomic potential predicts the formation energies of the crystalline phases of the Al–Tb system with an accuracy comparable to ab initio calculations. The structure factors of the Al 90 Tb 10 metallic liquid and glass obtained by MD simulations using the developed DNN interatomic potential are also in good agreement with the experimental X-ray diffraction data. The development of short-range order (SRO) in the Al 90 Tb 10 liquid and the undercooled liquid is also analyzed and three dominant SROs, i.e., Al-centered distorted icosahedron (DISICO) and Tb-centered ‘3661’ and ‘15551’ clusters, respectively, are identified.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A gyrokinetic simulation model for 2D equilibrium potential in the scrape-off layer of a field-reversed configuration

The equilibrium potential structure in the scrape-off layer (SOL) of the field-reversed configuration (FRC) can be affected by the penetration of edge biasing applied at the divertor ends. The primary focus of the paper is to establish a formulation that accurately captures both parallel and radial variations of the two-dimensional (2D) potential in SOL. The formulation mainly describes a quasi-neutral plasma with a logical sheath boundary. A full-f gyrokinetic ion model and a massless electron model are implemented in the GTC-X code to solve for the self-consistent equilibrium potential, given fixed radial potential profiles at the boundaries. The first essential point of this 2D model lies in its ability to couple radial and parallel dynamics stemming from resistive currents and drag force on ions. The model successfully recovers the fluid force balance and continuity equations. These collisional effects on 2D potential mainly appear through the density profile changes, modifying the potential through electron pressure gradient. This means an accurate prescription of electron density and temperature profiles is important in predicting the potential structure in the FRC SOL. The Debye sheath potential and the potential profiles applied at the boundaries can be additional factors contributing to the 2D variations in SOL. This comprehensive full-f scheme holds promise for future investigations into turbulent transport in the presence of the self-consistent 2D potential together with the non-Maxwellian distributions and open boundary conditions in the FRC SOL.

Physics↗
DOE OSTI2021

Ideal internal kink stability in presence of plasma flow and neoclassical toroidal viscosity due to energetic particles

Abstract The influence of energetic particles (EPs) on the ideal internal kink mode, in rotating tokamak plasmas, is numerically investigated by simultaneously solving MHD-kinetic hybrid equations together with a toroidal momentum balance equation utilizing the MARS-Q code (Liu et al 2013 Phys. Plasmas 20 042503). The neoclassical toroidal viscous (NTV) torque, induced by precessional drift resonances of trapped energetic particles, acts as the momentum sink term to damp the plasma flow. Quasi-linear initial value simulations show local reduction of the flow amplitude and enhancement of the flow shear near the q = 1 rational surface ( q is the safety factor) due to EP induced NTV. Both effects in turn destabilize the internal kink mode. These numerical findings are robust against the initial linear stability of internal kink, the initial plasma flow profile, as well as the equilibrium distribution model for EPs.

Physics↗