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At least 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Orphaned oil and gas well methane emission rates quantified using Gaussian plume inversions of ambient observations

Abstract. Annually, ∼ 3.6 million abandoned oil and gas wells in the US emit a combined ∼ 2.6 Tg methane (CH4), adversely affecting climate and regional air quality. However, these estimates depend on emission factors derived from measuring subpopulations of wells that vary by orders of magnitude due to very limited field sampling and poorly characterized distributions. Currently, US protocols to remediate orphaned wells lacks standardized quantification methods needed to both prioritize plugging and account for emission reductions. Therefore, sensitive, reliable, affordable, and scalable CH4 flux quantification methods are needed. We report the use of a simple Gaussian plume method where the dispersion parameters are constrained by in situ ground measurements of CH4 concentration at four locations 7.5–49 m downwind of the orphan well as well as local winds to estimate the leak rate from an orphan well. We derive a flux of 10.53 ± 1.16 kg CH4 h−1 during a venting procedure in April 2023 that agrees with the directly measured volumetric flow rate of 9.00 ± 0.25 kg CH4 h−1. This is 71 % greater than the 5.3 kg CH4 h−1 flux measured 7 months prior. Additionally, we discovered a secondary leak through the surface casing inferred as 0.43–0.67 kg CH4 h−1 both by our ground Gaussian analysis and by transecting the plume with an uncrewed aerial system (UAS). We show that in situ determination of the dispersion parameters used in our Gaussian inversions allows us to measure methane emissions to 15 % accuracy, significantly reducing errors when compared to the standard practice of assuming stability class. Our results help develop simpler methods and protocols for robust orphan well emission quantification that can be used for reporting.

Follansbee, Emily↗
DOE OSTI2023

Residual loss due to magnetic flux trapping in niobium superconducting microwave cavities

One of the significant source of radio frequency loss in superconducting microwave cavities is the trapped residual magnetic field during the cooldown due to the incomplete Messier effect. The sensitivity of flux trapping depends on the distribution of impurities, network of dislocations and defects which pin vortices. Recent advancement in cavity processing techniques resulted in very high quality factors with impurity doping, however the rf loss related to the flux trapping increases. High quality factor in SRF cavities is not only limited to particle accelerators but also emerging as an application to quantum computing and quantum information science. In this presentation, we present the results of measurements of flux trapping sensitivity on several 1.3 GHz elliptical accelerating cavities with different grain size, impurity content and surface preparations.

Dhakal, P.↗
DOE OSTI2024

Phenomenology of TMD parton distributions in Drell-Yan and 𝑍 0 boson production in a hadron structure oriented approach

We present a first practical implementation of a recently proposed hadron structure oriented (HSO) approach to transverse momentum dependent (TMD) phenomenology applied to Drell-Yan-like processes, including lepton pair production at moderate 𝑄 2 and 𝑍 0 boson production. We compare and contrast general features of our methodology with other common practices and emphasize aspects that we view as improvements. Separately, we discuss the importance of treatments that preserve various theoretical properties of the nonperturbative parts of TMD parametrizations for future applications that have the extraction of hadron structure as a primary goal. These include the HSO’s preservation of a basic TMD parton-model-like framework even while accounting for full TMD factorization and evolution, explicit preservation of the integral relationship between TMD and collinear parton density functions, and the ability to meaningfully compare different theoretical models of nonperturbative TMD parton distributions. In our examples, we show that there is significant sensitivity at moderate 𝑄 2 to both the form of the nonperturbative transverse momentum dependence and the parametrization of collinear parton densities. However, we also find that evolving to 𝑄 2 =𝑀$^2_𝑍$, without fitting, results in a satisfactory postdiction of existing data for 𝑍0 production, nearly independently of the modeling of nonperturbative transverse momentum behavior. We argue that this demonstrates that moderate 𝑄 measurements should be given greater weight than high 𝑄 measurements in extractions of nonperturbative transverse momentum dependence. We also obtain new extractions of the nonperturbative Collins-Soper kernel within the HSO approach. We discuss its features and compare with some earlier extractions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework

In this work, generalized polynomial chaos (gPC) expansion for land surface model parameter estimation is evaluated. We perform inverse modeling and compute the posterior distribution of the critical hydrological parameters that are subject to great uncertainty in the Community Land Model (CLM) for a given value of the output LH. The unknown parameters include those that have been identified as the most influential factors on the simulations of surface and subsurface runoff, latent and sensible heat fluxes, and soil moisture in CLM4.0. We set up the inversion problem in the Bayesian framework in two steps: (i) building a surrogate model expressing the input–output mapping, and (ii) performing inverse modeling and computing the posterior distributions of the input parameters using observation data for a given value of the output LH. The development of the surrogate model is carried out with a Bayesian procedure based on the variable selection methods that use gPC expansions. Our approach accounts for bases selection uncertainty and quantifies the importance of the gPC terms, and, hence, all of the input parameters, via the associated posterior probabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Matrix-free subcell residual distribution for Bernstein finite elements: Monolithic limiting

This paper is focused on the aspects of limiting in residual distribution (RD) schemes for high-order finite element approximations to advection problems. Both continuous and discontinuous Galerkin methods are considered in this work. Discrete maximum principles are enforced using algebraic manipulations of element contributions to the global nonlinear system. The required modifications can be carried out without calculating the element matrices and assembling their global counterparts. The components of element vectors associated with the standard Galerkin discretization are manipulated directly using localized subcell weights to achieve optimal accuracy. Low-order nonlinear RD schemes of this kind were originally developed to calculate local extremum diminishing predictors for flux-corrected transport (FCT) algorithms. In the present paper, we incorporate limiters directly into the residual distribution procedure, which makes it applicable to stationary problems and leads to well-posed nonlinear discrete problems. To circumvent the second-order accuracy barrier, the correction factors of monolithic limiting approaches and FCT schemes are adjusted using smoothness sensors based on second derivatives. Finally, the convergence behavior of presented methods is illustrated by numerical studies for two-dimensional test problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Parametrization of Generalized Parton Distributions from 𝑡-Channel String Exchange in AdS Spaces

We introduce a string-based parametrization for nucleon quark and gluon generalized parton distributions (GPDs) that is valid for all skewness. Our approach leverages conformal moments, representing them as the sum of spin-𝑗 nucleon 𝐴-form factor and skewness-dependent spin-𝑗 nucleon 𝐷-form factor, derived from 𝑡-channel string exchange in AdS spaces consistent with Lorentz invariance and unitarity. This model-independent framework, satisfying the polynomiality condition due to Lorentz invariance, uses Mellin moments from empirical data to estimate these form factors. With just five Regge slope parameters, our method accurately produces various nucleon quark GPD types and symmetric nucleon gluon GPDs through pertinent Mellin-Barnes integrals. Our isovector nucleon quark GPD is in agreement with existing lattice data, promising to improve the empirical extraction and global analysis of nucleon GPDs in exclusive processes, by avoiding the deconvolution problem at any skewness, for the first time.

QCD phenomenology↗
DOE OSTI2025

Complete definition of 𝑁 →Δ transition generalized parton distributions

We revisit the definition of the leading-twist chiral-even generalized parton distributions (GPDs) for 𝑁 →Δ baryon transitions. We identify and address deficiencies in previous definitions of the transition GPDs inspired by the transition form factors of the vector and axial vector currents. Through systematic analysis of all possible covariant structures, respecting discrete symmetries and the baryon spinor equations of motion, we derive complete sets of independent structures for the transition matrix elements of the vector and axial vector partonic operators. They contain additional structures proportional to the light-cone vector, corresponding to transition GPDs of vanishing first moment, which were not included in previous parametrizations. Their presence is confirmed independently by the light-front multipole expansion and the cross-channel SO(3) partial-wave analysis of the transition matrix elements. Our analysis provides a complete definition of the 𝑁 →Δ transition GPDs for use in theoretical and phenomenological studies.

baryons↗
DOE OSTI2020

Damped Ly α absorbers and atomic hydrogen in galaxies: the view of the GAEA model

ABSTRACT Using the GAEA semi-analytic model, we analyse the connection between Damped Ly α systems (DLAs) and H i in galaxies. Our state-of-the-art semi-analytic model is tuned to reproduce the local galaxy H i mass function, and that also reproduces other important galaxy properties, including the galaxy mass–gas metallicity relation. To produce catalogues of simulated DLAs we throw 105 random lines of sight in a composite simulated volume: dark matter haloes with log$(\frac{M_{200}}{ {\rm M}_{\odot }}) \ge 11.5$ are extracted from the Millennium Simulation, while for $9.2 \le \log (\frac{M_{200}}{ \mathrm{M}_{\odot }})\lt 11.5$ we use the Millennium II, and for $8 \le \log (\frac{M_{200}}{\mathrm{M}_{\odot }}) \lt 9.2$ a halo occupation distribution model. At 2 < z < 3, where observational data are more accurate, our fiducial model predicts the correct shape of the column density distribution function, but its normalization falls short of the observations, with the discrepancy increasing at higher redshift. The agreement with observations is significantly improved increasing both the H i masses and the disc radii of model galaxies by a factor of 2, as implemented ‘a posteriori’ in our 2M−2R model. In the redshift range of interest, haloes with $M_{200} \ge {10}^{11} \, \mathrm{M}_{\odot }$ give the major contribution to ΩDLA, and the typical DLA host halo mass is $\sim \!{10}^{11} \, \mathrm{M}_{\odot }$. The simulated DLA metallicity distribution is in relatively good agreement with observations, but our model predicts an excess of DLAs at low metallicities. Our results suggest possible improvements for the adopted modelling of the filtering mass and metal ejection in low-mass haloes.

Di Gioia, Serafina↗
DOE OSTI2025

Quantum stresses in the hydrogen atom

Gravitational form factors are often interpreted as providing access to stresses inside hadrons, in particular through Fourier transforms of the form factors 𝐷 and $\bar{𝑐}$. Some researchers, however, have expressed skepticism of this interpretation. I revisit the question, and argue that it is indeed appropriate to interpret these quantities as stress distributions. I consider the hydrogen atom’s ground state as a familiar example, and use the pilot wave interpretation of quantum mechanics to give the distributions a clear meaning. A striking result is that $\bar{𝑐}$—rather than 𝐷—quantifies the force law binding the system, which can be understood through Cauchy’s first law of motion.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2024

Ultrawide bandgap semiconductor heterojunction p–n diodes with distributed polarization-doped p-type AlGaN layers on bulk AlN substrates

Ultrawide bandgap heterojunction p–n diodes with polarization-induced AlGaN p-type layers are demonstrated using plasma-assisted molecular beam epitaxy on bulk AlN substrates. Current–voltage characteristics show a turn-on voltage of Vbi≈5.5 V, a minimum room temperature ideality factor of η≈1.63, and more than 12 orders of current modulation at room temperature. A stable current operation of the ultrawide bandgap semiconductor diode is measured up to a temperature of 300 °C. The one-sided n+–p heterojunction diode design enables a direct measurement of the spatial distribution of polarization-induced mobile hole density in the graded AlGaN layer from the capacitance–voltage profile. The measured average mobile hole density is p∼5.7×1017 cm−3, in close agreement with what is theoretically expected from distributed polarization doping. Light emission peaked at 260 nm (4.78 eV) observed in electroluminescence corresponds to interband radiative recombination in the n+ AlGaN layer. A much weaker deep-level emission band observed at 3.4 eV is attributed to cation-vacancy and silicon complexes in the heavily Si-doped AlGaN layer. These results demonstrate that distributed polarization doping enables ultrawide bandgap semiconductor heterojunction p–n diodes that have wide applications ranging from power electronics to deep-ultraviolet photonics. These devices can operate at high temperatures and in harsh environments.

Physics↗
DOE OSTI2020

Default Radioactive and Hazardous Waste Management (RHWM) Dose Conversion Factors (DCFs) and Weighting Factors and plutonium-239 equivalent Curie (PE-Ci) methodology for acceptance into the Waste Storage Facilities

DOE-STD-5506-2007 (Ref. 1) is the standard that provides the methodology for preparing hazard analysis and accident analysis for transuranic (TRU) waste facilities. The Waste Storage Facilities hazard and accident analysis for the DSA is developed in accordance with DOE-STD- 5506-2007. Two related issues need to be addressed when implementing DOE-STD-5506-2007 regarding the calculation of consequences from TRU waste releases in accident analysis: Consequences determined in accident analysis must be modeled using inhalation Dose Conversion Factors (DCFs) that are consistent with those from the International Commission on Radiological Protection Publication 72 (ICRP-72, Ref. 2).; The use of a statistical Material at Risk (MAR) representing the distribution of radiological loading of TRU waste containers based on the use of a plutonium-239 equivalent Curie (PE-Ci) methodology. The PE-Ci methodology simplifies accident analysis by allowing one to model releases based on the Curie value of one standard nuclide (e.g., Pu-239) instead of needing to model releases for every potential nuclide of interest. This is accomplished by normalizing the Curie value of all nuclides to a single Curie value of a standard nuclide by using a Weighting Factor that is a ratio of the DCFs associated with the nuclides and that of the standard nuclide. By using the ICRP-72 DCFs to calculate PE-Ci values used in the statistical MAR, the accident analysis that uses that statistical MAR will be consistent with the consequence methodology identified in DOE-STD- 5506-2007.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Generalized parton distributions from symbolic regression

AI/ML informed Symbolic Regression is the next stage of scientific modeling. We utilize a highly customizable symbolic regression package “PySR” to model the x and t dependence of the flavor isovector combination Hu-d(x, t, ) at = 0. These PySR models were trained on GPD results provided by both Lattice QCD and phenomenological sources GGL, GK, and VGG. We demonstrate, for the first time, the consistency and systematic convergence of Symbolic Regression by quantifying the disparate models through their Taylor expansion coefficients. In addition to PySR penalizing models with higher complexity and mean-squared error, we implement schemes that test specific physics hypotheses, including force-factorized x and t dependence and Regge behavior in PySR GPDs. We show that PySR can identify factorizing GPD sources based on their response to the Force-Factorized model. Here, knowing the precise behavior of the GPDs, and their uncertainties in a wide range in x and t, crucially impacts our ability to concretely and quantitatively predict hadronic spatial distributions and their derived quantities.

Dotson, Andrew [New Mexico State University, Las C↗
DOE OSTI2022

A new calibration method for charm jet identification validated with proton-proton collision events at $\sqrt{s}$ =13 TeV

Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb$^{-1}$ at √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evaluation of the excitation spectra with diffusion Monte Carlo on an auxiliary bosonic ground state

We aim to improve upon the variational Monte Carlo (VMC) approach for excitations replacing the Jastrow factor by an auxiliary bosonic (AB) ground state and multiplying it by a fermionic component factor. The instantaneous change in imaginary time of an arbitrary excitation in the original interacting fermionic system is obtained by measuring observables via the ground-state distribution of walkers of an AB system that is subject to an auxiliary effective potential. The effective potential is used to (i) drive the AB system’s ground-state configuration space toward the configuration space of the excitations of the original fermionic system and (ii) subtract from a diffusion Monte Carlo (DMC) calculation contributions that can be included in conventional approximations, such as mean-field and configuration interaction (CI) methods. In this novel approach, the AB ground state is treated statistically in DMC, whereas the fermionic component of the original system is expanded in a basis. The excitation energies of the fermionic eigenstates are obtained by sampling a fermion–boson coupling term on the AB ground state. We show that this approach can take advantage of and correct for approximate eigenstates obtained via mean-field calculations or truncated interactions. We demonstrate that the AB ground-state factor incorporates the correlations missed by standard Jastrow factors, further reducing basis truncation errors. Relevant parts of the theory have been tested in soluble model systems and exhibit excellent agreement with exact analytical data and CI and VMC approaches. In particular, for limited basis set expansions and sufficient statistics, AB approaches outperform CI and VMC in terms of basis size for the same systems. The implementation of this method in current codes, despite being demanding, will be facilitated by reusing procedures already developed for calculating ground-state properties with DMC and excitations with VMC.

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

Machine Learning Analysis of Hydrologic Exchange Flows and Transit Time Distributions in a Large Regulated River

Hydrologic exchange between river channels and adjacent subsurface environments is a key process that influences water quality and ecosystem function in river corridors. High-resolution numerical models were often used to resolve the spatial and temporal variations of exchange flows, which are computationally expensive. In this study, we adopt Random Forest (RF) and Extreme Gradient Boosting (XGB) approaches for deriving reduced order models of hydrologic exchange flows and associated transit time distributions, with integrated field observations (e.g., bathymetry) and hydrodynamic simulation data (e.g., river velocity, depth). The setup allows an improved understanding of the influences of various physical, spatial, and temporal factors on the hydrologic exchange flows and transit times. The predictors also contain those derived using hybrid clustering, leveraging our previous work on river corridor system hydromorphic classification. The machine learning-based predictive models are developed and validated along the Columbia River Corridor, and the results show that the top parameters are the thickness of the top geological formation layer, the flow regime, river velocity, and river depth; the RF and XGB models can achieve 70% to 80% accuracy and therefore are effective alternatives to the computational demanding numerical models of exchange flows and transit time distributions. Each machine learning model with its favorable configuration and setup have been evaluated. The transferability of the models to other river reaches and larger scales, which mostly depends on data availability, is also discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

On the pressure and temperature dependence of adsorption densities and other thermodynamic properties in gas shales

Black shale source rocks have become a key natural gas resource in the US and China. Unlike in conventional hydrocarbon reservoirs, a significant fraction of the gas in shales is adsorbed onto the inordinate specific surface areas (SSA) of micropores inside organic matter with densities exceeding those of bulk gas by an order of magnitude. Yet, the distribution of adsorbed versus bulk gas remains poorly understood. Experiments measure excess adsorption isotherms, which are corrected to absolute adsorption amounts by a factor that involves the density, &#x3C1; abs , of the adsorption layer(s). Constant values of &#x3C1; abs are widely used in the literature but, we argue, are inconsistent with the pressure- and temperature-dependence of adsorption behavior. In this work, we propose a more reliable approach that assumes a constant volume of each adsorption layer that can be determined from the SSA of the substrate. We measure nine high-pressure methane excess adsorption isotherms up to 15 MPa for three shale samples from China and Germany at temperatures of 65, 75, and 95 °C, and low-pressure carbon dioxide and nitrogen isotherms to estimate the SSA. We also investigate another 24 isotherms at 35, 50, and 60° C or 8 Chinese shale samples and 3 isotherms at 60, 90, and 120° C for an Argentinian shale sample from the literature. A new variation of the multi-layer Ono-Kondo lattice model is introduced to derive the temperature and pressure dependent adsorption layer densities, which are subsequently used to obtain the absolute adsorption isotherms of interest. Finally, this practical methodology has the potential to significantly improve our estimates of shale gas-in-place resources, and adsorption modeling more broadly.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Empirical evidence that mean soil contaminant concentration is not a conservative indicator of external exposure to wildlife

Adequate information on external exposure is often a limiting factor in ecological risk assessments because of a lack of exposure data for free-ranging animals as they interact with a heterogeneous distribution of contaminants. Instead, most wildlife exposure data are estimated from model simulations. However, empirical exposure data are rarely available to verify model results, or to test fundamental assumptions inherent in exposure assessments. We used novel, GPS-coupled radiation dosimeters on reindeer (Rangifer tarandus) to quantify their external exposure for five months in a Chernobyl fallout affected mountainous area of Norway. The exposure data were then used to test a fundamental assumption in screening-level risk assessments: Mean soil contaminant concentrations can be used to conservatively estimate chronic external exposures to representative animals. External exposure and GPS coordinates were obtained hourly and compared to model simulations of exposure based on airborne surveys of 137 Cs soil contamination. Our objectives were to determine 1) if modelled dose estimates based on mean 137 Cs soil concentrations were conservative, and 2) if modelled dose estimates could be improved by adjusting for spatial–temporal heterogeneity of contaminants using 137 Cs concentrations within reindeers’ GPS-defined home ranges and core areas. We found that external exposure modelled from mean soil contaminant concentrations underestimated exposure by 70% compared to empirical measurements from GPS-dosimeter collars worn on individual animals. Using area-weighted mean contaminant levels within the animals’ home range improved the model estimates, but still underestimated the field dosimeter data by 53%. The best estimate of external exposure was obtained when high-use areas within their home range, along with spatial heterogeneity of the contaminant, was accounted for by using area-weighted mean soil contaminant levels within GPS-derived core areas. Accounting for temporal use of core areas within animals’ home range provided a 24% improvement. Here, a comparison of our analyses to similar work performed on Chernobyl wolves found the two studies concur that risk assessors should be cautious in relying on the paradigm of using averaged soil contaminant levels to provide conservative estimates of external exposure to representative individuals. Results of modelled external exposure based on mean soil contaminant concentrations could misguide assessors and cause inappropriate management decisions.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2023

Comparison of inclusive and photon-tagged jet suppression in 5.02 TeV Pb+Pb collisions with ATLAS

Parton energy loss in the quark–gluon plasma (QGP) is studied with a measurement of photon-tagged jet production in 1.7 nb –1 of Pb+Pb data and 260 pb –1 of pp data, both at $\sqrt{^S{\text{NN}}}$ = 5.02 TeV, with the ATLAS detector. The process $pp$ → γ +jet+X and its analogue in Pb+Pb collisions is measured in events containing an isolated photon with transverse momentum ($p_{\text{T}}$) above 50 GeV and reported as a function of jet $p_{\text{T}}$. This selection results in a sample of jets with a steeply falling $p_{\text{T}}$ distribution that are mostly initiated by the showering of quarks. The $pp$ and Pb+Pb measurements are used to report the nuclear modification factor, $R_{\text{AA}}$, and the fractional energy loss, $S_{\text{loss}}$, for photon-tagged jets. In addition, the results are compared with the analogous ones for inclusive jets, which have a significantly smaller quark-initiated fraction. The $R_{\text{AA}}$ and $S_{\text{loss}}$ values are found to be significantly different between those for photon-tagged jets and inclusive jets, demonstrating that energy loss in the QGP is sensitive to the colour-charge of the initiating parton. Finally, the results are also compared with a variety of theoretical models of colour-charge-dependent energy loss.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗