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DOE OSTI2020

Modeling of thermal pressurization in tight claystone using sequential THM coupling: Benchmarking and validation against in-situ heating experiments in COx claystone

We apply thermoporoelasticity and a sequentially coupling technique for modeling thermally-driven coupled Thermo-Hydro-Mechanical (THM) processes in tight claystone. A THM benchmark case with a corresponding analytic solution for thermoporoelasticity under a constant heat loading verifies the model. Thereafter, two in situ heating experiments are simulated for model validation: a smaller-scale heating experiment (TED experiment) and a larger-scale experiment (ALC experiment) in Callovo-Oxfordian (COx) claystone at the Meuse/Haute-Marne underground research laboratory in France. The model exhibits good performance to match the observed temperature and pore pressure evolution for the smaller-scale TED experiment. For the larger-scale ALC experiment, general trends of thermal-pressurization are captured in the modeling, but pressure is underestimated at some monitoring points during cool-down. This indicates that the THM response in the field may be affected by the variability of rock's properties or irreversible or time-dependent mechanical processes that are not included in the current thermoporoelastic model. The main contributions of this work are as follows: (1) we verify and validate the numerical simulator, TOUGH-FLAC, to be a valuable coupled THM modeling tool; (2) prove that the laboratory determined material parameters can be used as reference values for upscaling experiments. However, to better identify and quantify THM processes with modeling of in situ tests, more emphasize should be dedicated to obtaining high-quality mechanical deformation data.

58 GEOSCIENCES↗

DOE OSTI2021

Neutrino event selection in the MicroBooNE liquid argon time projection chamber using Wire-Cell 3D imaging, clustering, and charge-light matching

An accurate and efficient event reconstruction is required to realize the full scientific capability of liquid argon time projection chambers (LArTPCs). The current and future neutrino experiments that rely on massive LArTPCs create a need for new ideas and reconstruction approaches. Wire-Cell, proposed in recent years, is a novel tomographic event reconstruction method for LArTPCs. The Wire-Cell 3D imaging approach capitalizes on charge, sparsity, time, and geometry information to reconstruct a topology-agnostic 3D image of the ionization electrons prior to pattern recognition. A second novel method, the many-to-many charge-light matching, then pairs the TPC charge activity to the detected scintillation light signal, thus enabling a powerful rejection of cosmic-ray muons in the MicroBooNE detector. A robust processing of the scintillation light signal and an appropriate clustering of the reconstructed 3D image are fundamental to this technique. In this paper, we describe the principles and algorithms of these techniques and their successful application in the MicroBooNE experiment. A quantitative evaluation of the performance of these techniques is presented. Using these techniques, a 95% efficient pre-selection of neutrino charged-current events is achieved with a 30-fold reduction of non-beam-coincident cosmic-ray muons, and about 80% of the selected neutrino charged-current events are reconstructed with at least 70% completeness and 80% purity.

3D imaging↗

DOE OSTI2017

Machine Learning Force Field Parameters from Ab Initio Data

Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (i.e., density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. Our results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not involved in the objective function, but were only used for model validation. The best model, optimized from the QM data at the DFMP2(fc)/jul-cc-pVTZ level, appears to perform even better than the original AMOEBA force field (amoeba09.prm), which was optimized empirically to match liquid properties. The present effort shows the possibility of using machine learning techniques to develop descriptive polarizable force field using only QM data. The ML/GA strategy to optimize force fields parameters described here could easily be extended to other molecular systems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2011

Error Detection, Factorization and Correction for Multi-View Scene Reconstruction from Aerial Imagery

Scene reconstruction from video sequences has become a prominent computer vision research area in recent years, due to its large number of applications in fields such as security, robotics and virtual reality. Despite recent progress in this field, there are still a number of issues that manifest as incomplete, incorrect or computationally-expensive reconstructions. The engine behind achieving reconstruction is the matching of features between images, where common conditions such as occlusions, lighting changes and texture-less regions can all affect matching accuracy. Subsequent processes that rely on matching accuracy, such as camera parameter estimation, structure computation and non-linear parameter optimization, are also vulnerable to additional sources of error, such as degeneracies and mathematical instability. Detection and correction of errors, along with robustness in parameter solvers, are a must in order to achieve a very accurate final scene reconstruction. However, error detection is in general difficult due to the lack of ground-truth information about the given scene, such as the absolute position of scene points or GPS/IMU coordinates for the camera(s) viewing the scene. In this dissertation, methods are presented for the detection, factorization and correction of error sources present in all stages of a scene reconstruction pipeline from video, in the absence of ground-truth knowledge. Two main applications are discussed. The first set of algorithms derive total structural error measurements after an initial scene structure computation and factorize errors into those related to the underlying feature matching process and those related to camera parameter estimation. A brute-force local correction of inaccurate feature matches is presented, as well as an improved conditioning scheme for non-linear parameter optimization which applies weights on input parameters in proportion to estimated camera parameter errors. Another application is in reconstruction pre-processing, where an algorithm detects and discards frames that would lead to inaccurate feature matching, camera pose estimation degeneracies or mathematical instability in structure computation based on a residual error comparison between two different match motion models. The presented algorithms were designed for aerial video but have been proven to work across different scene types and camera motions, and for both real and synthetic scenes.

42 ENGINEERING↗

DOE OSTI2017

Capturing the Sun: A Roadmap for Navigating Data-Access Challenges and Auto-Populating Solar Home Sales Listings

Capturing the Sun: A Roadmap for Navigating Data-Access Challenges and Auto-Populating Solar Home Sales Listings supports a vision of solar photovoltaic (PV) advocates and real estate advocates evolving together to make information about solar homes more accessible to home buyers and sellers and to simplify the process when these homes are resold. The Roadmap is based on a concept in the real estate industry known as automatic population of fields. Auto-population (also called auto-pop in the industry) is the technology that allows data aggregated by an outside industry to be matched automatically with home sale listings in a multiple listing service (MLS).

14 SOLAR ENERGY↗

DOE OSTI2013

THE HST EXTREME DEEP FIELD (XDF): COMBINING ALL ACS AND WFC3/IR DATA ON THE HUDF REGION INTO THE DEEPEST FIELD EVER

The eXtreme Deep Field (XDF) combines data from 10 years of observations with the Hubble Space Telescope Advanced Camera for Surveys (ACS) and the Wide-Field Camera 3 Infra-Red (WFC3/IR) into the deepest image of the sky ever in the optical/near-IR. Since the initial observations of the Hubble Ultra-Deep Field (HUDF) in 2003, numerous surveys and programs, including supernovae follow-up, HUDF09, CANDELS, and HUDF12, have contributed additional imaging data across this region. However, these images have never been combined and made available as one complete ultra-deep image dataset. We combine them now with the XDF program. Our new and improved processing techniques provide higher quality reductions of the total dataset. All WFC3/IR and optical ACS data sets have been fully combined and accurately matched, resulting in the deepest imaging ever taken at these wavelengths, ranging from 29.1 to 30.3 AB mag (5σ in a 0.''35 diameter aperture) in 9 filters. The combined image therefore reaches to 31.2 AB mag 5σ (32.9 at 1σ) for a flat f {sub ν} source. The gains in the optical for the four filters done in the original ACS HUDF correspond to a typical improvement of 0.15 mag, with gains of 0.25 mag in the deepest areas. Such gains are equivalent to adding ∼130 to ∼240 orbits of ACS data to the HUDF. Improved processing alone results in a typical gain of ∼0.1 mag. Our 5σ (optical+near-IR) SExtractor catalogs reveal about 14,140 sources in the full field and about 7121 galaxies in the deepest part of the XDF.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Characterizing the Variation and Covariation of Cloud Microphysical Properties and Implications for Simulation of Subgrid-scale Warm-Rain Processes in Earth System Models (Final DOE-ASR Report)

Warm marine boundary layer (MBL) clouds constitute an important component in the global climate system, and precipitation plays a central role in controlling the water budget, radiative effects, and lifetime of these MBL clouds. Unfortunately, because of the relatively coarse effective grid resolution of the current generation of Earth system models (ESMs), the variety of cloud microphysical processes occurring inside an ESM grid cell are often oversimplified or unconstrained by observations. For example, the warm rain processes (e.g., autoconversion and accretion) are usually parameterized as nonlinear functions of grid-mean cloud properties. Because of the nonlinear nature of these functions, neglecting variability within the ESM grid volume can lead to substantial biases in precipitation production, cloud cover, and surface radiative fluxes. In state-of-the art ESMs, the influence of subgrid-scale variability is represented as an enhancement factor (EF) coefficient to the autoconversion, and accretion rates calculated from the model variables. However, EF is typically taken to be a constant or even used as a knob to tune model cloud properties to match observations, an ad hoc approach that may yield a desired cloud outcome yet introduce compensating errors. In this project, we used the combination of in situ cloud microphysics measurements from the ACE-ENA field campaign and large-eddy simulations (LES) to characterize and understand subgrid-scale variations and co-variations of cloud microphysical properties and use the results to evaluate and improve the representation of subgrid warm-rain processes in ESMs, in particular the EF used to tune the autoconversion and accretion processes. In this final report, we summarize our research activities and main findings in Section 2, provide a list of publications (Section 3) and presentations (Section 4) resulted from our research, and briefly discuss the student activities supported by this project.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Refining Principal Stress Measurements in Reservoir Underburden in Regions of Induced Seismicity through Seismological Tools, Laboratory Experiments - Final Technical Report

This project developed methodologies to measure the in-situ principal stress in the deep subsurface through use of multiple independent, but complementary, seismic methods, laboratory verification, and development of theoretical frameworks. By leveraging existing regional and local datasets we developed, tested, and refined a set of diagnostic tools for determining the in-situ stress state with reduced uncertainty at and below reservoir depths (1.5-6 km). A set of novel tools was produced that are scale independent, such that their utility is equivalent on regional, field scale, and near borehole monitoring of principal stresses in reservoir underburden for carbon storage projects. During a 4-year Department of Energy (DOE) and Southern Company funded project, carried out by the Electric Power Research Institute (EPRI), Lawrence Livermore National Laboratory (LLNL), the University of Oklahoma (OU), and the U.S. Geological Survey (USGS), the project team developed methodologies to measure the far-field in-situ principal stress in the deep subsurface, leveraging induced seismicity data from waste-water disposal projects. These methodologies consisted in the use of well-established and technically advanced seismic processing methods, such as virtual seismometer method-moment tensor (VSM-MT) and shear wave splitting (SWS), that are adept at recovering the stress orientation and certain components of the stress tensor. These methods were applied to robust seismicity catalogs created with matched filter techniques near sites of active fluid disposal—a proxy for carbon storage sites where such datasets are more limited. Estimates of the stress orientation made with seismic processing tools were considered along with laboratory acoustic emission experiments conducted on rock samples from the region of interest. Stress orientations in the studied region do not vary significantly across distances of ~100 km, nor are they found to rotate through time as a consequence of local wastewater disposal, as previously speculated. Finally, the project team investigated the trade-offs among the different seismic methods and evaluated the range of uncertainty that is generated with these methodologies, which led to a practical use and refinement of the VSM-MT technique when it is applied to field datasets. Understanding the trade-offs between these different methods highlighted the potential benefits of improved quantification of uncertainties on stress field estimations.

58 GEOSCIENCES↗

DOE OSTI2024

The gravitational lensing imprints of DES Y3 superstructures on the CMB: a matched filtering approach

Low-density cosmic voids gravitationally lens the cosmic microwave background (CMB), leaving a negative imprint on the CMB convergence |$\kappa$|⁠. This effect provides insight into the distribution of matter within voids, and can also be used to study the growth of structure. We measure this lensing imprint by cross-correlating the Planck CMB lensing convergence map with voids identified in the Dark Energy Survey Year 3 (DES Y3) data set, covering approximately 4200 deg|$^2$| of the sky. We use two distinct void-finding algorithms: a 2D void-finder that operates on the projected galaxy density field in thin redshift shells, and a new code, Voxel, which operates on the full 3D map of galaxy positions. We employ an optimal matched filtering method for cross-correlation, using the Marenostrum Institut de Ciències de l’Espai N-body simulation both to establish the template for the matched filter and to calibrate detection significances. Using the DES Y3 photometric luminous red galaxy sample, we measure |$A_\kappa$|⁠, the amplitude of the observed lensing signal relative to the simulation template, obtaining |$A_\kappa = 1.03 \pm 0.22$| (⁠|$4.6\sigma$| significance) for Voxel and |$A_\kappa = 1.02 \pm 0.17$| (⁠|$5.9\sigma$| significance) for 2D voids, both consistent with Lambda cold dark matter expectations. We additionally invert the 2D void-finding process to identify superclusters in the projected density field, for which we measure |$A_\kappa = 0.87 \pm 0.15$| (⁠|$5.9\sigma$| significance). The leading source of noise in our measurements is Planck noise, implying that data from the Atacama Cosmology Telescope, South Pole Telescope and CMB-S4 will increase sensitivity and allow for more precise measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Nonlinear simulations to optimize magnetic nanoparticle hyperthermia

Magnetic nanoparticle hyperthermia is an attractive emerging cancer treatment, but the acting microscopic energy deposition mechanisms are not well understood and optimization suffers. We describe several approximate forms for the characteristic time of Néel rotations with varying properties and external influences. We then present stochastic simulations that show agreement between the approximate expressions and the micromagnetic model. The simulations show nonlinear imaginary responses and associated relaxational hysteresis due to the field and frequency dependencies of the magnetization. This suggests that efficient heating is possible by matching fields to particles instead of resorting to maximizing the power of the applied magnetic fields.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2018

NLO QCD corrections to SM-EFT dilepton and electroweak Higgs boson production, matched to parton shower in POWHEG

Here, we discuss the Standard Model — Effective Field Theory (SM-EFT) contributions to neutral- and charge-current Drell-Yan production, associated production of the Higgs and a vector boson, and Higgs boson production via vector boson fusion. We consider all the dimension-six SM-EFT operators that contribute to these processes at leading order, include next-to-leading order QCD corrections, and interface them with parton showering and hadronization in Pythia8 according to the POWHEG method. We discuss existing constraints on the coefficients of dimension-six operators and identify differential and angular distributions that can differentiate between different effective operators, pointing to specific features of Beyond-the-Standard-Model physics.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2016

Evolution and velocity fields for a buoyant jet in a stratified environment

Velocity fields for a turbulent, vertical, buoyant jet interacting with a linear density stratified environment are obtained to study the effect of stratification on flow evolution and entrainment. Analysis of the flow field with a Reynolds, Re, of 20,000 and a 3% density difference is accomplished using time-resolved particle image velocimetry in a refractive index matched flow facility. Flow field statistics are compared to a benchmark neutrally buoyant jet in a uniform environment. Velocity fields indicate that the buoyant jet is strongly affected from stratification, where the jet is no longer self-similar, and succumbs to a final height. Stratification also changes the entrainment process, where a double momentum effect occurs. Centerline analysis suggests overall turbulence suppression occurs from stratification. (authors)

42 ENGINEERING↗

DOE OSTI2013

A COMBINED VERY LARGE TELESCOPE AND GEMINI STUDY OF THE ATMOSPHERE OF THE DIRECTLY IMAGED PLANET, β PICTORIS b

We analyze new/archival VLT/NaCo and Gemini/NICI high-contrast imaging of the young, self-luminous planet β Pictoris b in seven near-to-mid IR photometric filters, using advanced image processing methods to achieve high signal-to-noise, high precision measurements. While β Pic b's near-IR colors mimic those of a standard, cloudy early-to-mid L dwarf, it is overluminous in the mid-infrared compared to the field L/T dwarf sequence. Few substellar/planet-mass objects—i.e., κ And b and 1RXJ 1609B—match β Pic b's JHK{sub s}L' photometry and its 3.1 μm and 5 μm photometry are particularly difficult to reproduce. Atmosphere models adopting cloud prescriptions and large (∼60 μm) dust grains fail to reproduce the β Pic b spectrum. However, models incorporating thick clouds similar to those found for HR 8799 bcde, but also with small (a few microns) modal particle sizes, yield fits consistent with the data within the uncertainties. Assuming solar abundance models, thick clouds, and small dust particles ((a) = 4 μm), we derive atmosphere parameters of log (g) = 3.8 ± 0.2 and T{sub eff} = 1575-1650 K, an inferred mass of 7{sup +4}{sub -3} M{sub J} , and a luminosity of log(L/L{sub ☉}) ∼–3.80 ± 0.02. The best-estimated planet radius, ≈1.65 ± 0.06 R{sub J} , is near the upper end of allowable planet radii for hot-start models given the host star's age and likely reflects challenges constructing accurate atmospheric models. Alternatively, these radii are comfortably consistent with hot-start model predictions if β Pic b is younger than ≈7 Myr, consistent with a late formation well after its host star's birth ∼12{sup +8}{sub -4} Myr ago.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2012

Unitarity-violation in generalized Higgs inflation models

Unitarity-violation presents a challenge for non-minimally coupled models of inflation based on weak-scale particle physics. We examine the energy scale of tree-level unitarity-violation in scattering processes for generalized models with multiple scalar fields where the inflaton is either a singlet scalar or the Higgs. In the limit that the non-minimal couplings are all equal (e.g. in the case of Higgs or other complex inflaton), the scale of tree-level unitarity-violation matches the existing result. However if the inflaton is a singlet, and if it has a larger non-minimal coupling than other scalars in the model, then this hierarchy increases the scale of tree-level unitarity-violation. A sufficiently strong hierarchy pushes the scale of tree-level unitarity-violation above the Planck scale. We also discuss models which attempt to resolve the issue of unitarity-violation in Higgs Inflation.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

An analytical phytoplankton model and its application in the tidal freshwater James River

Here, this study constructs an analytical model to understand the phytoplankton dynamics in a one-dimensional system by integrating physical and biological processes. We present an analytical solution of phytoplankton distribution along the longitudinal direction of a tidal river. The solution has two components: water age and accumulative growth. The water age represents the overall effect of physical transport due to advection, while the accumulative growth represents the accumulation of phytoplankton biomass due to biological processes during the transport. In addition, an alternative solution with nonlinear reaction term is given to account for the feedback mechanism of nonlinear processes that affect phytoplankton growth rate. The nonlinear reaction term can be also used to approximate the effect of physical mixing on phytoplankton distribution. The analytical solutions can be further used to predict the temporal variation and spatial distribution of phytoplankton along the tidal river. They also serve as a mathematical tool to unite different field phytoplankton observations. We applied the model in the Tidal Freshwater Region (TFR) of James River under different dynamic conditions and the model results match well with the observations, which validates the theory on different time scales. Furthermore, an analysis is conducted for the Local Chlorophyll-a Maximum (LCM) in the TFR. It shows that the condition for LCM is biologically controlled, but its location is regulated by river flow and river geomorphology.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Mg-Ion Conduction in Antiperovskite Solid Electrolytes Revealed by 25 Mg Ultrahigh Field NMR and First-Principles Calculations

Magnesium-ion batteries hold the potential to outperform the energy density of lithium-ion batteries, given the divalent charge carried by each Mg 2+ cation, but remain in an early stage of development. Here, in this study, 25 Mg solid-state nuclear magnetic resonance (ssNMR) is used to gain insight into the local structure and Mg-ion dynamics of candidate Mg-ion solid electrolytes, the antiperovskites Mg 3 SbN and Mg 3 AsN. Using the highest available magnetic field (35.2 T) for high-resolution solid-state NMR, the largest 25 Mg quadrupole coupling constants (C Q ) yet measured of up to 22 MHz are reported and corroborated by first-principles calculations. Predicted C Q values are shown to correlate with the antiperovskite’s tolerance factor; thus, 25 Mg NMR linewidths can report on lattice distortions and phase stability of these antiperovskites. Variable-temperature 25 Mg NMR spectra demonstrate changes at elevated temperatures, ascribed to Mg-ion motional effects. 25 Mg T 1 relaxometry measurements at ultrahigh field reveal a lower activation energy for the more distorted Mg 3 AsN phase, matching computational predictions of a lower energy barrier for Mg 2+ ion migration and suggesting that additional scrutiny of antiperovskites as Mg-ion conductors is warranted. Given the inherent challenges of 25 Mg NMR, this work demonstrates the benefits of combining ultrahigh field NMR spectroscopy, advanced pulse sequences, modern signal processing, and first-principles calculations to facilitate NMR of quadrupolar nuclei as a tool to probe the local structure and ion dynamics in beyond-Li battery materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2012

Simulations of laser-wakefield acceleration with external electron-bunch injection for REGAE experiments at DESY

We present particle-in-cell simulations for future laser-plasma wakefield experiments with external bunch injection at the REGAE accelerator facility at DESY, Hamburg, Germany. Two effects have been studied in detail: emittance evolution of electron bunches externally injected into a wake, and longitudinal bunch compression inside the wakefield. Results show significant transverse emittance growth during the injection process, if the electron bunch is not matched to its intrinsic betatron motion inside the wakefield. This might introduce the necessity to include beam-matching sections upstream of each plasma-accelerator section with fundamental implications on the design of staged laser wakefield accelerators. When externally injected at the zero-field crossing of the laser-driven wake, the electron bunch may undergo significant compression in longitudinal direction and be accelerated simultaneously due to the gradient in the acting force. The mechanism would allow for production of single high-energy, ultra-short (on the order of one femtosecond) bunches at REGAE. The optimal conditions for maximal bunch compression are discussed in the presented studies.

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

sparse-msrf:A package for sparse modeling and estimation of fossil-fuel CO2 emission fields

The software is used to fit models of emission fields (e.g., fossil-fuel CO2 emissions) to sparse measurements of gaseous concentrations. Its primary aim is to provide an implementation and a demonstration for the algorithms and models developed in J. Ray, V. Yadav, A. M. Michalak, B. van Bloemen Waanders and S. A. McKenna, "A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions", accepted, Geoscientific Model Development, 2014. The software can be used to estimate emissions of non-reactive gases such as fossil-fuel CO2, methane etc. The software uses a proxy of the emission field being estimated (e.g., for fossil-fuel CO2, a population density map is a good proxy) to construct a wavelet model for the emission field. It then uses a shrinkage regression algorithm called Stagewise Orthogonal Matching Pursuit (StOMP) to fit the wavelet model to concentration measurements, using an atmospheric transport model to relate emission and concentration fields. Algorithmic novelties described in the paper above (1) ensure that the estimated emission fields are non-negative, (2) allow the use of guesses for emission fields to accelerate the estimation processes and (3) ensure that under/overestimates in the guesses do not skew the estimation.

None, JinaLee↗