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DOE OSTI2015

An improved thermodynamic model for the complexation of trivalent actinides and lanthanide with oxalic acid valid to high ionic strength.

The dissociation constants of oxalic acid (Ox), and the stability constants of Am 3+ , Cm 3+ and Eu 3+ with Ox 2– have been determined at 25 °C, over a range of concentration varying from 0.1 to 6.60 m NaClO4 using potentiometric titration and extraction techniques, respectively. The experimental data support the formation of complexes, M(Ox) n 3 – 2n , where (M = Am 3+ , Cm 3+ and Eu 3+ and n = 1 and 2). The dissociation constant and the stability constant values measured as a function of NaClO 4 concentration were used to estimate the Pitzer parameters for the respective interactions of Am 3+ , Cm 3+ and Eu 3+ with Ox. Furthermore, the stability constants data of Am 3+ –Ox measured in NaClO 4 and in NaCl solutions from the literature were simultaneously fitted in order to refine the existing actinide–oxalate complexation model that can be used universally in the safety assessment of radioactive waste disposal. The thermodynamic stability constant: log β 0 101 = 6.30 ± 0.06 and log β 0 102 = 10.84 ± 0.06 for Am 3+ was obtained by simultaneously fitting data in NaCl and NaClO 4 media. Additionally, log β 0 101 = 6.72 ± 0.08 and log β 0 102 = 11.05 ± 0.09 for the Cm 3+ and log β 0 101 = 6.67 ± 0.08 and log β 0 102 = 11.15 ± 0.09 for the Eu 3+ were calculated by extrapolation of data to zero ionic strength in NaClO 4 medium only. For all stability constants, the Pitzer model gives an excellent representation of the data using interaction parameters β (0) , β (1) , and CΦ determined in this work. The thermodynamic model developed in this work will be useful in accurately modeling the potential solubility of trivalent actinides and early lanthanides to ionic strength of 6.60 m in low temperature environments in the presence of Ox. Furthermore, the work is also applicable to the accurate modeling transport of rare earth elements in various environments under the surface conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2019

Complexation of lanthanides and other metal ions by the polypyridyl ligand quaterpyridine: Relation between metal ion size, chelate ring size, and complex stability

Metal ion complexing properties of the ligand QPY (2,2':6',2'':6'',2'''-quaterpyridine) are reported in relation to its possible use as a functional group for reagents in the extraction and separation of Ln(III) (lanthanide) ions. QPY is almost totally insoluble in water, but variation of the intense π-π* transitions in the UV spectrum of 1 × 10 –5 M QPY solutions in 50% CH 3 OH/H 2 O (v/v) as a function of pH or metal ion concentration allowed for the determination of the protonation constant (pK) and log K 1 values with metal ions. The pK a values of QPY are 4.54 ± 0.02 and 3.47 ± 0.02 in 50% CH 3 OH/H 2 O. The log K 1 values determined by UV–visible spectroscopy for the Ln(III) ions by titration of 1:1 solutions of 1.0 × 10 5 M Ln(III) ion and QPY between pH 2 and 6 were: La(III), 3.79; Pr(III), 4.34; Nd(III) 4.57; Sm(III), 4.78; Gd(III) 4.69; Dy(III), 4.76, Ho(III), 4.94; Er(III), 5.36, Tm(III), 5.84, and Lu(III) 5.54, all at 25 °C and ionic strength zero. The log K 1 values for the Ln(III) ions show quite strong increases from La(III) to Lu(III), with a local maximum at Sm(III), and a local minimum at Gd(III). The local maxium at Sm(III) is attributed to this ion being the best-fit size for coordinating with polypyridyl ligands. The effect of preorganization of polypyridyls such as QPY with bridging benzo groups in the ligand backbone to yield DPP (2,9-dipyrid-2-yl-1,10-phenanthroline) is to produce significant increases in log K 1 for large metal ions such as Ln(III) ions, but for small metal ions such as Zn(II), there is a large decrease in log K 1 in passing from QPY to DPP: this shows how rigidification of the ligand can enhance the selectivity against small metal ions of polypyridyls forming five-membered chelate rings. DFT calculations are used to analyze the variation in log K 1 in passing from the La(III) complexes of QPY to DPP compared to those for the smaller Lu(III) ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Roles of individual radicals generated by a submerged dielectric barrier discharge plasma reactor during Escherichia coli O157:H7 inactivation

A submerged dielectric barrier discharge plasma reactor (underwater DBD) has been used on Escherichia coli O157:H7 (ATCC 35150). Plasma treatment was carried out using clean dry air gas to investigate the individual effects of the radicals produced by underwater DBD on an E. coli O157:H7 suspension (8.0 log CFU/ml). E. coli O157:H7 was reduced by 6.0 log CFU/ml for 2 min of underwater DBD plasma treatment. Optical Emission Spectra (OES) shows that OH and NO (α, β) radicals, generated by underwater DBD along with ozone gas. E. coli O157:H7 were reduced by 2.3 log CFU/ml for 10 min of underwater DBD plasma treatment with the terephthalic acid (TA) OH radical scavenger solution, which is significantly lower (3.7 log CFU/ml) than the result obtained without using the OH radical scavenger. A maximum of 1.5 ppm of ozone gas was produced during the discharge of underwater DBD, and the obtained reduction difference in E.coli O157:H7 in presence and in absence of ozone gas was 1.68 log CFU/ml. The remainder of the 0.62 log CFU/ml reduction might be due to the effect of the NO (α, β) radicals or due to the combined effect of all the radicals produced by underwater DBD. A small amount of hydrogen peroxide was also generated but does not play any role in E. coli O157:H7 inactivation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2013

WILSON-BAPPU EFFECT: EXTENDED TO SURFACE GRAVITY

In 1957, Wilson and Bappu found a tight correlation between the stellar absolute visual magnitude (M{sub V} ) and the width of the Ca II K emission line for late-type stars. Here, we revisit the Wilson-Bappu relationship (WBR) to claim that the WBR can be an excellent indicator of stellar surface gravity of late-type stars as well as a distance indicator. We have measured the width (W) of the Ca II K emission line in high-resolution spectra of 125 late-type stars obtained with the Bohyunsan Optical Echelle Spectrograph and adopted from the Ultraviolet and Visual Echelle Spectrograph archive. Based on our measurement of the emission line width (W), we have obtained a WBR of M{sub V} = 33.76 - 18.08 log W. In order to extend the WBR to being a surface gravity indicator, stellar atmospheric parameters such as effective temperature (T{sub eff}), surface gravity (log g), metallicity ([Fe/H]), and micro-turbulence ({xi}{sub tur}) have been derived from self-consistent detailed analysis using the Kurucz stellar atmospheric model and the abundance analysis code, MOOG. Using these stellar parameters and log W, we found that log g = -5.85 log W+9.97 log T{sub eff} - 23.48 for late-type stars.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

SDSS J074511.56+194926.5: Discovery of a metal-rich and tidally distorted extremely low mass white dwarf

We present the discovery of an unusual, tidally distorted extremely low mass white dwarf (WD) with nearly solar metallicity. Radial velocity measurements confirm that this is a compact binary with an orbital period of 2.6975 hr and a velocity semi-amplitude of K = 108.7 km s{sup –1}. Analysis of the hydrogen Balmer lines yields an effective temperature of T {sub eff} = 8380 K and a surface gravity of log g = 6.21 that in turn indicate a mass of M = 0.16 M {sub ☉} and a cooling age of 4.2 Gyr. In addition, a detailed analysis of the observed metal lines yields abundances of log (Mg/H) = –3.90, log (Ca/H) = –5.80, log (Ti/H) = –6.10, log (Cr/H) = –5.60, and log (Fe/H) = –4.50, similar to the sun. We see no evidence of a debris disk from which these metals would be accreted, though the possibility cannot entirely be ruled out. Other potential mechanisms to explain the presence of heavy elements are discussed. Finally, we expect this system to ultimately undergo unstable mass transfer and merge to form a ∼0.3-0.6 M {sub ☉} WD in a few Gyr.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

SDSS/SEGUE spectral feature analysis for stellar atmospheric parameter estimation

Large-scale and deep sky survey missions are rapidly collecting a large amount of stellar spectra, which necessitate the estimation of atmospheric parameters directly from spectra and make it feasible to statistically investigate latent principles in a large data set. We present a technique for estimating parameters T{sub eff}, log g, and [Fe/H] from stellar spectra. With this technique, we first extract features from stellar spectra using the LASSO algorithm; then, the parameters are estimated from the extracted features using the support vector regression. On a subsample of 20,000 stellar spectra from the Sloan Digital Sky Survey (SDSS) with reference parameters provided by the SDSS/SEGUE Spectroscopic Parameter Pipeline, estimation consistency are 0.007458 dex for log T{sub eff} (101.609921 K for T{sub eff}), 0.189557 dex for log g, and 0.182060 for [Fe/H], where the consistency is evaluated by mean absolute error. Prominent characteristics of the proposed scheme are sparseness, locality, and physical interpretability. In this work, each spectrum consists of 3821 fluxes, and 10, 19, and 14 typical wavelength positions are detected, respectively, for estimating T{sub eff}, log g, and [Fe/H]. It is shown that the positions are related to typical lines of stellar spectra. This characteristic is important in investigating physical indications from analysis results. Then, stellar spectra can be described by the individual fluxes on the detected positions (PD) or local integration of fluxes near them (LI). The aforementioned consistency is the result based on features described by LI. If features are described by PD, consistency is 0.009092 dex for log T{sub eff} (124.545075 K for T{sub eff}), 0.198928 dex for log g, and 0.206814 dex for [Fe/H].

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2015

A DEFINITION FOR GIANT PLANETS BASED ON THE MASS–DENSITY RELATIONSHIP

We present the mass–density relationship (log M − log ρ) for objects with masses ranging from planets (M ≈ 0.01 M{sub Jup}) to stars (M > 0.08 M{sub ⊙}). This relationship shows three distinct regions separated by a change in slope in the log M − log ρ plane. In particular, objects with masses in the range 0.3 M{sub Jup}–60 M{sub Jup} follow a tight linear relationship with no distinguishing feature to separate the low-mass end (giant planets) from the high-mass end (brown dwarfs). We propose a new definition of giant planets simply based on changes in the slope of the log M versus log ρ relationship. By this criterion, objects with masses less than ≈0.3 M{sub Jup} are low-mass planets, either icy or rocky. Giant planets cover the mass range 0.3 M{sub Jup}–60 M{sub Jup}. Analogous to the stellar main sequence, objects on the upper end of the giant planet sequence (brown dwarfs) can simply be referred to as “high-mass giant planets,” while planets with masses near that of Jupiter can be called “low-mass giant planets.”.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Sparse Cholesky factorization for solving nonlinear PDEs via Gaussian processes

In recent years, there has been widespread adoption of machine learning-based approaches to automate the solving of partial differential equations (PDEs). Among these approaches, Gaussian processes (GPs) and kernel methods have garnered considerable interest due to their flexibility, robust theoretical guarantees, and close ties to traditional methods. They can transform the solving of general nonlinear PDEs into solving quadratic optimization problems with nonlinear, PDE-induced constraints. However, the complexity bottleneck lies in computing with dense kernel matrices obtained from pointwise evaluations of the covariance kernel, and its partial derivatives, a result of the PDE constraint and for which fast algorithms are scarce. The primary goal of this paper is to provide a near-linear complexity algorithm for working with such kernel matrices. We present a sparse Cholesky factorization algorithm for these matrices based on the near-sparsity of the Cholesky factor under a novel ordering of pointwise and derivative measurements. The near-sparsity is rigorously justified by directly connecting the factor to GP regression and exponential decay of basis functions in numerical homogenization. We then employ the Vecchia approximation of GPs, which is optimal in the Kullback-Leibler divergence, to compute the approximate factor. This enables us to compute ϵ-approximate inverse Cholesky factors of the kernel matrices with complexity O(N log d (N/ϵ)) in space and O(N log 2d (N/ϵ)) in time. We integrate sparse Cholesky factorizations into optimization algorithms to obtain fast solvers of the nonlinear PDE. We numerically illustrate our algorithm’s near-linear space/time complexity for a broad class of nonlinear PDEs such as the nonlinear elliptic, Burgers, and Monge-Ampère equations. In summary, we provide a fast, scalable, and accurate method for solving general PDEs with GPs and kernel methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

SHαDE: survey description and mass–kinematics scaling relations for dwarf galaxies

ABSTRACT The Study of H α from Dwarf Emissions (SHαDE) is a high spectral resolution (R = 13 500) H α integral field survey of 69 dwarf galaxies with stellar masses 106 < M⋆ < 109 M⊙. The survey used FLAMES on the ESO Very Large Telescope. SHαDE is designed to study the kinematics and stellar populations of dwarf galaxies using consistent methods applied to massive galaxies and at matching level of detail, connecting these mass ranges in an unbiased way. In this paper, we set out the science goals of SHαDE, describe the sample properties, outline the data reduction, and analysis processes. We investigate the log M⋆–log S0.5 mass–kinematics scaling relation, which has previously shown potential for combining galaxies of all morphologies in a single scaling relation. We extend the scaling relation from massive galaxies to dwarf galaxies, demonstrating this relation is linear down to a stellar mass of M⋆ ∼ 108.6 M⊙. Below this limit, the kinematics of galaxies inside one effective radius appears to be dominated by the internal velocity dispersion limit of the H α-emitting gas, giving a bend in the log M⋆–log S0.5 relation. Replacing stellar mass with total baryonic mass using gas mass estimate reduces the severity but does not remove the linearity limit of the scaling relation. An extrapolation to estimate the galaxies’ dark matter halo masses, yields a log Mh–log S0.5 scaling relation that is free of any bend, has reduced curvature over the whole mass range, and brings galaxies of all masses and morphologies on to the virial relation.

Barat, Dilyar↗

DOE OSTI2023

Abundances of CNO elements in z ∼ 0.3–0.4 Lyman continuum leaking galaxies

We present observations with the Space Telescope Imaging Spectrograph onboard the Hubble Space Telescope (HST) of 11 Lyman continuum (LyC) leaking galaxies at redshifts, z , in the range 0.29–0.43, with oxygen abundances 12+log(O/H) = 7.64–8.16, stellar masses M ⋆ ∼ 10 7.8 –10 9.8 M ⊙ , and O 32 = [O III ] λ5007/[O II ] λ3727 of ∼ 5–20 aiming to detect the C III ] λ1908 emission line. We combine these observations with the optical Sloan Digital Sky Survey (SDSS) spectra for the determination of carbon, nitrogen, and oxygen abundances. Our sample was supplemented by 31 galaxies from the literature, for which carbon, nitrogen, and oxygen abundances can be derived from the HST and SDSS spectra. These additional galaxies, however, do not have LyC observations. We find that log(C/O) for the entire sample at 12+log(O/H) < 8.1 does not depend on metallicity, with a small dispersion of ∼0.13 dex around the average value of ∼−0.75 dex. On the other hand, the log(N/O) in galaxies at z > 0.1, including LyC leakers, is systematically higher compared to the rest of the sample with lower metallicity. We find that log(C/O) slightly decreases with increasing M ⋆ from ∼ −0.65 at M ⋆ = 10 6 M ⊙ to ∼ −0.80 at M ⋆ = 10 9 –10 10 M ⊙ , whereas log(N/O) is considerably enhanced at M ⋆ > 10 8 M ⊙ . The origin of these trends remains basically unknown. A possible solution would be to assume that the upper mass limit of the stellar initial mass function in more massive galaxies is higher. This would result in a higher production of oxygen and a larger fraction of massive stars with stellar wind polluting the interstellar medium with nitrogen.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

A comparison of the baryonic Tully–Fisher relation in MaNGA and IllustrisTNG

We compare an observed baryonic Tully–Fisher relation (BTFR) from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) and HI-MaNGA surveys to a simulated BTFR from the cosmological magnetohydrodynamical simulation, IllustrisTNG. To do so, we calibrate the BTFR of the local universe using 377 galaxies from the MaNGA and HI-MaNGA surveys, and perform mock 21 cm observations of matching galaxies from IllustrisTNG. The mock observations are used to ensure that the comparison with the observed galaxies is fair since it has identical measurement algorithms, observational limitations, biases, and uncertainties. For comparison, we also calculate the BTFR for the simulation without mock observations and demonstrate how mock observations are necessary to fairly and consistently compare between observational and theoretical data. We report a MaNGA BTFR of log$_{10} (M_{ \rm Bary}/M_\odot)= (2.97 \pm 0.18)$ log$_{10} V_{ \rm Rot} + (4.04 \pm 0.41)\, \log _{10}{M_{\odot }}$ and an IllustrisTNG BTFR of log$_{10} (M_{ \rm Bary}/M_\odot) = (2.94 \pm 0.23$) log$_{10} V_{ \rm Rot} + (4.15 \pm 0.44)\, \log _{10}{M_{\odot }}$. Thus, MaNGA and IllustrisTNG produce BTFRs that agree within uncertainties, demonstrating that IllustrisTNG has created a galaxy population that obeys the observed relationship between mass and rotation velocity in the observed universe.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Sentiment Analysis based Error Detection for Large-Scale Systems

Today's large-scale systems such as High Performance Computing (HPC) Systems are designed/utilized towards exascale computing, inevitably decreasing its reliability due to the increasing design complexity. HPC systems conduct extensive logging of their execution behaviour. In this paper, we leverage the inherent meaning behind the log messages and propose a novel sentiment analysis-based approach for the error detection in large-scale systems, by automatically mining the sentiments in the log messages. Our contributions are four-fold. (1) We develop a machine learning (ML) based approach to automatically build a sentiment lexicon, based on the system log message templates. (2) Using the sentiment lexicon, we develop an algorithm to detect system errors. (3) We develop an algorithm to identify the nodes and components with erroneous behaviors, based on sentiment polarity scores. (4) We evaluate our solution vs. other state-of-the-art machine/deep learning algorithms based on three representative supercomputers' system logs. Experiments show that our error detection algorithm can identify error messages with an average MCC score and f -score of 91% and 96% respectively, while state of the art ML/deep learning model (LSTM) obtains only 67% and 84%. To the best of our knowledge, this is the first work leveraging the sentiments embedded in log entries of large-scale systems for system health analysis.

error detection↗

DOE OSTI2018

Spatio-Temporal Analysis of HPC I/O and Connection Data

The HPC system consists of a set of layers of software and hardware for I/O and networking. System logs are helpful resources to understand what is going on in the system. A challenge is that it is non-trivial to analyze the logs maintained in various levels of the stack. Independent analysis might lead to an incomplete conclusion due to the limited coverage of each log. This work takes a comprehensive approach to analysis that incorporates the logs in the multiple layers and components, in order to facilitate the detection of anomalous activities. This research aims to identify and predict potential performance bottlenecks in the HPC system, by capturing the temporal variation patterns from heterogeneous, high-dimensional, and non-linear log data. In this paper, we share our preliminary efforts for spatio-temporal analysis of HPC I/O and connection data, with our initial observations from the analysis of one-week HPC log data sets collected from one of NERSC systems.

Choi, Jinhwan↗

DOE OSTI2016

SU-G-JeP1-08: Dual Modality Verification for Respiratory Gating Using New Real- Time Tumor Tracking Radiotherapy System

Purpose: The respirato ry gating system combined the TrueBeam and a new real-time tumor-tracking radiotherapy system (RTRT) was installed. The RTRT system consists of two x-ray tubes and color image intensifiers. Using fluoroscopic images, the fiducial marker which was implanted near the tumor was tracked and was used as the internal surrogate for respiratory gating. The purposes of this study was to develop the verification technique of the respiratory gating with the new RTRT using cine electronic portal image device images (EPIDs) of TrueBeam and log files of the RTRT. Methods: A patient who underwent respiratory gated SBRT of the lung using the RTRT were enrolled in this study. For a patient, the log files of three-dimensional coordinate of fiducial marker used as an internal surrogate were acquired using the RTRT. Simultaneously, the cine EPIDs were acquired during respiratory gated radiotherapy. The data acquisition was performed for one field at five sessions during the course of SBRT. The residual motion errors were calculated using the log files (E{sub log}). The fiducial marker used as an internal surrogate into the cine EPIDs was automatically extracted by in-house software based on the template-matching algorithm. The differences between the the marker positions of cine EPIDs and digitally reconstructed radiograph were calculated (E{sub EPID}). Results: Marker detection on EPID using in-house software was influenced by low image contrast. For one field during the course of SBRT, the respiratory gating using the RTRT showed the mean ± S.D. of 95{sup th} percentile E{sub EPID} were 1.3 ± 0.3 mm,1.1 ± 0.5 mm,and those of E{sub log} were 1.5 ± 0.2 mm, 1.1 ± 0.2 mm in LR and SI directions, respectively. Conclusion: We have developed the verification method of respiratory gating combined TrueBeam and new real-time tumor-tracking radiotherapy system using EPIDs and log files.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Application of a new hybrid particle swarm optimization-mixed kernels function-based support vector machine model for reservoir porosity prediction: A case study in Jacksonburg-Stringtown oil field, West Virginia, USA

Porosity is a fundamental property that characterizes the storage capability of fluid and gas-bearing formations in a reservoir. An accurate porosity value can be measured from core samples in the laboratory; however, core analysis is expensive and time consuming. Well-log data can be used to calculate porosity, but the availability of log suites is often limited in mature fields. Therefore, robust porosity prediction requires integration of core-measured porosity with available well-log suites to control for changes in lithology and fluid content. A support vector machine (SVM) model with mixed kernel function (MKF) is used to construct the relationship between limited conventional well-log suites and sparse core data. Porosity is the desired output, and two conventional well-log responses (gamma ray [GR] and bulk density) and three well-log-derived parameters (the slope of GR, the slope of density, and [Formula: see text]) are input parameters. A global stochastic searching algorithm, particle swarm optimization (PSO), is applied to improve the efficiency of locating the appropriate values of five control parameters in MKF-SVM model. The results of SVM with different traditional kernel functions were compared, and the MKF-SVM model provided an improvement over the traditional SVM model. To confirm the advantage of the hybrid PSO-MKF-SVM model, the results from three models: (1) radial basis function (RBF)-based least-squares SVM, (2) multilayer perceptron artificial neural network (ANN), and (3) RBF ANN, are compared with the result of the hybrid PSO-MKF-SVM model. The results indicate that the hybrid PSO-MKF-SVM model improves porosity prediction with the highest correlation coefficient ([Formula: see text] of 0.9560), the highest coefficient of determination ([Formula: see text] of 0.9140), the lowest root-mean-square error (1.6505), average absolute error value (1.4050), and maximum absolute error (2.717).

Geochemistry & Geophysics↗

DOE OSTI2020

Multi-Scale Lithofacies and Chemostratigraphic Analysis of Two Middle Devonian Marcellus Shale Wells in Northern West Virginia, USA

The Marcellus Shale Energy and Environmental Laboratory (MSEEL) consists of two project areas within the dry gas producing region of the Marcellus shale play in Monongalia County, West Virginia. MSEEL is a collaborative field project led by West Virginia University, with Northeast Natural Energy LLC, several industrial partners, and sponsored by the US Department of Energy National Energy Technology Laboratory. The study areas are drilled approximately 8.5 miles apart to better understand the vertical and lateral changes in stratigraphy over a short distance. Two vertical pilot wells, MIP-3H and Boggess 17H were drilled in the fall of 2015 and spring of 2019, respectively. Core was recovered from the MIP-3H (API: 47-061-01707-00-00) 112 feet (34m) between depths of 7445 to 7557 feet, and from the Boggess 17H (API: 47-061-01812-00-00) 139 feet (42m) between depths of 7908 and 8012 ft. A full suite of triple combo (gamma ray, neutron, density logs), image logs, and advanced logging tools were run in both wells and calibrated to core analysis. Core analysis includes medical computed tomography (CT) scans, mineralogy and chemostratigraphy determined from handheld X-Ray fluorescence (hhXRF) and X-Ray powder diffraction (XRD) measurements, and determination of total organic content (TOC). Lithofacies were determined at core-scale using traditional core description techniques and medical CT-scan images. Log-scale facies are based on mineralogy and TOC data and developed using petrophysical logging data calibrated to core data (XRD and pyrolysis data). Chemostratigraphic analysis utilized hhXRF data to determine the major and trace element trends in the cores. In the two wells six shale lithofacies were recognized at the core and log scale. Both wells show organic-rich facies (TOC > 6.5%) primarily in the middle and lower Marcellus, with a slight decrease in thickness of this interval in the Boggess 17H. This interval is interpreted as an increase in paleo-productivity (increased Ni, Zn, and V), decreased sedimentation (decreased detrital proxies), and anoxic to euxinic conditions (increased Mo and chalcophile elements). Paleo-redox conditions in both wells are dynamic throughout deposition transitioning between euxinic/anoxic to dysoxic/oxic. This trend is seen through elemental proxies and calcite/pyrite concretion distributions.

03 NATURAL GAS↗

DOE OSTI2019

Frio 2 : Raw CASSM Datasets

This submission contains the raw SEG-2 seismic datasets acquired in the CASSM experiment, part of the Frio-2 GCS pilot. The directory also includes the log files generated by the Geode seismograph (geometrics) used during acquisition. All SEG-2 files have a ".dat" suffix and log files have a ".log" suffix. Various supplementary files are also included (see below) including a set of flow and seismic models used in interpretation. The earlyGathers.tar.gz resource includes raw data acquired during system testing and pre-injection periods. All files correspond to the single source continuous active source seismic monitoring (CASSM) dataset described in the following papers. Daley, T.M., Solbau, R.D., Ajo-Franklin, J.B., and Benson, S.M. 2007, “Continuous Active-Source Seismic Monitoring of CO2 Injection in a Brine Aquifer”, Geophysics, Vol. 72, No. 5, p. A57-A61 Daley, T., Ajo-Franklin, J.B., and C. Doughty, 2011, “Constraining the reservoir model of an injected CO2 plume with crosswell CASSM at the Frio-II Brine Pilot”, International Journal of Greenhouse Gas Control (IJGGC), Vol. 5, No. 2, pp. 1022-1030. Zhu, T., Ajo-Franklin, J., and T. Daley, 2017, “Spatio-temporal changes in seismic attenuation caused by injected CO2 at the Frio-II pilot site, Dayton TX, USA”, Journal of Geophysical Research – Solid Earth, Vol. 122, No. 9, pp. 7156-7171. cassmDataRaw.tar : The main tar file containing all of the SEG-2 field records and the Geode log files. Stacking, time sampling (dt), and date information should be in the .log file. Each file corresponds to a single stacked gather for the single source deployed. Data was recorded on a 24 channel downhole hydrophone array. fieldNotes.tar : contains some of the scanned observer logs from the experiments as well as some planning images fieldPhotos.tar : contains a small set of photographs taken during the experiment frio_flow_seismic_models.mat : a matlab structure containing a set of flow and seismic models used in interpreting the CASSM data (see IJGGC paper).

GCS↗

DOE OSTI2022

A Mountaintop View Requires Minimal Sorting: A Faster Contour Tree Algorithm

Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in R d . A level set, or contour, at value v is a connected component of f –1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$ pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$ pϵP |p| log |p| complexity is inherent to computing contour trees.

97 MATHEMATICS AND COMPUTING↗