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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Zero-Truncated Poisson Tensor Decomposition for Sparse Count Data

We propose a novel statistical inference paradigm for zero-inflated multiway count data that dispenses with the need to distinguish between true and false zero counts. Our approach ignores all zero entries and applies zero-truncated Poisson regression on the positive counts. Inference is accomplished via tensor completion that imposes low-rank structure on the Poisson parameter space. Our main result shows that an $\textit{N}$-way rank-R parametric tensor 𝓜 ϵ (0, ∞) $I$Χ∙∙∙Χ$I$ generating Poisson observations can be accurately estimated from approximately $IR^2 \text{log}^2_2(I)$ non-zero counts for a nonnegative canonical polyadic decomposition. Several numerical experiments are presented demonstrating that our zero-truncated paradigm is comparable to the ideal scenario where the locations of false zero counts are known $\textit{a priori}$.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

lllinois Storage Corridor CarbonSAFE Phase III: Pre-drilling Site Assessment: Prairie State Generating Company

The Illinois Storage Corridor project will drill a stratigraphic test well as part of the Illinois Storage Corridor CarbonSAFE Phase 3 project near the Prairie State Generating Company coal-fired power plant near Marissa, Illinois. The pre-drilling site evaluation has considered the primary target reservoirs, the Potosi Dolomite and St. Peter Sandstone, and primary seal, the Maquoketa Group. Data to be collected from the well include core, fluid samples, in situ well tests, geophysical logs intended to provide information on lithologic, geomechanical, and geophysical characteristics to determine the feasibility for the geologic sequestration of 50 million metric tons or more of injected carbon dioxide. The planned drilling site has been evaluated using available subsurface geologic data and analyses from the Illinois Basin. These data provide lithologic and structural information, shallow groundwater resource distribution, location of known nearby wellbores, and regional drilling characteristics. The data were used to generate geologic structure and isopach maps for the target reservoir and caprock strata and for prognosing the tops of major lithologic units to aid drilling and coring procedures. The regional analyses indicate that no known structural features are expected to negatively impact the target storage reservoir or caprock. No protected and sensitive areas, groundwater resources, or existing resource development are expected to be impacted by the proposed well drilling activities. The well is planned to be drilled to a total depth of approximately 5,600 feet (1,707 m) and terminate in the Precambrian. Cores (up to 5 intervals) will be collected from the Maquoketa Group, confining units above the St. Peter Sandstone, St. Peter Sandstone, confining units of the Potosi Dolomite and the Potosi Dolomite. Water samples will be attempted to be collected from the St. Peter Sandstone and Potosi Dolomite. Potential impact on drilling progress is a lost circulation zone in the Potosi Dolomite, which has been demonstrated to have intermittent cavernous porosity from karstification elsewhere in the Illinois Basin. This document also presents a preliminary coring and sampling program, proposed logging suite, and well testing program, all of which will be reviewed during drilling.

01 COAL, LIGNITE, AND PEAT↗
NASA NTRS1998

The Study of Clusters of Galaxies and Large Scale Structures

The work on the ROSAT Deep Survey has been successfully completed. A number of interesting results have been established within this joint MPE, Cal Tech, JHU, ST Scl, ESO collaboration. First, a very large fraction, 70-80 percent, of the X-ray background has been directly resolved into point sources. We have derived a new log N-log S for X- ray sources and have measured a source density of 970 sources per square degree at a limiting flux level of 10(exp -15)/erg s sq cm (0.5-2.0 keV). Care was taken in these studies to accurately model and measure the effects of sources confusion. This was possible because of our observing strategy which included both deep PSPC and HRI observations. In the last year we initiated work in the design and development of the Next Generation Space Telescope.

Source record↗
DOE OSTI2021

25 Siβ + -decay spectroscopy

Background: β-decay spectroscopy provides valuable information on exotic nuclei and a stringent test for nuclear theories beyond the stability line. Purpose: To search for new β-delayed protons and γ rays of 25 Si to investigate the properties of 25 Al excited states. Method: 25 Si β decays were measured by using the Gaseous Detector with Germanium Tagging system at the National Superconducting Cyclotron Laboratory. The protons and γ rays emitted in the decay were detected simultaneously. Here, a Monte Carlo method was used to model the Doppler broadening of 24 Mg γ-ray lines caused by nuclear recoil from proton emission. Shell-model calculations using two newly developed universal sd-shell Hamiltonians were performed. Results: The most precise 25Si half-life to date has been determined. A new proton branch at 724(4) keV and new proton-γ-ray coincidences have been identified. Three 24 Mg γ-ray lines and eight 25 Al γ-ray lines are observed for the first time in 25 Si decay. The first measurement of the 25 Si β-delayed γ-ray intensities through the 25 Al unbound states is reported. All the bound states of 25 Al are observed to be populated in the β decay of 25 Si. Several inconsistencies between the previous measurements have been resolved, and new information on the 25 Al level scheme is provided. An enhanced decay scheme has been constructed and compared to the mirror decay of 25 Na and the shell-model calculations. Conclusions: The measured excitation energies, γ-ray and proton branchings, log $ft$ values, and Gamow-Teller transition strengths for the states of 25 Al populated in the β decay of 25 Si are in good agreement with the shell model calculations, offering gratifyingly consistent insights into the fine nuclear structure of 25 Al.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Performance evaluation of the USGS velocity model for the San Francisco Bay Area

In this study, we evaluated the performance of the United States Geological Survey velocity model developed for the San Francisco Bay Area (SFBA), version 21.1. The evaluation was performed through high-resolution three-dimensional physics-based ground motion simulations of seven small-magnitude earthquakes (ranging from magnitude 3.8 to 4.4) that occurred on the eastern side of the San Francisco Bay. The simulations were performed in the frequency range from 0 to 5 Hz with a minimum shear-wave velocity of 250 m/s, which allowed the capture of wave propagation effects of the near-surface soft materials that characterize local basins. Based on the direct comparison of Fourier amplitude spectra between recorded and simulated ground motions for more than 250 stations, we found that the velocity model generally performs well in the frequency range of 0.2–5 Hz. The median value of the Fourier amplitude residuals was found to be near zero for all seven earthquakes. The slight over-prediction of 0.2 log-natural units at frequencies above 3 Hz in our simulations was attributed to the potentially inaccurate representation of the source radiation pattern by a double-couple point source model, and simple representation of shallow small-scale underground structural complexity in the velocity model. Maps of spectral amplitude differences between the simulated and recorded data were used to identify areas responsible for systematic ground motion over-predictions or under-predictions. For example, while some sub-domains over soft sediments show over-prediction patterns, the block east of the Hayward fault is prone to exhibit patterns of under-prediction. These maps can be used to guide future refinements of the SFBA velocity model. Since our simulation methodology allows for the decoupling of the source and wave propagation effects, the ground motion data generated by our simulations can also be used to quantify the epistemic uncertainty due to the velocity model, in empirically based ground motion estimates for the SFBA.

58 GEOSCIENCES↗
DOE OSTI2025

Roughrider Carbon Storage Hub (Final Report)

The Roughrider Carbon Storage Hub was a 2-year project (October 2023 – September 2025) conducted by the Energy & Environmental Research Center (EERC) focused on advancing the feasibility of a commercial-scale carbon dioxide (CO 2 ) geologic storage hub in McKenzie County, North Dakota. The project’s objective was to investigate the potential that stacked storage complexes (multiple deep saline formations) can safely and economically store at least 50 million tonnes of CO 2 within 30 years. The captured CO 2 would be sourced from industrial emitters including project partner ONEOK, Inc.’s gas-processing plants and a planned gas-to-liquids facility. Drilling of the Roughrider 1 stratigraphic test well (14,979-ft total depth) was completed in November 2024. The wellbore intersected four candidate storage formations: Inyan Kara, Broom Creek, Mission Canyon, and Black Island–Deadwood. Operational challenges, including a stuck drill string, were resolved without long-term impact. A comprehensive logging and coring program was conducted, followed by successful well abandonment and site reclamation. Over 660 ft of 4-in. whole core was retrieved. Core plug samples were processed and analyzed for petrophysical and geochemical properties. Results confirmed promising porosity and permeability in the Inyan Kara and Broom Creek Formations and removal of the Mission Canyon and Black Island–Deadwood horizons from further investigation. Data derived from the logging and coring program were used to improve initial geologic models built from legacy data. CO 2 injection simulations showed that the Inyan Kara alone can feasibly store the target mass of CO 2 . Because of subtle differences in geologic structure and porosity trends between the formations, a stacked storage scenario using the Broom Creek and Inyan Kara Formations resulted in a larger overall plume area than using the Inyan Kara alone. Preliminary CO 2 pipeline routes from the industrial sources were mapped utilizing existing rights of way and evaluated for capacity and cost using U.S. Department of Energy Office of Fossil Energy and Carbon Management/National Energy Technology Laboratory models and U.S. Environmental Protection Agency emissions data. Integrating capture, transport, and storage cost estimates with policy incentives (e.g., 45Q credits) provided a total cost-per-ton analysis. Results indicate that the small scale of the volumes to be transported over the cumulative large distances does not support the project’s financial viability. However, the groundwork laid during this project from geological, regulatory, and social perspectives positions the Roughrider hub site as a promising candidate for commercial carbon storage in North Dakota, especially if the economy of scale is introduced for CO 2 transportation to the hub site.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2026

Quantum block encoding for one-pair semiseparable matrices

Quantum block encoding (QBE) is a crucial step in the development of most quantum algorithms, as it provides an embedding of a given matrix into a suitable larger unitary matrix. Historically, the development of efficient techniques for QBE has mostly focused on sparse matrices; less effort has been devoted to data-sparse (e.g., rank-structured) matrices. In this work we examine a particular case of rank structure, namely, one-pair semiseparable matrices. We present a new block encoding approach that relies on a suitable factorization of the given matrix as the product of triangular and diagonal factors. To encode the matrix, the algorithm needs $2\log(N)+7$ ancillary qubits. Assuming that the data input oracles can be implemented with polylogarithmic depth, or that a QRAM input model is available, our proposed method requires $\mathcal{O}({\rm polylog} (N))$ time and has an error of $\mathcal{O}(N^2)$, where $N$ is the matrix size.

Antonioli, Giacomo [Pisa U.; CERN] (ORCID:00090000↗
DOE OSTI2022

B/PS bulges in DESI Legacy edge-on galaxies – I. Sample building

ABSTRACT We present the biggest up-to-date sample of edge-on galaxies with boxy/peanut-shaped (B/PS) bulges and X-structures. The sample was prepared using images from the Dark Energy Spectroscopic Instrument (DESI) Legacy catalogue and contains about 2000 galaxies. To find suitable candidates in catalogue, we made the assumption that the residues (original images minus model) of galaxies with B/PS bulges should exhibit a characteristic X-shape. Galaxies with such features were selected by eye and then used as input data for a neural network training, which was applied to a bigger sample of edge-on galaxies. Using the available data and the photometric models from the literature, we investigated the observational and statistical properties of the sample created. Comparing the B/D ratios for galaxies with and without B/PS bulges, we found that the B/D ratio for galaxies from our sample is statistically higher, with typical values in the range ≈0.2–0.5 depending on the decomposition procedure. We studied how the opening angles φ of the X-structure and the length of its rays are distributed in the formed sample and found them to be consistent with previous measurements and predictions from N-body models, e.g. $\varphi \gtrsim 25{^\circ }$, but measured here for a much larger number of galaxies. We found a sharp increase in the B/PS bulge fraction for stellar masses log M⋆ ≳ 10.4, but for edge-on galaxies, which complements the results of previous works. The sample can be used in future work to test various bar models and their relationship with B/PS bulges, as well as to study their stability and evolution.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Flares, Warps, Truncations, and Satellite: The Ultra-thin Galaxy UGC 11859

The structure of the outskirts of galaxies provides valuable information about their past and evolution. Due to their projected orientation, edge-on isolated galaxies effectively serve as test labs in which to study the three-dimensional structures of galaxies, including warps and flares, and to explore the possible sources of such distortions. We analyzed the structure of the apparently isolated edge-on ultra-thin galaxy UGC 11859 to look for the presence of distortions. The deep optical imaging observations (${\mu }_{\mathrm{lim}}=30.6$ and 30.0 $\mathrm{mag}\ {\mathrm{arcsec}}^{-2}$ in the g- and r-bands, respectively) we acquired with the 10.4 m Gran Telescopio Canarias are used to derive the radial and vertical surface brightness profiles and g - r color radial profile. We find that UGC 11859's disk displays a significant gravitational distortion. A warp is clearly detected on one side of the disk, and the galactic plane on both sides of the center shows increasing scale height with an increasing galactocentric radius, indicating the presence of a flare in the stellar distribution. The surface brightness profile of the disk shows a sharp break at 24 kpc galactocentric radius, and a steep decline to larger radii, an "edge-on truncation," which we associate with the presence of the flare. The present study is the first observational support for a connection between truncations and flares. Just beyond the warped side of the disk, a faint galaxy is observed within a small angular distance, identified as a potential interacting companion. Based on ultradeep g and r photometry we estimate that if the potential companion is at the same distance as UGC 11859, the stellar mass of the satellite galaxy is log 10 (M ⊙ ) = ${6.33}_{-0.02}^{+0.02}$ .

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

Repurposing Drilling Control Diagnostics for Subsurface Edge Detection and Boundary Advisement During Planetary Drilling

Informed decision-making during lunar drilling and sampling missions will require data monitoring tools and specialized ground data systems. Accurate and updated situational awareness, with ongoing data monitoring, is critical for timely responses by to incoming science data. Traverse plans and scheduled activities may need to be flexibly changed in order to react to unexpected data or situations. Unlike (for example) Mars missions, the relative lightspeed closeness of the Moon allows for near-real-time ground processing of incoming mission and instrument data. An Apollo-class lunar regolith drill will in a sense “travel” a meter or two vertically at a given subsurface characterization site. As the drill penetrates into lunar regolith, it is likely to encounter a range of material densities, orientations, fracture toughness, and (perhaps) ice percentages. Lunar drill telemetry can provide science teams with a valuable first look into the subsurface structure, the regolith bulk properties, and constituents at each drilled site. Real-time AI-based recognition and reaction to downhole situations has been developed for automated deeper drilling on Mars and beyond. We can leverage the same knowledge bases and pattern-matching as areal-time interpreter of the subsurface, a situational awareness tool during drilling operations. We recently (Sept. 2019) demonstrated this AI drilling monitoring and analysis capability, in control of in-situ drilling and sampling operations, mounted on a KREX-2 rover in Chile’s Atacama Desert. Terrestrial automated drilling log analyses in oil exploration have used similar machine learning techniques in classifying and identifying features in drilling logs –but these typically are designed assuming a drilling fluid influencing downhole measurements and data (permeability, resistivity). Drilling models and existing AI software designed to detect and respond to drilling faults and hard materials can be repurposed, for near-real-time (ground-based) interpretation of drilling telemetry –a potentially valuable advisory tool for strata boundaries and changes in drilling parameters. On the Moon, this approach could be used to study the structure and to some extent the composition of lunar regolith vs. borehole depth, based on recognizable variations in fracture hardness, drilling energy and penetration rates while actively drilling. Since the early 2000s, a series of increasingly-capable real-time drilling telemetry interpretation and characterization software tools have been developed. These subsurface models and software tools have monitored the real-time drilling data received, and automatically identified changes in drill behavior (e.g., encountering a harder target layer, bit inclusions, drill choking due to infall downhole, and others) correlating these with subsurface structures and features. We discuss the mappings between drill borehole parameters, faults or events detected, and modeled changes in rock layer boundaries, in examples drawn from field testing at analog sites in an Arctic impact crater, Rio Tinto, and Chile’s Atacama Desert. These demonstrate how subsurface structural boundaries led to fault detections and responses by the software.

drilling advisor↗
DOE OSTI2020

Measurement of groomed jet substructure observables in p+p collisions at $\sqrt{s} =$ 200 GeV with STAR

In this letter, measurements of the shared momentum fraction ( z g ) and the groomed jet radius ( R g ), as defined in the SoftDrop algorithm, are reported in p+p collisions at s = 200 GeV collected by the STAR experiment. These substructure observables are differentially measured for jets of varying resolution parameters from R = 0.2 – 0.6 in the transverse momentum range 15 < p T , jet < 60 GeV/ c . These studies show that, in the p T , jet range accessible at s = 200 GeV and with increasing jet resolution parameter and jet transverse momentum, the z g distribution asymptotically converges to the DGLAP splitting kernel for a quark radiating a gluon. The groomed jet radius measurements reflect a momentum-dependent narrowing of the jet structure for jets of a given resolution parameter, i.e., the larger the p T , jet , the narrower the first splitting. For the first time, these fully corrected measurements are compared to Monte Carlo generators with leading order QCD matrix elements and leading log in the parton shower, and to state-of-the-art theoretical calculations at next-to-leading-log accuracy. We observe that PYTHIA 6 with parameters tuned to reproduce RHIC measurements is able to quantitatively describe data, whereas PYTHIA 8 and HERWIG 7, tuned to reproduce LHC data, are unable to provide a simultaneous description of both z g and R g , resulting in opportunities for fine parameter tuning of these models for p+p collisions at RHIC energies. We also find that the theoretical calculations without non-perturbative corrections are able to qualitatively describe the trend in data for jets of large resolution parameters at high p T , jet , but fail at small jet resolution parameters and low jet transverse momenta.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Porous Colloidal Nanoparticles as Injectable Multimodal Contrast Agents for Enhanced Geophysical Sensing

Injecting fluids into underground geologic structures is crucial for the development of long-term strategies for managing captured carbon and facilitating sustainable energy extraction operations. Here, we have previously reported that the injection of metal–organic frameworks (MOFs) into the subsurface can enhance seismic monitoring tools to track fluids and map complex structures, reduce risk, and verify containment in carbon storage reservoirs because of their absorption capacity of low-frequency seismic waves. Here, we demonstrate that water-based Cr/Zn/Zr MOF colloidal suspensions (nanofluids) are multimodal geophysical contrast agents that enhance near-wellbore logging tools. Based on experimental fluid-only measurements, MIL-101(Cr), ZIF-8, and UiO-66 nanofluids have distinct complex conductivity and/or low-field nuclear magnetic resonance (NMR) signatures that are relevant to field-deployed technologies, implying the potential to enhance near-wellbore monitoring of CO 2 injection and associated processes with downhole logging tools. Small- and wide-angle X-ray scattering characterization of ~0.5 wt % MIL-101(Cr) suspensions confirmed phase stability and provided insight into the fractal nature of colloidal nanoparticles. Finally, low-field (2 MHz) NMR measurements of MIL-101(Cr) nanofluid injection into a prototypical Berea sandstone demonstrate how paramagnetic high-surface area MOFs may dominate the relaxation times of hydrogen-bearing fluids in porous geologic matrices, enhancing the mapping of near-surface and near-wellbore transport pathways and advancing sustainable subsurface energy technologies.

NMR↗
DOE OSTI2023

MaNGA galaxy properties – II. A detailed comparison of observed and simulated spiral galaxy scaling relations

ABSTRACT We present a catalogue of dynamical properties for 2368 late-type galaxies from the MaNGA survey. The latter complements the catalogue of photometric properties for the same sample based on deep optical dark energy sky instrument legacy imaging survey (DESI) photometry processed with autoprof . Rotation curves (RCs), extracted by model-fitting H α velocity maps from the MaNGA Data Analysis Pipeline, extend out to 1.4 (1.9) Re for the primary (secondary) MaNGA samples, respectively. The RCs and ancillary MaNGA Pipe3D data products were used to construct various fundamental galaxy scaling relations that are also compared uniformly with similar relations from numerical investigation of a hundred astrophysical object (NIHAO) zoom-in simulations. Simulated NIHAO galaxies were found to broadly reproduce the observed MaNGA galaxy population for $\log (M_*/{\rm {\rm M}_{\odot })\, \gt\, 8.5}$. Some discrepancies remain, such as those pertaining to central stellar densities and the diversity of RCs due to strong feedback schemes. Also presented are spatially resolved scatters for the velocity-size-stellar mass (VRM*) structural relations using MaNGA and NIHAO samples. The scatter for these relations in the galaxian interiors is a consequence of the diversity of inner RC shapes, while scatter in the outskirts is dictated by the large range of stellar surface densities, which is itself driven by sporadic star formation. The detailed, spatially resolved scatter analysis highlights the complex interplay between local and global astrophysical processes and provides a strong constraint to numerical simulations.

Astronomy & Astrophysics↗
DOE OSTI2024

Mechanisms and models of the turbulent boundary layers at transcritical conditions

Computational models for high-pressure transcritical turbulence in wall-modeled large-eddy simulation typically rely on wall-function models to overcome the need for resolving the boundary layer structures. However, the mechanisms and models of turbulent boundary layer at transcritical conditions remain poorly understood since the near-wall flow and heat transfer are significantly affected by the enhanced fluctuations and steep gradients in thermodynamic properties. Here, to address this issue, we study the mechanisms of transcritical turbulent boundary layers and wall-attached models at transcritical conditions. It is shown that the real-fluid variable-property effects are associated with the coupling between the near-wall cycle and the wall-normal coherent motions in the outer layer, resulting in the amplification of turbulent energy in the outer layer and noticeable energy transfer between the log-layer and the outer layer; hence, turbulence in the log-layer is modulated by the outer layer. Based on this underlying physical principle, we propose the characteristic velocity and length scales for the attached eddy at transcritical conditions, and extend the attached eddy model to transcritical turbulent boundary layers by introducing a mixed scaling that incorporates both inner and outer scalings. We show that the new characteristic scales and extended attached-eddy model perform well in characterizing the structures in transcritical turbulent boundary layers.

Li, Fangbo↗
DOE OSTI2022

MgADP Promotes Myosin Head Movement toward Actin at Low [Ca 2+ ] to Increase Force Production and Ca 2+ -Sensitivity of Contraction in Permeabilized Porcine Myocardial Strips

Myosin cross-bridges dissociate from actin following Mg 2+ -adenosine triphosphate (MgATP) binding. Myosin hydrolyses MgATP into inorganic phosphate (P i ) and Mg 2+ -adenosine diphosphate (ADP), and release of these hydrolysis products drives chemo-mechanical energy transitions within the cross-bridge cycle to power muscle contraction. Some forms of heart disease are associated with metabolic or enzymatic dysregulation of the MgATP-MgADP nucleotide pool, resulting in elevated cytosolic [MgADP] and impaired muscle relaxation. We investigated the mechanical and structural effects of increasing [MgADP] in permeabilized myocardial strips from porcine left ventricle samples. Sarcomere length was set to 2.0 µm at 28 °C, and all solutions contained 3% dextran T-500 to compress myofilament lattice spacing to near-physiological values. Under relaxing low [Ca 2+ ] conditions (pCa 8.0, where pCa = -log 10 [Ca 2+ ]), tension increased as [MgADP] increased from 0-5 mM. Complementary small-angle X-ray diffraction measurements show that the equatorial intensity ratio, I 1,1 /I 1,0 , also increased as [MgADP] increased from 0 to 5 mM, indicating myosin head movement away from the thick-filament backbone towards the thin-filament. Ca 2+ -activated force-pCa measurements show that Ca 2+ -sensitivity of contraction increased with 5 mM MgADP, compared to 0 mM MgADP. These data show that MgADP augments tension at low [Ca 2+ ] and Ca 2+ -sensitivity of contraction, suggesting that MgADP destabilizes the quasi-helically ordered myosin OFF state, thereby shifting the cross-bridge population towards the disordered myosin ON state. Together, these results indicate that MgADP enhances the probability of cross-bridge binding to actin due to enhancement of both thick and thin filament-based activation mechanisms.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Properly Learning Decision Trees in almost Polynomial Time

We give an n O (log log n ) -time membership query algorithm for properly and agnostically learning decision trees under the uniform distribution over { ± 1} n . Even in the realizable setting, the previous fastest runtime was n O (log n ) , a consequence of a classic algorithm of Ehrenfeucht and Haussler. Our algorithm shares similarities with practical heuristics for learning decision trees, which we augment with additional ideas to circumvent known lower bounds against these heuristics. To analyze our algorithm, we prove a new structural result for decision trees that strengthens a theorem of O’Donnell, Saks, Schramm, and Servedio. While the OSSS theorem says that every decision tree has an influential variable, we show how every decision tree can be “pruned” so that every variable in the resulting tree is influential.

Computer Science↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗