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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

HOSS: an implementation of the combined finite-discrete element method

Nearly thirty years since its inception, the combined finite-discrete element method (FDEM) has made remarkable strides in becoming a mainstream analysis tool within the field of Computational Mechanics. FDEM was developed to effectively “bridge the gap” between two disparate Computational Mechanics approaches known as the finite and discrete element meth-ods. At Los Alamos National Laboratory (LANL) researchers developed the Hybrid Optimization Software Suite (HOSS) as a hybrid multi-physics platform, based on FDEM, for the simulation of solid material behavior complemented with the latest technological enhancements for full fluid–solid interaction. Furthermore, in HOSS, several newly developed FDEM algorithms have been implemented that yield more accurate material deformation formulations, inter-particle interaction solvers, and fracture and fragmentation solutions. Additionally, an explicit computational fluid dynamics solver and a novel fluid–solid interaction algorithms have been fully integrated (as opposed to coupled) into the HOSS’ solid mechanical solver, allowing for the study of an even wider range of problems. Advancements such as this are leading HOSS to become a tool of choice for multi-physics problems. Finally, HOSS has been successfully applied by a myriad of researchers for analysis in rock mechanics, oil and gas industries, engineering application (structural, mechanical and biomedical engineering), mining, blast loading, high velocity impact, as well as seismic and acoustic analysis. This paper intends to summarize the latest development and application efforts for HOSS.

58 GEOSCIENCES↗
DOE OSTI2022

The MU2E Experiment at FERMILAB: R&D, Design and Status

The Mu2e Experiment at Fermilab 1) will search for coherent, neutrinoless conversion of negative muons into electrons in the field of an aluminum nucleus, µ - + N (A, Z) → e - + N (A, Z). This is an example of Charged Lepton Flavour Violation (CLFV) never observed experimentally. The dynamics of such a process is well modelled by a two-body decay, resulting in a mono-energetic electron with an energy slightly below the muon rest mass (~104.967 MeV). If no events are observed in three years of running, Mu2e will set an upper limit on the ratio between conversion and capture rate R µe ≤ 6 × 10 -17 (@ 90% C.L.). This will improve the current limit of a factor of 10 4 over previous experiments. The experiment complements and extends the current/planned searches (µ → eγdecay at MEG , mu3e) as well as the direct searches for new physics at the LHC. Indeed, such CLFV searches in the muon sector probe new physics at a mass scale inaccessible with direct searches at either present or planned high-energy colliders. To detect the muon conversion process, a very intense pulsed beam of negative muons is produced by means of a S-shape Superconducting Solenoid Magnet System that is organized into three subsystems: the Production Solenoid, the Transport Solenoid and the Detector Solenoid. The beam is stopped at 10 GHz on an Aluminum target inside the Detector Solenoid. The Mu2e detectors, also installed inside the Detector Solenoid, are a high-precision tracker made on ~20000 straw tubes, and a calorimeter composed of ~1500 pure CsI crystals organized in two disks and readout by two large area UV-extended Silicon Photomultipliers (SiPMs). The Detector Solenoid region is surrounded by a Cosmic Ray Veto based on scintillators readout by SiPMs.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Structure and dynamics of ethane confined in silica nanopores in the presence of CO 2

Fundamental understanding of the subcritical/supercritical behavior of key hydrocarbon species inside nano-porous matrices at elevated pressure and temperature is less developed compared to bulk fluids, but this knowledge is of great importance for chemical and energy engineering industries. This study explores in detail the structure and dynamics of ethane (C 2 H 6 ) fluid confined in silica nanopores, with a focus on the effects of pressure and different ratios of C 2 H 6 and CO 2 at non-ambient temperature. Quasi-elastic neutron scattering (QENS) experiments were carried out for the pure C 2 H 6 , C 2 H 6 :CO 2 = 3:1, and 1:3 mixed fluids confined in 4-nm cylindrical silica pores at three different pressures (30 bars, 65 bars, and 100 bars) at 323 K. Two Lorentzian functions were required to fit the spectra, corresponding to fast and slow translational motions. No localized motions (rotations and vibrations) were detected. Higher pressures resulted in hindrances of the diffusivity of C 2 H 6 molecules in all systems investigated. Pore size was found to be an important factor, i.e., the dynamics of confined C 2 H 6 is more restricted in smaller pores compared to the larger pores used in previous studies. Molecular dynamics simulations were performed to complement the QENS experiment at 65 bars, providing supportive structure information and comparable dynamic information. The simulations indicate that CO 2 molecules are more strongly attracted to the pore surface compared to C 2 H 6 . The C 2 H 6 molecules interacting with or near the pore surface form a dense first layer (L1) close to the pore surface and a second less dense layer (L2) extending into the pore center. Both the experiments and simulations revealed the role that CO 2 molecules play in enhancing C 2 H 6 diffusion (“molecular lubrication”) at high CO 2 :C 2 H 6 ratios. The energy scales of the two dynamic components, fast and slow, quantified by both techniques, are in very good agreement. Herein, the simulations identified the fast component as the main contributor to the dynamics. Molecule motions in the L2 region are mostly responsible for the dynamics (fast and slow) that can be detected by the instrument.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Advancing river corridor science beyond disciplinary boundaries with an inductive approach to catalyse hypothesis generation

Abstract A unified conceptual framework for river corridors requires synthesis of diverse site‐, method‐ and discipline‐specific findings. The river research community has developed a substantial body of observations and process‐specific interpretations, but we are still lacking a comprehensive model to distill this knowledge into fundamental transferable concepts. We confront the challenge of how a discipline classically organized around the deductive model of systematically collecting of site‐, scale‐, and mechanism‐specific observations begins the process of synthesis. Machine learning is particularly well‐suited to inductive generation of hypotheses. In this study, we prototype an inductive approach to holistic synthesis of river corridor observations, using support vector machine regression to identify potential couplings or feedbacks that would not necessarily arise from classical approaches. This approach generated 672 relationships linking a suite of 157 variables each measured at 62 locations in a fifth order river network. Eighty four percent of these relationships have not been previously investigated, and representing potential (hypothetical) process connections. We document relationships consistent with current understanding including hydrologic exchange processes, microbial ecology, and the River Continuum Concept, supporting that the approach can identify meaningful relationships in the data. Moreover, we highlight examples of two novel research questions that stem from interpretation of inductively‐generated relationships. This study demonstrates the implementation of machine learning to sieve complex data sets and identify a small set of candidate relationships that warrant further study, including data types not commonly measured together. This structured approach complements traditional modes of inquiry, which are often limited by disciplinary perspectives and favour the careful pursuit of parsimony. Finally, we emphasize that this approach should be viewed as a complement to, rather than in place of, more traditional, deductive approaches to scientific discovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

GTP binding by Arabidopsis extra-large G protein 2 is not essential for its functions

The extra-large guanosine-5'-triphosphate (GTP)-binding protein 2, XLG2, is an unconventional Gα subunit of the Arabidopsis (Arabidopsis thaliana) heterotrimeric GTP-binding protein complex with a major role in plant defense. In vitro biochemical analyses and molecular dynamic simulations show that affinity of XLG2 for GTP is two orders of magnitude lower than that of the conventional Gα, AtGPA1. Here we tested the physiological relevance of GTP binding by XLG2. We generated an XLG2(T476N) variant with abolished GTP binding, as confirmed by in vitro GTPγS binding assay. Yeast three-hybrid, bimolecular fluorescence complementation, and split firefly-luciferase complementation assays revealed that the nucleotide-depleted XLG2(T476N) retained wild-type XLG2-like interactions with the Gβγ dimer and defense-related receptor-like kinases. Both wild-type and nucleotide-depleted XLG2(T476N) restored the defense responses against Fusarium oxysporum and Pseudomonas syringae compromised in the xlg2 xlg3 double mutant. Additionally, XLG2(T476N) was fully functional restoring stomatal density, root growth, and sensitivity to NaCl, but failed to complement impaired germination and vernalization-induced flowering. We conclude that XLG2 is able to function in a GTP-independent manner and discuss its possible mechanisms of action.

Plant Sciences↗
DOE OSTI2022

Reflection and transmission of electromagnetic pulses at a planar dielectric interface -- theory and quantum lattice simulations

There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is described by Maxwell equations with an appropriate description of the plasma as a dielectric medium. Before advancing to the tensor dielectric of a magnetized plasma, this paper considers electromagnetic wave propagation in a one-dimensional inhomogeneous scalar dielectric. The classic theory of scattering of plane electromagnetic waves at a planar interface, separating two different dielectric media, leads to Fresnel equations for reflection and transmission coefficients. In contrast to plane waves, this paper is on the reflection and transmission of a spatially confined electromagnetic pulse. Following an analytical formulation for the scattering of a Gaussian pulse, it is deduced that the maximum transmission coefficient for a pulse is $\sqrt{n_2/n_1}$ times that for a plane wave; the incident and transmitted pulses propagating in dielectric media with refractive indices $n_1$ and $n_2$, respectively. The analytical theory is complemented by numerical simulations using a quantum lattice algorithm for Maxwell equations. The algorithm, based on the Riemann-Silberstein-Weber representation of the electromagnetic fields and expressed in term of qubits, is an interleaved sequence of entangling operators at each lattice site and unitary streaming operators which transmit information from one site to an adjacent lattice site. Besides substantiating results from the theory for Gaussian pulses, numerical simulations show their validity for non-Gaussian pulses. Apart from their time-asymptotic forms, the simulations display an interplay between the incident, reflected, and transmitted pulses in the vicinity of the transition region between two dielectric media.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Targeting One- and Two-Dimensional Ta–Te Structures via Nanotube Encapsulation

Fine control over material synthesis on the nanoscale can facilitate the stabilization of competing crystalline structures. In this report we demonstrate how carbon nanotube reaction vessels can be used to selectively create one-dimensional TaTe 3 chains or two-dimensional TaTe 2 nanoribbons with exquisite control of the chain number or nanoribbon thickness and width. Transmission electron microscopy and scanning transmission electron microscopy reveal the detailed atomic structure of the encapsulated materials. Complex superstructures such as multichain spiraling and apparent multilayer moirés are observed. The rare 2H phase of TaTe 2 (1H in monolayer) is found to be abundant as an encapsulated nanoribbon inside carbon nanotubes. The experimental results are complemented by density functional theory calculations for the atomic and electronic structure, which uncovers the prevalence of 2H-TaTe 2 due to nanotube-to-nanoribbon charge transfer and size confinement. Calculations also reveal new 1T' type charge density wave phases in TaTe 2 that could be observed in experimental studies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Operator inference for non-intrusive model reduction with quadratic manifolds

This paper proposes a novel approach for learning a data-driven quadratic manifold from high-dimensional data, then employing this quadratic manifold to derive efficient physics-based reduced-order models. The key ingredient of the approach is a polynomial mapping between high-dimensional states and a low-dimensional embedding. This mapping consists of two parts: a representation in a linear subspace (computed in this work using the proper orthogonal decomposition) and a quadratic component. The approach can be viewed as a form of data-driven closure modeling, since the quadratic component introduces directions into the approximation that lie in the orthogonal complement of the linear subspace, but without introducing any additional degrees of freedom to the low-dimensional representation. Combining the quadratic manifold approximation with the operator inference method for projection-based model reduction leads to a scalable non-intrusive approach for learning reduced-order models of dynamical systems. Further, applying the new approach to transport-dominated systems of partial differential equations illustrates the gains in efficiency that can be achieved over approximation in a linear subspace.

42 ENGINEERING↗
DOE OSTI2024

Epitopes recognition of SARS-CoV-2 nucleocapsid RNA binding domain by human monoclonal antibodies

Coronavirus nucleocapsid protein (NP) of SARS-CoV-2 plays a central role in many functions important for virus proliferation including packaging and protecting genomic RNA. The protein shares sequence, structure, and architecture with nucleocapsid proteins from betacoronaviruses. The N-terminal domain (NP RBD ) binds RNA and the C-terminal domain is responsible for dimerization. After infection, NP is highly expressed and triggers robust host immune response. The anti-NP antibodies are not protective and not neutralizing but can effectively detect viral proliferation soon after infection. Two structures of SARS-CoV-2 NP RBD were determined providing a continuous model from residue 48 to 173, including RNA binding region and key epitopes. Five structures of NP RBD complexes with human mAbs were isolated using an antigen-bait sorting. Complexes revealed a distinct complement-determining regions and unique sets of epitope recognition. This may assist in the early detection of pathogens and designing peptide-based vaccines. Mutations that significantly increase viral load were mapped on developed, full length NP model, likely impacting interactions with host proteins and viral RNA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Identification and characterization of mono- and bifunctional galactan synthases in the pediatric pathogen Kingella kingae

The emerging pediatric pathogen Kingella kingae elaborates a lipopolysaccharide (LPS) that is extended with a galactofuranose homopolymer called galactan, which is a key virulence determinant that contributes to resistance to complement-mediated and neutrophil-mediated killing. Previous work has demonstrated that the pamABCDE locus is required for galactan synthesis. In this study, mutational studies suggested that the pamC gene product is a UDP-galactofuranose (Galf) transferase and is the galactan synthase. Analysis of genome sequence data revealed two distinct pamC alleles designated pamC1 and pamC2, which correlate with the two galactan structures in K. kingae. Examination of isogenic mutants expressing either pamC1 or pamC2 demonstrated that the pamC alleles are the determinants of galactan structure. Experiments with recombinant PamC1 and PamC2 in vitro established that these proteins are galactan synthases capable of extending synthetic Galf disaccharide acceptors in the presence of UDP-Galf. Homology analysis identified critical amino acids that are essential for PamC1 and PamC2 enzymatic activity both in vitro and in K. kingae. Structural analysis of the in vitro-modified synthetic acceptors implicated PamC1 as a monofunctional enzyme capable of generating a β-(1 → 5) Galf linkage and PamC2 as a bifunctional enzyme capable of generating β-(1 → 3) and β-(1 → 6) Galf linkages. This study advances our understanding of the GT2 family of UDP-galactofuranosyltransferases.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Detection of open cluster rotation fields from Gaia EDR3 proper motions

Context: Most stars from in groups which with time disperse, building the field population of their host galaxy. In the Milky Way, open clusters have been continuously forming in the disk up to the present time, providing it with stars spanning a broad range of ages and masses. Observations of the details of cluster dissolution are, however, scarce. One of the main difficulties is obtaining a detailed characterisation of the internal cluster kinematics, which requires very high-quality proper motions. For open clusters, which are typically loose groups with tens to hundreds of members, there is the additional difficulty of inferring kinematic structures from sparse and irregular distributions of stars. Aims: Here, we aim to analyse internal stellar kinematics of open clusters, and identify rotation, expansion, or contraction patterns. Methods: We use Gaia Early Data Release 3 (EDR3) astrometry and integrated nested Laplace approximations to perform vector-field inference and create spatio-kinematic maps of 1237 open clusters. The sample is composed of clusters for which individual stellar memberships were already known, thus minimising contamination from field stars in the velocity maps. Projection effects were corrected using EDR3 data complemented with radial velocities from Gaia Data Release 2 and other surveys. Results: We report the detection of rotation patterns in eight open clusters. Nine additional clusters display possible rotation signs. We also observe 14 expanding clusters, with 15 other objects showing possible expansion patterns. Contraction is evident in two clusters, with one additional cluster presenting a more uncertain detection. In total, 53 clusters are found to display kinematic structures. Within these, elongated spatial distributions suggesting tidal tails are found in five clusters. These results indicate that the approach developed here can recover kinematic patterns from noisy vector fields, as those from astrometric measurements of open clusters or other stellar or galactic populations, thus offering a powerful probe for exploring the internal kinematics and dynamics of these types of objects.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tradeoffs between uniform land protection and biodiversity-specific land protection with <2 °C global warming

Nearly 200 countries have pledged to conserve 30% of terrestrial ecosystems to stop the global biodiversity crisis. However, biodiversity is not uniformly distributed across countries. Adequately addressing this crisis requires a scientific basis for selecting protected land that considers both ecological benefits and impacts to humans. We use the global change analysis model to evaluate land use tradeoffs of four land protection cases under two climate cases. We find that biodiversity-specific land protection up to 39% globally can reduce land use constraints and food prices compared to protecting 30% of land uniformly in each country (’30 × 30’ initiative). Valuing terrestrial carbon for climate change mitigation reduces land conversion pressure and can complement protection strategies. Global impacts to agriculture of additional land protection are small, but regional impacts vary and may be considerable. Overall, biodiversity-specific land protection has greater potential than a uniform target to meet both ecological and human needs.

biodiversity↗
DOE OSTI2020

Dynamic in-situ imaging of methane hydrate formation and self-preservation in porous media

Here we present the results of dynamic in-situ 3D X-ray imaging of methane hydrates microstructure during methane hydrate formation and dissociation in sand samples. Short scanning times and high resolution provided by synchrotron X-rays allowed for better understanding of water movement and different types of gas-hydrate formation. Complementing previous observations, we conclude that the process of gas-hydrate formation is accompanied by the water movements caused by cryogenic water suction that happens in sequences of short fast movements with longer equilibrium states in between (when the water is immobile). Based on the 3D microstructure we identified two distinct types of gas-hydrate formation: (i) into the gas pockets and (ii) inside water volumes. For both mechanisms we do not see problems in gas or water supply to support the gas-hydrate formation. The rate of dissociation in the self-preservation mode (pressure drop at negative temperatures) appears to be different for these two types of gas hydrates. This means that the history of the gas-hydrate formation may influence its behaviour at the dissociation stage (e.g. gas-hydrate production).

58 GEOSCIENCES↗
DOE OSTI2022

Charting C–C coupling pathways in electrochemical CO 2 reduction on Cu(111) using embedded correlated wavefunction theory

The electrochemical CO 2 reduction reaction (CO 2 RR) powered by excess zero-carbon-emission electricity to produce especially multicarbon (C 2+ ) products could contribute to a carbon-neutral to carbon-negative economy. Foundational to the rational design of efficient, selective CO 2 RR electrocatalysts is mechanistic analysis of the best metal catalyst thus far identified, namely, copper (Cu), via quantum mechanical computations to complement experiments. Here, we apply embedded correlated wavefunction (ECW) theory, which regionally corrects the electron exchange-correlation error in density functional theory (DFT) approximations, to examine multiple C–C coupling steps involving adsorbed CO (*CO) and its hydrogenated derivatives on the most ubiquitous facet, Cu(111). We predict that two adsorbed hydrogenated CO species, either *COH or *CHO, are necessary precursors for C–C bond formation. The three kinetically feasible pathways involving these species yield all three possible products: *COH–CHO, *COH–*COH, and *OCH–*OCH. The most kinetically favorable path forms *COH–CHO. In contrast, standard DFT approximations arrive at qualitatively different conclusions, namely, that only *CO and *COH will prevail on the surface and their C–C coupling paths produce only *COH–*COH and *CO–*CO, with a preference for the first product. This work demonstrates the importance of applying qualitatively and quantitatively accurate quantum mechanical method to simulate electrochemistry in order ultimately to shed light on ways to enhance selectivity toward C 2+ product formation via CO 2 RR electrocatalysts.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

Combinatorial sputter deposition of ultrathick Au-Bi alloy films

We report gold-bismuth alloys are of interest as catalysts and catalytic sensing systems, electrochemical sensors, superconductors, and hohlraums for magnetically assisted inertial confinement fusion implosions. Radiation-hydrodynamics simulations with the Lasnex code of laser-driven hohlraums predict higher x-ray drive from Au-Bi alloys compared with cases of Au-Ta or pure Au and Bi hohlraums. Here, we use direct current magnetron sputtering in Ar gas, with co-sputtering from two elemental targets, to deposit Au-Bi alloys with Bi content of 9–77 at.% and thicknesses up to ~20 µm. Films are characterized by a combination of x-ray diffraction, Rutherford backscattering, scanning electron microscopy, substrate-curvature-based residual stress, and electronic transport measurements. Experiments are complemented by Monte Carlo simulations of ballistic sputtering and gas phase transport of depositing species and Ar gas atoms. Results show that all films are polycrystalline, with three distinct compositional regimes dominated by Au, Au 2 Bi, and Bi crystallographic phases. A metallic behavior of the temperature dependence of electrical resistivity is observed for all the films. Films with Bi content above ~30 at.% exhibit porosity, which is tolerable to hohlraum x-ray drive based on Lasnex simulations.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Room-temperature in-plane ferromagnetism in Co-substituted Fe 5 GeTe 2 investigated by magnetic x-ray spectroscopy and microscopy

The exploration of two-dimensional (2D) van der Waals ferromagnets has revealed intriguing magnetic properties with significant potential for spintronics applications. In this study, we examine the magnetic properties of Co-doped Fe 5 GeTe 2 using x-ray photoemission electron microscopy (XPEEM) and x-ray magnetic circular dichroism (XMCD), complemented by density functional theory calculations. Our XPEEM measurements reveal that the Curie temperature (T c ) of a bilayer of (Co x Fe 1-x ) 5-δ GeTe 2 (with x = 0.28) reaches ∼300 K—a notable enhancement over most 2D ferromagnets in the ultrathin limit. Interestingly, the T c shows only a small dependence on film thickness (bulk T c ≈ 340 K), in line with the observed in-plane (IP) magnetic anisotropy and robust IP exchange coupling. XMCD measurements indicate that the spin moments for both Fe and Co are significantly reduced compared to the theoretical values. These insights highlight the potential of Co-doped Fe 5 GeTe 2 for stable, high-temperature ferromagnetic applications in 2D materials.

(Co0.28Fe0.72)5GeTe2↗
DOE OSTI2020

Valley magnetism, nematicity, and density wave orders in twisted bilayer graphene

We analyze density wave and Pomeranchuk orders in twisted bilayer graphene. This complements our earlier analysis of the pairing instabilities. We assume that near half filling of either conduction or valence band, the Fermi level is close to Van Hove points, where the density of states diverges, and study potential instabilities in the particle-hole channel within a patch model with two valley degrees of freedom. The hexagonal symmetry of twisted bilayer graphene allows for either six or twelve Van Hove points. We consider both cases and find the same two leading candidates for particle-hole order. One is an SU(2)-breaking spin state with ferromagnetism within a valley. A subleading intervalley hopping induces antiferromagnetism between the valleys. The same state has also been obtained in strong-coupling approaches, indicating that this order is robust. Here, the other is a mixed state with 120° complex spin order and orthogonal complex charge order. In addition, we find a weaker but still attractive interaction in nematic channels, and discuss the type of a nematic order.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Data-assimilated time-lapse visco-acoustic full-waveform inversion: Theory and application for injected CO 2 plume monitoring

Continuous seismic monitoring for quantifying CO 2 plume migration and detection of any potential leakages in the subsurface is essential for the security of long-term anthropogenic carbon dioxide geologic storage. Traditional time-lapse full-waveform inversion (TLFWI) methods aim to map the CO 2 distribution by estimating seismic velocity changes, but recent studies find that CO 2 -induced attenuation is an important complement to seismic velocity for tracking the CO 2 plumes and even quantifying the CO 2 saturation. We have developed a novel data-assimilated TLFWI method to construct high-resolution time-lapse velocity and attenuation changes from dense time-lapse monitoring data. This method consists of two theoretical developments: visco-acoustic full-waveform inversion (QFWI) and multiparameter hierarchical matrix-powered extended Kalman filter (mHiEKF). The method is capable of (1) posing temporal constraints to retrieve time-lapse information from dense monitoring data by using mHiEKF, (2) accurately recovering high-spatial-resolution velocity and attenuation perturbations using first-order equation system-based QFWI, and (3) providing the model uncertainty by estimating their model standard deviation. With numerical examples, we first find the effectiveness of the new QFWI on estimating accurate velocity and attenuation models simultaneously. Then, a CO 2 leakage case and a realistic Frio-II CO 2 monitoring case are presented to find the advantages and applicability of our data-assimilated QFWI method for estimating time-lapse changes using dense time-lapse monitoring surveys. Here, by assimilating time-lapse seismic monitoring data over time, our data-assimilated QFWI method can improve the resolution of velocity and attenuation changes and decrease their model uncertainties.

58 GEOSCIENCES↗