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At least 919 records · Page 51

Clay, Water, and Salt: Controls on the Permeability of Fine-Grained Sedimentary Rocks

We report that the ability to predict the permeability of fine-grained soils, sediments, and sedimentary rocks is a fundamental challenge in the geosciences with potentially transformative implications in subsurface hydrology. In particular, fine-grained sedimentary rocks (shale, mudstone) constitute about two-thirds of the sedimentary rock mass and play important roles in three energy technologies: petroleum geology, geologic carbon sequestration, and radioactive waste management. The problem is a challenging one that requires understanding the properties of complex natural porous media on several length scales. One inherent length scale, referred to hereafter as the mesoscale, is associated with the assemblages of large grains of quartz, feldspar, and carbonates over distances of tens of micrometers. Its importance is highlighted by the existence of a threshold in the core scale mechanical properties and regional scale energy uses of shale formations at a clay content X clay ≈ 1/3, as predicted by an ideal packing model where a fine-grained clay matrix fills the gaps between the larger grains. A second important length scale, referred to hereafter as the nanoscale, is associated with the aggregation and swelling of clay particles (in particular, smectite clay minerals) over distances of tens of nanometers. Mesoscale phenomena that influence permeability are primarily mechanical and include, for example, the ability of contacts between large grains to prevent the compaction of the clay matrix. Nanoscale phenomena that influence permeability tend to be chemomechanical in nature, because they involve strong impacts of aqueous chemistry on clay swelling. The second length scale remains much less well characterized than the first, because of the inherent challenges associated with the study of strongly coupled nanoscale phenomena. Advanced models of the nanoscale properties of fine-grained media rely predominantly on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, a mean field theory of colloidal interactions that accurately predicts clay swelling in a narrow range of conditions (low salinity, low compaction, Na + counterion). An important feature of clay swelling that is not predicted by these models is the coexistence, in most conditions of aqueous chemistry and dry bulk density, of two types of pores between parallel smectite particles: mesopores with a pore width of >3 nm that are controlled by long-range interactions (the osmotic swelling regime) and nanopores with a pore width <1 nm that are controlled by short-range interactions (the crystalline swelling regime). Finally, nanogeochemical characterization and simulation techniques, including coarse-grained and all-atom molecular dynamics simulations, hold significant promise for the development of advanced constitutive relations that predict this coexistence and its dependence on aqueous chemistry.

58 GEOSCIENCES↗

Algorithmic Patterns for $$\mathcal {H}$$-Matrices on Many-Core Processors

In this work, we consider the reformulation of hierarchical ( \(\mathcal {H}\) ) matrix algorithms for many-core processors with a model implementation on graphics processing units (GPUs). \(\mathcal {H}\) matrices approximate specific dense matrices, e.g., from discretized integral equations or kernel ridge regression, leading to log-linear time complexity in dense matrix–vector products. The parallelization of \(\mathcal {H}\) matrix operations on many-core processors is difficult due to the complex nature of the underlying algorithms. While previous algorithmic advances for many-core hardware focused on accelerating existing \(\mathcal {H}\) matrix CPU implementations by many-core processors, we here aim at totally relying on that processor type. As main contribution, we introduce the necessary parallel algorithmic patterns allowing to map the full \(\mathcal {H}\) matrix construction and the fast matrix–vector product to many-core hardware. In this work, crucial ingredients are space filling curves, parallel tree traversal and batching of linear algebra operations. The resulting model GPU implementation hmglib is the, to the best of the authors knowledge, first entirely GPU-based Open Source \(\mathcal {H}\) matrix library of this kind. We investigate application examples as present in kernel ridge regression, Gaussian Process Regression and kernel-based interpolation. In this context, an in-depth performance analysis and a comparative performance study against a standard multi-core CPU \(\mathcal {H}\) matrix library highlights profound speedups of our many-core parallel approach.

97 MATHEMATICS AND COMPUTING↗

Time–series Analysis of Volume Change at Brady Hot Springs, Nevada, USA using Geodetic Data from 2003 – 2018

Brady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time–series analysis of each of the 1656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time–series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. Here, the rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix.

58 GEOSCIENCES↗

Nonequilibrium optical response of a one-dimensional Mott insulator

We define, compute, and analyze the nonequilibrium differential optical conductivity of the one-dimensional extended Hubbard model at half-filling after applying a pump pulse, using the time-dependent density matrix renormalization group method. The melting of the Mott insulator is accompanied by a suppression of the local magnetic moment and ensuing photogeneration of doublon-holon pairs. The differential optical conductivity reveals (i) mid-gap states related to parity-forbidden optical states and (ii) strong renormalization and hybridization of the excitonic resonance and the absorption band, yielding a Fano resonance. We offer evidence and interpret such a resonance as a signature of nonequilibrium optical excitations resembling excitonic strings, (bi)excitons, and unbound doublon-holon pairs, depending on the magnitude of the intersite Coulomb repulsion. We discuss our results in the context of pump and probe spectroscopy experiments on organic Mott insulators.

1-dimensional systems↗

Pair density wave in the doped three-band Hubbard model on two-leg square cylinders

A pair density wave (PDW) is a superconducting (SC) state with a spatially modulated order parameter. Although much is known about the properties of the PDW state, its realization in microscopic models with divergent susceptibility has been challenging. Here, in this work, we report a density-matrix renormalization group study of a three-band Hubbard model (also known as the Emery model) for cuprates on long two-leg square cylinders. Upon light doping, we find that the ground state of the system is consistent with that of a PDW state with mutually commensurate and power-law SC, charge (CDW), and spin (SDW) density wave correlations. The SC correlations are dominant between neighboring Cu sites with d-wave pairing symmetry. Interestingly, we find that the near-neighbor interactions, especially the near-neighbor attractive V pd interaction between neighboring Cu and oxygen sites, can notably enhance the SC correlations while simultaneously suppressing the CDW correlations. For a modestly strong attractive V pd , the SC correlations become quasi-long-ranged with a divergent PDW susceptibility.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Distinct critical behaviors from the same state in quantum spin and population dynamics perspectives

There is a deep connection between the ground states of transverse-field spin systems and the late-time distributions of evolving viral populations—within simple models, both are obtained from the principal eigenvector of the same matrix. However, that vector is the wave-function amplitude in the quantum spin model, whereas it is the probability itself in the population model. We show that this seemingly minor difference has significant consequences: Phase transitions that are discontinuous in the spin system become continuous when viewed through the population perspective, and transitions that are continuous become governed by new critical exponents. We introduce a more general class of models that encompasses both cases and that can be solved exactly in a mean-field limit. Numerical results are also presented for a number of one-dimensional chains with power-law interactions. We see that well-worn spin models of quantum statistical mechanics can contain unexpected new physics and insights when treated as population-dynamical models and beyond, motivating further studies.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A ROBUST MECHANISTIC APPROACH TO PREDICTION OF DEPARTURE FROM NUCLEATE BOILING

departure from nucleate boiling (DNB) sets a regulatory limit for licensing pressurized water reactors (PWRs). Under such conditions, the heated surface is permanently blanketed by a vapor film, leading to a sharp deterioration of the heat transfer coefficient at the heater/coolant interface and an abrupt temperature rise. Unfortunately, the path for an accurate, robust prediction of DNB has been elusive due to lack of consensus on its triggering mechanism. This work reviews existing physics-driven modeling tools in the first place. An evolutionary channel-scale mechanistic model that leverages key assumptions in the relatively well-accepted mechanisms of liquid sublayer dryout and near-wall bubble crowding is then proposed. Detailed validation of the proposed model has demonstrated its improved predictive capabilities over previous data/physics-driven models with regard to an extensive DNB-specific CHF test matrix covering a wide range of flow conditions. The unique feature of the proposed model lies in its ability to predict DNB for different heater geometries (including round tube, annulus, and rod bundle), which is essential in deciphering fuel performance metrics from different facilities and reactor types. The proposed model will be further implemented in fuel performance codes to help improve modeling of transient DNB scenarios such as during a reactivity-initiated accident (RIA).

Zhao, Xingang↗

Machine Learning Moment Closure Models for the Radiative Transfer Equation III: Enforcing Hyperbolicity and Physical Characteristic Speeds

This is the third paper in a series in which we develop machine learning (ML) moment closure models for the radiative transfer equation. In our previous work (Huang et al. in J Comput Phys 453:110941, 2022), we proposed an approach to learn the gradient of the unclosed high order moment, which performs much better than learning the moment itself and the conventional $P_N$ closure. However, while the ML moment closure has better accuracy, it is not able to guarantee hyperbolicity and has issues with long time stability. In our second paper (Huang et al., in: Machine learning moment closure models for the radiative transfer equation II: enforcing global hyperbolicity in gradient based closures, 2021. arXiv:2105.14410), we identified a symmetrizer which leads to conditions that enforce that the gradient based ML closure is symmetrizable hyperbolic and stable over long time. The limitation of this approach is that in practice the highest moment can only be related to four, or fewer, lower moments. In this paper, we propose a new method to enforce the hyperbolicity of the ML closure model. Motivated by the observation that the coefficient matrix of the closure system is a lower Hessenberg matrix, we relate its eigenvalues to the roots of an associated polynomial. Here, we design two new neural network architectures based on this relation. The ML closure model resulting from the first neural network is weakly hyperbolic and guarantees the physical characteristic speeds, i.e., the eigenvalues are bounded by the speed of light. The second model is strictly hyperbolic and does not guarantee the boundedness of the eigenvalues. Several benchmark tests including the Gaussian source problem and the two-material problem show the good accuracy, stability and generalizability of our hyperbolic ML closure model.

97 MATHEMATICS AND COMPUTING↗

Identification and Quantification of Carbon Phases in Conversion Fuel for the Transient Reactor Test Facility

As part of an overall effort to convert US research reactors to low-enriched uranium (LEU) fuel use, a LEU conversion fuel is being designed for the Transient Reactor Test Facility (TREAT) at the Idaho National Laboratory. TREAT fuel compacts are comprised of UO2 fuel particles in a graphitic matrix material. In order to refine heat transfer modeling, as well as determine other physical and nuclear characteristics of the fuel, the amount and type of graphite and non-graphite phases within the fuel matrix must be known. In this study, we performed a series of complementary analyses, designed to allow detailed characterization of the graphite and phenolic resin based fuel matrix. Methods included Scanning Electron and Transmission Electron Microscopies, Raman spectroscopy, X-ray Diffraction, and Dual-Beam Focused Ion Beam Tomography. Our results indicate that no single characterization technique will yield all of the desired information; however, through the use of statistical and empirical data analysis, such as curve fitting, partial least squares regression, volume extrapolation and spectra peak ratios, a degree of certainty for the quantity of each phase can be obtained.

10 SYNTHETIC FUELS↗

Identification and Quantification of Carbon Phases in Conversion Fuel for the Transient Reactor Test Facility

As part of an overall effort to convert US research reactors to low-enriched uranium (LEU) fuel, a LEU conversion fuel is being designed for the Transient Reactor Test Facility (TREAT) at the Idaho National Laboratory. TREAT fuel compacts are comprised of UO{sub 2} fuel particles in a graphitic matrix material. In order to refine heat transfer modeling, as well as determine other physical and nuclear characteristics of the fuel, the amount and type of graphite and non-graphite phases within the fuel matrix must be known. In this study, we performed a series of complementary analyses, designed to allow detailed characterization of the graphite and phenolic resin based fuel matrix. Methods included Scanning Electron Microscopy, Raman spectroscopy, and X-ray Diffraction. Our results indicate that no single characterization technique will yield all of the desired information; however, through the use of statistical and empirical data analysis, such as curve fitting, partial least squares regression, volume extrapolation and spectra peak ratios, a degree of certainty for the quantity of each phase can potentially be obtained. Although no one type of analysis has provided a complete determination of the quantities and identities of all carbon phases present in the fuel matrix, additional information has been gathered and is being used to refine future analysis methods. From the three types of quantification performed, results have been within 1% (92.8%, 93.02% and 93.6% for BSE image analysis, XRD and Raman spectroscopy, respectively). More work remains to identify any trace crystalline carbonaceous phases that may be present, quantify any traces that are identified, and develop and use further complementary bulk phase quantification techniques. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Universality for 1d Random Band Matrices: Sigma-Model Approximation

The paper continues the development of the rigorous supersymmetric transfer matrix approach to the random band matrices started in (J Stat Phys 164:1233–1260, 2016; Commun Math Phys 351:1009–1044, 2017). We consider random Hermitian block band matrices consisting of W×W random Gaussian blocks (parametrized by j,k∈Λ=[1,n]{sup d}∩ℤ{sup d}) with a fixed entry’s variance J{sub jk}=δ{sub j,k}W{sup −1}+βΔ{sub j,k}W{sup −2}, β>0 in each block. Taking the limit W→∞ with fixed n and β, we derive the sigma-model approximation of the second correlation function similar to Efetov’s one. Then, considering the limit β,n→∞, we prove that in the dimension d=1 the behaviour of the sigma-model approximation in the bulk of the spectrum, as β≫n, is determined by the classical Wigner–Dyson statistics.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Investigation of the discontinuous precipitation of U-Nb alloys via thermodynamic analysis and phase-field modeling

U-Nb’s discontinuous precipitation, $\gamma^{bcc}_{matrix}$, $\alpha^{orth}_{cellular}$, $\gamma\prime^{bcc}_{cellular}$, is intriguing in the sense that it allows formation and growth of the metastable $\gamma\prime$ phase during the course of its occurrence. Previous attempts to explain the thermodynamic origin of U-Nb’s discontinuous precipitation hypothesized that the energy of $\alpha$ forms an intermediate common tangent with the first potential of the double-well energy of $\gamma$ at the $\gamma\prime$ composition. In this work, we examine different possible mechanisms by which the discontinuous precipitation product in the U-Nb system can be stabilized. We put forward a mechanism by which the bulk free energy of the $\gamma$ can develop a non-monotonic dependency with composition. Additionally we posit that local contributions due to lattice mismatch between the $\alpha$ and $\gamma$ phases may be responsible for the generation of metastable states that may stabilized by thermodynamics as well as by kinetics. Our work suggests that local misfit strain tends to play a crucial role in the growth of the discontinuous precipitation product. Depending on the magnitude of strain developed at the $\alpha$/$\gamma\prime$ interfaces, either an increasing $\gamma\prime$ composition or a random distribution of $\gamma\prime$ compositions around the equiatomic value with respect to increasing temperature could be expected. Moreover, we show how it is possible to stabilize the discontinuous precipitation front through highly anisotropic and fast interface diffusion.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Water Remediation: PVA-Based Magnetic Gels as Efficient Devices to Heavy Metal Removal

Scientific and technological researches are devoted to obtain materials capable of retaining different kinds of pollutants, contributing to contamination solutions. In this context, hydrogels have emerged as great candidates because of their excellent absorption properties as well as good mechanical, thermal and chemical properties. More specifically, ferrogels (magnetic gels) present the extra advantage of being easily manipulated by a permanent magnet. Here, we present the results derived from the application of ferrogels as efficient tools to extract heavy metal pollutants from wastewater samples. The gels were prepared following the method of freezing and thawing of a polyvinyl alcohol aqueous solution with magnetic nanoparticles coated with polyacrylic acid. Ferrogels were fully characterized and their ability to retain Cu{sup 2+} and Cd{sup 2+}, as model heavy metals, was studied. Thus kinetics and mechanisms of adsorption were evaluated and modeled. The concentration of MNPs on the PVA matrix was key to improve the adsorption capability (approximately the double of retention is improved by the MNPs addition). The adsorption kinetics was determined as pseudo-second order model, whereas the Langmuir model was the most appropriate to explain the behavior of the gels. Finally reuse ability was evaluated to determine the real potential of these materials, the ferrogels demonstrated high efficiency up to about five cycles, retaining about 80–90% of their initial adsorption capability. All the results indicated that the materials are promising candidates able to compete with the commercial technology regarding to water remediation.

36 MATERIALS SCIENCE↗

Axial Tensile Failure Analysis of SiC{sub f}/Ti Composite Based on Continuum Cohesive Zone Model

In this paper, the failure behavior of SiC fiber-reinforced Ti-6Al-4V matrix composite (SiC{sub f}/Ti) under longitudinal loads was studied experimentally and theoretically. Experimental results show that the interface of SiC{sub f}/Ti composite is continuous and integral. Through SEM observations, it was found that transverse matrix cracks initiated from the debonding region of the interface. A three-dimensional representative volume element was developed to simulate the failure process of SiC{sub f}/Ti-6Al-4V composite. A continuum cohesive zone model is employed to describe the debonding behavior at the interface, compared with a discrete one. More accurate simulated results were obtained by a continuum cohesive zone model, corresponding to experimental results. The transverse cracking behavior of the matrix was simulated. The stress–strain curves predicted by the continuum cohesive zone model show a good agreement with the experimental results. The fiber volume fraction, interface strength and interface toughness are investigated to exhibit their influences upon the longitudinal mechanical characteristics of SiC{sub f}/Ti-6Al-4V composite.

36 MATERIALS SCIENCE↗

Transport Upscaling under Flow Heterogeneity and Matrix-Diffusion in Three-Dimensional Discrete Fracture Networks

For this work, we investigate the combined effects of network scale flow variability and retention due to matrix-diffusion on the scaling behavior of transport through fractured media. Two of the principal mechanisms controlling the transport of solutes through fractured low-permeability media are broad distributions of flow velocities and retention times in the solid matrix. We study the relative impact of these two processes under different initial conditions using a set of three-dimensional discrete fracture network simulations. We use these simulations to develop and calibrate an upscaled continuous time random walk (CTRW) approach for advective transport based on an Ornstein-Uhlenbeck model for the particle velocities that accounts for the fracture-matrix coupling using a compound Poisson process. This CTRW model can be conditioned on the initial solute distribution and allows to observe late-time scaling behavior at distances beyond what is feasible to observe using high-fidelity direct numerical simulations. We determine that the initial distribution of particles leads to marked differences in the persistent long-term scale behavior in the solute travel time distributions, even those undergoing retention due to matrix diffusion through implementation and analysis of the model.

54 ENVIRONMENTAL SCIENCES↗

A micro-scale cutting model for UD CFRP composites with thermo-mechanical coupling

Cutting a unidirectional carbon fiber-reinforced polymer (UD CFRP) structure is the basic unit for CFRP machining, which is a complex thermal-mechanically coupled process. To reveal the deformation mechanism and predict cutting force in UD CFRP micro cutting, a micro-scale fracture model for UD CFRP cutting with thermal-mechanical coupling is demonstrated in this paper, which captures the failure modes for fibers, matrix and the interface based on a micro-level RVE using a relatively simple damage based fracture method. The thermal-mechanical coupling model at the micro scale is developed on the basis of the plastic energy dissipation and frictional heating during cutting. Failure models for the fiber, matrix and interface region are applied depending on the material properties of each of these three phases. Numerical simulations based on the above model with different fiber orientations were performed to predict the deformation and forces of different components in UD CFRP. Cutting experiments with the same fiber orientations as considered in the simulations were carried out to validate the force and deformation results. The predicted force and deformation patterns match well with evidence from our experiments. In general, the cutting force is larger than the thrust force regardless of fiber orientation. The cutting force reaches a maximum as the fiber orientation approaches 90 , but thrust forces do not vary substantially across cases. When the fiber orientation is acute, the deformation of fibers is much smaller than when the cutting angle is obtuse. Surface roughness follows the same trend with cutting angle as fiber deformation.

42 ENGINEERING↗

A deep learning-based Bayesian framework for high-resolution calibration of building energy models

Calibrating building energy models (BEMs), i.e., closing discrepancy between modeling and field measurements, is of significance to support its applications in building sustainability and resilience analysis. However, as being widely used in practice, current Bayesian calibration is mostly performed in low-resolution (annual or monthly), instead of high-resolution (hourly or sub-hourly), which is crucial to support emerging BEM applications, such as building-renewable energy integration (demand response) and smart control. This is attributable to the gaps in current Bayesian calibration process, including (1) difficulty in supporting reliable high-resolution calibration with over-parameterization and multi-solution issues, (2) inadequacy of meta-model to capture temporal building dynamics in high-resolution, and (3) excessive computational burdens of covariance matrix calculation in Bayesian inference. Therefore, to close these gaps, this research proposes a novel deep learning-based Bayesian calibration framework, involving pre-calibration mechanism, Long Short-Term Memory as surrogate models, and simplified covariance matrix calculation, to calibrate BEMs in high temporal resolution (i.e., hourly) with enhanced accuracy and computational efficiency. Finally, the case study demonstrates its effectiveness to match modeling outcomes with measurements and realize CV-RMSE of < 30 % and NMBE of < 6 % in hourly resolution, as well as a significant reduction of calibration time (by > 99 %, from > 600 h to ~ 1.5 h).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

An Alternative Conceptual Model for the Spent Nuclear Fuel–Water Interaction in Deep Geologic Disposal Conditions

For the long-term safety assessment of direct disposal of spent nuclear fuel in deep geologic repositories, knowledge on the radionuclide release rate from the UO 2 matrix is essential. This work provides a conceptual model to explain the results of leaching experiments involving used nuclear fuel or simulant materials in confirmed reducing conditions. Key elements of this model are: direct effect of radiation from radiolytic species (including defects and excited states) in the solid and in the first water layers in contact with its surface; and excess H 2 may be produced due to processes occurring at the surface of the spent fuel and in confined water volumes, which may also play a role in keeping the spent fuel surface in a reduced state. The implication is that the fractional radionuclide release rate used in most long-term safety assessments (10 -7 year -1 ) is over estimated because it assumes that there is net UO 2 oxidation caused by radiolysis, in contrast with the alternative conceptual model presented here. Furthermore, conventional water radiolysis models and radiation chemical yields published in the literature are not directly applicable to a heterogeneous system such as the spent fuel–water interface. Suggestions are provided for future work to develop more reliable models for the long-term safety assessment of spent nuclear fuel disposal.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗