3D Domain Research Articles

Influence of ferromagnetic interlayer exchange coupling on current-induced magnetization switching and Dzyaloshinskii-Moriya interaction in Co/Pt/Co multilayer system.

This paper investigates the relationship among interlayer exchange coupling (IEC), Dzyaloshinskii-Moriya interaction (DMI), and multilevel magnetization switching within a Co/Pt/Co heterostructure, where varying Pt thicknesses enable control over the coupling strength. Employing Brillouin Light Scattering to quantify the effective DMI, we explore its potential role in magnetization dynamics and multilevel magnetization switching. Experimental findings show four distinct resistance states under an external magnetic field and spin Hall effect related spin current. We explain this phenomenon based on the asymmetry between Pt/Co and Co/Pt interfaces and the interlayer coupling, which, in turn, influences the DMI and subsequently impacts the magnetization dynamics. Numerical simulations, including macrospin, 1D domain wall, and simple spin wave models, further support the experimental observations of multilevel switching and help uncover the underlying mechanisms. Our proposed explanation, supported by magnetic domain observation using polar-magnetooptical Kerr microscopy, offers insights into both the spatial distribution of magnetization and its dynamics for different IECs, thereby shedding light on its interplay with DMI, which may lead to potential applications in storage devices.

Imputation of 3D genome structure by genetic–epigenetic interaction modeling in mice

Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions have previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here, we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic–epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic–epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF-binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of 3D chromatin structure.

Imputation of 3D genome structure by genetic-epigenetic interaction modeling in mice.

Gene expression is known to be affected by interactions between local genetic variation and DNA accessibility, with the latter organized into three-dimensional chromatin structures. Analyses of these interactions have previously been limited, obscuring their regulatory context, and the extent to which they occur throughout the genome. Here, we undertake a genome-scale analysis of these interactions in a genetically diverse population to systematically identify global genetic-epigenetic interaction, and reveal constraints imposed by chromatin structure. We establish the extent and structure of genotype-by-epigenotype interaction using embryonic stem cells derived from Diversity Outbred mice. This mouse population segregates millions of variants from eight inbred founders, enabling precision genetic mapping with extensive genotypic and phenotypic diversity. With 176 samples profiled for genotype, gene expression, and open chromatin, we used regression modeling to infer genetic-epigenetic interactions on a genome-wide scale. Our results demonstrate that statistical interactions between genetic variants and chromatin accessibility are common throughout the genome. We found that these interactions occur within the local area of the affected gene, and that this locality corresponds to topologically associated domains (TADs). The likelihood of interaction was most strongly defined by the three-dimensional (3D) domain structure rather than linear DNA sequence. We show that stable 3D genome structure is an effective tool to guide searches for regulatory elements and, conversely, that regulatory elements in genetically diverse populations provide a means to infer 3D genome structure. We confirmed this finding with CTCF ChIP-seq that revealed strain-specific binding in the inbred founder mice. In stem cells, open chromatin participating in the most significant regression models demonstrated an enrichment for developmental genes and the TAD-forming CTCF-binding complex, providing an opportunity for statistical inference of shifting TAD boundaries operating during early development. These findings provide evidence that genetic and epigenetic factors operate within the context of 3D chromatin structure.

Application of 1D model for overland flow simulations on 2D complex domains

High computational demand limits the applications of two-dimensional (2D) shallow water equation models for high resolution overland flow simulations, while one-dimensional (1D) models can achieve higher computing efficiency. This study applied a 1D hydrodynamic model to surrogate 2D models for overland flow simulations on complex 2D domains. With one dimension reduced, the surrogate model simulation would have acceptable accuracy with much higher computing efficiency. The surrogating is fulfilled through mimicking 2D models in mesh generations, so that the 1D channel network is generated in such a way that it geometrically covers the whole domain without overlapping and intersection, and hydrologically follows the steepest slopes. Several benchmark cases on 2D domains in both laboratory and field scales with complex geometry, where no 1D models have been ever applied, are used to compare the 1D and 2D model simulations. The comparisons demonstrate that the 1D model does have potentials to efficiently simulate overland flow on 2D complex domains with accuracy comparable to 2D models.

3D Full-Waveform Tomography of Standard Penetration Test-Seismic Wavefields in Karst Florida Limestone

The shallow subsurface across large parts of Florida consists of weathered karst limestone, a spatially variable porous stratigraphy with significant influence in the design and load capacity of deep foundations. For reliable load transfer of the super structure into the bearing soil/rock, detection of voids and weak zones is crucial. This study investigated the capabilities of a recently developed standard penetration test (SPT)-seismic testing method for characterizing a large volume of soil/rock properties with a single SPT. The method utilizes a three-dimensional full-waveform inversion (3D FWI) of wavefields induced by SPT blows at depths (in-depth source) to characterize the subsurface around the SPT borehole. A site in Florida that presents shallow, surface karst limestone, was the location of a field experiment that consisted of two 36- × 18-m areas, each with an SPT at the area center. Seismic wavefields induced by SPT blows at depth were recorded by 72 vertical geophones on the ground surface and analyzed by the 3D FWI. The results revealed that subsurface soil/rock properties were characterized in submeter pixels over a large 3D domain of 24 × 36 × 18 m (depth × length × width). Multiple voids at various depths from 5 to 17 m were successfully detected at the site and confirmed by SPT data. The results suggested that the SPT-seismic method is an efficient tool for site investigation, as a bridge pier or pile group could be designed with only one SPT.

Development of stochastically reconstructed 3D porous media micromodels using additive manufacturing: numerical and experimental validation

We propose an integrated methodology for the design and fabrication of 3D micromodels that are suitable for the pore-scale study of transport processes in macroporous materials. The micromodels, that bear the pore-scale characteristics of sandstone, such as porosity, mean pore size, etc, are designed following a stochastic reconstruction algorithm that allows for fine-tuning the porosity and the correlation length of the spatial distribution of the solid material. We then construct a series of 3D micromodels at very fine resolution (i.e. 16μ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$16\\,\\upmu $$\\end{document}m) using a state-of-the-art 3D printing infrastructure, specifically a ProJet MJP3600 3D printer, that utilizes the Material Jetting technology. Within the technical constraints of the 3D printer resolution, the fabricated micromodels represent scaled-up replicas of natural sandstones, that are suitable for the study of the scaling between the permeability, the porosity and the mean pore size. The REV- and pore-scale characteristics of the resulting physical micromodels are recovered using a combination of X-ray micro-CT and microfluidic studies. The experimental results are then compared with single-phase flow simulations at pore-scale and geostatistic models in order to determine the effects of the design parameters on the intrinsic permeability and the spatial correlation of the velocity profile. Our numerical and experimental measurements reveal an excellent match between the properties of the designed and fabricated 3D domains, thus demonstrating the robustness of the proposed methodology for the construction of 3D micromodels with fine-tuned and well-controlled pore-scale characteristics. Furthermore, a pore-scale numerical study over a wider range of 3D digital domain realizations reveals a very good match of the measured permeabilities with the predictions of the Kozeny–Carman formulation based on a single control parameter, k0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_0$$\\end{document}, that is found to have a practically constant value for porosities ϕ≥0.2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\phi \\ge 0.2$$\\end{document}. This, in turn, enables us to customize the sample size to meet REV constraints, including enlarging pore morphology while considering the Reynolds number. It is also found that at lower porosities there is a significant increase in the fraction of the non-percolating pores, thus leading to different k0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$k_0$$\\end{document}, as the porosity approaches a numerically determined critical porosity value, ϕc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\phi _c$$\\end{document}, where the domain is no longer percolating.

HaLo‐NeRF: Learning Geometry‐Guided Semantics for Exploring Unconstrained Photo Collections

AbstractInternet image collections containing photos captured by crowds of photographers show promise for enabling digital exploration of large‐scale tourist landmarks. However, prior works focus primarily on geometric reconstruction and visualization, neglecting the key role of language in providing a semantic interface for navigation and fine‐grained understanding. In more constrained 3D domains, recent methods have leveraged modern vision‐and‐language models as a strong prior of 2D visual semantics. While these models display an excellent understanding of broad visual semantics, they struggle with unconstrained photo collections depicting such tourist landmarks, as they lack expert knowledge of the architectural domain and fail to exploit the geometric consistency of images capturing multiple views of such scenes. In this work, we present a localization system that connects neural representations of scenes depicting large‐scale landmarks with text describing a semantic region within the scene, by harnessing the power of SOTA vision‐and‐language models with adaptations for understanding landmark scene semantics. To bolster such models with fine‐grained knowledge, we leverage large‐scale Internet data containing images of similar landmarks along with weakly‐related textual information. Our approach is built upon the premise that images physically grounded in space can provide a powerful supervision signal for localizing new concepts, whose semantics may be unlocked from Internet textual metadata with large language models. We use correspondences between views of scenes to bootstrap spatial understanding of these semantics, providing guidance for 3D‐compatible segmentation that ultimately lifts to a volumetric scene representation. To evaluate our method, we present a new benchmark dataset containing large‐scale scenes with ground‐truth segmentations for multiple semantic concepts. Our results show that HaLo‐NeRF can accurately localize a variety of semantic concepts related to architectural landmarks, surpassing the results of other 3D models as well as strong 2D segmentation baselines. Our code and data are publicly available at https://tau‐vailab.github.io/HaLo‐NeRF/.

Uncertainty Analysis for Ferromagnetic-Paramagnetic Phase Transition Behavior of Magnetic Materials

This study aims to model the phase transition of ferromagnetic materials using two- (2D) and three-dimensional (3D) Ising models, incorporating long-range magnetic spin-to-spin interactions and the influence of an external magnetic field. The 2D Ising model is investigated mainly for a 4×4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$4\ imes 4$$\\end{document} domain, while its extension to larger domains is also explored. For the 3D Ising model, the selection of representative volume element is discussed in terms of free energy. An uncertainty quantification formulation is integrated into the Ising model to capture the uncertainties related to the external magnetic field and evaluate their effects on the phase transition from a ferromagnetic to a paramagnetic state. Despite the common use and known effectiveness of the Ising model, there is still no universally accepted exact solution for the 3D domains, making it an ongoing research focus. The research also acknowledges the complexities and limitations arising from experimental methods, despite the insights they provide on the microscopic dynamics of ferromagnetic materials during phase transitions.

Efficient atomistic/continuum coupling using lattice Green’s functions

Coupled Atomistic/Continuum (A/C) simulation methods significantly reduce the number of degrees of freedom in the solution of a boundary value problem by using continuum elasticity in domains where defects interact elastically. A/C coupling involves two boundaries: (a) an inner boundary that connects the atomistic and continuum domain and (b) an outer boundary where displacement or force boundary conditions are applied. Here, the lattice Green’s function (LGF)–based flexible boundary condition method is combined with the LGF-based discrete boundary element method to satisfy coupling and boundary conditions at the inner and outer boundaries, respectively, of 3D domains. The coupling algorithms for Dirichlet boundary conditions are presented, with other cases being similar. The LGF is further replaced by a more efficient coarsened LGF method that coarsens the atomistic degrees of freedom at the outer boundary. The scaling of memory and computation versus 3D size and degree of coarsening are discussed. The method and its accuracy are demonstrated using a large 2D problem involving applied forces inside the atomistic domain.

Spontaneous Formation of 1D/3D Perovskite Heterojunctions for Efficient Inverted Perovskite Solar Cells

AbstractInterfacial modification is a key strategy for improving the performance of perovskite photovoltaic devices. While the modification of the top surface of the perovskite active layer is well established, engineering of the buried interface is highly challenging. Here, the spontaneous formation of a 1D/3D perovskite heterojunction at the buried interface of a perovskite active layer by incorporating choline acetate alongside the perovskite precursors is reported. Importantly, extensive spectroscopic and microscopic characterization and solid‐state nuclear magnetic resonance experiments demonstrate the formation of phase‐pure 1D and 3D domains. The 1D/3D junction results in a suppression of the defect states and an improved energetic level alignment at the buried interface, leading to a maximum power conversion efficiency of >24% when incorporated in inverted architecture perovskite solar cells. This work introduces a versatile approach to the modification of the buried interface of the perovskite active layer.

Direct numerical simulation of three-dimensional particle-laden thermal convection using the Lattice Boltzmann Method

In thermal multiphase flows, the modulation in the heat transfer rate due to the presence of finite-size solid particles attract growing interest in recent years. This study focuses on developing a robust and efficient simulation method for particle-laden Rayleigh-Bénard convection. The present work utilizes the double distribution function-based thermal lattice-Boltzmann method (TLBM), which enables successful simulations of multiphase fluid-thermal interactions. The no-slip boundary of the moving solid particles is handled by the interpolated bounce-back scheme. Additionally, Galilean invariant momentum exchange and heat exchange approaches are employed for hydrodynamic force and heat transfer calculation at the solid boundaries. The accuracy of the current method is verified with several benchmark cases, including three-dimensional single-phase Rayleigh-Bénard convection, as well as the settling of hot and cold spherical particles in a three-dimensional enclosure. Furthermore, we explore the modulation of Rayleigh-Bénard flows due to the presence of freely moving finite-size particles. The simulations are conducted on a distributed memory cluster with a 3D domain decomposition technique facilitated by the MPI library. A brief discussion on the parallel performance of the simulations is provided for both particle-laden and single-phase flow scenarios. Finally, the effects of finite-size solid particles on the overall heat transfer efficiency and modulation to the flow field in three-dimensional particle-laden turbulent Rayleigh-Bénard convection are discussed. The results show that addition of solid particles results in a moderate increase in the overall Nusselt number, and this enhancement is mainly due to the increased heat flux transported by the particles.

Multinode Shepard method for two-dimensional elliptic boundary problems on different shaped domains

In this paper, we continue the study on the application of multinode Shepard method to numerically solve elliptic Partial Differential Equations (PDEs) equipped with various conditions at the boundary of domains of different shapes. In particular, for the first time, the multinode Shepard method is proposed to solve elliptic PDEs with Dirichlet and/or Neumann boundary conditions. The method has been opportunely handled to efficiently work dealing with scattered distribution of points and, to this aim, several experiments in different 2d domains have been performed. Comparisons with the analytic solution and the results generated by the Kansa’s RBF solvers have been reported referring to Halton points. The results are very promising and should be of interest for applications in the real world.

Formation of Polar Crown Filament Magnetic Fields by Supergranular Helicity Injection

To understand the magnetic fields of the polar crown filaments (PCFs) at high latitudes near polar regions of the Sun, we perform magnetofrictional numerical simulations on the long-term magnetic evolution of bipolar fields with roughly east–west polarity inversion lines (PILs) in a 3D spherical wedge domain near polar regions. The Coriolis-effect-induced vortical motions at the boundaries of several supergranular cells inject magnetic helicity from the photospheric boundary into the solar atmosphere. Supergranular-scale helicity injection, transfer, and condensation produce strongly sheared magnetic fields. Magnetic reconnections at footpoints of the sheared fields produce magnetic flux ropes (MFRs) with helicity signs consistent with the observed hemispheric helicity rule. The cross-sectional area of MFRs exhibits an uneven distribution, resembling a “foot-node-foot” periodic configuration. Experiments with different tilt directions of PILs indicate that the PCFs preferably form along PILs with the western end close to the polar region. The bending of PILs caused by supergranular flows, forming S-shape (Z-shape) PIL segments, promotes the formation of dextral (sinistral) MFRs. The realistic magnetic models we obtained can serve as starting points for the study of the plasma formation and eruption of PCFs.

Dual-Perspective Knowledge Enrichment for Semi-supervised 3D Object Detection

Semi-supervised 3D object detection is a promising yet under-explored direction to reduce data annotation costs, especially for cluttered indoor scenes. A few prior works, such as SESS and 3DIoUMatch, attempt to solve this task by utilizing a teacher model to generate pseudo-labels for unlabeled samples. However, the availability of unlabeled samples in the 3D domain is relatively limited compared to its 2D counterpart due to the greater effort required to collect 3D data. Moreover, the loose consistency regularization in SESS and restricted pseudo-label selection strategy in 3DIoUMatch lead to either low-quality supervision or a limited amount of pseudo labels. To address these issues, we present a novel Dual-Perspective Knowledge Enrichment approach named DPKE for semi-supervised 3D object detection. Our DPKE enriches the knowledge of limited training data, particularly unlabeled data, from two perspectives: data-perspective and feature-perspective. Specifically, from the data-perspective, we propose a class-probabilistic data augmentation method that augments the input data with additional instances based on the varying distribution of class probabilities. Our DPKE achieves feature-perspective knowledge enrichment by designing a geometry-aware feature matching method that regularizes feature-level similarity between object proposals from the student and teacher models. Extensive experiments on the two benchmark datasets demonstrate that our DPKE achieves superior performance over existing state-of-the-art approaches under various label ratio conditions. The source code and models will be made available to the public.

Point2Real: Bridging the Gap between Point Cloud and Realistic Image for Open-World 3D Recognition

Recognition in open-world scenarios is an important and challenging field, where Vision-Language Pre-training paradigms have greatly impacted the 2D domain. This inspires a growing interest in introducing 2D pre-trained models, such as CLIP, into the 3D domain to enhance the ability of point cloud understanding. Considering the difference between discrete 3D point clouds and real-world 2D images, reducing the domain gap is crucial. Some recent works project point clouds onto a 2D plane to enable 3D zero-shot capabilities without training. However, this simplistic approach leads to an unclear or even distorted geometric structure, limiting the potential of 2D pre-trained models in 3D. To address the domain gap, we propose Point2Real, a training-free framework based on the realistic rendering technique to automate the transformation of the 3D point cloud domain into the Vision-Language domain. Specifically, Point2Real leverages a shape recovery module that devises an iterative ball-pivoting algorithm to convert point clouds into meshes, narrowing the gap in shape at first. To simulate photo-realistic images, a set of refined textures as candidates is applied for rendering, where the CLIP confidence is utilized to select the suitable one. Moreover, to tackle the viewpoint challenge, a heuristic multi-view adapter is implemented for feature aggregation, which exploits the depth surface as an effective indicator of view-specific discriminability for recognition. We conduct experiments on ModelNet10, ModelNet40, and ScanObjectNN datasets, and the results demonstrate that Point2Real outperforms other approaches in zero-shot and few-shot tasks by a large margin.

Cross-Constrained Progressive Inference for 3D Hand Pose Estimation with Dynamic Observer-Decision-Adjuster Networks

Generalization is very important for pose estimation, especially for 3D pose estimation where small changes in the 2D images could trigger structural changes in the 3D space. To achieve generalization, the system needs to have the capability of detecting estimation errors by double-checking the projection coherence between the 3D and 2D spaces and adapting its network inference process based on this feedback. Current pose estimation is one-time feed-forward and lacks the capability to gather feedback and adapt the inference outcome. To address this problem, we propose to explore the concept of progressive inference where the network learns an observer to continuously detect the prediction error based on constraints matching, as well as an adjuster to refine its inference outcome based on these constraints errors. Within the context of 3D hand pose estimation, we find that this observer-adjuster design is relatively unstable since the observer is operating in the 2D image domain while the adjuster is operating in the 3D domain. To address this issue, we propose to construct two sets of observers-adjusters with complementary constraints from different perspectives. They operate in a dynamic sequential manner controlled by a decision network to progressively improve the 3D pose estimation. We refer to this method as Cross-Constrained Progressive Inference (CCPI). Our extensive experimental results on FreiHAND and HO-3D benchmark datasets demonstrate that the proposed CCPI method is able to significantly improve the generalization capability and performance of 3D hand pose estimation.

Novel cobalt-incorporated two dimensional covalent organic frameworks for supercapacitor applications

Covalent-organic frameworks (COFs), are a promising new class of crystalline porous organic materials with confined structures either in 2D or 3D domains. The current study focuses on using a solvothermal approach consisting of sealed pyrex tubes to synthesize two-dimensional TBP-COF and TBP-COF that have been doped with cobalt (Co) (TBP-Co@COF). The results of the experimentally acquired X-ray diffraction study were compared with those from simulations, and it was discovered that both are in good agreement. A thorough theoretical analysis of the layer packing in AA stacking (P1) and AB stacking (P1) modes using the Materials Studio revealed that AA stacking is more stable than the AB stacking (P1) structure. The formation of imine linkage and incorporation of Co into the COF are indicated by the result of XPS. Unaggregated dispersion of Co particles can be seen on the square and rectangular sheets of TBP-COF in TEM and SEM images. Both materials are fabricated as electrode materials and evaluated for their supercapacitor applications. The TBP-Co@COF shows an enhanced specific capacitance (CSp) of 975F/g compared to the TBP-COF (827F/g) at 2 mV/s scan rate. TBP-Co@COF exhibit an energy density (ED) of 69 Wh/kg even at a high power density (PD) of 75000 W/kg and also retains 79 % of its initial capacitance up to 2000 cycles. TBP-COF and TBP-Co@COF were fabricated for an asymmetric supercapacitor device (ASD) and found to exhibit a CSp of 191F/g at a scan rate of 2 mV/s.

Field-scale numerical investigation of a hybrid gas production method from the oceanic hydrate accumulation at site NGHP-02-09 in the Krishna-Godavari Basin, and the associated geomechanical responses

The objectives of this study are to investigate (a) the technical feasibility of gas production from a gas hydrate accumulation at Site NGHP-02-09 in the Krishna-Godavari Basin, India Ocean using a hybrid production method involving a combination of depressurization and thermal stimulation, as well as (b) the associated geomechanical system response when considering both a simplified and a full geomechanical model. This is an extension of the earlier numerical study of Moridis et al. (2019a) of the site using cylindrical (single-well) 2D systems, which indicated (a) the main source of the produced gas to be CH4 dissolved in the water rather than CH4 from hydrate dissociation because of the presence of a high-permeability water-bearing zone that short-circuits the depressurization process and (b) the possibility of adverse geomechanical issues caused by significant displacements that could not be adequately investigated and resolved by the one-way coupling scheme invoked in that study. The proposed hybrid production plan involves two vertical wells in a 3D Cartesian domain: an injection well of warm ocean (saline) water and a production well at an appropriate distance, with the expectation that the hydrate dissociation caused by the depressurization at the production well can be augmented by the thermal effect of the injected warm water (as well as by its salinity), thus mitigating the effects of the high-permeability water zone. The results of this study that uses high-resolution 3D grids indicate that (a) the hybrid production scheme does not appear to offer any advantage over the simple single-well depressurization method of the earlier study, (b) the majority of the produced gas originates from CH4 exsolution from the water rather from hydrate dissociation, and (c) consideration of full geomechanics leads to generally slightly higher dissociation and fluid production because of the evolution of lower porosities and permeabilities, but also to the disappearance of the gas phase after 62 days of production, after which time CH4 from hydrate dissociation is fully dissolved in the water before production. Thus, the hybrid scheme investigated here appears ineffectual in enhancing hydrate dissociation and gas production, and the hydrate deposits at the Site NGHP-02-09 do not appear to be a promising production target under the conditions in this study, in agreement with the earlier conclusion of Moridis et al. (2019a).

Strong solutions and attractor dimension for 2D NSE with dynamic boundary conditions

We consider incompressible Navier–Stokes equations in a bounded 2D domain, complete with the so-called dynamic slip boundary conditions. Assuming that the data are regular, we show that weak solutions are strong. As an application, we provide an explicit upper bound of the fractal dimension of the global attractor in terms of the physical parameters. These estimates comply with analogous results in the case of Dirichlet boundary condition.

A fast, matrix-based method to perform omnidirectional pressure integration

Experimentally-measured pressure fields play an important role in understanding many fluid dynamics problems. Unfortunately, pressure fields are difficult to measure directly with non-invasive, spatially resolved diagnostics, and calculations of pressure from velocity have proven sensitive to error in the data. Omnidirectional line integration methods are usually more accurate and robust to these effects as compared to implicit Poisson equations, but have seen slower uptake due to the higher computational and memory costs, particularly in 3D domains. This paper demonstrates how omnidirectional line integration approaches can be converted to a matrix inversion problem. This novel formulation uses an iterative approach so that the boundary conditions are updated each step, preserving the convergence behavior of omnidirectional schemes while also keeping the computational efficiency of Poisson solvers. This method is implemented in Matlab and also as a GPU-accelerated code in CUDA-C++. The behavior of the new method is demonstrated on 2D and 3D synthetic and experimental data. Three-dimensional grid sizes of up to 125 million grid points are tractable with this method, opening exciting opportunities to perform volumetric pressure field estimation from 3D PIV measurements.