Coupled Kinetic-Fluid Simulations of Ganymede's Magnetosphere and Hybrid Parallelization of the Magnetohydrodynamics Model

The largest moon in the solar system, Ganymede, is the only moon known to possess a strong intrinsic magnetic field. The interaction between the Jovian plasma and Ganymede's magnetic field creates a mini-magnetosphere with periodically varying upstream conditions, which creates a perfect laboratory in nature for studying magnetic reconnection and magnetospheric physics. Using the latest version of Space Weather Modeling Framework (SWMF), we study the upstream plasma interactions and dynamics in this subsonic, sub-Alfvénic system. We have developed a coupled fluid-kinetic Hall Magnetohydrodynamics with embedded Particle-in-Cell (MHD-EPIC) model for Ganymede's magnetosphere, with a self-consistently coupled resistive body representing the electrical properties of the moon's interior, improved inner boundary conditions, and high resolution charge and energy conserved PIC scheme. I reimplemented the boundary condition setup in SWMF for more versatile control and functionalities, and developed a new user module for Ganymede's simulation. Results from the models are validated with Galileo magnetometer data of all close encounters and compared with Plasma Subsystem (PLS) data. The energy fluxes associated with the upstream reconnection in the model is estimated to be about 10^-7 W/cm^2, which accounts for about 40% to the total peak auroral emissions observed by the Hubble Space Telescope. We find that under steady upstream conditions, magnetopause reconnection in our fluid-kinetic simulations occurs in a non-steady manner. Flux ropes with length of Ganymede's radius form on the magnetopause at a rate about 3/minute and create spatiotemporal variations in plasma and field properties. Upon reaching proper grid resolutions, the MHD-EPIC model can resolve both electron and ion kinetics at the magnetopause and show localized crescent shape distribution in both ion and electron phase space, non-gyrotropic and non-isotropic behavior inside the diffusion regions. The estimated global reconnection rate from the models is about 80 kV with 60% efficiency. There is weak evidence of $sim 1$ minute periodicity in the temporal variations of the reconnection rate due to the dynamic reconnection process. The requirement of high fidelity results promotes the development of hybrid parallelized numerical model strategy and faster data processing techniques. The state-of-the-art finite volume/difference MHD code Block Adaptive Tree Solarwind Roe Upwind Scheme (BATS-R-US) was originally designed with pure MPI parallelization. The maximum problem size achievable was limited by the storage requirements of the block tree structure. To mitigate this limitation, we have added multithreaded OpenMP parallelization to the previous pure MPI implementation. We opt to use a coarse-grained approach by making the loops over grid blocks multithreaded and have succeeded in making BATS-R-US an efficient hybrid parallel code with modest changes in the source code while preserving the performance. Good weak scalings up to 50,0000 and 25,0000 of cores are achieved for the explicit and implicit time stepping schemes, respectively. This parallelization strategy greatly extends the possible simulation scale by an order of magnitude, and paves the way for future GPU-portable code development. To improve visualization and data processing, I have developed a whole new data processing workflow with the Julia programming language for efficient data analysis and visualization. As a summary, 1. I build a single fluid Hall MHD-EPIC model of Ganymede's magnetosphere; 2. I did detailed analysis of the upstream reconnection; 3. I developed a MPI+OpenMP parallel MHD model with BATSRUS; 4. I wrote a package for data analysis and visualization.PHDClimate and Space Sciences and EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163032/1/hyzhou_1.pd

Embedded Kinetic Simulation of Ganymede’s Magnetosphere: Improvements and Inferences

The largest moon in the solar system, Ganymede, is also the only moon known to possess a strong intrinsic magnetic field and a corresponding magnetosphere. Using the new version of Hall magnetohydrodynamic with embedded particle‐in‐cell model with a self‐consistently coupled resistive body representing the electrical properties of the moon’s interior, improved inner boundary conditions, and the flexibility of coupling different grid geometries, we achieve better match of magnetic field with measurements for all six Galileo flybys. The G2 flyby comparisons of plasma bulk flow velocities with the Galileo Plasma Subsystem data support the oxygen ion assumption inside Ganymede’s magnetosphere. Crescent shape, nongyrotropic, and nonisotropic ion distributions are identified from the coupled model. Furthermore, we have derived the energy fluxes associated with the upstream magnetopause reconnection of ∼10−7W/cm2 based on our model results and found a maximum of 40% contribution to the total peak auroral emissions.Key PointsHall MHD‐EPIC model of Ganymede’s magnetosphere uses realistic inner boundary conditions and energy‐conserving PIC schemeIon‐scale kinetics at upstream magnetopause are fully resolved, shown by the nongyrotropic/anisotropic distributionsElectron precipitation of ∼10−7 W/cm2 shows up to half of the peak emission brightness contributed by upstream reconnectionPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151299/1/jgra55029_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151299/2/jgra55029.pd

Density-invariant Features for Distant Point Cloud Registration

Registration of distant outdoor LiDAR point clouds is crucial to extending the 3D vision of collaborative autonomous vehicles, and yet is challenging due to small overlapping area and a huge disparity between observed point densities. In this paper, we propose Group-wise Contrastive Learning (GCL) scheme to extract density-invariant geometric features to register distant outdoor LiDAR point clouds. We mark through theoretical analysis and experiments that, contrastive positives should be independent and identically distributed (i.i.d.), in order to train densityinvariant feature extractors. We propose upon the conclusion a simple yet effective training scheme to force the feature of multiple point clouds in the same spatial location (referred to as positive groups) to be similar, which naturally avoids the sampling bias introduced by a pair of point clouds to conform with the i.i.d. principle. The resulting fully-convolutional feature extractor is more powerful and density-invariant than state-of-the-art methods, improving the registration recall of distant scenarios on KITTI and nuScenes benchmarks by 40.9% and 26.9%, respectively. Code is available at https://github.com/liuQuan98/GCL.Comment: In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 202

Spontaneous imbibition behavior in porous media with various hydraulic fracture propagations: A pore-scale perspective

Hydraulic fracturing technology can improve the geologic structure of unconventional oil and gas reservoirs, yielding a complex fracture network resulting from the synergistic action of hydraulic and natural fractures. However, the impact of spontaneous imbibition associated with hydraulic fracture propagation on the reservoir matrix remains poorly understood. In this study, combining the Cahn-Hilliard phase field method with the Navier-Stokes equations, pore-scale modeling was employed to capture the evolution of the oil-water interface during dynamic spontaneous imbibition for hydraulic fracture propagation in a two-end open mode. This pore-scale modeling approach can effectively circumvent the challenges of conducting spontaneous imbibition experiments on specimens partitioned by hydraulic fractures. A direct correlation was established between the pressure difference curve and the morphology of discharged oil phase in the primary hydraulic fracture, providing valuable insights into the distribution of oil phase in spontaneous imbibition. Furthermore, it was shown that secondary hydraulic fracture propagation expands the longitudinal swept area and enhances the utilization of natural fractures in the transverse swept area during spontaneous imbibition. When secondary hydraulic fracture propagation results in the interconnection of upper and lower primary hydraulic fractures, competitive imbibition occurs in the matrix, leading to reduced oil recovery compared to the unconnected models. Our results shed light upon the spontaneous imbibition mechanism in porous media with hydraulic fracture propagation, contributing to the refinement and application of hydraulic fracturing techniques.Document Type: Original articleCited as: Zhou, Y., Guan, W., Zhao, C., Zou, X., He, Z., Zhao, H. Spontaneous imbibition behavior in porous media with various hydraulic fracture propagations: A pore-scale perspective. Advances in Geo-Energy Research, 2023, 9(3): 185-197. https://doi.org/10.46690/ager.2023.09.0