3D Simulations Research Articles

A simulation on field distribution and particle capture characteristics in a multi-wire PHGMS system

ABSTRACT In the development history of high gradient magnetic separation (HGMS), the introduction of pulsating flow was extremely important, it successfully solved the problem of matrix clogging and allowed continuous and stable operation in the industry. However, the current pulsating HGMS (PHGMS) theory remains inadequately understood. In this paper, a 2D simulation model was established in COMSOL Multiphysics to reveal the magnetic field characteristics, flow field distribution, and particle capture dynamics in a PHGMS system. Quantitative comparisons were carried out between single-wire and multi-wire systems in the presence and absence of pulsation flow. The simulation results indicated that due to the coupled effect of neighboring magnetic wires in matrix, the magnetic field strength around an individual magnetic wire would slightly drop while the flow field velocity would increase. The introduction of pulsating flow could increase the peak value of fluid velocity and give particles a chance to move up and down. The analysis of particles travels length and capture probability indicated that the recovery for fine particles might be improved by increasing the strength of pulsating flow. This study provided a novel strategy for the highly efficient recovery of fine, weakly magnetic materials.

Mathematical Approach for Directly Solving Air–Water Interfaces in Water Emptying Processes

Emptying processes are operations frequently required in hydraulic installations by water utilities. These processes can result in drops to sub-atmospheric pressure pulses, which may lead to pipeline collapse depending on soil characteristics and the stiffness of a pipe class. One-dimensional mathematical models and 3D computational fluid dynamics (CFD) simulations have been employed to analyse the behaviour of the air–water interface during these events. The numerical resolution of these models is challenging, as 1D models necessitate solving a system of algebraic differential equations. At the same time, 3D CFD simulations can take months to complete depending on the characteristics of the pipeline. This presents a mathematical approach for directly solving air–water interactions in emptying processes involving entrapped air, providing a predictive tool for water utilities. The proposed mathematical approach enables water utilities to predict emptying operations in water pipelines without needing 2D/3D CFD simulations or the resolution of a differential algebraic equations system (1D model). A practical application is demonstrated in a case study of a 350 m long pipe with an internal diameter of 350 mm, investigating the influence of air pocket size, friction factor, polytropic coefficient, pipe diameter, resistance coefficient, and pipe slope. The mathematical approach is validated using an experimental facility that is 7.36 m long, comparing it with 1D mathematical models and 3D CFD simulations. The results confirm that the derived mathematical expression effectively predicts emptying operations in single water installations.

Assessing Protein Surface-Based Scoring for Interpreting Genomic Variants

Clinical genomics sequencing is rapidly expanding the number of variants that need to be functionally elucidated. Interpreting genetic variants (i.e., mutations) usually begins by identifying how they affect protein-coding sequences. Still, the three-dimensional (3D) protein molecule is rarely considered for large-scale variant analysis, nor in analyses of how proteins interact with each other and their environment. We propose a standardized approach to scoring protein surface property changes as a new dimension for functionally and mechanistically interpreting genomic variants. Further, it directs hypothesis generation for functional genomics research to learn more about the encoded protein’s function. We developed a novel method leveraging 3D structures and time-dependent simulations to score and statistically evaluate protein surface property changes. We evaluated positive controls composed of eight thermophilic versus mesophilic orthologs and variants that experimentally change the protein’s solubility, which all showed large and statistically significant differences in charge distribution (p < 0.01). We scored static 3D structures and dynamic ensembles for 43 independent variants (23 pathogenic and 20 uninterpreted) across four proteins. Focusing on the potassium ion channel, KCNK9, the average local surface potential shifts were 0.41 kBT/ec with an average p-value of 1 × 10−2. In contrast, dynamic ensemble shifts averaged 1.15 kBT/ec with an average p-value of 1 × 10−5, enabling the identification of changes far from mutated sites. This study demonstrates that an objective assessment of how mutations affect electrostatic distributions of protein surfaces can aid in interpreting genomic variants discovered through clinical genomic sequencing.

Impact of solar-wind turbulence on a planetary bow shock. A global 3D simulation

The interaction of the solar-wind plasma with a magnetized planet generates a bow-shaped shock ahead of the wind. Over recent decades, near-Earth spacecraft observations have provided insights into the physics of the bow shock, and the findings suggest that solar-wind intrinsic turbulence influences the bow shock dynamics. On the other hand, theoretical studies, primarily based on global numerical simulations, have not yet investigated the global three-dimensional (3D) interaction between a turbulent solar wind and a planetary magnetosphere. This paper addresses this gap for the first time by presenting an investigation of the global dynamics of this interaction that provides new perspectives on the underlying physical processes. We use the newly developed numerical code Menura to examine how the turbulent nature of the solar wind influences the 3D structure and dynamics of magnetized planetary environments, such as those of Mercury, Earth, and magnetized Earth-like exoplanets. We used the hybrid particle-in-cell (PIC) code Menura to conduct 3D simulations of the turbulent solar wind and its interaction with an Earth-like magnetized planet through global numerical simulations of the magnetosphere and its surroundings. Menura runs in parallel on graphics processing units (GPUs), enabling efficient and self-consistent modeling of turbulence. By comparison with a case in which the solar wind is laminar, we show that solar-wind turbulence globally influences the shape and dynamics of the bow shock, the magnetosheath structures, and the ion foreshock dynamics. Also, a turbulent solar wind disrupts the coherence of foreshock fluctuations, induces large fluctuations on the quasi-perpendicular surface of the bow shock, facilitates the formation of bubble-like structures near the nose of the bow shock, and modifies the properties of the magnetosheath region. The turbulent nature of the solar wind impacts the 3D shape and dynamics of the bow shock, magnetosheath, and ion foreshock region. This influence should be taken into account when studying solar-wind--planet interactions in both observations and simulations. We discuss the relevance of our findings for current and future missions launched into the heliosphere.

Dynamic Simulation Model of Miniature Tracked Forestry Tractor for Overturning and Rollover Safety Evaluation

This study proposes a method to construct a dynamic simulation model to implement the lateral overturning and backward rollover characteristics of an actual tractor. Based on theoretical analysis, factors affecting these characteristics are identified, which include tractor weight, track width, wheelbase, location of mass center, weight distribution, heights of front and rear axles, and geometric shapes. The location of the mass center of the actual tractor is measured based on the standard test procedure set by the International Organization for Standardization, and the remaining influencing factors are derived through measurements. A three-dimensional (3D) model of the tractor is constructed to reflect all these factors. Additionally, a simulation model utilizing this 3D model is developed using a commercial dynamic simulation software program. The ability of the model to simulate the overturning and rollover characteristics of the actual tractor is verified by comparing the static sidelong falling angle and minimum turning radius with those of the actual tractor. The errors between the characteristics of the actual tractor and those of the 3D model and dynamic simulations are shown to be less than 5%, thus indicating that the proposed method can effectively simulate the overturning and rollover characteristics of the actual tractor.

Modular and extendable 1D-simulation for microfluidic devices

Microfluidic devices have been the subject of considerable attention in recent years. The development of novel microfluidic devices, their evaluation, and their validation requires simulations. While common methods based on Computational Fluid Dynamics (CFD) can be time-consuming, 1D simulation provides an appealing alternative that leads to efficient results with reasonable quality. Current 1D simulation tools cover specific microfluidic applications; however, these tools are still rare and not widely adopted. There is a need for a more versatile and adaptable tool that covers novel applications, like mixing and the addition of membranes, and allows easy extension, resulting in one comprehensive 1D simulation tool for microfluidic devices. In this work, we present an open-source, modular, and extendable 1D simulation approach for microfluidic devices, which is available as an open-source software package at https://github.com/cda-tum/mmft-modular-1D-simulator. To this end, we propose an implementation that consists of a base module (providing the core functionality) that can be extended with dedicated application-specific modules (providing dedicated support for common microfluidic applications such as mixing, droplets, membranes, etc.). Case studies show that this indeed allows to efficiently simulate a broad spectrum of microfluidic applications in a quality that matches previous results or even fabricated devices.

3D Hydrodynamic Simulations of Massive Main-sequence Stars. III. The Effect of Radiation Pressure and Diffusion Leading to a 1D Equilibrium Model

We present 3D hydrodynamical simulations of core convection with a stably stratified envelope of a 25 M ⊙ star in the early phase of the main sequence. We use the explicit gas-dynamics code PPMstar, which tracks two fluids and includes radiation pressure and radiative diffusion. Multiple series of simulations with different luminosities and radiative thermal conductivities are presented. The entrainment rate at the convective boundary, internal gravity waves in and above the boundary region, and the approach to dynamical equilibrium shortly after a few convective turnovers are investigated. We perform very long simulations on 8963 grids accelerated by luminosity boost factors of 1000, 3162 and 10,000. In these simulations, the growing penetrative convection reduces the initially unrealistically large entrainment. This reduction is enabled by a spatial separation that develops between the entropy gradient and the composition gradient. The convective boundary moves outward much more slowly at the end of these simulations. Finally, we present a 1D method to predict the extent and character of penetrative convection beyond the Schwarzschild boundary. The 1D model is based on a spherically averaged reduced entropy equation that takes the turbulent dissipation as input from the 3D hydrodynamic simulation and takes buoyancy and all other energy sources and sinks into account. This 1D method is intended to be ultimately deployed in 1D stellar evolution calculations and is based on the properties of penetrative convection in our simulations carried forward through the local thermal timescale.

Height-function-based 4D reference metrics for hyperboloidal evolution

Hyperboloidal slices are spacelike slices that reach future null infinity. Their asymptotic behaviour is different from Cauchy slices, which are traditionally used in numerical relativity simulations. This work uses free evolution of the formally-singular conformally compactified Einstein equations in spherical symmetry. One way to construct gauge conditions suitable for this approach relies on building the gauge source functions from a time-independent background spacetime metric. This background reference metric is set using the height function approach to provide the correct asymptotics of hyperboloidal slices of Minkowski spacetime. The present objective is to study the effect of different choices of height function on hyperboloidal evolutions via the reference metrics used in the gauge conditions. A total of 10 reference metrics for Minkowski are explored, identifying some of their desired features. They include 3 hyperboloidal layer constructions, evolved with the non-linear Einstein equations for the first time. Focus is put on long-term numerical stability of the evolutions, including small initial gauge perturbations. The results will be relevant for future (puncture-type) hyperboloidal evolutions, 3D simulations and the development of coinciding Cauchy and hyperboloidal data, among other applications.

Effects of translation misalignment on ion optics with slit apertures

For ion thrusters, the deflection of the ion beam caused by the relative translation of the grids is one of the primary factors limiting the erosion lifetime of the ion optical system. A two-dimensional (2D) simulation package of the ion optic system is developed to investigate the ion sputtering corrosion due to grid translation misalignment. For benchmark cases, the 2D simulation package shows a reasonable consistency compared to the experimental method in ion beam deflection angle and drain-to-beam current ratio, indicating the effectiveness of the simulation package. The deviation between the simulated deflection angle and the experimental value is within 8.86%. Furthermore, this 2D package is employed to analyze the variation patterns of ion beam, ion collection, and the distribution of ion sputtering rates caused by grid translation. The simulation results indicate that the ion beam deflection occurs in the direction opposite to grid translation. The number of ions collected at different positions on the acceleration grid shows different tendencies. Only the upstream surface Sy− and the aperture surface Sx+ will be subjected to energetic ion impingement. The sputtering of energetic ions on these two surfaces becomes the dominant factor limiting the grid’s ion corrosion lifetime when the grid translation is significant. The sputtering rate of energetic ions can exceed that of charge exchange (CEX) ions by more than 10 times. The proportion of the region where energetic ions contribute to sputtering expands with increasing grid misalignment, reaching up to 52.5% on surface Sx+. Additionally, the downstream surface Sy+ and the aperture surface Sx− are only subjected to CEX ion sputtering regardless of grid translation. Moreover, the CEX ion sputtering regions on surfaces Sx− and Sx+ expand as the grid misalignment distance increases. The peak in the ion sputtering rate distribution profile on surface Sy+ becomes more prominent due to grid translation, with the sputtering rate at the peak position reaching approximately 1.65 times that of the surrounding lower-rate regions. The analysis of the electric field indicates that local electric field variations caused by grid misalignment are the underlying reason for the ion erosion characteristics.

A high-order generalised differential quadrature element method for simulating 2D and 3D incompressible flows on unstructured meshes

In this paper, a high-order generalised differential quadrature element method (GDQE) is proposed to simulate two-dimensional (2D) and three-dimensional (3D) incompressible flows on unstructured meshes. In this method, the computational domain is decomposed into unstructured elements. In each element, the high-order generalised differential quadrature (GDQ) discretisation is applied. Specifically, the GDQ method is utilised to approximate the partial derivatives of flow variables and fluxes with high-order accuracy inside each element. At the shared interfaces between different GDQ elements, the common flux is computed to account for the information exchange, which is achieved by the lattice Boltzmann flux solver (LBFS) in the present work. Since the solution in each GDQ element solely relies on information from itself and its direct neighbouring element, the developed method is authentically compact, and it is naturally suitable for parallel computing. Furthermore, by selecting the order of elemental GDQ discretisation, arbitrary accuracy orders can be achieved with ease. Representative incompressible flow problems, including 2D laminar flows as well as 3D turbulent simulations, are considered to evaluate the accuracy, efficiency, and robustness of the present method. Successful numerical simulations, especially for scale-resolving 3D turbulent flow problems, confirm that the present method is efficient and high-order accurate.

Beryllium–tungsten graded density inner shells in double shell capsules for improved hydrodynamic stability

The outer surface of the high-Z inner shell in the double shell configuration of inertial confinement fusion experiments experiences Rayleigh–Taylor instability growth during the implosion process due to inverted density and pressure gradients between a highly compressed foam interstitial layer and the accelerating dense inner shell. Graded density layers have long been known to reduce instability growth rates. In this study, we employ high-fidelity radiation hydrodynamic simulations to demonstrate this improved stability when grading beryllium into tungsten. We first characterize the response to L-band preheat of these layers using a newly calibrated radiation drive. While graded layer capsules suffer reduced performance (here, measured as DD neutron yield from a CD foam fuel) in 1D simulations due to reduced kinetic energy coupling and reduced fuel compression, they suffer less of a performance drop when 2D instabilities are accounted for. With the improved stability of graded layers, we explore the performance of capsules with larger fuel radii and thinner shells as a preliminary study to find new designs in which graded layers produce the highest yields.

Junction conditions for one-dimensional network hemodynamic model for total cavopulmonary connection using physically informed deep learning technique

Abstract This paper presents a novel methodology utilizing physics-informed neural network (PINN) as a junction condition for a 1D network model of blood flow in total cavopulmonary connection generated by the Fontan procedure. The technique integrates a 3D mesh generation process based on the parameterization of the junction geometry, along with a sophisticated physically regularized neural network architecture. Synthetic datasets are produced using 3D steady Stokes simulations within fixed boundaries. We use a physically informed feedforward neural network that utilizes a physically regularized loss function, which incorporates the principle of mass conservation. Our PINN achieves a tolerance of 6% on the test set. We develop a 1D-PINN multiscale model based on a previously developed method for multiscale 1D–3D simulations. Comparison with 1D–3D Stokes based model and 3D Navier–Stokes based model verifies the 1D-PINN model. In the first and second comparison, the maximum deviations of the averaged pressures and flows do not exceed 1.48% and 12.26%, respectively.

Enhancing 3D planetary atmosphere simulations with a surrogate radiative transfer model

Abstract This work introduces an approach to enhancing the computational efficiency of 3D atmospheric simulations by integrating a machine-learned surrogate model into the OASIS global circulation model (GCM). Traditional GCMs, which are based on repeatedly numerically integrating physical equations governing atmospheric processes across a series of time-steps, are time-intensive, leading to compromises in spatial and temporal resolution of simulations. This research improves upon this limitation, enabling higher resolution simulations within practical timeframes. Speeding up 3D simulations holds significant implications in multiple domains. Firstly, it facilitates the integration of 3D models into exoplanet inference pipelines, allowing for robust characterisation of exoplanets from a previously unseen wealth of data anticipated from JWST and post-JWST instruments. Secondly, acceleration of 3D models will enable higher resolution atmospheric simulations of Earth and Solar System planets, enabling more detailed insights into their atmospheric physics and chemistry. Our method replaces the radiative transfer module in OASIS with a recurrent neural network-based model trained on simulation inputs and outputs. Radiative transfer is typically one of the slowest components of a GCM, thus providing the largest scope for overall model speed-up. The surrogate model was trained and tested on the specific test case of the Venusian atmosphere, to benchmark the utility of this approach in the case of non-terrestrial atmospheres. This approach yields promising results, with the surrogate-integrated GCM demonstrating above 99.0% accuracy and 147 factor GPU speed-up of the entire simulation compared to using the matched original GCM under Venus-like conditions.

Examining the Role of Surface Temperature on Boundary Layer Stability and Transition to Turbulence

This study investigates the influence of varying surface temperature on the critical Reynolds number to understand the onset of turbulence in the boundary layer of a flat plate. Computational Fluid Dynamics (CFD) simulations in ANSYS Fluent have been utilized for the purpose of this study. The study systematically varies surface temperature to measure its impact on flow stability. The research demonstrates that an increase in surface temperature results in a lower critical Reynolds number (leading to an earlier transition from laminar to turbulent flow) by modeling air as the working fluid and applying the k-ω SST turbulence model. The results align with theoretical predictions which highlight the destabilizing effect of temperature-induced viscosity changes. This finding has practical implications for aerospace engineering, HVAC systems, and environmental modeling where controlling turbulence can optimize performance and energy efficiency. The study acknowledges limitations due to the use of a 2D model and suggests future work using 3D simulations and other flow conditions to expand the applicability of the findings.

LOSS BREAKDOWN IN AXIAL TURBINES: A NEW METHOD FOR VORTEX LOSS AND WAKE DETECTION FROM 3D RANS SIMULATIONS

Abstract To enhance turbine efficiency, it is essential to mitigate the losses generated by irreversible phenomena in turbine flows, including boundary layers, shock waves, vortices, and trailing edge wakes. Fast and accurate detection of losses is crucial from the earliest design stages, where reduced-order models based on oversimplified correlations are employed. This requires a deep understanding of the physics behind loss-generating mechanisms, attainable by examining the 3D flow. While existing criteria can identify various phenomena, accurately quantifying vortex-generated losses remains challenging, as these losses frequently extend beyond the vortical structure. This paper provides a straightforward and effective approach to localize and assess vortex-related losses. The method is grounded in Zlatinov's decomposition of the entropy generation rate into a streamwise and secondary flow component. A criterion based on vortex kinematics evaluates the vortex's strength, enabling the determination of its spatial influence and contribution to overall losses. To validate the method, a post-processing code is developed to perform loss breakdown, using existing identification criteria and new techniques introduced within this work, particularly for wake detection. 3D RANS simulations on various configurations, from simple curved ducts to nozzle guide vanes, allow to gradually test and validate the computational tool. Results confirm that the highest entropy generation rates occur outside the vortical structure and show good ability to identify both the vortex shape and its area of influence in terms of losses. A significant improvement in predicting vortex losses is observed, especially for turbine blades with leakage vortices.

3D Model Simulation in Preoperative Planning of Complex and Revision Hip Replacement

Complex and revision hip arthroplasty has remained one of the most discussed orthopedic topics in recent years. With the advancement of printing technologies 3D preoperative planning and live model simulation provides us with “hands on” procedures without any risk for the patient. Modern computer technologies present the possibility for preoperative planning of Total Hip Arthroplasty (THA) in digital environment. 3D printing of anatomical models in real size allows accurate assessment of the pathological deviations of the anatomy, precise preoperative planning of the reconstruction and simulation of the operative intervention ex-vivo. We present a series of 3D simulations for planning hip replacement, illustrating the technique, discussing its advantages and disadvantages, in complex primary and revision hip arthroplasty. In the complex and revision surgery of the hip joint, a correct assessment of bone defects is mandatory. Reconstructing the biomechanical parameters – centre of rotation, femoral offset and leg length discrepancy, is also of great significance. The 3D reconstruction with biomodel simulations offers exceptional accuracy in this respect. The method can be an excellent tool for education of surgeons in training and residents.

Three-Dimensional (3D) Flood Simulation Aids Informed Decision Making: A Case of a Two-Story Underground Parking Lot in Beijing

Flooding in underground spaces, such as subway stations, underground malls, and garages, has increased due to intensified rainfall, urbanization, and population growth. Traditional 2D simulations often overlook crucial vertical flow variations, especially in steep transitions like stairs and ramps. The current study aims to investigate the flood dynamics in large underground geometries by taking a parking lot in Beijing, China, as a study case. The model overcomes the limitations of previous simulations by adapting a full 3D mesh-based simulation with reasonable computational cost. Unlike earlier studies, this model employs a high temporal resolution transient inflow at the inlet to the underground space. Simulation scenarios consider different return periods (5, 20, and 100 years) and inlet water depths, providing an analysis of their impact on flood status in the underground structure. The model generates high spatial–temporal results, enabling precise detection of flood-prone locations, evacuation times, and suggested mitigation techniques. The results recommend evacuating from hazard areas before the 10th minute during extreme flood events. Additionally, the study estimates a 40% increase in flood hazards for scenarios with direct connections between levels. Overall, the study highlights the importance of 3D simulations for accurate risk assessment.

Probing Three-dimensional Magnetic Fields. III. Synchrotron Emission and Machine Learning

Synchrotron observation serves as a tool for studying magnetic fields in the interstellar medium and intracluster medium, yet its ability to unveil three-dimensional (3D) magnetic fields, meaning probing the field’s plane-of-the-sky (POS) orientation, inclination angle relative to the line of sight, and magnetization from one observational data, remains largely underexplored. Inspired by the latest insights into anisotropic magnetohydrodynamic (MHD) turbulence, we found that synchrotron emission’s intensity structures inherently reflect this anisotropy, providing crucial information to aid in 3D magnetic field studies: (i) the structure’s elongation gives the magnetic field’s POS orientation and (ii) the structure’s anisotropy degree and topology reveal the inclination angle and magnetization. Capitalizing on this foundation, we integrate a machine learning approach—convolutional neural network (CNN)—to extract this latent information, thereby facilitating the exploration of 3D magnetic fields. The model is trained on synthetic synchrotron emission maps, derived from 3D MHD turbulence simulations encompassing a range of sub-Alfvénic to super-Alfvénic conditions. We show that the CNN is physically interpretable and the CNN is capable of obtaining the POS orientation, inclination angle, and magnetization. Additionally, we test the CNN against the noise effect and the missing low-spatial frequency. We show that this CNN-based approach maintains a high degree of robustness even when only high-spatial frequencies are maintained. This renders the method particularly suitable for application to interferometric data lacking single-dish measurements. We applied this trained CNN to the synchrotron observations of a diffuse region. The CNN-predicted POS magnetic field orientation shows a statistical agreement with that derived from synchrotron polarization.

The Influence of the Intake Geometry on the Performance of a Four-Stroke SI Engine for Aeronautical Applications

In this work, the influence of plenum and port geometry on the performance of the intake process in a four-stroke spark ignition engine for ultralight aircraft applications is analyzed. Three intake systems are considered: the so-called “standard plenum”, with a relatively small plenum volume, the “V1 plenum”, with a larger plenum volume, and the “standard plenum” equipped with a large curvature manifold called the “G2 port”. Both measurements and 3D CFD simulations, by using Ansys® Academic Fluent, Release 20.2, are performed to characterize and analyze the steady-flow field in the intake system for selected valve lifts. The experimental data and the numerical results are in excellent agreement with each other. The results show that at the maximum valve lift, i.e., 12 mm, the V1 plenum allows an increase in the air mass flow rate of 9.1% and 9.4% compared to the standard plenum and the standard plenum with the “G2 port”, respectively. In addition, the volumetric efficiency has been estimated under unsteady-flow conditions for all geometries at relatively high engine rpms. The difference between numerical results and measurements is less than 1% for the standard plenum, thus proving the accuracy of the model, which is then used to study the other configurations. The V1 plenum shows a fairly constant volumetric efficiency as the engine speed increases, although such an efficiency is lower than that of the other two geometries considered in this work. Specifically, the use of the “G2 port” leads to an increase of 1.5% in terms of volumetric efficiency with respect to the configuration with the original manifold. Furthermore, for the “G2 port” configuration, higher turbulent kinetic energy and higher swirl and tumble ratios are observed. This is expected to result in an improvement of air–fuel mixing and flame propagation.

Accreting Neutron Stars in 3D General-relativistic Magnetohydrodynamic Simulations: Jets, Magnetic Polarity, and the Interchange Slingshot

Abstract Accreting neutron stars differ from black holes by the presence of the star’s own magnetic field, whose interaction with the accretion flow is a central component in understanding these systems’ disk structure, outflows, jets, and spin evolution. It also introduces an additional degree of freedom, as the stellar dipole can have any orientation relative to the inner disk’s magnetic field. We present a suite of 3D general-relativistic magnetohydrodynamic simulations in which we investigate the two extreme polarities, with the dipole field being either parallel or antiparallel to the initial disk field, in both the accreting and propeller states. When the magnetosphere truncates the disk near or beyond the corotation radius, most of the system’s properties, including the relativistic jet power, are independent of the star–disk relative polarity. However, when the disk extends well inside the corotation radius, in the parallel orientation the jet power is suppressed and the inner disk is less dense and more strongly magnetized. We suggest a physical mechanism that may account for this behavior—the interchange slingshot—and discuss its astrophysical implications. When the star is in the rapidly accreting regime, which in most cases will be associated with strong spin-up, we expect large observational differences between the two magnetic orientations. This may be reflected in increased variability as the accretion flow drags in successive magnetic structures of varying polarity.