Spherical Model Research Articles

Fine‐Tuning of Elastic Properties by Modifying Ordering of Parallel Nanolayer Inclusions in Hard Sphere Crystals

It is known that changes on the microscopic, structural level of materials exert changes on their macroscopic properties, in particular elastic ones. This approach can be used to alter the elastic properties of materials. However, it is not easy to predict the impact of a particular change in the structure of crystals. The recent studies show that depending on the size, shape, and orientation of inclusions used, the resulting elastic properties may differ. Inclusions may enhance, weaken, or eliminate the auxetic properties in a hard sphere model. This study is focused on the influence of the spatial distribution of planar inclusions within the hard sphere crystal and its impact on its elastic properties. Periodic systems containing two nanolayer inclusions in the representative volume element, oriented orthogonally to ‐direction and in various spatial ordering, are considered. It has been shown that introducing layer inclusions causes the deterioration of auxetic properties in the ‐direction. However, the latter weakly depends on the spatial ordering of the inclusion layers. Moreover, changes in the size of the inclusion particles, combined with different ordering of the inclusion layers, can be used to coarsely and finely tune the elastic properties of the model crystal.

A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning

Path planning is a fundamental research issue for enabling autonomous flight in unmanned aerial vehicles (UAVs). An effective path planning algorithm can greatly improve the operational efficiency of UAVs in complex environments like urban and mountainous areas, thus offering more extensive coverage for various tasks. However, existing path planning algorithms often encounter problems such as high computational costs and a tendency to become trapped in local optima in complex 3D environments with multiple constraints. To tackle these problems, this paper introduces a hybrid multi-strategy artificial rabbits optimization (HARO) for efficient and stable UAV path planning in complex environments. To realistically simulate complex scenarios, we introduce spherical and cylindrical obstacle models. The HARO algorithm balances exploration and exploitation phases using a dual exploration switching strategy and a population migration memory mechanism, enhancing search performance and avoiding local optima. Additionally, a key point retention trajectory optimization strategy is proposed to reduce redundant path points, thus lowering flight costs. Experimental results confirm the HARO algorithm’s superior search performance, planning more efficient and stable paths in complex environments. The key point retention strategy effectively reduces flight costs during trajectory optimization, thereby enhancing adaptability.

Atrial Topology for a Unified Understanding of Typical and Atypical Flutter.

Macroreentry stands as the predominant mechanism of typical and atypical flutter. Despite advances in mapping, many aspects of macroreentrant atrial tachycardia remain unsolved. In this translational study, we applied principles of topology to understand the activation patterns, entrainment characteristics, and ablation responses in a large clinical macroreentrant atrial tachycardia database. Because the atrium can be topologically seen as a closed sphere with holes, we used a computational fixed spherical mesh model with a finite number of holes to induce and analyze macroreentrant atrial tachycardia. The ensuing insights were used to interpret high-density activation maps, postpacing interval-tachycardia cycle length values (difference between postpacing interval and tachycardia cycle length), and ablation response in 131 cases of typical and atypical flutter (n=106 left atrium, n=25 right atrium). Modeling of macroreentrant atrial tachycardia revealed that reentry on closed surfaces consistently manifests itself as paired rotation and that an odd number of critical boundaries is mathematically impossible. Together with mathematical confirmation by the index theorem, this led to a unifying construct that could explain the number of loops, difference between postpacing interval and tachycardia cycle length values, and ablation outcomes (termination, no change, or prolongation in tachycardia cycle length) in all 131 cases. Combining topology with the index theorem offers a novel and cohesive framework for understanding and managing typical and atypical flutter.

Fine analysis and size optimization of spherical hinge in swivel construction

Contact stress and friction torque are the two primary mechanical responses of a spherical hinge. In general engineering practice, the calculation methods for contact stress and friction in spherical hinges often involve simplifying the spherical hinge into a planar hinge. To accurately analyze the stress state of the spherical hinge, it is essential to establish a detailed model. In this study, 17 groups of spherical hinge models were developed. The support radius, curvature radius, and thickness of the spherical hinge are considered influencing factors, while the maximum contact stress, friction torque, and amount of steel used are treated as responses. A three-factor, three-level, and three-response design is implemented. Using the response surface method, optimization design is conducted, resulting in two proposed optimization schemes. The maximum contact stress is reduced by 40.10% and 10.91%, respectively, while the friction torque is decreased by 0.82% and 26.50%, respectively. The maximum error between the predicted and calculated values is 7.04%. This indicates that the model presented in this study possesses sufficient predictive accuracy and can effectively guide the selection of spherical hinge dimensions.

Resonant Excitation of Kelvin Waves by Interactions of Subtropical Rossby Waves and the Zonal Mean Flow

Abstract Equatorial Kelvin waves can be affected by subtropical Rossby wave dynamics. Previous research has demonstrated the Kelvin wave growth in response to subtropical forcing and the resonant growth due to eddy momentum flux convergence. However, the relative importance of the wave–mean flow and wave–wave interactions for the Kelvin wave growth compared to the direct wave excitation by the external forcing has not been made clear. This study demonstrates the resonant Kelvin wave excitation by interactions of subtropical Rossby waves and the mean flow using a spherical shallow-water model. The use of Hough harmonics as basis functions makes Rossby and Kelvin waves prognostic variables of the model and allows the quantification of terms contributing to their tendencies in physical and wave spaces. The simulations show that Kelvin waves are resonantly excited by interactions of Rossby waves and the balanced zonal mean flow in the subtropics, provided the Rossby and Kelvin wave frequencies, which are modified by the mean flow, match. The resonance mechanism is substantiated by analytical expressions. The Kelvin wave tendencies are caused by velocity and depth tendencies: The velocity tendencies due to the meridional advection of the zonal mean velocity can be outweighed by the zonal advection of the Rossby wave velocity or by the depth tendencies due to Rossby wave divergence. Identifying the resonant excitation mechanism in data should contribute to the quantification of Kelvin wave variability originating in the subtropics. Significance Statement This study seeks to understand how Kelvin waves, which are eastward-propagating disturbances in the tropical atmosphere, are connected to Rossby wave dynamics in the subtropics. Using idealized simulations, the Kelvin wave excitation is explained as a resonance effect due to interactions of Rossby waves and the zonal mean flow. The mechanism contributes to the understanding of atmospheric wave interactions and extratropical effects on the tropics. Further work searching for evidence of the new mechanism in atmospheric data may shed a new light on subseasonal variability in the tropics, such as the Madden–Julian oscillation.

Optimizing waste heat recovery for hydrogen production: Modeling and simulation of ternary size metallic granule flow in a cooling cylinder

In order to recover the waste heat of high temperature metallic granules to produce steam for hydrogen production, a waste heat recovery cooling cylinder with cooling water channel is innovatively developed. The simulation is carried out based on DEM and soft sphere model to study the flow characteristics of ternary size metallic granules. The model of cooling cylinder is established and verified by comparing to the experiment data. The change rule of bed shape in the waste heat recovery cooling cylinder is examined, and the inclination angle, rotational speed and filling rate are assessed to find their influence on the flow characteristics of ternary size metallic granules. The results indicated that, with the increase of inclination angle, the axial velocity increases by 482.76%, which means the reduce of residence time of granules. With the increase of rotational speed, the axial velocity has an increase of 161.54%, the sum velocity increases by 158.49%, leading to a decrease of residence time. As the filling rate increases from 1.5% to 15.5%, the contact number has an increase of 91.53%, which lead to the increase of heat transfer area. The residence time and heat transfer area will directly affect the waste heat recovery efficiency, so a proper arrangement of granule flow is significant for enhancing the heat transfer efficiency.

Regional spherical harmonic model for large telescope pointing error correction

Regional spherical harmonic model for large telescope pointing error correction

Comparative analysis of technological properties and microstructure of titanium powders of different classes of alloys

The results of a study of the technological properties of titanium powders of pseudo-α and pseudo-β alloys are presented. A comparative analysis of the characteristics of powder materials obtained by centrifugal spraying has been carried out. The results of the granulometric composition of the powders were obtained, and the calculation of the spatial packing of particles was applied within the framework of the hard sphere model for various fractional compositions. To compare the microstructure and mechanical properties, test samples from pseudo-α and pseudo-β titanium alloys were obtained using the hot isostatic pressing method according to selected modes.

Resonance scattering generated by rotating bodies

Abstract The scattering of rotating bodies to a polarized plane wave, including the dielectric cylinder and sphere, is studied. The resonance caused by rotation is emphasized. Numerical results prove that the resonance scattering caused by rotation can be realized in the optical range. It is sensitive to the rotation dimensionless parameter γ. The internal Mie mode corresponding to the electromagnetic field intensity changes with γ, and the resonant mode appears when the particle rotates at a specific speed. Moreover, the resonant mode changes with γ. It causes resonance scattering to appear in the same particle at different speeds. Inside particles, resonant rings are composed of a series of array points and are determined by γ. Under resonance conditions, the energy near the rotating cylinder is consistent with its rotation direction. In contrast, the direction of energy flow in the rotating sphere model is opposite to the direction of particle rotation. This work provides a novel idea for the design of ultra-sensitive sensors and resonators. It has promising applications in optical communication, optical microscopy, and optical signal processing.

The supermassive black hole merger-driven evolution of high-redshift red nuggets into present-day cored early-type galaxies

ABSTRACT Very compact ($R_\mathrm{e}\lesssim 1$ kpc) massive quiescent galaxies (red nuggets) are more abundant in the high-redshift Universe ($z\sim 2$–3) than today. Their size evolution can be explained by collisionless dynamical processes in galaxy mergers which, however, fail to reproduce the diffuse low-density central cores in the local massive early-type galaxies (ETGs). We use sequences of major and minor merger N-body simulations starting with compact spherical and disc-like progenitor models to investigate the impact of supermassive black holes (SMBHs) on the evolution of the galaxies. With the ketju code we accurately follow the collisional interaction of the SMBHs with the nearby stellar population and the collisionless evolution of the galaxies and their dark matter haloes. We show that only models including SMBHs can simultaneously explain the formation of low-density cores up to sizes of $R_\mathrm{b} \sim 1.3$ kpc with mass deficits in the observed range and the rapid half-mass size evolution. In addition, the orbital structure in the core region (tangentially biased orbits) is consistent with observation-based results for local cored ETGs. The displacement of stars by the SMBHs boost the half-mass size evolution by up to a factor of 2 and even fast rotating progenitors (compact quiescent discs) lose their rotational support after 6–8 mergers. We conclude that the presence of SMBHs is required for merger-driven evolution models of high-redshift red nuggets into local ETGs.

Ionisation of atoms determined by kappa refinement against 3D electron diffraction data.

Conventional refinement strategies used for three-dimensional electron diffraction (3D ED) data disregard the bonding effects between the atoms in a molecule by assuming a pure spherical model called the Independent Atom model (IAM) and may lead toan inaccurate or biased structure. Here we show that it is possible to perform a refinement going beyond theIAM with electron diffraction data. We perform kappa refinement which models charge transfers between atoms while assuming a spherical model. We demonstrate the procedure by analysing five inorganic samples; quartz, natrolite, borane, lutecium aluminium garnet, and caesium lead bromide. Implementation of kappa refinement improved the structure model obtained over conventional IAM refinements and provided information on the ionisation of atoms. The results were validated against periodic DFT calculations. The work presents an extension of the conventional refinement of 3D ED data for a more accurate structure model which enables charge density information to be extracted.

Correction to: Free Energy Fluctuations of the Bipartite Spherical SK Model at Critical Temperature

Correction to: Free Energy Fluctuations of the Bipartite Spherical SK Model at Critical Temperature

Structural analysis of superparamagnetic colloid aggregates confined in spherical cavities under external magnetic field

In this study, we investigated the behaviour of aggregates composed of superparamagnetic colloids under the influence of an external magnetic field, confined within several spherical cavities. The study included systems of two and three cavities in contact, as well as two cavities separated by a distance d along the direction of the external field. Monte Carlo computer simulations employing a model of hard spheres with central dipoles were realised to explore the behaviour of the magnetic particles, constrained to move within pairs (and trios) of spherical cavities. The primary focus of this investigation was to elucidate the structures formed by magnetic particles within systems presented here. Chains or ribbons primarily form within the central region of the spherical cavities. The aggregates within each cavity are drawn towards one another until they make contact at the closest points of the cavities. This behaviour is replicated when there is a separation distance between the spherical cavities, including cases where three cavities are in contact. This phenomenon may explain the observed attraction between magnetoliposomes as reported in the literature [García-Jimeno et al. Nanoscale. 9 (39), 15131–15143 (2017)].

Prediksi Risiko Emisi Karbon Dioksida Melalui Pemodelan GSTAR Kriging di Wilayah Asia

This study analyzes the variability of carbon dioxide emissions across Asia, revealing that China, India, and Indonesia are the primary contributors with extremely high average emissions and standard deviations. The GSTAR(3;1,1,1) model has been shown to be optimal for forecasting future emissions, based on lower RMSE and MAPE values. Ordinary Kriging analysis using the isotropic spherical semivariogram model provides the most accurate predictions for unobserved areas, with contour maps indicating that the northeastern region of Asia will continue to face high emission concentrations until 2027. While countries such as Brunei and Armenia have managed to keep emission levels low, the instability of emission trends across Asia underscores the need for emission reduction strategies tailored to the specific context of each country.

Theia 456: Tidally Shredding an Open Cluster

The application of clustering algorithms to the Gaia astrometric catalog has revolutionized our census of stellar populations in the milky Way, including the discovery of many new dispersed structures. We focus on one such structure, Theia 456 (COIN-Gaia-13), a loosely bound collection of ∼320 stars spanning ∼120 pc that has previously been shown to exhibit kinematic, chemical, and gyrochronal coherency, indicating a common origin. We obtain follow-up radial velocities and supplement these with Gaia astrometry to perform an in-depth dynamical analysis of Theia 456. By integrating stellar orbits through a Milky Way potential, we find the currently dispersed structure coalesced into a small cluster in the past. Via Bayesian modeling, we derive a kinematic age of 245 ± 3 Myr (statistical), a half-mass–radius of 9 ± 2 pc, and an initial one-dimensional velocity dispersion of 0.14 ± 0.02 km s−1. Our results are entirely independent of model isochrones, details of stellar evolution, and internal cluster dynamics, and the statistical precision in our age derivation rivals that of the most precise age-dating techniques known today, though our imperfect knowledge of the Milky Way potential and simple spherical model for Theia 456 at birth add additional uncertainties. Using posterior predictive checking, we confirm these results are robust under reasonable variations to the Milky Way potential. Such low-density structures that are disrupted by the Galactic tides before virializing may be ubiquitous, signifying that Theia 456 is a valuable benchmark for studying the dynamical history of stellar populations in the Milky Way.

Study on the characteristics particles of coarse grain material in high bench dump

Particle shape is an important factor affecting the strength and deformation of coarse materials in dumps. However, conducting research on particle shape in current laboratory experiments, and there exists no classification standard for the particle shape of the dump. Considering the project on high-bench dump in Jiangxi Province, based on the random particle construction method, this study determined the characteristic particles of coarse grain material in the dumping site by combining field investigation results, large-scale direct shear tests, and numerical analysis. Further, the influence mechanism of coarse grain content and characteristic particles on the mechanical characteristics of the dump were analyzed. The results showed that the increase in coarse grain content enhanced the irregularity of particle shape, increased the internal friction angle between particles, and reduced the cohesion of the dump. Moreover, with increase in the normal stress, the shear strength changed from insignificant to gradually enhanced, although the increasing trend slowed down. The constructed random particle model can well solve the effects of occlusion, nesting, and friction between particles that is neglected by the standard spherical particle model, and the fitting degree is better. The particle characteristics of coarse-grain materials in the dump were primarily block, strip, and flake. The three types of shape characteristics under low normal stress did not affect the mechanical properties of the dump. Further, with the increase in normal stress, the stress-strain curve reflected the shape characteristics and content of the dominant characteristics in the dump. Specifically, the block sample exhibited the dominant characteristics and the most content under the same normal stress, followed by the strip sample, with the flake sample exerting the least influence. The research results provide a theoretical basis for long-term safe operation, disaster monitoring, and early warning of high bench dump.

Time‐lapse inversion of self‐potential data through particle filtering

AbstractIn environmental sciences, comprehending the movement of subsurface contaminants is crucial for formulating effective remediation measures. The self‐potential (SP) method has become a common tool for delineating landfill contamination plumes. Contaminant diffusion or migration represents dynamic processes, with corresponding SP responses evolving over time. However, conventional SP interpretation approaches have predominantly relied on static single‐frame inversion, overlooking the temporal correlation in time‐series SP data and resulting in cumulative errors. To tackle this challenge, we introduce a novel method for time‐lapse inversion of SP data leveraging particle filtering. This approach recursively refines the priori state model through posteriori observations to achieve precise estimations of dynamic models. Specifically, a spherical polarization model is deployed to establish the state equations of underground contaminant diffusion and transport models, whereas the observation model is derived through forward modeling. The proposed method is validated using two synthetic examples and one lab‐measured dataset. The findings demonstrate the efficacy of the time‐lapse inversion algorithm in precisely estimating dynamic models, outperforming static single‐frame inversion based on the particle swarm optimization algorithm. The posteriori distribution of particles approximates a bell‐shaped distribution, with the true state closely positioned near the peak probability. Therefore, we affirm that conducting time‐lapse inversion of time‐series SP data through particle filtering is an effective and dependable approach for accurately estimating dynamic model states.

Bionic Design of High-Performance Joints: Differences in Failure Mechanisms Caused by the Different Structures of Beetle Femur-Tibial Joints.

Beetle femur-tibial joints can bear large loads, and the joint structure plays a crucial role. Differences in living habits will lead to differences in femur-tibial joint structure, resulting in different mechanical properties. Here, we determined the structural characteristics of the femur-tibial joints of three species of beetles with different living habits. The tibia of Scarabaeidae Protaetia brevitarsis and Cetoniidae Torynorrhina fulvopilosa slide through cashew-shaped bumps on both sides of the femur in a guide rail consisting of a ring and a cone bump. The femur-tibial joint of Buprestidae Chrysodema radians is composed of a conical convex tibia and a circular concave femur. A bionic structure design was developed out based on the characteristics of the structure of the femur-tibial joints. Differences in the failure of different joint models were obtained through experiments and finite element analysis. The experimental results show that although the spherical connection model can bear low loads, it can maintain partial integrity of the structure and avoid complete failure. The cuboid connection model shows a higher load-bearing capacity, but its failure mode is irreversible deformation. As key parts of rotatable mechanisms, the bionic models have the potential for wide application in the high-load engineering field.

BEMM-GEN: A Toolkit for Generating a Biomolecular Environment-Mimicking Model for Molecular Dynamics Simulation.

Understanding the influence of the cellular environment on protein conformations is crucial for elucidating protein functions within living cells. In studies using molecular dynamics (MD) simulation, carbon nanotubes and hydrophobic cages have been widely used to emulate the cellular environment inside specific large biomolecules such as ribosome tunnels and chaperones. However, recent studies suggest that these uniform hydrophobic models may not adequately capture the environmental effects inside each biomolecule. Based on these facts, it is necessary to generate spherical and cylindrical models with varied chemical properties corresponding to the components within target biomolecules. We developed a biomolecular environment-mimicking model generator (BEMM-GEN) that generates spherical and cylindrical models with user-specified chemical properties and allows the integration of arbitrary protein conformations into the generated models. BEMM-GEN provides model and protein complex structures, along with the corresponding parameter files for MD simulation (AMBER and GROMACS), and users immediately run their MD simulation based on the generated input files. BEMM-GEN can be freely downloaded and installed via a Python package manager (pip install BEMM-gen). The source code files and a user manual for operation are provided on GitHub (https://github.com/y4suda/BEMM-GEN).

Preferred Distance in Human-Drone Interaction.

In two augmented-reality experiments, we transferred the paradigm of interpersonal distance regulation to human-drone interaction. In the first experiment, we used a simple spherical drone model and explored how both hovering height and approach angle affect the preferred distance. Drone height above the ground had a strong effect. The preferred distance to the drone was larger than that typically found toward human actors, in particular, when the drone trajectory was very high. In the second experiment, we sought to gain a deeper understanding of the factors that may influence this effect. In addition to the simple spherical drone model used in the first experiment, we also varied its appearance and attachment to the ground. Surprisingly, anthropomorphic features increased preferred distances. We, therefore, discuss the extent to which social aspects and subjectively perceived danger influence the preferred distance for interaction with drones, which thus need to be considered in the design of human-drone interaction.