Space Research Articles

CALCULATION OF PLASMA HEATING BY CHARGED PRODUCTS OF THERMONUCLEAR REACTIONS BASED ON A SIMPLIFIED FOKKER–PLANCK EQUATION

A two-time-layer scheme has been developed for solving the simplified kinetic Fokker–Planck equation related to the transport of charged products of thermonuclear reactions, which includes an interpolation procedure in four-dimensional grid space. Instabilities in the scheme were detected at low particle velocities and for a specific choice of particle deceleration in the ion field, which enters the kinetic equation as a parameter. It was shown that the thermalization condition, which prohibits solving the kinetic equation for particles with energy lower than the average ion energy, significantly limits the number of thermonuclear reactions where instability can manifest. The scheme was tested on the problem of relaxation to a stationary state and on a problem with a prescribed time-dependent thermonuclear reaction rate, for which an exact solution to the kinetic equation can be found.

ON THE STRUCTURE OF HELICAL AXISYMMETRIC SOLUTIONS OF THE NAVIER-STOKES SYSTEM FOR INCOMPRESSIBLE FLUIDS

A class of exact solutions to the Navier-Stokes equations for axisymmetric vortex flows of incompressible fluids is obtained. Invariant manifolds of flows with rotational symmetry relative to a given axis in three-dimensional coordinate space are identified, and the structure of the solutions is described. It is established that typical invariant regions of such flows are rotational figures homeomorphic to a torus, forming a structure of topological fibration, such as in a sphere, cylinder, and more complex configurations composed of such figures. The results are extended to similar solutions of the magnetohydrodynamics (MHD) system and Maxwell’s electrodynamics equations, which possess ℝ3 analogous properties. Examples of axisymmetric vortex vector fields and the topological fibrations they generate on manifolds invariant ℝ3 under the dynamical systems defined by these fields are provided.

Minimally Deformed Anisotropic Version of Tolman-Finch-Skea Stellar Model in Einstein Gauss Bonnet Gravity

Abstract In this article, a known anisotropic solution named Tolman-Finch-Skea (TFS) is discussed under gravitational decoupling (GD) approach in the framework of $4$-dimensional Einstein-Gauss-Bonnet (EGB) gravity. The radial metric potential is linearly transformed with the minimal geometric deformation (MGD) approach while the temporal metric part remains unchanged. The system of EGB field equations converted into two distinct systems of field equations, where one of them is against the standard energy-momentum-tensor (EMT), while the other one is related to the external gravitational source. The first system is determined by using aforementioned known solution, while the second one is closed by using mimic constraint on pressure. Moreover, the junction conditions at the inner and outer surfaces of stellar object are examined with Boulware-Deser 4D space--time as the outer geometry. The stellar model is physically analyzed by using the parameters like energy conditions, causality condition, Herrera's cracking condition, compactness and red shift.

CNN-Based Multi-Object Detection and Segmentation in 3D LiDAR Data for Dynamic Industrial Environments

Autonomous navigation in dynamic environments presents a significant challenge for mobile robotic systems. This paper proposes a novel approach utilizing Convolutional Neural Networks (CNNs) for multi-object detection in 3D space and 2D segmentation using bird’s eye view (BEV) maps derived from 3D Light Detection and Ranging (LiDAR) data. Our method aims to enable mobile robots to localize movable objects and their occupancy, which is crucial for safe and efficient navigation. To address the scarcity of labeled real-world datasets, a synthetic dataset based on a simulation environment is generated to train and evaluate our model. Additionally, we employ a subset of the NVIDIA r2b dataset for evaluation in the real world. Furthermore, we integrate our CNN-based detection and segmentation model into a Robot Operating System 2 (ROS2) framework, facilitating communication between mobile robots and a centralized node for data aggregation and map creation. Our experimental results demonstrate promising performance, showcasing the potential applicability of our approach in future assembly systems. While further validation with real-world data is warranted, our work contributes to advancing perception systems by proposing a solution for multi-source, multi-object tracking and mapping.

JNR Skyrmions

The JNR ansatz provides a simple formula to obtain families of charge N self-dual SU(2) Yang-Mills instantons in four-dimensional Euclidean space, from the free data of N + 1 distinct points with associated positive weights. Here an analogous formula is presented for Skyrme fields in three-dimensional Euclidean space. These families of Skyrme fields include good approximations to a range of Skyrmions, with energies that are typically within a few percent of the numerically computed solutions.

Tensor linearity of two-dimensional isotropic functions in the plane problem of nonlinear theory of elasticity

It is shown that a nonlinear isotropic tensor function of the second rank in two-dimensional space, which is a power series in its tensor argument, is representable by a finite binomial tensor linear relation. Expressions of two coefficients of this relation are given in terms of an infinite set of coefficients of the original series and two independent invariants of the tensor argument. In relation to continuum mechanics, the reducibility of the constitutive relations in the plane problem of tensor nonlinear elasticity theory to the tensor linear connection of the corresponding second-order minors of stresses and strains is established.

Minimal translation factorable surfaces in hyperbolic space

The theory of Minimal Surfaces is one of the most interesting subject in mathematics. The study and computation of minimal surfaces has a long history. Lagrange made the first investigation of the minimal surfaces by asking a simple question named as Plateau’s problem which concerns with finding a surface of least area that spans a given fixed one-dimensional contour in three-dimensional Euclidean space. The study of this kind of surfaces has motivated the development of numerous concepts and techniques in the calculus of variations which later have been applied to solving a great quantity of problems in very diverse areas ranging from the study of partial differential equations to topology and even to settling conjectures in relativity. Mathematically, a minimal surface corresponds to the solution of a nonlinear partial differential equation. In this paper, we define two types of Translation-Factorable (T-F) surfaces in the 3-dimensional hyperbolic space. Then, we obtain the complete classification of these surfaces with vanishing mean curvature by solving some differential equations.

Horocycle regulator: Exact cutoff-independence in AdS/CFT

While the entanglement entropy of a single subregion in quantum field theory is formally infinite and requires regularization, certain combinations of entropies are perfectly finite in the limit that the regulator is removed, the mutual information being a common example. For generic regulator schemes, such as a holographic calculation with a uniform radial cutoff, these quantities show nontrivial dependence on the regulator at finite values of the cutoff. We investigate a holographic regularization scheme defined in three-dimensional anti-de Sitter space constructed from , curves in two-dimensional hyperbolic space perpendicular to all geodesics approaching a single point on the boundary, that leads to finite information measures that are cutoff independent, even at finite values of the regulator. We describe a broad class of such information measures, and describe how the field theory dual to the horocycle regulator is inherently nonlocal. Published by the American Physical Society 2024

Spatiotemporal Urban Evolution Along the China–Laos Railway in Laos Determined Using Multiple Sources of Remote-Sensed Landscape Indicators and Interpretable Machine Learning

Constructing high-speed railways (HSRs) is critical for developing countries to stimulate economic growth and urbanization. This study focuses on the Lao section of the China–Laos Railway (CLR) and employs explicitly spatial remote sensing images to investigate the urban development surrounding HSR stations. Data-driven machine learning and causal inference approaches are integrated to quantify the spatial–temporal evolution and discover its driving factors. The results suggest that the CLR has had positive spatial spillover effects on the development of the surrounding urban space. These spillover effects have exhibited a distance attenuation pattern, reflecting obvious development in 2D rather than in 3D urban space. Meanwhile, the distance to stations and adjacent city centers as well as functional urban characteristics, such as land use patterns and industrialization level, have significantly influences the surrounding spatial development. Specifically, in industrial-dominated cities, the surrounding spatial changes have been most significant under the influence of the HSR. Change related to industrial and residential land use has shown significant land expansion patterns and increased utilization efficiency, reflecting that industrialization and urbanization have been the primary drivers of land demand surrounding the HSR. The findings offer valuable insights and references for developing nations to formulate and implement spatial management policies and initiatives related to HSR.

A 3D calibration method for binocular vision system

Abstract Binocular vision system calibration is extremely important in three-dimensional (3D) measurement. During the calibration process, the establishment of an appropriate objective function has a direct impact on the calibration accuracy. For common two-dimensional (2D) calibration methods, differences in 2D calibration and 3D measurement coordinate systems result in loss of accuracy. Furthermore, for the newly proposed 3D calibration methods, the epipolar constraints in the 2D pixel coordinate system and the reconstruction errors in the 3D physical space need to be balanced by weights, resulting in uncertainties in the calibration results. To address these issues, we propose a novel calibration method that minimizes the distances between the control point and the left and right camera rays. The distances between the control points and the camera rays describe the 3D reconstruction errors, and the distances between the left camera and the right camera rays describe the geometry information between the two cameras to ensure that the epipolar constraints are satisfied. As a result, these two types of constraints/errors are measured under the same 3D coordinate system. Therefore, the epipolar constraints and the reconstruction errors are naturally balanced. We have conducted computer simulations and real experiments, and the results show that the proposed calibration method is effective in improving the accuracy compared with the state-of-the-art methods.

Mobile phone based laser scanning as a low-cost alternative for multidisciplinary data collection

Airborne and terrestrial laser scanners have traditionally been used as specialised toolsets for three-dimensional scene capture in engineering, providing highly accurate measurements with increasingly minimal human interaction. However, commercial or engineering-grade scanning instruments remain expensive and sensitive, requiring costly routine calibrations to ensure their optimum functionality. The recent inclusion of laser scanning sensors by mobile phone corporations such as Apple Computer Inc. is now analogous to the integration of Global Navigation Satellite Systems (GNSS) and cameras into smartphones as seen decades ago. Likely, these initial efforts to include the scanning sensor in mobile phones will see rapid improvements in the application and accuracy of the sensor to serve the growing need for scanning applications for transdisciplinary users. However, there is a limited amount of literature that benchmarks the emerging and low-cost scanning sensors to existing commercial ones to inform practice, thus prompting a need for researchers to evaluate and provide scientific evidence that can inform multidisciplinary scanning. It was noted that there was some absolute positional shift and scan drift in the iPhone Light Detection and Ranging (LiDAR) data. The researchers therefore investigated the extent to which the accuracy of laser scanning tools available within the iPhone 12 Pro compared to engineering-grade laser scanners. Outcomes from the study showed that iPhone scanners can deliver the required models, despite being unstable in dynamic environments when pitched against engineering-grade LiDAR scanners. The research recommends that stabilisers, such as stabilising gimbals or enhanced GNSS receivers, be used in practice to achieve improved accuracy from the mobile phone LiDAR.

Three-dimensional embodied visibility graph analysis: Investigating and analyzing values along an outdoor path

In visibility analysis, a major focus is the relationship between people and the environment, and one of the most important spatial concepts is Isovist. Although typically represented in two dimensions in architecture, this concept has recently been computed in a three-dimensional environment. However, embodied 3D isovist Theory as developed to date does not account for locomotion. In this paper, therefore, we combine that theory with 3D visibility graph theory to develop and propose the Three-Dimensional Embodied Visibility Graph (3D E-VGA). To present and evaluate the proposed model in an architectural environment, we analyze the three-dimensional scene of a pedestrian moving along a path in an outdoor environment, specifically that of a container housing design project in Cairo known as “Sheltainer.” Further, we investigate the relationships between the t-d ratio, the v-h ratio, vertical jaggedness, connectivity, and integration values and conclude that of these the last three-vertical jaggedness, connectivity, and integration- are significantly correlated with each other. However, the relationship between v-h, t-d, and connectivity and integration values has not been determined. Therefore, analyzing both values related to embodied 3D isovist and 3D visibility graph provides us with a more comprehensive and effective analysis of pedestrians’ visual perceptions along a path.

In-Depth Structural Analysis of a Stapled Pentapeptide and Its Assembly Into Straight α-Helices.

Peptide self-assembly is a complex hierarchical process involving the progressive formation of secondary structures, such as α-helices, β-sheets, and turns, during the early stages. It is precisely these multi-component building blocks that contribute to the complexity of protein assemblies in living organisms. While coiled coils are well-understood in protein folding, determining the structural characteristics governing their lateral packing remains challenging. Here, a stapled pentapeptide (CIHs) that forms straight α-helices are reported. Using single crystal X-ray diffraction and Microcrystal electron diffraction (Micro-ED), the atomic-level assembly mechanism of CIHs is investigated. This study describes the specific geometric standards based on these α-helical building blocks and their interactions. By modulating the hydrophobic interface between these blocks via side-chain alterations, this study validates that these mutant assemblies can inherit the specific spatial geometry and regular interaction interfaces of straight α-helices. These results provide a simple template for exploring the hierarchical assembly of straight α-helices and studying the impact of side chains on lateral packing, opening new avenues for the development of high-order peptide assemblies based on straight α-helices.

A converse of De Gua’s theorem for orthocentric tetrahedra

Summary We establish a converse of De Gua’s theorem for orthocentric tetrahedra in the three-dimensional space with a proof using the converse of the Pythagorean theorem and Heron’s formula.

Three-Dimensional Printing of Bioinspired Hierarchical Structures for Enhanced Fog Collection Efficiency in 3D Space via Vat Photopolymerization

Collecting fog water is crucial for dry areas since natural moisture and fog are significant sources of freshwater. Sustainable and energy-efficient water collection systems can take a page out of the cactus’s playbook by mimicking its native fog gathering process. Inspired by the unique geometric structure of the cactus spine, we fabricated a bioinspired artificial fog collector consisting of cactus spines featuring barbs of different sizes and angles on the surfaces for water collection and a series of microcavities within microchannels inspired by Nepenthes Alata on the bottom to facilitate water flowing to the reservoir. However, replicating the actual shape of the cactus spine using conventional manufacturing techniques is challenging, and research in this area has faced a limitation in enhancing water-collecting efficiency. Here, we turned to 3D printing technology (vat photopolymerization) to create bio-mimetic fog collectors with a variety of geometric shapes that would allow for the most effective conveyance and gathering of water. Various barb sizes, angles between each barb in a single array, spine and barb arrangements, and quantity of barbs were tested experimentally and numeric analysis was carried out to measure the volume of water collected and optimize the mass rate. The result shows that optimal fog collection is with a mass flow rate of 0.7433 g/min, with Li = 900 μm, θ = 45°, ϕ = 90°, Nb = 2, and Ns = 5. This study presents a sustainable and ecologically sound method for efficiently collecting humid air, which is expected to be advantageous for the advancement of future-oriented fog-collection, water-transportation, and separation technologies.

How fast are viruses spreading in the wild?

Genomic data collected from viral outbreaks can be exploited to reconstruct the dispersal history of viral lineages in a two-dimensional space using continuous phylogeographic inference. These spatially explicit reconstructions can subsequently be used to estimate dispersal metrics that can be informative of the dispersal dynamics and the capacity to spread among hosts. Heterogeneous sampling efforts of genomic sequences can however impact the accuracy of phylogeographic dispersal metrics. While the impact of spatial sampling bias on the outcomes of continuous phylogeographic inference has previously been explored, the impact of sampling intensity (i.e., sampling size) when aiming to characterise dispersal patterns through continuous phylogeographic reconstructions has not yet been thoroughly evaluated. In our study, we use simulations to evaluate the robustness of 3 dispersal metrics - a lineage dispersal velocity, a diffusion coefficient, and an isolation-by-distance (IBD) signal metric - to the sampling intensity. Our results reveal that both the diffusion coefficient and IBD signal metrics appear to be the most robust to the number of samples considered for the phylogeographic reconstruction. We then use these 2 dispersal metrics to compare the dispersal pattern and capacity of various viruses spreading in animal populations. Our comparative analysis reveals a broad range of IBD patterns and diffusion coefficients mostly reflecting the dispersal capacity of the main infected host species but also, in some cases, the likely signature of rapid and/or long-distance dispersal events driven by human-mediated movements through animal trade. Overall, our study provides key recommendations for the use of lineage dispersal metrics to consider in future studies and illustrates their application to compare the spread of viruses in various settings.

Hierarchical Polyimide Nonwoven Fabric with Ultralow-Reflectivity Electromagnetic Interference Shielding and High-Temperature Resistant Infrared Stealth Performance

Designing and fabricating a compatible low-reflectivity electromagnetic interference (EMI) shielding/high-temperature resistant infrared stealth material possesses a critical significance in the field of military. Hence, a hierarchical polyimide (PI) nonwoven fabric is fabricated by alkali treatment, in-situ growth of magnetic particles and "self-activated" electroless Ag plating process. Especially, the hierarchical impedance matching can be constructed by systematically assembling Fe3O4/Ag-loaded PI nonwoven fabric (PFA) and pure Ag-coated PI nonwoven fabric (PA), endowing it with an ultralow-reflectivity EMI shielding performance. In addition, thermal insulation of fluffy three-dimensional (3D) space structure in PFA and low infrared emissivity of PA originated from Ag plating bring an excellent infrared stealth performance. More importantly, the strong bonding interaction between Fe3O4, Ag, and PI fiber improves thermal stability in EMI shielding and high-temperature resistant infrared stealth performance. Such excellent comprehensive performance makes it promising for military tents to protect internal equipment from electromagnetic interference stemmed from adjacent equipment and/or enemy, and inhibit external infrared detection.

Periodic and chaotic behaviors of a compound pendulum driven by a horizontal periodic external force

Abstract Based on the oscillation experiments of a compound pendulum driven by a horizontal periodic external force, a nonlinear dynamical model is established and studied numerically. The periodic, quasiperiodic and chaotic orbits are found in the motions of the compound pendulum in response to several driving forces. The numerical results are in qualitative agreement with those in the experiments. It is found that
the chaotic attractor in the three-dimensional phase space displays a two-dimensional torus structure.
On a Poincare section, the chaotic attractor consists of the relative rotating core and its trailing tails.
The fractal dimension of the chaotic attractor on the Poincare section is determined by using the box-counting method. The bifurcation diagram shows that the transition of the system from periodic motion to chaos is realized by the period-doubling bifurcation. The first Feigenbaum universal constant is approximately determined in the period-doubling bifurcation process.
The competition between the inherent vibration and the external driving vibration of the system
is thus thought as the physical mechanism for leading to the complex phenomena such as the period-doubling bifurcation and chaos.
The numerical results combining with the experimental ones can provide an intuitive and in-depth understanding of chaotic phenomena, which is of great significance for the optimization design and the stability control in the engineering technology.

Three-Dimensional Event-Triggered Predefined-Time Cooperative Guidance Law

To address the problem of multiple missiles attacking a maneuvering target simultaneously in three-dimensional space, we propose a new predefined-time cooperative guidance law based on an event-triggered mechanism. The settling time of the system states under this guidance law is independent of the initial states, and the upper bound of the settling time can be directly set by the explicit parameters in the guidance law. Firstly, the time-to-go estimate is taken as a consistency variable, and the communication failure and time-delay that are easily encountered during the communication process are taken into account; the event-triggered mechanism is introduced into the guidance law along the line of sight (LOS) direction, and the event-triggered threshold is given. Then, a predefined-time extended state observer is used to accurately estimate disturbances. In addition, the stability of the proposed guidance laws along and perpendicular to the LOS direction is proven by the Lyapunov theory. Finally, the superiority of the proposed guidance law introducing the event-triggered mechanism in reducing energy consumption and its effectiveness in encountering communication failure and time-delay are verified through simulations.

A global dynamic evolution snow ablation optimizer for unmanned aerial vehicle path planning under space obstacle threat

In this paper, an improved Global Dynamic Evolution Snow Ablation Optimizer (GDSAO) is proposed in order to solve the problem of global optimization and Unmanned Aerial Vehicle (UAV) path planning in 3D space with obstacle threats. Three improvement schemes are proposed in GDSAO: (1) Population initialization is carried out using the theory of the best point set to obtain a more diverse initial population; (2) A dynamic snowmelt ratio using the global evolutionary dispersion is proposed to adapt the exploitation process of the original SAO to the evolutionary process of population fitness; (3) A neighborhood dimensional search scheme is proposed to update the locations of all searched individuals outside the elite pool to obtain better population fitness. The algorithm was tested on 30 10-dimensional problems at CEC 2017 and performed better than a series of joint and leading optimization algorithms. The path planning problem of UAV was solved, and the path satisfying all obstacle avoidance threats and corner constraints was obtained. By comparison, GDSAO is superior to the existing algorithms in terms of reliability and stability of optimization.