Search Results (140)

The rapid accumulation of space debris poses a serious threat to operational spacecraft, with the capture and removal of rapidly tumbling non-cooperative targets being a primary challenge. Non-contact electromagnetic de-tumbling technology is a promising solution due to its enhanced safety. This paper addresses the issue of torque modeling and validation in the electromagnetic de-tumbling process for a specific configuration involving a magnetic dipole and a spherical shell under a symmetrically distributed magnetic field. Based on the principles of electromagnetic induction, an approximate analytical expression for the electromagnetic eddy current torque on a rotating spherical shell within a dipole magnetic field is first derived. A high-fidelity finite element model is then established, which reveals a systematic discrepancy between the initial theoretical model and numerical simulation results. A distance-dependent power-law correction factor is introduced to calibrate the theoretical model, significantly improving its accuracy and reducing the average error to 1.5 percent. Finally, a ground-based experimental platform is designed and implemented. The experimental results demonstrate that the corrected approximate analytical model agrees well with the empirical data, verifying its validity and accuracy under the given conditions and providing a reliable theoretical basis for the design of future space debris de-tumbling controllers. Full article

This study numerically investigates the growth and dynamics of a single vapor bubble in a rectangular microchannel under subcooled and saturated inlet conditions using the phase-field method coupled with the Lee phase-change model. Results demonstrate that subcooled flow induces early bubble nucleation, pronounced lateral expansion along the heated wall, and prolonged bubble-wall contact due to stronger condensation at the interface and thinner microlayer formation. Enhanced recirculating vortices and steeper thermal gradients promote vigorous evaporation and increased local heat flux, resulting in faster downstream bubble propagation driven by significant axial pressure gradients. Analysis of temperature gradient and heat flux profiles confirms that subcooled conditions produce higher wall heat flux and more frequent peaks in evaporative flux compared to the saturated case, indicating intensified phase-change activity and thermal transport. Conversely, saturated conditions produce more spherical bubbles with dominant vertical growth, weaker condensation, and symmetrical thermal and pressure fields, leading to slower growth and delayed detachment near the nucleation site. These findings highlight the critical influence of inlet subcooling on bubble morphology, flow structures, heat transfer, and pressure distribution, underscoring the thermal management advantages of subcooled boiling in microchannel applications. Full article

This study investigates three distinct charged gravastar models within the framework of $f\left(T\right)$ modified gravity, considering the functional forms $f\left(T\right)=T$, $f\left(T\right)=a+bT$, and $f\left(T\right)=T^2$. Inspired by the Mazur–Mottola conjecture, we propose these models as singularity-free alternatives to black holes, each characterized by a three-region structure: (i) an interior de Sitter core, (ii) an intermediate thin shell composed of ultrarelativistic matter, and (iii) an exterior region described by the Reisner Nordstrom solution and other novel spherically symmetric vacuum solutions. We derive a complete set of exact, singularity-free solutions for the charged gravastar configuration, demonstrating their mathematical consistency and physical viability in the context of alternative gravity theories. Notably, the field equations governing the thin shell are solved using an innovative approach based on Killing vector symmetries, eliminating the need for approximations commonly employed in prior studies. Furthermore, we analyze key physical properties of the thin shell, including its proper length, entropy distribution, and energy content. A thorough examination of the energy conditions reveals the thermodynamic stability and viability of these models. Our results contribute to the growing body of work on exotic compact objects and provide new insights into the interplay between modified gravity, electromagnetism, and non-singular black hole alternatives. Full article

With the iterative evolution of SLAM (Simultaneous Localization and Mapping) technology in the robotics domain, the SLAM paradigm based on three-dimensional Gaussian distribution models has emerged as the current state-of-the-art technical approach. This research proposes a novel MSGS-SLAM system (Monocular Semantic Gaussian Splatting SLAM), which innovatively integrates monocular vision with three-dimensional Gaussian distribution models within a semantic SLAM framework. Our approach exploits the inherent spherical symmetries of isotropic Gaussian distributions, enabling symmetric optimization processes that maintain computational efficiency while preserving geometric consistency. Current mainstream three-dimensional Gaussian semantic SLAM systems typically rely on depth sensors for map reconstruction and semantic segmentation, which not only significantly increases hardware costs but also limits the deployment potential of systems in diverse scenarios. To overcome this limitation, this research introduces a depth estimation proxy framework based on Metric3D-V2, which effectively addresses the inherent deficiency of monocular vision systems in depth information acquisition. Additionally, our method leverages architectural symmetries in indoor environments to enhance semantic understanding through symmetric feature matching. Through this approach, the system achieves robust and efficient semantic feature integration and optimization without relying on dedicated depth sensors, thereby substantially reducing the dependency of three-dimensional Gaussian semantic SLAM systems on depth sensors and expanding their application scope. Furthermore, this research proposes a keyframe selection algorithm based on semantic guidance and proxy depth collaborative mechanisms, which effectively suppresses pose drift errors accumulated during long-term system operation, thereby achieving robust global loop closure correction. Through systematic evaluation on multiple standard datasets, MSGS-SLAM achieves comparable technical performance to existing three-dimensional Gaussian model-based semantic SLAM systems across multiple key performance metrics including ATE RMSE, PSNR, and mIoU. Full article

Symmetry plays a key role in the study of stress and strain analysis of spherical tanks, as described in detail in the main text. The inherent geometric symmetry of a spherical tank–being uniform in all directions from its center–allows for significant simplification of finite element models. This radial symmetry means that the stress and strain fields under uniform internal pressure are also symmetrical, reducing the computational domain to a small, representative portion of the tank rather than the entire structure. By using these symmetry principles, the study not only ensures the accuracy of its predictions but also achieves a high degree of computational efficiency, making complex engineering problems easier and more accessible. The application of symmetry, therefore, is not just a theoretical concept but a practical tool that underlies the methodology and success of this analysis. This study investigates the mechanical behavior of a spherical tank subjected to internal fluid pressure, utilizing the finite element method (FEM) as a primary analytical tool. Spherical tanks are widely used for the storage of various fluids, including liquefied natural gas (LNG), compressed gases, and water. Their design is critical to ensure structural integrity and safety. This research aims to provide a comprehensive stress and strain analysis of a typical spherical tank, focusing on the hoop and meridian stresses, and their distribution across the tank’s geometry. A 3D finite element model of a spherical tank will be developed using commercial FEA software. The model will incorporate realistic material properties (e.g., steel alloy) and boundary conditions that simulate the support structure and internal fluid pressure. The analysis will consider both linear elastic and potentially non-linear material responses to explore the tank’s behavior under various operational and overpressure scenarios. The primary objectives of this study are as follows: (1) determine the maximum principal stresses and strains within the tank wall, (2) analyze the stress concentration at critical points, such as support connections and nozzle penetrations, and (3) validate the FEM results against classical analytical solutions for thin-walled spherical pressure vessels. The findings will provide valuable insights into the structural performance of these tanks, highlighting potential areas of concern and offering a robust numerical approach for design optimization and safety assessment. This research demonstrates the power and utility of FEM in engineering design, offering a more detailed and accurate analysis than traditional analytical methods. Full article

This study proposes a couple of analytical solutions that characterize the anisotropic dense celestial bodies within the Rastall-Rainbow theoretical framework. The analysis assumes a static spherically symmetric matter distribution and derives the corresponding modified field equations. By utilizing well-established radial metric functions and merging them with the two principal pressures, we obtain differential equations related to the time component. Subsequently, we perform the integration of these equations to determine the remaining geometric quantity that encompasses various integration constants. The proposed interior solutions are then matched with the Schwarzschild exterior metric at the boundary of the compact object, facilitating the determination of the constants. Additionally, the incorporation of the non-minimal coupling parameter into these constants is accomplished by enforcing the null radial pressure at the boundary. Afterwards, we rigorously examine the physical characteristics and critical stability conditions of the formulated models under observational data from two pulsars, say 4U 1820-30 and LMC X-4. It is concluded that our models are well-aligned with essential criteria required to ensure the physical viability of stellar structures, subject to specific parametric values. Full article

In this work, we explore a class of spherically symmetric black hole (BH) solutions within the framework of modified gravity, focusing on a non-ghost-free $f(R,G)$ theory coupled to a scalar field. We present a novel black hole geometry that arises as a deformation of the Schwarzschild solution and analyze its physical and thermodynamic properties. Our results show that the model satisfies stability conditions, with the Ricci scalar R, as well as its first and second derivatives, remaining positive throughout the spacetime. The solution admits multiple horizons and exhibits strong curvature singularities compared to those in general relativity. Furthermore, it supports a non-trivial scalar field potential. A comprehensive thermodynamic analysis is performed, including evaluations of the entropy, temperature, heat capacity, and quasi-local energy. We find that the black hole exhibits thermodynamic stability within certain ranges of model parameters. In addition, we investigate geodesic deviation and derive the conditions necessary for stability within the $f(R,G)$ gravitational framework. Full article

We describe some properties of the hyperbolically symmetric black hole (hereafter referred to as the $HSBH$) proposed a few years ago. We start by explaining the main motivation behind such an idea, and we determine the main differences between this scenario and the classical black hole (hereafter referred to as the $CBH$) scenario. Particularly important are the facts that, in the $HSBH$ scenario, (i) test particles in the region inside the horizon experience a repulsive force that prevents them from reaching the center, (ii) test particles may cross the horizon outward only along the symmetry axis, and (iii) the spacetime within the horizon is static but not spherically symmetric. Next, we examine the differences between the two models of black holes in light of the Landauer principle and the Hawking results on the eventual evaporation of the black hole and the paradox resulting thereof. Finally, we explore what observational signature could be invoked to confirm or dismiss the model. Full article

This work presents a semi-classical, quantum-corrected model of gravitational collapse for a charged, spherically symmetric dust cloud, extending the classical Oppenheimer–Snyder (OS) framework through loop quantum gravity effects. Our goal is to study phenomenological quantum modifications to geometry, without necessarily embedding them within full loop quantum gravity (LQG). Building upon the quantum Oppenheimer–Snyder (qOS) model, which replaces the classical singularity with a nonsingular bounce via a modified Friedmann equation, we introduce electric and magnetic charges concentrated on a massive thin shell at the boundary of the dust ball. The resulting exterior spacetime generalizes the Schwarzschild solution to a charged, regular black hole geometry akin to a quantum-corrected Reissner–Nordström metric. The Israel junction conditions are applied to match the interior APS (Ashtekar–Pawlowski–Singh) cosmological solution to the charged exterior, yielding constraints on the shell’s mass, pressure, and energy. Stability conditions are derived, including a minimum radius preventing full collapse and ensuring positivity of energy density. This study also examines the geodesic structure around the black hole, focusing on null circular orbits and effective potentials, with implications for the observational signatures of such quantum-corrected compact objects. Full article

A model for the flow and thermal explosion of a micropolar gas is investigated, assuming the equation of state for a real gas. This model describes the dynamics of a gas mixture (fuel and oxidant) undergoing a one-step irreversible chemical reaction. The real gas model is particularly suitable in this context because it more accurately reflects reality under extreme conditions, such as high temperatures and high pressures. Micropolarity introduces local rotational dynamic effects of particles dispersed within the gas mixture. In this paper, we first derive the initial-boundary value system of partial differential equations (PDEs) under the assumption of spherical symmetry and homogeneous boundary conditions. We explain the underlying physical relationships and then construct a corresponding approximate system of ordinary differential equations (ODEs) using the Faedo–Galerkin projection. The existence of solutions for the full PDE model is established by analyzing the limit of the solutions of the ODE system using a priori estimates and compactness theory. Additionally, we propose a numerical scheme for the problem based on the same approximate system. Finally, numerical simulations are performed and discussed in both physical and mathematical contexts. Full article

Alternative fuels obtained from renewable sources, providing low greenhouse gas emissions and high energy efficiency, offer significant advantages in terms of sustainability. In addition, the wide applicability of these fuel types in sectors such as housing, transportation, and industry creates significant opportunities in terms of reducing dependence on fossil fuels. Alternative fuels should be evaluated not only according to their environmental contributions but also based on multi-dimensional criteria such as economic cost, technical suitability, sustainability level, fuel properties, infrastructure requirements, and social acceptance. In this context, a comparative analysis of alternative fuel types in terms of various basic parameters is no longer optional, but a necessity. These parameters generally include symmetrical relationships such as balanced trade-offs between economic and environmental dimensions or mutual effects between technical and social criteria. However, they also show variability and uncertainty depending on the fuel type. Therefore, Spherical Fuzzy Multi-Criteria Decision Making (SF-MCDM) methods, which can effectively represent symmetry in membership and hesitation degrees, have been used to achieve more realistic and reliable results in uncertain decision environments. The proposed model provides a systematic and flexible evaluation structure that helps decision makers determine the most appropriate alternative fuel options and contributes to the formation of sustainable energy policies. Full article

Previous investigations devoted to non-spherical nanoparticles for biosensing have primarily addressed two hot topics, namely, finding nanoparticles with the best shape for refractive index sensing properties and the optimization of size parameters. In this study, based on these hot topics, Au-Ag alloy nanoparticles with excellent optical properties were selected as the research object. Targeting rotationally symmetric Au-Ag alloy nanoparticles for biosensing applications, the complex media function correction model and T-matrix approach were used to systematically analyze the variation patterns of extinction properties, refractive index sensitivity, full width at half maximum, and figure of merit of three rotationally symmetric Au-Ag alloy nanoparticles with respect to the size of the particles and the Au molar fraction. In addition, we optimized the figure of merit to obtain the best size parameters and Au molar fractions for the three rotationally symmetric Au-Ag alloy nanoparticles. Finally, the range of dimensional parameters corresponding to a figure of merit greater than 98% of its maximum value was calculated. The results show that the optimized Au-Ag alloy nanorods exhibit a refractive index sensitivity of 395.2 nm/RIU, a figure of merit of 7.16, and a wide range of size parameters. Therefore, the optimized Au-Ag alloy nanorods can be used as high-performance biosensors. Furthermore, this study provides theoretical guidance for the application and preparation of rotationally symmetric Au-Ag alloy nanoparticles in biosensing. Full article

This research introduces an innovative probabilistic method for examining torsional stress behavior in spherical shell structures through Monte Carlo simulation techniques. The spherical geometry of these components creates distinctive computational difficulties for conventional analytical and deterministic numerical approaches when solving torsion-related problems. The authors develop a comprehensive mesh-free Monte Carlo framework built upon the Feynman–Kac formula, which maintains the geometric symmetry of the domain while offering a probabilistic solution representation via stochastic processes on spherical surfaces. The technique models Brownian motion paths on spherical surfaces using the Euler–Maruyama numerical scheme, converting the Saint-Venant torsion equation into a problem of stochastic integration. The computational implementation utilizes the Fibonacci sphere technique for achieving uniform point placement, employs adaptive time-stepping strategies to address pole singularities, and incorporates efficient algorithms for boundary identification. This symmetry-maintaining approach circumvents the mesh generation complications inherent in finite element and finite difference techniques, which typically compromise the problem’s natural symmetry, while delivering comparable precision. Performance evaluations reveal nearly linear parallel computational scaling across up to eight processing cores with efficiency rates above 70%, making the method well-suited for multi-core computational platforms. The approach demonstrates particular effectiveness in analyzing torsional stress patterns in thin-walled spherical components under both symmetric and asymmetric boundary scenarios, where traditional grid-based methods encounter discretization and convergence difficulties. The findings offer valuable practical recommendations for material specification and structural design enhancement, especially relevant for pressure vessel and dome structure applications experiencing torsional loads. However, the probabilistic characteristics of the method create statistical uncertainty that requires cautious result interpretation, and computational expenses may surpass those of deterministic approaches for less complex geometries. Engineering analysis of the outcomes provides actionable recommendations for optimizing material utilization and maintaining structural reliability under torsional loading conditions. Full article

Numerical simulation has become a pivotal tool for analyzing airflow dynamics and temperature patterns during the precooling of postharvest horticultural products stacked in vented package. In this study, a three-dimensional mathematical model for iceberg lettuces stacked symmetrically in plastic crate was developed. The influence of the physical model at different gap sizes on the simulation accuracy was studied by assessing wall drag coefficient, airflow distribution, and heat transfer efficiency. The results show a reasonable decrease in the drag coefficient with an increasing gap size to 6 mm in terms of airflow distribution inside the plastic crate; any further increase in gap size and the average airflow velocity in both windward and leeward sides decreases rapidly. Interestingly, the gap size exhibited a limited impact on heat transfer characteristics during the cooling process. Thus, 6 mm was found to be the optimal distance to ensure good accuracy in simulation results and reduce the complexity of grid division. The numerical model was verified by experimental data. Moreover, the validation confirms good consistency between the simulated predictions and experimental measurements. This study provides a theoretical basis for establishing a reliable numerical model for the precooling of agricultural produce stacked symmetrically in a vented package. Full article

An accurate 3D pose estimation of spherical objects remains challenging in industrial inspections and robotics due to their geometric symmetries and limited feature discriminability. This study proposes a texture-optimized simulation framework to enhance pose prediction accuracy through optimizing the surface texture features of the design samples. A hierarchical texture design strategy was developed, incorporating complexity gradients (low to high) and color contrast principles, and implemented via VTK-based 3D modeling with automated Euler angle annotations. The framework generated 2297 synthetic images across six texture variants, which were used to train a MobileNet model. The validation tests demonstrated that the high-complexity color textures achieved superior performance, reducing the mean absolute pose error by 64.8% compared to the low-complexity designs. While color improved the validation accuracy universally, the test set analyses revealed its dual role: complex textures leveraged chromatic contrast for robustness, whereas simple textures suffered color-induced noise (a 35.5% error increase). These findings establish texture complexity and color complementarity as critical design criteria for synthetic datasets, offering a scalable solution for vision-based pose estimation. Physical experiments confirmed the practical feasibility, yielding 2.7–3.3° mean errors. This work bridges the simulation-to-reality gaps in symmetric object localization, with implications for robotic manipulation and industrial metrology, while highlighting the need for material-aware texture adaptations in future research. Full article