Search Results (2,180)

This study has established and resolved a new mathematical model of a homogeneous, generalized, magnetothermoelastic half-space with a thermally loaded bounding surface, subjected to ramp-type heating and supported by a solid foundation where these types of mathematical models have been widely used in many sciences, such as geophysics and aerospace. The governing equations are formulated according to the Green–Lindsay theory of generalized thermoelasticity. This work’s uniqueness lies in the examination of Maxwell’s time-fractional equations via the definition of Caputo’s fractional derivative. The Laplace transform method has been used to obtain the solutions promptly. Inversions of the Laplace transform have been computed via Tzou’s iterative approach. The numerical findings are shown in graphs representing the distributions of the temperature increment, stress, strain, displacement, induced electric field, and induced magnetic field. The time-fractional parameter derived from Maxwell’s equations significantly influences all examined functions; however, it does not impact the temperature increase. The time-fractional parameter of Maxwell’s equations functions as a resistor to material deformation, particle motion, and the resulting magnetic field strength. Conversely, it acts as a catalyst for the stress and electric field intensity inside the material. The strength of the main magnetic field considerably influences the mechanical and electromagnetic functions; however, it has a lesser effect on the thermal function. Full article

Spray dust removal is currently the primary method of dust control technology, while it exhibits low efficacy in dust removal capability. A Phase Doppler Particle Analyzer (PDPA) experimental system was constructed to study the influence of dust suppressants on the coupling behavior of dust–mist particles using comparative methods. According to the experimental results of the atomization effect of the spray, the Sauter Mean Diameter (D32) of the mist size of the dust suppressants showed an increasing trend compared to water. This trend became less obvious with an increase in spray pressure, and a reduction in the surface tension of the dust suppressants promoted an increase in the particle size distribution of water mist. According to the test results of the dust–mist coupling behavior experiment, compared with water, the coupling efficiency of Dodecyl Alcohol (DA), Alkylphenol Polyoxyethylene (OP-10), and Sodium Dodecyl Sulfate (SDS) increased by 27.0%, 20.3%, and 15.0%, respectively. This indicates a proportional relationship between the wetting performance of the dust suppressants and the dust–mist coupling rate and an inverse relationship between the surface tension of the dust suppressant solutions and the dust removal efficiency. The research findings hold major possibilities for enhancing the dust removal efficiency. Full article

This paper proposes a semi-analytical solution for one-dimensional consolidation of viscoelastic unsaturated soil considering a variable permeability coefficient under exponential loading. The governing equations of excess pore air pressure (EPAP) and excess pore water pressure (EPWP) were acquired by introducing the Merchant viscoelastic model. By employing Lee’s correspondence principle and the Laplace transform, the solutions for EPAP and EPWP were derived under the boundary conditions of the permeable top surface and impermeable bottom surface. Crump’s method was then used to execute the inverse Laplace transform, yielding a semi-analytical solution in the time domain. Through typical examples, the dissipation of EPAP and EPWP and the change of the average degree of consolidation over time under the influence of different elastic moduli, viscoelastic coefficients, and air-to-water permeability ratios were studied. The variation of the permeability coefficient and its influence on consolidation were also analyzed. The findings of this research show that the consolidation rate of viscoelastic unsaturated soil is slower than that of elastic unsaturated soil; however, an acceleration in the consolidation of the soil is observed when changes in the permeability coefficient are considered. These discoveries enhance our comprehension of the consolidation behaviors exhibited by viscoelastic unsaturated soil, thereby enriching the knowledge base on its consolidation traits. Full article

This paper is devoted to the study of stochastic optimal control of averaged stochastic differential delay equations (SDDEs) with semi-Markov switchings and their applications in economics. By using the Dynkin formula and solution of the Dirichlet–Poisson problem, the Hamilton–Jacobi–Bellman (HJB) equation and the inverse HJB equation are derived. Applications are given to a new Ramsey stochastic models in economics, namely the averaged Ramsey diffusion model with semi-Markov switchings. A numerical example is presented as well. Full article

Inverse lithography technology (ILT) plays a pivotal role in advanced semiconductor manufacturing because it enables pixel-level mask modifications, significantly enhances pattern fidelity, and expands process windows. However, traditional gradient-based ILT methods often struggle with the trade-off between imaging fidelity and mask manufacturability due to coupled optimization objectives. We propose a frequency-separated dual-stage optimization framework (FD-ILT) that strategically decouples these conflicting objectives by exploiting the inherent low-pass characteristics of lithographic systems. The first stage optimizes low-frequency (LF) components using hierarchical downsampling to generate a high-fidelity continuous transmission mask. This approach reduces computational complexity while refining resolution progressively. The second stage enforces manufacturability by exclusively adjusting high-frequency (HF) features through morphological regularization and progressive binarization penalties while maintaining the mask LF to preserve imaging accuracy. Our method achieves simultaneous control of both aspects by eliminating gradient conflicts between fidelity and manufacturing constraints. The simulation results demonstrate that FD-ILT achieves superior imaging quality and manufacturability compared to conventional gradient-based ILT methods, offering a scalable solution for advanced semiconductor nodes. Full article

This study investigates the hydrothermal gasification (HTG) of apricot tree resin, focusing on the yield and chemical composition of the resulting gas and aqueous phases. K₂CO₃ and KOH were used as catalysts within a temperature range of 300–600 °C, with a constant reaction time of 60 min. The results show that temperature and catalyst choice significantly influence gas yield, liquid composition, and solid residue formation. Higher temperatures increased the gas yield while decreasing aqueous and solid residues. The catalytic effect of K₂CO₃ and KOH enhanced the gaseous product conversion, with KOH achieving the highest gas yield and lowest residue formation at 600 °C. Among the liquid-phase compounds, carboxylic acids and 5-methyl furfural were the most abundant, reaching peak concentrations at 300 °C in the presence of K₂CO₃. The addition of alkali catalysts reduced key acidic intermediates such as glycolic, acetic, and formic acids. The inverse relationship between temperature and liquid/solid product formation underscores the importance of optimizing reaction conditions for efficient biomass conversion. These findings contribute to the growing field of biomass valorization by highlighting the potential of underutilized tree resins in sustainable biofuel production, advancing knowledge in renewable hydrogen production, and supporting the broader development of bio-based energy solutions. Full article

This paper presents an improved coupled radial basis function (ICRBF) approach for solving inverse steady-state heat conduction problems. The proposed method combines infinitely smooth Gaussian radial basis functions with a real-valued mth-order conical spline, where m serves as a coupling index. Unlike the original coupled RBF approach, which relied on multiquadric RBFs paired with a fixed fifth-order spline or later integer-order extensions, our real-order spline generalization enhances accuracy and simplifies the tuning of m. We present a particle swarm optimization approach to optimize the coupling index m. This work represents the first application of the CRBF framework to inverse steady-state heat conduction problems. The ICRBF methodology addresses three key limitations of traditional RBF frameworks: (1) it resolves the persistent issue of shape parameter selection in global RBF methods; (2) it inherently produces well-posed linear systems that can be solved directly, avoiding the need for the regularization typically required in inverse problems; and (3) it delivers superior accuracy compared to existing approaches. Extensive numerical experiments on benchmark problems demonstrate that the proposed method achieves high accuracy and robust numerical stability in solving steady-state heat conduction Cauchy inverse problems, even under significant noise contamination. Full article

Waxy crude oil displays complex rheological behaviors, including viscoelasticity, thixotropy, and yield stress, under the gelling point temperature. To characterize these complex rheological behaviors, numerous models have been proposed, all of which typically involve extensive unknown parameters to be determined. Traditional least squares methods for determining model parameters have problems such as difficulty in determining the initial values for parameter fitting, susceptibility to falling into local optimal solutions, and instability of the fitting results. For this purpose, this paper proposes a parameter inversion method for determining thixotropic model parameters by integrating Adaptive Differential Evolution (ADE) with Bayesian inversion. By leveraging the global search capability of the ADE algorithm and the probabilistic uncertainty quantification advantages of the Bayesian method, the accuracy and stability of model parameter fitting are significantly enhanced. This paper conducted a comparative analysis between the proposed thixotropic model parameter inversion method and traditional methods based on the Houska model, using the thixotropic test data of Daqing and Xianhe waxy crude oil. The results show that the fitting errors of the new method are significantly smaller than those of the least squares method. Furthermore, the new method can invert to obtain superior thixotropic model parameters even under suboptimal initial parameter conditions while maintaining robust optimization capability. The novel method for inverting thixotropic model parameters outperforms the least squares method in terms of algorithm convergence, stability, robustness, and model fitting accuracy, solving the problem of difficult fitting of unknown parameters in thixotropic models. Full article

In addressing the optimal motion planning issue for multi-arm rock drilling robots, this paper introduces a high-precision motion planning method based on Multi-Strategy Sampling RRT* (MSS-RRT*). A dual Jacobi iterative inverse solution method, coupled with a forward kinematics error compensation model, is introduced to dynamically correct target positions, improving end-effector positioning accuracy. A multi-strategy sampling mechanism is constructed by integrating DRL position sphere sampling, spatial random sampling, and goal-oriented sampling. This mechanism flexibly applies three sampling methods at different stages of path planning, significantly improving the adaptability and search efficiency of the RRT* algorithm. In particular, DRL position sphere sampling is prioritized during the initial phase, effectively reducing the number of invalid sampling points. For training a three-arm DRL model with the twin delayed deep deterministic policy gradient algorithm (TD3), the Hindsight Experience Replay-Obstacle Arm Transfer (HER-OAT) method is used for data replay. The cylindrical bounding box method effectively prevents collisions between arms. The experimental results show that the proposed method improves motion planning accuracy by 94.15% compared to a single Jacobi iteration. MSS-RRT* can plan a superior path in a shorter duration, with the planning time under optimal path conditions being only 20.71% of that required by Informed-RRT*, and with the path length reduced by 21.58% compared to Quick-RRT* under the same time constraints. Full article

Photonic integrated interferometric imaging systems (PIISs) provide a compact solution for high-resolution Earth observation missions with stringent size, weight, and power (SWaP) constraints. As an indirect imaging method, a PIIS exhibits fundamentally different noise response characteristics compared to conventional remote sensing systems, and its imaging performance under practical operational scenarios has not been thoroughly investigated. The primary objective of this paper is to evaluate the operational capabilities of PIISs under remote sensing conditions. We (1) establish a signal-to-noise-ratio model for PIISs with balanced four-quadrature detection, (2) analyze the impacts of intensity noise and turbulent phase noise based on radiative transfer and turbulence models, and (3) simulate imaging performance with WorldView-3-like parameters. The results of the visibility signal-to-noise ratio (SNR) analysis demonstrate that the system’s minimum detectable fringe visibility is inversely proportional to the reciprocal of the sub-aperture intensity signal-to-noise ratio. When the integration time reaches 100 ms, the minimum detectable fringe visibility ranges between ${10}^{-2}$ and ${10}^{-3}$ (at 10 dB system efficiency). Imaging simulations demonstrate that recognizable image reconstruction requires integration times exceeding 10 ms for 10 cm baselines, achieving approximately 25 dB PSNR and 0.8 SSIM at 100 ms integration duration. These results may provide references for potential applications of photonic integrated interferometric imaging systems in remote sensing. Full article

This study addresses the urgent need for advanced digitalization tools in air pollution detection, particularly within resource-constrained municipal settings like those in Ukraine, aligning with directives such as the AAQD. The forecasting information system for integrating data processing, analysis, and visualization to improve environmental monitoring practices is described in this article. The system utilizes machine learning models (ARIMA and BATS) for time series forecasting, automatically selecting the optimal model based on accuracy metrics. Spatial analysis employing inverse distance weighting (IDW) provides insights into pollutant distribution, while correlation analysis identifies relationships between pollutants. The system was tested using retrospective data from the Kremenchuk agglomeration (2007–2024), demonstrating its ability to forecast air quality parameters and identify areas exceeding maximum permissible pollutant concentrations. Results indicate that BATS often outperforms ARIMA for several key pollutants, highlighting the importance of automated model selection. The developed system offers a cost-effective solution for local municipalities, enabling data-driven decision-making, optimized monitoring network placement, and improved alignment with European Union environmental standards. Full article

This survey provides a review of the theoretical research on the classic system of matrix equations $AX=C$ and $XB=D$, which has wide-ranging applications across fields such as control theory, optimization, image processing, and robotics. The paper discusses various solution methods for the system, focusing on specialized approaches, including generalized inverse methods, matrix decomposition techniques, and solutions in the forms of Hermitian, extreme rank, reflexive, and conjugate solutions. Additionally, specialized solving methods for specific algebraic structures, such as Hilbert spaces, Hilbert $C^{\ast }$-modules, and quaternions, are presented. The paper explores the existence conditions and explicit expressions for these solutions, along with examples of their application in color images. Full article

This paper presents an obstacle avoidance strategy for mobile manipulators consisting of a robotic arm and a base with a non-holonomic differential wheel system. The algorithm makes it possible to avoid obstacles in a dynamic environment, without planning the path a priori. A series of examples are proposed in simulation using Matlab and analyzed to show how the algorithm works if the obstacle interferes with the manipulator or the base. In addition, the possibility of prioritizing the movement of certain parts of the system using the weighted pseudo-inverse matrix is introduced. In this way, it is possible to give movement priority to the base if it is necessary to move the robot over long distances while keeping the manipulator as still as possible. The use of null space to keep the end-effector stationary while it avoids obstacles is also explored, exploiting the system’s redundancy and allowing the rest of the kinematic chain and the mobile base to move accordingly. Finally, current standards are analyzed and a solution is shown that allows the robot to vary its behavior to avoid obstacles depending on the distance to the target point. Full article

This study proposes a force–position hybrid control method for quadruped robots based on the Model Predictive Control (MPC) algorithm, aiming to address the challenges of stability and adaptability in complex terrain environments. Traditional control methods for quadruped robots are often based on simplified models, neglecting the impact of complex terrains and unstructured environments on control performance. To enhance the real-world performance of quadruped robots, this paper employs the MPC algorithm to integrate force and position control to achieve precise force–position hybrid regulation. By transforming foot-end forces into joint torques and optimizing them using kinematic inverse solutions, the robot’s stability and motion accuracy in challenging terrains is further enhanced. In this study, a Kalman filter-based state estimation method is adopted to estimate the robot’s state in real time, enabling closed-loop control through the MPC framework, combined with kinematic inverse solutions for hybrid control. The experimental results demonstrate that the proposed MPC algorithm significantly improves the robot’s adaptability and control accuracy across various terrains. In particular, it exhibits superior performance and robustness in multi-contact and uneven terrain scenarios. This research provides a novel approach for deploying quadruped robots in dynamic and complex environments and offers strong support for further optimization of motion control strategies. Full article

The aim of this work is to propose an explanation of the inverse mass hierarchy of the low-lying nonet of the scalar mesons in the framework of the massless Nambu–Jona-Lasinio $U_R\left(3\right)\times U_L\left(3\right)$ quark model. The proposed explanation is based on symmetry principles. The collective meson states are described via quark–antiquark pairs, whose condensates lead simultaneously to spontaneous breaking of chiral and flavour symmetry. It is shown that, due to flavour symmetry breaking, two iso-doublets of $K_0^{*}\left(700\right)$ mesons play the role of Goldstone bosons. It is also proven that there exists a solution with degenerate masses of the $a_0\left(980\right)$ and $f_0\left(980\right)$ mesons and a zero mass of the $f_0\left(500\right)$ meson. Full article