Search Results (82)

This paper proposes a finite-time adaptive observer with online disturbance learning for time-varying disturbed systems. By integrating parameter-dependent Lyapunov functions and slack matrix techniques, the method eliminates conservative static disturbance bounds required in prior work while guaranteeing fixed-time convergence. The proposed approach features a non-diagonal gain structure that provides superior noise rejection capabilities, demonstrating 41% better performance under measurement noise compared to conventional methods. A power systems case study demonstrates significantly improved performance, including 62% faster convergence and 63% lower steady-state error. These results are validated through LMI-based synthesis and adaptive disturbance estimation. Implementation analysis confirms the method’s feasibility for real-time systems with practical computational requirements. Full article

A versatile, clear, and accurate method for determining the steady states of multi-component diffusion through composite membranes is presented in this study. This method can be used for simulating and designing membranes with any support orientation with respect to the zeolite film. In the mathematical model of the membrane, it was assumed that mass transport in the zeolite layer occurs by surface diffusion in accordance with the generalized Maxwell–Stefan model. Diffusion in the macroporous support was described by the dusty gas model (DGM). An alternative model of diffusion in the zeolite was proposed to the universally accepted model, which uses a matrix of thermodynamic factors Γ. Thus, the difficulty of analytically determining this matrix for more complex adsorption equilibria was eliminated. This article is dedicated to methodological and cognitive aspects. The practical features of the method are illustrated using two gas mixtures as examples, namely {H₂, CO₂} and {H₂, n-C₄H₁₀}. The roles of zeolite and support in the separation of these mixtures are discussed. It was demonstrated under what circumstances the presence of the support can be neglected in the steady-state analysis of the membrane. The effect of the alternative application of the dusty gas model or viscous flow only in the microporous support was discussed. Full article

This research advances steady state analysis and cost optimization of the M/M/1/N single vacation queueing system with setup time, working vacation, and working breakdown. The server works at a lower service rate instead of stopping work completely during both the vacation period and breakdown period—a key distinction from traditional vacation and breakdown strategies, where the server typically halts operations entirely. The setup time exists between the idle period and the regular busy period. The finite quasi birth-and-death process of this queueing system model is established. The stationary probability vector of the system is calculated using the matrix geometric method. Performance measures, such as output variance, availability, throughput rate, and stationary probabilities, are obtained using the theory of the fundamental matrix and covariance matrix. A cost optimization model based on system performance measures is established. The sparrow search algorithm is adopted to solve the cost optimization model. Through numerical experiments, the influences of system parameters on system performance measures and cost optimization function are analyzed, and the efficiency of the sparrow search algorithm for solving the cost optimization model is verified. The experimental results affirm the effectiveness and practicability of the proposed method, which provides a better theoretical basis for the practical application of the queueing system in communication engineering and production systems. Full article

Consider a class of coupled discrete-time Riccati equations arising from jump systems. To compute their solutions when systems reach a steady state, we propose an operator Newton method and correspondingly establish its quadratic convergence under suitable assumptions. The advantage of the proposed method lies in the fact that its subproblems are solved using the operator Smith method, which allows it to maintain quadratic convergence in both the inner and outer iterations. Moreover, it does not require the constant term matrix of the equation to be invertible, making it more broadly applicable than existing inverse-free iterative methods. For large-scale problems, we develop a low-rank variant by incorporating truncation and compression techniques into the operator Newton framework. A complexity analysis is also provided to assess its scalability. Numerical experiments demonstrate that the presented low-rank operator Newton method is highly effective in approximating solutions to large-scale structured coupled Riccati equations. Full article

In recent years, global agriculture has encountered several challenges exacerbated by the effects of changes in climate, such as extreme water shortages for irrigation and heat waves. Water-deficit stress adversely affects the morpho-physiology of numerous crops, including soybean (Glycine max L.), which is considered as promising crop in Bangladesh. Seaweed extract (SWE) has the potential to improve crop yield and alleviate the adverse effects of water-deficit stress. Remote and proximal sensing are also extensively utilized in estimating morpho-physiological traits owing to their cost-efficiency and non-destructive characteristics. The study was carried out to evaluate soybean morpho-physiological traits under the application of water extracts of Gracilaria tenuistipitata var. liui (red seaweed) with two varying irrigation water conditions (100% of total crop water requirement (TCWR) and 70% of TCWR). Principal component analysis (PCA) revealed that among the four treatments, the 70% irrigation + 5% (v/v) SWE and the 100% irrigation treatments overlapped, indicating that the application of SWE effectively mitigated water-deficit stress in soybeans. This result demonstrates that the foliar application of 5% SWE enabled soybeans to achieve morpho-physiological performance comparable to that of fully irrigated plants while reducing irrigation water use by 30%. Based on Pearson’s correlation matrix, a simple linear regression model was used to ascertain the relationship between unmanned aerial vehicle (UAV)-derived vegetation indices and the field-measured physiological characteristics of soybean. The Normalized Difference Red Edge (NDRE) strongly correlated with stomatal conductance (R² = 0.76), photosystem II efficiency (R² = 0.78), maximum fluorescence (R² = 0.64), and apparent transpiration rate (R² = 0.69). The Soil Adjusted Vegetation Index (SAVI) had the highest correlation with leaf relative water content (R² = 0.87), the Blue Normalized Difference Vegetation Index (bNDVI) with steady-state fluorescence (R² = 0.56) and vapor pressure deficit (R² = 0.74), and the Green Normalized Difference Vegetation Index (gNDVI) with chlorophyll content (R² = 0.73). Our results demonstrate how UAV and physiological data can be integrated to improve precision soybean farming and support sustainable soybean production under water-deficit stress. Full article

Failures in gas path components pose significant risks to aeroengine performance and safety. Traditional fault diagnosis methods often require extensive data and struggle with real-time applications. This study addresses these critical limitations in traditional studies through physics-informed modeling and adaptive estimation. A nonlinear component-level model of the JT9D engine is developed through aero-thermodynamic governing equations, enhanced by a dual-loop iterative cycle combining Newton–Raphson steady-state resolution with integration-based dynamic convergence. An augmented state-space model that linearizes nonlinear dynamic models while incorporating gas path health characteristics as control inputs is novelly proposed, supported by similarity-criterion normalization to mitigate matrix ill-conditioning. A hybrid identification algorithm is proposed, synergizing partial derivative analysis with least squares fitting, which uniquely combines non-iterative perturbation advantages with high-precision least squares. This paper proposes a novel enhanced Kalman filter through integral compensation and three-dimensional interpolation, enabling real-time parameter updates across flight envelopes. The experimental results demonstrate a 0.714–2.953% RMSE in fault diagnosis performance, a 3.619% accuracy enhancement over traditional sliding mode observer algorithms, and 2.11 s reduction in settling time, eliminating noise accumulation. The model maintains dynamic trend consistency and steady-state accuracy with errors of 0.482–0.039%. This work shows marked improvements in temporal resolution, diagnostic accuracy, and flight envelope adaptability compared to conventional approaches. Full article

The contact process is a nonequilibrium Hamiltonian model that, even in one dimension, lacks an exact solution and has been extensively studied via Monte Carlo simulations, both in steady-state and time-dependent scenarios. Although the effects of particle mobility and diffusion on criticality have been preliminarily explored, they remain poorly understood in many aspects. In this work, we examine how the critical rate of the model varies with the probability of particle mobility. By analyzing different stochastic evolutions of the system, we employ two modern approaches: (1) Random Matrix Theory (RMT): By building on the success of RMT, particularly Wishart-like matrices, in studying statistical physics of systems with up-down symmetry via magnetization dynamics [R. da Silva, IJMPC 2022], we demonstrate its applicability to models with an absorbing state; (2) Optimized Temporal Power Laws: By using short-time dynamics, we optimize power laws derived from ensemble-averaged evolutions of the system. Both methods consistently reveal that the critical rate decays with mobility according to a simple Belehradek function. Additionally, a straightforward mean-field analysis supports the decay of the critical parameter with mobility, although it predicts a simpler linear dependence. We also demonstrate that the more sophisticated pair approximation mean-field model developed by ben-Avraham and Köhler aligns closely with the Belehradek function, precisely matching our lattice simulation results. Full article

This study investigates the effects of a vibration force field on the mixing and structural properties of polylactic acid (PLA), polybutylene succinate (PBS), and ethylene–glycidyl methacrylate terpolymer (EGMA) blends. A balanced triple-screw dynamic extrusion process was utilized to prepare PLA/PBS/EGMA composites under various vibration parameters, specifically amplitude and frequency. The results indicate that the introduction of a vibration force field significantly enhances the dispersion of the PLA/PBS/EGMA blend, leading to improved mechanical properties, thermal stability, and crystallization behavior. When the vibration frequency was 6 Hz and the amplitude was 1.0 mm, the impact strength increased from the steady-state value of 70.86 KJ/m² to 88.21 KJ/m². When the amplitude was 0.4 mm and the frequency was 10 Hz, the impact strength reached 81.86 KJ/m². The orthogonal experimental design and entropy method analysis revealed that vibration frequency and amplitude play a dominant role in optimizing mechanical performance, whereas processing temperature and rotor speed exhibit minimal impact. Scanning electron microscopy (SEM) analysis confirmed that the vibration force field reduces phase separation, promoting a finer and more homogeneous dispersion of PBS and EGMA within the PLA matrix. Additionally, TGA and DTG curves suggest that when the vibration amplitude and frequency are lower than specific thresholds, the thermal stability of the blend deteriorates. In contrast, when they exceed those thresholds, thermal stability improves. For instance, with an amplitude of 1.0 mm, the initial degradation temperature (T5) climbs from 328.6 °C to 333.7 °C. At a frequency of 10 Hz, T5 reaches 333.1 °C. These findings provide theoretical support for the application of vibration-assisted extrusion in the development of high-performance biodegradable polymer blends. Full article

New quality productive forces serve as a catalyst for high-quality development and act as a critical driver of Chinese-style modernization. This study evaluated the degree of new quality productive force in China’s five major urban agglomerations between 2013 and 2022 using the entropy approach. Additionally, it utilized kernel density estimation, the Dagum Gini coefficient, and Markov chain analysis to explore the spatial and temporal dynamics of these forces and their evolutionary trends. The findings revealed the following: (1) Overall, the new quality productive forces in China’s five major urban agglomerations have exhibited a steady upward trend, although the overall level remains relatively low. Among these regions, the Pearl River Delta ranks the highest, followed by the Yangtze River Delta, Beijing–Tianjin–Hebei, Chengdu–Chongqing, and the Urban Cluster in the Middle Reaches of the Yangtze River. Nevertheless, significant potential for improvement persists. (2) The traditional Markov probability transfer matrix suggests that the new quality productive forces in these urban agglomerations are relatively stable, with evidence of “club convergence”. Meanwhile, the spatial Markov transfer probability matrix indicates that transfer probabilities are influenced by neighborhood contexts. (3) Over time, the new quality productive forces in Chinese urban agglomerations show a tendency to concentrate at higher levels, reflecting gradual improvement. The developmental state and evolutionary patterns of new quality productive forces in Chinese urban agglomerations are thoroughly evaluated in this paper, along with advice for accelerating their growth to promote Chinese-style modernization. Full article

This study proposes a design procedure for the multi-objective aeroelastic optimization of a tow-steered composite wing structure that operates at transonic speed. The aerodynamic influence coefficient matrix is generated using the doublet lattice method, with the steady-state component further refined through high-fidelity computational fluid dynamics (CFD) analysis to enhance accuracy in transonic conditions. Finite element analysis (FEA) is used to perform structural analysis. A multi-objective transonic aeroelastic optimization problem is formulated for the tow-steered composite wing structure, where the objective functions are designed for mass and critical speed, and the design constraints include structural and aeroelastic limits. A comparative analysis of eight state-of-the-art algorithms is conducted to evaluate their performance in solving this problem. Among them, the Multi-Objective Multi-Verse Optimization (MOMVO) algorithm stands out, demonstrating superior performance and achieving the best results in the aeroelastic optimization task. Full article

This paper presents a data-driven kinematic model for the end-effector pose control applied to a variety of manipulator robots, focusing on the entire end-effector’s pose (position and orientation). The measured signals of the full pose and their computed derivatives, along with a linear combination of an estimated Jacobian matrix and a vector of joint velocities, generate a model estimation error. The Jacobian matrix is estimated using the Pseudo Jacobian Matrix (PJM) algorithm, which requires tuning only the step and weight parameters that scale the convergence of the model estimation error. The proposed control law is derived in two stages: the first one is part of an objective function minimization, and the second one is a constraint in a quasi-Lagrangian function. The control design parameters guarantee the control error convergence in a closed-loop configuration with adaptive behavior in terms of the dynamics of the estimated Jacobian matrix. The novelty of the approach lies in its ability to achieve superior tracking performance across different manipulator robots, validated through simulations. Quantitative results show that, compared to a classical inverse-kinematics approach, the proposed method achieves rapid convergence of performance indices (e.g., Root Mean Square Error (RMSE) reduced to near-zero in two cycles vs. a steady-state RMSE of 20 in the classical approach). Additionally, the proposed method minimizes joint drift, maintaining an RMSE of approximately 0.3 compared to 1.5 under the classical scheme. The control was validated by means of simulations featuring an UR5e manipulator with six Degrees of Freedom (DOF), a KUKA Youbot with eight DOF, and a KUKA Youbot Dual with thirteen DOF. The stability analysis of the closed-loop controller is demonstrated by means of the Lyapunov stability conditions. Full article

The transport of fission products in molten salt reactors has attracted much attention. However, few codes can completely describe the transport characteristic, though the migration of fission products in the molten salt reactor is essential to estimate the source term, decay heat, and radiation shielding. This study built a program named ThorFPMC (Thorium Fission Products Migration Code) that can handle the multi-physics transport characteristic based on the flow burnup code ThorMODEc (Thorium MOlten Salt Reactor Specific DEpletion Code). A problem-related depletion chain compression method was applied to decrease the order of the solve matrix. The matrix exponential and splitting methods were applied to solve the steady state and transient calculation, respectively. Error analysis showed that for a specific problem, the simplified depletion chain matrix index method could solve the fission products migration equation with an arbitrary time-step with high speed (s) and high precision (10⁻⁴); the splitting method could reach a precision of 10⁻² level for the full fuel depletion chain, multi-nodes, and transient problems. Compared to the Strang splitting method, the perturbation splitting method has higher precision and less time consumption. In summary, the developed programmer could describe the migration effect of fission products in molten salt reactors, which provides a significant tool for the design of molten salt reactors. Full article

To study the nonlinear dynamic behavior and system stability of a rubbing overhung rotor with viscoelastic and memory-effect damping and random uncertain parameters, this paper introduces a fractional-order modeling and stochastic dynamic analysis method for the nonlinear overhung rotor system with frictional impact faults. Firstly, the dynamic equations of the overhung rotor considering friction effect and fractional damping effect are established based on the transfer matrix method and fractional order derivative. Then, the time-domain response of the fractional-order dynamic equations is solved by combining the Runge–Kutta method and the continuous fractional expansion, and the steady-state response characteristics of different fractional damping are analyzed in the deterministic case. Finally, to analyze the response of the system under the effect of stochastic parameters, the sparse grid-based PCE metamodel of the system response is developed. Statistical moments, probability distributions, and sensitivity indices of the response of stochastic systems are revealed. The results of this paper provide a theoretical basis for efficient and accurate prediction of the stochastic response of nonlinear rubbing overhung rotor systems. Full article

Interdependent criteria play a crucial role in complex decision-making across various domains. Traditional methods often struggle to evaluate and prioritize criteria with intricate dependencies. This paper introduces a generalized method integrating the analytic network process (ANP), the decision-making trial and evaluation laboratory (DEMATEL), and the consistent fuzzy analytic hierarchy process (CFAHP) in a fuzzy environment. The Drazin inverse technique is applied to derive a fuzzy total priority matrix, and we normalize the row sum to achieve the steady-state fuzzy priorities. A numerical example in the information systems (IS) industry demonstrates the approach’s real-world applications. The proposed method derives narrower fuzzy spreads compared to the past fuzzy analytic network process (FANP) approaches, minimizing objective uncertainty. Total priority interdependent maps provide insights into complex technical and usability criteria relationships. Comparative analysis highlights innovations, including non-iterative convergence of the total priority matrix and the ability to understand interdependencies between criteria. The integration of the FANP’s network structure with the fuzzy DEMATEL’s influence analysis transcends the capabilities of either method in isolation, marking a significant methodological advancement. By addressing challenges such as parameter selection and mathematical complexity, this research offers new perspectives for future research and application in multi-attribute decision-making (MADM). Full article

Additive manufacturing (AM) is an advanced manufacturing method that produces objects by sequential layering. Material extrusion AM (MEAM) with continuous-fibre reinforcement is becoming more widely used in naval structures, which are exposed to the marine environment. However, the water diffusion process and the effect of water ageing on the mechanical performance of AM materials are not yet well understood because of their complex internal structure, caused by defects generated during manufacturing. Current research on diffusion is mostly based on experimental methods for conventionally manufactured materials without considering AM-induced defects. The objective of this study is to explore how the defects inherent to MEAM affect water diffusion in a composite material by the capillary effect. Results from a numerical study of capillary flow in MEAM polymer are applied as a boundary condition in the subsequent finite-element analysis. The study illustrates that flow in the capillary reaches the steady state quicker compared to the saturation time in the matrix, predicted by Fick’s diffusion equation. It is demonstrated that the capillary effect can significantly affect the water diffusion in MEAM parts and reduce the saturation time to one-third compared to the case without accounting for this effect. Full article