Search Results (6,465)

In this study, a three-dimensional nonlinear finite element (FE) model was developed using Abaqus/Explicit to simulate the effects of internal blasts. The numerical model was validated against two previously published numerical and experimental works, demonstrating strong agreement in deformation results. A parametric study was carried out to evaluate the influence of several key factors on the deformation of the receiver tunnel subjected to an explosion in the adjacent donor tunnel. The investigation considered critical variables such as lining material, tunnel inner diameter, cross-sectional shape, spacing between tunnels, and TNT charge weight. The results clearly indicate that expanded polystyrene (EPS) foam, across various densities, demonstrates superior capacity for absorbing blast waves compared to polyurethane and aluminum foams. Furthermore, it was found that lower-density EPS foam provides enhanced mitigation of deformation in tunnel linings. The findings also revealed that damage to the tunnel walls is more strongly correlated with the tunnel shape where the circular tunnel exhibited the best performance. It showed the lowest deformation and delayed peak response. In addition, tunnel deformation increases markedly with higher TNT charge weights. A blast of 1814 kg produced approximately five times the deformation compared to a 454 kg charge. Moreover, it is seen that increasing the spacing between donor and receiver tunnels from 1.5 D to 2.5 D led to a 38.7% reduction in maximum deformation. Full article

Global environmental changes significantly alter ecosystem services (ESs), particularly in fragile regions like the Tibetan Plateau. While methodological advances have improved spatial assessment capabilities, understanding of how multiple drivers interact to shape ecosystem service heterogeneity remains limited to regional scales, especially across complex alpine landscapes. This study aims to clarify whether multi-factor interactions produce nonlinear enhancements in ES explanatory power and how these driver–response relationships vary across heterogeneous terrains. We quantified spatiotemporal patterns of four key ecosystem services—water yield (WY), soil conservation (SC), carbon sequestration (CS), and habitat quality (HQ)—across the southeastern Tibetan Plateau from 2000 to 2020 using multi-source remote sensing data and spatial econometric modeling. Our analysis reveals that SC increased by 0.43 t·hm⁻²·yr⁻¹, CS rose by 1.67 g·m⁻²·yr⁻¹, and HQ improved by 0.09 over this period, while WY decreased by 3.70 mm·yr⁻¹. ES variations are predominantly shaped by potent synergies, where interactive explanatory power consistently surpasses individual drivers. Hydrothermal coupling (precipitation ∩ potential evapotranspiration) reached 0.52 for WY and SC, while climate–vegetation synergy (precipitation ∩ normalized difference vegetation index) achieved 0.76 for CS. Such climate–restoration synergies now fundamentally shape the region’s ESs. Geographically weighted regression (GWR) further revealed distinct spatial dependencies, with southeastern regions experiencing strong negative effects of land use type and elevation on WY, while northwestern areas showed a positive elevation associated with WY but negative effects on SC and HQ. These findings highlight the critical importance of accounting for spatial non-stationarity in driver–ecosystem service relationships when designing conservation strategies for vulnerable alpine ecosystems. Full article

This study evaluates the performance of single concrete-filled frictional Fibre-Reinforced Polymer (FRP) piles embedded in saturated liquefiable sand and subjected to seismic loading using a shaking table. A unidirectional shaking table equipped with a 1000 mm × 1000 mm × 1000 mm laminar shear box with 27 lamina rings was utilized in the study. FRP tubes manufactured from epoxy-saturated Carbon Fibre-Reinforced Polymer (CFRP) and Glass Fibre-Reinforced Polymer (GFRP) fabrics were filled with 35 MPa concrete and allowed to cure for 28 days, serving as model piles for the experimental programme, with cylindrical concrete prisms employed to represent the behaviour of traditional piles. Pile dimensions and properties based on scaling relationships were selected to account for the nonlinear nature of soil–pile systems under seismic loading. Scaled versions of ground motions from the 2010 Val-des-Bois and 1995 Hyogo-Ken Nambu earthquakes were implemented as input motions in the tests. The results show limited variation in the inertial and kinematic responses of the piles, especially before liquefaction. Head rocking displacements were within 5% of each other during liquefaction. Post liquefaction, the concrete-filled FRP piles showed lower response compared to the traditional concrete pile. The results suggests that concrete-filled FRP piles, especially those made from carbon fibre, provide practical alternatives for use. Full article

Advances in CMOS image sensors (CISs) have led to utilization in various industrial fields, including machine vision, medical, surveillance, the automotive industry, and the Internet of Things (IoT). One critical metric for CISs is the dynamic range (DR), which indicates the range of light intensity that can clearly capture images. As the technology evolves, wide dynamic range (WDR) becomes increasingly required for more diverse applications. To further advance these industries, this paper presents the active-pixel-type CIS design techniques and architectures developed to achieve WDR. These include the following: the basic concepts of the active pixel sensor, readout mechanism, and DR of the CIS; multiple exposure and dual conversion gain (DCG) schemes that are conventionally used to address a trade-off in the CIS; lateral overflow integration capacitor (LOFIC) and dual photodiode (PD) architectures that can improve the DR by utilizing trade-offs in the DR and exposure mechanism; CISs with logarithmic and linear–logarithmic (Lin-Log) responses to enable non-linear characteristics; and techniques that can be employed for higher sensitivity in dark conditions. This comprehensive study of various techniques and architectures can also be utilized for cutting-edge tech advances and future research, including neuromorphic array architecture. Full article

Permanent magnet synchronous motors (PMSMs) are widely preferred in modern applications due to their high efficiency, high torque-to-inertia ratio, high power factor, and rapid dynamic response. Achieving optimal PMSM performance requires precise control, which depends on accurate estimation of motor speed and rotor position. This information is traditionally obtained through sensors such as encoders; however, these devices increase system cost and introduce size and integration constraints, limiting their use in many PMSM-based applications. To overcome these limitations, sensorless control strategies have gained significant attention. Since PMSMs inherently exhibit nonlinear dynamic behavior, accurate modeling of these nonlinearities is essential for reliable sensorless operation. In this study, a Runge–Kutta Extended Kalman Filter (RKEKF) approach is developed and implemented to enhance estimation accuracy for both rotor position and speed. The developed method utilizes the applied stator voltages and measured phase currents to estimate the motor states. Experimental validation was conducted on the dSPACE DS1104 platform under various operating conditions, including forward and reverse rotation, acceleration, low- and high-speed operation, and loaded operation. Furthermore, the performance of the developed RKEKF under load was compared with the conventional Extended Kalman Filter (EKF), demonstrating its improved estimation capability. The real-time feasibility of the developed RKEKF was experimentally verified through execution-time measurements on the dSPACE DS1104 platform, where the conventional EKF and the RKEKF required 47 µs and 55 µs, respectively, confirming that the proposed approach remains suitable for real-time PMSM control while accommodating the additional computational effort associated with Runge–Kutta integration. Full article

Due to the complexity of aerodynamic coupling between the duct and propeller, the overall design and optimization of ducted fans often require extensive experience and time. Meanwhile, traditional design methods based on Blade Element Momentum Theory, Lifting Surface Theory, Vortex Lattice Methods, and Panel Method usually exhibit certain deviations between their design results and actual outcomes. This is because these approaches struggle to accurately calculate the aerodynamic coupling effects between the duct and propeller, coupled with numerous simplifications inherent in the methods themselves. Considering the strong nonlinear coupling relationship between the duct and propeller, the Response Surface Method (RSM), which enables efficient and accurate analysis of multi-variable coupling effects, was selected for the parameter design and optimization of ducted fans. Computational Fluid Dynamics (CFD) was applied to evaluate the impact of design parameters on overall aerodynamic performance. This approach addresses the limitations of traditional methods, including low design accuracy, high computational cost, and insufficient multi–objective optimization capability. It explicitly models multi-parameter coupling and nonlinear effects using a small number of experimental points, combined with the Multi-Objective Genetic Algorithm (MOGA) to find the global optimum. Compared to the baseline duct fan, the optimized duct fan achieved a 9.6% increase in overall lift and a 9.5% improvement in lift efficiency. Full article

Clearance in joints caused by assemblage, manufacturing errors, and wear is inevitable, which will affect the dynamic performance of the dual-manipulator system on spacecraft. The motion of the dual-manipulator system with clearances in imperfect joints is the motion of dual-manipulator system with ideal joints. In this paper, the dynamic responses and motion accuracy ofdual-manipulator system on spacecraft considering clearance effects are investigated numerically. The imperfect joint with clearance is considered as contact force constraint and the mathematical model of revolute joint with clearance is established, where the normal contact force is established using nonlinear continuous contact force model and the friction effect is considered using modified Coulomb friction model. Then, a dual-manipulator system on spacecraft with clearance joints is used as the numerical example to implement the investigation. The effects of clearances on dynamic responses and motion accuracy of the dual-manipulator system are presented and discussed via different case studies. Numerical simulation results indicate that clearances present significant effects on the dynamic performances of dual-manipulator system due to contact and impact in clearance joints. The motion accuracy and stability of the dual-manipulator system are obviously reduced. The investigation in this work clearly shows the effects of clearances on dynamic performance of the dual-manipulator system on spacecraft, which is the basis for robust control system design of dual-manipulator system. Full article

The Wiegand effect is a nonlinear magnetic phenomenon observed in specially processed Wiegand wires, representing a macroscopic manifestation of the Barkhausen effect. It is characterized by a large, sharp Barkhausen jump in the wire’s magnetization curve under an external alternating magnetic field. However, the underlying magnetic structure of these wires and the precise mechanism responsible for the Wiegand effect remain inadequately understood. In this study, we propose a conceptual model for the magnetic structure of Wiegand wires. Experimental samples with varying diameters were prepared through FeCl₃ solution etching. The magnetic properties of individual layers within the wire were systematically investigated using the surface magneto-optic Kerr effect, Wiegand pulse measurements, and minor hysteresis loop analysis. By correlating these experimental results with JMAG simulations based on the proposed magnetic structure model, we elucidate the layer-by-layer magnetization reversal processes under alternating magnetic fields and clarify the fundamental mechanism that triggers the large Barkhausen jump. Full article

In the context of China’s dual-carbon agenda and the Digital China initiative, elucidating the role of digital literacy in shaping consumption-based household carbon emissions (HCE) is essential for advancing low-carbon urban living and supporting a broader green transition. Existing research has rarely examined, at the individual level, how digital capability shapes household consumption decisions and the structure of carbon emissions. Accordingly, this study draws on matched household-individual microdata from the China Family Panel Studies (CFPS). We employ a two-way fixed effects model, kernel density analysis, and qualitative comparative analysis. We test the nonlinear effect of digital literacy on household consumption-related carbon emissions and examine its heterogeneity. We also examined the mediating role of perceived environmental pressure, social trust and income level. The research results show that: (1) The net impact of digital literacy on carbon emissions related to household consumption shows an inverted U-shaped curve, rising first and then falling. When digital literacy is low, it mainly increases emissions by expanding consumption channels, reducing transaction costs and improving convenience. Once digital literacy exceeds a certain threshold, the mechanism will gradually turn to optimize the consumption structure, so as to support the low-carbon transformation of individuals. (2) The impact of digital literacy on HCE is structurally different in different types of consumption. In terms of transportation and communication expenditure, the emission reduction effect is the most significant, and with the improvement in digital literacy, this effect will become more and more obvious. For housing-related consumption, the turning point appeared the earliest. With the improvement in digital literacy, its effect will enter the emission reduction stage faster. (3) Digital literacy can reduce carbon emissions related to household consumption by enhancing residents’ perception of environmental pressure and strengthening social trust. However, it may also increase emissions by increasing residents’ incomes, because it will expand the scale of consumption, which will lead to an increase in carbon emissions related to household consumption. (4) The heterogeneity analysis shows that as digital literacy improves, carbon emissions increase more strongly among rural residents, people with low human capital, low-income households, and women. However, the turning-point threshold for emission reduction is relatively lower for women and rural residents. (5) Low-carbon transitions in household consumption are shaped by dynamic interactions among multiple factors, and multiple pathways can coexist. Digital literacy can work with environmental responsibility to endogenously promote low-carbon consumption behavior. It can also, under well-developed infrastructure, empower households and amplify the emission-reduction effects of technology. Full article

Accurate modeling and parameter estimation of photovoltaic (PV) systems are vital for advancing energy sustainability and achieving global decarbonization goals. Reliable PV models enable better integration of solar resources into smart grids, improve system efficiency, and reduce maintenance costs. This aligns with the vision of sustainable energy systems that combine intelligent optimization with environmental responsibility. The recently introduced Black-Winged Kite Algorithm (BWKA) has shown promise by emulating the predatory and migratory behaviors of black-winged kites; however, it still suffers from issues of slow convergence, limited population diversity, and imbalance between exploration and exploitation. To address these limitations, this paper proposes an Improved Black-Winged Kite Algorithm (IBWKA) that integrates two novel strategies: (i) a Soft-Rime Search (SRS) modulation in the attacking phase, which introduces a smoothly decaying nonlinear factor to adaptively balance global exploration and local exploitation, and (ii) a Quadratic Interpolation (QI) refinement mechanism, applied to a subset of elite individuals, that accelerates local search by fitting a parabola through representative candidate solutions and guiding the search toward promising minima. These dual enhancements reinforce both global diversity and local accuracy, preventing premature convergence and improving convergence speed. The effectiveness of the proposed IBWKA in contrast to the standard BWKA is validated through a comprehensive experimental study for accurate parameter identification of PV models, including single-, double-, and three-diode equivalents, using standard datasets (RTC France and STM6_40_36). The findings show that IBWKA delivers higher accuracy and faster convergence than existing methods, with its improvements confirmed through statistical analysis. Compared to BWKA and others, it proves to be more robust, reliable, and consistent. By combining adaptive exploration, strong diversity maintenance, and refined local search, IBWKA emerges as a versatile optimization tool. Full article

This paper describes a composite control approach that improves the accuracy and dynamic performance of the control of a voice-coil-driven, two-dimensional fast steering mirror (FSM). Strong nonlinearity, perturbation of parameters, unmodeled dynamics and external disturbances typically compromise the performance of the FSM. The proposed controller combines a tracking differentiator (TD), linear extended state observer (LESO), and a double-integral global fast terminal-sliding mode control (DIGFTSMC). The TD corrects the reference command signal, and the LESO approximates and counteracts system disturbances. The sliding surface is then equipped with the double-integral operators and an improved adaptive reaching law (IARL) to enhance tracking accuracy, response speed and robustness. Prior to physical experiments, systematic numerical simulations were conducted for five control algorithms across four typical test scenarios, verifying the proposed controller’s feasibility and preliminary performance advantages. It is found through experimentation that the proposed controller lowers the time esterified by the step response adjustment by 81.0% and 48.4% more than the PID controller and the DIGFTSMC approach with no IARL, respectively, and the proposed controller enhances error control when tracking sinuoidal signals and multisinusoidal signals. Simulation results consistently align with experimental trends, confirming the proposed controller’s superior convergence speed, tracking precision, and disturbance rejection capability. Furthermore, it cuts the angular movement swing by an average of over 44% through dismissing needless vibration interruptions as compared to other sliding mode control techniques. Experimental results demonstrate that the proposed composite control approach significantly enhances the disturbance rejection, control accuracy, and dynamic tracking performance of the voice-coil-driven FSM system. Full article

This paper presents an experimental and numerical investigation of continuous reinforced concrete (RC) beams made of self-compacting concrete (SCC) strengthened with fiber-reinforced polymer (FRP) bars using the Near-Surface Mounted (NSM) method. While the majority of previous studies have focused on simply supported beams, this work examines two-span continuous beams, which are more representative of real structural behavior. Four SCC beams were tested under static loading to evaluate the influence of the FRP reinforcement position on flexural capacity and deformational characteristics. The beams were strengthened using glass FRP (GFRP) bars embedded in epoxy adhesive within pre-cut grooves in the concrete cover. Experimental results showed that FRP reinforcement significantly increased the ultimate load capacity, while excessive reinforcement reduced ductility, leading to a more brittle failure mode. A three-dimensional finite element model was developed in Abaqus/Standard using the Concrete Damage Plasticity (CDP) model to simulate the nonlinear behavior of concrete and the bond–slip interaction at the epoxy–concrete interface. The numerical predictions closely matched the experimental load–deflection responses, with a maximum deviation of less than 3%. The validated model provides a reliable tool for parametric analysis and can serve as a reference for optimizing the design of continuous SCC beams strengthened by the NSM FRP method. Full article

Detecting structural defects is one of the primary challenges engineers face. Consequently, the development of techniques and methods capable of detecting structural defects has always been critical. It should be emphasized that crack detection is only meaningful if it occurs before the final stages of structural failure. Accordingly, the early identification of structural defects has become a significant research challenge, motivating the development of techniques and diagnostic parameters that can effectively capture and reflect the structure’s nonlinearity or non-uniform behavior. This study aims to provide a more detailed examination of modulation phenomena observed in the measured response using the vibro-acoustic modulation (VAM) method, and propose a new model that simultaneously incorporates all three conventional modulation types (amplitude, frequency, and phase), which may offer a more accurate representation of the response signal behavior. Both theoretical and experimental results clearly confirm that the phase shifts of individual frequency components in the frequency domain vary throughout the lifetime of the tested specimen. This behavior, as anticipated by the proposed model, reveals a strong correlation between phase shifts and modulation indices (MIs). Furthermore, the relative sensitivity analysis indicates that the phase shift is more sensitive than the modulation index (MI), suggesting its strong potential as an indicator for early defect detection in structural components. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

The article discusses the control of nonlinear processes with first-order dominant dynamics, focusing on implementation using modern hardware available in various programmable devices and embedded systems. The first two approaches rely on linearization with an ultra-local process model, considering small changes of the process input and output around a fixed operating point, which can be adjusted through gain scheduling with the setpoint variable. This model is used to configure either the historically established automatic reset controller (ARC) or a stabilizing proportional (P) controller enhanced by an inversion-based disturbance observer (DOB). This solution can be interpreted as an application of modern control theory (MCT), as DOB-based control (DOBC) or as advanced disturbance rejection control (ADRC). Alternatively, they can be viewed as a special case of automatic offset control (AOC) based on two types of linear process models. In the third design method, setpoint tracking by exact linearization (EL) is extended with a nonlinear DOB designed using the inverse of the nonlinear process dynamics (EEL). The fourth approach augments EL-based tracking with a DOB derived from the transfer functions of nonlinear processes (NTF). An illustrative example involving the control of a liquid reservoir with a variable cross-section clarifies motivation for the definition of (linear) local and ultra-local process models as well as their advantages in designing robust control that accounts for process uncertainties. Thus, the speed, homogeneity, and shape of transient responses, the ability to reconstruct disturbances, control signal saturation, and measurement noise attenuation are evaluated according to the assumptions specified in the controller design. The novelty of the paper lies in presenting a unifying perspective on several seemingly different control options under the impact of measurement noise. By explaining their essence, advantages, and disadvantages, it provides a foundation for controlling more complex time-delayed systems. The paper emphasizes that certain aspects of controller design, often overlooked in traditional linearization procedures, can significantly improve closed-loop properties. Full article