Search Results (1,952)

The supporting system of super-large cooling towers is crucial for the structural safety of nuclear power plants. The X-shaped reinforced concrete column has emerged as a promising solution due to its superior stability. However, the performance of the cast-in-place base joint, which is a key force-transfer component, requires thorough investigation. This study experimentally investigates the mechanical performance of the joints under ultimate vertical compressive and tensile loads. The loads represent gravity-dominated and extreme wind uplift scenarios, respectively. A comprehensive testing program monitored load–displacement responses, strain distributions, crack propagation, and failure modes. The compression specimen failed in a ductile flexural compression manner with plastic hinge formation above the column base. In contrast, the tension specimen exhibited a tension-controlled failure pattern. Crucially, the joint remained stable after column yielding in both loading scenarios. The result validates the “strong connection–weak member” design principle. The findings confirm that the proposed cast-in-place joint possesses excellent load-bearing capacity and ductility. Therefore, the study provides a reliable design basis for the supporting structures of super-large cooling towers. Full article

To address poor seismic performance, large residual displacement, and insufficient self-centering capacity of prefabricated frame joints in building industrialization, this study proposes a novel self-centering prefabricated frame joint reinforced with shape memory alloy fiber (SMAF)–engineered cementitious composite (ECC) composites (SMAF-ECC). A validated finite element model of the proposed joint was established using ABAQUS, with comparative analyses conducted against conventional reinforced concrete (RC) and ECC-strengthened (RC-E) joint models to explore the effect of SMAF volume content on seismic performance. Results show that replacing the joint core zone concrete with SMAF-ECC significantly enhances the joint’s seismic and self-centering capabilities, reducing residual displacement and optimizing hysteretic behavior. SMAF volume content is a key factor affecting performance, with an optimal value identified and excessive content leading to fiber agglomeration and degraded self-centering ability. This study provides a feasible solution to improve the seismic resilience of prefabricated frame joints, laying a foundation for the application of SMAF-ECC in prefabricated structures. Full article

Minor displacements and deflections of rail fastener clips pose a critical risk to railway safety, which are difficult to quantify accurately using traditional object detection methods. This paper proposes an improved YOLOv8-pose-based method, You Only Look Once version 8-pose with GAM, SPPF-Attention, and Wise-IoU (YOLOv8-pose-GSW) for automated and quantitative pose detection of fastener clips. Firstly, a high-precision keypoint detection network is constructed by integrating a Global Attention Mechanism (GAM) into the neck, enhancing the Spatial Pyramid Pooling Fast (SPPF) module to Spatial Pyramid Pooling Fast with Attention (SPPF-Attention) in the backbone, and adopting the Wise Intersection over Union (Wise-IoU) loss function. Subsequently, a posterior verification mechanism based on spatial constraint error is designed to eliminate unreliable detections by leveraging the inherent geometric priors of fasteners. Finally, the deflection angle, longitudinal displacement, and lateral displacement of the clip are calculated from the verified keypoints. Experimental results demonstrate that the proposed method achieves an Average Precision at IoU threshold from 0.5 to 0.95 (AP@0.5:0.95) of 77.5%, representing a 3.6% improvement over the baseline YOLOv8s-pose model, effectively balancing detection accuracy and computational efficiency. This work provides a reliable technical solution for the refined maintenance of rail fasteners. Full article

This review aims to provide a complete and comprehensive state of the art of the SCOSSA computer code, which is a one-dimensional nonlinear computer code used for the analysis of seismic site response and soil instability. Indeed, among the effects of earthquakes, the activation of landslides and liquefaction constitute two of the predominant causes of vulnerability in the physical and built environment. The SCOSSA computer code (Seismic Code for Stick–Slip Analysis) was initially developed to evaluate the permanent displacements of simplified slopes using a coupled model, and introduced several improvements with respect to the past, namely, the formulation for solving the dynamic equilibrium equations incorporates the capability for automated detection of the critical sliding surface; an up-to-date constitutive model to represent hysteretic material behavior and a stable iterative algorithm to support the solution of the system in terms of kinematic variables. To address liquefaction-induced failure, a simplified pore water pressure generation model was subsequently developed and integrated into the code, coupled with one-dimensional consolidation theory. This review retraces the main features, developments, and applications of the computer code from the origin to the present version. Full article

The dynamic characteristics of flotation foam, such as velocity and breakage rate, are critical factors that influence mineral separation efficiency. However, challenges inherent in foam images, including weak textures, severe deformations, and motion blur, present significant technical hurdles for dynamic monitoring. These issues lead to a fundamental conflict between the efficiency and accuracy of traditional feature matching algorithms. This paper introduces a novel progressive framework for dynamic feature matching in flotation foam images, termed “stable extraction, efficient coarse screening, and precise matching.” This framework first employs the Accelerated-KAZE (AKAZE) algorithm to extract robust, scale- and rotation-invariant feature points from a non-linear scale-space, effectively addressing the challenge of weak textures. Subsequently, it innovatively incorporates the Grid-based Motion Statistics (GMS) algorithm to perform efficient coarse screening based on motion consistency, rapidly filtering out a large number of obvious mismatches. Finally, the Progressive Sample and Consensus (PROSAC) algorithm is used for precise matching, eliminating the remaining subtle mismatches through progressive sampling and geometric constraints. This framework enables the precise analysis of dynamic foam characteristics, including displacement, velocity, and breakage rate (enhanced by a robust “foam lifetime” mechanism). Comparative experimental results demonstrate that, compared to ORB-GMS-RANSAC (with a Mean Absolute Error, MAE of 1.20 pixels and a Mean Relative Error, MRE of 9.10%) and ORB-RANSAC (MAE: 3.53 pixels, MRE: 27.36%), the proposed framework achieves significantly lower error rates (MAE: 0.23 pixels, MRE: 2.13%). It exhibits exceptional stability and accuracy, particularly in complex scenarios involving low texture and minor displacements. This research provides a high-precision, high-robustness technical solution for the dynamic monitoring and intelligent control of the flotation process. Full article

This paper presents a nonlinear vertical dynamic model of an electromagnetic suspension (EMS) system in maglev trains regulated by a dual nonlinear saturation controller (DNSC) under simultaneous resonance ($\Omega \cong {\omega }_s, {\omega }_s\cong 2{\omega }_c$). The governing nonlinear differential equations of the system are addressed analytically utilizing the multiple time-scale technique (MTST), concentrating on resonance situations obtained from first-order approximations. The suggested controller incorporates two nonlinear saturation functions in the feedback and feedforward paths to improve system stability, decrease vibration levels, and enhance passenger comfort amidst external disturbances and parameter changes. The dynamic bifurcations caused by DNSC parameters are examined through phase portraits and time history diagrams. The goal of control is to minimize vibration amplitude through the implementation of a dual nonlinear saturation control law based on displacement and velocity feedback signals. A comparative analysis is performed on different controllers such as integral resonance control (IRC), positive position feedback (PPF), nonlinear integrated PPF (NIPPF), proportional integral derivative (PID), and DNSC to determine the best approach for vibration reduction in maglev trains. DNSC serves as an effective control approach designed to minimize vibrations and enhance the stability of suspension systems in maglev trains. Stability evaluation under concurrent resonance is conducted utilizing the Routh–Hurwitz criterion. MATLAB 18.2 numerical simulations (fourth-order Runge–Kutta) are employed to analyze time-history responses, the effects of system parameters, and the performance of controllers. The evaluation of all the derived solutions was conducted to verify the findings. Additionally, quadratic velocity feedback leads to intricate bifurcation dynamics. In the time domain, higher displacement and quadratic velocity feedback may destabilize the system, leading to shifts between periodic and chaotic movements. These results emphasize the substantial impact of DNSC on the dynamic performance of electromagnetic suspension systems. Frequency response, bifurcation, and time-domain evaluations demonstrate that the DNSC successfully reduces nonlinear oscillations and chaotic dynamics in the EMS system while attaining enhanced transient performance and resilience. Full article

Transmission tower guy wires are critical flexible tension members ensuring the stability and safe operation of overhead power transmission networks. However, these components are vulnerable to external impacts from falling rocks, ice masses, and other natural hazards, which can cause excessive deformation, anchorage loosening, and catastrophic failure. Current design standards primarily consider static loads, lacking comprehensive models for predicting dynamic impact responses. This study presents a theoretical model for predicting the peak impact response of guy wires by modeling the impact process as a point mass impacting a nonlinear spring system. Using an energy-based elastic potential method combined with cable theory, analytical solutions for axial force, displacement, and peak impact force are derived. Newton–Cotes numerical integration solves the implicit function to obtain closed-form solutions for efficient prediction. Validated through finite element simulations, deviations of peak displacement, peak impact force, and peak axial force between theoretical and numerical results are within ±4%, ±18%, and ±4%, respectively. Using the validated model, parametric studies show that increasing the inclination angle from 15° to 55° slightly reduces peak displacement by 2–4%, impact force by 1–13%, and axial force by 1–10%. Higher prestress (100–300 MPa) decreases displacement and impact force but increases axial force. Longer lengths (15–55 m) cause linear displacement growth and nonlinear force reduction. Impacts near anchorage points help control displacement risks, and impact velocity generally has a more significant influence on response characteristics than impactor mass. This model provides a scientific basis for impact-resistant design of power grid infrastructure and guidance for optimizing de-icing strategies, enhancing transmission system safety and reliability. Full article

This paper presents a magnetic-flux-based encoder for BLDC drives that maintains high accuracy under rotor eccentricity and dynamic transients. Conventional Hall-sensor-based angle estimators rely on ideal sinusoidal flux assumptions and degrade in the presence of air-gap distortion or misalignment. To overcome these limitations, a nonlinear autoregressive network with exogenous inputs (NARXNet) is proposed as a temporal neural observer that learns the nonlinear, time-dependent mapping between measured flux densities and the true electrical rotor angle. A physics-informed data augmentation framework combines experimentally measured magnetic flux maps with dynamic simulation to generate diverse training scenarios at low and variable speeds. Validation demonstrates mean angular errors below 2°, 95th-percentile errors under 5°, and negligible drift, with enhanced resilience to eccentric displacement and acceleration transients compared to classical methods. The proposed approach provides a compact, data-driven sensing solution for robust, encoderless electric drive control. Full article

Autonomous Unmanned Aerial Vehicles (UAVs) are widely used in smart agriculture, logistics, and warehouse management, where precise trajectory prediction is important for safety and efficiency. Traditional approaches require complex physical modeling including mass properties, moment of inertia measurements, and aerodynamic coefficient calculations, which creates significant barriers for custom-built UAVs. Existing trajectory prediction methods are primarily designed for motion forecasting from dense historical observations, which are unsuitable for scenarios lacking historical data (e.g., takeoff phases) or requiring trajectory generation from sparse waypoint specifications (4–6 constraint points). This distinction necessitates architectural designs optimized for spatial interpolation rather than temporal extrapolation. To address these limitations, we present a segmented LSTM framework for complete autonomous flight trajectory prediction. Given target waypoints, our architecture decomposes flight operations, predicts different maneuver types, and outputs the complete trajectory, demonstrating new possibilities for mission-level trajectory planning in autonomous UAV systems. The system consists of a global duration predictor (0.124 MB) and five segment-specific trajectory generators (∼1.17 MB each), with a total size of 5.98 MB and can be deployed in various edge devices. Validated on real Crazyflie 2.1 data, our framework demonstrates high accuracy and provides reliable arrival time predictions, with an Average Displacement Error ranging from 0.0252 m to 0.1136 m. This data-driven approach avoids complex parameter configuration requirements, supports lightweight deployment in edge computing environments, and provides an effective solution for multi-UAV coordination and mission planning applications. Full article

Polymer solutions exhibit radial flow characteristics upon injection into a formation via the wellbore. Accurately characterizing their viscoelastic properties at varying seepage velocities and quantifying their impact on displacement efficiency are crucial for advancing polymer flooding technology. This study simulated shear rate variations during polymer injection and integrated laboratory-measured viscoelastic properties with permeability characteristics in porous media. An analysis of the oil displacement performance between viscoelastic polymer solutions and a purely viscous fluid, glycerol, was conducted. The key findings are as follows: (1) Polymer elasticity, characterized by the first normal stress difference, diminishes with decreasing injection time/solution concentration. Significant viscoelasticity is observed near the wellbore, weakening in deeper reservoir regions. (2) The polymer type and injection conditions govern the development of solution “effective viscosity” during porous medium flow. A fundamental trend under elevated flow velocities is an increase in effective viscosity with shear rate. (3) Comparison with glycerol demonstrates that the viscoelastic effect of polymer solutions enhances heavy-oil displacement efficiency. The magnitude of this viscoelastic effect within the porous medium directly correlates with its contribution to improved displacement efficiency. Full article

Photoacoustic (PA) velocimetry offers a promising solution to the limitations of conventional techniques for measuring blood flow velocity. Given its moderate penetration depth and high spatial resolution, PA imaging is considered suitable for measuring low-velocity blood flow in capillaries located at moderate depths. High-resolution measurements based on PA signals from individual blood cells can be achieved using a high-frequency transducer. However, high-frequency signals attenuate rapidly within biological tissue, restricting the measurable depth. Consequently, low-frequency transducers are required for deeper measurements. To date, PA flow velocimetry employing low-frequency transducers remains insufficiently explored. In this study, we investigated the effect of the concentration of particles that mimic blood cells within vessels under low-concentration conditions. The performance of flow velocity measurement was evaluated using an ultrasonic transducer (UST) with a center frequency of 10 MHz. The volume fraction of particles in the solution was systematically varied, and the spatially averaged flow velocity was assessed using two different distinct analysis methods. One method employed a time-shift approach based on cross-correlation analysis. Flow velocity was estimated from PA signal redpairs generated by particles dispersed in the fluid, using consecutive pulsed laser irradiations at fixed time intervals. The other method employed a pulsed Doppler method in the frequency domain, widely applied in ultrasound Doppler measurements. In this method, flow velocity redwas estimated from the Doppler-shifted frequency between the transmitted and received signals of the UST. For the initial analysis, numerical simulations were performed, followed by experiments based on displacement measurements equivalent to velocity measurements. The target was a capillary tube filled with an aqueous solution containing particles at different concentration levels. The time–domain method tended to underestimate flow velocity as particle concentration increased, whereas the pulsed Doppler method yielded estimates consistent with theoretical values, demonstrating its potential for measurements at high concentrations. Full article

Implementing compressed air energy storage (CAES) in lined caverns provides a promising technical solution for large-scale energy storage, and the reasonable selection of sealing materials is essential for its success. Flexible membrane materials including sprayable polymers, rubber sheets, and airbags have recently been considered economical and practical sealing options. However, research on flexible membrane sealed CAES caverns remains limited, particularly regarding their mechanical response and parameter sensitivities. To address this gap, an elastic multilayer thick-walled cylinder model verified by physical model tests is proposed. Analytical solutions for the stress and displacement fields of the surrounding rock and concrete lining are derived, and a calculation scheme is designed to evaluate the influence and sensitivity of key parameters. Results indicate that under high internal pressure, both the lining and surrounding rock undergo radial compression without yielding, whereas the lining experiences adverse tensile stresses in the hoop direction. The maximum hoop tensile stress reached the order of 1~3 MPa under typical CAES operating pressures, and tensile-compressive stress transformation may occur in the lining under certain parameter combinations. Sensitivity analysis further shows that internal pressure, in situ stress, surrounding rock elastic modulus, and cavern radius are the dominant factors influencing the mechanical behavior of the system, while geometric and lining parameters have secondary but non-negligible effects. The findings provide theoretical support for the stability analysis and material design of flexible membrane sealed CAES caverns and offer useful guidance for determining allowable operating pressures and selecting lining configurations. Full article

To address the limitations of optical interferometry (strict environmental requirements, high cost) and piezoelectric methods (hysteresis, creep) in micro-displacement measurement, this study proposes a collaborative measurement approach based on the parallel plate capacitance principle—with its core innovation lying in integrated optimization rather than original principles. Unlike existing studies that separately optimize mechanics, hardware, or algorithms, this work achieves the first synergy of three components: a mechanical coupling mechanism (integrating a high-resolution optical mount and a micrometer) for parallel plate regulation, a 21-bit capacitance detection module based on the STM32-PCAP01 (with a resolution of 0.0001 pF), and a linear response model relating capacitance to the reciprocal of displacement. Experimental validation confirms its engineering feasibility for sub-nanometer-level precision: with a 10 cm plate radius and 3–20 mm initial spacing, the system achieves 277.215 ± 0.244 pF·mm sensitivity and <0.05 μm displacement resolution. The relative error of micro-displacement measurement in the 10 μm range is less than 1.56%. Based on the hardware resolution, the system possesses the theoretical capability to detect displacements as low as 10⁻⁸ to 10⁻⁹ m. Compared to laser interferometry, it operates stably in common industrial environments without vibration isolation or darkrooms, reducing costs by ~90% while maintaining comparable accuracy. This cost-effective solution enables online precision measurement in semiconductor manufacturing and MEMS testing, with its multi-physics collaborative design offering a new paradigm for intelligent sensor development. Full article

A theoretical model of the interaction between a following current and a semi-infinite floating ice sheet under compressive stress near a vertical impermeable wall is developed, within the scope of linear water wave theory, to study the hydroelastic behavior. The conceptual framework defining the buoyant ice structure incorporates the tenets of elastic beam theory. The associated fluid dynamics are governed by strict adherence to the potential flow paradigm. To resolve the undetermined parameters appearing in the Fourier series decomposition of the potential functions, investigators systematically apply higher-order criteria detailing the coupling relationships between modes. The current results are compared with a specific case of results available in the literature, and the convergence analysis of the analytical solution is made for computational accuracy. Further, the free edge conditions are applied at the edge of the floating ice sheet, and the effects of current speed, compressive stress, the thickness of the ice sheet, flexural rigidity, water depth on the strain, displacements, reflection wave amplitude, and the horizontal force on the rigid vertical wall are analyzed in detail. It is found that the higher values of the following current heighten the strain, displacements, reflection amplitude, and force on the wall. The study’s outcomes are considered to benefit not just cold region design applications but also the engineering of resilient floating structures for oceanic and offshore environments, and to the design of marine structures. Full article

Nonlinear water waves (NWWs) can be generated by the vertical bottom disturbance, which represents the conceptual processes of the rise of seabed rupture under seismic loads. To explore the correlation between the disturbance parameters and the wave features, a Reynolds-averaged Navier–Stokes (RANS) model is applied, with the flow turbulence and fluid–structure interaction (FSI) being resolved by the k–ɛ model and the immersed boundary method (IBM), respectively. The free surface is tracked using the volume of fluid (VOF) method. After validating against the theoretical solutions and experimental results, the effects of disturbance duration and bulk on the wave features at the source region (the generation stage) and offshore direction (the propagation stage) are systematically discussed. The fixed maximal vertical displacement is considered, with four moving durations and five disturbance widths being simulated, resulting in four disturbance velocities and five disturbance bulks. The results indicate that the proposed RANS model can accurately create various wave patterns (including the linear, solitary, and tsunami-like waves) generated by bottom disturbances. Special attentions are paid to the tsunami-like wave. The wave evolution exhibits strong dependence on disturbance duration and width, with shorter durations triggering earlier soliton fission and longer widths accelerating phase celerity. These findings highlight the critical role of disturbance parameters in governing soliton formation and energy propagation patterns, which are vital in disaster forecasting. Full article