Search Results (556)

The steam generator is a core component of nuclear power plants that facilitates heat exchange between the primary and secondary circuits, directly impacting the overall operation of the plant in terms of safety and reliability. During prolonged operation, the heat transfer tubes of the steam generator are subjected to erosion, corrosion, and cracking due to high-temperature, high-pressure fluid impact and vibration. Existing in-service inspection strategies for heat transfer tubes generally employ fixed intervals and coverage, failing to effectively differentiate the actual risk of tubes in various regions, leading to wasted inspection resources or safety hazards. This paper proposes a dynamic inspection and plugging management strategy based on flow-induced vibration (FIV) analysis, specifically utilizing the flow stability ratio (FSR). By calculating the FSR of heat transfer tubes, the strategy categorizes them into high-risk, medium-risk, and low-risk regions, and dynamically adjusts inspection frequency and coverage based on these risk levels. Theoretical analysis and validation with actual data demonstrate that this strategy can improve inspection efficiency and ensure the safety of the steam generator. Full article

With the exponential growth of natural gas reserves and utilization scale in China, underground gas storage (UGS) facilities—critical infrastructure within the natural gas production-supply-storage-sales system—have entered a phase of rapid expansion. As the core component connecting subsurface reservoirs with surface systems, wellbore integrity directly influences operational safety and service lifespan of UGS facilities. However, current leakage detection and integrity analysis methodologies for gas storage wellbores remain deficient in effective real-time monitoring capabilities. Traditional methods, however, are constrained by limited spatial coverage and insufficient precision, rendering them inadequate for comprehensive, continuous safety monitoring requirements. To address this industry challenge, this study proposes a real-time wellbore integrity monitoring framework based on distributed fiber optic sensing technology, integrating distributed temperature sensing (DTS) and distributed acoustic sensing (DAS) devices into a synergistic monitoring system. The DTS component enables preliminary localization of potential leakage points through detection of minute temperature anomalies along the wellbore, while the DAS unit accurately identifies acoustic signatures caused by gas leakage within casings via monitoring of acoustic vibration signals propagating along the optical fiber. Through joint analysis of DTS and DAS data streams, real-time diagnosis of wellbore leakage events and integrity status can be achieved. Field trials demonstrated that this hybrid monitoring system achieved leakage localization accuracy within 1.0 m, effectively distinguishing normal operational signals from abnormal leakage characteristics. During actual monitoring operations, no indications of wellbore integrity compromise were detected; only minor noise and interference signals originating from surface construction activities were observed. Full article

Resilient wheels are widely employed in metro vehicles to mitigate vibration and noise, in which rubber damping components play a critical role in load transmission and fatigue resistance. However, stress concentration and cyclic loading can significantly compromise their durability and service life. In this study, the structural optimization and fatigue life of rubber damping components in resilient wheels are systematically investigated based on finite element analysis and in-service metro operational data. A three-dimensional finite element model incorporating hyperelastic material behavior is developed to evaluate stress distributions under three representative conditions: press-fit assembly, straight-line operation, and curved-track operation. Based on the resulting stress fields, critical high-stress regions within the rubber component are identified and selected as targets for structural optimization. The Design of Experiments (DOE) methodology, integrated with the Isight 2022 optimization platform, is employed to determine the optimal geometric parameters that minimize the von Mises equivalent stress. Furthermore, a fatigue life prediction framework is established using actual metro service mileage data. Fatigue performance is assessed using Fe-safe 2022 software in conjunction with rubber fatigue crack propagation theory, and the results before and after optimization are systematically compared. This study demonstrates that stress concentrations in resilient wheel rubber damping components predominantly occur at fillet transition regions, governed by load transfer characteristics under press-fitting and service conditions. Through DOE-based structural optimization, the critical geometric parameters are effectively refined, leading to a significant reduction in stress levels in key regions. As a result, the proposed approach markedly improves fatigue performance, extending the minimum fatigue life from 1300 days to 24,322 days, thereby substantially enhancing the durability and reliability of the resilient wheel system. Full article

Lateral wear inevitably develops on the wheel treads of high-speed trains after a period of operation. Extensive research has been dedicated to circumferential wear (e.g., wheel polygonization), whereas studies on lateral tread wear and its impact on wheel-rail noise remain limited. This study investigates this issue through a combined approach of field measurements and numerical simulation. First, lateral wear profiles are measured on in-service high-speed train wheels, and their patterns are systematically analyzed. Subsequently, a three-dimensional transient wheel-rail rolling contact model is developed using the explicit finite element method. This model is employed to analyze the effects of the lateral hollow wear depth on the contact patch position and wheel-rail forces at 400 km/h. Finally, these calculated forces are imported into a coupled wheel-rail vibration and acoustic radiation model to predict noise characteristics at different wear depths. This study clarifies the coupling of lateral tread hollow wear with wheel-rail contact characteristics at 400 km/h and quantifies its mechanical influence on high-frequency wheel-rail noise via contact patch evolution and structural receptance variation. The results demonstrate that lateral wear manifests as hollow wear, with a maximum depth of approximately 1 mm within a reprofiling cycle. It has been found that as the hollow wear depth increases, the contact patch center shifts toward the wheel flange, and its major axis elongates. Consequently, wheel-rail noise increases significantly with greater wear depth. Specifically, a wear depth increase of 0.78 mm leads to increments of 2.3 dB in wheel noise, 0.9 dB in rail noise, and 1.0 dB in total wheel-rail noise. These findings underscore that tread hollow wear is a significant contributor to high-speed wheel-rail noise, highlighting the need for its consideration in maintenance and noise control strategies. Full article

Pavement rutting is caused by grooves formed by vehicle traffic, affecting driving comfort, safety, and service life. Rutting detection methods have evolved from manual and automated approaches to intelligent detection for smart cities and maintenance. However, lightweight intelligent detection still faces challenges such as insufficient accuracy and technical complexity, and a mature system has yet to be established. This study aims to develop a portable intelligent terminal for pavement rut detection, which can address the challenges associated with traditional pavement rut detection while providing accuracy and reliability. In this study, rutting detection experiments were performed on a full-scale accelerated loading track to collect data on vibration acceleration, angular velocity, and attitude angles. Comparative experiments were carried out between traditional and lightweight detection methods. Subsequently, GRU-CNN, LSTM–Transformer, GRU, and LSTM models were developed to analyze and compare their performance in predicting rutting depth. The results show that the terminal operates stably, offering convenient usability and reliable data acquisition. Furthermore, vehicle angular velocity and roll angle emerge as critical indicators reflecting rutting impacts on driving states and prove suitable for pavement rut depth detection. The proposed GRU-CNN model achieves superior accuracy and overall performance relative to widely used models. Under synchronous detection conditions, the lightweight method yields a mean absolute error (MAE) of 1.22 mm, achieving performance improvements of 17.32%, 8.74%, and 10.08% over the LSTM–Transformer, GRU, and LSTM models, respectively. Additionally, the method yields a mean absolute percentage error of approximately 10.6%, representing error reductions of 15.87%, 19.08%, and 23.74% compared to the aforementioned baseline models, which meets application requirements. Innovation lies in the development of a lightweight intelligent terminal and GRU-CNN hybrid model that integrates vehicle dynamic parameters for large-scale pavement rutting detection. This study presents a lightweight, real-time pavement rutting detection method based on vehicle operation data for the construction and maintenance of smart cities and intelligent transportation infrastructure, combining the features of high cost effectiveness, high accuracy, and ease of large-scale application. Full article

Cement concrete is a critical pavement construction material. However, under prolonged exposure to heavy traffic loads and the combined effects of multiple factors, it frequently exhibits premature slab failure and concurrent multiple defects, severely limiting its service performance and lifespan. The dynamic behavior of cement concrete pavement under heavy-load conditions and the influence of subgrade geometry and pavement width on dynamic bearing performance remain insufficiently understood. To address this issue, this study employs finite element software Abaqus 2020 to construct a three-dimensional finite element model of heavy-duty cement concrete pavement under six typical conditions, including uncut and unfilled subgrade, low embankment, high embankment, cut slope, and different pavement widths. Utilizing an implicit dynamic algorithm, the model simulates and analyzes the acceleration response, dynamic stress distribution, and evolution of strain energy density within the pavement structure under vehicle dynamic loading. The results indicate that the peak acceleration is highest for the uncut subgrade (159.214 m/s²) and lowest under the cut condition (146.566 m/s²), demonstrating that the cutting structure can effectively suppress pavement vibration intensity. Among subgrade types, high embankments exhibit the greatest capacity for reducing strain energy concentration; at the slab corners, the baseline strain energy density of 8.882 J/m³ is reduced by 4.2%, 7.8%, and 5.0% under low embankment, high embankment, and cut conditions, respectively. Regarding pavement width, wider configurations reduce slab vibration intensities, stored strain energy, peak stresses, and stress concentrations, benefiting long-term service life, but concurrently elevate slab corner strain energy accumulation, increasing the risk of corner fracture and compromising load-bearing capacity. These findings provide scientific and technical support for the structural design and performance optimization of heavy-duty cement concrete pavements. Full article

Aluminum–silicon (Al-Si) alloys are widely used in aerospace, automotive manufacturing, power electronics, marine engineering and other fields due to their excellent physical properties. However, their corrosion resistance is insufficient in harsh service environments. In this study, a variety of characterization methods were adopted, including scanning electron microscopy (SEM), X-ray diffraction (XRD), electrochemical measurements (electrochemical impedance spectroscopy (EIS) and potentiodynamic polarization), immersion corrosion tests, and scanning vibrating electrode technique (SVET). The results show that the appropriate heat treatment regime can significantly enhance the corrosion resistance of the alloy, while improper aging parameters will aggravate the corrosion tendency. The optimal heat treatment regime is solution treatment at 500 °C for 4 h followed by aging at 200 °C for 48 h. Under this condition, the corrosion current density (i_corr) is as low as 79.30 μA/cm², and the low-frequency impedance modulus and phase angle in EIS tests are optimal. The as-extruded alloy exhibits severe localized corrosion, while the heat-treated alloy transforms into mild and uniform corrosion. The underlying mechanism is that heat treatment induces the formation of uniformly distributed nanoscale Mg₂Si and Al₃(Sc,Zr) precipitates, which synergistically improve the corrosion resistance of the alloy by weakening micro-galvanic coupling and facilitating the formation of a stable passive film. Full article

To solve the problems of high-precision attitude control and vibration isolation of satellite payloads, this paper conducts in-depth research on satellite attitude dynamics and maglev active vibration isolation control technology. A dual-super collaborative control scheme is proposed, which consists of payload module ultra-high precision and ultra-high stability control, relative position control of two modules, and service module attitude control. The target attitude and angular velocity obtained by maneuver path planning and attitude guidance are transmitted to the attitude and orbit control management unit, and the total control command torque is formed by combining feedback control and feedforward control, which is then distributed to each maglev actuator to realize high-precision control of the payload module. The architecture of the maglev vibration isolation system is designed, and its dynamic model is established based on the Newton–Euler equation. Meanwhile, the dynamic model of the maglev actuator is constructed, and the active control strategy is designed by adopting PID control. The models of output force and torque are established, system parameters are set for simulation analysis of dynamic responses such as displacement, attitude and electromagnetic force, and a 20% pull-bias robustness test is carried out. Simulation results show that the system has high isolation accuracy, stability, and can effectively suppress the interference and shaking of the platform and load, with strong robustness. Full article

Lightweight and slender footbridges exemplify sustainable, material-efficient infrastructure, yet their vibration performance is frequently governed by high dynamic sensitivity, which directly affects serviceability, user comfort, and structural durability. This paper provides a critical review of full-scale experimental investigations and validated finite element simulations addressing the dynamic behavior of various footbridges, focusing on the influence of structural typology, material solutions, and excitation characteristics on vibration-related performance within sustainability-driven design objectives. This article is organized into three core research themes: (1) standards and guidelines in bridge engineering practice, (2) dynamics of footbridges with special structural response to human-induced loading, including walking, running, crowd actions, and higher harmonic contributions, and (3) case studies, based on which the gaps in the current approach are formulated. Based on a synthesis of findings from leading research on structural dynamics and sustainable infrastructure, this paper highlights critical gaps in current vibration serviceability guidance for footbridges. Concluding remarks delineate the principal research challenges and formulate evidence-based, practical recommendations to enhance the resilience, vibration comfort compliance, and sustainability of future footbridge infrastructure. Full article

Large-span bridges with bluff body girders are susceptible to vortex-induced vibration (VIV) due to their low frequency, light mass, and relatively low damping ratio, affecting fatigue life and serviceability. While research progress has been made on VIV mechanisms and control measures, systematic investigations on the application of vortex generators (VGs) to narrow Π-shaped railway girders remain scarce, and the potential synergistic effect of combining VGs with conventional aerodynamic measures has not been explored. To address this gap, wind tunnel tests were conducted on a 1:50 scale sectional model of a narrow Π-shaped steel girder for a railway cable-stayed bridge. The experimental program systematically investigated the VIV response of the original girder and evaluated the suppression effectiveness of conventional aerodynamic measures (vertical stabilizers, deflectors, modified fairings) and spanwise control using VGs. Parametric optimization of VG height (0.1 H–0.2 H, where H is the girder height), spacing (2/3 L₀ and L₀, where L₀ = 12.5 m is the standard segment length), and installation position (upper fairing, lower fairing, girder bottom) was performed. Results show that under wind angles of attack from −5° to +5° and a damping ratio of 0.36%, the original girder exhibits pronounced vertical VIV with a maximum RMS amplitude of 0.025 m, approximately 3.15 times the code limit. Conventional measures alone fail to adequately suppress VIV. However, the optimal combination of VGs (height 0.2 H, spacing L₀, installed on the lower fairing) with a 0.5 m wide, 15° inclined deflector effectively suppresses VIV under wind AOAs of 0°, ±3°, and –5°, achieving suppression below the measurable threshold. This study contributes the first comprehensive parametric investigation of VGs for narrow Π-shaped railway girders, reveals a synergistic effect when combining VGs with deflectors, and incorporates practical engineering constraints (such as aesthetic requirements) into the optimization process. Full article

The results of the development and practical application of a comprehensive system for studying gear cutting processes are presented. The processes are traditional hobbing, modern power skiving, and radial-circular methods. Carrying out these processes is based on the gear teeth continuous generating method using complex kinematics. This complicates the analysis, description and modeling of the processes. The developed system provides for a logical sequence of step-by-step modeling and simulation of interrelated processes and phenomena accompanying gear processing. Reproducing volumetric chips and calculating their parameters provides the basis for determining deformation and contact processes, cutting forces, elastic deformations, machining accuracy and energy costs per operation. After establishing the operation to overcome friction and heat flows, the degree of heating and the temperature of the working surfaces are calculated to predict tool wear and its service life. Based on the parametric non-uniformity of the considered processes, the intensity of oscillations and vibrations of gear cutting machines is predicted, and their impact on the quality of gear surfaces and the accuracy of gears is determined. These approaches enable the study of such processes at the level of individual teeth and blades during cutting. They also allow gear cutting technology and cutting tools to be optimized according to the most important criteria and performance assessments. Full article

Spatial efficiency drives the adoption of integrated station–bridge structures in maglev transit, yet the rigid coupling between track and station poses inherent challenges to vibration serviceability. This study isolates the impact of support constraints, specifically contrasting rigid connections with pinned supports, on the dynamic performance of a five-story maglev station. Using a unified, high-fidelity 3D coupled model that incorporates electromagnetic suspension nonlinearity, we evaluated structural responses under train speeds of 60–120 km/h. Simulations identify a critical operational threshold: while the waiting hall remains compliant with standard comfort criteria (DIN 4150-3), the platform floor exceeds the 1.5% g acceleration limit during dual-track operations at speeds ≥ 100 km/h. Beyond standard safety checks, the main scientific innovation of this study is revealing the mechanical transmission paths of structure-borne vibrations at the track-frame interface. The results demonstrate that rigid connections create full mechanical coupling, directly passing train-induced bending moments into the station frame. Conversely, pinned supports release the rotational degrees of freedom, which physically cuts off the primary energy transmission route. By explaining this structural decoupling mechanism, this work moves beyond a specific engineering case study to provide a fundamental theoretical framework for vibration control in complex maglev hubs. Full article

Bolted joints are extensively used in mechanical and civil engineering structures because of their low cost, standardized design, and ease of installation and maintenance. The preload in a bolted connection is critical for ensuring joint stability and service reliability; however, preload degradation commonly occurs under complex operating conditions, particularly in environments involving sustained or cyclic vibration. To tackle this problem, this study proposes a portable, force-controllable percussion system for bolt looseness detection. The system integrates a solenoid-driven automatic percussion device, acoustic signal acquisition, onboard data-processing, and real-time visualization of diagnostic results. By adjusting the driving current of the solenoid, the percussion force can be accurately controlled, ensuring stable and repeatable excitation. Benefiting from its compact structure and low cost, the proposed system is suitable for real-time, on-site inspection of bolt looseness. Furthermore, a novel audio-processing approach based on a Siamese Capsule Network is developed to identify bolt looseness conditions. Compared with existing percussion-based techniques, the proposed method exhibits improved classification performance, especially in recognizing bolt states that are unseen during training. Exploratory experimental results validate the effectiveness of the proposed system and demonstrate its strong potential for practical engineering applications. Full article

Cylinder–plate combined structures (CPCS) are widely used in aerospace, marine engineering, and offshore platform systems. During service, they are frequently subjected to stochastic excitations induced by turbulent boundary layers, acoustic loads, hydrodynamic disturbances, and broadband operational vibrations. Excessive random vibration responses may significantly reduce structural reliability, accelerate fatigue damage, and compromise operational safety. To address these engineering challenges, a unified stochastic dynamic analysis and vibration suppression framework is established for functionally graded graphene platelet-reinforced composites (FG-GPLRC) CPCS equipped with distributed dynamic vibration absorbers (DVAs). Adopting the First-order Shear Deformation Theory (FSDT), a comprehensive energy functional for the CPCS is established, in which the penalty method is implemented to impose boundary conditions and ensure interface continuity. Subsequently, the Pseudo-excitation Method (PEM) is utilized to convert the stochastic vibration analysis into an equivalent deterministic harmonic problem, and the governing equations are spatially discretized by combining the spectral geometric method (SGM) with the Ritz variational procedure, enabling efficient evaluation of power spectral density (PSD) and root-mean-square (RMS) responses. The reliability of the proposed model is verified through a series of numerical validation comparisons. On this basis, comprehensive parametric investigations are conducted to assess how material properties, structural geometries, and critical DVA parameters influence system behavior. The results demonstrate that the incorporation of distributed DVAs can achieve superior vibration suppression performance. This study provides an efficient and reliable theoretical framework for stochastic vibration analysis and damping design of advanced composite plate–shell coupled structures operating in complex random environments, offering important theoretical support for dynamic optimization design in aerospace and marine engineering applications. Full article

Accurate estimation of structural damping is essential for seismic performance assessment and design for earthquake-resistant buildings. From a sustainability perspective, reliable evaluation of dynamic properties is crucial in extending the service life of existing structures and reducing the need for material-intensive interventions. Ambient vibration measurements enable non-invasive identification of damping characteristics, supporting sustainable assessment of the built environment. This paper presents an analysis of the dynamic response of a four-story reinforced concrete structure. Ambient vibration recordings are obtained with Geodas Aquisition Station and one-second velocity sensors made by Butan Service And Tokio Soil Ltd., available from CERS (Seismic Risk Assessment Research Center) research center from TUCEB (Technical University of Civil Engineering of Bucharest). The sensors were installed at the top level of the analyzed structure. The method used for estimating the damping ratio is the Random Decrement Technique (RDT). The influence of the several parameters involved in the method is investigated, such as the triggering value, the dimension of the time window sub-samples, and the number of cycles considered within a window relative to the natural period of the structure. For the analysis of the parameters specific to the RDT method, computational routines were developed using syntax compatible with OCTAVE/MATLAB R2019b. Filters were applied to isolate the natural vibration modes. The variability in the parameters demonstrates that the developed method is robust. Full article