Search Results (410)

Magnetorheological elastomers (MREs) exhibit magnetic-field-dependent stiffness and can, therefore, be used to tune the natural frequency of a dynamic vibration absorber through the applied coil current. This study evaluates the extension of a previously developed MRE-based semi-active absorber to two automotive noise, vibration, and harshness transmission paths: road-input-related subframe vibration and engine-induced seat vibration. A standard cylindrical actuator was installed below the subframe of a passenger vehicle and tested on a rough road at 10, 20, and 30 km/h. Vehicle speed was used as the operating-condition feedback variable for current selection, while additional fixed-current measurements were conducted to characterize the current-dependent response. Cabin sound pressure was measured simultaneously. A compact actuator with a lightweight resin housing was also developed for the seat application; engine speed was used as the feedback variable, and the current was selected with reference to the second-order engine excitation. The natural frequencies of both actuators increased with current, although the compact actuator had a smaller tuning range. The actuator-installed conditions produced local, current-dependent reductions in subframe and seat vibration spectra. Changes in cabin sound pressure were smaller, frequency-dependent, and not uniform. The results demonstrate the feasibility of the operating-condition-based tuning of MRE dynamic absorbers for local automotive vibration paths, while also identifying limitations associated with passive installation effects, magnetic-circuit efficiency, packaging, and multi-path cabin acoustics. Full article

Fms-related receptor tyrosine kinase 3 internal tandem duplication (FLT3-ITD) mutations occur in approximately 20–25% of patients with acute myeloid leukemia (AML) and are associated with increased relapse risk and inferior survival outcomes. Although measurable residual disease (MRD) has become a key prognostic tool for guiding post-remission treatment decisions, FLT3-ITD was historically considered a suboptimal MRD marker because of its subclonal nature, structural heterogeneity and dynamic behavior during disease evolution. In addition, FLT3-ITD has not yet been fully integrated into routine MRD monitoring due to methodological limitations and a lack of standardized workflows. The latest European LeukemiaNet (ELN)-DAVID 2025 recommendations stressed the use of ultra-high sensitivity (UHS) next-generation sequencing (NGS) technologies to detect FLT3-ITD MRD with improved precision, enabling reliable longitudinal tracking of patient-specific clones at very low variant allele frequencies (VAF). Indeed, despite prospective evidence supporting this approach remaining limited, FLT3-ITD-based MRD monitoring is emerging as a clinically relevant prognostic indicator, contributing to the identification of patients at increased risk of relapse and refining risk stratification, while also informing therapeutic decision-making, particularly in the peri-transplant setting. The present review summarizes the biological underpinnings of FLT3-ITD mutated (FLT3-ITD^mut) AML, discusses the methodological challenges of MRD detection, and critically evaluates the evolving role of MRD in refining relapse prediction, supporting post-remission therapy tailoring, and contributing to a harmonized framework for FLT3-ITD^mut AML management. Full article

Exposure to high-quality visual environments characterized by features such as structural order, biophilic/natural elements, and positive atmosphere is important for walking experience within community life circles (CLCs). However, compared with the static configuration of visual environments within CLCs, dynamic walking-based exposure may highlight unpredictable encounter areas and heterogeneous environmental quality. Neglecting this mismatch may misdirect environmental interventions and limit their health-promoting potential. This study aims to integrate multidimensional visual environment features into interpretable scene clusters to improve comparability and measure configuration–exposure mismatches across CLCs at scale. We examine 1262 CLCs in Harbin, China, identifying visual scene clusters from 67,840 street-view images and extracting exposure frequencies from 981,500 mobility tracks. The results show that (1) eight scene clusters effectively describe the complex visual environments of CLCs; (2) significant small-to-moderate mismatches exist between configuration and exposure; (3) the trend of commute-related walking activity is often consistent with strengthened exposure to high-disorder scenes and weakened exposure to some high-quality scenes with positive atmospheres. This study provides a data-driven framework for identifying mismatches in both the intensity and spatial distribution of visual scene configuration and exposure, supporting refined community environmental governance. Full article

To reduce ram deflection and positional deviation at the boring spindle front end of a floor-type milling and boring machine under large extension, a ram-boring spindle assembly was investigated. A finite element model was established based on the actual structure, guideway support, and spindle assembly. Gravity-induced deformation and vertical displacement at the boring spindle front end under different extension conditions were analyzed to identify weak regions. The Solid Isotropic Material with Penalization method was then used to optimize the adjustable internal region of the ram with the objective of reducing structural compliance. The topology–density distribution and the deformation characteristics under different extension conditions were then used to guide an engineering reconstruction of the internal stiffeners, considering casting, assembly, internal space constraints, and engineering experience. Static analysis, displacement testing, and modal analysis were performed to verify the optimized structure. Results show that the maximum total deformation under simultaneous maximum extension decreased from 0.10268 mm to 0.097325 mm, while the mass decreased from 2424 kg to 2363 kg. The measured vertical displacement decreased from 0.114 mm to 0.108 mm. The first six natural frequencies increased by 1.48–5.91%. The proposed reconstruction improves deformation control and dynamic performance while reducing mass. Full article

Contact-induced mistuning at the blade–disk interface is a major source of variability in the dynamic response of bladed disks, yet its identification remains challenging due to the intrinsic complexity of the contact phenomenon. Contact mistuning in this framework is defined as the variation of the contact topology at the blade–disk interface, i.e., the spatial distribution of contacting and non-contacting regions governing the mechanical interaction between components. This work proposes a data-driven framework for the identification of contact mistuning based on a reduced set of experimentally measured maps. A statistical representation of the contact space is constructed using Principal Component Analysis. This representation is subsequently exploited to generate physically consistent synthetic contact patterns. These are combined with blade intrinsic mistuning parameters to build a dataset linking contact conditions and blade variability to the natural frequencies of a disk–one-blade assembly. A k-nearest neighbors algorithm is employed for inverse identification using a subset of measured natural frequencies. The identification relies on modes selected through sensitivity analysis, and robustness is improved using a weighted distance metrics. The methodology is validated using both a reduced-order model based digital twin and experimental data. The results show accurate identification of contact patterns, confirmed through comparison of modal properties of the full mistuned assembly. Therefore, the proposed framework provides a practical tool for the experimental identification of contact mistuning in bladed disks. Full article

Accurate identification of electromagnetically induced stator vibration frequency components is essential for the online condition monitoring of hydro-generators, particularly for assessing the dynamic state of the stator core under normal operating conditions. In engineering practice, the fast Fourier transform (FFT) is widely used for vibration spectrum analysis; however, because the measured vibration response is simultaneously affected by electromagnetic excitation, mechanical rotation, hydraulic disturbance, and external harmonic interference, FFT-based spectra often contain multiple frequency components whose structural relevance is difficult to determine directly. To address this issue, this paper proposes a coupled continuous wavelet transform and power spectral density transmissibility (CWT-PSDT) method for identifying key vibration frequency components with stable time-frequency energy and inter-sensor transmissibility in hydro-generator stator vibration signals. In the proposed framework, the analytic Morlet wavelet is first employed to localize dominant energy bands in the time-frequency domain, and PSDT is then used to screen frequency components with relatively stable inter-sensor transmissibility characteristics, thereby reducing the ambiguity caused by excitation-dominated spectral components. A clamped-clamped beam model is first used for numerical validation, and the maximum identification error of the first five natural frequencies is 4.22%. Experiments on a Francis turbine-generator test rig under five operating conditions further show that the proposed method can distinguish the mechanical rotational component near 10.3 Hz from the electromagnetic-related component near 50.8 Hz, while retaining higher-order electromagnetic-related components around 150 Hz and 250 Hz. The results demonstrate that the proposed CWT-PSDT method provides a physically interpretable and data-efficient approach for extracting stator-core-related spectral features, and offers a theoretical basis for spectrum-based online monitoring and future abnormal-condition comparison of hydro-generator stator responses. Full article

Recent years have seen significant advancements in the field of structural health monitoring (SHM) using computer vision, which has steadily developed into a practical and effective technique for measuring the dynamic properties of structures. With the long-range, non-contact, and easy-to-use features of this measurement technology, some difficulties associated with utilizing conventional techniques to detect the natural frequencies of tall structures can be reduced. Because it is label-free, the method also avoids attaching physical targets or sensors to energized, difficult-to-access structures. This paper proposes a label-free computer vision measurement method, which uses a label-free detection system to determine the tracking feature points, and then tracks the feature points of the structure based on the KLT optical flow method. Finally, the natural frequencies of the structure are obtained by frequency domain analysis of the vibration signal of the feature points. Experimental studies on indoor transmission tower models and outdoor high street lamps were conducted to confirm the viability of the above technology. The test findings were compared with the measurements from a 941B accelerometer, and the impact of several aspects, such as frame rate, resolution, and measuring distance, on the accuracy of the results was examined. The test findings show that the label-free system identifies the first several natural frequencies, including the fundamental, with the modal-frequency estimates agreeing with the 941B accelerometer to within roughly 0.02–0.04 Hz across the first three modes; the larger percentage error at the fundamental reflects its low frequency rather than reduced accuracy, since the absolute discrepancies are comparable across all modes. The study’s findings may serve as a guide for developing software that will be used in the future to assess structural health monitoring using computer vision. Full article

To meet the demand for high-range and high-frequency impact acceleration measurements, a fiber Bragg grating (FBG) accelerometer with a double-sided symmetrical inclined cantilever beam structure is proposed. The sensing principle is analyzed based on inertial and FBG sensing theories, and theoretical models for sensitivity and resonant frequency are derived. Using PPA-CF material and parameter optimization, the structural dimensions of the cantilever beam, effective fiber length, and proof mass are determined through numerical simulation. Finite element modal analysis shows a first-order natural frequency of 1284 Hz, with the dominant mode being axial translation of the mass block, ensuring pure axial strain on the FBG. A drop-weight impact calibration system is established for experimental testing. Results demonstrate that the sensor achieves a resonant frequency exceeding 1333 Hz, a measurement range above 500 g, and a practical sensitivity of approximately 1.183 pm/g. The linear response exhibits a coefficient of determination, R², of 0.9875, confirming excellent linearity. The proposed accelerometer effectively balances high-frequency response and measurement accuracy, providing a reliable solution for high-frequency impact monitoring in aerospace and impact dynamics applications. Full article

Monitoring the dynamic response of structures subjected to operational loads is a key component of structural health assessment, providing valuable information for safety evaluation and maintenance planning. In the last decade, video-based measurements have received growing attention for modal identification and damage detection applications, offering a promising alternative to traditional sensor-based approaches. Unlike conventional monitoring systems, which provide discrete measurements and often require extensive instrumentation, computer vision techniques enable dense, non-contact measurements while reducing installation costs and accessibility constraints. Moreover, Motion Magnification algorithms can be combined with computer vision-based identification techniques to amplify displacements within selected frequency ranges, facilitating the detection of low-amplitude structural vibrations. In this work, a semi-automated methodology for structural identification is presented and validated through two experimental applications involving vibrating systems monitored with commercial cameras. The proposed framework combines computer vision algorithms, Motion Magnification (MM), correlation analysis, and Principal Component Analysis (PCA), the latter being adopted as a noise-reduction and dimensionality-reduction tool to extract the most informative features from large sets of time-histories. In contrast to previous studies primarily focused on damage detection and frequency evolution tracking, the present work specifically investigates the influence of key user-defined parameters on the reliability of the identified frequencies and provides practical calibration guidelines for future applications. The methodology was validated against reference measurements obtained from an optical monitoring system and it successfully identified the natural frequencies of the analysed structures with errors ranging from 0.84% to 1.75%. Sensitivity analyses performed on the region of interest size and position, as well as on the correlation threshold, demonstrated the robustness of the proposed workflow. The results confirm that the proposed approach represents a reliable, low-cost, and minimally invasive alternative to conventional dynamic monitoring techniques, while providing practical recommendations for its implementation in real-world structural health monitoring applications. Full article

Accurate identification of axial forces in beam structures with unknown boundary conditions is important for structural assessment and safety monitoring. Most existing methods are based on Euler–Bernoulli beam theory and neglect the effect of rotational inertia. This simplification may reduce the accuracy of axial force identification for short beam members. To address this limitation, this study develops an axial force identification method that accounts for rotational inertia effects. First, a free-vibration governing equation for axially loaded beam members is derived based on the Reissner energy approach. Compared with the Euler–Bernoulli beam, the derived equation further accounts for the effect of rotational inertia. Then, based on the proposed dynamic formulation, an axial force identification method applicable to beam members with unknown boundary conditions is established by utilizing measured natural frequencies and mode shapes. Finally, the effectiveness and accuracy of the proposed method are systematically validated through both numerical simulations and experimental investigations on beam members. Numerical results indicate that incorporating rotational inertia improves axial force identification accuracy compared with conventional approaches, particularly for short beam members and higher-order modes. Experimental results further confirm its effectiveness, with a maximum identification error reduction of 7.69%. Full article

Ground vibration testing (GVT) plays a key role in the validation of numerical models and the assessment of aeroelastic stability in lightweight aircraft structures. This study presents an experimental and numerical investigation of a full-scale composite flying wing unmanned aerial vehicle (UAV) intended for vertical take-off and landing operations. Due to its low structural mass and highly integrated configuration, the aircraft exhibits increased sensitivity to modeling assumptions, boundary conditions, and measurement uncertainties. A finite element model was developed in Ansys, incorporating detailed laminate definitions and the internal sandwich structure. Experimental modal testing was performed under free-free boundary conditions using an electrodynamic shaker and a distributed measurement consisting of 94 response locations. Frequency Response Functions (FRFs), coherence analysis, and the Complex Mode Indication Function (CMIF) were employed to identify the dominant structural modes. Particular attention was given to the bending and torsional modes that govern aeroelastic behavior. Comparison of experimental and numerical results showed good agreement in mode shapes, while discrepancies in natural frequencies ranged from 10.4% to 20.1%. The results demonstrate that the model adequately captures the dynamic behavior of the aircraft and provides a reliable basis for future aeroelastic and flutter analyses of lightweight composite flying wing. Full article

This paper provides a comprehensive review of recent studies on event-triggered control schemes for DC microgrids. Several event-triggered mechanisms (ETMs) are thoroughly discussed, including static, dynamic, self-triggered, and edge-based algorithms. Considering the strengths and weaknesses of these algorithms, it is found that although such ETMs can decrease communication burden in the system, they are also susceptible to communication delays, Zeno behaviour, sensitivity to control parameter changes in triggering conditions, and inability to adapt to the fluctuating nature of renewable energy sources (RESs). Furthermore, this article examines implementation challenges, including data packet loss, quantisation effects, actuator faults, and a lack of cybersecurity measures, to provide readers with a clear vision of future trends in this field. Based on the main findings of the investigation, this review paper proposes possible areas for future research, highlighting the need for event-triggered control schemes that operate in discrete time, handle delays, and adapt to varying operating conditions. Other concepts, including adaptive control parameters for triggering conditions based on machine learning, the adoption of advanced cybersecurity measures, and data-aware transmission approaches that consider both communication frequency and total data volume, are also discussed. To conduct a comprehensive review of all the above-mentioned ETMs, several databases, including IEEE Xplore, Elsevier, and MDPI, were searched using the main keywords in this field, such as event-triggered, self-triggered, and edge-based ETMs, in conjunction with DC microgrids. This facilitated an in-depth analysis of such control schemes, including their strengths and weaknesses, providing readers with a strong basis for selecting a proper control scheme suited to their future research. Full article

This study conducted shaking table tests on silo-bulk systems to enhance the understanding of their seismic performance. A novel experimental setup was designed to measure the horizontal pressure and acceleration of the bulk material against the silo wall, enabling the assessment of interaction and energy dissipation effects within the system. Dynamic characteristics, including accelerations, displacement responses, and lateral pressures of the granular particles, were recorded at various earthquake intensity levels. The influence and energy dissipation effect of the granular particles on the dynamic behavior of the silo-bulk system were analyzed, providing an experimental basis for determining the effective mass coefficient of the granular material. The results indicate that a flat-bottom circular silo-bulk system exhibits favorable seismic performance. The stiffness-to-mass ratio and natural frequency of the system decrease with increasing bulk mass. Under seismic excitation, the bulk material contributes significantly to energy dissipation and damping control within the system. The calculated effective mass coefficient ranges approximately between 0.5–0.65 for the half-full silo and 0.5–0.70 for the full silo. The acceleration amplitude and additional lateral pressure on the silo wall exceed those within the bulk material itself, with the additional lateral pressure increasing progressively along the silo height. The overpressure coefficient can reach 2.0 under high-level seismic excitation corresponding to the intensity VII. The relevant results can provide reference for the seismic design of silos. Full article

Rockfall from slope unstable rock masses is a typical geological hazard induced by brittle failure, with abrupt occurrence, limited macroscopic deformation before failure, and a short warning lead time. Conventional static analysis methods are useful for design-stage stability checks, but they cannot continuously capture structural-plane damage or update the stability state in real time. Dynamic evaluation based on structural dynamics links measurable parameters such as natural frequency, damping ratio, mode shape, vibration trajectory, wave velocity, and energy dissipation to the degradation of structural planes. This review synthesizes the dynamic behavior mechanism, parameter system, theoretical models, sensing technologies, and engineering applications for slope unstable rock masses. Different from previous reviews that mainly summarize rockfall monitoring or conventional slope stability analysis, this paper organizes the literature by failure mode, monitoring scale, model assumptions, field validation, uncertainty sources, and engineering applicability. The single-degree-of-freedom models for sliding-, toppling-, and falling-type rock masses, multi-block chain-collapse models, and data-physics dual-driven surrogate models are compared critically. Contact monitoring based on MEMS sensors, non-contact LDV monitoring, acoustic emission, microseismic monitoring, coda wave interferometry, and cloud-edge early-warning architectures are further reviewed. Key challenges include field-scale validation under heterogeneous and anisotropic geological conditions, environmental compensation, robust threshold calibration, and probabilistic linkage between dynamic indicators and failure probability. The review provides guidance for selecting dynamic evaluation models, designing field monitoring systems, and developing full-life-cycle digital-twin platforms for rockfall risk mitigation. Full article

During the harvest period, the role of lateral leaves in the dynamic behavior of the walnut (Juglans regia) branch–leaf–fruit subsystem remains unclear, and vibration harvesting parameter selection still lacks targeted guidance. To address this issue, a local walnut branch–leaf–fruit subsystem was studied by combining a discrete dynamic model, free-vibration tests, forced-vibration tests, and MATLAB simulations to investigate the effects of lateral leaf number on system dynamics. A representative single-fruit subsystem with six lateral leaves was selected, and four leaf number conditions (zero, two, four, and six) were examined. High-speed imaging was used to identify leaf motion patterns, while natural frequencies and fruit tracking point displacement responses were measured. The results showed that lateral leaves mainly exhibited three motion modes during vibration: spin, swing, and spin–swing compound motion. Under the six-leaf condition, spin motion was dominant. As the number of lateral leaves increased from 0 to 6, the first-order natural frequency decreased from 13.92 ± 6.37 Hz to 8.79 ± 4.03 Hz, a reduction of 36.8%. Forced-vibration results showed that increasing lateral leaf number significantly reduced the displacement response of the fruit tracking point in the non-excitation directions. Under the six-leaf condition, the maximum displacements in the Y- and Z-directions were reduced by 56.0% and 55.8%, respectively, compared with the leafless condition, indicating that the forced response became more concentrated in the main excitation direction. In the original MATLAB model, lateral leaves were simplified as fixed lumped mass damping elements, and the predicted results differed from the experimental trends. After introducing dynamic damping parameters matched to leaf motion patterns, the simulated trends became closer to the experimental results. These findings indicate that lateral leaf number is an important structural factor affecting the natural characteristics and directional forced responses of the walnut branch–leaf–fruit subsystem. The results provide theoretical and experimental references for optimizing vibration parameters and supporting low-damage, high-efficiency walnut vibration harvesting. Full article