Search Results (461)

The accurate identification of modal parameters is essential for structural health monitoring (SHM), as it provides critical insights into the presence of damage or degradation within the structure. A promising technique, stochastic subspace identification (SSI) has numerous advantages in operational modal analysis (OMA), particularly in implementing automated OMA. Hence, an improved procedure is proposed in this study, addressing the size of the SSI matrix, the estimation of system order, and the removal of spurious modes for automated modal analysis. A general instruction for user-defined parameters is first reviewed and summarized. Subsequently, a proposed procedure is then introduced and framed into three steps. Key advances include the preliminary identification of fundamental frequency, which helps the overall automated work, adequately assigning the size of the SSI matrix, which can improve decomposition, and a decay function, which provides a good estimation of system order. To demonstrate and verify the procedure, a numerical simulation of a ten-story shear-type building structure and two field datasets, collected from reinforced concrete (RC) frames in Taiwan, are utilized. Consequently, the results suggest that the proposed three-step procedure based on SSI can facilitate automated OMA for continuous and long-term SHM, in terms of autonomously adjusting user-defined parameters. Full article

An efficient numerical approach utilizing a variational weak form, grounded in 2D elastic theory and variational principles, is proposed for analyzing the in-plane vibrational behavior of rectangular plates resting on elastically restrained boundaries. The differential and integral operators can be discretized into matrix representations employing the differential quadrature method (DQM) and Taylor series expansion techniques. The discretization of dynamics equations stems directly from a weak formulation that circumvents the need for any transformation or discretization of higher-order derivatives encountered in the corresponding strong equations. Utilizing the matrix elementary transformation technique, the displacements of boundary and internal nodes are segregated, subsequently leading to the derivation of the generalized eigenvalue problem pertaining to the free vibration analysis of the Functionally Graded Material (FGM) rectangular plate. Furthermore, the study examines the impact of the gradient parameter, aspect ratio, and elastic constraints on the dimensionless frequency characteristics of the FGM rectangular plate. Ultimately, the modal properties of an in-plane FGM rectangular plate are investigated. Full article

This paper investigates the optimal planning of high-speed rail (HSR) freight operations, pricing strategies, and government carbon tax policies. The primary objective is to enhance the market share of HSR freight, thereby reducing carbon dioxide (CO₂) emissions associated with freight activities. The modal shift problem is formulated as a bi-level multi-objective model and solved using a specifically designed hybrid algorithm. The upper-level model integrates multiple objectives of the government (minimizing tax while maximizing the emission reduction rate) and HSR operators (maximizing profits). The lower-level model represents shippers’ transportation mode choices through network equilibrium modeling, aiming to minimize their costs. Numerical analysis is conducted using a transportation network that includes seven major central cities in China. The results indicate that optimizing HSR freight services with carbon tax policies can achieve a 56.97% reduction in CO₂ emissions compared to air freight only. The effectiveness of the government’s carbon tax policy in reducing CO₂ emissions depends on shippers’ emphasis on carbon reduction and the intensity of the carbon tax. Full article

With the growing need for lightweight, durable, and high-performance structures, additively manufactured (AM) polymer composite structures have captured significant attention in the engineering community. These structures offer considerable advantages in various dynamic engineering sectors including automotive, aviation, and military. Thus, this investigation emphasizes the numerical analysis of the dynamic properties and vibration control of AM polylactic acid (PLA) composite structures reinforced with continuous glass fibers (CGFR-PLA) and carbon fibers (CCFR-PLA), with 0°–0° and 0°–90° layer orientations. The findings of this numerical study are compared and validated against earlier published experimental results. Initially, the numerical models were created using the Abaqus CAE 2024, replicating the actual experimental models. The numerical bending modal frequency of each numerical model is determined, and the 0°–0° oriented models exhibited considerably higher values compared to the corresponding 0°–90° models. Significant differences were noted between the numerical and experimental values in the higher modes, mainly due to existence of voids and misalignment in the actual models that were not considered in numerical models. Following this, a numerical amplitude frequency response (AFR) analysis was conducted to observe vibration amplitude variations as a function of frequency. The AFR numerical results demonstrated consistent trends with the experimental results despite differences between the absolute values of both scenarios. Afterwards, vibration amplitude control analysis was performed under the influence of a macro fiber composite (MFC) actuator. The findings from both numerical and experimental cases revealed that vibration control was noticeably higher in 0°–0° oriented structures compared to 0°–90° structures. Experimental models demonstrated higher vibration control effectiveness than the corresponding numerical models. Although significant differences between the numerical and experimental vibration response values were observed in each composite structure, the numerical results exhibited consistent trends with the experiments. This discrepancy is attributed to the challenge of capturing all boundary conditions of the experimental scenario and incorporating them into the numerical simulation. Full article

Wheel polygonal wear of metro deteriorates the vibration environment of the vehicle system, potentially leading to resonance-induced fatigue failure of components. This poses serious risks to operational safety and increases maintenance costs. To address the adverse effects of wheel polygonal wear, dynamic tracking tests and numerical simulations were conducted. The modal analysis focused on the vehicle–track coupling system, incorporating various track structures to explore the formation mechanisms and key influencing factors of polygonization. Test results revealed dominant polygonal wear patterns of the seventh to ninth order, inducing forced vibrations in the 50–70 Hz frequency range. These frequencies closely match the P2 resonance frequency generated by wheel–rail interaction. When vehicle–track coupling is considered, the track’s frequency response shows multiple peaks within this range, indicating susceptibility to resonance excitation. Additionally, rail joint irregularities act as geometric excitation sources that trigger polygonal development, while the P2 force resonance mode plays a critical role in its amplification. Full article

The proliferation of malicious social bots poses severe threats to cybersecurity and social media information ecosystems. Existing detection methods often overlook the semantic value and emotional cues conveyed by emojis in user-generated tweets. To address this gap, we propose ESA-BotRGCN, an emoji-driven multi-modal detection framework that integrates semantic enhancement, sentiment analysis, and multi-dimensional feature modeling. Specifically, we first establish emoji–text mapping relationships using the Emoji Library, leverage GPT-4 to improve textual coherence, and generate tweet embeddings via RoBERTa. Subsequently, seven sentiment-based features are extracted to quantify statistical disparities in emotional expression patterns between bot and human accounts. An attention gating mechanism is further designed to dynamically fuse these sentiment features with user description, tweet content, numerical attributes, and categorical features. Finally, a Relational Graph Convolutional Network (RGCN) is employed to model heterogeneous social topology for robust bot detection. Experimental results on the TwiBot-20 benchmark dataset demonstrate that our method achieves a superior accuracy of 87.46%, significantly outperforming baseline models and validating the effectiveness of emoji-driven semantic and sentiment enhancement strategies. Full article

Graphene interfaces in layered dielectrics can support unique electromagnetic modes, but analyzing these modes requires robust computational techniques. This work presents a numerical method for computing TE-polarized eigenmodes in a planar stratified dielectric slab with an infinitesimally thin graphene sheet at its interface. The governing boundary-value problem is reformulated as coupled initial-value problems and solved via a customized shooting method, enabling accurate calculation of complex propagation constants and field profiles despite the discontinuity at the graphene layer. We demonstrate that the graphene significantly alters the modal spectrum, introducing complex leaky and surface waves with attenuation due to graphene’s conductivity. Numerical results illustrate how the layers’ inhomogeneity and the graphene’s surface conductivity influence mode confinement and loss. These findings confirm the robustness of the proposed computational approach and provide insights relevant to the design and analysis of graphene-based waveguiding devices. Full article

This study is titled “Success Factors in Transport Interventions: A Mixed-Method Systematic Review (1990–2022)”. The purpose of the systematic review is to (1) identify effective interventions for transitioning individuals from private car reliance to sustainable transport, (2) summarise psychosocial theories shaping transportation choices and identify enablers and barriers influencing sustainable mode adoption, and (3) determine the success factors for interventions promoting sustainable transport choices. The last search was conducted on 18 November 2022. Five databases (Scopus, Web of Science, MEDLINE, APA PsycInfo, and ProQuest) were searched using customised Boolean search strings. The identified papers were included or excluded based on the following criteria: (a) reported a modal shift from car users or cars to less CO₂-emitting modes of transport, (b) covered the adoption of low-carbon transport alternatives, (c) comprised interventions to promote sustainable transport, (d) assessed or measured the effectiveness of interventions, or (e) proposed behavioural models related to mode choice and/or psychosocial barriers or drivers for car/no-car use. The identified papers eligible for inclusion were critically appraised using Sirriyeh’s Quality Assessment Tool for Studies with Diverse Designs. Inter-rater reliability was assessed using Cohen’s Kappa to evaluate the risk of bias throughout the review process, and low-quality studies identified by the quality assessment were excluded to prevent sample bias. Qualitative data were extracted in a contextually relevant manner, preserving context and meaning to avoid the author’s bias of misinterpretation. Data were extracted using a form derived from the Joanna Briggs Institute. Data transformation and synthesis followed the recommendations of the Joanna Briggs Institution for mixed-method systematic reviews using a convergent integrated approach. Of the 7999 studies, 4 qualitative, 2 mixed-method, and 30 quantitative studies successfully passed all three screening cycles and were included in the review. Many of these studies focused on modelling individuals’ mode choice decisions from a psychological perspective. In contrast, case studies explored various transport interventions to enhance sustainability in densely populated areas. Nevertheless, the current systematic reviews do not show how individuals’ inner dispositions, such as acceptance, intention, or attitude, have evolved from before to after the implementation of schemes. Of the 11 integrated findings, 9 concerned enablers and barriers to an individual’s sustainable mode choice behaviour. In addition, two integrated findings emerged based on the effectiveness of the interventions. Although numerous interventions target public acceptance of sustainable transport, this systematic review reveals a critical knowledge gap regarding their longitudinal impact on individuals and effectiveness in influencing behavioural change. However, the study may be affected by language bias as it only included peer-reviewed articles published in English. Due to methodological heterogeneity across the studies, a meta-analysis was not feasible. Further high-quality research is needed to strengthen the evidence. This systematic review is self-funded and has been registered on the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY; Registration Number INPLASY202420011). Full article

Background: The increasing use of technologies operating between 10 and 200 kHz, such as RFID, wireless power transfer systems, and induction cooktops, raises concerns about electromagnetic interference (EMI) with cardiac implantable electronic devices (CIEDs). The mechanisms of interaction within this frequency range have been only partially addressed by both the scientific and regulatory communities. Methods: A physical twin of a pacemaker/implantable defibrillator (PM/ICD) was developed to experimentally assess voltages induced at the input stage by low-to-mid-frequency magnetic fields. The setup simulates the two sensing modalities programmable in PMs/ICDs and allows for the analysis of different implant configurations, lead geometries, and positions within a human body phantom. Results: Characterization of the physical twin demonstrated its capability to reliably measure induced voltages in the range of 5 mV to 1.5 V. Its application enabled the identification of factors beyond the implant’s induction area that contribute to the induced voltage, such as the electrode-tissue interface and body-induced currents. Conclusions: This physical twin represents a valuable tool for experimentally validating the mechanisms of EMI in CIEDs, providing insights beyond current standards. The data obtained can serve as a reference for the validation of numerical models and patient-specific digital twins. Moreover, it offers valuable information to guide future updates and revisions of international electromagnetic compatibility standards for CIEDs. Full article

This work introduces a novel approach to extract beam bridge mode shapes using the residual response between consecutive contact points of vehicles passing through a bridge. A comprehensive investigation is conducted on several critical parameters, including window size, vehicle velocity, road roughness, and beam damping property, as well as the influence of traffic flow. To enhance the mode shape extraction performance using the approximate expression of the contact points’ displacements under noisy disturbance, two new signal denoising methods, CEEMDAN-NSPCA and CEEMDAN-IWT, are proposed based on complete ensemble empirical mode decomposition (CEEMDAN). CEEMDAN-NSPCA integrates CEEMDAN with principal component analysis and a coefficient-based filtering strategy. While CEEMDAN-IWT utilizes an improved wavelet thresholding technique with adaptive threshold selection. The numerical simulations demonstrate that both methods could effectively attenuate high-frequency noise with small amplitudes and retain low-frequency components. Among them, CEEMDAN-IWT exhibits superior denoising performance and greater stability, making it particularly suitable for robust modal identification in noisy environments. Full article

The article discusses the causes of excessive noise and vibrations of a live steam pipeline in a power unit. A scanning laser vibrometer was used to measure the vibrations of the live steam pipeline for two power units. Additionally, the sound (noise) level of the live steam pipeline was measured with an acoustic camera. A discrete model of the pipeline was created, and FEM modal analysis was performed. Based on experimental tests and numerical simulations, the sources of noise were identified. The final conclusions propose methods of eliminating the harmful noise. Full article

Under cyclic moving load action, tensile-dominant structures are prone to crack initiation due to cumulative damage effects. The presence of cracks leads to structural stiffness degradation and nonlinear redistribution of dynamic characteristics, thereby compromising str18uctural integrity and service performance. The current research on the dynamic behavior of cracked structures predominantly focuses on transient analysis through high-fidelity finite element models. However, the existing methodologies encounter two critical limitations: computational inefficiency and a trade-off between model fidelity and practicality. Thus, this study presents an innovative analytical framework to investigate the dynamic response of cracked simply supported beams subjected to moving loads. The proposed methodology conceptualizes the cracked beam as a system composed of multiple interconnected sub-beams, each governed by the Euler–Bernoulli beam theory. At crack locations, massless rotational springs are employed to accurately capture the local flexibility induced by these defects. The transfer matrix method is utilized to derive explicit eigenfunctions for the cracked beam system, thereby facilitating the formulation of coupled vehicle–bridge vibration equations through modal superposition. Subsequently, dynamic response analysis is conducted using the Runge–Kutta numerical integration scheme. Extensive numerical simulations reveal the influence of critical parameters—particularly crack depth and location—on the coupled dynamic behavior of the structure subjected to moving loads. The results indicate that at a constant speed, neither crack depth nor position alters the shape of the beam’s vibration curve. The maximum deflection of beams with a 30% crack in the middle span increases by 14.96% compared to those without cracks. Furthermore, crack migration toward the mid-span results in increased mid-span displacement without changing vibration curve topology. For a constant crack depth ratio (γ_i = 0.3), the progressive migration of the crack position from 0.05 L to 0.5 L leads to a 26.4% increase in the mid-span displacement (from 5.3 mm to 6.7 mm). These findings highlight the efficacy of the proposed method in capturing the complex interactions between moving loads and cracked concrete structures, offering valuable insights for structural health monitoring and assessment. Full article

In this study, a series of comprehensive experimental tests were conducted to assess the impact of permanent displacements observed during the construction of the Cho’ponota L1 Bridge in Uzbekistan and to evaluate the bridge’s structural suitability for service. The investigation included Operational Modal Analysis and static and dynamic vehicular load tests, conducted using two trucks with different weights under varying loading scenarios and speeds. A total of 28 static and 24 dynamic load cases were tested across the bridge’s four spans. Displacement measurements were acquired using geodetic instruments during the static tests, while acceleration data were recorded during dynamic tests using high-sensitivity accelerometers, from which Dynamic Amplification Factors were calculated. The results indicated that all displacement values remained within permissible safety limits, and no visible damage or cracking was detected. Beyond conventional analysis, the study proposed a test-assisted digital twin framework in which high-fidelity field data were integrated into a finite-element model. The initial numerical model was calibrated using modal properties obtained from OMA, and discrepancies were minimized through iterative updates to material parameters, especially concrete stiffness. The resulting validated digital twin accurately reflects the bridge’s current structural condition and can be used for future predictive simulations and performance-based evaluations. The findings underscore the effectiveness of combining non-destructive testing with digital twin methodology in diagnosing structural behavior and offer a replicable model for assessing bridges experiencing construction-related anomalies. Full article

This study investigates noise detection and damping-based noise mitigation strategies for cavity structures, with a specific focus on addressing noise issues in the conveyor trough of combine harvesters. Despite its practical significance, research on the noise generation mechanisms, transmission paths, and control measures for conveyor troughs remains limited, particularly under varying operational conditions. To bridge this gap, this work integrates experimental measurements with numerical simulations to systematically analyze and optimize the noise reduction performance of the conveyor trough. Noise measurements were conducted using the sound intensity method, revealing sound pressure levels in the range of 93–95 dB. Frequency spectrum analysis identified key noise sources and dominant frequency components. Finite element analysis (FEA) and vibration modal testing were performed to uncover critical noise-inducing factors, including chain meshing impacts and structural resonances. Based on these findings, a damping optimization strategy was proposed by incorporating constrained damping layers to attenuate vibration and reduce noise in targeted frequency bands. The effectiveness of this approach was validated through multiple coherence analysis, which confirmed significant suppression of structural vibration noise in the 0–500 Hz range, while experimental results showed that the optimized conveyor trough structure achieved a maximum reduction of 0.4071 dB in continuous equivalent A-weighted sound pressure under load conditions. This research provides a comprehensive methodology for noise control and structural optimization of conveyor trough systems, offering valuable theoretical and practical insights for enhancing the operational comfort and environmental performance of combine harvesters. Full article

Cutaneous warts caused by human papillomavirus (HPV) are among the most common dermatological conditions, affecting the quality of life of numerous people. Although they are widespread, effective and reliable treatment alternatives are limited, emphasizing the necessity for novel treatment options. Intralesional immunotherapy has emerged as a promising alternative, aiming to stimulate the host immune response to achieve the clearance of both treated and distant lesions. This review explores the immunopathogenesis of cutaneous warts and provides an in-depth analysis of intralesional therapies including measles–mumps–rubella (MMR) vaccine, purified protein derivative (PPD), Bacillus Calmette–Guérin (BCG), Candida antigen, Mycobacterium w vaccine (MWV), vitamin D3, and autoinoculation. We provide a comprehensive analysis of the most promising modalities, highlighting their mechanism of action, outcomes, advantages, and limitations. Although initial data indicate that intralesional immunotherapy offers advantageous efficacy and tolerability, there is a lack of standardized treatment protocols and randomized controlled trials to endorse its broad application. Nevertheless, considering its potential to address local and distant lesions with minimal adverse effects, intralesional immunotherapy may represent a transformative approach to managing cutaneous warts. Full article