Search Results (429)

This study aims to determine the current seismic resistance of two masonry minarets that were severely damaged during the 6 February 2023 Kahramanmaraş earthquakes, while also evaluating whether a model-updating approach based on experimental dynamic characteristics can reliably capture the actual seismic behavior and collapse mechanism of such structures under real earthquake conditions. The dynamic characteristics of the minarets were identified using Operational Modal Analysis (OMA) based on previous in-situ vibration measurements. These characteristics were used to calibrate finite element models through a model-updating process employing Multi-Criteria Decision-Making (MCDM) methods. The initial modal analyses revealed discrepancies of up to 13.7% in natural frequencies and 9.7% in mode shapes. After applying MCDM methods to a wide set of model variants, these differences were reduced to 2.0% and 9.2%, respectively, improving the agreement between numerical and experimental results. Once the most representative models were obtained, nonlinear seismic analyses were performed using actual ground motion records from the earthquake. The results included evaluations of peak displacements, base shear forces, and principal stresses. The concentration of principal stresses near the transition zone showed good qualitative agreement with the observed collapse locations, indicating a reasonable consistency between numerical results and observed damage patterns. These findings demonstrate the value of integrating OMA-based model updating with MCDM methods and support a data-driven framework for assessing the seismic performance of historical masonry structures. Full article

In intelligent vehicle navigation, efficient sensor data processing and accurate system stabilization is critical to maintain robust performance, especially when GNSS signals are unavailable or unreliable. Classical calibration methods for Inertial Measurement Units (IMUs), such as discrete and system-level calibration, fail to capture time-varying, non-linear, and non-Gaussian noise characteristics. Likewise, Kalman filters typically assume static measurement noise levels for non-holonomic constraints (NHCs), resulting in suboptimal performance in dynamic environments. Furthermore, zero-velocity detection plays a vital role in preventing error accumulation by enabling reliable zero-velocity updates during motion stops, but classical thresholding approaches often lack robustness and precision. To address these limitations, we propose a novel multitask deep neural network (MTDNN) architecture that jointly learns IMU calibration, adaptive noise level estimation for NHC, and zero-velocity detection solely from raw IMU data. This shared-encoder design is utilized to minimize computational overhead, enabling real-time deployment on resource-constrained platforms such as Raspberry Pi. The model is trained using post-processed GNSS-RTK ground truth trajectories obtained from both a proprietary dataset and the publicly available 4Seasons dataset. Experimental results confirm the proposed system’s superior accuracy, efficiency, and real-time capability in GNSS-denied conditions. Full article

Based on the Direct Probability Integral Method (DPIM), this study investigates the global seismic reliability of reinforced concrete (RC) frame structures considering the randomness of material parameters and the non-stationarity of ground motions. A doubly non-stationary ground motion model is established using evolutionary power spectrum theory combined with the spectral representation–stochastic function method. A dimensionality reduction technique is adopted to generate ground motion samples compatible with the design response spectrum. A finite element model of the RC frame is developed in Abaqus. Modal analysis and deterministic time history analysis are conducted to obtain the dynamic characteristics and seismic responses of the structure. Based on 600 representative ground motion time histories generated using the maximum frontier (MF) discrepancy sampling method, nonlinear time history analyses are performed. The DPIM is then employed to calculate the statistical characteristics of structural responses and quantify response variability, enabling a rational evaluation of the structural safety margin. Finally, based on the equivalent extreme value event theory and DPIM, the reliability of the structure under a single failure mode and the global reliability under multiple failure modes are computed. The results show that the global reliability of the structure is 82.088%, which is significantly lower than that of any single failure mode. This study provides a quantitative reference for evaluating the global seismic reliability of RC frame structures subjected to nonstationary seismic excitation. Full article

Water-surface perception is critical for autonomous surface vehicle navigation, where reliable tracking of task-relevant objects is essential for safe and robust operation. Referring multi-object tracking (RMOT) provides a flexible tracking paradigm by allowing users to specify objects of interest through natural language. However, existing RMOT benchmarks are mainly designed for ground or satellite scenes and fail to capture the distinctive visual and semantic characteristics of water-surface environments, including strong reflections, severe illumination variations, weak motion constraints, and a high proportion of small objects. To address this gap, we introduce Refer-ASV, the first RMOT dataset tailored for ASV navigation in complex water-surface scenes. Refer-ASV is constructed from real-world ASV videos and features diverse navigation scenes and fine-grained vessel categories. To facilitate systematic evaluation on Refer-ASV, we further propose RAMOT, an end-to-end baseline framework that enhances visual–language alignment throughout the tracking pipeline by improving visual–language alignment and robustness in challenging maritime environments. Experimental results show that RAMOT achieves a HOTA score of 39.97 on Refer-ASV, outperforming existing methods. Additional experiments on Refer-KITTI demonstrate its generalization ability across different scenes. Full article

Long-period ground motions (LPGMs), rich in low-frequency content, can resonate with long-period structures like high-rise buildings, leading to severe damage. As seismic design shifts from safety toward resilience, limited attention to LPGMs makes it difficult to ensure the seismic resilience of long-period structures. This study used Perform-3D software to model three high-rise reinforced concrete (RC) frame–shear wall structures with varying periods and one with infill walls for resilience assessment. The resilience indicators and seismic resilience grades under LPGMs and ordinary ground motions (OGMs) were compared using the Standard for Seismic Resilience Assessment of Buildings (GB/T38591-2020) and the Guideline for Evaluation of Seismic Resilience Assessment of Urban Engineering Systems (RISN-TG041-2022), which are national standards in China. The results show that the structural response under LPGMs is significantly different from that under OGMs. In particular, the influence of LPGMs on displacement-sensitive non-structural components is much greater than OGMs. Resilience indicators were higher under LPGMs. The presence of infill walls notably reduced resilience indicators, with a stronger effect under OGMs. Based on GB/T38591-2020, the seismic resilience of each structure generally decreases by 1–2 grades under LPGMs, while evaluations based on RISN-TG041-2022 show similar ratings under both LPGMs and OGMs. Full article

With the development of 6G communication technology, Space–Air–Ground Integrated Networks (SAGINs) have become critical infrastructure for global intelligent collaborative computing. However, federated learning deployment in SAGINs faces three severe challenges: the high dynamics of satellite orbital motion, node resource heterogeneity, and privacy vulnerabilities in data transmission. This paper proposes an adaptive compressed sensing differential privacy federated learning framework based on orbital spatiotemporal characteristics. First, we design orbital periodicity-driven time-varying sparse sensing matrices that dynamically adjust compression strategies according to satellite orbital positions, achieving intelligent communication efficiency optimization. Second, we propose an orbital predictability-based privacy budget temporal allocation mechanism and perform differential privacy noise injection in the compressed domain, establishing a compression–privacy joint optimization algorithm. Furthermore, we construct an energy–communication–privacy ternary collaborative mechanism that achieves multi-objective dynamic balance through model predictive control. Finally, we design reinforcement learning-based dynamic routing scheduling and hierarchical aggregation strategies to effectively handle the time-varying characteristics of network topology. Simulation experiments demonstrate that compared to existing methods, the proposed approach achieves 3–12% improvement in model accuracy and 30–50% enhancement in communication efficiency while maintaining differential privacy protection with dynamic privacy budget $\epsilon \in [0.1,10.0]$ and compression ratio $\rho \in [0.2,0.8]$. Unlike static compressed sensing approaches that ignore orbital periodicity, the proposed orbital-driven time-varying sensing matrices reduce reconstruction error by up to 19.4% compared to fixed-matrix baselines, validating the synergistic effectiveness of integrating orbital spatiotemporal characteristics with federated learning in 6G SAGIN deployments. The framework assumes reliable orbital propagation via SGP4/SDP4 models and does not account for Doppler frequency shifts or inter-satellite link handover delays; future extensions include scalability to mega-constellations and integration of quantum-resistant privacy mechanisms. Full article

Quantifying the vulnerability of buildings is fundamental to seismic risk mitigation, and fragility curves are among the most widely used tools for this purpose. With the growing availability and access to post-earthquake damage data from reconnaissance campaigns and measured ground motion parameters, new opportunities have emerged to derive and refine fragility models, improving the seismic damage prediction models and the quantification of seismic risk. Following the 2010 Haiti earthquake, extensive datasets were compiled that include both structural and geotechnical characteristics, as well as observed damage states for a wide range of building classes. In this study, two such datasets are employed in a complementary manner to develop disaggregated fragility models to probabilistically quantify structural damage conditioned on specific building and site attributes, rather than parameters averaged over an entire building stock. The first dataset comprises approximately 335,000 building assessment tags collected, and it is used to develop a set of baseline fragility curves conditioned on parameters such as number of stories, soil type, wall system, topography, roof type, and building age. The second dataset comprises 170 reinforced concrete buildings with more detailed and reliable information, and it is used to update the baseline fragility models using Bayesian estimation. The Bayesian updating introduces fragilities specific to the presence of captive columns and priority index, a metric representing the ratio of wall and column area to floor area. Bayesian updating is performed within a Markov Chain Monte Carlo (MCMC) framework using the Metropolis–Hastings algorithm. The resulting fragility functions reveal the high vulnerability of the Haitian building stock and demonstrate how multiple site and structural attributes influence seismic fragility. Full article

To effectively enhance the seismic performance of traditional Chinese timber structures, this study proposes a reinforcement method utilizing friction dampers. Based on the working mechanism of friction dampers and the extended discrete element theory, an analytical model for timber structures equipped with these dampers was developed and validated through shake table tests. Subsequently, dynamic analyses were conducted to systematically evaluate the enhanced seismic energy dissipation capacity of the ancient timber structures by the reinforcement of friction dampers. The friction coefficient (μ), bolt pre-tension strain (ε), and action distance (l) were selected as key parameters. A multi-objective optimization function was constructed using the weighted sum method, enabling a multi-objective parameter optimization analysis for the friction dampers to identify the optimal parameter combination under specific conditions. The results indicate that the established extended discrete element model effectively simulates the dynamic characteristics of the structure. The installation of friction dampers significantly enhanced the structure’s energy dissipation capacity and substantially reduced the peak displacement. However, due to the initial stiffness introduced by the dampers, the lateral stiffness of the column frame increased markedly, leading to a significant amplification of the acceleration response, with a maximum increase in peak acceleration reaching 77%. The multi-objective optimization analysis revealed that with weighting coefficients λ_a = λ_b = 0.5, the optimal damper parameter combination is μ = 0.36, ε = 102 με, and l = 268 mm. Under these conditions, the structural displacement response decreased by 38.5%, while the acceleration response increased by 93.7%. It is noted that the derived optimal design solutions are pertinent to the specific structural typology and ground motions considered. Full article

Historical masonry minarets are highly vulnerable to seismic actions due to their slender geometry, limited tensile capacity, and material heterogeneity. However, their response to near-fault ground motions characterized by velocity pulses remains insufficiently explored. This study investigates the seismic response of the historical Tavanlı Mosque Minaret (1894, Trabzon, Türkiye) subjected to pulse-like (PL) and non-pulse-like (NPL) near-fault ground motions. A three-dimensional finite element model (FEM) was developed in ANSYS Workbench and systematically calibrated using empirical formulations to represent the current dynamic condition of the structure. Seismic performance was evaluated through linear dynamic analyses in terms of displacement demands, principal stress distribution, and drift-ratio-based performance levels. The results indicate that model calibration significantly modifies the dynamic characteristics, increasing the fundamental frequency from 0.734 Hz to 1.126 Hz and reducing displacement demands by approximately 35–76% across the considered records. Despite this improvement, PL ground motions consistently generate more critical deformation demands than NPL motions, frequently exceeding Collapse Prevention (CP) limits even when Peak Ground Acceleration (PGA) values are relatively low. A key finding is that seismic demand cannot be reliably predicted by peak intensity measures or pulse-period ratios ($T_p/T_1$) alone; rather, velocity-related parameters and pulse coherence govern the structural response. These results demonstrate that integrating empirical model calibration with pulse-sensitive seismic analysis is essential for reliable seismic assessment and conservation planning of slender historical masonry structures located in near-fault regions. The study offers a systematic framework that integrates model calibration and pulse-sensitive seismic analysis for evaluating the drift-controlled response of slender historical masonry minarets in near-fault regions. Full article

To evaluate the seismic performance of single-degree-of-freedom (SDOF) systems under mainshock–aftershock (MS–AS) seismic excitation, nonlinear time-history analyses were conducted on SDOF systems with various parameter combinations, using 50 sets of real MS–AS sequences and 150 sets of artificial sequences generated by repetition, random, and attenuation methods. The results indicate that the ground motion characteristics of MS–AS sequences generated by the repetition, random, and attenuation methods differ from those of real MS–AS sequences, with the repetition and random methods tending to overestimate the peak ground motion parameters and acceleration response spectra of MS–AS sequences, and the attenuation method potentially underestimating them, while all three methods for generating MS–AS sequences are prone to overestimating the ground motion duration of MS–AS sequences. Residual deformation is influenced by relative yield strength coefficient (η), aftershock relative intensity (χ), post-yield stiffness ratio (r), natural vibration period (T) and the hysteresis model under MS–AS seismic excitation, and residual deformation exhibits a positive dependence on aftershock intensity (χ) and a negative dependence on post-yield stiffness ratio (r), while the relationship between residual deformation and relative yield strength coefficient (η) is influenced by the natural vibration period (T), showing a positive correlation in the short-period range and a negative correlation in the mid-to-long period range. A log-normal distribution can be adopted to describe the probability distribution of the ratio of residual deformation to peak elastic-plastic deformation subjected to MS–AS seismic excitation with different parameters. Finally, a probabilistic prediction model for residual deformation under MS–AS seismic excitation was proposed which can effectively predict residual deformation under MS–AS seismic excitation. Full article

The development of high-efficiency energy dissipation devices is crucial for mitigating the significant threat posed by seismic loads to modern buildings. Therefore, the purpose of this work is to design a novel fluid viscous inerter damper (FVID) and systematically investigate its mechanical performance through theoretical derivations, experiments, and finite element simulations. Furthermore, the impact of FVIDs on the seismic performance of structures is comprehensively evaluated. The advantage of FVID is that under external excitation, the fluid can flow through multiple channels, thereby generating inertial and damping forces to dissipate energy. The theoretical model of FVID’s output force is determined based on FVID’s construction and fluid flow characteristics. The hysteresis performance of the FVID is evaluated through cyclic loading tests, and the influence of the cross-sectional radius and number of turns of the helical tube on its output force is analyzed. By performing finite element simulations of the internal flow field of FVID, the distributions of fluid pressure and velocity at different positions within FVID are analyzed. Based on Simulink, the focus is on investigating the control effect of FVID on structural responses under non-pulse near-field ground motions, pulse-type near-field ground motions, and far-field ground motions. The results indicate that the FVID has a strong energy-dissipation capacity and can effectively reduce structural responses under different types of earthquakes. The cross-sectional radius of the helical tube is a key design parameter that determines the damper’s output force. For highly destructive pulse-type near-field ground motions, FVIDs still exhibit excellent comprehensive performance in the structure. Full article

In the 20th century, several large-magnitude earthquakes (M > 7.0) occurred in Greece and surrounding areas, some of which caused extensive structural damage and significant loss of life. Unfortunately, for these earthquakes, there was no recorded ground motion intensity data to extract information about the macroseismic intensity distribution within the affected areas. A characteristic example of such an earthquake is the M7.2 of 12 August 1953 on Cephalonia island, which led to the almost complete destruction of settlements across the Cephalonia, Zakynthos, and Ithaca islands in western Greece. Although the vulnerability of the buildings affected in 1953 substantially differs from modern structures, the intensity and spatial extent of the shaking indicate that an event of similar magnitude could, even today, place the built environment and critical infrastructure of the region at high seismic risk. This study aims to estimate peak ground acceleration and velocity (PGA–PGV) and macroseismic intensity for the Cephalonia, Zakynthos, and Ithaca islands associated with earthquake scenarios comparable to the 1953 event (M7.2), incorporating seismotectonic information about active faults linked to the historical earthquake and considering associated uncertainties. Ground motion prediction models recently developed for Greece are employed. High PGA values (0.41–0.44 g) are estimated for the M7.2 earthquake, for rock site conditions (Vs30 $\ge$ 790 m/s), covering almost the entire island of Cephalonia; these can be considered as the minimum values expected on rock site conditions for a similar earthquake scenario. Full article

Background/Objectives: During adult walking, ground reaction forces (GRFs) consistently intersect near a point above the center of mass (CoM), termed the virtual pivot point (VPP). The VPP is hypothesized to contribute to upper body stabilization. However, little is known about its presence and developmental trajectory during early childhood. This study investigated age-related differences in VPP position, variability, and GRF focusing during walking in typically developing children. Methods: Kinematic and kinetic data were collected from 29 children across three age groups: Group I (aged 1 year), Group II (aged 2–3 years), and Group III (aged 10–15 years) using markerless motion capture and force plates. VPP position relative to the CoM, its variability and GRF focusing (R²) were analyzed in sagittal plane during single support phases. Results: Across all age groups, GRFs were strongly focused toward a VPP (R² > 0.95), with no significant age-related differences in GRF focusing. In contrast, significant age-related differences emerged in VPP position and variability. The normalized vertical VPP position increased progressively from Group I (7.58 cm) to Group III (14.79 cm). Notably, in several toddlers, the VPP was located at or below the CoM, contrasting with the consistent above-CoM position observed in adolescents. Conclusions: These findings demonstrate that while GRF focusing behavior is present in toddlers who can walk independently, VPP characteristics undergo substantial developmental changes. The shifting VPP position and the decrease in variability in toddlers likely reflect progressive changes in gait mechanics and trunk stabilization strategies during childhood. Full article

Under extreme heterogeneous loading conditions in the deep sea, obtaining well-preserved and stratigraphically coherent cores is a critical challenge that requires urgent resolution. Current methods cannot directly determine the preservation of core stratigraphic information or the sampling behaviour of drill bits through experimentation. Consequently, a new evaluation method for angular velocity-based stratigraphic preservation, which is grounded in Discrete Element Method (DEM) theory, is proposed. Simulation modelling uses the Hertz–Mindlin contact model to construct a multi-scale geotechnical–drill string numerical coupling model. The drill string structure is simplified while incorporating actual geometric dimensions and material properties. By simulating and extracting particle angular velocity data under various operating conditions, a correlation is established between particle motion characteristics and the stratigraphic preservation status. Experiments were conducted on a customised drilling rig platform using specimens with deep-sea geomechanical properties consistent with the simulations. Drilling tools with multiple inner diameter specifications were configured, and multiple variable combinations of the rotational speed and feed rate were set. The degree of bedding preservation in the sampled cores was recorded synchronously. The study clarified the relationship between particle angular velocity and bedding preservation, identifying the influence patterns of parameters such as the tool inner diameter, rotational speed, and feed rate on bedding preservation. Results indicate that when the rotational speed exceeds 200 rpm and the feed rate falls below 0.018 m/s, stratigraphic distortion significantly increases; the drill bit inner diameter exhibits a non-linear negative correlation with core disturbance. This study provides theoretical underpinnings and experimental evidence for multi-parameter process optimisation in maintaining stratigraphic integrity during deep-sea submersible coring operations. Full article

This study examines residual low-order (linear and constant) phase errors in interferometric synthetic aperture radar (InSAR) when compact, high-frequency radar sensors are mounted on commercial uncrewed aerial vehicles (UAVs). Although higher carrier frequencies and shorter standoff ranges enable fine-resolution interferometry, the same characteristics—together with UAV platform instability—make the system highly vulnerable to motion-induced phase errors, which can significantly degrade or even invalidate DEM reconstruction. This paper first quantifies the admissible motion-error bounds for reliable multi-baseline phase-gradient estimation, and then introduces a post-autofocus correction scheme that estimates the residual linear term from the interferometric fringe frequency and refines it via an FFT-based correlation objective, while the constant term is calibrated using ground control points (GCPs). The method is validated through simulations of a 24 GHz UAV demonstrator. To the best of our knowledge, this work provides the first post-autofocus demonstration of linear-and-constant residual-error mitigation for UAV-based high-frequency multi-baseline InSAR. In the considered K-band setting, the proposed approach reduces the DEM error from 42 m to 0.2 m (≈98% improvement). Full article