Search Results (208)

Prestressed and post-tensioned concrete structural elements constitute approximately 43.4% of modern bridge infrastructure, representing 58.2% of the total bridge surface area due to their long-span capabilities. Despite their structural efficiency, evaluating residual post-tensioning forces and diagnosing localized degradation within internally grouted tendons—such as localized stress corrosion cracking (SCC), grout voids, and moisture infiltration—remains a critical challenge due to geometric confinement and high material attenuation. This paper presents a non-destructive Structural Health Monitoring (SHM) methodology optimized for the continuous and periodic assessment of post-tensioned anchorage zones under operational traffic loads. The proposed Identification of Active Anomalies (IAA) system integrates the Acoustic Emission (AE) method with unsupervised machine learning to classify multi-mechanism structural degradation. By implementing a mathematically transparent k-means clustering framework initialized via the k-means++ heuristic, high-velocity multi-parameter AE data streams are partitioned within an n-dimensional Euclidean feature space. The scientific novelty of this work lies in its real-scale validation on an operational, highly complex cable-stayed bridge, establishing a previously unpublished acoustic signature database (the 2025 Signal Database). The empirical validity of the algorithm’s predictive boundaries was confirmed through forensic physical inspections and material sampling during a major structural rehabilitation in 2026, which corroborated the active corrosion states within heavily confined post-tensioned anchorage blocks. Furthermore, extracted AE pattern classes are explicitly correlated with structural crack opening widths, enabling real-time tracking of macro-defect propagation, anchorage slippage, and active micro-structural corrosion. Full article

Accurate crack width measurement is essential for the condition assessment of reinforced concrete (RC) bridges, yet most unmanned aerial vehicle (UAV) inspections remain limited to pixel-level observations that cannot be converted into reliable metric units without an external scale reference. This paper presents a lightweight, drone-agnostic UAV-mounted metrology system that enables standards-aligned metric crack width measurement directly from inspection imagery. The payload integrates a focusable diffractive optical element (DOE) red laser that projects a cross pattern of known angular geometry, three TF-Luna time-of-flight (ToF) distance sensors, and an ESP-WROOM-32 microcontroller that provides dual-rate sampling, Bluetooth Low Energy (BLE) streaming, and on-board logging. A two-stage calibration links the synchronized distance measurements to the physical length of the projected cross, yielding an image-specific pixel-to-millimeter scale that is applied to pixel-level crack widths obtained from a vision-based segmentation pipeline. The system is field-deployed on the Puente Huamani Bridge in Pisco, Peru, where measurements of 39 cracks classified under AASHTO MBEI condition states are compared against independent manual measurements by six inspectors. The proposed system reduces measurement variability across all condition states (CS), lowering the average coefficient of variation from 0.36 to 0.10 for fine CS1 cracks, from 0.27 to 0.11 for CS2, and from 0.22 to 0.07 for CS3. Cross-platform adaptability is demonstrated through an additional deployment on a DJI Matrice 350 RTK at the Low Level Bridge in Edmonton, Canada. The results indicate that the system provides a practical, low-cost, and scalable solution for repeatable, standards-aligned UAV-based bridge crack assessment. Full article

The dominance and impact of pronounced thermal buoyancy effects on the thermal and hydrodynamic properties of a horizontally heated cylinder of circular configuration immersed in a vertically ascending laminar flow stream have been numerically investigated. The dynamics are determined by numerically solving the standard energy and two-dimensional laminar Navier–Stokes equations and by incorporating buoyancy through the Boussinesq approximation in the mixed-convection co-flow configuration. The Reynolds number ($Re$) is varied within the range of $80\le Re\le 160$, while the Prandtl number $\left(Pr\right)$ is maintained constant at 0.71. The thermal buoyancy effect of the co-flow configuration is assessed by altering the Richardson number ($0\le Ri\le 1$). The code is validated against and compared against several numerical and experimental results, and its strong prediction capabilities are confirmed. This study examines significantly observed von Kármán vortices and their disappearance at above a threshold Richardson number, which has been identified as the critical Richardson number. This study provides a detailed explanation of a new phenomenon, termed ‘vortex switching’, which arises from the interaction between inertia–buoyancy interactions. The study showcases representative patterns of vorticity, streamlines, and isotherms while also plotting the average Nusselt numbers against the $Ri$ for various $Re$. Furthermore, it offers a correlation for the changes in wake width, recirculation bubble length, and vortex switching length, which are essential for optimizing design and enhancing thermal efficiency. Lastly, the thermal characteristics provide deeper insights into the impact of thermal buoyancy on wake dynamics and heat transfer. Full article

Concentration polarization is a common phenomenon in membrane separation processes and generally impairs mass transfer efficiency. Electrodialysis (ED) is considered a promising technology for concentrating high-salinity solutions used in air-conditioning systems; however, concentration polarization under high-concentration operating conditions remains insufficiently understood. In this study, a numerical framework combining a simplified model and a coupled transport model was developed to characterize concentration distributions within an ED concentrate channel. The effects of flow velocity, current density, and feed concentration on concentration profiles were systematically investigated. The results show that transmembrane water transport plays an important role in concentration polarization, and neglecting this effect leads to significant overestimation of ion concentration near the membrane surface. Although ion concentration increases markedly in the vicinity of the ion-exchange membranes, it remains nearly constant in the bulk region along the flow direction. Based on this non-uniform concentration distribution, a conceptual ED configuration with separated flow channels was proposed and evaluated. The results indicate that selectively extracting the enriched boundary-layer region can enhance the outlet concentration of the product stream, whereas increasing the intermediate channel width reduces volumetric yield, revealing a clear trade-off between concentration enhancement and production capacity. Full article

Robust monitoring of weld pool dynamics is critical for automated arc welding; however, single-modality sensors are frequently constrained by severe optical interference and high-frequency environmental noise. To address these limitations, we propose M2WPR-Net, a novel multimodal framework that synergizes visual and acoustic signals for simultaneous weld width regression and physical quality classification. The architecture employs a dual-stream ResNet50 backbone to process heterogeneous sensory data. Specifically, the visual stream utilizes a Convolutional Block Attention Module (CBAM) to suppress intense arc glare and localize the weld pool. Concurrently, the acoustic stream transforms 1D audio sequences into 2D Gramian Angular Summation Field (GASF) textures, which are subsequently refined by Squeeze-and-Excitation (SE) networks to isolate target frequency channels. A central contribution of this study is a bidirectional cross-modal attention mechanism based on Query–Key–Value (Q-K-V) matrix operations. Overcoming the shortcomings of static feature concatenation, this module dynamically aligns the modalities, enabling acoustic cues to guide visual feature extraction and vice versa, thereby mitigating information bottlenecks. Optimized via a joint multi-task loss function, the proposed M2WPR-Net significantly outperforms existing single-modal and conventional fusion baselines. Experimental results demonstrate that the network achieves a Mean Absolute Error (MAE) of 0.18 mm for width prediction and a 93.5% accuracy in penetration state classification, confirming its resilience and practical applicability in complex industrial welding environments. Full article

Fe-Cr-C-based coatings were fabricated on Q690 steel via ultrasonic vibration-assisted plasma cladding at varying ultrasonic powers (0–65 W) with a fixed frequency of 18.5 kHz. The coatings primarily consisted of martensite, retained austenite, and (Cr,Fe)₇C₃ carbides, along with (Cr,Fe,Mo)-B borides along grain boundaries. Increasing ultrasonic power promoted cavitation and acoustic streaming, which refined columnar dendrites, reduced elemental segregation (notably for B and Mo), and increased the fraction of fine equiaxed grains without altering phase composition. As a result, the average microhardness increased from 797.1 to 828.5 HV0.1. The friction coefficient decreased from 0.675 to 0.626, while the wear-track width, wear depth, and wear mass loss decreased from 4.0 mm to 2.5 mm, from 112.5 μm to 32.4 μm, and from 20.40 mg to 4.75 mg, respectively. The wear mechanism shifted from severe adhesive wear to mild abrasive wear. These results demonstrate that increasing ultrasonic vibration power effectively refines the solidification microstructure and significantly improves the hardness and wear resistance of plasma-clad Fe-Cr-C-based coatings. Full article

Headwater stream dynamics are vital for understanding hydrological and ecological processes in watersheds; however, traditional monitoring methods can be costly and time-consuming. This technical note documents the limitations and challenges encountered when deploying a low-cost camera system for continuous streamflow monitoring in a forested headwater stream in Ohio, USA. The study stream, with a channel width of less than 1 m and watershed of 0.4 km², is much smaller than previously studied streams. The camera system was constructed using inexpensive and easily accessible electronics, and it enabled application of large-scale particle image velocimetry (LSPIV) to videos collected at a frequency of 15 min. The application of LSPIV to much larger streams is well-established in previous studies; however, its application to extremely small headwater streams is understudied. Preliminary testing in a flume showed that this system was capable of providing accurate discharge measurements. In the field, however, a rating curve calibrated based on the LSPIV-derived flow estimates had an R² value of 0.70, which was weaker than relationships previously reported in the literature. The rating curve overestimated flows at lower channel stages and underestimated them at higher stages when compared to physical discharge measurements. Examination of the videos collected during field deployment revealed that unsteady flow conditions introduced significant variability in the rating curve analysis. Environmental noise from raindrops, illumination conditions, and leaf litter also caused erroneous flow measurements in the LSPIV results. This technical note presents a critical evaluation of the performance of LSPIV-based camera system in extremely small streams, and practitioners and researchers are advised to follow several best practices, offered as lessons learned from our study, to minimize specific sources of error during implementation. Full article

With the rapid deployment of deep neural networks (DNNs) on edge devices, traditional hardware accelerators face significant challenges in terms of data security, computational redundancy caused by sparsity, and uneven utilization of on-chip resources. This paper proposes SaE-FPGA, a secure and efficient DNN accelerator designed specifically for edge FPGA platforms. The architecture introduces three core innovations: (1) Hash-Bypass Processing Unit (HBPU): Integrating a high-speed SHA-256 hardware engine with a hash-sparse bitmap mechanism, it enables real-time data integrity verification within a single clock cycle while skipping computations for redundant zero-value data. (2) Flexible Mixed-Precision Processing Element (FMP): By reconfiguring idle BRAM and LUT resources into an active lookup table multiplication engine, it overcomes the physical bit-width limitations of DSP blocks and supports INT8/INT6/INT4 mixed-precision multiplication. (3) Multi-mode Reconfigurable Streaming Frame (MRSF): A sparse-aware, elastic load balancing and data routing mechanism designed to mask long memory access latencies and ensure high hardware resource utilization. Experimental results on the Zynq 7045 platform demonstrate that SaE-FPGA reduces redundant computations by 23.2% while maintaining high precision and minimizing precision loss. The system effectively mitigates the risk of physical tampering. When tested on ResNet-50, it achieved a 27.2% improvement in energy efficiency and a 2.97× speedup compared to DSP-based FPGA solutions. Furthermore, by fully exploiting the hybrid BRAM-LUT and DSP configuration, the proposed accelerator achieves a remarkable peak throughput of 782.4 GOPS. Full article

Accurate and reproducible delineation of stream bankfull geometry remains a persistent challenge in environmental planning. To address this gap, we developed the Cross-Sections and Dimensions Tool, a semi-automated, slope-based method for extracting stream cross-sections and estimating bankfull width, elevation and depth using high-resolution elevation data. The tool applies a configurable slope threshold to identify bank edges, generates perpendicular cross-sections from a stream centreline, and stores all outputs in a structured geodatabase to ensure transparency and reproducibility. Validation against manually delineated bankfull polygons across 191 km of stream length in Greater Melbourne, Australia, demonstrated strong spatial agreement, with an average F1 score (a measure of prediction-observation overlap) of 74% and a mean absolute error of 0.64 m in bankfull elevation. The tool was most reliable in larger streams (Strahler order 5 and above) with low to moderate vegetation canopy cover (<80%). We also investigated the practical visibility limits of small or indistinct channels typically encountered by human mappers and verified that the tool did not produce unrealistic channel delineations. This approach advances geomorphic feature extraction by grounding bankfull delineation in deterministic geometry rather than hydrological recurrence or data-driven modelling. In practice, it enables scalable, transparent, and repeatable analysis of stream morphology for ecological assessment, infrastructure planning, and waterway management. Full article

The rapid inspection of urban road hazards, such as subsurface voids and pipeline damage, demands high efficiency and precision in detection technology. Conventional Ground Penetrating Radar (GPR) systems often face limitations in urban environments, including slow survey speeds, poor channel scalability, and the trade-off between shallow resolution and deep penetration. The proposed system integrates a dual-band antenna array (200 MHz and 400 MHz) to resolve the classical resolution–penetration trade-off, simultaneously capturing high-resolution shallow data and achieving deep subsurface penetration in a single pass. To overcome the sampling rate bottleneck inherent in low-cost microcontrollers, a custom Time-Division Step Multiplexing (TDSM) protocol extends the equivalent sampling period to 0.38 µs across 24 parallel channels while maintaining a 200 kHz pulse repetition rate—enabling real-time data streaming at vehicle speeds up to 70 km/h with 5 cm trace spacing. This capability directly addresses the critical challenge of traffic disruption on urban arterials caused by conventional slow-speed GPR surveys. Complementing this, a master-slave FPGA-MCU hierarchical architecture provides seamless channel scalability from 24 to 36 channels, adapting to diverse swath width requirements without hardware redesign. Laboratory physics model experiments demonstrate a penetration depth exceeding 3 m after convolutional sparse fusion of the dual-band data, covering the typical burial depth of urban utilities. This study provides a deployable high-resolution underground detection solution for rapid urban infrastructure surveys and emergency disease detection by breaking the traditional constraints of channel number, sampling rate, and detection speed, significantly reducing interference with urban main traffic. Full article

Acoustofluidics has emerged as a transformative technology for contact-free manipulation of microparticles and fluids in microscale systems. Although bulk acoustic waves (BAWs) are known to displace inhomogeneous fluids through acoustic radiation force acting at fluid interfaces, the capability of surface acoustic waves (SAWs) to produce analogous relocation phenomena remains largely unexplored. This study addresses a critical gap in acoustofluidic theory by presenting the first comprehensive finite element method investigation of SAW-driven motion of inhomogeneous fluid confined within microchannels of widths equal to one full or one-half SAW wavelength. Unlike BAW-based system that generate uniform pressure fields across channel heights, SAW devices exhibit inherently nonuniform vertical pressure distributions and intense near-boundary streaming—features that fundamentally alter fluid relocation dynamics. Our simulations demonstrate that despite high-frequency operation (6.65 MHz) and strong ARF, standing SAW fields fail to achieve stable fluid relocation in both initially stable and unstable configurations due to vertical pressure stratification and rapid floor-level streaming. Nevertheless, these same characteristics generate vigorous transverse folding flows that enable exceptionally rapid homogenization, offering a distinct acoustofluidic mechanism for on-chip mixing. These findings not only elucidate fundamental physical differences between BAW and SAW actuation in multiphase microfluidic systems but also establish design principles for SAW-induced microfluidic mixers. The results provide crucial theoretical guidance for device optimization where rapid homogenization is desired over stable stratification. Full article

Amazon streams are home to a great richness and diversity of fish, having an essential role in maintaining the aquatic ecosystem multifunctionality and global biodiversity. Here, we investigated the structure of the ichthyofauna of upland streams of the Lower Tapajós River and analyzed ecological descriptors of fish assemblages in different drainages in the rainy and dry seasons. A total of 3715 individuals from 110 species were collected. Species richness was higher during the dry season (99 species) than in the rainy season (66 species). Local environmental variables were measured or obtained from publicly accessible databases. Our results showed that ichthyofauna responds to hydrological changes in upland streams in the eastern Amazon. Abundance and richness were greatest during the dry season, with important contributions from representatives of the order Characiformes. Stream structural variables explained most of the variance in assemblage composition (adjusted R² = 0.102, p = 0.004), with channel width, depth, and canopy cover as key factors. The findings underscore the importance of assessing drainage and seasonality effects not only to understand ichthyofaunal biodiversity but also to adequately design research efforts, conservation strategies, and monitoring programs for aquatic environments in the eastern Amazon. Full article

This study examines the erosion potential of earthen spillways under the growing risks posed by changing climate and extreme flood events, which threaten the stability and safety of dam infrastructure. Specifically, it employs a machine learning approach to evaluate how readily available spillway width and stream power can predict erosion potential. Site-specific erosion prediction methods are often costly and time-consuming because they rely on extensive field investigations and physical modeling. To address these challenges, this research employs multiple machine learning algorithms, including logistic regression, Support Vector Machine, and Random Forest, on existing data to classify spillways as erodible or non-erodible cases. The Random Forest model demonstrated the best predictive performance, achieving 82.7% accuracy on the test dataset. To further interpret the reliability of model predictions, a Bayesian probability analysis was performed, revealing that when the model predicts erosion, there is a 59% probability that the dam will actually experience erosion. These results highlight how integrating existing datasets with machine learning and probabilistic reasoning can enhance dam safety assessment by considering the accuracy, efficiency, and reliability of spillway erosion predictions. Full article

This work presents a lightweight and interpretable framework for the early warning of voltage stability degradation in distribution networks, based on fractal and spectral features from flow measurements. We propose a Fast Voltage Stability Index (FVSI), which combines four independent indicators: the Detrended Fluctuation Analysis (DFA) exponent α (a proxy for long-term correlation), the width of the multifractal spectrum Δα, the slope of the spectral density β in the low-frequency range, and the $c_2$ curvature of multiscale structure functions. The indicators are calculated in sliding windows on per-node series of voltage in per unit Vpu and reactive power Q, standardized against an adaptive rolling/first-N baseline, and anomalies over time are accumulated using the Exponentially Weighted Moving Average (EWMA) and Cumulative SUM (CUSUM). A full online pipeline is implemented with robust preprocessing, automatic scaling, thresholding, and visualizations at the system level with an overview and heat maps and at the node level and panel graphs. Based on the standard IEEE 13-node scheme, we demonstrate that the Fractal Voltage Stability Index (FVSI_Fr) responds sensitively before reaching limit states by increasing α, widening Δα, a more negative $c_2$, and increasing β, locating the most vulnerable nodes and intervals. The approach is of low computational complexity, robust to noise and gaps, and compatible with real-time Phasor Measurement Unit (PMU)/Supervisory Control and Data Acquisition (SCADA) streams. The results suggest that FVSI_Fr is a useful operational signal for preventive actions (Q-support, load management/Photovoltaic System (PV)). Future work includes the calibration of weights and thresholds based on data and validation based on long field series. Full article

Cordulegaster heros is an endemic species for Central and Southeastern Europe and one of the species protected under the European Union’s Habitats Directive. To adequately protect this species and its habitats, it is of crucial importance to have detailed information on its distribution, habitat requirements and potential threats to its survival. The main aims of this study were to record Cordulegaster heros geographical and altitudinal distribution and habitat requirements (stream width, fine substrate content and habitat shading), along with the importance of protected area network in its conservation and threats to its habitats in Croatia. To achieve those aims, we investigated 201 perennial and intermittent streams across three biogeographical regions (Continental, Alpine, Mediterranean). Additionally, in a small-scale study conducted in streams located within a protected area, we assessed the species’ relationship with water quality. According to the current results, Cordulegaster heros was confirmed to reproduce in 44 perennial streams in the Continental and Alpine regions, with a significantly higher number of sites and species’ abundance recorded in the Continental region. As the species was not recorded in the Mediterranean region, its occurrence there remains unverified. The species occurred at an altitudinal range between 150 and 665 m a.s.l., with 77% of the sites being between 150 and 350 m a.s.l. It was mostly documented in streams with widths up to 250 cm, fine sediment content up to 30%, and high habitat shading (>75%). A small-scale assessment of its relationship with water parameters within a protected area revealed a significant correlation with higher concentration of oxygen and lower conductivity, confirming its requirements for clean and well-oxygenated habitats. Approximately 57% of the sites where this species was recorded are within the protected area network. However, because most known occurrences are concentrated within only one area, the Continental region, along with the rather low population densities and anthropogenic threats (e.g., deforestation, hydro-morphological alterations) present at 43% of those streams, further monitoring activities are necessary. The presented results provide a basis for further monitoring of Cordulegaster heros and its habitats in Croatia. Full article