Search Results (74)

The scour protection performance of the conical structure under different slope angles, α, was investigated through numerical simulations. By solving the Navier–Stokes (N–S) equations, using the Renormalization Group (RNG) k–ε turbulence model and the Meyer-Peter and Müller (MPM) sediment transport formula, the scour protection performance, undermining process, and the flow field around the devices were fully analyzed at different slope angles. The findings indicate that the conical scour protection provides effective protection against scour damage. As the slope angle increases, greater scour depth is observed around the structure. A critical slope angle was identified between 30° and 40°, slope angle effects are obvious below the threshold; otherwise, it minimized. Undermining is the main cause of failure of such stiff scour protection, mainly driven by flow contraction and sand sliding. Upstream undermining beneath the structure is more pronounced, while the downstream undermining is largely related to the near-bed flow separation point. The critical undermining point (CUP) is proposed based on the undermining curve to distinguish the undermining state, which is critical in scour protection and structural stability. Full article

The present studies focus on the analysis of the inherent differences between temperature- and pyrolysis-based models and foster a rational and comprehensive understanding of numerical models for lightning strike damage in laminated composites. A systematic methodology combining numerical simulation and pyrolysis kinetics analysis has been developed to examine the inherent differences in damage area and depth, damage threshold, electrical conductivity characteristics, and Joule energy between temperature- and pyrolysis-based models. The results indicate that the pyrolysis-based model demonstrates closer agreement with experimental data in terms of both damage area and damage depth predictions compared to the temperature-based model. The two damage thresholds (500 °C and pyrolysis degree of 0.1) yield equivalent predictions of overall damage, but the temperature-based criterion neglects localized heating rate effects. The pyrolysis-based model exhibits significantly delayed through-thickness conductivity development during initial current conduction compared to the temperature-based model due to the influence of heating rate. This lag results in the pyrolysis-based model predicting larger damage areas and shallower penetration depths. Joule heating analysis further confirms that the pyrolysis-based model exhibits higher overall electrical resistance than the temperature-based model. Through a systematic comparison of temperature- and pyrolysis-based models, this research holds the significance of enhancing the understanding of lightning strike damage mechanisms and advancing the development of high-fidelity numerical models for predicting lightning strike damage in laminated composite. Full article

This study presents a novel probabilistic framework that combines the Duration Time Method (DTM) with the ATC-58 damage assessment procedure. The method reduces computational cost by 30% compared to incremental dynamic analysis (IDA) while maintaining < 10% error in collapse prediction for low-to-mid-rise buildings. Accordingly, this study proposes a simplified framework based on the duration time method to estimate seismic responses by considering the uncertainty associated with the record as the most important uncertainty in the seismic responses of structures, and to offer an alternative to the conventional and computationally intensive incremental time history analysis. Then, using the results of the incremental time history and duration analysis in the proposed framework on a sample frame set consisting of 34 concrete frames from 1 to 20 stories, the strengths and weaknesses of the aforementioned method have been investigated. Considering the results of this step, the prediction of probable collapse threshold modes as the most challenging type of response has been identified and investigated in more depth with the help of simple methods. Finally, and in accordance with the research objective, various parameters of seismic damage in the aforementioned frames were extracted using the results of incremental time history analysis and the proposed framework based on the duration time method and using the ATC-58 guideline procedure, and by presenting the related errors, an attempt has been made to provide the audience with a measure of accuracy in estimating damages using this method. Finally, considering the strengths and weaknesses of the proposed method and estimating the volume of calculations in different stages of damage estimation, an attempt has been made to present a strategy for predicting maximum damage based on probabilities in order to examine multiple design options. Full article

The Bekasi River Basin is highly vulnerable to severe and recurrent flooding, as evidenced by significant infrastructure and environmental damage during major events. This study investigates the catastrophic floods of 2016, 2020, 2022, and 2025 by implementing the Rainfall-Runoff-Inundation (RRI) model to simulate key hydrological processes. After validation using historical water level data, the model performed effectively, achieving the highest coefficient of determination (R² = 0.75) and lowest root mean square error (RMSE = 0.66) at Cileungsi Station. In contrast, the lowest R² = 0.02, and the highest RMSE = 3.74 at Pondok Gede Permai (PGP) Station. The results reveal a concerning trend of worsening 5-year flood events, with the 2025 flood reaching a peak inundation depth exceeding 3 m and affecting an area of 2.97 km², caused by a rainfall threshold of more than 180 mm/day. Furthermore, the model shows a rapid hydrological response, with a time lag of approximately 7 h or less between peak rainfall and flood onset across three monitoring stations. Analysis indicates these severe floods were primarily triggered by heavy rainfall combined with significant land cover changes. The findings provide valuable insights for flood prediction and mitigation strategies in this vulnerable region. Full article

Natural disasters often result in significant damage to infrastructure, generating vast amounts of debris in towns and water bodies. Timely post-disaster damage assessment is critical for enabling swift cleanup and recovery efforts. This study presents a combination of methods to efficiently estimate and analyze debris on land and on water. Specifically, analyses were conducted at Claytor Lake and Damascus, Virginia where flooding occurred as a result of Hurricane Helene on 27 September 2024. We use the Phoenix U15 motor glider equipped with the GoPro Hero 9 camera to collect aerial imagery. Orthomosaic images and 3D maps are generated using OpenDroneMap (ODM) software, version 3.5.6, providing a detailed view of the affected areas. For lake debris estimation, we employ a hybrid approach integrating machine learning-based tools and traditional techniques. Lake regions are isolated using segmentation methods, and the debris area is estimated through a combination of color thresholding and edge detection. The debris is classified based on the thickness and a volume range of debris is presented based on the data provided by the Virginia Department of Environmental Quality (VDEQ). In Damascus, debris estimation is achieved by comparing pre-disaster LiDAR data (2016) with post-disaster 3D ODM data. Furthermore, we conduct flood modeling using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) to simulate disaster impacts, estimate the flood water depth, and support urban planning efforts. The proposed methodology demonstrates the ability to deliver accurate debris estimates in a time-sensitive manner, providing valuable insights for disaster management and environmental recovery initiatives. Full article

To address the challenge of determining the borehole layout scheme in the practical application of high-pressure gas expansion rock breaking, this study takes the excavation of the safety passage at Kaixuan Road Station on the North Extension Line 2 of Chongqing Metro Line 18 as the engineering background. The rock-breaking capacity was evaluated by analyzing the damaged zone volume caused by gas expansion using FLAC3D 6.0 numerical simulation software, and vibration monitoring was conducted for the historical buildings on the surface. This study revealed the following: (1) When the borehole depth is 1.2 m and the charge length is 0.6 m, the optimal angle is 70°, with the optimal vertical and horizontal spacing between holes being 1200 mm and 2000 mm, respectively. (2) The numerical simulations indicated that by adjusting the charge density, the optimized sandstone borehole network parameters could be applied to mudstone strata, and the rock-breaking effect was similar. The difference in the volume of the damaged zones obtained in the two strata was less than 3%. (3) The vibration analysis demonstrated that the peak particle velocity generated by high-pressure gas expansion rock fracturing at the ancient building directly above was 0.06316 cm/s, which was lower than the threshold value of 0.1 cm/s and approximately 67.95% lower than that of explosive blasting. Furthermore, when the tunnel depth exceeded 29 m, the vibration velocity of surface structures remained within the safety range. The results verified the feasibility of applying the same borehole network parameters to different strata, providing theoretical support for the practical application of high-pressure gas expansion rock fracturing technology in engineering projects. Full article

This study experimentally investigated the influence of vegetation integrity, vertical architecture and morphology, flexibility, and patch length on tsunami bore attenuation and structural force reduction, using Pandanus odoratissimus (screwpine) as a model species. A key aspect of the experimental design was the simulation of vegetation breakage, defined as occurring when the tsunami water depth exceeded 80% of tree height, a critical threshold for structural failure. Results showed that vegetation under non-breaking conditions significantly attenuated water levels and hydrodynamic forces, with maximum tsunami force reductions of up to 70% for rigid and 66.5% for flexible vegetation, particularly when the patch extended further inland (i.e., longer vegetation length). In contrast, vegetation breakage led to a notable decline in protective performance, with horizontal and uplift force reductions dropping between 10.1–45.2% and 10.7–16.7%, respectively, in short patches. Flexible vegetation exhibited the greatest loss of effectiveness due to structural collapse. However, longer vegetation patches played a compensatory role, maintaining higher force reduction even under breaking conditions. Notably, broken P. odoratissimus still contributes to energy dissipation through its intact dense aerial roots that resist flow near the bed. These findings highlight the importance of maintaining vegetation integrity for effective tsunami mitigation, while also recognizing that partially damaged vegetation retains some protective function, particularly when configured in extended patches. Full article

Structural cracks are internal distresses that cannot be observed from pavement surfaces. However, the existing evaluation methods for asphalt pavement structures lack the consideration of these cracks, which are crucial for accurate pavement assessment and effective maintenance planning. This study develops a novel framework combining a three-dimensional (3D) ground penetrating radar (GPR) and finite element modeling (FEM) to evaluate the severity of structural cracks. First, the size and depth development of structural cracks on a four-layer asphalt pavement were determined using the 3D GPR. Then, the range of influence of the structural crack on structural bearing capacity was analyzed based on 3D FEM simulation model. Structural cracks have a distance-dependent diminishing influence on the deflection in the horizontal direction, with the most pronounced effects within a 20-cm width zone surrounding the cracks. Finally, two indices have been proposed: the pavement structural crack index (PSCI) to assess the depth of crack damage and the structural crack reflection ratio (SCRR) to evaluate surface reflection. Besides, PSCI and SCRR are used to classify the severities of structural cracks: none, low, and high. The threshold between none/low damage is a structural crack damage rate of 0.19%, and the threshold between low/high damage is 0.663%. An experiment on a 132-km expressway indicated that the proposed method achieved 94.4% accuracy via coring. The results also demonstrate the strong correlation between PSCI and pavement deflection (R² = 0.92), supporting performance-based maintenance strategies. The results also demonstrate the correlation between structural and surface cracks, with 65.8% of the cracked sections having both structural and surface cracks. Full article

As open-pit mining extends to greater depths, slope stability is becoming a critical factor in ensuring safe production. This issue is particularly pronounced in geological settings with weak interlayers, where sudden slope failures are more likely to occur, demanding precise and reliable stability assessment methods. In this study, a typical open-pit slope with weak interlayers was investigated. Acoustic testing and ground-penetrating radar were employed to identify rock mass structural features and delineate loose zones, enabling detailed rock mass zoning and the development of numerical simulation models for stability analysis. The results indicate that (1) the slope exhibits poor overall integrity, dominated by blocky to fragmented structures with well-developed joints and significant weak interlayers, posing a severe threat to stability; (2) in the absence of support, the slope’s dissipated energy, displacement, and plastic zone volume all exceeded the failure threshold (Δ < 0), and the safety factor was only 0.962, indicating a near-failure state; after implementing support measures, the safety factor increased to 1.31, demonstrating a significant improvement in stability; (3) prior to excavation, the energy damage index (ds) in the 1195–1240 m platform zone reached 0.82, which dropped to 0.48 after reinforcement, confirming the effectiveness of support in reducing energy damage and enhancing slope stability; (4) field monitoring data of displacement and anchor rod forces further validated the stabilizing effect of the support system, providing strong assurance for safe mine operation. By integrating cusp catastrophe theory with energy-based analysis, this study establishes a comprehensive evaluation framework for slope stability under complex geological conditions, offering substantial practical value for deep open-pit mining projects. Full article

In the Asia–Pacific, where rice is an essential crop for food security and economic activity, tropical cyclones and consecutive floods can cause substantial damage to rice fields. Humanitarian organizations have developed impact-based forecasting models to be able to trigger early actions before floods arrive. In this study we show how Sentinel-1 SAR data and Otsu thresholding can be used to estimate flooding and damage caused to rice fields, using the case study of tropical storm Talas (2017). The current most accurate global Digital Elevation Model FABDEM was used to derive flood depths. Subsequently, rice yield loss curves and rice field maps were used to estimate economic damage. Our analysis results in a total of 475 km² of inundated rice fields in seven Northern Vietnam provinces. Flood depths were mostly shallow, with 2 km² having a flood depth of more than 0.5 m. Using these flood extent and depth values with rice damage curves results in lower damage values than the ones based on ground reporting, indicating a likely underestimation of flood depth. However, this study demonstrates that Sentinel-1-derived flood maps with the high-resolution DEM can deliver rapid damage estimates, also for those areas where there is no ground-based reporting of rice damage, showing its potential to be used in impact-based forecasting model training. Full article

MIL-STD-1530D and the United States Air Force (USAF) Structures Bulletin EZ-SB-19-01 require an ability to predict the growth of naturally occurring three-dimensional cracks with crack depths equal to what they term an equivalent initial damage size (EIDS) of 0.254 mm. This requirement holds for both additively manufactured and conventionally built parts. The authors have previously presented examples of how to perform such predictions for additively manufactured (AM) Ti-6Al-4V; wire arc additively manufactured (WAAM) 18Ni 250 Maraging steel; and Boeing Space, Intelligence and Weapon Systems laser bed powder fusion (LPBF) Scalmalloy^®, which is an additively manufactured Aluminium-Scandium-Mg alloy, using the Hartman-Schijve crack growth equation. In these studies, the constants used were as determined from ASTM E647 standard tests on long cracks, and the fatigue threshold term in the Hartman-Schijve equation was set to a small value (namely, 0.1 MPa √m). This paper illustrates how this approach can also be used to predict the growth of naturally occurring three-dimensional cracks in WAAM CP-Ti (commercially pure titanium) specimens built by Solvus Global as well as in WAAM-built Inconel 718. As in the prior studies mentioned above, the constants used in this analysis were taken from prior studies into the growth of long cracks in conventionally manufactured CP-Ti and in AM Inconel 718, and the fatigue threshold term in these analyses was set to 0.1 MPa √m. These studies are complemented via a prediction of the growth of naturally occurring three-dimensional cracks in conventionally built M300 steel. Full article

Coal mining provides energy and economic benefits but also causes environmental damage, including land degradation, pollution, and surface temperature anomalies. Underground coal fires can severely impact the environment, leading to abnormal heat, ground deformation, and ecological harm. Using Landsat-9 imagery and meteorological data, we developed a new threshold-based method to detect large-scale land surface temperature anomalies (LSTAs). By analyzing multiple images from November to February, we improved the accuracy of this method. The LSTA data were integrated with topographic indexes and different coal seam depths to filter irrelevant points. A Wilcoxon test, correlation analysis, and linear regression were performed with the LSTA multi-data matrix to quantify the relationships between the topographical and temperature indexes. The results revealed significant differences in elevation (relative elevation), slope, and TWI across different coal seam depths (p < 0.001). LST distribution in November, December, and February was significantly different among the three different seam depth units (p < 0.001). Relative elevation strongly correlated with temperature. The relationship between relative elevation and temperature may change seasonally due to seasonal climatic fluctuations and heterogeneous underlying surface characteristics. Full article

In the mechanical harvesting process, pineapple fruits are prone to damage. Traditional detection methods struggle to quantitatively assess pineapple damage and often operate at slow speeds. To address these challenges, this paper proposes a pineapple mechanical damage detection method based on machine vision, which segments the damaged region and calculates its area using multiple image processing algorithms. First, both color and depth images of the damaged pineapple are captured using a RealSense depth camera, and their pixel information is aligned. Subsequently, preprocessing techniques such as grayscale conversion, contrast enhancement, and Gaussian denoising are applied to the color images to generate grayscale images with prominent damage features. Next, an image segmentation method that combines thresholding, edge detection, and morphological processing is employed to process the images and output the damage contour images with smoother boundaries. After contour-filling and isolation of the smaller connected regions, a binary image of the damaged area is generated. Finally, a calibration object with a known surface area is used to derive both the depth values and pixel area. By integrating the depth information with the pixel area of the binary image, the damaged area of the pineapple is calculated. The damage detection system was implemented in MATLAB, and the experimental results showed that compared with the actual measured damaged area, the proposed method achieved an average error of 5.67% and an area calculation accuracy of 94.33%, even under the conditions of minimal skin color differences and low image resolution. Compared to traditional manual detection, this approach increases detection speed by over 30 times. Full article

Climate changes have increased heavy rainfall, intensifying flood damage, especially along small streams with steep slopes, fast flows, and narrow widths. In Korea, nearly half of flood-related casualties occur in these regions, underscoring the need for effective flood early warning systems. However, predicting flood depths is challenging due to the complex channels and rapid flood wave propagation in small streams. This study developed a flood early warning framework (FEWF) tailored for small streams in Korea, optimizing rainfall–discharge nomographs using hydro-informatic data from four streams. The FEWF integrates a four-parameter logistic model with real-time updates with a nomograph using a robust constrained nonlinear optimization algorithm. A simplified two-level early warning system (attention and severe) is based on field-verified thresholds. Discharge predictions estimate the water depth in unmeasured cross-sections using the Manning formula, with real-time data updates allowing for the dynamic identification of the flood depth. The framework was validated during the 2022 flood event, where no inundation or bank failures were observed. By improving flood prediction and adaptive management, this framework can significantly enhance disaster response and reduce casualties in vulnerable small stream areas. Full article

Mycoplasma bovis is one of the most important pathogens in animal husbandry, and the current infection and morbidity rates are increasing year by year, causing great losses to the farming industry and seriously affecting animal welfare. In this study, we took tracheal tissues from calves infected with M. bovis to make pathological tissue sections for observation, and selected tracheal tissues for transcriptome sequencing to screen differentially expressed genes based on the threshold |log2FoldChange| > 1 and Padjust < 0.05 and functional enrichment, to explore in depth the potential mechanisms of bovine tracheal damage caused by bovine tracheitis. Experiments were conducted to observe the changes in tracheal tissues after M. bovis infection through pathological sections of the trachea of M. bovis-infected calves. From the transcriptome sequencing results, we mined the main differential genes and important metabolic pathways of M. bovis causing damage to the trachea of calves. It was found that the cricoid cartilage tissue of the trachea was congested and hemorrhagic after M. bovis infection in calves, and the pathological sections showed localized necrosis of epithelial cells, disorganization, high inflammatory cell infiltration in the interepithelial and lamina propria, and some epithelial cell detachment. Transcriptome sequencing identified 4199 DEGs, including 1378 up-regulated genes and 2821 down-regulated genes. KEGG enrichment analysis indicated that the differential genes were enriched to 59 significantly differing signaling pathways, and a number of important metabolic pathways related to tracheitis induced by M. bovis-infected calves were unearthed. The major ones included IL-17, the Toll-like receptor, JAK/STAT, the PI3K-Akt signaling pathway, etc. In this study, we found that M. bovis infection of calves caused inflammatory damage to the trachea, and transcriptome sequencing results also showed significant differences in the expression of key genes such as IL-6 inflammatory factor, CASP8, and APOA1. Full article