Search Results (131)

Urban pluvial waterlogging has become a major challenge for densely populated cities due to increasingly extreme rainfall events and the rapid expansion of impervious surfaces. In response to the growing demand for localized waterlogging risk assessments, an automated evaluation framework is proposed that integrates high-resolution digital elevation models (DEMs), rainfall scenarios, and classified building data within a GIS-based modeling system. The methodology consists of four modules: (i) design of rainfall scenarios and runoff estimation, (ii) waterlogging depth simulation based on volume-matching algorithms, (iii) construction of depth–damage curves for residential and commercial buildings, and (iv) building-level economic loss estimation though differentiated depth–damage functions for residential/commercial assets—a core innovation enabling sector-specific risk precision. A case study was conducted in the Lixia District, Jinan City, China, involving 15,317 buildings under a 50-year return period rainfall event. The total economic losses were shown to reach approximately USD 327.88 million, with residential buildings accounting for 88.6% of the total. The model achieved a mean absolute percentage error within 5% for both residential and commercial cases. The proposed framework supports high-precision, building-level urban waterlogging damage assessment and demonstrates scalability for use in other high-density urban areas. Note: all monetary values were converted from Chinese Yuan (CNY) to U.S. Dollars (USD) using an average exchange rate of 1 USD = 7.28 CNY. Full article

The skeleton curve plays a crucial role in evaluating the seismic capacity of damaged structures. The research explored the application of data-driven machine learning approaches to predict the skeleton curves of earthquake-damaged reinforced concrete (RC) columns. Various machine learning methods, including Lasso regression, K-nearest neighbor (KNN), support vector machine (SVM), decision tree, and AdaBoost, were employed to develop a machine learning prediction model (MLPM) for seismic-damaged RC columns. A substantial dataset for the MLPM was derived from finite element (FE) analysis results. The input parameters for the machine learning models included the design specifications of the numerical column model and the damage index (DI), while the coordinates of key points on the skeleton curves served as the output parameters. The findings indicated that the K-nearest neighbor algorithm exhibited the best predictive performance, particularly for the yielding and peak points. The most influential input feature for predicting peak strength was the shear span-to-effective depth ratio, followed by the DI. The ML-based models demonstrated higher efficiency than numerical simulations and theoretical calculations in predicting the skeleton curves of damaged RC columns. Full article

This article presents a numerical study of the influence of applied nonlinearities on the response of a flat slab–column structure under progressive collapse conditions. A key aspect of the work is the extension of nonlinear static analysis by considering cases of material nonlinearity combined with both linear and nonlinear geometry, using a corotational formulation and a damage-based elasto-plastic concrete model. A multi-layer shell element implemented in the OpenSees platform is used to distinguish between the strength characteristics of the concrete and reinforcement, with particular attention given to the modeling of the slab–column connection in nonlinear analyzes involving both shell and beam elements. The applied vertical pushover analysis enabled the derivation of load–displacement curves and the identification of the sequence in which plastic hinges can be formed. The development of membrane action resistance, expressed through the formation of compressive and tensile rings, is observed numerically when both material and geometric nonlinearities are simultaneously considered. Moreover, the transition from compressive membrane action to tensile membrane action occurs once the deflections reach the value equal to the effective depth of the slab. This insight may serve as an important guideline for the development of future revisions to design standards related to progressive collapse. 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

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, the effect of plastic residual strain on the corrosion behavior of ZK60 magnesium alloy was systematically revealed using a research method combining experimental characterization and numerical simulation. Based on the multiphysical field coupling theory, a numerical model containing deformation field, corrosion phase field, and material transfer field was constructed, and the dynamic simulation of plastic residual strain-induced corrosion damage was successfully realized. Tafel polarization curves obtained from electrochemical tests were fitted to the key parameters of the secondary current distribution. The kinetic parameter L controlling the corrosion rate in the phase-field model was innovatively determined by the inverse calibration method, and a quantitative relationship between the kinetics of electrochemical corrosion and the phase-field theory was established. The corrosion depth distribution of the pre-strained specimens is quantitatively characterized and the results are in agreement with the finite element simulation results. The coupled strain-corrosion analysis method proposed in this study provides a theoretical basis for the design and life prediction of corrosion resistance of components under complex stress states. Full article

In order to explore the rules for the variation in the adfreeze shear strength at the interface between frozen soil and a pile foundation, and their influencing factors, a measuring system was developed to estimate the freezing strength at the interface by utilizing a pile-pressing method under a cryogenic environment. Experimental results demonstrate that the maximum vertical pressure on the pile top increased significantly with the decrease in temperature under the same moisture content. The shear stress–shear displacement curves, at the bottom part of the interface, presented strain-softening characteristics, while the strain-hardening phenomenon was observed at the upper part of the interface. The strength parameters of the interface decreased with the increase in the pile depth. Moreover, the influence of temperature on the shear strength of the interface was more significant compared with that of the moisture content. The research results can provide references for the construction of pile foundations, structural design optimization, and for frozen damage prevention and treatment in permafrost regions. Full article

Seismic risk assessment is pivotal for ensuring the reliability of prefabricated subway stations, where selecting optimal intensity measures (IMs) critically enhances probabilistic seismic demand models and fragility analysis. While peak ground acceleration (PGA) is widely adopted for above-ground structures, its suitability for underground systems remains debated due to distinct dynamic behaviors. This study identifies the most appropriate IMs for soft soil-embedded prefabricated subway stations at varying depths through nonlinear finite element modeling and develops corresponding fragility curves. A soil–structure interaction model was developed to systematically compare seismic responses of shallow-buried, medium-buried, and deep-buried stations under diverse intensities. Incremental dynamic analysis was employed to construct probabilistic demand models, while candidate IMs (PGA, PGV, and v_rms) were evaluated using a multi-criteria framework assessing correlation, efficiency, practicality, and proficiency. The results demonstrate that burial depth significantly influences IM selection: PGA performs optimally for shallow depths, peak ground velocity (PGV) excels for medium depths, and root mean square velocity (v_rms) proves most effective for deep-buried stations. Based on these optimized IMs, seismic fragility curves were generated, quantifying damage probability characteristics across burial conditions. The study provides a transferable IM selection methodology, advancing seismic risk assessment accuracy for prefabricated underground infrastructure. Through a systematic investigation of the correlation between IM applicability and burial depth, coupled with the development of fragility relationships, this study establishes a robust technical framework for enhancing the seismic performance of subway stations, and provides valuable insights for seismic risk assessment methodologies in underground infrastructure systems. Full article

As mineral resource extraction progresses to greater depths, it has become imperative for geomechanical applications to understand the thermomechanical degradation mechanisms of rocks under thermal loading. To investigate the thermomechanical characteristics of granite subjected to thermal treatments ranging from ambient to 1000 °C, we conducted uniaxial compression tests integrating P-wave velocity measurements, digital image correlation (DIC), and acoustic emission (AE) monitoring. The key findings reveal the following: (1) the specimen volume exhibits thermal expansion while the mass loss and P-wave velocity reduction demonstrate a temperature dependence; (2) the uniaxial compressive strength (UCS) and elastic modulus display progressive thermal degradation, while the peak strain shows an inverse relationship with temperature; (3) acoustic emission signals exhibit a strong correlation with failure–time curves, progressing through three distinct phases: quiescent, progressive accumulation, and accelerated failure, and fracture mechanisms transition progressively from tensile-dominated brittle failure to shear-induced ductile failure with increasing thermal loading; and (4) the damage evolution parameter exhibits exponential growth beyond 600 °C, reaching 98.85% at 1000 °C, where specimens demonstrate a complete loss of load-bearing capacity. These findings provide critical insights for designing deep geological engineering systems involving thermomechanical rock interactions. Full article

Background: Despite the vast evidence of the beneficial effect of vagus nerve stimulation on the course of myocardial infarction confirmed in studies using animal models, the introduction of this method into actual clinical practice remains uncommon. Objective: The objective of our study was to evaluate the effect of transcutaneous vagus nerve stimulation (tVNS) on in-hospital and long-term outcomes for patients with ST-elevation myocardial infarction. Materials and Methods: A blind, randomized, placebo-controlled clinical trial was conducted. The participants were randomly split into two groups. The Active tVNS group was subjected to stimulation of the tragus containing the auricular branch of the vagus nerve. The Sham tVNS group underwent stimulation of the lobule. Stimulation was performed immediately on admission before the start of the percutaneous coronary intervention (PCI). Then, tVNS continued throughout the entire PCI procedure and 30 min after its completion. The primary endpoints were hospital mortality and 12-month mortality. The secondary endpoints were in-hospital and remote non-lethal cardiovascular events. The combined endpoint consisted of major adverse cardiovascular events (MACEs)—recurrent myocardial infarction, stroke/TIA, and overall mortality. Results: A total of 110 patients were randomized into the Active tVNS group (n = 55) and the Sham tVNS group (n = 55). The incidences of hospital mortality, cardiogenic shock, and AV block 3 were statistically less common in the Active tVNS group than in the Sham tVNS group (p = 0.024*, p = 0.044*, and p = 0.013*, respectively). In the long-term period, no statistical differences were found in the studied outcomes obtained following the construction of Kaplan–Meyer survival curves. When comparing groups by total mortality, taking into account hospital mortality, we observed a tendency for the survival curves to diverge (Logrank test, p = 0.066). Statistical significance was revealed by the composite endpoint, taking into account hospital events (Logrank test, p = 0.0016*). Conclusions: tVNS significantly reduced hospital mortality (p = 0.024*), the level of markers of myocardial damage, and the frequency of severe cardiac arrhythmias in patients with acute myocardial infarction. In the long term, the prognostic value of tVNS was revealed by the composite endpoint major adverse cardiovascular events. Further studies with an expanded sample are needed for a more detailed verification of the data obtained to confirm the effectiveness of tVNS and allow an in-depth analysis of the safety and feasibility of its use in routine clinical practice. This clinical trial is registered with ClinicalTrials database under a unique identifier: NCT05992259. Full article

Laser-induced breakdown spectroscopy (LIBS) is widely used for online quantitative analysis in industries due to its rapid analysis and minimal damage. However, challenges like signal instability, matrix effects, and self-absorption hinder the measurement accuracy. Recent approaches, including the internal standard method and crater limitation method, aim to improve the stability but suffer from high computational demands or complexity. This study proposes a method to enhance LIBS stability by utilizing craters formed from laser ablation without external cavity assistance. It first improves the plasma temperature calculation reliability using multiple elemental spectral lines, after which electron density calculations are performed. By fitting plasma parameter curves based on laser pulse counts and using a laser confocal microscope for crater analysis, stable plasma conditions were found within crater areas of 0.400 mm² to 0.443 mm² and depths of 0.357 mm to 0.412 mm. Testing with elemental spectral lines of Ti II, K II, Ca I, and Fe I showed a significant reduction in the relative standard deviation (RSD) of the LIBS spectral line intensity, demonstrating an improved signal stability within specified crater dimensions. Full article

The cyclic behavior of reinforced concrete (RC) beam–column joints (BCJs) is still one of the critical issues in structural engineering. In this context, for the purpose of gaining a more in-depth insight about the sophisticated behavior of BCJs under cyclic loading scenarios, the current work aims to investigate the cyclic behavior of reinforced concrete beam–column joints. The cyclic behavior of four interior reinforced concrete beam–column joints, with plain and deformed bars, which are representative of the seismically non-conforming structures from the 1970s, were experimentally investigated. The corresponding results of the specimens were compared with each other to better understand and highlight the differences between the force–drift curves and envelopes and damage patterns of each of the specimens. Furthermore, a numerical validation of the laboratory testing results was established with the DIANA FEA code for both monotonic and cyclic loading scenarios, and the force–displacement plots were compared with the associated laboratory results for validation purposes. The crack propagation and final damage states of the numerical models of beam–column joints are presented and discussed in detail. The results showed good agreement between the numerical and experimental behavior, and a graphical representation of the critical regions affected by damages was also shown, which could ultimately contribute to future retrofitting solutions for strengthening the BCJ region in existing RC structures. Full article

The accurate calibration of snow parameters is necessary to establish an accurate simulation model of snow, which is generally used to study tire–snow interaction. In this paper, an innovative parameter inversion method based on in situ test results is proposed to calibrate the snow parameters, which avoids the damage to the mechanical properties of snow when making test samples using traditional test methods. A coupled Eulerian–Lagrangian (CEL) model of plate loading in snow was established; the sensitivity of snow parameters to the macroscopic load–sinkage relationship was studied; a plate-loading experiment was carried out; and the parameters of snow at the experimental site were inverted. The parameter inversion results from the snow model were verified by the experimental test results of different snow depths and different plate sizes. The results show the following: (1) The material cohesive, angle of friction, and hardening law of snow have great influence on the load–sinkage relationship of snow, the elastic modulus has a great influence on the unloading/reloading stiffness of snow, and the influence of density and Poisson’s ratio on the load–sinkage relationship can be ignored. (2) The correlation coefficient between the inversion result and the matching test data is 0.979, which is 0.304 higher than that of the initial inversion curve. (3) The load–sinkage relationship of snow with different snow depths and plate diameters was simulated by using the model parameter of inversion, and the results were compared with the experimental results. The minimum correlation coefficient was 0.87, indicating that the snow parameter inversion method in this paper can calibrate the snow parameters of the test site accurately. Full article

Cotton topping is a crucial aspect of cotton production, inhibiting apical dominance in cotton plants. Existing cotton topping machinery often results in over-topping. To address this challenge, the characteristics of manual topping operations were emulated by incorporating bionic principles to analyze the motions involved. Studying the artificial topping action and the trajectory of hand movements led to the design of a bionic topping manipulator and a trajectory-generating mechanism, serving as the core component of the cotton topping device. A flat-bottomed follower disc cam mechanism was used to facilitate the automatic opening and closing of the manipulator. The cam’s working area was divided, its contour curve selected, and the manipulator’s pulling spring’s action point and length determined. Subsequently, parametric equations for the motion trajectory of the bionic topping manipulator were established. Building on the topping mechanism’s working principle, a mechanical model was developed to analyze the swing of cotton plants. The model demonstrates that the displacement at the free end of the stalk was primarily influenced by its length. A lifter was then designed to reduce plant swing amplitude and orderly distribute its top position. The designed prototype of a single-row cotton bionic topping device was tested and verified through orthogonal tests, using operating speed, rotational speed, and topping depth as test factors. The topping rate and over-topping rate served as the indices for testing. The results indicated an average topping rate of 78.67% and an over-topping rate of 8%. This was achieved at a 0.3 m/s operating speed, a 40 r/min rotational speed, and a 110 mm topping depth. Cotton topping devices demonstrated greater effectiveness in minimizing damage to cotton plants, and future research should focus on enhancing topping rates even further. This study provides a theoretical foundation and test data to support the design of cotton topping machinery, guiding future mechanical improvements and agricultural practices. Full article

A thermal protection system is critical for ensuring the safe take-off and return of various aircraft. A key heat-resistant material within this system is the ceramic fiber insulation tile (CFIT), which is a porous three-dimensional network material with density ranges from 0.3 to 0.4 g/cm³ that exhibits complex mechanical behaviors. Due to the complexity of the service environment, experimental methods cannot accurately capture the mechanical behavior of a CFIT. Although simulation-based methods can provide insights, an accurate constitutive model for CFITs has yet to be established. To predict its complex mechanical behavior, an elastic–plastic damage constitutive model was established for CFITs. Based on the Hashin criteria and four fundamental assumptions, a yield rule was modified by introducing a damage factor in the TTT direction. The model was encoded into a user–material subroutine (UAMT) integrated within ABAQUS to capture the mechanical responses under four typical working conditions. The change trend of the simulation curve closely aligned with that of the experiment curve, better characterizing the stress–strain relationship of the CFIT under different working conditions such as compression, tension, and shear and the error was less than 18%. The proposed approach was validated by designing a millimeter-level indentation experiment. The results in this paper demonstrate that the maximum loading depths of the simulation and experiment were consistent, and the relative errors were within 12%, respectively. The research provides a reliable elastic–plastic damage constitutive model to predict the mechanical behavior of CFITs under complex working conditions. Full article