Search Results (35)

Dust storms are one of the important natural hazards that affect the lives of inhabitants all around the world, especially in North Africa and the Middle East. In this study, wind speed, wind direction, and air temperature patterns are investigated in one of the dustiest cities in Sistan Basin, Zahedan City, located in southeast Iran, over a 17-year period (2004–2020) using a WRF model and ground observation data. The city is located near a dust source and is mostly affected by local dust storms. The World Meteorology Organization (WMO) dust-related codes show that the city was affected by local dust, with 52 percent of the total dust events occurring during the period (2004–2021). The city’s weather station reported that 17.5% and 43% were the minimum and maximum dusty days, respectively, during 2004–2021. The summer and July were considered the dustiest season and month in the city. Since air temperature, wind speed, and wind direction are important factors in dust rising and propagation, these meteorological factors were simulated using the Weather Research and Forecasting (WRF) model for the Zahedan weather station. The WRF model’s output was found to be highly correlated with the station data; however, the WRF simulation mostly overestimated when compared with station data during the study period (2004–2020). The model had a reasonable performance in wind class frequency distribution at the station, demonstrating that 42.6% of the wind was between 0.5 and 2, which is in good agreement with the station data (42% in the range of 0.5–2). So, the WRF model effectively simulated the wind class frequency distribution and the wind direction at Zahedan station, despite overestimating the wind speed as well as minimum, maximum, and average air temperatures during the 17-year period. Full article

In view of the problem that vibration of superstructures under vibration loads of metro trains causes, this research used a metro depot and superstructure project as its background and proposed a numerical simulation method based on the impedance analytical model and finite element model to simulate and predict the vibration and secondary noise response of subway trains affecting multi-story buildings at different locations on the ground and in the superstructure. The method’s accuracy was verified using real measurement data. The research shows that vibrations generated by subway operations vertically at lower floors remain relatively unchanged, then slowly attenuate before increasing near the top floors. Mitigation measures should primarily address four aspects: rails, fasteners, sleepers, and roadbed. The adverse effects of vibration can be controlled by reducing the excitation intensity of the vibration source, attenuating vibrations along the propagation path, and isolating vibrations in the foundation and interior of the building. This research method can quickly and accurately predict the vibration and noise conditions of superstructure properties and provide support for vibration and noise reduction in practical engineering. Full article

Leaf chlorophyll content (LCC) is an important physiological index to evaluate the photosynthetic capacity and growth health of crops. In this investigation, the focus was placed on the chlorophyll content per unit of leaf area (LCC_A) and the chlorophyll content per unit of fresh weight (LCC_W) during the tuber formation phase of potatoes in Northern Shaanxi. Ground-based hyperspectral data were acquired for this purpose to formulate the vegetation index. The correlation coefficient method was used to obtain the “trilateral” parameters with the best correlation between potato LCC_A and LCC_W, empirical vegetation index, any two-band vegetation index constructed after 0–2 fractional differential transformation (step size 0.5), and the parameters with the highest correlation among the three spectral parameters, which were divided into four combinations as model inputs. The prediction models of potato LCC_A and LCC_W were constructed using the support vector machine (SVM), random forest (RF) and back propagation neural network (BPNN) algorithms. The results showed that, compared with the “trilateral” parameter and the empirical vegetation index, the spectral index constructed by the hyperspectral reflectance after differential transformation had a stronger correlation with potato LCC_A and LCC_W. Compared with no treatment, the correlation between spectral index and potato LCC and the prediction accuracy of the model showed a trend of decreasing after initial growth with the increase in differential order. The highest correlation index after 0–2 order differential treatment is DI, and the maximum correlation coefficients are 0.787, 0.798, 0.792, 0.788 and 0.756, respectively. The maximum value of the spectral index correlation coefficient after each order differential treatment corresponds to the red edge or near-infrared band. A comprehensive comparison shows that in the LCC_A and LCC_W estimation models, the RF model has the highest accuracy when combination 3 is used as the input variable. Therefore, it is more recommended to use the LCC_A to estimate the chlorophyll content of crop leaves in the agricultural practices of the potato industry. The results of this study can enhance the scientific understanding and accurate simulation of potato canopy spectral information, provide a theoretical basis for the remote sensing inversion of crop growth, and promote the development of modern precision agriculture. Full article

Planetary boundary layer (PBL) flow over complex terrain during a cold surge event was investigated using 3-hourly radiosonde measurements in upwind, near ridge, and downwind locations of mountains in the northeastern part of Republic of Korea and using a high-resolution (333-m) numerical simulation. A cold surge occurred on 23 January 2018 and lasted for 4 days. We analyzed onset day of the cold surge when air temperature dropped rapidly. Analysis of the radiosonde data shows that the PBL was characterized by an adiabatic layer with strong capping inversion in early morning and evening as well as during daytime in the upwind and near-ridge sites. The PBL flow at the near-ridge site was strongest among three sites except at 0600 local standard time (LST) when the PBL flow in the lee was strongest. We performed high-resolution (333-m) numerical simulations using the Weather Research and Forecasting (WRF) model. The adiabatic PBL in the upwind site at 0600 LST was simulated, although its depth was underestimated. The model reproduced the strong low-level wind at 0600 LST and large wind shear during the daytime in the lee, but it did not capture the exact timing of the large wind shear. The model showed overall good performance in simulating the vertical profile of the virtual potential temperature and wind below 2 km above ground level at the three sites, with a high index of agreement (IOA) except for the wind at 1200 and 1500 LST in the lee. To examine the cause for the different behavior of PBL flow in the lee of mountains between 0600 LST and the daytime, we calculated the Froude number for PBL flow using radiosonde measurements based on reduced gravity shallow water (RGSW) theory. At 0600 LST, the upwind Froude number F₀ was close to 1, while during the daytime, it was much lower than 1. The observed lee flow behavior was consistent with the flow regime change of a single layer over an obstacle with changing F₀; the flow with a propagating lee jump changes into that with a stationary lee jump with decreasing F_0. Numerical simulation shows that the steepening of streamlines of lee-wave field leads to a jump-like structure in the lee of mountains during the daytime. Full article

The detection of subgrade distresses in ballastless track railways poses a formidable challenge due to the presence of steel interference caused by the unique characteristics of high-speed rail track slabs and the dense arrangement of the steel reinforcement mesh within them. Here, we aim to examine the influence of varying distribution patterns of steel reinforcement in ballastless tracks on the detection of subgrade distresses using ground-penetrating radar. Through a combination of on-site testing and forward modeling, this paper analyzes the interference of steel reinforcement on the detection of voids beneath the steel using electromagnetic waves. The research findings reveal that incident electromagnetic waves from the ground-penetrating radar experience attenuation near steel reinforcements, with only a fraction able to penetrate the surface layer and propagate into the subsurface through interstitial gaps between the reinforcing bars. Furthermore, this influence diminishes as the spacing between the reinforcing bars increases and the bar diameter decreases. When steel bars are distributed on the upper and lower layers, the detection results of the lower void are most significantly influenced by the interlocking of the steel bars in the two layers. These research results can offer theoretical and technical support for the detection of ailments in high-speed railway subgrades. Full article

In earthquake-prone areas, pile-anchor structures are widely employed for slope reinforcement due to their reliable performance. Current research has primarily focused on static and quasi-static analyses of slopes reinforced by using pile-anchor structures, with limited investigation into their dynamic response. In this work, the finite element method (FEM) is used to study the dynamic behavior of a pile-anchor slope system, and the extended finite element method (XFEM) is used to simulate the progressive failure processes of piles. Three different reinforcement schemes, which include no support, pile support, and pile-anchor support, are considered to examine the performance of the pile-anchor structure. The simulation results suggest that the pile-anchor structure displays a reduction of 39.6% and 40.6% in the maximum shear force and bending moment of the piles, respectively, compared to the pile structure. The XFEM is utilized to model the progressive failure process of the piles subjected to seismic loading. We find that crack initiation in the pile body near the slip surface, for both the pile supported and the pile-anchor supported conditions, occurs when the peak ground acceleration arrives. Crack growth in the piles completes in a very short period, with two distinct increments of crack area observed. The first increment occurs when the peak ground acceleration arrives and is significantly larger than the second increment. Consequently, for the seismic design of piles, it is necessary to strengthen the pile body around slip surfaces. The novelty of this paper is that we realize the simulation of crack initiation and propagation in piles subjected to seismic loading. Full article

Despite recent advances in both coupled fire modeling and measurement techniques to sample the fire environment, the fire–atmosphere coupling mechanisms that lead to fast propagating wildfires remain poorly understood. This knowledge gap adversely affects fire management when wildland fires propagate unexpectedly rapidly and shift direction due to the fire impacts on local wind conditions. In this work, we utilized observational data from the FireFlux2 prescribed burn and numerical simulations performed with a coupled fire–atmosphere model WRF-SFIRE to assess the small-scale impacts of fire on local micrometeorology under moderate wind conditions (10–12 m/s). The FireFlux2 prescribed burn provided a comprehensive observational dataset with in situ meteorological observations as well as IR measurements of fire progression. To directly quantify the effects of fire–atmosphere interactions, two WRF-SFIRE simulations were executed. One simulation was run in a two-way coupled mode in which the heat and moisture fluxes emitted from the fire were injected into the atmosphere, and the other simulation was performed in a one-way coupled mode for which the atmosphere was not affected by the fire. The difference between these two simulations was used to analyze and quantify the fire impacts on the atmospheric circulation at different sections of the fire front. The fire-released heat fluxes resulted in vertical velocities as high as 10.8 m/s at the highest measurement level (20 m above ground level) gradually diminishing with height and dropping to 7.9 m/s at 5.77 m. The fire-induced horizontal winds indicated the strongest fire-induced flow at the lowest measurement levels (as high as 3.3 m/s) gradually decreasing to less than 1 m/s at 20 m above ground level. The analysis of the simulated flow indicates significant differences between the fire-induced circulation at the fire head and on the flanks. The fire-induced circulation was much stronger near the fire head than at the flanks, where the fire did not produce particularly strong cross-fire flow and did not significantly change the lateral fire progression. However, at the head of the fire the fire-induced winds blowing across the front were the strongest and significantly accelerated fire progression. The two-way coupled simulation including the fire-induced winds produced 36.2% faster fire propagation than the one-way coupled run, and more realistically represented the fire progression. Full article

Although the numerical models can estimate the significant influence of local site conditions on the seismic propagation characteristics near the surface in many studies, they cannot feasibly predict the seismic ground motion amplification in regular engineering practice or earthquake hazard assessment due to the high computational cost and their complex implementation. In this paper, the scattering problem of trapezoidal sedimentary basins, one of the representatives of local complex sites with a relatively small model size, and simplified by practice in this type of study, was selected as the basin model. A series of standard basin models were built to quantify the relationship between the site condition parameters and the site amplification parameters (the peak ground acceleration and the hazard location). In addition, the factors that influence seismic ground motion amplification, such as the basin shape ratio, the soil depth, the basin edge dip angle, the ratio of shear wave velocity between the bedrock and the soil layer, the damping coefficient, and the fundamental frequency, were selected to investigate the sensitivity. A convolutional neural network (CNN) algorithm based on deep learning replacing traditional recursive algorithms was explored to establish a prediction model of basin amplification characteristics. By the Bayesian optimization method, the structural parameters of the CNN predicting model were selected to improve the accuracy of the prediction model. The results show that the optimized CNN models could predict the amplification characteristics of the basin better than the un-optimized CNN models. Three prediction models were established with the site condition parameters as the input parameters and their output parameters were the maximum amplification value of the peak ground acceleration (PGA), the hazard location, and their combination for each basin. To analyze the CNN’s prediction ability, each CNN model used about 80% of the data from the seismic model repose results for training and the remaining data (20%) for testing. By comparing the CNN prediction results with the FE simulation results, the accuracy and rationality of each prediction model were studied. The results show that, compared to a single numerical model, the CNN prediction results of the site amplification features could be quickly obtained by inputting the relevant parameters. Compared to recursive class models, the established CNN prediction model can directly establish the relationships among multiple input and multiple output parameters. A comparison of the three kinds of CNN models shows that the prediction accuracy of the joint parameter model was slightly lower than that of the two single-output models. Full article

The theory of equatorward moving east-west elongated auroral arcs associated with field line resonance (FLR) has been proposed for decades. However, confirming this theory requires in-situ observations of FLR within the magnetosphere and simultaneous all-sky imager observations of equatorward moving auroral arcs near satellite footpoints. In this study, we present the first observations of multiple equatorward moving auroral arcs related to impulse-excited FLR, using datasets from the WIND, Geotail satellites, and an all-sky imager at China’s Zhongshan Station (ZHS) in Antarctica. In the presented event, the ultra-low-frequency waves associated with solar wind dynamic pressure pulse was mainly toroidal mode, which is consistent with the theory that the toroidal mode waves usually related with external source. The all-sky imager located in Zhongshan station recorded several equatorward moving auroral arcs, followed by reverse propagating ones. The latitudinal width of the equatorward moving auroral arcs was on the order of 25 km and had an average equatorward propagation of ~0.37 km/s, which is very similar to the value from previous work. To better illustrate the observed evolution of auroral arcs related with the FLRs we proposed a simple model to evaluate the FACs induced by the FLRs in different latitudes. The latitudinal distribution evolution of FACs agrees well with the ground-based optical observations. Full article

In this paper, long-period ground motion is used as the dynamic input to study the performance evolution of curved tunnel lining structure under seismic wave propagation excitation. This paper presents numerical studies on seismic waves, considering propagation effect, and aims to illustrate the response principle and structural failure mechanism of tunnel structures under long-period ground motion. Firstly, based on the dynamic analysis method, the dynamic balance equation of a tunnel under the seismic wave effect was analyzed. Secondly, this equation was applied to the 3D finite element software, the corresponding numerical model and boundary conditions were established, and the parameterized numerical analysis of the tunnel was carried out. Finally, according to the numerical simulation results, the seismic response principle and structural failure mechanism of a tunnel structure under long-period ground motion were discussed. The research results show that the depth and segment thickness of the tunnel significantly affect the seismic performance of the tunnel. The seismic response mechanism of a curved tunnel is complex, which shows that the relative displacements on the left and right symmetrical positions are different. The displacement inside the curve is less than the displacement outside the curve. Compared with other types of ground motion, the near-site motion considering the seismic wave propagation effect can lead to large deformation of the tunnel, which damages the lining structure greatly, and the enhancement effect is prominent for the long shield tunnel. Full article

The ground surface near a wind turbine has a significant influence on the sound propagation from the turbine, and it is therefore important to determine the ground impedance, a quantity that characterizes the ground surface acoustically. Outdoor ground parameters required by a multi-parameter model used to calculate the ground acoustic-impedance are typically unknown, which brings inconvenience for the model use. This paper introduces a technique to determine the parameters of ground acoustic-impedance for use in a multi-parameter impedance model (for example, the Attenborough four-parameter model). The technique consists of three steps: first, the data for sound-pressure level measured at a distance from two different heights are collected, and the sound-pressure-level difference is calculated; second, in line with the experimental data and the sound-pressure-level calculation formula, the MATLAB optimization tool is used to find the optimal values of the parameters used in the impedance model; and finally, when the optimization is finished, the acoustic impedance of the ground is obtained by substituting the optimal values into the impedance model. To check the performance of the calculation, the calculated sound-pressure-level difference is compared to the experimental one. Compared with a traditional method, the technique can significantly reduce the calculation error. Full article

The dynamic interaction between the ground fissure and an oblique two-section horseshoe-shaped subway tunnel under the subway dynamic load was investigated based on a series of model tests in this study. The results indicated that the subway subway-induced vibration attenuated in different degrees when propagating in the directions in the soil layer, while the ground fissure had an attenuation effect on subway vibration. Furthermore, the vibration of the soil layer below the tunnel near the ground fissure was stronger than that of the upper soil layer, and the vibration response at the tunnel bottom was stronger than that of the arch waist and the tunnel crown. The additional contact pressure between the tunnel bottom and the soil was relatively large when the ground fissure was not active, while the additional strain at the top and bottom of the tunnel caused by the excitation was small. Moreover, when the hanging wall of the ground fissure descended, the additional contact pressure at the tunnel crown in the hanging wall and the tunnel bottom in the footwall significantly increased, and a negative additional stain was identified at those two positions. Meanwhile, a positive additional stain was identified at the tunnel crown in the footwall and the tunnel crown in the hanging wall, increasing with the descent of the hanging wall. Full article

A miniaturized four-element antenna of 20 mm × 20 mm with edge-to-edge distance of 4.9 mm between the array antennas operating from 4.6–8.6 GHz is investigated in this article. The antenna consists of 4 × integrated dipole driven elements, and complementary split ring resonator (CSRR) metacells are loaded on the both sides of each dipole arms. The loaded meta-couplers magnetically couple to dipole drivers, and the induced resonance effect improves the 10-dB impedance bandwidth (IBW) to 60.6%. To improvise the isolation between antenna elements, metallic vias are implemented that trap electromagnetic (EM)-surface waves to condense into the ground. So, the meta-couplers induce electromagnetic (EM)-propagation as surface wave trapments for radiation and decouple near-field condensed currents, acting as couplers/decouplers. The maximum isolation achieved is >−22.5 dB without any external decoupling network. The diversity parameters indicate good attributes in isotropic, indoor, and outdoor channel environments with an envelope correlation coefficient (ECC) < 0.165 and realized gain of 5.5 dBi with average radiation efficiency of 80–90% in the desired operating bands. An equivalent circuit model using lumped components is designed for the proposed four-element antenna. For validation, a prototype antenna is fabricated and measured to be implemented in 5G applications, which shows good correlation with the full-wave simulated results. Full article

Rapid urbanization and industrialization lead to severe air pollution in China, threatening public health. However, it is challenging to understand the pollutants’ spatial distributions by relying on a network of ground-based monitoring instruments, considering the incomplete dataset. To predict the spatial distribution of fine-mode particulate matter (PM_2.5) pollution near the surface, we established models based on the back propagation (BP) neural network for PM_2.5 mass concentration in North China using remote sensing products. According to our predictions, PM_2.5 mass concentrations are affected by changes in surface reflectance and the dominant particle size for different seasons. The PM_2.5 mass concentration predicted by the seasonal model shows a similar spatial pattern (high in the east but low in the west) influenced by the terrain, but shows high value in winter and low in summer. Compared to the ground-based data, our predictions agree with the spatial distribution of PM_2.5 mass concentrations, with a mean bias of +17% in the North China Plain in 2017. Furthermore, the correlation coefficients (R) of the four seasons’ instantaneous measurements are always above 0.7, indicating that the seasonal models primarily improve the PM_2.5 mass concentration prediction. Full article

Optically thin layers of tiny ice particles near the summer mesopause, known as noctilucent clouds, are of significant interest within the aeronomy and climate science communities. Ground-based optical cameras mounted at various locations in the arctic regions collect the dataset during favorable summer times. In this paper, first, we compare the performances of various deep learning-based image classifiers against a baseline machine learning model trained with support vector machine (SVM) algorithm to identify an effective and lightweight model for the classification of noctilucent clouds. The SVM classifier is trained with histogram of oriented gradient (HOG) features, and deep learning models such as SqueezeNet, ShuffleNet, MobileNet, and Resnet are fine-tuned based on the dataset. The dataset includes images observed from different locations in northern Europe with varied weather conditions. Second, we investigate the most informative pixels for the classification decision on test images. The pixel-level attributions calculated using the guide back-propagation algorithm are visualized as saliency maps. Our results indicate that the SqueezeNet model achieves an F1 score of 0.95. In addition, SqueezeNet is the lightest model used in our experiments, and the saliency maps obtained for a set of test images correspond better with relevant regions associated with noctilucent clouds. Full article