Search Results (94)

To meet the requirements for radar echo acquisition and feature extraction from stratified media and rough-surfaced targets, a vehicle was geometrically modelled in CAD. Monte Carlo techniques were applied to generate the rough interfaces at air–snow and snow–soil boundaries and over the vehicle surface. Soil complex permittivity was characterized with a four-component mixture model, while snow permittivity was described using a mixed-media dielectric model. The composite electromagnetic scattering from a rough-surfaced vehicle on snow-covered soil was then analyzed with the finite-difference time-domain (FDTD) method. Parametric studies examined how incident angle and frequency, vehicle orientation, vehicle surface root mean square (RMS) height, snow liquid water content and depth, and soil moisture influence the composite scattering coefficient. Results indicate that the coefficient oscillates with scattering angle, producing specular reflection lobes; it increases monotonically with larger incident angles, higher frequencies, greater vehicle RMS roughness, and higher snow liquid water content. By contrast, its dependence on snow thickness, vehicle orientation, and soil moisture is complex and shows no clear trend. Full article

This study investigates the mechanical behavior and safety performance of buried natural gas pipelines crossing seismically active fault zones and liquefaction-prone areas, with particular application to the China–Russia East-Route Natural Gas Pipeline. The research combines experimental testing, numerical simulation, and machine learning to develop an advanced framework for pipeline safety assessment under seismic loading conditions. A series of large-scale pipe–soil interaction experiments were conducted under seismic-frequency cyclic loading, leading to the development of a modified soil spring model that accurately captures the nonlinear soil-resistance characteristics during seismic events. Unlike prior studies focusing on static or specific seismic conditions, this work uniquely integrates real cyclic loading test data to develop a frequency-dependent soil spring model, significantly enhancing the physical basis for dynamic soil–pipeline interaction simulation. Finite element analyses were systematically performed to evaluate pipeline response under liquefaction-induced ground displacement, considering key influencing factors including liquefaction zone length, seismic wave frequency content, operational pressure, and pipe wall thickness. An innovative machine learning-based predictive model was developed by integrating LightGBM, XGBoost, and CatBoost algorithms, achieving remarkable prediction accuracy for pipeline strain (R² > 0.999, MAPE < 1%). This high accuracy represents a significant improvement over conventional analytical methods and enables rapid safety assessment. The findings provide robust theoretical support for pipeline routing and seismic design in high-risk zones, enhancing the safety and reliability of energy infrastructure. Full article

Biochar has garnered considerable attention for its potential to improve soil properties due to its unique characteristics. However, the precise measurement of soil water content using electromagnetic sensors becomes challenging after biochar is incorporated. This study investigated the impact of biochar on soil water content measurement by adding biochar of varying dosages and particle sizes to a typical loess, under both room and subzero temperature conditions by using time domain reflectometry (TDR) and frequency domain reflectometry (FDR) techniques. The results demonstrate that biochar amendment significantly influenced the measurement accuracy of both TDR and FDR. A clear dosage-dependent relationship was observed, with measurement errors exhibiting progressive escalation as biochar addition rates increased. At room temperature, the root mean square error (RMSE) values for loess were remarkably low (TDR: 0.029; FDR: 0.093). In contrast, the 9% coarse-grained biochar-amended soil (BAS-9%C) showed substantially elevated RMSE values (TDR: 0.2006; FDR: 0.1468). Furthermore, comparative analysis revealed that particle size significantly affected measurement precision, with coarse-grained biochar demonstrating more pronounced interference effects than fine-grained biochar at equivalent application rates. At subzero temperatures, BAS-6%C exhibited significantly higher RMSE values (TDR: 0.1753; FDR: 0.2022) compared to BAS-6%F (TDR: 0.079; FDR: 0.1872). A dielectric mixing model was established for calculating the dielectric constant of BAS. In addition, calibration equations for accurately determining the water content of biochar-amended loess under both room and subzero temperature conditions were established. Furthermore, the mechanisms by which biochar influenced the performance of the TDR and FDR sensors are comprehensively discussed. These findings can provide valuable theoretical foundation and practical guidance for future soil improvement with biochar and accurate water content measurement in BAS. Full article

Water use strategies reflect the ability of plants to adapt to drought caused by climate change. However, how these strategies change with stand development and seasonal drought is not fully understood. This study used stable isotope techniques (δD, δ¹⁸O, and δ¹³C) combined with the MixSIAR model to quantify the seasonal changes in water use sources and water use efficiency (WUE) of Eucalyptus urophylla S.T.Blake × E. grandis (E. urophylla × E. grandis) at four stand ages (2-, 4-, 9- and 14-year-old) and to identify their influencing factors. Our results showed that the young (2-year-old) and middle-aged (4-year-old) stands primarily relied on shallow soil water throughout the growing season due to the limitations of a shallow root system. In contrast, the mature (9-year-old) and overmature (14-year-old) stands, influenced by the synergistic effects of larger and deeper root systems and relative extractable water (REW), exhibited more flexibility in water use, mainly relying on shallow soil water in wet months, but shifting to using middle and deep soil layer water in dry months, and quickly returning to mainly using shallow soil water in the episodic wet month of the dry season. The WUE of E. urophylla × E. grandis was affected by the combined effect of air temperature (T), vapor pressure deficit (VPD), and REW. WUE was consistent across the stand ages in the wet season but decreased significantly with stand age in the dry season. This suggests that mature and overmature stands depend more on shifting their water source, while young and middle-aged stands rely more on enhanced WUE to cope with seasonal drought stress, resulting in young and middle-aged stands being more vulnerable to drought stress. These findings offer valuable insights for managing water resources in eucalyptus plantations, particularly as drought frequency and intensity continue to rise. Full article

Soil porosity, as an essential indicator for assessing soil quality, plays a key role in guiding agricultural production, so it is beneficial to detect soil porosity. However, the currently available methods do not apply to high-precision and rapid detection of soil with a black-box nature in the field, so this paper proposes a soil porosity detection method based on ultrasound and multi-scale CNN-LSTM. Firstly, a series of ring cutter soil samples with different porosities were prepared manually to simulate soil collected in the field using a ring cutter, followed by ultrasonic signal acquisition of the soil samples. The acquired signals were subjected to three kinds of data augmentation processes to enrich the dataset: adding Gaussian white noise, time shift transformation, and random perturbation. Since the collected ultrasonic signals belong to long-time series data and there are different frequency and sequence features, this study constructs a multi-scale CNN-LSTM deep neural network model using large convolution kernels based on the idea of multi-scale feature extraction, which uses multiple large convolution kernels of different sizes to downsize the collected ultra-long time series data and extract local features in the sequences, and combining the ability of LSTM to capture global and long-term dependent features enhances the feature expression ability of the model. The multi-head self-attention mechanism is added at the end of the model to infer the before-and-after relationship of the sequence data to improve the degradation of the model performance caused by waveform distortion. Finally, the model was trained, validated, and tested using ultrasonic signal data collected from soil samples to demonstrate the accuracy of the detection method. The model has a coefficient of determination of 0.9990 for detecting soil porosity, with a percentage root mean square error of only 0.66%. It outperforms other advanced comparative models, making it very promising for application. Full article

This study investigates how structural dynamic characteristics affect the response to high-frequency dominant seismic excitations, using a 3D numerical analysis considering soil–structure interaction (SSI). For this purpose, an SSI analysis was conducted using the finite element analysis software LS-DYNA, incorporating four representative Korean geotechnical characteristics and the 2016 Gyeongju earthquake, characterized by dominant high-frequency components. A comparison was conducted between a fixed-end model without considering SSI and an embedded model with SSI for a high-rise structure (40 stories) with low natural frequencies, and a low-rise structure (5 stories) with high natural frequencies. The analysis focused on key dynamic responses, including the natural frequency, frequency of maximum response, and maximum relative displacement of the structures, to identify differences in the SSI effect based on the structures’ dynamic characteristics and the soil types. The analysis generally revealed that the SSI effect lowers the natural frequencies of structures and increases the damping effect. It was also found that depending on the match between the dominant frequency range of the seismic excitations and the range of the structure’s natural frequencies, larger dynamic responses were calculated when SSI was considered, suggesting that it may be necessary to consider SSI for conservative design results. Full article

The carbon cycle in terrestrial ecosystems is a crucial component of the global carbon cycle, and drought is increasingly recognized as a significant stressor impacting their carbon sink function. Net ecosystem productivity (NEP), which is a key indicator of carbon sink capacity, is closely related to vegetation Net Primary Productivity (NPP), derived using the Carnegie-Ames-Stanford Approach (CASA) model. However, there is limited research on desert grassland ecosystems, which offer unique insights due to their long-term data series. The relationship between NEP and drought is complex and can vary depending on the intensity, duration, and frequency of drought events. NEP is an indicator of carbon exchange between ecosystems and the atmosphere, and it is closely related to vegetation productivity and soil respiration. Drought is known to negatively affect vegetation growth, reducing its ability to sequester carbon, thus decreasing NEP. Prolonged drought conditions can lead to a decrease in vegetation NPP, which in turn affects the overall carbon balance of ecosystems. This study employs the improved CASA model, using remote sensing, climate, and land use data to estimate vegetation NPP in desert grasslands and then calculate NEP. The Standardized Precipitation Evapotranspiration Index (SPEI), based on precipitation and evapotranspiration data, was used to assess the wetness and dryness of the desert grassland ecosystem, allowing for an investigation of the relationship between vegetation productivity and drought. The results show that (1) from 1982 to 2022, the distribution pattern of NEP in the Inner Mongolia desert grassland ecosystem showed a gradual increase from southwest to northeast, with a multi-year average value of 29.41 gCm⁻². The carbon sink area (NEP > 0) accounted for 67.99%, and the overall regional growth rate was 0.2364 gcm⁻²yr⁻¹, In addition, the area with increasing NEP accounted for 35.40% of the total area (p < 0.05); (2) using the SPEI to characterize drought changes in the Inner Mongolia desert grassland ecosystems, the region as a whole was mainly affected by light drought. Spatially, the cumulative effect was primarily driven by short-term drought (1–2 months), covering 54.5% of the total area, with a relatively fast response rate; (3) analyzing the driving factors of NEP using the Geographical detector, the results showed that annual average precipitation had the greatest influence on NEP in the Inner Mongolian desert grassland ecosystem. Interaction analysis revealed that the combined effect of most factors was stronger than the effect of a single factor, and the interaction of two factors had a higher explanatory power for NEP. This study demonstrates that NEP in the desert grassland ecosystem has increased significantly from 1982 to 2022, and that drought, as characterized by the SPEI, has a clear influence on vegetation productivity, particularly in areas experiencing short-term drought. Future research could focus on extending this analysis to other desert ecosystems and incorporating additional environmental variables to further refine the understanding of carbon dynamics under drought conditions. This research is significant for improving our understanding of carbon cycling in desert grasslands, which are sensitive to climate variability and drought. The insights gained can help inform strategies for mitigating climate change and enhancing carbon sequestration in arid regions. Full article

Rainfall is of vital importance to terrestrial ecosystems and its intermittent characteristics have a profound impact on plant growth, soil biogeochemical cycles, and water resource management. Rainfall frequency, one of the key statistics of rainfall intermittency, has received relatively little research attention. Leveraging scale-dependent relationships in rainfall frequencies and using various global precipitation datasets, we found most grid-scale rainfall frequencies are relatively large and do not converge to the field-scale frequencies as grid size decreases. Specifically, these differences are as high as 41.8% for the Global Precipitation Climatology Project (GPCP) and 74.8% for the fifth-generation European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5), which are much larger than the differences in mean rainfall rates but can be partially corrected by redefining wet days with higher rainfall thresholds. These differences across most regions of the world should be interpreted as the inherent biases associated with the model structure or algorithms used for deriving precipitation data and cannot be reduced simply by increasing the data resolutions. Such biases could propagate into the hydrological process and influence the calibration of the rainfall-runoff process, one of the key nonlinear relationships in land surface modeling. We, therefore, call for urgent research into this topic to avoid misunderstandings of rainfall intermittency and ensure its proper application in various fields. Full article

This paper presents a comprehensive method for analyzing prestressed concrete bridges subjected to multiple concurrent dynamic loads, incorporating soil–structure interaction (SSI) and seismic wave propagation effects. The study develops a comprehensive numerical framework that simultaneously accounts for traveling seismic waves, train-induced vibrations, and soil–foundation dynamics. Three-dimensional finite element modeling captures the complex interaction between the bridge structure, foundation system, and surrounding soil medium. The investigation considers the spatial variability of ground motion and its influence on the bridge’s dynamic response, particularly examining how different wave velocities and coherency patterns affect structural behavior. Advanced material constitutive models based on damage mechanics theory are implemented to represent both linear and non-linear structure responses under dynamic loading conditions. The analysis reveals that traditional simplified approaches, which neglect SSI, train, and seismic loading combinations, and traveling wave effects may significantly misestimate the structural demands. The results demonstrate how wave passage effects can either amplify or attenuate the combined response depending on the relationship between seismic wave velocity, the frequency content of the ground motion recordings, and the local soil conditions. These findings could contribute to the development of more reliable design methodologies for prestressed bridges in seismically active regions with significant railway traffic. Full article

Determining the fundamental frequency of Offshore Wind Turbines (OWTs) is crucial to ensure the reliability and longevity of the structure. This study presents a global sensitivity analysis of the fundamental frequency of OWTs on jacket foundations. Monte Carlo sampling was employed to generate a diverse set of wind turbines, emplacements, and jacket designs, ensuring that the generated samples are realistic and yield relevant conclusions. The fundamental frequency and its partial derivatives were obtained via a previously developed ANN model. The relative sensitivities were computed to facilitate the comparison of their influence. The results demonstrate that wind turbine properties are the most relevant variables affecting the fundamental frequency, with a decrement in frequency caused by tower height and rotor-nacelle assembly mass, as well as an increment due to the section dimensions of the tower, particularly at its base. Soil properties have a significant effect on foundation stiffness for soft and light soils but can be neglected for hard and heavy soils. The diameter and thickness of the braces also show different relevance depending on their dimensions, producing rigid links between legs for greater sections. This study provides a measure of the variables influencing the fundamental frequency, facilitating a deeper comprehension of this phenomenon. Full article

Caisson foundations are commonly used as the tower foundations in many long-span bridges. However, the seismic performance analysis of bridge structures using caisson foundations typically assumes that the tower is fixed at the base, applying the free-field ground acceleration to the base. Consequently, the impact of soil–caisson dynamic interaction (SCDI) on the caisson foundation motion is not considered. To investigate the SCDI effects on the motion of the caisson foundation, two different systems of 1 g shaking table model tests were carried out: a free-field system model test and a soil–caisson system model test. The test results show that an increase in the peak acceleration of the table input seismic wave is associated with a greater influence of SCDI on the motion of the caisson foundation. Compared with the free-field ground motion, the SCDI effects reduce the amplitude of the horizontal acceleration of the caisson foundation motion but introduce a significant rotational component. Additionally, both effects are frequency-dependent and become more significant with increasing frequency. The shaking table test study presented in this paper reveals several crucial features of SCDI that influence the motion of the caisson foundation, enhancing the comprehension of the mechanism of SCDI and providing essential data support for subsequent theoretical and numerical simulation studies. Full article

Soil–structure interaction (SSI) leads to a modification in the dynamic properties of structure, but due to the complexity of analysis, it is traditionally assumed in seismic designs that the structure is fixed-supported on the ground, which brings about potential risks to the seismic performances of structure. The study works on the possibility of SSI having detrimental effects by comparing the dynamic responses of the SSI system to a fixed-base structure, and presents charts for an evaluation of the system frequency of SSI for the purpose of engineering practice. In order to reveal the physical nature, the SSI model is reduced to its simplest form, consisting of a SDOF oscillator, a three-dimensional rectangular foundation, and a multi-layered half-space. The energy dissipation in the soil is achieved by foundation impedances and the substructure method. Previously, the foundation impedances are usually acquired by two-dimensional or axisymmetric three-dimensional models in uniform half-space to avoid the high cost of the more realistic, fully 3D models, while a high-precision indirect boundary element method is employed, combined with the non-singular Green’s functions of distributed loads to calculate the foundation impedances. Although SSI dampens the peak amplitude of structure response in the frequency domain, case studies on four buildings’ responses to 42 earthquakes in the time history show a possibility of 15–20% that SSI amplifies the dynamic responses of structures, such as the maximum and the mean values in the time history, depending on the properties of the structures and the site, as well as the frequency component of incident waves. Full article

When harvesting cereals and fodder grasses, a two-phase method is often used. This process is carried out using trailed and suspended collecting units. The former are asymmetrical and often pose problems regarding the stability of their movement in the horizontal plane. In practice, suspended harvesting units with a front-mounted header are becoming more and more widely used. The disadvantage of their use is that the soil is exposed after passing through the space between the swaths of the mown crop. This is followed by an intense loss of moisture. In order to eliminate this shortcoming, a collecting unit was proposed, consisting of a tractor with a front attachment and a disc harrow mounted at the rear. An appropriate mathematical model was developed to justify the scheme and parameters of such a unit. In this case, this model is used to assess the controllability of the movement of the dynamic system under the influence of control action in the form of the angular rotation of the tractor’s steered wheels. As a result of mathematical modelling, it was found that satisfactory controllability of the movement of the harvesting units can be ensured by acting on the tractor’s driven wheels with a frequency of 0–1 s⁻¹ and a working speed of close to 3 m·s⁻¹. In this case, it is desirable to set the deflection resistance coefficient of the rear tyres of the tractor (and therefore, the air pressure in them) to a smaller value, and that of the front tyres to a larger value. This helps both to improve the movement controllability of the harvesting unit and to reduce its energy consumption by an average of 6.75%. The emissivity of selected harmful chemicals and particulates emitted by the harvesting unit, depending on the fuel burned, was also examined. The way in which the use of the harvesting unit affects the reduction of emissions of harmful compounds into the atmosphere was also revealed. Full article

Biochar application is considered an effective method for reducing nitrous oxide (N₂O) emissions from soil. However, the mechanisms underlying the influence of various biochar dosages on soil N₂O emissions and the duration of one-time biochar application remain unclear. The effects of different biochar application rates and a one-time application on soil N₂O emissions in the Huanghuaihai Plain of China were investigated through a field experiment from 2020 to 2022. In the wheat and maize rotation system, six treatments were administered: no biochar (C0); 2 (C1), 4 (C2), 8 (C3), and 12 t/hm² biochar (C4) applied annually; and a one-time application of 12 t/hm² biochar (CS) in 2018. Our results indicate that, compared with C0, biochar significantly inhibited soil N₂O emissions, particularly in the C3 and C4 treatments, with reductions of 31.36–56.21% and 36.92–52.45%, respectively. However, CS did not significantly affect soil N₂O emissions during the study period. These findings suggest that the biochar’s inhibitory effect on soil N₂O emissions is contingent upon the dosage and frequency of application. A structural equation model revealed that biochar decreases soil N₂O emissions by enhancing the reduction in N₂O during denitrification. Under the conditions of this experiment, based on a logistic ecological model, a one-time application of 12 t/hm² biochar was projected to significantly reduce soil N₂O emissions for approximately 1.77 years. On the whole, biochar reduces soil N₂O emissions mainly by regulating N₂O production through denitrification, and the duration of this inhibition of N₂O emissions mainly depends on the application amount and frequency of biochar application. Full article

The uplift of underground structures induced by soil liquefaction can damage underground structure systems. Numerical simulations have shown that uplift is positively correlated with the energy of horizontal input motion. However, the effects of vertical input motion on uplift have not been studied comprehensively in the past. Previous studies on the vertical motion concluded that the effects of vertical motion on uplift depend on the overall characteristics of earthquake motion. These motion characteristics have only been studied separately in previous studies. A comprehensive study to explore the interactions and overall effects of these characteristics on the uplift of underground structures is essential. In this study, the FLAC program with the PM4Sand model was used as a numerical tool to explore the effects of vertical input motion on the uplift of underground structures. The numerical model was calibrated using centrifuge test results, and 48 earthquake motions were selected as input motions to study the effects of the overall characteristics of earthquake motions on the uplift of underground structures. The simulation results show that the frequency content characteristics of horizontal and vertical motion are the major factors affecting the uplift magnitude and the responses of liquefiable soils. However, most simulation cases show that the inclusion of vertical motion causes a 10% difference in the tunnel uplift, compared to cases without vertical motion. Full article