Search Results (1,470)

This study establishes a multiphysics coupling model of acoustics, mechanics, and electrostatics through COMSOL, systematically explores the sound field distribution and stress–strain characteristics of tailing particles in sand silos under different frequencies of ultrasonic radiation, and proposes an optimization scheme for the sound field. The simulation results show that under 28 kHz ultrasonic radiation, the amplitude of sound pressure in the sand silo (173 Pa) is much lower than that at 40 kHz (1220 Pa), which can avoid damaging the original settlement mode of the tail mortar. At the same time, the periodic fluctuation amplitude of its longitudinal sound pressure is significantly greater than 25 kHz, which can promote settlement by enhancing particle tensile and compressive stress, achieving the best comprehensive effect. The staggered placement scheme of the transducer eliminates upward disturbance in the flow field by changing the longitudinal opposing sound field to oblique propagation, reduces energy dissipation, and increases the highest sound pressure level in the compartment to 130 dB. The sound pressure distribution density is significantly improved, further enhancing the settling effect. This study clarifies the correlation mechanism between ultrasound parameters and tailings’ settling efficiency, providing a theoretical basis for parameter optimization of ultrasound-assisted tailing treatment technology. Its results have important application value in the optimization of tailings settling in metal mine tailing filling. Full article

This study presents a comprehensive analysis of the microphysical structures of Meiyu heavy rainfall (near-surface rainfall intensity > 8 mm/h) across different life stages in the Yangtze-Huaihe River Valley (YHRV). We classified the heavy rainfall events into three life stages of developing, mature, and dissipating using ERA5 reanalysis and IMERG precipitation estimates, and examined vertical microphysical structures using Dual-frequency Precipitation Radar (DPR) data from the Global Precipitation Measurement (GPM) satellite during the Meiyu period from 2014 to 2023. The results showed that convective heavy rainfall during the mature stage exhibits peak radar reflectivity and surface rainfall rates, with the largest near-surface mass weighted diameter (D_m ≈ 1.8 mm) and the smallest droplet concentration (dBN_w ≈ 38). Downdrafts in the dissipating stage preferentially remove large ice particles, whereas sustained moisture influx stabilizes droplet concentrations. Stratiform heavy rainfall, characterized by weak updrafts, displays narrower particle size distributions. During dissipation, particle breakups dominate, reducing D_m while increasing dBN_w. The analysis of the relationship between microphysical parameters and rainfall rate revealed that convective heavy rainfall shows synchronized growth of D_m and dBN_w during the developing stage, with D_m peaking at about 2.1 mm near 70 mm/h before stabilizing in the mature stage, followed by small-particle dominance in the dissipating stage. In contrast, stratiform rainfall exhibits a “small size, high concentration” regime, where the rainfall rate correlates primarily with increasing dBN_w. Additionally, convective heavy rainfall demonstrates about 22% higher precipitation efficiency than stratiform systems, while stratiform rainfall shows a 25% efficiency surge during the dissipation stage compared to other stages. Full article

Accurate estimation of winter wheat yield under saline stress is crucial for addressing food security challenges and optimizing agricultural management in regional soils. This study proposed a method integrating Sentinel-2 data and field-measured soil salt content (SC) using a random forest (RF) method to improve yield estimation of winter wheat in Kenli County, a typical saline area in China’s Yellow River Delta. First, feature importance analysis of a temporal vegetation index (VI) and salinity index (SI) across all growth periods were achieved to select main parameters. Second, yield models of winter wheat were developed in VI-, SI-, VI + SI-, and VI + SI + SC-based groups. Furthermore, error assessment and spatial yield mapping were analyzed in detail. The results demonstrated that feature importance varied by growth periods. SI dominated in pre-jointing periods, while VI was better in the post-jointing phase. The VI + SI + SC-based model achieved better accuracy (R² = 0.78, RMSE = 720.16 kg/ha) than VI-based (R² = 0.71), SI-based (R² = 0.69), and VI + SI-based (R² = 0.77) models. Error analysis results suggested that the residuals were reduced as the input parameters increased, and the VI + SI + SC-based model showed a good consistency with the field-measured yields. The spatial distribution of winter wheat yield using the VI + SI + SC-based model showed significant differences, and average yields in no, slight, moderate, and severe salinity areas were 7945, 7258, 5217, and 4707 kg/ha, respectively. This study can provide a reference for winter wheat yield estimation and crop production improvement in saline regions. Full article

Electric vehicles (EVs) offer a sustainable solution for reducing carbon emissions in the transportation sector. However, their increasing widespread adoption poses significant challenges for local distribution grids, many of which were not designed to accommodate the heightened and irregular power demands of EV charging. Components such as transformers and distribution networks may experience overload, voltage imbalances, and congestion—particularly during peak periods. While upgrading grid infrastructure is a potential solution, it is often costly and complex to implement. The unpredictable nature of EV charging behavior further complicates grid operations, as charging demand fluctuates throughout the day. Therefore, efficient integration into the grid—both for charging and potential discharging—is essential. This paper reviews recent studies on the impacts of high EV penetration on distribution grids and explores various strategies to enhance grid performance during peak demand. It also examines promising optimization methods aimed at mitigating negative effects, such as load shifting and smart charging, and compares their effectiveness across different grid parameters. Additionally, the paper discusses key challenges related to impact analysis and proposes approaches to improve them in order to achieve better overall grid performance. Full article

We developed a mathematical model to examine the scattering of radiation by a periodic structure of circular and elliptical microcavities formed in a planar optical waveguide. The waveguide simulates the behaviour of a 62.5/125 µm multimode optical fibre. The calculations focused on the intensity distribution of scattered light with a wavelength of 1310 nm along the periodic structure, i.e., along the side surface of the waveguide, as a function of the microcavity dimensions and their spatial arrangement within the waveguide core. The optimal geometrical parameters of the microstructure, ensuring the most uniform light scattering, were identified. The model is valid for multimode optical fibres containing strictly periodic structures of microcavities with spherical or elliptical cross-sections that scatter laser radiation in all directions. One potential application of such fibres is as light sources in medical probes for surgical procedures requiring additional illumination and uniform irradiation of affected tissues. Furthermore, the findings of this study offer significant potential for the development of sensing elements for fibre-optic sensors. The findings of this study will facilitate the design of scattering structures with microcavities that ensure a highly uniform scattering pattern. Full article

Trihalomethanes (THMs) are a class of disinfectant by-products present in chlorinated tap water. Mainly due to their carcinogenic potential, their concentration in drinking water is now limited by regulations. In Romania, little is known about their distribution in urban drinking water supply systems, their magnitude, or their seasonal variation. Drinking water suppliers periodically adapt and optimise their water treatment methods for economic reasons and in response to regulatory changes and technological developments. The formation of THMs is influenced by the physicochemical parameters of water (pH, temperature, total organic carbon—TOC) and by environmental factors (geographical, climatological). Most of these factors have significant seasonal variations that lead to the formation of THMs in variable concentrations. In this study, we analysed the seasonal trends in surface water quality (considering variations in temperature, pH, and TOC) and correlated them with the concentration of THMs in drinking water over two calendar years. Water samples were collected from the Arges River, in a geographical area comprised of plains. The results show that the formation of THMs is enhanced by increasing temperature over the course of a year, with the highest concentrations being obtained in July 2022 (98.7 µg/L THMs at 30.5 °C) and in August 2023 (81.9 µg/L THMs at 30.4 °C). The main parameters that trigger the formation of THMs are the organic matter content and the disinfectant dose; the pH has a moderate effect, and its effect is correlated with the concentration of organic matter. There were noted strong seasonal changes in the concentration of THMs, with the maximum peak being in the middle and late summer and the minimum peak being in winter. This indicates the possibility that the quality of drinking water may change as a result of climate change. In addition, monitoring and chlorination experiments have established that the concentration of THMs is directly proportional with the TOC. Full article

To investigate the slope instability caused by differential frost heaving mechanisms from the slope crest to the toe during frost heave processes, this study takes a typical silty clay slope in Xinjiang, China, as the research object. Through indoor triaxial consolidated undrained shear tests, eight sets of natural and frost-heaved specimens were prepared under confining pressure conditions ranging from 100 to 400 kPa. The geotechnical parameters of the soil in both natural and frost-heaved states were obtained, and a spatiotemporal thermo-hydro-mechanical coupled numerical model was established to reveal the dynamic evolution law of anchor rod axial forces and the frost heave response mechanism between the frame and slope soil. The analytical results indicate that (1) the frost heave process is influenced by slope boundaries, resulting in distinct spatial variations in the temperature field response across the slope surface—namely pronounced responses at the crest and toe but a weaker response in the mid-slope. (2) Under the coupled drive of the water potential gradient and gravitational potential gradient, the ice content in the toe area increases significantly, and the horizontal frost heave force exhibits exponential growth, reaching its peak value of 92 kPa at the toe in February. (3) During soil freezing, the reverse stress field generated by soil arching shows consistent temporal variation trends with the temperature field. Along the height of the soil arch, the intensity of the reverse frost heave force field displays a nonlinear distribution characteristic of initial strengthening followed by attenuation. (4) By analyzing the changes in anchor rod axial forces during frost heaving, it was found that axial forces during the frost heave period are approximately 1.3 times those under natural conditions, confirming the frost heave period as the most critical condition for frame anchor design. Furthermore, through comparative analysis with 12 months of on-site anchor rod axial force monitoring data, the reliability and accuracy of the numerical simulation model were validated. These research outcomes provide a theoretical basis for the design of frame anchor support systems in seasonally frozen regions. Full article

Subtropical plateau lakes, which are distinguished by their elevated altitudes and subtropical climates, display distinct ecological dynamics. Nevertheless, the spatial and seasonal variations in the plankton community structure, as well as their interactions with environmental factors, remain inadequately understood. This study investigated the alterations in the phytoplankton and zooplankton community structure across different geographical regions (southern, central, and northern) and seasonal periods (rainy and dry) in Erhai lake, located in a subtropical plateau in China. The results indicated that the average values of total nitrogen (TN), total phosphorus (TP), chlorophyll-a (Chla), pH, and conductivity are significantly higher during the rainy season in comparison to the dry season. Furthermore, during the rainy season, there were significant differences in the concentrations of TN, TP, and Chla among the three designated water areas. Notable differences were also observed in the distribution of Microcystis, the density of Cladocera and copepods, and the biomass of copepods across the three regions during this season. Conversely, in the dry season, only the biomass of Cladocera exhibited significant variation among the three water areas. The redundancy analysis (RDA) and variance partitioning analysis demonstrated that the distribution of plankton groups (Cyanophyta, Cryptophyta, and Cladocera) is significantly associated with TN, Secchi depth (SD), and Chla during the rainy season, whereas it is significantly correlated with TP and SD during the dry season. These findings underscore the critical influence of environmental factors, shaped by rainfall patterns, in driving these ecological changes. In the context of the early stages of eutrophication in Lake Erhai, it is essential to ascertain the spatial distribution of water quality parameters, as well as phytoplankton and zooplankton density and biomass, during both the rainy and dry seasons. Full article

Global warming is driving significant changes in aquatic ecosystems, where temperature fluctuations influence biological processes across multiple levels of organisation. As ectothermic organisms, fish are particularly susceptible, with even minor thermal shifts affecting their metabolism, behaviour, and overall fitness. Understanding these responses is essential for evaluating the ecological and evolutionary consequences of climate change. This study investigates the effects of acute (4-day) and chronic (21-day) exposure to three temperature regimes—18 °C (low), 26 °C (control), and 34 °C (high)—on the spatio-temporal shoaling behaviour of adult zebrafish (Danio rerio). Groups of four fish were tested for six minutes in water maintained at the same temperature as their prior acclimation. Shoaling behaviour was assessed by analysing shoal structure—encompassing shoal dimensions and cohesion—as well as spatial positioning. Parameters measured included inter-fish distance, shoal volume, shoal area, homogeneity index, distance to the centroid, and the shoal’s vertical and horizontal distribution. Results revealed complex behavioural changes influenced by both temperature and duration of exposure. At 18 °C, zebrafish showed a marked preference for the bottom zone and exhibited no significant temporal modulation in exploratory behaviour—patterns indicative of heightened anxiety-like responses. In contrast, exposure to 34 °C resulted in increased shoal cohesion, particularly under chronic conditions, and a progressive increase in environmental exploration over the six-minute test period. This enhancement in exploratory activity was especially evident when compared to the first minute of the test and was characterised by greater vertical movement—reflected in the increased use of the upper zone—and broader horizontal exploration, including more frequent occupation of peripheral areas. These findings align with previous research linking thermal variation to neurobiological and proteomic alterations in zebrafish. By elucidating how temperature modulates social behaviour in ectotherms, this study offers valuable insights into the potential behavioural impacts of climate change on aquatic ecosystems. Full article

A VOC-contaminated shallow aquifer in an industrial site was investigated to evaluate its potential for natural attenuation. The shallow groundwater aquifer beneath the industrial site has been contaminated by dissolved volatile organic compounds (VOCs) such as trichloroethylene (TCE), cis-1,2-dichloroethylene (cis-DCE), and vinyl chloride (VC) for more than three decades. Monitoring and investigation were implemented during 2011–2024, aiming to propose future groundwater aquifer management strategies. This study included groundwater borehole investigation, well installation monitoring, hydraulic head measurements, slug tests, groundwater samplings, and microbial analyses. Microbial investigations identified the predominant group of microorganisms of Proteobacteria, indicating biodegradation potential, as demonstrated by the presence of cis-DCE and VC. BIOSCREEN was used to evaluate the process of natural attenuation, incorporating site-specific parameters. A two-layer groundwater flow model was developed using MODFLOW with hydraulic conductivities obtained from slug tests. The site has an average hydraulic head of 259.6 m amsl with a hydraulic gradient of 0.026, resulting in an average groundwater flow velocity of 11 m/y. Hydraulic conductivities were estimated during model calibration using the PEST pilot point technique. A reactive transport model, RT3D, was used to simulate dissolved TCE transport over 30 years, which can undergo sorption as well as biodegradation. Model calibration demonstrated a satisfactory fit between observed and simulated groundwater heads with a root mean square error of 0.08 m and a correlation coefficient (r) between measured and simulated heads of 0.81, confirming the validity of the hydraulic conductivity distribution. The TCE plume continuously degraded and gradually migrated southward, generating a cis-DCE plume. The concentrations in both plumes decreased toward the end of the simulation period at Source 1 (located upstream), while BIOSCREEN results confirmed ongoing natural attenuation primarily by biodegradation. The integrated MODFLOW-RT3D-BIOSCREEN approach effectively evaluated VOC attenuation and plume migration. However, future remediation strategies should consider enhanced bioremediation to accelerate contaminant degradation at Source 2 and ensure long-term groundwater quality. Full article

Dual polarimetric SAR is capable of reflecting the biophysical and geometrical information of terrain with open access data availability. When it is combined with time-series observations, it can effectively capture the dynamic evolution of scattering characteristics of crops in different growth cycles. However, the actual planting of crops often shows spatial dispersion, and the same crop may be dispersed in different plots, which fails to adequately consider the correlation information between dispersed plots of the same crop in spatial distribution. This study proposed a crop classification method based on multi-temporal dual polarimetric data, which considered the utilization of information between near and far spatial plots, by employing superpixel segmentation and a HyperGraph neural network, respectively. Firstly, the method utilized the dual polarimetric covariance matrix of multi-temporal data to perform superpixel segmentation on neighboring pixels, so that the segmented superpixel blocks were highly compatible with the actual plot shapes from a long-term period perspective. Then, a HyperGraph adjacency matrix was constructed, and a HyperGraph neural network (HGNN) was utilized to better learn the features of plots of the same crop that are distributed far from each other. The method fully utilizes the three dimensions of time, polarization and space information, which complement each other so as to effectively realize high-precision crop classification. The Sentinel-1 experimental results show that, under the optimal parameter settings, the classified accuracy of combined temporal superpixel scattering features using the HGNN was obviously improved, considering the near and far distance spatial correlations of crop types. Full article

Water vapor plays a crucial role in maintaining global energy balance and water cycle, and it is closely linked to various meteorological disasters. Precipitable water vapor (PWV), as an indicator of variations in atmospheric water vapor content, has become a key parameter for meteorological and climate monitoring. However, due to limitations in observation costs and technology, traditional atmospheric monitoring techniques often struggle to accurately capture the distribution and variations in space–time water vapor. With the continuous advancement of Global Navigation Satellite System (GNSS) technology, ground-based GNSS monitoring technology has shown rapid development momentum in the field of meteorology and is considered an emerging monitoring tool with great potential. Hence, based on the GNSS observation data from July 2023, this study retrieves PWV using the Global Pressure and Temperature 3 (GPT3) model and evaluates its application performance in the “7·31” extremely torrential rain event in Beijing in 2023. Research has found the following: (1) Tropospheric parameters, including the PWV, zenith tropospheric delay (ZTD), and zenith wet delay (ZWD), exhibit high consistency and are significantly affected by weather conditions, particularly exhibiting an increasing-then-decreasing trend during rainfall events. (2) Through comparisons with the PWV values through the integration based on fifth-generation European Centre for Medium-Range Weather Forecasts (ERA-5) reanalysis data, it was found that results obtained using the GPT3 model exhibit high accuracy, with GNSS PWV achieving a standard deviation (STD) of 0.795 mm and a root mean square error (RMSE) of 3.886 mm. (3) During the rainfall period, GNSS PWV remains at a high level (>50 mm), and a strong correlation exists between GNSS PWV and peak hourly precipitation. Furthermore, PWV demonstrates the highest relative contribution in predicting extreme precipitation, highlighting its potential value for monitoring and predicting rainfall events. Full article

Dissolved oxygen (DO) is a fundamental water quality parameter that directly determines aquaculture productivity. China contributes 57% of the global aquaculture production, with the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) serving as a key contributor. However, this region faces significant environmental challenges due to increasing intensive stocking densities and outdated management practices, while also grappling with the systematic monitoring limitations of large-scale operations. To address these challenges, in this study, a random forest-based model was developed for DO concentration retrieval (R² = 0.82) using Landsat 8/9 OLI imagery. The Lindeman, Merenda, and Gold (LMG) algorithm was applied to field data collected from four cities—Foshan, Hong Kong, Huizhou, and Zhongshan—to identify key environmental drivers to the changes in DO concentration in these cities. This study also employed satellite imagery from multiple periods to analyze the spatiotemporal distribution and trends of DO concentrations over the past decade, aiming to enhance understanding of DO variability. The results indicate that the average DO concentration in fishponds across the GBA was 7.44 mg/L with a statistically insignificant upward trend. Spatially, the DO levels remained slightly lower than those in other waters. The primary environmental factor influencing DO variations was the pH levels, while the relationship between natural factors such as the temperature and DO concentration was significantly hidden by aquaculture management practices. The further analysis of fishpond water quality parameters across land uses revealed that fishponds with lower DO concentrations (7.293 mg/L) are often located in areas with intensive human intervention, particularly in highly urbanized regions. The approach proposed in this study provides an operational method for large-scale DO monitoring in aquaculture systems, enabling the qualification of anthropogenic influences on water quality dynamics. It also offers scalable solutions for the development of adaptive management strategies, thereby supporting the sustainable management of aquaculture environments. Full article

This study assesses the use of Quantile-Mapping methods for bias correction and downscaling in climate change studies. A “Perfect Model Experiment” is conducted using high-resolution climate simulations as pseudo-references and coarser versions as biased data. The focus is on European daily temperature and precipitation under the RCP 8.5 scenario. Six methods are tested: an empirical Quantile-Mapping approach, the “Cumulative Distribution Function—transform” (CDF-t) method, and four CDF-t variants with different parameters. Their performance is evaluated based on univariate and multivariate properties over the calibration period (1981–2010) and a future period (2071–2100). The results show that while Quantile Mapping and CDF-t perform similarly during calibration, significant differences arise in future projections. Quantile Mapping exhibits biases in the means, standard deviations, and extremes, failing to capture the climate change signal. CDF-t and its variants show smaller biases, with one variant proving particularly robust. The choice of discretization parameter in CDF-t is crucial, as the low number of bins increases the biases. This study concludes that Quantile Mapping is not appropriate for adjustments in a climate change context, whereas CDF-t, especially a variant that stabilizes extremes, offers a more reliable alternative. Full article

The vibration noise of plate structures in engineering is strongly related to the modal resonance, and modal design is the key to improve the dynamic characteristics of plate structures and avoid structural resonance. This paper investigates the dynamic and mode characteristics for an edge periodic acoustic black hole plate structure to provide a new approach to vibration and sound attenuation in plate structures. Firstly, based on the principles of symmetry and periodicity, this work presents the geometrical modeling and mathematical description of a rectangular plate with symmetrical periodic acoustic black holes at its edge. Then, it presents the dynamic modeling of a rectangular plate with periodic acoustic black holes at its edge via the “remove-and-fill” substitution method, which reveals the effects of the structural parameters and period distribution, etc., on the modal characteristics of vibration. The study indicates that the power law index, radius, number and configuration (e.g., semicircular, rectangular block shape) of the edge periodic acoustic black holes significantly affect the modal frequency of the rectangular plate, and increasing the radius of the acoustic black holes or the number of the black holes results in a decrease in the modal frequency of the rectangular plate. Moreover, the four-side symmetric layout achieves broader modal frequency modulation, while semicircular acoustic black holes can achieve a lower modal frequency compared with the rectangular wedge-shaped acoustic black hole. The theoretical model is verified by finite element simulation (FEM) and experiments, in which the errors of the first six modal frequencies are within 2%. The research in this paper provides a theoretical basis for the realization of modal frequency control in plate structures and the suppression of structural resonance through the design of edge periodic acoustic black hole structures. Full article