Search Results (2,330)

An efficient and reliable heat dissipation system is essential for the safe and stable operation of high-power water-cooled couplers. However, thermal analysis methods accounting for the centrifugal effects on coolant flow remain limited. This paper presents a high-accuracy equivalent thermal network model (ETNM) for analyzing the temperature distribution in water-cooled permanent magnet couplers (WPMCs), based on fluid–structure interaction and rotational centrifugal flow-field inversion. First, the ETNM is established based on key assumptions. Subsequently, an eddy current loss calculation method based on permanent magnet mapping is proposed to accurately determine the heat source distribution. The convective heat transfer coefficient of the coolant is then precisely derived by inverting the flow field obtained from fluid–structure coupling simulations under rotational centrifugal conditions. Finally, the model is applied for temperature analysis, and its accuracy is verified through both finite element simulations and experimental tests. The calculated results show errors of only 3.2% compared to numerical simulation and 5.6% compared to experimental data, indicating strong agreement of the proposed thermal analysis method. The accuracy of copper conductor (CC) temperature prediction is improved by 32.73%, and that of permanent magnet (PM) prediction by 33.33%. Furthermore, this method enables accurate estimation of individual component temperatures, effectively preventing operational failures such as PM demagnetization, CC softening, and severe vibrations caused by overheating. Full article

Chlorine contact tanks are crucial for wastewater disinfection, with performance strongly influenced by internal hydraulic characteristics. This study applies Computational Fluid Dynamics (CFD) to analyze and improve the hydraulics of the chlorination contact tank in a Wastewater Treatment Plant in the Southern Italy. A three-dimensional transient CFD model was developed using the Reynolds-Averaged Navier–Stokes (RANS) equations with the Renormalized Group (RNG) turbulence closure. The model simulated flow patterns, tracer transport, and chlorine decay kinetics under the existing configuration and two alternative configurations. Conservative tracer pulse simulations enabled the calculation of Residence Time Distributions (RTDs) and hydraulic efficiency indicators, including the Baffling Factor (θ₁₀), Morrill index (Mo), and Aral–Demirel index (AD). A typical contact tanks geometry exhibits specific hydraulic characteristics, including recirculation behind baffles and stagnant zones in sharp corners, which inevitably affects the contact time. The first alternative, namely featuring rounded corners, moderately reduced dead zones, but did not substantially mitigate recirculation. The second alternative, herein called combining rounded corners with perforated baffle walls, substantially improved hydraulic performance, yielding flow patterns closer to plug-flow. RTD peaks were higher and narrower for the modified designs, and hydraulic indices improved, with Mo decreasing by approximately 5%. These hydraulic enhancements are expected to increase disinfection efficiency by providing more uniform chlorine exposure. The results demonstrate that geometric modifications effectively optimize contact tank hydraulics and highlight the role of CFD as a design and retrofit tool for water and wastewater disinfection systems. Full article

This paper investigates the flow of a second-grade hybrid nanofluid through a Darcy–Forchheimer porous medium under Cattaneo–Christov heat and mass flux models. The hybrid nanofluid, composed of alumina and copper nanoparticles in water, enhances thermal and mass transport, while the second-grade model captures viscoelastic effects, and the Darcy–Forchheimer medium accounts for both linear and nonlinear drag. Using similarity transformations and the spectral quasilinearisation method, the nonlinear governing equations are solved numerically and validated against benchmark results. The results show that hybrid nanoparticles significantly boost heat and mass transfer, while Cattaneo–Christov fluxes delay thermal and concentration responses, reducing the near-wall temperature and concentration. The distributions of velocity, temperature, concentration, and microorganism density are markedly affected by porosity, the Forchheimer number, the bio-convection Peclet number, and relaxation times. The results illustrate that hybrid nanoparticles significantly increase heat and mass transfer, whereas thermal and concentration relaxation factors delay energy and species diffusion, thickening the associated boundary layers. Viscoelasticity, porous medium resistance, Forchheimer drag, and bio-convection all have an influence on flow velocity and transfer rates, highlighting the subtle link between these mechanisms. These breakthroughs may be beneficial in establishing and enhancing bioreactors, microbial fuel cells, geothermal systems, and other applications that need hybrid nanofluids and non-Fourier/non-Fickian transport. Full article

This study proposed a cloud model-based framework for assessing the seismic robust-ness of water supply networks (WSN). A multi-scale robustness indicator system was developed, which considers physical-layer attributes (pipe material, length), topological-layer graph characteristics (node degree), and functional-layer hydraulic metrics (water supply adequacy rate). The cloud-probability density evolution method was employed to address parameter uncertainties, while Monte Carlo simulation was used to integrate these three indicators through the cloud composite weighting method to analyze the robustness qualitatively and quantitatively. The proposed method utilizes a forward cloud generator to generate the robustness distribution clouds for both net-work nodes and community-level systems, and its robustness level can be classified according to the standard cloud. A case study demonstrated the practical application of this assessment approach. The presented methodology for evaluating WSN robustness during seismic events provides critical insights for developing disaster prevention plans, formulating emergency response strategies, and implementing targeted seismic reinforcement measures. The integration of cloud theory with probabilistic assessment offers a novel paradigm for infrastructure resilience evaluation under uncertainty. Full article

As an important component of the global fishery economy, the crab breeding and processing industry faces the dual challenges of sustainable development and technological upgrading. This paper first systematically analyzes the regional distribution and core biological characteristics of major global economic crab species, laying a foundation for the targeted design of processing technologies and equipment. Secondly, based on advances in crab processing technology, the industry is categorized into two systems: live crab processing and dead crab processing. Live crab processing has formed a full-chain technological system of “fishing–temporary rearing–depuration–grading–packaging”. Dead crab processing focuses on high-value utilization: high-pressure processing enhances the quality of crab meat; liquid nitrogen quick-freezing combined with modified atmosphere packaging extends shelf life; and biological fermentation and enzymatic hydrolysis facilitate the green extraction of chitin from crab shells. In terms of intelligent equipment application, sensor technology enables full coverage of aquaculture water quality monitoring, precise classification during processing, and vitality monitoring during transportation. Automation technology reduces labor costs, while fuzzy logic algorithms ensure the process stability of crab meat products. The integration of the Internet of Things (IoT) and big data analytics, combined with blockchain technology, enables full-link traceability of the “breeding–processing–transportation” chain. In the future, cross-domain technological integration and multi-equipment collaboration will be the key to promoting the sustainable development of the industry. Additionally, with the support of big data and artificial intelligence, precision management of breeding, processing, logistics, and other links will realize a more efficient and environmentally friendly crab industry model. Full article

Monte Carlo methods offer a fast, cost-effective approach for modeling environmental systems influenced by random variability. This study applied them to three abiotic cases: (I) water quality in a lentic surface water source, (II) sizing of a homogenization chamber for solid waste treatment, and (III) removal of atmospheric particulate matter by rain. Deterministic models produced wide and inconsistent estimates: BOD₅ concentrations from 5.28 to 19.81 mg/L (275% relative difference), chamber volumes from 24.12 to 116.53 m³, and particulate matter reductions with up to 60 µg/m³ per month variation. Monte Carlo simulations, by contrast, captured system variability and provided more robust outputs: a design value of 94.84 m³ for the homogenization chamber, narrower ranges for BOD₅, and realistic distributions of atmospheric PM concentrations. Results show that reliance on average values introduces strong biases and mathematical incompatibilities, while the Monte Carlo approach yields quantitative predictions that are both accurate and operationally useful. This confirms its relevance as a practical tool for analyzing and designing environmental systems under uncertainty. Full article

To overcome the limitations of lengthy laboratory testing cycles and insufficient on-site responsiveness, this study developed an online rapid monitoring device for volatile organic compounds (VOCs) in soil–water–air systems based on photoionization detection (PID) technology. The device integrates modular sensor units, incorporates an electromagnetic valve-controlled multi-medium adaptive switching system, and employs an internal heating module to enhance the volatilization efficiency of VOCs in water and soil samples. An integrated system was developed featuring “front-end intelligent data acquisition–network collaborative transmission–cloud-based warning and analysis”. The effects of different temperatures on the monitoring performance were investigated to verify the reliability of the designed system. A polynomial fitting model between concentration and voltage was established, showing a strong correlation (R² > 0.97), demonstrating its applicability for VOC detection in environmental samples. Field application results indicate that the equipment has operated stably for nearly three years in a mining area of Shandong Province and an industrial park in Anhui Province, accumulating over 600,000 valid data points. These results demonstrate excellent measurement consistency, long-term operational stability, and reliable data acquisition under complex outdoor conditions. The research provides a distributed, low-power, real-time monitoring solution for VOC pollution control in mining and industrial environments. It also offers significant demonstration value for standardizing on-site emergency monitoring technologies in multi-media environments and promoting the development of green mining practices. Full article

River flood management is a complex, multidimensional challenge that requires the integration of technical, social, and regulatory perspectives, among others. This study examines the main challenges in achieving sustainable river flood management and provides a comprehensive framework for addressing them. It explores approaches to mitigate the increasing frequency and severity of river floods, which are worsened by urban expansion and climate change. This study distinguishes river floods from other types, highlighting their specific characteristics and impacts. It presents a timeline of flood management, from traditional levee construction to modern integration in water resources management. Three critical perspectives are included: the Social Component, which stresses the importance of community engagement, equitable risk distribution, and cultural considerations; the Technical Component, which evaluates current technologies such as predictive hydrological models, green infrastructure, and early warning systems; and the Regulatory Component, which reviews existing policies and legal frameworks, noting gaps in international cooperation and enforcement. The paper emphasizes the need for interdisciplinary collaboration and robust governance. By addressing these core challenges, it offers insights for policymakers, engineers, and stakeholders seeking to mitigate flood risks in a rapidly changing world. Full article

Studies have shown that natural organic matter can regulate pollutant behavior through multiple pathways; however, research on the environmental behavior of veterinary antibiotics (VAs) in typical alkaline calcareous loess soil under the influence of exogenous organic matter remains limited. This study investigated the influence of humic acid (HA), as a representative of natural organic matter, on the sorption behavior of ciprofloxacin (CIP) in sierozem—a typical alkaline calcareous loess soil. Using the batch equilibrium method, we examined how HA affects CIP sorption under various environmental conditions to better understand the environmental fate of VAs in soil–water systems with low organic matrix content. Results showed that CIP sorption onto sierozem involved both fast and slow processes, reaching equilibrium within 2 h, with sorption capacity increasing as HA concentration increased. Kinetic data were well described by the pseudo-second-order model regardless of HA addition, suggesting multiple mechanisms governing CIP sorption, such as chemical sorption reaction, intraparticle diffusion, film diffusion, etc. Sorption decreased with increasing temperature both before and after HA amendment, indicating an exothermic process. Isotherm analysis revealed that both the Linear and Freundlich models provided excellent fits (R² ≈ 1), implying multilayer sorption dominated by hydrophobic distribution. In ion effect experiments, cations at concentrations above 0.05 mol/L consistently inhibited CIP sorption, with inhibition strength following the order: Mg²⁺ > K⁺ > Ca²⁺ > NH₄⁺, and intensifying with increasing ionic strength. However, HA addition significantly mitigated this inhibition, likely due to complexation between HA’s functional groups (e.g., carboxyl and hydroxyl) and cations, which reduced their competitive effect and enhanced CIP sorption. pH-dependent experiments indicated stronger CIP sorption under acidic conditions. HA addition increased soil acidity, further promoting CIP retention. In summary, HA enhances CIP sorption in sierozem by providing additional sorption sites and modifying soil surface properties. These findings improve our understanding of how exogenous organic matter influences the behavior of emerging contaminants such as antibiotics in soil–water systems, offering valuable insights for environmental risk assessment in semi-arid agricultural regions. Full article

The increasing complexity of water distribution systems (WDSs) and the growing demand for sustainable infrastructure management have spurred interest in Building Information Modelling (BIM) and Digital Twin (DT) technologies. This study presents a comprehensive bibliometric and thematic literature review aiming to identify key trends, research clusters, and knowledge gaps at the intersection of BIM, DT, and WDSs. Using the Scopus database, 95 relevant publications from 2004 to 2024 were systematically analyzed. VOSviewer was applied to create, visualize, and analyze maps of countries, journals, documents, and keywords based on citation, co-citation, collaboration, and co-occurrence data. The results indicate a sharp rise in scholarly attention after 2020, with dominant contributions from European institutions. Co-authorship networks show limited global interconnectedness, suggesting that developing countries should especially prioritize integrated DT and BIM for more inclusive and diverse research partnerships. This study characterizes the state of the art and future requirements for research on the use of DT and BIM technologies in WDSs and makes a noteworthy contribution to the body of knowledge. Future research should focus on integrating DT and BIM technologies with ML, which represents scalability challenges of real-time anomaly detection integration models, advancing decision-making and operational resilience in WDNs. Full article

This study proposes a model for a wet string grid dust removal system based on gas–droplet–particle turbulent Eulerian–Lagrangian simulation, providing in-depth insights into the dust removal mechanism of droplet groups and its impact on dust collection efficiency. Through numerical simulations and theoretical derivation, we systematically introduce the mathematical expression of the droplet group dust removal efficiency and validate its applicability in wet string grid dust removal processes. The study reveals that the dust removal efficiency of the wet string grid system is influenced by multiple factors, including airflow velocity, droplet distribution, and the interaction between droplets and dust particles. By adjusting spray volume, wind speed, and the geometric parameters of the water mist zone, the dust removal process was optimized. The results show that increasing the wind speed enhances dust removal efficiency, but excessive wind speed reduces the dust capture efficiency of droplets. Additionally, based on simulation results of the flow field, the study identifies key factors influencing the dust removal efficiency of droplet groups and provides valuable insights for optimizing wet string grid dust removal systems in practical engineering. Full article

In coastal regions, the interaction between freshwater and seawater creates a dynamic system in which the spatial distribution of salinity critically constrains the use of freshwater for human consumption. Although saline intrusion is a globally widespread phenomenon, its inland extent varies significantly with hydrological conditions, posing a persistent threat to groundwater quality and sustainability. This study aimed to characterize salinity distribution using an integrated karst-watershed approach, thereby enabling the identification of both lateral and vertical salinity gradients. The study area is in the northwestern Yucatan Peninsula. Available hydrogeological data were analyzed to determine aquifer type, soil texture, evidence of saline intrusion, seawater fraction, vadose zone thickness, and field measurements. These included sampling from 42 groundwater sites (open sinkholes and dug wells), which indicated a fringe zone approximately 5 km in size influenced by seawater interaction, in mangrove areas and in three key zones of salinity patterns: west of Mérida (Celestun and Chunchumil), and northern Yucatan (Sierra Papacal, Motul, San Felipe). Vertical Electrical Sounding (VES) and conductivity profiling in two piezometers indicated an apparent seawater influence. The interface was detected at a depth of 28 m in Celestun and 18 m in Chunchumil. These depths may serve as hydrogeological thresholds for freshwater abstraction. Results indicate that saltwater can extend several kilometers inland, a factor to consider when evaluating freshwater availability. This issue is particularly critical within the first 20 km from the coastline, where increasing tourism exerts substantial pressure on groundwater reserves. A coastal-to-inland salinity was identified, and an empirical equation was proposed to estimate the seawater fraction (fsea%) as a function of distance from the shoreline in the Cenote Ring trajectory. Vertically, a four-layer model was identified in this study through VES in the western watershed: an unsaturated zone approximately 2.6 m thick, a confined layer in the coastal Celestun profile about 9 m thick, a freshwater lens floating above a brackish layer between 8 and 25 m, and a saline interface at 37 m depth. The novelty of this study, in analyzing all karstic water surfaces together as a system, including the vadose zone and the aquifer, and considering the interactions with the surface, is highlighted by the strength of this approach. This analysis provides a better understanding and more precise insight into the integrated system than analyzing each component separately. These findings have significant implications for water resource management in karst regions such as Yucatan, underscoring the urgent need for sustainable groundwater management practices to address seawater intrusion. Full article

The socioecological system (SES) of the Qilian Mountains community—mountains, water, forests, fields, lakes, grasslands, and sands—faces considerable challenges from climate change and anthropogenic pressures. Here, we aimed to examine the coupled coordination relationships within the Qilian Mountains community. Using a comprehensive evaluation index system for the socioeconomic components of the life community, we analyzed the spatiotemporal evolution of the coupled coordination degree (CCD) from 2000 to 2023, identified key hindering factors, and forecasted future trends based on a grey prediction model. The overall CCD achieved a historic leap from near-disharmony to sound coordination. The findings reveal the following: (1) The overall CCD achieved a historic leap from near-disharmony to sound coordination from 0.340 to 0.523, indicating a transition into a synergistic development phase, though with persistent spatial disparities. (2) System coordination is primarily constrained by water, farmland, and grassland subsystems, with water supply–demand imbalance being the foremost regional obstacle. In the Hexi Oasis area, this manifests as a sharp contradiction between farmland expansion and agricultural water demand. In the Qinghai region, it is deeply intertwined with topography, water yield modulus, and the distribution of forested and aquatic areas. (3) GM(1,1) projections suggest a continued upward trajectory for CCD, yet also underscore the complexity and long-term nature of coordinated development. This study established a framework for socioecological system research in arid and vulnerable regions, with the conclusions providing a reference for optimizing national ecological security barrier construction and regional high-quality coordinated development. Full article

Stratocumulus clouds are cloud systems composed of stratiform clouds with embedded convective clouds, possessing strong catalytic potential and serving as key target cloud systems for weather modification operations. In this study, the parameterization of ice nucleation for silver iodide (AgI) particles was applied to the Thompson microphysics scheme in the WRF model. Numerical experiments were designed for a stratocumulus cloud that occurred over the Hulunbuir region, northeastern China, on 31 May 2021, to investigate how the structure and evolution of cloud macro- and microphysical properties and precipitation formation respond to glaciogenic seeding. The simulation results indicate that AgI nucleation increased ice concentrations at 4–5 km altitude, enhancing ice crystal formation through condensation–freezing and deposition nucleation and the growth of ice particles through auto-conversion and riming, leading to increased precipitation. The results also show that owing to the non-uniform distribution of supercooled water within this stratocumulus cloud system, the consumption of AgI and the enhanced ice nucleation release latent heat more strongly in regions with higher supercooled water content. This leads to more pronounced isolated updrafts, altering the structure of shear lines and subsequently influencing regional precipitation distribution after silver iodide seeding concludes. These findings reveal that seeding influences both the microphysical and dynamic structures within clouds and highlight the non-uniform seeding effects within cloud systems. This study contributes to a deeper understanding of the effects of artificial seeding on stratocumulus clouds in high-latitude regions and holds significant reference value for artificial weather modification efforts in mixed-phase stratiform clouds. Full article

Evapotranspiration (ET) plays a vital role in understanding water and energy cycles in forest ecosystems, particularly in tropical regions where rubber plantations are widespread. In this study, a rubber plantation system was used. By combining meteorological data from flux towers and 30 periods of Landsat-8 image data, we estimated the daily ET of a rubber plantation from 2022 to 2024 using the Surface Energy Balance System (SEBS) model. Additionally, the study employed the eddy covariance method to validate the accuracy of the daily average ET estimated by the SEBS model in different source areas, in order to explore the model’s applicability. Simultaneously, we examined the key drivers influencing ET in rubber plantations by analyzing meteorological factors and physiological growth indicators. The results indicated that the SEBS model exhibited the highest estimation accuracy (R² = 0.90, RMSE = 0.43 mm, RE = 15.23%) for the rubber plantation ET in the region 1.5 km away from the flux tower, and the retrieval accuracy of 30 periods of ET was higher (RMSE ≤ 1 mm, RE ≤ 46.84%), indicating that the SEBS model was well-suited for estimating ET in rubber plantations. From 2022 to 2024, the daily average and monthly cumulative ET showed a unimodal distribution, with high summer and low winter values; the average monthly accumulated ET during the wet season (102.75 mm) was found to be significantly greater than that during the dry season (50.61 mm). On the daily and monthly scales, the correlation between atmospheric pressure, temperature, and ET was the most significant. These findings enhance our understanding of rubber plantation water use patterns and support the application of remote sensing models for regional water resource management, offering valuable insights for optimizing irrigation strategies and ensuring sustainable rubber production in tropical regions. Full article