Search Results (30,847)

To investigate the evolution of turbulent-structure scales in decelerating open-channel flow, this study uses a high-frequency particle image velocimetry system in combination with a 28 m high-precision variable-slope flume to conduct controlled flume experiments. The analysis includes cross-sectional specific energy, velocity profiles, turbulence intensity, Reynolds stress, cross-correlation, and power spectral density. The study examines the turbulent statistical characteristics of decelerating flow and the evolution of turbulent-structure scale distributions during streamwise development. The results show that the velocity profile within the decelerating-flow region generally follows a logarithmic distribution, whereas the outer-region velocity profile gradually deviates from the logarithmic law as water depth increases. Compared with uniform open-channel flow, decelerating flow exhibits significantly higher turbulence intensities and Reynolds-stress levels. During flow development, turbulent structures maintain stronger spatial coherence, with spatial correlation increasing as water depth increases. As the nonuniformity coefficient γ increases, the turbulent-structure scale distribution shifts from bimodal to unimodal. Across the measured sections, the dominant turbulent-structure scales range approximately from λ/H = 2.5 to 20, over the ranges Re_τ = 596–849 and γ = 1.2–2.8. During downstream development, turbulent kinetic energy increases progressively and is redistributed from large and small scales toward intermediate scales. These results provide new insight into turbulence-scale redistribution in decelerating open-channel flow. Full article

The river ecosystems of the Qinghai–Tibet Plateau, recognized as a vital component of the “Asian Water Tower,” possess unique hydrological conditions and extreme environments that have shaped key indicator groups, most notably zooplankton. The community dynamics and structural characteristics of these zooplankton exhibit regular spatio-temporal distribution patterns across elevational gradients and seasonal successions. However, the intrinsic mechanisms underlying community succession and their correlations with environmental factors remain poorly understood, and the primary environmental drivers influencing community structure require further elucidation. Based on systematic zooplankton surveys and environmental data collection conducted across the Lhasa River basin from 2019 to 2021, this study established a comprehensive species inventory comprising 113 taxa across four major groups, alongside a multi-dimensional environmental dataset. We analyzed the spatio-temporal heterogeneities of zooplankton community structures—including abundance, biomass, and diversity indices—across different seasons and river reaches. The results revealed the composition and seasonal turnover of dominant taxa, with rotifers accounting for 39.82% of the total taxonomic richness. Mean zooplankton abundance and biomass across the basin were 1.18 ind./L and 343.60 × 10⁻⁵ mg/L, respectively, with peak values observed during autumn and within the Chabalang Wetland. The zooplankton community structure in the upstream, midstream, and downstream reaches, as well as associated wetlands, was significantly correlated with specific environmental factors (p < 0.05), including ammoniacal nitrogen (NH₄⁺-N), magnesium (Mg²⁺), total hardness (TH), potassium (K⁺), iron (Fe²⁺), sodium (Na⁺), sulfite (SO₃²⁻), nitrate ion (NO₃⁻), chloride ion (Cl⁻), total phosphorus (TP), and sulfide (S²⁻). Cl⁻, TH, Mg²⁺, SO₃²⁻, and elevation (Ele) were the key environmental drivers significantly influencing zooplankton abundance across seasons (p < 0.05). Furthermore, zooplankton abundance decreased significantly with increasing elevation during the winter. This research deepens our understanding of community assembly mechanisms in plateau river ecosystems and provides a scientific foundation for aquatic biodiversity conservation and ecological management in the Lhasa River basin. Full article

This paper presents an active prevention and control technology for bed separation water inrush hazards, the effectiveness of which has been validated. Based on the hazard degree identification of such hazards and corresponding preventive measures, the Fuzzy Analytic Hierarchy Process (FAHP) and Expert Grading System (EGS) are adopted to analyze the prevention mechanisms and determine the indicator weights of different influencing factors. The results show that enhancing drainage capacity and accurately predicting bed separation water inflow are two effective measures to prevent water inrush or reduce the hazard risk coefficient. In addition, controlling the development of water-conducting fractured zones and optimizing drainage measures are also effective approaches to reducing the risk coefficient. The research results provide a theoretical basis and practical guidance for the prevention and control of bed separation water inrush hazards, and offer an effective and cost-efficient method for addressing such mining-induced hazards. Full article

The reuse of treated wastewater for agricultural irrigation is increasingly considered a strategic response to water scarcity and climate change, particularly in Mediterranean regions. This study examines the local feasibility and social acceptance of water reuse within the framework of Regulation (EU) 2020/741, focusing on its implementation in Italy. The research combines policy analysis, technical assessment of effluent quality from the GIDA wastewater treatment plant (Prato, Tuscany), GIS-based spatial evaluation, and a mixed-method survey of local agri-food producers. Results show substantial compliance with EU minimum quality requirements, alongside additional constraints arising from national regulatory thresholds. Survey findings reveal cautious but tangible openness among farmers toward reclaimed water use, particularly in response to increasing climate-related pressures. The case of Prato is further analysed within the Prato Circular City and local food policy frameworks, highlighting the role of participatory governance and multi-actor engagement in supporting reuse initiatives. The study contributes empirical evidence on the interaction between EU regulation, national implementation measures, and local socio-institutional conditions shaping peri-urban water reuse systems. Furthermore, it serves as a preliminary framework for future economic feasibility studies and the subsequent regulatory and permitting phases required to operationalize this practice. Full article

This study introduces an intelligent output feedback hybrid $H_2/H_{\infty }$ robust controller for a pumped storage unit regulation system (PSURS), utilizing an enhanced salp swarm algorithm (ISSA). A linearized PSURS model is developed through transfer function analysis. Utilizing this model, a robust controller design is executed using linear matrix inequalities (LMIs) to craft an output feedback hybrid $H_2/H_{\infty }$ controller that aims for both optimal and robust performance. The $H_2/H_{\infty }$ controller designed in this paper boasts a straightforward structure that eliminates the need for multiple-state feedback, simplifying its integration into practical PSURS applications. In addition, the ISSA plays a critical role in the design phase by optimally tuning the weight parameters of the controller to ensure its effectiveness. Simulation tests have demonstrated that this newly developed intelligent output feedback hybrid $H_2/H_{\infty }$ robust controller markedly enhances the stability of the PSURS. It shows superior control quality and robustness compared to traditional controllers. Furthermore, when applied to a multi-machine power system within PSURS simulations, this controller effectively improves system damping and helps mitigate frequency fluctuations. Full article

In flood disaster emergency decision-making, the dynamic changes in expert trust relationships directly affects the efficiency of reaching a decision consensus. This paper constructs a dynamic evolution model of expert trust relationships in flood disaster emergency decision-making from the perspective of preference distance: the initial trust matrix and weights of experts based on four dimensions including cooperation intensity, social relations, background similarity, and subjective initial trust; the cognitive trust is quantified by using the intuitionistic fuzzy Hamming distance, and the trust relationship is dynamically update through the exponential fusion method; the Louvain community discovery algorithm is introduce to achieve dynamic clustering of experts and weight updates of experts in combination with the dynamic changes in trust relationships; and a consensus feedback adjustment mechanism is designed to optimize the preferences of experts with lower consensus. At the same time, the dynamic trust model is verified by combining a flood disaster case. Case validation shows that the model completes consensus iteration in just four rounds, with the maximum increase in cognitive trust due to opinion convergence reaching 0.18 during the evolution process. The model effectively captures changes in trust among experts during decision-making, improving consensus convergence speed while ensuring that the final solution aligns with the comprehensive considerations required in emergency scenarios. This study provides a quantitative tool for large-group decision-making in flood emergencies under high-pressure, information-poor environments; one that balances dynamic trust evolution with efficient consensus building. Full article

This study contributes to the modeling and optimization model for reverse osmosis water treatment (ROWT) due to a lack of economic and operational aspects. This study proposes a hybrid modeling and optimization framework using a hybrid artificial neural network (ANN) and genetic algorithm (GA) to enhance the accuracy of economic and operational predictions for ROWT. The ANN model is developed using seventeen key process parameters extracted from various ROWT plants, including flow rate, pH, conductivity, and turbidity. The GA is employed to optimize the network architecture and learning parameters based on the mean absolute percentage error (MAPE) as the fitness function. The findings of this study indicate that the GA-optimized model significantly outperforms the baseline model, reducing MAPE for the economic aspect (84.9% improvement) and the operational aspect (32.2% improvement). The findings from this study indicate that the hybrid ANN–GA approach is a management decision-making tool for reducing expenses without compromising water quality in ROWT management. The practical implications of this study are that predictions not only meet operational parameters but also predict expenses incurred, allowing managers to plan future budgets by optimizing ROWT resources and maintenance activities. Full article

Municipal sewage sludge is an environmental liability but also an energy-rich biomass that can support circular economy resource recovery. Here, we benchmark thin-layer drying of dewatered municipal sewage sludge (sludge cake) (40 g; layer thickness ≤ 5 mm) under open-air, convective hot air (40–150 °C), and microwave (70–1200 W) conditions to quantify drying kinetics, hygienisation indicators, and a screening-level energy-use proxy. High-power microwave drying reduced the time to constant mass from 32 h (open air) and 25 h 05 min (40 °C convection) to 20 min (900 W) and 14 min 05 s (1200 W). Faecal indicators (total/thermotolerant coliforms and presumptive Escherichia coli) were below detection after ≥100 °C convection or ≥300 W microwave treatment, while mesophilic aerobes and sulfite-reducing Clostridium spp. decreased by ~3–4 log10 with increasing exposure. A dragonfly-optimised ε-support vector regression model (DA–SVR) predicted drying trajectories across modes (overall RMSE ≈ 0.79 percentage points; held-out RMSE ≈ 1.47; R² ≥ 0.99). Overall, microwave thin-layer drying coupled with DA–SVR decision support enables constraint-based screening of sewage–sludge conditioning windows for logistics and thermal valorisation pathways; the framework can be extended to incorporate additional analytical endpoints where available. Full article

The interaction between circular piers and turbulent open-channel flow generates complex three-dimensional structures, including horseshoe vortices at the pier base and wake vortices downstream. These structures increase vertical velocities, pressure fluctuations, and shear stresses, contributing to erosion and structural instability. Although these phenomena have been widely studied, limited attention has been given to surface geometric modifications as a flow-control strategy. This study employs Large Eddy Simulation (LES) to evaluate the influence of a hexagonal dimple pattern on circular piles in a free-surface channel. The dimples were defined by varying diameter, depth, and spacing to reduce vertical velocity and alter vortex formation. The computational domain represents a 0.40 m wide, 12 m long, and 1.2 m high rectangular channel, with an inlet mass flow of 9.4 kg/s and 0.10 m water depth. Model validation against particle image velocimetry (PIV) data showed 99% correlation, confirming numerical accuracy. Results demonstrate that textured surfaces modify flow dynamics by enhancing kinetic energy dissipation and generating micro-vortices that weaken dominant structures. The optimal configuration (6 mm diameter, 2 mm depth, 1 mm spacing) reduced downward vertical velocity by 42% and wake vortex shedding frequency by 24%, indicating improved hydraulic stability and erosion mitigation potential. Full article

Sewerage systems are a main element of a city’s infrastructure. Roughness coefficients are fundamental parameters for sewage system operation. The intermittent nature of the flow leads to the appearance of deposits that become an integral part of the sewerage systems. Deposited material not only leads to the loss of hydraulic capacity and decreases the concentration of dissolved oxygen (which is found in direct relation to all quality parameters), but it also results in more transported particles being intercepted. In the design calculations, the roughness coefficient is estimated rather than calculated. It has been demonstrated that the estimation of stress within and above roughness elements improves the predictive capability for the concentration of suspended sediment. In this study, we focused on a local evaluation of the roughness coefficient when the flow velocity is below the minimum self-cleansing velocity. Some authors consider the selection of the most reliable method for estimating bed shear stress to be the main challenge. Other authors have suggested that all possible methods should be applied simultaneously to achieve a reliable bed shear stress estimation, knowing that the roughness coefficient can be determined through the shear boundary stress. We calculate the local roughness coefficient in Manning’s equation using a laboratory model, considering clear water flowing over a solid boundary with consolidated deposits, represented by artificial roughness elements (calibrated hemispheres). The European standard EN 752:2017 specifies a minimum average cross-sectional velocity of 0.7 m/s for pipe self-cleansing. This study established the range of possible roughness coefficient values when the minimum velocity design criterion is not met. The second criterion was to consider acceptable a sediment deposit occupying between 1% and 2% of the collector diameter. Velocity distributions around artificial roughness and statistical parameters of the turbulent flow were obtained using a PIV system. Five methods were implemented and the range of roughness coefficient values varied between 0.007 and 0.023. This variation is closely related to sewer performance. We selected the dissipation method as the primary reference for this study, as it is most closely aligned with the underlying physics of flow over roughness elements. This approach allows for robust validation by correlating multiple characteristic mechanisms of the turbulent cascade. Full article

The enhancement of startup and performance in a Tetradesmus obliquus-polyurethane sponge biofilm system was investigated via the regulation of the phytohormone Indole-3-acetic acid (IAA). IAA supplementation at 1 and 5 mg/L increased biofilm biomass and chlorophyll a content, with the maximum biofilm biomass reaching 48.2 mg/g, and improved nutrient removal performance under shock-loading conditions, particularly for total nitrogen (TN) and total phosphorus (TP). IAA treatment was associated with EPS remodeling, including an increase in the protein/polysaccharide ratio to 0.68 and a 16% enrichment in tryptophan-like protein components. These EPS-related changes coincided with a decrease in the absolute zeta potential to −2.49 mV, which may be relevant to enhanced initial biofilm development. The corresponding EPS-related changes were characterized by three-dimensional excitation–emission matrix (3D-EEM) and Fourier transform infrared (FTIR) analyses using representative concentrations. Furthermore, the IAA-treated biofilm showed improved resilience under low, medium, and high loading conditions, with the most favorable TN removal reaching 87% at 1 mg/L IAA. These results suggest that IAA supplementation at 1 and 5 mg/L can promote microalgal biofilm start-up and improve nutrient-removal resilience under the tested conditions, with 5 mg/L showing the strongest response in biofilm growth and structural characterization. Full article

Ground subsidence and shaft lining deformation caused by compressed dewatered bottom aquifers in deep unconsolidated strata mining areas are critical engineering challenges, making the study of the seepage–soil deformation coupling mechanism during groundwater injection remediation vital. This study built a visual cylindrical model (1025 mm × 150 mm); formulated well-graded analogous materials based on the D₂₀ principle to simulate sandy gravel layers; embedded FBG sensors at 200/400/600 mm depths, combined with a dial indicator on the model top; and conducted two water injection–dewatering cycles. Results indicate: water injection generates excess pore water pressure, placing the entire model in a tensile stress state with top rebound; post-injection vertical stress redistributes (tension above the injection point, compression below, and an interlaced transitional band), validating the necessity of full-section injection; during the second injection–dewatering cycle, tensile strain at the upper monitoring point reaches 597.77 με, while compressive strain at lower depths reaches −253.90 με, internal deformation stabilizes within 6.5–10.0 days, injection improves the in situ stress state by reducing effective stress, and the deformation of the field strata remains in a stabilization period, with the stabilization time decreasing as the depth of the strata increases. This study clarifies the temporal evolution and representative spatial variation in internal strain at monitored depths during injection, providing theoretical and design references for optimizing water injection schemes to mitigate coal mine shaft damage. Full article

Fenton-based processes are widely used advanced oxidation methods that are known for degrading persistent pollutants. However, these techniques often generate significant amounts of iron-containing sludge, which poses environmental disposal challenges due to its complex composition. Furthermore, the sludge produced by the Fenton process contains a high content of Fe(III) compounds, which can serve as an iron source to stimulate dissimilatory iron reduction (DIR), enhancing the performance of anaerobic digestion. Based on the characterization results from a previous study, this work investigated the use of the ferrous precipitate generated by the electrochemical peroxidation process applied to tannery wastewater treatment as an additive to enhance volatile fatty acids (VFAs) production during dark fermentation. The performance of ferrous precipitate (R-Fe₃O₄) was compared to that of conventional magnetite (Fe₃O₄) during dark fermentation under high organic loading conditions, emphasizing their potential to enhance hydrolysis efficiency and VFAs production yields, while promoting sustainable resource recovery and reuse within a circular bioeconomy framework. The results showed that the addition of both Fe₃O₄ and R-Fe₃O₄ significantly increased the VFAs yields, with a predominance of long-chain fatty acids. The presence of CaCO₃ in the ferrous precipitate contributed to maintaining a stable pH environment, supporting microbial activity and enhancing the hydrolysis of soluble compounds. Moreover, the availability of essential micronutrients within the ferrous precipitate favored greater microbial diversity. Consequently, the addition of R-Fe₃O₄ promoted VFAs production, even at higher organic loading rates, suggesting a promising application of Fenton-based by-products as functional additives to improve the economic and environmental performance of the dark fermentation process. Full article

Promoting irrigation efficiency is a central pillar of global water sustainability strategies but empirical evidence shows a counterintuitive outcome named the irrigation efficiency paradox or rebound effect. This occurs when on-farm water savings do not translate into basin-scale conservation and may even intensify water scarcity. This paper critically re-examines the rebound effect, moving beyond conventional hydrological and economic explanations toward an integrated socio-hydrological perspective. We argue that the paradox is not merely a technical accounting issue or a form of the Jevons Paradox, but a systemic problem arising from interactions among behavior, institutions, and political economy. The review traces the concept’s evolution and synthesizes global evidence on its main drivers and controversies. It critically evaluates dominant research paradigms, emphasizing the need for greater methodological pluralism. Significant gaps remain, particularly regarding behavioral economics, political economy, and social and environmental externalities. We conclude that overcoming the efficiency paradox requires a policy shift from technological fixes to transformative governance. Full article

The development of renewable energy and the increasing demand for electricity underscore the importance of pumped storage for grid stability. Under low-flow pump operating conditions, pump-turbines frequently exhibit hump characteristics, causing severe hydraulic instability and strong pressure pulsations. This study investigates the formation of a hump using full-channel numerical simulations based on the Scale-Adaptive Simulation turbulence model. The numerical flow–head characteristics were validated against the available experimental H–Q data, while the pressure pulsation results were used for qualitative mechanism analysis. The results reveal three major mechanisms: pre-swirl and spiral backflow in the draft tube, non-uniform runner inflow, and vortex flow-induced separation in the wicket gates. An analysis of entropy production reveals that vortex dissipation is responsible for as much as 71% of hydraulic losses in the hump region. In order to mitigate these effects, four stabilizing fins were installed inside the draft tube. The simulations indicate that the fins possess the capability to inhibit swirl and backflow, confine the vortices within the fin–runner interface, improve inflow uniformity and reduce overall hydraulic losses. As a result, the structural modification significantly attenuates the pressure pulsation amplitudes at key monitoring points and visibly shortens the recovery periods. The region of the hump and positive slope of the performance curve are considerably reduced while the head near the region of the hump is increased. Although the intrinsic hump characteristic is still present, the fin-based flow-control strategy can effectively improve the performance and stability of the pump-turbine, which can guide the design and optimization of high-efficiency pumped-storage plants. Full article