The substantial spatiotemporal variation of dissolved oxygen (DO) during the aeration process significantly affects the pollutant removal efficiency in wastewater treatment. Traditional monitoring methods often provide non-intuitive results and delayed information. In this study, computational fluid dynamics (CFD) and the Activated Sludge Model No.1 (ASM1) were combined to systematically investigate the reaction processes of wastewater components in the aerobic tank of an integrated wastewater treatment unit under different aeration conditions, with a specific focus on the removal of chemical oxygen demand (COD), ammonium nitrogen (NH4+-N), and total nitrogen (TN). An oxygen mass transfer model based on the double-film theory was incorporated into ASM1 to explicitly link gas-phase oxygen to liquid-phase DO dynamics and to refine the representation of aerobic-anoxic reactions, and a population balance model (PBM) was introduced to quantify the effects of bubble coalescence and breakup on oxygen transfer. The CFD-PBM predictions of the aeration flow field were validated against particle image velocimetry (PIV) measurements, with relative errors below 6.49%, and the integrated CFD-ASM1_2O modelwas further calibrated and confirmed using actual wastewater treatment data, showing good agreement in pollutant removal efficiencies. In addition, a specific energy consumption (SEC) index was proposed to evaluate the aeration economy. This study provides a mechanistic link between flow field characteristics, bubble behavior, oxygen transfer, and biochemical reactions, supporting energy-efficient optimization of aeration systems.

Pedestrian detection technology has been widely applied in public places, which is crucial for crowd management and safety control, especially in high-density scenarios where traditional detection methods face challenges in terms of robustness and accuracy due to frequent occlusion, extreme scale change and background interference. To address the above issues, a novel pedestrian detection model YOEiFPN is proposed for dense crowd scenes based on the YOLO11 framework in this paper. Firstly, the EfficientNetV2 module is absorbed as the backbone in the model to extract fine and rich semantic features efficiently from diverse scales of raw images, enhancing the network’s capacity to handle varied pedestrian sizes and appearances. Besides, the BiFPN module is developed considering efficient and robust cross-scale information flow to facilitate the multi-scale feature fusion. Finally, the novel design and collaborative work of the two modules can improve feature representation and reduce computational complexity. Five datasets covering various crowd densities, occlusion levels, perspectives and scenarios are selected as the benchmark. Evaluation metrics such as Precision, Recall, mean Average Precision (mAP) and F1-score are used to quantify the model performance. The ablation experiment results indicate that incorporating both modules in YOEiFPN can achieve better detection accuracy compared to models with only a single module replaced. The average precision of the proposed model on multiple datasets exceeds 90%, which is higher than existing object detection models, particularly under severe occlusion and dense crowd conditions. Furthermore, due to its efficient lightweight design, the proposed model is superior to other models in parameter count, gradient occupancy and inference speed. The study provides a practical and robust framework for efficient pedestrian detection, which is helpful for crowd surveillance and risk identification in high-density public places.

In recent years, flood disasters have frequently impacted urban areas, resulting in significant casualties and property loss worldwide. To ensure the safety of residents during flooding events, it is urgent to conduct large-scale evacuations in flood-prone areas. However, the impacts of flooding on urban evacuation are dynamically coupled with real-world conditions, which are often overlooked in current research. Therefore, a dynamic evacuation planning framework is proposed in this paper to provide safe and efficient evacuation routes for urban population under various flood scenarios. Firstly, the flood spreading process is accurately simulated across different rainfall patterns. Secondly, the dynamic influences of floods on travel speed, instability risk and road capacity are incorporated and quantified in the evacuation planning. Finally, the quickest evacuation routes are generated for evacuees in different residential areas to achieve both safety and efficiency objectives. Based on a case study, it is found that both the increased evacuation preparation time and larger rainfall intensity have an adverse effect on the evacuation safety and efficiency, significantly reducing the evacuation success rate under severe floods. The expressways carrying the largest traffic volume are crucial for ensuring the efficient evacuation during floods. Furthermore, the uneven utilization of shelters due to the flood impact and limited capacity should be considered in urban planning. The study can bring practical guidance for emergency departments and decision-makers to mitigate disaster losses and develop evacuation schemes in urban floods.

In recent years, urban floods caused by heavy rains occur frequently, leading to heavy casualties and economic losses worldwide. Transportation network serves as the backbone of urban lifeline engineering, which is crucial for ensuring residents' safety and emergency evacuation in flood disasters. Therefore, to investigate the flood hazard for pedestrians and vehicles during the rainstorm, an urban rain-flood coupling model is firstly established and validated to accurately simulate the flood inundation process by fusing multiple types of high-precision data. Four rainfall patterns with return periods of 5 years, 10 years, 50 years and 100 years are designed based on the Chicago rainfall method. The critical instability conditions for heterogeneous pedestrians and vehicles are obtained. Finally, a quantitative assessment framework for flood hazard on urban roads is proposed based on flood simulation results and instability risk analysis. The results indicate that the flood hazard level for pedestrians and vehicles increases with the increment of rainfall intensity and duration. Compared to pedestrians, the adverse impact of floods on vehicles is greater since the length of dangerous roads for vehicles increases by 4.5 times. Compared with adults and SUVs, children and cars are more vulnerable to floods, with the length of dangerous roads increasing by 6 times and 90 % respectively. In emergency circumstances, based on the flood hazard distribution and evacuation distances, feasible evacuation routes and evacuation modes in different residential areas are planned to ensure the safety of citizens. The study is helpful to improve emergency responses and traffic management under urban flood disasters.

Artificial intelligence enables rapid wastewater quality monitoring through soft sensing techniques, effectively overcoming traditional digestion time limitations. This study evaluated four predictive models: support vector regression (SVR), polynomial ridge regression (PolyRidge), multilayer perceptron (MLP), and long short-term memory (LSTM). A dedicated dataset combining experimental measurements with ASM1-based simulations incorporating biological reactions and multiphase flow was established. Data preprocessing addressed concept drift from variability and outliers, while augmentation strategies enhanced the limited dataset. Optimized models achieved mean determination coefficients of 0.7867 (SVR), 0.7933 (PolyRidge), 0.52 (MLP), and 0.56 (LSTM). PolyRidge demonstrated superior accuracy with 6.37-min training, followed by SVR (10.74 min). Notably, MLP's aeration prediction accuracy improved exponentially with augmentation intensity (small noise injection, k-NN, and MICE R2 is 0.7346, 0.7583, and 0.7802), reaching 0.9845. Based on on-site tests and prediction analysis in Guizhou, after removing missing and abnormal data points, all models show good fitting accuracy for COD and TN, with SVR performing best overall. These findings highlight the potential of specific machine learning approaches for efficient and accurate wastewater quality prediction.

Aeration conditions are critical for controlling hydrodynamics and membrane fouling in membrane bioreactors (MBRs), yet the role of aeration position in integrated sewage treatment systems remains poorly quantified. This study investigates an integrated anaerobic-anoxic-oxic-MBR membrane tank using a computational fluid dynamics-population balance model with non-Newtonian rheology of the mixed liquor. Aeration positions 5-45 mm below the membrane module were evaluated for their effects on flow structure, bubble distribution, and membrane-surface shear. The model was validated against measured bubble rise velocities, with a maximum relative error of 4.67%. The results demonstrate that aeration position strongly governs the formation of high-velocity cores, low-velocity zones, and gas holdup distribution, and thus the spatial patterns of turbulent kinetic energy and gas-liquid shear on the membrane surface. Increasing the aeration position to an intermediate level enhances bottom turbulence and mixing, reduces the fraction of low-velocity regions,and alleviates sludge deposition,whereas excessively high aeration positions lead to non-uniform velocity and gas distribution and aggravated local membrane fouling. Under practical operating conditions, an intermediate aeration position also helps control local sludge concentration and floc size, thereby mitigating pore blocking development. Overall, the findings highlight aeration position as a key yet often overlooked design and operational parameter for optimizing integrated MBR performance.

This study investigates the factors influencing the performance characteristics of annular jet pumps (AJPs) conveying non-Newtonian fluids, to enhance their suction capability for marine organisms such as jellyfish, which exhibit properties close to non-Newtonian fluids. Based on the power-law fluid model, realizable k-epsilon model, and volume of fluid (VOF) model, shear-thinning carboxymethyl cellulose (CMC) was selected to simulate marine organisms like jellyfish. Fluent software was employed to numerically simulate the performance characteristics and internal flow field of the annular jet pumps. The results demonstrate that the shear-thinning effect of non-Newtonian fluids reduces the maximum efficiency point of annular jet pumps and decreases the flow rate ratio corresponding to this efficiency point. As the concentration of CMC solution increased to 0.5%, the maximum efficiency point decreased by 5.5%, and the flow rate ratio corresponding to this efficiency point dropped from 1 to 0.8. These findings provide reference and insights for analyzing the full flow field of annular jet pumps pumping shear-thinning non-Newtonian fluids and for structural design of such pumps.

Micro- and nanoplastics (MNPs) are emerging pollutants in agricultural ecosystems, accumulating in soils and adversely affecting plant growth and crop yields. Although their toxicity is increasingly reported, the role of stress mitigators in reducing MNPs-induced toxicity in soil-plant systems remains insufficiently summarized. This review evaluates current research on mitigation strategies, including nanoparticles, phytohormones, biochar, chemicals, nutrients, plant growth-promoting bacteria and rhizobacteria, fungi, and signaling molecules. Evidence shows that these mitigators can reduce MNPs-induced stress by improving rhizosphere microbial communities, increasing plant growth and photosynthetic efficiency, and regulating biochemical, transcriptomic, and metabolomic responses. In addition, important tolerance pathways and mechanisms influenced by these mitigators are also discussed. The review highlights major knowledge gaps in existing studies and proposes future research directions. Overall, it provides a concise framework to guide the development of effective mitigation approaches to address MNPs contamination and improve sustainable crop production under emerging environmental stress conditions.

Organic cathodes hold promise for potassium-ion batteries (PIBs) but suffer from dissolution and poor conductivity. Here, we report a molecular grafting strategy to construct a stable beta-PTCDA-D cathode by incorporating the nitrogen-rich heterocyclic linker 3,5-diamino-1,2,4-triazole (DAT) into perylene-3,4,9,10-tetracarboxylic dianhydride (PTCDA). DAT incorporation promotes charge transfer and reduces the energy barrier for K+ storage. Meanwhile, the amidation reaction generates a robust molecule with extensive pi-conjugation, strong hydrogen-bonding interactions, and enlarged interlayer spacing. These structural advantages improve electronic conductivity, suppress dissolution, and stabilize K+ intercalation/deintercalation, thereby maintaining structural integrity during cycling. As a result, beta-PTCDA-D delivers a high reversible capacity of 100 mAh g-1 at 100 mA g-1, outstanding rate performance (75 mAh g-1 at 500 mA g-1), and excellent long-term stability with 76% retention after 200 cycles. Furthermore, a full cell paired with nanographite further demonstrates practical applicability. This work demonstrates the effectiveness of molecular interaction engineering in stabilizing small-molecule organic cathodes and provides a viable pathway for high-performance and sustainable PIBs.

With its ability to operate efficiently at low flow rates and high-water heads, the Hydraulic pump as turbine(PAT) exhibits considerable promise for micro-hydroelectric power generation. The unsteady behaviour, including axial-force variation, pressure-pulsation, and flow-field model, are revealed by wavelet transform analysis and proper orthogonal-decomposition (POD) method. This study investigates the unsteady-flow and pressure-pulsation characteristics of a Hydraulic PAT across 0.6Qd, 0.8Qd, 1.0Qd, and 1.2 Qd flow rates. This paper explores the effect of pressure pulsations near the volute-tongue due to rotor-stator interaction, amplified by flow obstruction and vortex-shedding at higher blade passing frequency. Entropy production is proposed to calculate the hydraulic losses in Hydraulic PAT. The vortex identification method was applied to analyze the vortex structures under varying flow conditions, with a larger vortex region and higher turbulence intensity observed at 0.6 Qd compared to 0.8 Qd. The novel application of POD analysis revealed jet-wake dominance at design flow rates and secondary flow structures at lower flow rates. POD analysis shows that at flow rates of 0.6Qd, 0.8Qd, 1.0Qd, and 1.2Qd, the first-order mode energy contributions were 43.2%, 60.1%, 72.6%, and 31.1%, respectively, indicating a dominance of jet-wake at design-flow and an increase in secondary flow-structures at lower flowrates.

Oil-Immersed Motor-Pumps (OIMPs) integrate electric motors and hydraulic pumps and serve as the core energy conversion unit for distributed electrification drives of high-end equipment. Significant energy dissipation caused by oil churning within OIMPs severely limits operating efficiency. However, there is a lack of effective evaluation methods for churning power loss of OIMPs, hindering the optimization for high-efficiency operation. For that, this study proposes the multi-dimensional coupling model for churning power loss under a wide speed range, which couples a three-dimensional (3D) oil churning model with a one-dimensional (1D) oil source model. Coupling is achieved by mapping the oil sources onto the narrow annular surfaces, where 27 dynamic overset interactions are constructed to provide moving boundaries for these annular surfaces. Besides, a specialized and visualized test rig is developed to validate model accuracy, which achieves an average relative prediction error of 5.08%. During the conversion from electrical energy to hydraulic power, the complex compound motion intensifies turbulent dissipation and churning power loss. The total churning power loss exhibits a sharp nonlinear increase with speed, reaching more than 35% of the rated output power at 16000 r/min. The motor rotor dominates the total loss at 65.02%, while cylinder block and piston-slipper assemblies account for 12.51% and 20.56%, respectively. The proposed model clarifies the churning loss mechanism and provides essential guidance for the energy efficiency optimization and thermal management of wide-speed OIMPs.

With the continuous expansion of urban population and increasingly convenience of travel conditions, the frequency and scale of mass events have increased significantly, which has brought severe challenges to crowd safety and traffic management. In reality, pedestrians mainly rely on vision to obtain information of the surrounding environment. Therefore, based on the information processing mechanism of individuals, a visual-based minimum cost velocity model composed of the perception layer, decision layer and operation layer is proposed in this paper. Specifically, pedestrian firstly acquire the visible environmental information within their perception field in the perception layer, and then determine the velocity direction based on the minimum cost function considering the distance factor, inertial factor and psychological factor. Meanwhile, the velocity magnitude is obtained based on the headway-speed relation in the decision layer. Finally, collision between pedestrians is resolved and the final comfortable movement for crowds is executed in the operation layer. Besides, both the qualitative and quantitative methods are adopted to verify the reliability and generality of the model in various scenarios at the individual and collective levels. The validation results indicate that our model can not only reproduce typical phenomena in crowd dynamics, but also accurately simulate the process of pedestrian movement in typical scenarios. Furthermore, the comparison results with other existing models also demonstrate the superiority of the model. The proposed model provides a more reasonable and realistic framework for predicting crowd flow, which is helpful to deeply understand the complex laws of pedestrian dynamics.

To enable the precise prediction and control of erosion in hydraulic fracturing pipelines, this study employs a CFD-DEM method coupled with a wear model to quantitatively analyze the influence of shear-thinning fracturing fluids on proppant transport and elbow erosion. The study reveals a critical, non-monotonic effect of fluid concentration on erosion. Compared to the water baseline, the low-concentration (0.2%) fluid, by enhancing particle impact kinetic energy, counter-intuitively caused the maximum elbow erosion rate to surge by approximately 40%. However, as the concentration was further increased to 0.4%, the fluid’s effective viscosity became dominant, causing the maximum erosion rate to plummet relative to the 0.2% case, ultimately falling to a level ∼8% below the water baseline. More importantly, the high-concentration fluid altered particle trajectories, leading to a significant shift of the peak erosion zone from the elbow’s midpoint (∼77°) to its outlet (90°). This finding quantifies the complex impact of fracturing fluid rheology on erosion and provides critical data and a new perspective for proactively managing pipeline integrity by optimizing the fluid’s non-Newtonian properties.

Understanding the underlying mechanisms behind cavitation-induced noise plays a crucial role in promoting sustainable marine technologies and mitigating underwater acoustic pollution. To address the difficulty of capturing nonlinear flow-acoustic interactions under cavitating conditions, a novel hybrid method, this study proposes a novel hybrid method based on the DDES turbulence model and developed a numerical prediction method for cavitation noise combining three-dimensional implicit vortex sound theory with cavitation. The method is validated by experiment, with head and efficiency prediction errors less than 4.2% and noise level deviations within 4.8%. Results show that: as the cavitation number drops, vapour cavities extend along the blade passage and contribute to intensified vortex structures near the impeller's entrance. Pressure pulsation frequencies are 0.167fBPF at the impeller and 1fBPF at the volute, with strong dynamic-static interference near the volute tongue. Flow-induced noise exhibits a discrete distribution, with peak sound pressure levels at 1fBPF in the low-frequency range and 6-7fBPF in the mid-to-high frequencies. Bubble pulsation amplifies noise at sigma = 0.07, 0.062, and 0.060, while severe flow blockage at sigma = 0.051 reduces noise levels. Noise sources are primarily concentrated near the volute tongue and impeller-volute junction, where impeller rotation induces a 'jet wake'-like pattern, and impeller motion significantly influences noise source distribution near the volute tongue. The synergy angle analysis reveals efficient acoustic radiation near the impeller inlet. These findings provide theoretical support for low-noise design and cavitation noise control in hydraulic machinery.

In integrated wastewater treatment systems(IWTS), aeration accounts for the most energy-intensive process. However, the quantitative influence of initial bubble diameter (d0 = 1-4 mm) on aeration efficiency remains insufficiently characterized. This study employs computational fluid dynamics coupled with the Population Balance Model (CFD-PBM), incorporating an oxygen transfer model to predict the impact of d0 on oxygen transfer efficiency in the aerobic tank. Results reveal that dissolved oxygen (DO) distribution exhibits a clear dependence on d0. Specifically, a d0 of 2 mm not only maintains a high oxygen transfer rate (kLa = 6 × 10-3 s-1), but also significantly enhances the vertical uniformity of DO distribution. The oxygen transfer coefficient (kL) is influenced by both flow field and d0, with the latter playing a more dominant role. For small-scale IWTS (depth ≤1 m), a d0 of 2 mm is recommended as the optimal aeration design parameter, as it achieves an optimal balance between oxygen transfer efficiency and DO distribution uniformity.

When using supplementary cementitious materials to replace cement partially, the carbon emissions of cement products can be reduced, but it often leads to reduced strength. This study explores the application potential of carbide slag (CS) and calcined coal gangue (CCG), byproducts of acetylene production, to partially replace cement. The effects of these two materials on the macroscopic properties and microstructure of cement-based materials were analyzed through systematic experiments. The compressive strength, ultrasonic pulse velocity, and electrical resistivity test results showed that replacing 20% of cement with CCG did not cause significant changes in the test results of the specimens. An X-ray diffraction (XRD) analysis showed that these two materials can produce additional hydration products. Scanning electron microscopy images (SEM) further revealed that CCG produces hydration products to fill microscopic pores. Thermogravimetric analysis (TG) results after 28 days showed that with the addition of supplementary cementitious materials, calcium hydroxide (CH) in CS reacts with CCG, resulting in the consumption of CS. Finally, the environmental impact of CS and CCG was assessed. It was found that CS is more favorable for reducing carbon emissions compared to CCG. However, when considering the effect of cement replacement on compressive strength, combining these two materials is more advantageous for sustainable development. Overall, the use of CS and CCG demonstrated good performance in promoting sustainable development.

As key emergency equipment, high-flow pump devices play a vital role in urban flood control and drainage, and their hydraulic performance directly influences the safety and stability of the entire system. To meet diverse drainage demands during emergency operations, a new type of high-flow drainage pump, capable of operating in series, parallel, and variable-speed modes, has been developed. Using the SST k-ω turbulence model combined with entropy production theory and pressure pulsation analysis, unsteady numerical simulations were conducted to investigate the transient internal flow under series and parallel operating conditions. The numerical model was verified through comparison with experimental hydraulic-performance data, demonstrating good agreement. The results show that under series operation, the pump speed decreases from 1500 r/min to 193 r/min before reversing to −1748 r/min, while under parallel operation the runaway speed reaches −1657 r/min. The flow rate and torque exhibit strong nonlinear variations, with reverse flow and oscillatory behavior appearing in the impeller passages. During the runaway stage, entropy production peaks at 28.17 W/K under series conditions and 29.09 W/K under parallel conditions, with turbulent dissipation accounting for more than 69% of the total. High-entropy regions extend toward the impeller outlet, while energy losses are predominantly concentrated in the secondary suction chamber, contributing 47.56% and 57.12% under the respective conditions. Pressure pulsation analysis indicates that the dominant frequency components are concentrated at the blade-passing frequency (100 Hz) and its harmonics, with the strongest fluctuations near the primary impeller outlet. These results provide theoretical and engineering guidance for improving the efficiency and stability of emergency drainage systems.

Smartphone use while walking has become increasingly prevalent, which significantly affects pedestrian safety and increases the risk of traffic accidents, especially in avoidance scenarios. Therefore, to reveal the avoidance mechanism and gait features under mobile phone use distractions, a series of walking experiments under varying distraction conditions including no phone use, text-browsing, message-sending, and video-watching were conducted. Multiple types of data such as physiological signals including the electrocardiogram (ECG) and electrodermal activity (EDA), and high-precision motion trajectories were synchronously obtained. To characterize the entire avoidance process, three critical positions including the start point, maximum point and end point are identified in this paper. The results show that distracted pedestrians initiate evasive maneuvers when they are close to obstacles, whereas non-distracted pedestrians prefer to avoid obstacles in advance. Moreover, the right-side avoidance strategy is adopted by most pedestrians under different distraction levels. Physiological signal indicates that distracted pedestrians experience elevated levels of psychological stress. Besides, the walking speed is significantly decreased in distracted circumstances. The gait analysis demonstrates that distracted pedestrians exhibit shorter step length, larger step width and longer step time during the avoidance phase. Furthermore, the real-time messaging task consumes large cognitive resources of pedestrians, which has the most pronounced impact on pedestrian safety. The study elucidates how the use of smartphones affects the avoidance mechanism of pedestrians, which can help develop intervention measures and safety strategies to reduce the risk of distracted walking in public places.

Flood disasters occur frequently worldwide, causing a large number of casualties and property damage. Urban subway stations are one of the most vulnerable places to flooding. Therefore, to evaluate the flood hazard for passengers in subway stations, an evacuation safety assessment method is proposed in this paper. The flood inundation process is firstly simulated, and the flood depth and flow velocity in subway stations are obtained based on the hydrodynamic model. Secondly, a crowd evacuation model considering the dynamic flood impacts is established, and the simulation results are validated through the qualitative and quantitative methods. Thirdly, the ASET is calculated based on the critical instability status of pedestrians in floods, and the RSET is obtained based on the simulated evacuation time. Finally, the evacuation safety index (ESI), namely the difference between ASET and RSET, is proposed to accurately identify the danger and quantitatively assess the crowd safety at both micro and macro levels in flood scenarios. The results indicate that the staircase areas are more dangerous due to the large water speed, especially under the large inlet flow and evacuee number. Moreover, with the increase of preparation time, the ASET significantly decreases while the RSET increases notably, making it difficult for the crowd to evacuate safely. The study provides useful insights for flood hazard assessment in subway stations, which can help the emergency department to make timely decisions and formulate evacuation plans to ensure the safety of passengers in sudden flood events.

The vortex interactions in the rotor tip region and the resulting loss significantly reduce energy utilization efficiency of gas turbines. The vortex interactions and loss generation mechanisms in the tip region, under the effects of suction side cutback rim, are investigated numerically in this paper. The results show that a large notch could cause intruding gas to disrupt the scraping vortex, increasing the internal gap loss. More importantly, the rim notch causes a dramatic increase in leakage near the notch, leading to the formation of the leading-edge tip leakage vortex (LTLV). The interaction between the LTLV and the upper passage vortex (UPV) causes significant local loss and leads to the rapid dissipation of the UPV. This is beneficial for suppressing the interaction and mixing losses between the UPV and the tip leakage vortex (TLV) downstream. These two opposing effects mean that there may be an optimal rim notch configuration where the strength of the LTLV is just right to balance these two types of losses, potentially improving turbine aerodynamic performance. The effect mechanisms of the LTLV on the TLV and the UPV could provide guidance for flow control technologies based on the introduction of novel vortices.