Abstract:Understanding the three-dimensional(3D) structure distribution of granular sludge is crucial for its settlement ability and stability, yet research on the 3D pore structure and distribution characteristics remains scarce. In this study, anerobic ammonium oxidation granular sludge is scanned using synchrotron radiation X-ray phase microscopic computed tomography,and its structure is reconstructed using Avizo. The diameter, spatial distribution, and fractal dimension of the pore structure are analyzed to establish a pore network model for granular sludge. Subsequently, absolute permeability calculations are performed. This research contributes to the theoretical foundation for the stable and efficient application of granular sludge systems in sewage treatment.

Abstract:Controlled indoor experiments were conducted to measure the excitation emission matrix spectroscopy (EEMs), SUVA₂₅₄, TN, TP and DOC of both ice and water samples during the freeze-thaw process. The results showed an increase in the fluorescence intensity of tryptophan-like peak A, tyrosine-like peak B, and humic acid-like peak C in the aqueous phase during freezing. Additionally, the concentrations of TN and TP increased to 1.47 and 1.13 times the original water sample levels, indicating the migration of tryptophan-like, tyrosine-like and humic acid-like dissolved organic compounds, TN and TP from the ice phase to the aqueous phase due to the freeze concentration effect. As the volume of ice expanded, these substances migrated into the sediment and were released from the sediment into the water during the dissolution process. Correlation analysis results further showed that aromatic substances were more likely to migrate into the aqueous phase during freezing.

Abstract:A recyclable composite catalyst, Cu-FeO_x@AC, comprising Cu-Fe bimetallic oxides loaded on granular activated carbon, was developed for exploring novel algal treatment technology in eutrophic water. The catalyst was prepared using hydrothermal and high-temperature calcination methods and characterized via XRD, SEM, FTIR and XPS. Investigations into the effects of Cu-FeO_x loading ratio on AC, PMS quantity, initial pH, and different reaction systems were conducted to optimize algae removal. The study also explored the algae removal efficiency of the Cu-FeO_x@AC activated PMS system. Free radical shielding experiments and XPS analysis were carried out to explore the reaction mechanism of the Cu-FeO_x@AC activated PMS system. Results showed that at an initial pH of 6, initial algae concentration of 1.4×10⁹ per liter, catalyst dosage of 0.2 g/L, and PMS dosage of 0.5 g/L, the algae degradation rate reached 97.25% within 90 min. In this system, algal cells were adsorbed onto Cu-FeO_x@AC, facilitating valence conversion between Fe and Cu. The synergistic action of AC and the composite catalyst produced holes, ·O2-, ·OH, SO4-· and singlet oxygen, effectively removing algal cells.

Abstract:The treatment of leachate from most incineration plants in China often involves the use of “membrane bioreactor (MBR) + reverse osmosis” technology. However, this process faces challenges due to the high concentration of fulvic acid in the reverse osmosis system influent, resulting in membrane fouling. In this study, a persulfate synergistic electrochemical system(EC+PS system) was used to reduce the fulvic acid concentration. The study focused on identifying the main active substances responsible for removing fulvic acid in the system. The effect of initial pH value, persulfate dosage(PS), current density, plate space, NaCl concentration on the degradation of fulvic acid was investigated. The results showed that fulvic acid removal mainly relied on Cl- provided by HClO,·OH and SO4-· in succession. The fulvic acid removal rate decreased slightly with increasing initial pH and plate spacing, exhibited an initial increase followed by a decrease with rising initial PS concentration, showed an initial increase followed by stability with increasing current density, and slightly decreased with the increase of Cl- concentration. Both current density and persulfate dosage were identified as the main influencing factors for fulvic acid removal. In practical applications, the leachate effluent from the MBR of an actual incinerator was treated using the EC+PS system under a current density 30 mA/cm², potassium persulfate 9 g/L and reaction time 6 h. Three-dimensional fluorescence spectrum analysis showed that the removal rate of fulvic acid in both visible and ultraviolet regions reached 98.65% and 97.80%, respectively, indicating the effectiveness of the EC+PS system in removing fulvic acid from real wastewater samples.

Abstract:Helmet wearing detection is susceptible to interference from complex background. To address this challenge, the YOLOv4 algorithm is employed. However, YOLOv4 faces issues such as slow detection speed, high memory consumption, computational complexity and demanding hardware performance requirements. This study integrates the MobileNet network to alleviate these challenges in YOLOv4. Additionally, cross-module feature fusion is introduced in MobileNet network, enabling effective fusion of high-level semantic features and low-level semantic features. Despite these advancements, small targets in images poses problems such as low resolution, limited informative features, coexistence of multiple scales, and potenial loss of feature information during continuous convolution. To mitigate these issues, this paper introduces neck optimization strategies, such as improving the feature pyramid FPN and introducing/ improving attention mechanism. These strategies focus on target information and reduce interference from background information during helmet detection. Simulation results show that the improved YOLOv4 neck-optimized network achieves a detection speed of 34.28FPS on the CPU platform, which is about 16 times faster than YOLOv4 network. Moreover, its detection accuracy is 4.21% higher than that of the YOLOv4 algorithm. This optimized algorithm strikes a balance between speed and accuracy.

Abstract:Given the significant interference and the variable model parameters encountered in pH value control in the sewage treatment reaction process, this study capitalizes on the independence between the set value response and the interference response of the internal model control to proposed a pH optimization control strategy, integrating internal model control and a neural network inverse model. By incorporating a low-pass filter into the system and using the RBF neural network for online identification of the inverse model of the controlled object, the robustness and anti-interference capability of pH value control in the sewage treatment are improved. This approach effectively addresses the challenge of varying model parameters in the neutralization reaction pH value control process. MATLAB simulation results show that compared with conventional PID control and neural internal model control strategies without a filter, the proposed optimal control strategy reduces overshoot by up to 17.4% and shortens the adjustment time by up to 113.6 s. These improvements effectively improve the system’s robustness and anti-interference capabilities. Engineering applications validate the effectiveness of the proposed strategy, ensuring pH value control deviation within ±0.2. Consequently, the control accuracy and system stability are significantly improved.

Abstract:Due to the inherent complexity and irregularity of cold load time series data, problems such as gradient disappearance, modal aliasing and over-fitting are prone to occur during the prediction process. Predicting the cold load of large public buildings remains a challenging task. To solve this problem and improve the prediction accuracy, the VMD-GRU model is proposed in this study. Real data from large public buildings were utilized to test the proposed model. The prediction process involves the following steps: 1) Correlation analysis of the original data and selection of highly correlated predictors; 2) Decomposition of the original data sequence into independent eigenmode functions using VMD; 3) Prediction of each component using GRU ; 4) Aggregation of component prediction results to obtain the cold load prediction value. To validate the model's effectiveness, a large public building in Xi'an is taken as an example for energy consumption analysis. The results are compared with other prediction models, including BP, GRU, EMD-BP, VMD-BP, EMD-GRU. Experimental results show that the proposed model effectively solves the problems, such as gradient disappearance, modal aliasing and over-fitting, accurately predicting the cold load of large public buildings.

Abstract:Swarm intelligence heuristic algorithms offer several advantages in solving large-scale distributed problems. This paper addresses the shortcomings of the traditional wolf pack algorithm which is prone to fall into local optimal and low precision. The paper proposes an improved wolf pack algorithm incorporating adaptive step size and levy flight search strategy after analyzing the characteristics of the wolf pack. Firstly, optimizing the adaptive step size improves search precision, effectively accelerates the convergence speed. Secondly, the incorporation of the levy flight search strategy of expands the search scope, improving the global search capability of the algorithm. Finally, to verify the algorithm’s performance, simulations and real-world cases were conducted, comparing it with other improved algorithms. The test results show that the improved wolf pack algorithm has obvious advantages in convergence speed, accuracy and stability.

Abstract:With the continuous growth of urban development and outdoor activities, residents are spending more time outdoors. The quality of outdoor environment and thermal comfort significantly impacts the physical and mental health of residents. However, the issue of winter outdoor thermal comfort has received limited attention. Using Chongqing Three Gorges Square in a hot summer and cold winter area as a case study, this research addresses the problem of winter outdoor thermal comfort. By conducting measurements of the winter thermal environment and administering thermal comfort questionnaires, the study utilizes the Rayman software to calculate the PET (physiological equivalent temperature) values as parameters for thermal comfort evaluation. A functional relationship between TCV (thermal comfort voting value), TSV (thermal sensation voting value) and PET is established. This relationship helps define the winter thermal comfort range for various outdoor environmental spaces. Additionally, a comprehensive winter comfort evaluation model suitable for hot summer and cold winter areas is proposed. The findings of this research serves as essential reference data for advancing the study of outdoor thermal comfort in regions characterized by hot summers and cold winters.

Abstract:To investigate the heat transfer characteristics of a ground heat exchanger(GHE) with shape-stabilized phase change material(SSPCM) backfill, a 30 W cylindrical heating rod was used as a linear heat source in place of the GHE. Expanded graphite adsorbed paraffin was used to create SSPCM, which was then mixed with ordinary backfill sand at a mass ratio of 3:7 to prepare a mixed backfill material. The heat transfer characteristics of the SSPCM mixed backfill material were studied under intermittent operation during summer. The research results indicate that the temperature field formed by the SSPCM mixed backfill material had obvious advantages, with smaller temperature fluctuations. In short-term operation modes, the excess temperature difference near the pipe wall could reach about 10 ℃ when compared with ordinary sand backfill. The effect of alleviating temperature fluctuations became more prominent as the distance from the heating center decreased. There were no significant differences in stable temperature and recovery time after recovery under the two backfill conditions. During intermittent and multi-cycle operation, the temperature in the backfill area was lower than in continuous operation. If the temperature rise caused by running time exceeded the latent heat utilization stage of phase change materials, SSPCM could not fully utilize the advantages of phase change energy storage. These experimental results hold valuable insights for the practical application of SSPCM.

Abstract:Addressing the issue of poor pavement performance in reclaimed asphalt mixture caused by the deterioration of aged asphalt properties, this study explores the use of triethoxy silane to convert strong polar carbonyl and sulfoxide groups in aged asphalt into hydroxyl groups. Simultaneously, low polarity ester or ether are generated. Subsequently, the hydroxyl groups are esterified with the end group deactivator isocyanate to achieve end group deactivation. The chemical repair mechanism was explored through analyzing the microcosmic chemical structure and polarity changes of aged asphalt at each repair stage. By comparing the results to matrix asphalt, the chemical repair effects of hydrogenation reduction and end-group deactivation on aged asphalt were evaluated by the analysis and testing of dynamic viscosity and low temperature properties of aged asphalt before and after repair. The results show that the chemical structure of aged asphalt is changed by hydrogenation and passivation. The carbonyl and sulfoxide groups in aged asphalt are reduced to hydroxyl groups by triethoxylsilane, which are then esterified to ester by isocyanate. After hydrogenation and passivation, the polarity of aged asphalt significantly weakens, leading to a substantial reduction in intermolecular forces and viscosity. Consequently, the low temperature deformation capacity is significantly improved. Furthermore, a strong correlation between low-temperature properties and the functional group index of aged asphalt was observd.

Abstract:At present, there are few studies focusing on the preparation process of biomass oil warm mix asphalt. A rational preparation process is crucial to ensuring the performance of biomass oil warm mix asphalt. In this study, warm mix asphalt is prepared using biomass oil along with 70 #, 90 # base asphalt. The optimal preparation process of biomass oil warm mix asphalt is determined using the entropy weight Topsis method. The high and low-temperature performance of the biomass oil warm mix asphalt is evaluated by dynamic shear rheological test and bending beam rheological test. The warm mixing mechanism of biomass oil warm-mixed asphalt is studied using infrared spectroscopy and asphalt four-component test. The results show that the optimum preparation process for biomass oil warm-mixed 90 # and 70 # base asphalt involves a shear temperature of 130 °C, shear rate of 1500 r / min, shear time of 10 min and development time of 15 min. The addition of biomass oil reduces the high temperature performance of asphalt, but improves its low temperature performance. The mixing process of biomass oil and asphalt mainly involves physical blending, improving the dispersion of asphalt micelles. This results in the migration of asphalt components, ultimately enhancing the asphalt performance.