Abstract: Increasing concerns surrounding the rising global energy demand has forced humans to look for alternative energy sources such as the development and utilization of natural gas and nuclear energy, or to increase the efficiency of energy use, thereby optimizing the use of energy. Improving energy efficiency is an effective method that can quickly and efficiently reduce the energy demand and supply gap. Furthermore, developing new technologies for energy storage and energy saving is an effective way to solve the energy crisis, which is of great significance for the sustainable development of energy. Latent heat storage has become a popular research topic owing to its large energy storage density and small temperature changes during energy storage and its excellent thermal stability and high safety. Currently, phase-change materials have been widely used in solar heating systems, air conditioning systems, thermally regulated textiles, energy-efficient building construction, temperature-controlled greenhouses and other fields. The development of phase-change energy storage technology is significant for promoting the development of alternative energy sources and improving energy efficiency. However, phase change materials are prone to liquid leakage during the solid-liquid phase transition, which limits their application. To solve this problem, researchers have started introducing porous support materials to phase-change materials. Porous support materials have attracted extensive research attention in recent years owing to their outstanding properties such as high specific surface area, large pore volume, and low density. Porous support materials can absorb phase-change materials in their pores through the physical adsorption phenomena such as capillary action and interfacial tension, and thereby gradually develop into important substrates for phase-change material encapsulation. Inorganic materials are used as carriers for phase change energy storage materials. Compared with organic carrier materials, inorganic carrier materials have higher mechanical strength, flame retardancy and thermal conductivity, which can reduce the production cost of phase-change energy storage materials, and have a high research value. Mesoporous silica materials have good physical and chemical stability, biocompatibility, flame retardancy, low toxicity, corrosion resistance, controllable size, adjustable surface morphology and high specific surface area. They can comprehensively improve the performance of various aspects of phase change composites and broaden the application space of phase change energy storage materials. In this review, the effects of pore size, pore structure, and pore surface properties on the crystallization behavior of phase change materials in mesoporous silica carriers developed in recent years were comprehensively analyzed, and prospects of research methods for heat storage efficiency were explored.
Abstract: The H13 steel is widely used in hot rolling, hot extrusion, and hot forging because of its remarkable fatigue resistance performance, hot strength, and impact toughness. To further extend the service life of the steel, the production of high-purity die steel is vital. Carbide-forming elements with a mass fraction of about 8%, including Cr, Mo, and V, are contained in H13 steel to prevent the coarsening of austenite or strengthen the steel through secondary hardening. However, owing to the presence of these elements, primary carbides are easily to be found in H13 steel because of the segregation of carbide-forming elements during solidification. The presence of large primary carbides is one of the main causes of the fatigue crack of H13 steel. Therefore, it is of great significance to systematically study the behavior of primary carbides in H13 steel. The excellent material properties of H13 steel were firstly affirmed in combination with the composition characteristics, and then the relationship between the primary carbides and the service life of H13 steel were summarized. The service life of H13 steel reduces with an increase in the primary carbide size. The hazard of primary carbide on the H13 surface steel is much greater than that inside the steel. The characteristics of primary carbides in H13 steel were further systematically discussed, including two-dimensional (2D) and three-dimensional (3D) morphologies, thermal stability and precipitation mechanism. A great difference exits between the 2D and 3D characteristics of primary carbides. In the 2D analyses, the density of the primary carbides appears high, while their size is small. The actual characteristics of primary carbides can be obtained only by 3D observation. Four primary carbide control methods in H13 steel are compared, including composition optimization, cooling rate control, Mg treatment and rare earth treatment. Composition optimization and cooling rate control have been successfully applied in the actual production process. Rare earth treatment may be an effective control method with Chinese characteristics. The relevant discussion and research work in this article can play a certain enlightening role in the rational control of the primary carbides in H13 steel.
Abstract: The Google knowledge graph is a knowledge base used by Google and its services to enhance the search engine's results with information gathered from a variety of sources. Since its inception by Google to improve users' quality of experience of the search engine, the knowledge graph has become a term that is recently ubiquitously used in medical, education, finance, e-commerce and other industries to promote artificial intelligence (AI), which evolves from perceptual intelligence to cognitive intelligence. As a branch of knowledge engineering, a knowledge graph is based on the semantic network of knowledge engineering, and it combines the latest advancements achieved in machine learning, natural language processing, knowledge representation, and inference. Both academia and industries are showing keen interest in AI, and several studies are in progress under promotion of big data. With its powerful semantic processing and open interconnection capabilities, the knowledge graph can break the data isolation in different scenarios, and can generate application value in intelligent information services such as intelligent search and recommendation, intelligent question answering, and content distribution networks, thereby making information services more intelligent. The state of the art of knowledge graph technologies is outlined by introducing a process of building a knowledge graph. A knowledge graph is a structured representation of facts, consisting of entities, relations and semantic descriptions. A comprehensive summary of the overall lifecycle technologies of the knowledge graph is provided, including knowledge extraction, knowledge fusion, knowledge reasoning, and knowledge application. But the focus is on knowledge fusion and knowledge reasoning. Entities, relations, attributes, and other knowledge elements can be extracted from existing structured, semi-structured, unstructured data sources, and websites given in encyclopedia using knowledge extraction. With knowledge fusion, the ambiguity between referential items such as entities, relations, and attributes can be eliminated, and a series of basic facts can be obtained. The final knowledge base is formed through ontology extraction, knowledge reasoning and quality evaluation. Following the three steps of knowledge extraction, knowledge fusion, and knowledge reasoning, it can iteratively update the knowledge graph and realize full process automation knowledge acquisition, such as realizing the automatic extraction, automatic association and fusion, automatic processing of fragmented Internet knowledge, and realizing automatic linking of entries and auxiliary functions of entry editing. Finally, the future directions and possible challenges of the knowledge graph are discussed.
Abstract: A blockchain is a cryptographic distributed database and network transaction accounting system. In the current era of major technological changes, blockchain technology, with its cryptographic structure, peer-to-peer (P2P) network, consensus mechanism, smart contract and other mechanisms, is decentralized, tamper-proof, and traceable and has become a hot spot in the development of informatization. Classified protection is one of the basic policies of information security in China. The implementation of the information security level protection system can not only guide various industries in performing security management in accordance with the equivalent security standards, but also ensure that supervision and evaluation institutions follow the laws and regulations, which is of significance to network security. As the application of blockchain technology in various industries is becoming more extensive, it is necessary to simultaneously promote the national classified protection of blockchain security assessment, which contributes to the sustainable and healthy development of blockchains in China. According to the revised assessment methods of grade protection, in addition to the status of universality requirements, evaluation specifications should be formulated for specific technologies and fields (such as cloud computing, mobile Internet, Internet of Things, industrial control, and big data). In view of the particularity of blockchain technology, China has initiated the formulation of blockchain evaluation specifications, but has not applied the level protection standards to the formulation of blockchain evaluation specifications. Therefore, the assessment requirements and enforcement proposals are specified for the blockchain’s core technologies, such as P2P network, distributed ledger, consensus mechanism, and smart contracts, according to the application and data security layer requirements at Level 3. Moreover, the current running data of blockchains and their security audit mechanism based on the log workflow were summarized and analyzed respectively in compliance with the control points specified in classified protection 2.0. Our investigation indicates that blockchains can satisfy the requirements of evaluation items in three aspects, namely, software fault tolerance, resource control, and backup and recovery. However, further improvements are needed for other aspects, including security audit, access control, identification and authentication, and data integrity.
Abstract: In the process of filling a large-scale goaf, due to the limitations in the capacity of the mixing tank, it is difficult to completely filling the goaf all once, but multiple fillings of a goaf can easily produce a layered structure in the cemented tailings backfill. This layered structure has a significant effect on the mechanical properties of the cemented tailings backfill. To analyze the influence of these structural characteristics on the mechanical properties and evolution of cracks in cemented tailings backfill, the layered cemented tailings backfill specimens with height ratios of 0.2, 0.4, 0.6 and 0.8, and cement-tailing ratios of 1∶4, 1∶6, 1∶8 and 1∶10 were made, and then the uniaxial compression test was carried out by using a GAW–2000 servo test system, and finally the crack distribution inside the cemented tailings backfill were analyzed by using 2D particle flow software(PFC-2D). The results show that: (1) the relationship between the uniaxial compressive strength and the height ratio of the layered backfill can be represented by an exponential function, and the relationship between the uniaxial compressive strength and the cement-tailing ratio can be represented by a polynomial function. The relationship between the elastic modulus and the height ratio and the cement-tailing ratio can be represented by a polynomial function. The uniaxial compressive strength and the elastic modulus are found to decrease with increase in the height ratio, and increase with increase in the cement-tailing ratio, with both being more sensitive to the cement-tailing ratio. (2) The evolution curve of cracks in the cemented tailings backfill increases gradually at first, and then rapidly increases to about 80% of the peak strength, whereby the larger is the cement-tailing ratio, the lager is the height ratio. Furthermore, the earlier the fast-rising inflection point occurs, the more easily is the backfill specimen damaged, and the curve begins to decline rapidly after exceeding the peak strength. (3) The layered backfill fails primarily by mainly shear failure, tensile failure and conjugate shear failure, and the failure is mainly concentrated in the middle weak layer. The larger is the height ratio, the denser are the cracks, the bigger is the cement-tailing ratio, and the more easily the cracks evolve to both ends.
Abstract: Paste backfill is similar to surface paste disposition. Paste backfill technology is an innovative method of treating tailings, which is carried out beneath the earth. This process is widely used worldwide in many metal mining industries due to its advantages in safety, environmental protection, and high economic benefit. The rheological properties of paste backfill are essential factors in pipeline design. After analyzing paste backfilling practices for a long time, it is concluded that the slump determined according to concrete standards is not suitable for paste backfill of tailings. To increase the efficiency of the process, a spread parameter was introduced in the cement slurry flow test method to investigate the rheological properties of the paste backfill. Experiments were conducted to analyze the relationship between spread and other factors such as mass fraction (Cw) of paste backfill, cement-tailings ratio, yield stress, and viscosity. Based on the test results of spread and rheological parameters of paste backfill of tailings in five mines, the empirical model representing spread and yield stress of paste backfill of tailings was constructed and compared with the deduced analytical model. The results show that the spread of paste backfill is mainly related to mass fraction, and the effect of cement-tailings ratio on it is small. The spread of paste backfill decreases with the increase in mass fraction, yield stress, and viscosity. The spread of paste backfill of tailings with mass fraction of 68%, 70% and 72% are 20.37, 17.22 and 12.44 cm, respectively. Spread of paste backfill has an exponential relationship with its yield stress. The error between the yield stress calculated using empirical model and the actual test is within 25%, and decreases with the increase in mass fraction of paste backfill, which will be within 10%. The yield stress calculated using analytical model and empirical model are more or less the same when the spread of paste backfill of tailings is between 12 cm and 16 cm. The calculated yield stresses of analytical model are generally higher than actual test values. Compared with the slump, the spread test is simple and easy to operate, which can adequately characterize the rheological properties of paste backfill of tailings and guide in-situ backfilling.
Abstract: The rake torque of deep cone thickener, pipeline resistance, and paste accumulation slope were important technological parameters for the efficient paste backfill process, which are to be solved or optimized for the practical application in mines. The yield stress of paste was considered as an important rheological parameter for solving these technological parameters. In the past, the research of yield stress of the materials for unclassified tailings paste was limited to the concept and analysis of yield stress fluids used. For example, the fluids such as Bingham fluid, H–B fluid, and Casson fluid were commonly used. When the shear stress of the paste was less than yield stress, the slurry paste remained stationary, and the paste started to flow when shear stress was greater than yield stress. So it concluded that the yield stress was an important parameter in the transition from solid state to flow state. It was considered that yield stress of paste with a certain ratio of material had a unique value, which was regarded as inherent physical property of paste. At present, most rheological studies of concentrated suspensions had found that the evolution of particle structure in suspensions resulted in thixotropy, which increased the difficulty of measuring yield stress of suspensions. Considering the unclassified tailings as specific experimental sample, experiments with different mass fractions paste were carried out and yield stresses were measured. The influence of measuring velocity and measuring time on yield stress of paste was analyzed. It is found that the yield stress value is correlated with measuring protocol. By comparing and analyzing peak yield stress, dynamic yield stress, and static yield stress, the variations in yield stress of paste with measuring time and measuring velocity under certain conditions were obtained. It is observed that the peak yield stress and static yield stress are proportional to measuring velocity of paste, and the dynamic yield stress is inversely proportional to measuring time. The coefficients of variation of degree of yield stress with discreet features are evaluated. The dynamic yield stress of 74% mass fraction paste has the largest Cv, which is 27.07%, while the static yield stress of 66% mass fraction paste has the smallest Cv, which is 2.33%. Further, the variation of particle interaction force and particle network structure with measuring velocity and measuring time during paste yielding was analyzed from the mesoscopic level. The mechanism of variation in yield stress of paste was elucidated based upon the analysis and the results and the necessary values of parameters were obtained for the efficient backfill process.
Abstract: Proppant injection during hydraulic fracturing is to prevent the closure of hydraulic fractures. As a result, the distribution of proppant in the fracture impact the productivity to a great extent. In order to study the rule of proppant transportation and distribution in complex fracture network, and the influence of uneven proppant distribution on the exploitation dynamic characteristics, a full-coupled 3D finite element method calculation model for tight oil reservoir considering sand injection during hydraulic fracturing was established, based on several mathematical models proposed by the author in the past. In the model, a mixture model was utilized, which had advantages to deal with two-phase flow containing solid particles in dispersed phase, to simulate the proppant transportation process in fracture networks. Then, a tight oil reservoir model was established to evaluate the effect of the proppant distribution on the reservoir performance. The calculation results show that in the fracture network, proppant particles will accumulate at the fracture intersection, and the proppant concentration is higher than other parts of the fracture network. The height of proppant settlement dune in the secondary fracture is 25%–50% lower than that in the main fracture, and the communication of secondary fractures has enhanced the proppant settlement degree. Moreover, factors like injection velocity, proppant materials and proppant size are proved to have a strong relation to the average conductivity of fracture network, which could impact the fracture design considerably. Furthermore, the uneven distribution of proppant in fracture network has a great influence on the simulation results. When the reservoir permeability reaches 0.05 mD, the calculation results show that the height, without considering the uneven distribution, of proppant settlement is 41.7% higher than the actual value. Therefore, the uneven distribution of proppant cannot be ignored in the simulation of low permeability reservoir. However, when the matrix permeability is 5 mD, the difference between the actual and simulated result will be within 5%. Thus, it is reasonable to neglect the uneven distribution of proppant in estimations.
Abstract: In wet zinc smelting process, iron slag generated by hematite process has high iron content, uniform particle size, and stable thermodynamics, which have evident advantages. However, impurities are present in hematite slag, including jarosite, basic ferric sulfate, adsorptive salts, and small amounts of iron carbonate and iron silicate, that limit its comprehensive recovery and utilization. In view of these impurities in hematite slag, in this study, iron oxide red was prepared using a high-temperature hydrothermal method. The effects of different acidity levels, temperatures, preparation times, and liquid–solid ratios on the contents of iron, zinc, and sulfur were studied, as were the removal rates of zinc and sulfur and dissolution rate of iron. The experimental results show that the iron content in the iron oxide red products increases from 58.66% to 66.83% at following parameters: pH 1, temperature 220 ℃, preparation time 3 h, liquid–solid ratio 6∶1, and rotation speed 400 r·min?1. The iron content of the ferrous minerals increases from 94.05% to 97.79%, sulfur content decreases from 2.96% to 0.82%, and zinc content decreases from 1.03% to 0.18%. As determined by X-ray diffraction, compared with hematite slag, the peak value of the iron oxide signal in the iron oxide red products is higher and that of the miscellaneous peak is lower. Scanning electron microscopy analysis/energy dispersive analysis of X-rays show that the amounts of sulfate and other impurities on the surface of the iron oxide red products are significantly reduced after high-temperature hydrothermal treatment. However, the morphologies and sizes of the hematite slag and red iron oxide product particles do not change. After the experimental treatment, the iron oxide red products are determined to meet the national standard: iron oxide red content grade C, water soluble substance and water-soluble chloride and sulfate content type III, sieve residue type 2, 105 ℃ volatile type V2, source type a standard.
Abstract: LaCrO3 ceramic is a promising function material in areas such as high temperature piezoelectric materials and solid oxide fuel cells (SOFC). However, its practical applications are limited by fatal flaws including their low density and poor conductivity. To address these challenges, spark plasma sintering (SPS) was used to prepare the high-density LaCrO3 ceramic. Additionally, Ru, a multivalent metallic element, was doped in the A site of the LaCrO3 ceramic to investigate the conductivity of the La1?xRuxCrO3 (x=0?0.25). X-ray power diffraction (XRD) results and scanning electron microscope images show that the sintered La1?xRuxCrO3 ceramic has a single perovskite phase and high density. The characteristic peak shifting observed in the XRD pattern indicates that the Ru element has been successfully doped in the A site of the LaCrO3 ceramic. Whereas, the results of the Energy dispersive spectrometer (EDS) prove that there is no obvious change in the Ru content before and after sintering by SPS, which indicates that no actual Ru loss can occur during the SPS process at 1600 °C. Moreover, the conductivity of the sintered La1?xRuxCrO3 increases with increasing Ru content and temperature. The results also indicate that there is good linear relationship between ln(σT) and 1/T, demonstrating that the conductivity of the La1?xRuxCrO3 obeys the Arrhenius law. The activation energy of the doped La1?xRuxCrO3 ceramic is smaller than that of the LaCrO3 ceramic. Lastly, the feasibility of the application of doped La1?xRuxCrO3 ceramics as the inert anode of molten salt electrolysis in CaCl2 melt has been investigated at the temperature of 800 °C. These findings demonstrate that the doped La1?xRuxCrO3 ceramic has an excellent chemical corrosion-resistant property. However, it has poor thermal stability, which inhibits its application as an inert anode. Future studies focusing on the improvement of the heat-shock resistance and elucidating the corrosion resistance mechanism of La1?xRuxCrO3 in CaCl2 melt is recommended.
Abstract: Owing to strict dimension accuracy demands, pre-hardening treatment has been widely used in the mold for production of large plastic parts. However, the large volume of mold leads to the existence of tempered martensite and bainite structure on the cross section by pre-hardened heat treatment, and the uneven structure makes great influences on the cutting performance of the pre-hardening plastic mold steel. For service materials, machinability is affected by strength, work temperature, cutting conditions, plastic deformation, phase. Pioneering researchers tended to focus on the influences of temperature, cutting conditions and little is known about the effect of different microstructures in same materials. In this work, 718 steels with tempered martensite, lower bainite and grain bainite structures were prepared by heat treatment. The microstructures and mechanical properties were characterized by optical microscopy, scanning electron microscopy, X-ray diffractometer and universal tensile testing machine. Meanwhile, the effects of mechanical properties and structure on processing properties were studied by high-speed milling experiments and optical profilometer. The results show that when the cutting speed was lower than 145 m·min?1, the bainite was easier to cut than tempered martensite, and the life of tool cutting for bainite was 30%?40% higher than life of tool cutting for tempered martensite. When the cutting speed was higher than 165 m·min?1, tempered martensite microstructure worked softening and the life of tool cutting for it increased, moreover, its workability advanced. The ridges were observed on the milling surface of grain bainite because of severe tool adhesion and tempered martensite structure has the best milling surface roughness. Under consideration, the comprehensive machinability of the three kinds of microstructure are ranked from high to low: lower bainite structure, martensite structure and granular bainite structure. The adoption of 300 ℃ austempering process can effectively improve the synthesis cutting performance of 718 plastic die steel.
Abstract: The error between the actual damping force and the simulated damping force obtained using the Bouc–Wen model under non-identification excitation conditions is large, and the model is too sensitive to non-identification excitation amplitude and thus features poor accuracy. To solve this sensitivity problem, an improved model describing hysteretic characteristics of shock absorbers was proposed. Firstly, the mechanical properties of a magnetorheological (MR) damper were tested to obtain the damping force under various excitation amplitudes, frequencies and currents using a mechanical testing and simulation(MTS) fatigue testing machine. The smooth hysteresis loop curve was simulated based on the relationship between the slope of the hysteresis loop and the damping force. The quadratic polynomial function was used to characterize the relationship between the slope of hysteresis loop and the damping force according to the hysteresis curve characteristics. At the same time, the revision term of the exponential function for the velocity value was introduced, and the parameters of the established improved Simulink model were identified. The damping forces under different working conditions were obtained from the experiment, and the new model was simulated and validated. The damping forces obtained from new model and the experiment were compared, and the curves obtained from the model agree well with the experimental results under different working conditions. Meanwhile, the improved model was compared with the Bouc–Wen model based on the characteristic curves of the damping force. The results show that the improved model can better simulate the damping force values obtained from tests under different conditions, and is superior to the Bouc–Wen model. At the same time, the problem of poor accuracy of the Bouc–Wen model under non identification excitation conditions was improved. The new model lays the foundation for ensuring the accuracy of the vehicle suspension system response under various working conditions.
Abstract: At present, the diagnosis of prostate cancer mainly relies on the level of prostate-specific antigen (PSA) followed by a prostate biopsy. The technology, transrectal ultrasound (TRUS), has been the most popular method for diagnosing prostate cancer because of its advantages, such as real-time, low cost, easy operation. However, the low imaging quality of ultrasound equipment makes it difficult to distinguish regions of malignant tumors from those of healthy tissues from low-quality images, which results in missing diagnoses or overtreating conditions. In contrast, magnetic resonance (MR) images of the prostate can quickly locate the position of malignant tumors. It is crucial to register the annotated MR images and the corresponding TRUS image to perform a targeted biopsy of the prostate tumor. The registration fusion of prostate magnetic resonance and transrectal ultrasound images helps to improve the accuracy of the prostate lesions targeted biopsy. Traditional registration methods that are usually manually selected, specific anatomical landmarks in segmented areas used as a reference, and performed rigid or nonrigid registration, which is inefficient because of the low quality of prostate TRUS images and the substantial differences in pixel intensity of the prostate between MR and TRUS images. This paper proposed a novel prostate MR/TRUS image segmentation and the automatic registration method was based on a supervised learning framework. First, the prostate active appearance model was trained to be applied in the prostate TRUS images segmentation task, and the random forest classifier was used for building a boundary-driven mathematical model to realize automatic segmentation of TRUS images. Then, some sets of MR/TRUS images contour landmarks were computed by matching the corresponding shape descriptors used for registration. The method was validated by comparing the automatic contour segmentation results with standard results, and the registration results with a traditional registration method. Results showed that our method could accurately realize the automatic segmentation and registration of prostate TRUS and MR images. The DSC (Dice similarity coefficient, DSC) accuracy of nine sets of registration results is higher than 0.98, whereas the average location accuracy of the urethral opening is 1.64 mm, which displays a better registration performance.
Abstract: Unexpected failures and unscheduled maintenance activities of mechanical systems might incur considerable waste of resources and high investment costs. Thus, in recent years, prognostics and health management (PHM) has received a lot of attention because of its importance in maintenance cost reduction and machine fault prognostics. The remaining useful life (RUL) of machinery is defined as the length from the current time to the end of its useful life, which is the core technology of PHM. During the operation of machines and equipment, a large amount of data generated by different sensors in the system is collected using various methods. These data often characterize the health status of machinery to a certain extent. By applying the systematic approach to these data, valuable information for strategic decision-making can be obtained. However, traditional machine learning algorithms are usually not efficient enough to handle the complex and nonlinear characteristics of the system and deal with big data. With the rapid development of modern computational hardware and theory, deep learning algorithms show unique advantages in characterizing the system complexity and processing big data. Because of the low-accuracy prediction of the RUL of machines or equipment, a neural network integrating the one-dimensional convolutional neural network (1D CNN) and the bidirectional long short-term memory (BD-LSTM) was proposed. To extract the features of the time series and generate more training samples, the sliding window algorithm was used to process the data and the Kalman filter was applied to denoise the data. Then, the dataset was standardized and the RUL labels were set. Instead of artificial feature extraction, this study used 1D CNN to extract features from the data and discarded the pooling layer of CNN. The extracted high-dimensional features were inputted into the BD-LSTM for regression prediction, and the neural network was integrated by bagging to predict the RUL. Finally, the effectiveness and superiority of the model compared with the machine or deep learning model were verified using the National Aeronautics and Space Administration dataset. Results showed that the proposed model can more accurately predict the RUL than the machine or deep learning model.
Abstract: The removal process of waste water sludge formed in tomato sauce processing plants was analyzed and explored. The operation mode of sequencing batch reactors (SBR) was used to explore the changes in particle sizes and the removal capacity of COD, N and P in the process of granulation; the sludge characteristics, water quality, organic pollutant degradation capacity and the optimal proportion of sludge in the mixed sludge system were analyzed when the particle sludge and flocculent sludge coexisted in different proportions. The majority of particle sizes of granular sludge are in the range of 0.45?3 mm, and the removal rates of COD, ${{\rm{NH}}_{4}^{+}} $—N and ${{\rm{PO}}_{4}^{3-}} $—P are over 98%, 90% and 90% respectively. When the quality ratio of granular sludge accounts for 50% of the total sludge, the removal rate of COD is the highest, which is more than 98%, the removal rate of ${{\rm{NH}}_{4}^{+}} $—N is 78.72%, and the concentration of ${{\rm{PO}}_{4}^{3-}} $—P in the effluent is about 1.0 mg·L?1, the removal rate of can reach 70.68%. The removal of nitrogen and phosphorus is also good. When the quality proportion of granular sludge is more than 75%, the removal rate of COD is higher than 98%, and the removal rate of ${{\rm{NH}}_{4}^{+}} $—N and ${{\rm{PO}}_{4}^{3-}} $—P is higher than 90%. SVI30 value is lower than 35 mL·g?1, SVI5/SVI30 is close to 1, MLVSS/MLSS is 0.90, with high activity, good sludge settling performance, and vigorous growth of microorganisms. Therefore, SBR is expected to discharge aged particles, control the quality proportion of granular sludge ≥75%, and maintain the required proportion of flocculent sludge and granular sludge of 10%–25%. At the same time, the particle size range is controlled at 0.45–3.00 mm. Two way sludge discharge is used to remove particles larger than 3.0 mm together with excess flocculent sludge. The reactor has excellent organic matter removal performance. It can realize the long-term stable operation, effectively remove the granular sludge, and solve the problem of granular sludge disintegration.
Monthly, started in 1955 Supervising institution：Ministry of Education Sponsoring Institution：University of Science and Technology Beijing Editorial office：Editorial Department of Chinese Journal of Engineering Publisher：Science Press Chairperson：Ren-shu Yang Editor-in-Chief：Ai-xiang Wu ISSN 2095-9389CN 2095-9389
