Abstract: With the rapid depletion of shallow mineral resources, an increasing number of mines are stepping into deep mining to ensure resource continuity, which generally forms a coordinated production model that includes both existing shallow production systems and new deep projects. Given the complex production patterns of both multi-mining areas and multi-sections formed during the process of deep mining, how to achieve geological resource continuity, stable production capacity, balanced supply grade, and sustainable economic benefits are the key issue to be addressed in the mining scheme during the transition to deep-area. When an underground mine transitions to deep mining, it is necessary to steadily advance the production task and maintain the steady growth of metal quantity and economic benefit. Therefore, to maintain production continuity and stability, it is necessary to optimize the production plan for underground metal mines. Considering the situation of multi-section mining submontanely, the Sanshandao gold mine is used as a case study to investigate the complex production layout of multi-section mining simultaneously subjected to constraints of production capacity balance, grade requirements, and other production system capacities through in-depth analysis of the production capacity continuity in the process of mining transition to deep mineral resources. An optimization model is constructed aiming at maximizing the comprehensive resource exploitation value of multi-section mining. A mathematical planning model for the continuation and optimal allocation of production capacity during the transition period of deep mining is constructed with the optimization goal of maximizing the comprehensive exploitation return of resources from multiple mining areas, taking the constraints of overall capacity succession, balanced output grade, and capacity limits of each mining area into account. Following the solution of the Sanshandao gold mine’s production capacity, succession during the transition to deep-area is obtained. The model considers the coordination and succession of multiple mining areas and sections in terms of time and space, and it achieves a smooth production system transition from shallow to deep areas through accurate evaluation of existing operation conditions and optimal allocation of production factors, all while ensuring the production tasks and economic efficiency targets are met. The optimization model is programmed in Python, and it is solved using the Gurobi software. The results show that the best capacity continuation and production task allocation schemes are obtained to effectively ensure benefit improvement as well as production capacity balance and stability. The example application validates the scientific and efficacy of the optimization model, which can be used by other mines to optimize production plans when switching to deep mining.
Abstract: With the gradual development of mines, tunnels, and other underground constructions, theoretical research on the influence of internal defects in rock structure on rock dynamic fracture behavior and related engineering practices are of great importance. In this paper, a digital laser dynamic caustics experimental system is used to conduct three-point bending drop hammer impact tests on three groups of polymethyl methacrylate specimens with different angles of bedding (30°, 45°, and 60°). The fracture process of the specimens and the shape change process of the dynamic caustic speckle at the crack tip were recorded using a high-speed camera. The characteristics of dynamic stress intensity factors Ⅰ and Ⅱ were obtained, and the crack tip displacement and velocity curves were analyzed. Combined with the discrete lattice spring model (DLSM), the fracture morphology of the specimens was analyzed, and the variation law of the stress field and field at the crack tip was obtained. The transmission and reflection characteristics of stress waves were studied at stratification. Finally, the impact of the fracture characteristic stratification parameters of the medium was analyzed using DLSM. The results show that the fracture characteristics of the specimens, the initiation time of the crack, and the propagation speed of the crack in the bedding plane vary with the bedding angle. With increasing bedding angle, the initiation time of the crack advances, the propagation speed of the crack increases along the weak bedding plane after extending to the bedding plane, and the crack is more inclined to extend along the weak bedding plane to complete specimen fracture. With the crack expansion, the type Ⅱ stress intensity factor appears, and the specimen fracture shows the characteristics of tension–shear composite failure. Before arriving at a particular bedding speed, cracks fluctuate up and down, and attenuation in the aftermath of the bedding generally has lower volatility change; the elastic modulus and bedding thickness affect the dynamic fracture characteristics of the specimens. If the bedding elastic modulus is less than 0.1 GPa, the crack extension in the bedding plane distance increases with the elastic modulus. If it is more than 0.1 GPa, when the bedding for the organic glass bonding effect increases, the crack goes directly through the bedding. The propagation distance of cracks along the weak plane of the bedding increases with the bedding thickness.
Abstract: In this study, a numerical simulation is used to study the effect of initiation methods on the damage distribution on both sides of an air-spaced charge blasthole using lead azide as the explosive and polymethyl methacrylate as the experimental material. The digital image correlation system determines the evolution of the global strain field and the strain attenuation pattern of the air section, and the dynamic caustics experimental system investigates the effect of detonation methods on the dynamic fracture behavior of the precrack. The experimental results show that the damage induced on both sides of the cylindrical charge blasthole has significant fractal properties. The damage degree corresponding to each initiation point of the charge section is the smallest, and the damage degree gradually increases along the detonation path. When it approaches the noninitiating end, the damage degree reduces further due to a decrease in the energy accumulation rate and a portion of the energy dissipation. When the outer detonation method is employed, both sides of the central air section are damaged, but not when the other detonation methods are used. The effect of different initiation methods on the radial compressive strain of the air segment strain field is mostly reflected in the strain size and strain decay rate, whereas the effect on the axial tensile strain is primarily reflected dynamically and in the decay rate. The attenuation coefficient of the strain field is the greatest when the outer detonation is initiated, regardless of whether the strain is radial or axial. The fracture behavior of the precrack end varies considerably depending on the detonation method. When both the inner and outer detonations are used, the crack exhibits a typical I type generated by tensile failure. When antarafacial detonation is used, the crack initiation is mixed I–II, and the specific performance is tensile-shear destruction. The origin of the crack initiation at the end of the precrack is described using LS-DYNA numerical simulation software, and the distribution pattern of the stress field at the blasthole wall is derived. The pressure distribution along the axial hole wall of the blasthole is considerably affected by different detonation methods. The charge section is mainly reflected in the position of the pressure peak and the pressure distribution shape, whereas the air section is primarily reflected in the size of the pressure peak and the pressure distribution shape.
Abstract: The force chain network is a crucial basis for characterizing the essential features of granular media microscopic mechanics and for studying the mechanical behavior of their macroscopic structures. Due to the complexity and multiformity of the force chain configuration, the topological data analysis (TDA) method provides a simple, effective, and manageable method to quantitatively describe the force network. Based on the theory of persistent homology in TDA, the analysis method of granules from contact network to force network to topological model is established. The two key factors affecting the structure of a force chain network are its connectivity and closure. β0 reflects the number of particle clusters whose normal force is greater than the provided threshold. β1 reflects the number of holes in the force chain cluster. Persistent homology, a mathematical method to calculate the topological features of structures in metric spaces with different resolutions, is applied to the structural analysis of force chain networks. Different from other methods that separately consider force threshold levels, the evolution of a force chain structure at the force threshold level is helpful in understanding the persistence characteristics of geometric structures at various force levels and describing the force chain network completely and deeply. For example, the top coal and overburden force chain evolution in top-coal caving mining is investigated through photoelastic experiments, and the TDA of the top-coal caving force network chain is performed. The research shows that when the particle stress is obtained as the threshold ε of persistent homology analysis in top-coal caving mining, the Betti number in persistent homology analysis can be used to evaluate periodic weighting. In the overlying strata and front of the working face, the curves of β0 are parabolic, of which the peak values under the periodic weighting are higher than that under the initial condition. Furthermore, the difference between them is that the peak values in the overlying strata are located in the range of strong force chains, whereas those in front of the working face are located in the range of sub-strong force chains. The curves of β1 show L-shaped, suggesting that within [0.3, 1], β1 approaches 0; within [0, 0.2], β1 is approximately inversely proportional to ε; and within [0.3, 1], β1 trends to 0. Topological studies of persistent homology provide an effective method for quantitative analysis of the complicated force chain network evolution and macroscopic mechanical behavior in granular media.
Abstract: Stainless steels are widely used for corrosion resistance and as construction materials. The existence of harmful inclusions probably deteriorates corrosion resistance and easily causes nozzle clogging, surface defects, and the occurrence of cracks. Reoxidation during the casting start process significantly affects the cleanliness of molten steel, which may result in the downgrading or discarding of the steel. The production route of Al-killed stainless steel in this work is “EAF → AOD → LF → Calcium treatment → Continuous casting of round billet.” At LF departure, steel samples were taken at different moments during the casting start process to investigate the effect of reoxidation on the cleanliness of molten steel and the evolution of inclusions in the steel. It aims to achieve effective control of inclusions in the steel. The morphology, composition, amount, and size of inclusions in Al-killed stainless steel were studied using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS), as well as automated SEM/EDS inclusion analysis (ASPEX). The effects of the oxygen content from reoxidation and the temperature decrease during solidification on the inclusion composition were calculated by the thermodynamic software FactSage 7.2. The evolution behavior and mechanism of inclusions during the casting start process of Al-killed stainless steel were analyzed and discussed. The findings showed that the total oxygen and nitrogen contents, as well as the number density of inclusions in the steel during the casting start process, indicated a similar change trend. They were increased to 7.4×10?5, 0.0674%, and 17.1 mm?2, respectively, at casting 20 min, and then gradually decreased. Inclusions in the steel have been well modified by calcium treatment at LF departure, and its composition was primarily CaO?Al2O3?SiO2?MgO. The effects of calcium treatment were mitigated by reoxidation during the casting start process. Inclusions in the round billet were transformed to MnO?Al2O3?SiO2?CaO at casting 20 min. When the pouring time was 60 min, the cleanliness of the molten steel almost reached a steady state during continuous casting. The contents of total oxygen and nitrogen with the number density of inclusions in the steel were 3.2×10?5, 0.0628%, and 7.1 mm?2, respectively, and inclusions were transformed back to CaO?Al2O3?SiO2?MgO. Furthermore, reoxidation increases the oxygen content in molten steel and promotes the formation of MnO?Al2O3?SiO2?CaO inclusions. Collision and coalescence among inclusions produce large-sized CaO?Al2O3?SiO2?MnO?(MgO) inclusions in the steel. The decrease of the temperature during solidification promotes the precipitation of the MgO?Al2O3 spinel phase and CaO?2MgO?8Al2O3 phase. As a result, the Al2O3 content in inclusions increases.
Abstract: The phase transformation of carbon steel has always been a research hotspot. Researchers study the phase transformation process of steel in terms of the original structure, chemical composition, and process conditions, and the cooling rate in process conditions has an important influence on the phase transformation of steel. In this study, Thermo-calc thermodynamic software is used to simulate and calculate the phase transformation process of 3.52%Al (mass fraction) delta ferrite transformation-induced plasticity (δ-TRIP) steel, and differential scanning calorimetry (DSC) and the Ohnaka microsegregation model are used to analyze the effect of cooling rate on the peritectic transformation temperature and solute element segregation during solidification of 3.52%Al δ-TRIP steel. The results show that the smaller the cooling rate is, the closer the DSC phase transition temperature is to the thermodynamic equilibrium value calculated by Thermo-calc. Increasing the cooling rate from 10 to 30 to 50 ℃·min?1 decreases the phase transition temperature of L→L+δ and first decreases and then increases those of L+δ→L+δ+γ and L+δ+γ→δ+γ. The former temperature is mainly affected by cooling, and the latter temperatures are mainly affected by element segregation. Among the six elements (C, Si, Mn, P, S, and Al) of 3.52%Al δ-TRIP steel, the segregation of S is the most severe. This result is obtained because the partition coefficient k of the S element at the solid–liquid interface is much smaller than those of other solute elements. The rapid S element enrichment at the end of solidification increases the possibility of sulfide precipitation, forms a low melting point liquid film between dendrites, reduces the zero plastic temperature, and increases the solidification brittleness range and crack sensitivity. Therefore, the sulfur content in steel should be strictly controlled during composition smelting. The cooling rate slightly affects C, Mn, and S segregation but greatly affects Si, P, and Al segregation, and the degree of segregation of Si, P, and Al increases with the cooling rate. The segregation of Si, P, and Al delays the peritectic reaction process, the segregation of Si and P slightly delays the peritectic reaction process, and Al segregation clearly delays the peritectic reaction process. With increasing cooling rate, the lower the peritectic reaction area moves, the slower the peritectic reaction process. This study can provide a theoretical basis for the continuous casting process parameters of δ-TRIP steel.
Abstract: In the current study, Al–Ti–O inclusions after Ti-alloyed in an ultra-low carbon IF steel were analyzed. It was found that Al–Ti–O inclusions were classified into seven types based on their morphologies, including four types with an Al2O3 outer layer and the other three without the Al2O3 outer layer. Approximately 78.0% of Al–Ti–O inclusions had an Al2O3 outer layer. There was little separated TiOx inclusion detected in the steel. Without the consideration of the Al2O3 layer of Al–Ti–O complex inclusions, the core of Al–Ti–O complex inclusions was generally similar to that without the Al2O3 outer layer. Compared with the sample at 1 minute after the Ti addition, the number density of Al–Ti–O inclusions without an Al2O3 outer layer in the sample at 4 minutes after the Ti addition decreased by 0.21 mm?2, while the number density of Al–Ti–O inclusions with an Al2O3 outer layer increased by 0.19 mm?2. After the titanium alloying process, a large number of Al–Ti–O inclusions without the Al2O3 outer layer were transiently generated. Further, the Al2O3 outer layer was formed on the surface of inclusions, leading to the increase of the percentage of Al–Ti–O inclusions with the Al2O3 outer layer to 78.0%. Thermodynamic calculated results show that the evolution route of inclusions was solid Al2O3 → liquid Al–Ti–O → solid Ti2O3 with the increase of titanium content in the steel. The inclusion of Al2O3 was the only stable phase in the liquid steel in equilibrium, while the high concentration of titanium in the local steel during the titanium alloying process led to the formation of titanium-containing oxides. When the oxygen content in the steel was lower than 0.03%, inclusions were mainly solid Al2O3. Inclusions containing TiOx were formed with oxygen content in the local steel exceeding 0.03% during the reoxidation process. The formation mechanism of Al–Ti–O inclusions was divided into two steps. After the titanium alloying process in the refining, when the local titanium content in the steel was higher than 0.42%, the [Ti] reacted with the molten steel to transiently form Al2O3–TiOx and TiOx. With the mixing of the titanium in the molten steel, the generated TiOx-containing oxides were reduced by [Al] in the steel. Inclusions of Al2O3?TiOx and TiOx gradually transformed to Al2O3 on the surface.
Abstract: Modified steel slag powder was used to create a modified steel slag/rubber composite material using self-made steel slag grinding modifier and combining it with carbon black and rubber matrix to treat hot braised steel slag, electric furnace steel slag, and air-quenched steel slag. Next, the thermal conductivity of the three types of modified steel slag/rubber composites was measured using a thermal conductivity instrument at 1, 3, 5, 7, 9, and 11 days. The surface contact angle θ and crosslinking density of the above composites were calculated using Young’s and Flory’s equations before and after thermal oxygen aging, and their changes were analyzed using thermogravimetric analysis (TGA) and scanning electron microscopy (SEM). As a result, the thermal conductivity of the modified electric furnace slag/rubber composite material was the lowest [0.187 W·m?1·K?1]. Among them, the median diameter (d50) of the modified electric furnace slag particles was the smallest (3.49 μm) without thermal oxygen aging, easily forming a compact structure of rubber-wrapped slag, but more challenging to develop thermal conductivity paths that reduced thermal conductivity. In the process of thermal oxygen aging, the structure of rubber-wrapped slag was destroyed. While the modified electric furnace slag/rubber composite material had large pores and the best dispersibility, which reduced interface thermal resistance and easily formed thermal conductivity paths, its thermal conductivity was the highest. After thermal oxygen aging, it was found that long cracks, deep holes, and increased roughness lying on rubber composite material surface increase the water absorption and decrease the contact angle. Besides, due to the largest particle size of the modified hot braised slag, oxygen is more likely to enter the rubber composite material under the heat action to react with the rubber molecular chain (double bond) to generate free radicals, thus raising molecular weight and growing crosslinking density. The modified air-quenched slag had the highest basicity (3.3), was detrimental to the vulcanization process, and was prone to forming an unstable carbon layer, resulting in more secondary combustion and a lower crosslinking density. Moreover, the mass fraction of residual material called carbon residue was only 1.02% at 800 ℃ and it had the worst durability after thermal oxygen aging.
Abstract: Web 3.0 has widely piqued the interest of academia and industry as the next-generation internet. Therefore, this study analyzes the development process and status of Web 3.0 from the perspectives of countries (policies, companies, and products), international organizations (ITU, IEEE, IET, and W3C), and publications databases (Scopus, CNKI). It is concluded that the fundamental technology in Web 3.0 remains the bottleneck limiting its further development. This study performed an in-depth analysis of the fundamental technologies in Web 3.0 from four perspectives. The first is computing and networking. The ubiquitous “Internet of Things” architecture generates a large amount of real-time data, and it has become an inevitable trend to form a cloud, edge, and end multi-level computing collaboration mode. Furthermore, 5G and 6G network and computing technologies work collaboratively to lay a solid foundation for the best user experience. The second is a secure and reliable technology. In Web 3.0, data become users’ data assets. Blockchain technology, privacy-computing technology, and identity management technology are needed to build the technical foundation for value transmission when transferring digital assets and currency. The third technology is virtual-real fusion. Web 3.0 is a three-dimensional holographic, which means that not only will the virtual and real world be integrated, but the virtual world will also break the barriers between each virtual ecology. The technologies related to the fusion of the virtual and real world include virtual and real interaction technology, IoX and technologies related to the fusion of the virtual world include cross-chain technology. The fourth is intelligent interaction technology. The new generation of the internet will not only respond mechanically to the users’ search content but will also be able to read information like humans, providing users with more accurate, reliable, and personalized services. Intelligent interaction technology mainly includes: semantic web technology, big data, data mining technology, and artificial intelligence technology. Finally, it summarizes the future changes caused by Web 3.0 in the economy, society, culture, and Web 3.0 road with Chinese characteristics. Web 3.0 economic reform is mainly reflected in user-centered value creation. The social reform of Web 3.0 is mainly reflected in reshaping organizations, transforming from traditional and centralized to decentralized organizations. The cultural reform of Web 3.0 is mainly reflected in three fields. It protects the rights and interests of artists and artistic works, which greatly promotes the creation of art in Web 3.0; moreover, it promotes the preservation of cultural heritage and the development of tourism. It also establishes Game Finance (GameFi) to promote the improvement of language, writing, music, aesthetics, and other aspects of games. At present, we need Web 3.0 to impart new momentum to the economic, technological, cultural, and social changes, whether it is based on the demand for upgrading information technology or the need to get rid of the persistent downturn in the global economy caused by the epidemic.
Abstract: The development of unmanned vehicles has been extremely rapid in recent years. Unmanned vehicles require path tracking control. Based on mature mathematical modeling methods for unmanned vehicles, path tracking control research using model-based control methods, such as feedback linearization control, optimal control, and model predictive control, is very common. Currently, two types of model-based control methods are commonly used in the path tracking control of unmanned vehicles: based on global and local models. The path tracking control based on the global model has a coupling relationship between the longitudinal speed of the unmanned vehicle and the lateral displacement error and longitudinal displacement error in the global coordinate system. Furthermore, this coupling relationship varies with the heading angle, making the controller unable to take the longitudinal speed as a control input to improve the accuracy of path tracking control. Path tracking controllers based on local models usually use errors as reference models, making the controller less accurate when the curvature of the reference path greatly varies. To address the above issue, an unmanned vehicle path tracking control method based on a time-varying local model is proposed considering the principle of rolling optimization of nonlinear model predictive control. Specifically, a time-varying local coordinate system is first established based on the time-varying pose of the vehicle. Then, a reference path in front of the vehicle is entered into this local coordinate system. The model-based iterative prediction is completed in this local coordinate system, and finally, the control is achieved using the optimization solution. The proposed control method is verified by co-simulation using MATLAB and CarSim. The simulation conditions include low-speed and high-adhesion road conditions, low-speed and low-adhesion road conditions, and high-speed low-adhesion road conditions. The simulation results show that the path tracking controller based on the time-varying local model outperforms the path tracking controller based on the global model, the path tracking controller based on the local model, and the Stanley path tracking controller. The maximum absolute value of the displacement error of the proposed controller does not exceed 0.3342 m under all simulation conditions, and the maximum absolute value of the heading error does not exceed 0.0913 rad. Moreover, the proposed controller can still complete the path tracking in situations where other controllers fail, such as high-speed and low-adhesion road conditions.
Abstract: Sleep takes approximately 1/3 of a person’s lifetime; therefore, its quality profoundly affects learning, physical recovery, and metabolism. Clinically relevant human physiological data are collected using polysomnography, which is analyzed by sleep technologists to determine sleep stages. However, the manual method is prone to having a cumbersome workload due to a large amount of data analysis and different data formats. Simultaneously, manually analyzed results are influenced by doctors’ medical clinical experience, which may cause inconsistent diagnoses. Recently, with the development of artificial intelligence, computer science, other technologies, and their interdisciplinarity, a series of typical achievements have been accomplished in intelligent diagnosis, laying the foundation for medical artificial intelligence in the sleep medicine field. In sleep research, realizing automatic sleep signal analysis and recognition assists doctors in diagnosis and reduces their workload, thus having important clinical significance and application value. Although deep neural networks are becoming popular for automatic sleep stage classification with supervised learning, large-scale, labeled datasets remain difficult to acquire. Learning from raw polysomnography signals and derived time-frequency image representations has been an interesting solution. However, extracting features from only a single dimension leads to inadequate feature extraction and, thus, limited accuracy. Hence, this paper aims to learn multi-view representations for physiological signals with semi-supervised learning. Specifically, we make the following contributions: (1) We propose a multi-view, hybrid neural network model containing a multichannel view time-frequency domain feature extraction mechanism, an attention mechanism, and a feature fusion module. Among these aspects, the multichannel view time-frequency domain mechanism extracts time domain and frequency domain signal features to achieve multi-view feature extraction. The attention mechanism module enhances salience features and achieves interclass feature extraction in the frequency domain. The feature fusion module fuses and classifies the above features. (2) A semi-supervised learning strategy is used to learn unlabeled electroencephalogram (EEG) data, which solves the problem of sleep data underutilization due to insufficient labeling of EEG signals in clinical practice. (3) Extensive experiments conducted on sleep stage classification demonstrate state-of-the-art performance compared with supervised learning and a semi-supervised baseline. Experimental results on three public databases (Sleep?EDF, DOD?H, and DOD?O) and one private database show that our semi-supervised method achieves accuracies of 81.6%, 81.5%, 79.2%, and 75.4%. The results show that our proposed model is comparable to a fully supervised sleep staging model while substantially reducing the technician’s workload in data labeling.
Abstract: The development of an electromagnetic spectrum monitoring (ESM) system based on a low-earth orbit (LEO) constellation has shown to be an effective method of achieving global ESM and is now a research hotspot in several fields. In the classic LEO-based ESM system, the “on-satellite acquisition and processing” architecture is used in which the satellite gathers and analyzes electromagnetic signal data before transmitting the processed results back to the data center on the ground. Although this framework can reduce the transmission pressure on the satellite-ground link, it yields a limited system performance of the single satellite payload. This paper proposes an intelligent processing framework for the LEO-based ESM system with separate acquisition and processing. In this framework, the satellites serve as forwarding nodes for electromagnetic signal data. The satellites are only responsible for acquiring electromagnetic signal data, which is then processed by a data center on the ground. Unlike the traditional framework, this framework delivers massive amounts of raw electromagnetic data to the ground. To address the problem that the massive data in this framework are difficult to process using traditional technical methods, deep learning is organically integrated with the key technologies of the traditional framework. Deep learning provides a new option for realizing global space–time continuous ESM. The three key technologies involved in the proposed framework are spectrum sensing, blind source separation, and passive positioning based on deep learning, and their research progress in recent years has been sorted out. Compared with ground-based systems, constellation-based systems have the following characteristics: (1) the satellites are far away from the radiation source; (2) the satellites are fast; (3) the satellites show long-distance distribution among them; (4) the topology of the constellation is always in high-speed dynamic change. These characteristics cause a significant divergence between their essential technologies and the research of ground-based systems for these technologies. However, the present efforts relating to essential technologies are based on research conducted on ground-based platforms. There is an issue of applicability to consider when immediately transitioning them to the constellation-based system. Thus, the suitability of each important technology for the migration of constellation-based systems is thoroughly examined. The future trajectory of each major technological breakthrough is then investigated. Finally, recommendations for further studies are made based on the leading technologies of the intelligent processing framework for LEO-based ESM systems.
Abstract: Being an environmentally friendly technology, Microbially Induced Calcium Carbonate Precipitation (MICP) has become a popular research topic in the field of geotechnical and environmental engineering, among which island microbial technology is a promising direction. This paper systematically summarizes the basic principles of microbial mineralization and the progress made in the use of MICP in construction work done on islands, such as the reinforcement of calcareous sand, protection of island slopes from erosion, and reinforcement of pile foundations, and the numerical modeling performed in island engineering. The following conclusions can be drawn: MICP produces calcium carbonate, which is the same as calcareous sand, and thus MICP can be used to meet the ecological reinforcement requirements of islands. The temperature and soil pH of the islands are suitable for MICP. Urease activity in soil nonlinearly increases as environmental temperature increases in the range from 5 ℃ to 40 ℃, and the soil pH influences pore solution concentrations, which in turn affects the deposition rate, yield, and morphology of calcium carbonate. The optimal pH value required for the mineralization caused by Sporosarcina pasteurii is approximately 9. However, the influence of the special environmental characteristics of islands, such as radiation, waves and currents, on MICP requires further study. Island microbial technology can be used to greatly enhance the strength and stiffness of calcareous sand in islands, the bearing capacity of pile foundations constructed in islands, and the erosion resistance of island slopes against waves and currents. The verification of the applicability of MICP in an island environment and the determination of the efficiency of bacterial urease activity, morphology and deposition rate of calcium carbonate in calcareous sand, physical and mechanical properties and uniformity of cemented calcareous sand layers in that environment require in-situ reinforcement tests. Most of the previous research on MICP is laboratory experiments. The spatiotemporal evolutions of the chemical substances used in various processes of MICP cannot be determined in real-time. The labor and other resources used in field experiments, which are highly dependent on field conditions, are expensive. Therefore, a reliable numerical model is highly important to understand the biochemical processes associated with MICP. However, research on MICP numerical models is still in its infancy, and currently, the MICP models are verified mainly using element and model tests. The development of a numerical model for the multiple processes of MICP suitable for the environmental conditions, such as temperature, soil pH, waves, and currents, of an island and verification of the accuracy of the model based on in situ reinforcement tests is extremely important. The findings can provide a reference for soil reinforcement in an island environment using MICP.
Abstract: The existing theory of multiphase seepage can neither explain the cause of the discontinuous phase near the end of relative permeability nor consider the complex flow of multiphase mixing, interface interaction, and mass transfer between phases. In this paper, all phases in pores were treated as a mixed fluid of one phase to investigate multiphase seepage characteristics. Multiphase fluid transport in porous media was studied, including phase dissolution, phase interface change, phase mass transfer, and mixed phases. The exchange relation and flow mechanism of multiphase fluid in porous media, i.e., the law of multiphase mixed flow, are clarified. On the basis of the first and second laws of thermodynamics, the framework of the thermodynamic equilibrium relations of a multiphase system was constructed considering phase equilibria during the seepage process. Consequently, a theoretical model of multiphase mixed seepage was established by combining the multiphase mass conservation and multiphase equilibrium thermodynamics equations in the seepage period, which leads to the proposed mixed seepage theory that this paper focuses on. Then, the similarities and differences between conventional multiphase seepage theory and mixed seepage theory were discussed and described comparatively. The analysis and results indicate that the overall velocity of a multiphase system is positively correlated with the pressure gradient, as well as an outcome of the seepage mixing degree defined as a function of saturation, interfacial tension, pressure gradient, and porosity. Additionally, the seepage mixing degree is the product of the mixed seepage coefficient, which reflects the interaction between phases, and the mobility. Defining the seepage mixing degree can convert the motion equation of mixed seepage into a form similar to the generalized Darcy's law, reflecting the fundamental distinction between these two theories. A multiphase system is considered to comprise continuous phases in conventional multiphase seepage theory. However, the fluid phase can be discontinuous and dispersed in other phases. Furthermore, the quantitative relation between total pressure and phase pressure cannot be directly determined, so the capillary force is ignored in many cases. The treatment of these problems is where the limitation of conventional multiphase seepage theory and the comparative superiority of mixed seepage theory lie. Subsequently, a classic case of oil–water two-phase seepage was examined to validate the practicability and adaptability of mixed seepage theory. It can be derived that the multiphase permeability item related to saturation is a simplified form of the seepage mixing degree. The results illustrate that mixed seepage theory reflects the intrinsic features of multiphase seepage and reveals the inner rules of the phase mixing flow process. This theoretical work remedies the conventional approach of extending single-phase Darcy's law to multiphase cases and addresses the deficiency in the generalized Darcy's law by introducing the overall effect to accurately explain the migration of coupling phases, which is of substantial theoretical significance and practical implications.
Abstract: The national strategic goal of “carbon peak and carbon neutrality” can be achieved without lowering living standards by the immediate development of energy saving devices. Where and how to use energy saving devices also must be considered. Energy consumption for building operations occupies a very large proportion of the total energy consumption, with over half of the building operation energy consumption being used for heating and cooling. Electrochromic smart windows can adjust the transmittance of solar radiation into a building by regulating them according to people’s preferences or weather conditions, thereby reducing energy usage. Because electrochromic smart windows use the dual injection of ions and electrons to cause polarization absorption of the material and optical modulation to block solar radiation, they do not require a continuous energy supply to maintain the state, thereby reducing the energy consumption for lighting and cooling while ensuring the building’s aesthetics. Electrochromic materials are the most important part of electrochromic smart windows. Tungsten oxide is a popular electrochromic material and is considered a promising material for electrochromic applications. Tungsten oxide has a large optical modulation range and good stability. After nearly half a century of development, tungsten oxide-based electrochromic smart windows are gradually moving from the laboratory to practical applications. This review will introduce some performance evaluation standards of electrochromic smart windows, including optical modulation range, response time, coloration efficiency, and stability. Based on the performance evaluation standard of electrochromic smart windows, this review provides a summary of several strategies to improve the electrochromic performance of tungsten oxide and presents evaluations of the strategies’ advantages and shortcomings, including the fabrication of oxygen vacancies, doping of heterogeneous metal elements, morphology and size regulation, electrolyte ion screening, and the use of solid electrolytes. Introducing oxygen vacancies in tungsten oxide can improve the optical modulation range; however, it may affect the stability of tungsten oxide. Doping of heterogeneous metal elements can enhance the coloration efficiency at the cost of prolonging the response time. Adjusting morphology and size can shorten the time of electrochromic response; however, it is difficult to control both the morphology and the size of materials. Replacing the electrolyte ion can improve all properties if a suitable ion can be found. Using a solid electrolyte will broaden the scope of tungsten oxide application at the cost of degraded electrochromic properties. Finally, based on the existing problems in the development of electrochromic smart windows and the recently reported promising technologies, this review presents a projection of the development of tungsten oxide-based electrochromic smart windows.
Abstract: To implement the national development goal of “carbon peak, carbon neutral” and address the bottlenecks and challenges encountered by the steel industry in the process of moving toward low-carbon development, a series of studies on policies, technologies, and action plans has been conducted. Given the current situation and changing trend of carbon dioxide emission intensity of domestic and foreign iron and steel enterprises, the reasons for the different intensities of carbon dioxide emissions were analyzed. Further, general directions for carbon dioxide emission peak and carbon dioxide neutralization development in the Chinese iron and steel industry were provided. This study also analyzed the “carbon peak, carbon neutral” targets and implementation plans of the Chinese iron and steel industry and large domestic steel enterprises. The study mainly assessed the current production, current equipment used, technological process, and actual case of carbon dioxide emissions of a large iron and steel enterprise. Future changes in production equipment, production process evolution, technological innovation, and energy transformation based on planning aspects were fully considered in this analysis. A concrete technology roadmap of low-carbon development was made for Chinese iron and steel enterprises as a guide in implementing the national goal of “carbon peak, carbon neutralization.” This roadmap emphasizes that the enterprise will encounter three stages: carbon peak stage platform, steadily declining period, and depth of decarburization. It suggests the consideration of the following: implementing six technical development path that iron element resource optimization, process optimization reconstruction, system efficiency promotion, energy structure optimization, great progress in low-carbon technology, coupling between industries, and constructing a data management system for carbon dioxide emissions, and constructing carbon footprint platforms for the full life-cycle assessment (LCA) of steel products. The analysis found that the total carbon dioxide emissions in 2025 and 2030 will be reduced by 10% and 30%, respectively, and carbon dioxide neutrality will be achieved in 2050. Additionally, the plans of enterprises for their technological paths are clarified. The expected reduction in carbon emissions owing to the implementation of each technological path toward carbon dioxide reduction is calculated. The carbon reduction effects of different technological paths are compared in various development stages. Finally, combined with the establishment and execution process of the low-carbon development technology roadmap of enterprises, some suggestions on the low-carbon development of Chinese iron and steel enterprises are provided.
Abstract: Polycyclic aromatic hydrocarbons (PAHs) are a group of toxic organic compounds from vehicle emissions. Many PAHs are carcinogenic, teratogenic, mutagenic, and immunotoxic, causing a negative impact on human health and severe damage to the environment and ecosystems. Although PAH derivatives, including nitro-polycyclic aromatic hydrocarbons (NPAHs) and oxygenated polycyclic aromatic hydrocarbons (OPAHs), are one to three orders of magnitude lower in concentration than PAH parents, some components are far more mutagenic and carcinogenic than PAH parents. The PAHs and their derivatives in motor vehicle exhaust emission are mainly caused by the incomplete combustion of fossil fuels, and their emission characteristics vary with the combustion conditions and fuel compositions. With the increasingly strict control of exhaust emission standards and the gradual popularization of electric vehicles, non-exhaust emissions have become the main contributors to traffic air pollution. Therefore, as the main source of PAHs in an urban environment, non-exhaust emissions, including brake wear, tire wear, road dust resuspension, and road wear emissions, cannot be ignored in terms of their contribution proportion. The emission characteristics of PAHs and their derivatives from vehicles are mainly affected by many factors, such as combustion conditions, road conditions, and the types of motor vehicle parts and materials. This paper collates and summarizes the existing data on vehicle exhaust and non-exhaust emissions of PAHs and their derivatives at home and abroad. In general, for exhaust emission, stricter emission standards lead to lower emission of PAHs and their derivatives; under operating modes, including cold start and acceleration, the engine combustion efficiency is reduced, leading to an increase in emission; the emission of diesel vehicles is much higher than that of gasoline vehicles; gasoline direct injection (GDI) exhibits higher PAH emissions than port fuel injection (PFI); and emissions increase with increasing vehicle mileage. At present, studies on the non-exhaust emission of PAHs and their derivatives are lacking. Existing studies find that the chemical composition of brake pads, braking conditions, tire materials, and pavement conditions affect non-exhaust emissions, but these findings have a high degree of uncertainty and need further research. This paper is intended to analyze the emission characteristics of PAHs and their derivatives from motor vehicles under different influence factors to provide a scientific basis for developing emission control technology and formulating policy standards.
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
