Abstract: The exploration and development of unconventional oil and gas become the hotspot in worldwide petroleum industry at present and in the future time. The unconventional resources are the succession and growth of conventional oil and gas production. Mineral resource investigations reveal that tight oil reservoirs in China contain highly geological and recoverable reserves, effective development of which is of great significance but restricted by poor reservoir physical properties and complex oil-water distribution. After decades of exploration and development, low and ultra-low permeability reservoirs have been successfully developed. However, development patterns and flow mechanisms suitable for tight oil are still insufficient, and the field application is far from mature yet. This study first summarized the resource distribution, geological characteristics, exploration, and development status of tight oil reservoirs in China. Then, development patterns and corresponding fundamental scientific issues of tight oil reservoirs were discussed. Corresponding nonlinear flow laws, mathematical flow models of multi-field and multiscale related to different exploitation patterns and scientific issues were summarized. Related study results of the authors were also introduced. Finally, a future development trend was proposed for each aspect. We hope that this study will provide some guiding to promote the tight oil exploration in China.
Abstract: As a new type of heat transfer device with a unique working mechanism, the pulsating heat pipe (PHP) has high heat transfer efficiency, high resistance capability to drying out, and good environmental adaptability. Its structure is simple and variable, and the cost is low. Thus, the pulsating heat pipe has a good value for practical application and is currently a research hotspot in the field of heat transfer technology. On the basis of the introduction of the general advantages, structure types, and working principle of the pulsating heat pipe, this study first summarized the structure models, such as the straight tube, single elbow tube, and partially single elbow tube, and the theoretical models, such as the mass-spring-damping model, mass-momentum-energy equation model, and other mathematical models, commonly used in the current theoretical modeling research. Then, the operational process, working mechanism, and latest research progress in pulsating heat pipes at home and abroad were reviewed from the aspects of experimental and computational visualization research. The influence of different design and use parameters, such as pipe diameter and length, shape of the section, heating method, filling rate, angle of inclination, input power, and type of working fluid, on the start-up performance, heat transfer performance, and heat transfer limit of the pulsating heat pipe was systematically introduced. Furthermore, from the design and application perspectives, the research on pulsating heat pipes applied in electronic equipment, solar energy collection, thermal management of power unit, and heat exchange in low-temperature environment was reviewed, and the effects and advantages of pulsating heat pipes in practical application were demonstrated. Finally, the future research directions and development trends were forecasted. It is pointed out that the working mechanism, working performance, working process, and optimization design method of pulsating heat pipes can be investigated through a more detailed theoretical and simulation modeling.
Abstract: The presence of a large amount of fine particles and muddy ore during the heap leaching process leads the occurrence of low leaching rate. Herein, agglomeration experiments using low-grade secondary copper sulfide ore were conducted to enhance the poor heap permeability and low leaching rate caused by the presence of a large amount of fine particles during the heap leaching process. The optimum binder, agglomeration technology, and agglomeration method were selected after investigating the bonding effects of different binders on mineral particles. The effect of single factor, including the binder mass fraction, acid quality, and bulk of water spraying on agglomeration experiments were conducted before the orthogonal experiment. The key factors that have a considerable effect on agglomeration were identified through the orthogonal experiment. According to the experimental results, the order of bonding effect of different granulation binders is as follows: SFS-2 > SFS-3 > cement > hemihydrate gypsum > SFS-1 > SFS-0 > sodium silicate > cationic polyacrylamide. The effect of agglomeration is the best when SFS-2 is selected as a binder, the acid quality is measured as 25 kg·t-1, and the mass fraction of spraying water is 30% during the agglomeration process. The wet strength and compressive strength reaches up to 94.62% and 417.44 N, respectively, after drying. The acid leaching time of agglomerations is maintained for more than 25 d, during which the shape of agglomerations remains unchanged and is without obvious fracture. According to the orthogonal experiment, the factors affecting the agglomeration in the descending order are as follows: binder mass fraction, acid quality, and bulk of water spraying. The bacterial inoculation experiment in the presence of binder was conducted, but it shows no considerable effect of binder on the bacterial community. The bacterial number of experiment in the presence of binder reaches 8.79×107 mL-1, while that in the absence of binder is 8.86×107 mL-1. The leaching experiments results show that the copper leaching rate increases by 12.74% after agglomeration because agglomeration increases the porosity between the minerals and improves the contact between leaching solution and minerals.
Abstract: Al-Si alloys are widely used in modern industries, transportation, and other engineering applications. Processability and mechanical properties of Al-based alloys can be improved via the addition of scandium. Sc added to Al metal for fabricating Sc-containing Al alloys using molten salt electrolysis has been recently considered as promising technology. However, alloying elements, such as Sc and Si are often unevenly distributed in such Al-based alloys. In this study, Al-7Si-Sc ternary alloy was prepared via molten salt electrolysis aided with ultrasound to investigate the effects of ultrasound on the microstructure and distribution of the strengthening phase. Electrolysis was performed on molten salts of Na3AlF6-19%KF-29%AlF3-2%CaF2 at a temperature of 800℃ and current density of 1 A·cm2, in which Sc2O3 (99.99% purity) and Al-7Si alloy served as the raw material and cathodic metal, respectively. Ultrasound (20 kHz, 200 W) was introduced into the cathode metal from the cell bottom. Sc contents in the as-prepared alloy samples were determined using inductively coupled plasma atomic emission spectrometry (ICP-AES). Microstructures of the alloy samples were characterized using optical microscope and scanning electron microscope coupled with an energy dispersive X-ray analyzer. Results reveal that ultrasound can increase Sc content in the ternary alloy prepared via molten salt electrolysis and refine the eutectic silicon clusters and the ternary AlSi2Sc2 phase. Compared with the alloys made without ultrasound aid, the silicon cluster size decreases from approximately 500 to 200 μm (~60%) and the refined ternary phase of AlSi2Sc2 uniformly distributes in the metal matrix. Results also indicate that ultrasound can considerably optimize the microstructure of Al-7Si-Sc alloy prepared via molten salt electrolysis. This process can prevent problems such as the segregation of alloying elements and uneven microstructures observed when using the traditional alloy-making process.
Abstract: Owing to the increasing surface quality of plastic products, such as plastic medical supplies and resin lenses, the demands of plastic molds have increased. Corrosion and wear are the most important failure behaviors of plastic molds; therefore, best-quality plastic mold materials should feature high hardness and corrosion resistance. Super martensitic stainless steels show the optimum combination of strength, hardness, and wear and corrosion resistance after appropriate heat treatment. Therefore, they are the most mainstream materials in the field of high-grade die steel, especially AISI 420. Herein, AISI 420 steels with different average particle sizes and roundness of spheroidized microstructures were treated by different quenching and tempering procedures. Hardness test, scanning electron microscope, and X-ray powder diffraction were then used to research the impact of the spheroidized microstructure on the quenching and tempering characteristics. Additionally, the differences in corrosion resistance were investigated using a potentiodynamic polarization test and soaking corrosion in 3.5% NaCl solution. The results show that small and diffuse spheroidized microstructures increase the solution degree of the C element in AISI 420 steel during quenching, improving the hardening capacity, but increasing the amount of retained austenite simultaneously. Smaller-sized Cr-rich carbides enable the AISI 420 steel to dissolve more Cr element in the austenitizing procedure; therefore, the Cr content of the matrix is higher after quenching and tempering, which reduces the probability of the chromium-depleted area and shows better pitting resistance. Fewer large-sized, undissolved carbides reduce the probability of pitting nucleation in a corrosive environment and improve the corrosion resistance of AISI 420 steel. After tempering at 250℃, AISI 420 shows excellent corrosion resistance and higher hardness. While the steel exhibits the highest hardness, it also bring about the greatest damage to corrosion resistance when tempered at 480℃.
Abstract: Composite coatings were prepared by laser cladding combined with micro-arc oxidation technique on the surface of S355 offshore steel, and the composite coating structures were analyzed using scanning electron microscopy, energy-dispersive spectroscopy, and X-ray diffraction. The corrosion behavior of the composite coating in 3.5% NaCl solution was investigated by polarization curve, electrochemical impedance spectroscopy, corrosive wear test, and immersion corrosion test, and compared with that of the cladding layer and substrate. The results show that the composite coating is mainly divided into inner dense layer and outer loose layer. The loose layer is mainly composed of γ-Al2O3, and the dense layer is mainly composed of α-Al2O3, and the surface hardness of the composite coating reaches the maximum value of HV0.2 1423.3, which is 47.6% higher than that of the cladding coating. Moreover, the surface hardness of S355 offshore steel is significantly improved. The interaction between corrosion and wear in the substrate is mainly corrosion-accelerating abrasion, whereas that in the coating is wear-accelerating corrosion. After micro-arc oxidation treatment, the corrosion potential of the composite coating moves negatively, the passive current density increases, the scale factor of wear-accelerated corrosion gradually decreases, and the corrosive wear resistance of the coating significantly improves. The immersion corrosion method of the cladding coating is mainly pitting corrosion, the composite coating is slightly corroded, and the maximum impedance modulus reaches 105.3 Ω·cm2, which is two orders of magnitude higher than that of the cladding coating. This finding indicates that the corrosive wear resistance of the coating can be further improved after composite treatment.
Abstract: A graphene-nanoflakes (GNFs)-reinforced GNFs/Al-15Si-4Cu-Mg composite was prepared through low-temperature ball-grinder milling and vacuum hot-press sintering. The influences of the GNFs mass content on the microstructural and mechanical properties of the GNFs/Al-15Si-4Cu-Mg composite were investigated via scanning electron microscope, X-ray diffraction, energy disperse spectroscopy, and transmission electron microscope. Meanwhile, tensile strength and micro-hardness tests were conducted. The corresponding result show that for the specimens with 0.4% and 0.8% (mass fraction) GNFs in mass fraction, the nanoflakes are concentrated on the border of the aluminum alloy grain and played a major role in restraining the matrix grain expansion and avoiding crystal particle coarsening. Moreover, the interface bonding between the GNFs and Al-15Si-4Cu-Mg matrix is strong. There are primary β-Si particles, Mg2Si, and Al2Cu-phase precipitated dispersedly throughout the aluminum matrix. The strong interface bonding between the GNFs and Al-15Si-4Cu-Mg matrix leads to the effective impeding of the dislocation slippage and the improvement in the properties of the GNFs/Al-15Si-4Cu-Mg composites. With the addition of the 1.0% GNFs, it is difficult for the GNFs to disperse but easy for them to cluster together to form black impurities on the grain border, inducing brittle Al4Cu2Mg8Si7 phase precipitation along the aluminum alloy grain boundary. As the content of GNFs increases, the composite tensile strength first increases and then decreases. With an addition of 0.8% GNFs, the composite exhibited higher strength and micro- hardness (321 MPa of tensile strength and HV 98 of micro hardness), with the strength and micro-hardness increasing by 19.3%和46.2%, respectively, compared with the pure Al-15Si-4Cu-Mg composite without added GNFs. With the addition of 0.4% GNFs, the yield strength reaches 221 MPa; however, the micro-hardness and ductility (elongation rate) are enhanced. The combined properties of the GNFs/Al-15Si-4Cu-Mg composite obtained are clearly improved.
Abstract: MoSi2 intermetallic is well known as one of the most promising compounds used as structural components due to its high melting point, relatively low density, excellent oxidation resistance, and good strength at high temperatures. Unfortunately, MoSi2 has poor toughness at low temperatures and low creep strength at elevated temperatures. Especially, MoSi2 alloy usually exhibits severe "pest oxidation" at low temperatures of between 400 and 900℃. These problems limit the applications of MoSi2 alloys. The main methods to solve these problems are alloying and compounding. Unfortunately, so far, the problem of low-temperature oxidation resistance of MoSi2 has not been completely solved, and its composite materials are reinforced using external means. In a previous work, SiC particle-reinforced MoSi2 matrix composites were prepared by an in situ synthesis technique, and the microstructures and the mechanical behaviors at room temperature and high temperature were systematically studied. In this work, the long-term oxidation behavior of in situ synthesized SiC particulate-reinforced MoSi2 matrix composites with different volume fractions and occurring at 900℃ for 1000 h was investigated. The composites are not observed to disintegrate (pest) after oxidation for 1000 h. The oxidation resistances of six kinds of materials appear excellent. The composite synthesized by in situ possesses higher oxidation resistance than the traditional composite, which is fabricated by hot-pressing the mixture of commercial powders of MoSi2 and SiC. The surface of scales consists of α-SiO2 (α-quartz), and the subsurface is composed of Mo5Si3. The oxidation of the composites is conducted not only between MoSi2 and O2, but also SiC is oxidized. Selective oxidation of Si completely takes place at 900℃. This selective oxidation results in the spontaneously formation of a layer of dense SiO2 protective scale on the MoSi2 surface, making the material exhibit excellent long-term oxidation resistance.
Abstract: The omnidirectional mobile robot (OMR), which is different from the two-wheeled differential drive mobile robots, can achieve three-degree-of-freedom motion in a plane with no non-holonomic constraint. Therefore, this type of robot has been widely used in many fields owing to its superior maneuverability and controllability. In practical applications, the trajectory tracking problem of the OMRs is a key issue that requires an urgent solution. The challenges with respect to the tracking performance can be categorized into the following: first, the parameter uncertainty of the OMR model and external disturbances affect the accuracy of the control. Second, on account of the limited workspace and the security requirements, the positions, attitudes, and speeds of the OMRs are subject to state constraints during the tracking process. Finally, the limited capability of the actuators can lead to input saturation, which will further degrade the tracking performance or even result in failure to track the desired trajectory. Thus, this study investigates the trajectory-tracking control problem of the OMRs with full-state constraints and input saturation. The kinematics and dynamics for a class of three-wheeled omnidirectional mobile robots were presented with the model uncertainties and external disturbance. Moreover, the barrier Lyapunov method was applied to handle the state constraints using the backstepping technique so that none of the state variables violated the restrictions. Meanwhile, adaptive control laws were designed to deal with the parameter uncertainties and unknown bounded disturbance. Moreover, an anti-windup compensator was adopted to ensure the input torque of the robot met the input constraints. The Lyapunov theory was used to prove that all the signals in the closed-loop system were uniformly bounded when the control parameters were selected suitably. Finally, using numerical simulations, the proposed robust adaptive controller was compared with other controllers, and the results verify the effectiveness and robustness of the proposed method.
Abstract: The super maneuverability of aircraft is a key factor determining its success or defeat in air combat. The analysis and control of aircraft post stall maneuvering at a high angle of attack can greatly improve the aircraft maneuverability. When the aircraft performs a high-angle-of-attack maneuver, the aircraft's attack angle far exceeds the stall angle; thus, the aerodynamic and aerodynamic moment characteristics are not only strongly nonlinear but also have delay effects and strong coupling characteristics. Moreover, the linear control method based on the linearization of small disturbance hardly satisfies the control requirement because there is no typical leveling state. Traditional nonlinear control methods include nonlinear dynamic inverse, sliding mode control, and robust control for high-angle-of-attack maneuvering of aircraft. However, these methods rely on the accurate model of the aircraft and are greatly affected by modeling errors. To realize the high-angle-of-attack maneuver control for an aircraft with thrust vector, a three-channel decoupling control strategy based on active disturbance rejection control was proposed herein. Based on the public data of the third-generation fighter F16, a thrust vector model was developed. The desired triaxial moments were generated by the thrust vector nozzle combination. Active disturbance rejection controllers were independently designed in longitudinal, lateral, and heading channels. The unmodeled dynamics, uncertainty, and strong coupling between the channels were regarded as total disturbance, which was estimated and compensated online. The angular rate damping feedback term made the closed-loop dynamics of the original aircraft approximate a generalized object, which reduced the design order of the active disturbance rejection controller. As two typical post-stall maneuvers, Cobra maneuver and Herbst maneuver were selected for control strategy verification. The numerical simulation results show that the designed three-channel independent active disturbance rejection controllers can eliminate the strong coupling among channels and realize a high-angle-of attack maneuver for the aircraft with thrust vector. The Monte Carlo simulation results show that the control strategy has good robustness.
Abstract: Recently, motor driving systems have been widely applied in the military and industries. Load tracking control is one of the commonly considered issues in such systems. In this study, a plant/controller co-design based on finite-time control was developed for the motor driving system. A finite-time convergent controller was also presented to address the tracking problem in the motor driving system. Because the system state was unknown, a filter was developed to estimate the velocity of the load. The overall system, including the tracking controller and filter, is proven to be finite-time stable. Hence, the upper bound of the convergence time can be determined. To enhance the control performance of the motor driving system, the coupling between plant and controller is considered and a co-design scheme was developed for the motor driving system. First, a combined performance index, which could indicate the largest load with satisfactory control performance, was established. Both the plant and controller parameters were considered in the developed performance index to simultaneously optimize the plant and controller. Through this optimization, the system-level optimality can be determined and a better control performance can be achieved. Moreover, a nested optimization strategy was adopted to simplify the co-design scheme and an adaptive cuckoo search algorithm was used to achieve the co-design result. Through the nested optimization scheme, the controller parameter is optimized in the inner loop and the plant parameter can be optimized in the outer loop. The cuckoo search algorithm exhibits a superior performance because it has fewer parameters that need to be tuned than most existing algorithms. Hence, the co-design problem can be simplified and resolved reliably using the proposed method. Contrastive simulation results indicates the efficacy of the proposed method.
Abstract: As the internet coverage continues to expand, obtaining valuable information from a large amount of fragmented semi-structured text data has become a huge challenge considering the vast amount of social public information. Event trigger identification technology can effectively mine and refine text information so that the users can quickly and accurately get what they need; thus, it has gradually become an active research area in the field of natural language processing. An event trigger word is generally a word or phrase that marks the occurrence of the event, then trigger word identification has been applied to many aspects and plays an important role in the fields of knowledge base construction, intelligent search engine, automatic question answering robot, and automatic summarization. However, the text data are characterized by high dimensionality and ambiguity. The existing identification methods are mostly based on manual complex feature engineering or only consider the features in a certain text window. In this process, manual analysis and selection of a large number of features are required. Considerable reliance on natural language processing tools leads to the inability of applying the model on a large scale, and there are problems of erroneous cascade communication and complicated feature engineering. This paper proposed a fusion model based on the bidirectional long short-term memory (BiLSTM) and feed-forward neural networks to complete the trigger identification task for public security events. First, the high-level features of the entire text were extracted through BiLSTM to avoid manual feature extraction, which was associated with the existing machine learning methods. Then, contacted features were used to input feed-forward neural networks and identify event triggers. The experimental results show that the proposed method achieves good performance in the Chinese emergency corpus, CEC, and the Micro-F1 is 78.47%. In addition, the importance of different contacted features was also discussed in trigger word recognition tasks, and the importance of three types of features, namely part of speech, syntax, and entity, in text analysis was analyzed. It is concluded that syntactic features are most helpful to the task of event-trigger word recognition.
Abstract: Internet public opinion is an important source of people's views on social hotspots and national current affairs. Topic detection in network long text contributes toward the analysis of network public opinion. According to the results of topic detection, the policymaker can timely and reliably make scientific decisions. In general, topic detection can be divided into two steps, i.e., representation learning and topic discovery. However, common representation learning methods, such as state vector space model (VSM) and term frequency-inverse document frequency, often lead to the problems of high dimensionality, sparsity, and latent semantic loss, whereas traditional topic discovery methods depend heavily on the text input orders. To overcome these, a novel topic detection method was presented herein. First, Word2vec & latent Dirichlet allocation (LDA)-based methods for representation learning were proposed to avoid the problem of high-dimensional sparsity and neglect of latent semantics. Weighted fusion of the text feature word implicit topic extracted by LDA and the feature word vector of Word2vec mapping could not only perform dimensionality reduction but also completely represent text information. Furthermore, Single-Pass and hierarchical agglomerative clustering for topic discovery could be more robust for input orders. To evaluate the effectiveness and efficiency of the proposed method, extensive experiments were conducted on a real-world multi-source dataset, which was collected from university social platforms. The experimental results show that the proposed method outperforms other methods, such as VSM and Single-Pass, by improving the clustering accuracy by 10%-20%.
Abstract: Self-tuning control is an important approach to intelligent control system design because this kind of control system uses online parameter estimation (or learning) to derive the model of the plant, and as a result of model parameter estimation (or learning), the controller parameters can be adjusted online. However, we still lack a unified analysis tool (which is independent of specific controller design strategy and parameter estimation algorithm) that can be used by engineers to easily understand and judge the stability, convergence, and robustness of this kind of self-tuning control system. This study is focused on a unified analysis of deterministic multivariable self-tuning control systems with the help of the virtual equivalent system (VES) approach based on the transfer function concept. For different parameter estimation situations (three cases are considered, i.e., parameter estimation converges to its true value, parameter estimation converges to other values, and parameter estimation does not converge), four theorems and two corollaries on the stability, convergence, and robustness of deterministic multivariable self-tuning control systems are given with some remarks. These results are independent of specific controller design strategy and parameter estimation algorithm. From the results obtained in this study, it is concluded that the convergence of parameter estimates is unnecessary for the stability and convergence of a self-tuning control system. The feedback information of the self-tuning control system itself is sufficient to achieve the control objective, i.e., the external excitation signal is unnecessary for the deterministic multivariable self-tuning control system. Moreover, on the basis of the results of the stability, convergence, and robustness of deterministic multivariable self-tuning control systems, we have obtained a profound understanding of the self-tuning control system design method. This understanding will provide more flexibility for engineers in real applications of this kind of controller design strategy.
Abstract: Optical coherence tomography (OCT) plays an important role in the diagnosis of ocular fundus diseases. Retinal OCT images contain a large amount of useful information for the diagnosis of ocular fundus diseases and are often used to detect small lesions of the fundus. At present, many medical researchers have used OCT to determine the statistical characteristics of the retina to analyze various fundus diseases. When interpreting the OCT images, ophthalmologists will focus on the location of the lesions in the images and the characteristic morphology conducive to abnormal judgment and compare the histological structure of specific objects in the images with the known normal morphology. In the comparison process, the ophthalmologist will conduct a variety of quantitative analyses of OCT retinal images and determine the severity of the abnormalities and the location of the lesions. Finally, on the basis of the differences between the morphologies and types of diseases, the diagnostic decision is obtained. However, at present, OCT instruments generally only provide the thickness, area, and other commonly used characteristic data, and these data are often inadequate to determine the disease. Computer graphics processing technology has been applied to the auxiliary analysis of OCT images. However, this kind of research often confines the object of study to several specific fundus diseases and makes targeted selection of quantitative features. In the actual diagnosis process, it is difficult to confine the retinal images to some known abnormal cases because of the complexity of the situation. In this study, a retinal feature quantization method based on a reference model was proposed, and a series of quantifiable features suitable for computer judgment and analysis of retinal state were proposed. On the basis of the segmentation and extraction of the internal limiting membrane (ILM), junctions of the inner and outer segments of photoreceptors (ISOS) and Bruch's membrane (BM) in normal OCT images, a reference model of normal retina was constructed by the statistical method. Combining the reference model with the retinal thickness, smoothness, and continuity, the thickness characteristics, thickness ratio characteristics, gradient characteristics, curvature, standard deviation, and correlation coefficient characteristics of different regions of the retina were calculated. On the basis of the reference model of normal OCT images, the quantitative values of retinal thickness and morphological characteristics were obtained. By analyzing and comparing the characteristic value differences between abnormal OCT images and reference model, the location and severity of abnormal morphology caused by lesions could be characterized in the abnormal OCT images. The experimental results show that the normal retinal feature information obtained by the reference model can provide a numerical reference for ophthalmologists. At the same time, the characteristic values obtained by quantizing the abnormal OCT images can show the abnormal morphology, which provides a basis for subsequent abnormal judgment.
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
