Processes, Volume 11, Issue 9 (September 2023) – 297 articles

This paper attempts to analyze and assess Yongchuan Xiuya tea quality quickly, accurately, and digitally. The sensory evaluation method was first used to assess Yongchuan Xiuya tea quality, and then near infrared spectroscopy (NIRS) was obtained, and standard methods were applied to the testing of the chemical components. Next, principal component analysis (PCA) and the correlation coefficient method were used to comprehensively screen out the representative components. Finally, NIRS combined with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN) methods were applied to build quality evaluation models for Yongchuan Xiuya tea, respectively, and external samples were employed to examine the practical application results of the best model. The cumulative variance contribution rate of the first three principal components of the ingredients in tea was 97.73%. Seven components closely related to tea quality were screened out, namely, amino acids, total catechin, epigallocatechin gallate (EGCG), tea polyphenols, water extracts, epicatechin gallate (ECG), and epigallocatechin (EGC) (p < 0.01). Between the two models established to predict the tea quality, the model built by the PLS method had the better results, whose coefficient of determination of prediction (Rp2) and root mean square error of prediction (RMSEP) were 0.7955 and 1.2263, respectively, and the best results were obtained by the nonlinear BP-ANN model, whose R_p² and RMSEP were 0.9315 and 0.6787, respectively. The 10 external Yongchuan Xiuya samples were employed to test the best BP-ANN model, and the results of R² and RMSEP were 0.9579 and 0.6086, respectively, meaning that the model has good robustness. Therefore, the model established by NIRS combined with the BP-ANN method can be used to assess Yongchuan Xiuya tea quality rapidly, accurately, and digitally, and it can also provide new ideas and methods for evaluating the quality of other teas. Full article

The diffusion coefficient (D) is a key parameter that characterizes the gas transport occurring in coal seams. Typically, D is calculated using the desorption curve of particle coal. However, this method cannot accurately reflect the diffusion characteristics under the stress constraint conditions of in situ coal seams. In this study, different metamorphic deformed coals of medium and high coal rank were considered based on Fick’s law of counter diffusion. The change laws of D under different confining pressures, gas pressures, and temperature conditions were tested and analyzed, and the influencing mechanisms on D are discussed. The results showed that D of different metamorphic deformed coals exponentially decreased with an increase in confining pressures, and exponentially increased with increases in gas pressures and temperature. There is a limit diffusion coefficient. The influence of the confining pressure on D can essentially be determined by changes in the effective stress, and D negatively affects the effective stress, similar to permeability. The effect of gas pressure on D involves two mechanisms: mechanical and adsorption effects, which are jointly restricted by the effective stress and the shrinkage and expansion deformation of coal particles. Temperature mainly affects D by changing the root-mean-square speed and average free path of the gas molecules. Under the same temperature and pressure conditions, D first increased and then decreased with an increase in the degree of deformation. D of the fragmented coal was the largest. Under similar deformation conditions, D of the high-rank anthracite was larger than that of the medium-rank fat coal. Porosity is a key factor affecting the change in D in different metamorphic deformed coals. Full article

Well structures with ultra-long sections have become one of the most applied technologies in the field of shale gas development. While there have been many technical challenges, enhancing the breaking efficiency and stability of polycrystalline diamond compact (PDC) bits has become an essential issue of focus. Since 2013, the well structure in the Duvernay area has been optimized multiple times, and the rate of penetration (ROP) of the entire wellbore has nearly doubled. However, there are significant differences in terms of the performances of different PDC bits, and there is still room for improvement to optimize these drill bits. For this reason, a confined compressive strength test was conducted to obtain the rock mechanical parameters from shale cores extracted from the long horizontal section. Using these data, a finite element model (FEM) was developed with a corresponding scale. A calibration of the elastic-plastic damage constitutive models was then performed using the FEM. The breaking mechanism of three different PDC bits was examined using a “PDC bit-bottom hole” interaction FEM model, facilitating guidance for bit selection and design optimization: (1) The type B PDC bit, which has four blades and 20 cutters, exhibited the highest mechanical specific energy (MSE) and the lowest vibration across three directional mechanical characteristics. This design is recommended for engineering applications. (2) Lower axial vibrations were produced when the CDE was used as the rear element when compared to those when using the BHE. However, an increase within an acceptable range was observed in the TOB and circumferential vibrations. Thus, for redesigning work on the type B bit, the assembly of the CDE is suggested. (3) A decrease in the MSE and vibration in three directional mechanical characteristics was observed when the depth of cut (DOC) was varied between 1.5 and 2.0 mm. A broadening in the range of lateral forces was noted when a DOC of 2.0 mm was used. Therefore, for the redesign of the type B bit, the assembly of CDEs as rear elements at a DOC of 1.5 mm is recommended. In conclusion, a new practical method for the selection and optimization of PDC bit design, based on rock mechanics and the FEM theory, is proposed. Full article

The prediction of the glass-forming ability (GFA) of metallic glasses (MGs) can accelerate the efficiency of their development. In this paper, a dataset was constructed using experimental data collected from the literature and books, and a machine learning-based predictive model was established to predict the GFA. Firstly, a classification model based on the size of the critical diameter (D_max) was established to determine whether an alloy system could form a glass state, with an accuracy rating of 0.98. Then, regression models were established to predict the crystallization temperature (T_x), glass transition temperature (T_g), and liquidus temperature (T_l) of MGs. The R² of the prediction model obtained in the test set was greater than 0.89, which showed that the model had good prediction accuracy. The key features used by the regression models were analyzed using variance, correlation, embedding, recursive, and exhaustive methods to select the most important features. Furthermore, to improve the interpretability of the prediction model, feature importance, partial dependence plot (PDP), and individual conditional expectation (ICE) methods were used for visualization analysis, demonstrating how features affect the target variables. Finally, taking Zr-Cu-Ni-Al system MGs as an example, a prediction model was established using a genetic algorithm to optimize the alloy composition for high GFA in the compositional space, achieving the optimal design of alloy composition. Full article

The joints and fissures in a natural rock mass can affect the mechanical properties of the rock mass, the propagation of a blasting stress wave, and the blasting effect of the smooth surface of roadways. In the process of roadway drilling and blasting, there will inevitably be some joints between the two blast holes. Taking the joint angle as the starting point, this paper studies the rule of rock explosion crack propagation and stress variation when there are joints with different angles between two blast holes and analyzes the influence of joints on rock mechanical properties and blasting effects. The numerical simulation method and the software ANSYS/LS-DYNA are used to establish 7 rock mass models with various joint angles. When there is no joint between two holes and joints of 15°, 30°, 45°, 60°, 75°, and 90°, the propagation of explosive cracks and stress variations in the rock mass are discussed. The results show that the joints at different angles have obvious guiding and blocking effects on the propagation of explosive cracks, and as joint angles increase, the guiding effect becomes more apparent and the blocking effect becomes weaker. The effective stress of the rock mass will vary depending on the angles of the joints between the hole and the joint. As the joint angle increases, the joint’s influence on the reflection and superposition of stress waves gradually weakens, and the peak value of the effective stress of the rock mass gradually decreases. The peak effective stress of the rock mass on the blasting side of the joint is similarly impacted by the superposition of stress waves, and the extreme value may be seen at the critical node of each change curve. The explosive crack will break through at the critical location because the maximal effective stress of the rock mass is distributed in a “W” form on the blasting side of the joint. Full article

The development of sensor networks allows for easier time series data acquisition in industrial production. Due to the redundancy and rapidity of industrial time series data, accurate anomaly detection is a complex and important problem for the efficient production of the textile process. This paper proposed a semantic inference method for anomaly detection by constructing the formal specifications of anomaly data, which can effectively detect exceptions in process industrial operations. Furthermore, our method provides a semantic interpretation of exception data. Hybrid signal temporal logic (HSTL) was proposed to improve the insufficient expressive ability of signal temporal logic (STL) systems. The epistemic formal specifications of fault offline were determined, and a data-driven semantic anomaly detector (SeAD) was constructed, which can be used for online anomaly detection, helping people understand the causes and effects of anomalies. Our proposed method was applied to time-series data collected from a representative textile plant in Zhejiang Province, China. Comparative experimental results demonstrated the feasibility of the proposed method. Full article

Wider application of BiVO₄ (BVO) for photocatalytic water treatment is primarily limited by its modest photocatalytic effectiveness, despite its appropriately narrow band gap for low-cost, sunlight-facilitated water treatment processes. In this study, we have photomodified an isotype BVO, consisting of a tetragonal zircon and monoclinic scheelite phase, with Fe (Fe@BVO) and Ag (Ag@BVO) ionic precursors under UV illumination in an aqueous ethanol solution in order to assess their effect on the opto-electronic properties and effectiveness for the removal of ciprofloxacin (CIP). Fe@BVO failed to demonstrate enhanced effectiveness over pristine BVO, whereas all Ag@BVO achieved improved CIP degradation, especially 1% Ag@BVO. At pH 4 and 6, 1% Ag@BVO demonstrated nearly 24% greater removal of CIP than BVO alone. Photomodification with Fe created surface oxygen vacancies, as confirmed by XPS and Mott–Schottky analysis, which facilitated improved electron mobility, although no distinct Fe-containing phase nor Fe-doping was detected. On the other hand, the introduction of mid-band gap states by oxygen vacancies decreased the reducing power of the photogenerated electrons as the flat band potentials were shifted to more positive values, thus likely negatively impacting superoxide formation. In contrast, Ag-photomodification (Ag@BVO) resulted in the formation of Ag₂O/AgO and Ag nanoparticles on the surface of BVO, which, under illumination, generated hot electrons by surface plasmon resonance and enhanced the mobility of photogenerated electrons. Our research underscores the pivotal role of photogenerated electrons for CIP degradation by BiVO₄-based materials and emphasizes the importance of appropriate band-edge engineering for optimizing contaminant degradation. Full article

The rock mass is susceptible to instability and damage during cavern construction. The blast-induced cracking process of the rock mass contains a wealth of information about the precursors of instability, and the identification of fracture nucleation signals is a prerequisite for effective hazard warning. A laboratory mechanical test and microseismic (MS) monitoring were carried out in the Baihetan Cavern to investigate the fracture nucleation process in the rock mass. MS monitoring shows that pre-existing microcracks were closed or new cracks were generated under the action of high stress, which caused the migration of microcracks. As the crack density increases, the fracture interaction gradually increases. The study of the rock fracture nucleation mechanism helps to reveal the MS sequences during the rock fracture process, and the fore-main shock was found in the MS sequence during access tunnel excavation. This study can effectively provide guidance for the early warning of rock mass failure and the stability analysis of underground caverns under blasting excavation disturbance. Full article

Shale oil reservoirs in the Daanzhai section of central Sichuan are mainly developed in the Daer subsection, with a rich resource base and great exploration and development potential. However, the shale oil reservoir is characterized by shale and limestone interactions, poor physical properties, undeveloped fractures, and large differences in the fracture pressure of interactive reservoirs. Therefore, it is necessary to use temporary plugging and diverting fracturing technology to improve the complexity of fractures in reservoir reconstruction. To this end, an experimental device was innovatively established that takes into account the morphology of fractures and the permeability of reservoirs, and it can evaluate the temporary blocks and turns within third-level fractures in a reservoir. It can simulate third-level turning fractures under conditions involving 3–15 mm crack openings and different roughness values. Using this device and method, the combination and particle-size optimization experiments involving the temporary plugging agents used in the field were carried out, and the field tests were carried out in Well Long’an 1 and Well Ren’an 1 in the Sichuan Basin. The test results show that the pressure response after temporary plugging is obvious, which can significantly improve microseismic event points and increase the reservoir’s reconstruction volume. Compared with Well Nanchong 2H, the length in kilometers of the SRV after tackling key problems increases from 3918 × 10⁴ m³ to 4578 × 10⁴ m³, an increase of 17%. The average crack length increased from 265 m to 321 m, an increase of 21%, achieving a significant breakthrough in the “oil production gap”. Full article

This article presents the technical aspects that may reduce electric power consumption during the welding of pipes with the high-frequency induction (HFI) method. Experiments were carried out at Huta Łabędy S.A. Steelworks, during the test production of 323.9 × 5.6 mm pipes of P235GH steel grade. Two sets of HFI heating system settings were studied: with a variable squeeze force of the heated edges and a variable position of the inductor in relation to the welding point. It was proven that the temperature at the welding point increased due to the stronger squeeze of the heated edges, which reduced the electric power consumption. Reducing the distance of the inductor relative to the welding point had the same effect. By optimizing the squeeze force and the position of the inductor, energy consumption was reduced by about 5.5%. Microstructural studies of the welds did not show any adverse effects of the optimization. Full article

Intelligent textile clothing is one of the most popular topics in the field. In recent decades, rapid advances have been made in the area of intelligent textile clothing research, and the intellectual structure pertaining to this domain has significantly evolved. We used CiteSpace 6.2.R4, VOSviewer 1.6.19, to evaluate and visualize the results, analyzing articles, countries, regions, institutions, authors, journals, citations, and keywords. Both a macroscopic sketch and a microscopic characterization of the entire knowledge domain were realized. The aim of this paper is to utilize bibliometric and knowledge mapping theories to identify relevant research papers on the subject of smart textiles and clothing that have been published by the China Knowledge Network Web of Science (WOS) within the last decade. It is concluded that the main topics of smart textile and garment research can be divided into nine categories: wearable electronics, smart textiles, flexible antennas, energy storage, textile actuators, mechanical properties, asymmetric supercapacitors, carbon nanotubes, and fiber extrusion. In addition to the latter analysis, emerging trends and future research foci were predicted. This review will help scientists discern the dynamic evolution of intelligent textile clothing research as well as highlight areas for future research. Full article

Triboelectric nanogenerators (TENGs) are emerging as a form of sustainable and renewable technology for harvesting wasted mechanical energy in nature, such as motion, waves, wind, and vibrations. TENG devices generate electricity through the cyclic working principle of contact and separation of tribo-material couples. This technology is used in outstanding applications in energy generation, human care, medicinal, biomedical, and industrial applications. TENG devices can be applied in many practical applications, such as portable power, self-powered sensors, electronics, and electric consumption devices. With TENG energy technologies, significant energy issues can be reduced or even solved in the near future, such as reducing gas emissions, increasing environmental protection, and improving human health. The performance of TENGs can be enhanced by utilizing materials with a significant contrast in their triboelectrical characteristics or by implementing advanced structural designs. This review comprehensively examines the recent advancements in TENG technologies for harnessing mechanical waste energy sources, with a primary focus on their sustainability and renewable energy attributes. It also delves into topics such as optimizing tribo-surface structures to enhance output performance, implementing energy storage systems to ensure stable operation and prolonged usage, exploring energy collection systems for efficient management of harvested energy, and highlighting practical applications of TENG in various contexts. The results indicate that TENG technologies have the potential to be widely applied in sustainable energy generation, renewable energy, industry, and human care in the near future. Full article

Efficiency and compactness are core strengths of the supercritical carbon dioxide (sCO${}_2$) Brayton cycle, which is considered an alternative to the steam Rankine cycle for moderate-temperature heat sources (350–800 °C). Numerical investigations on system design and analysis have received considerable attention, with the aim of improving the sCO${}_2$ cycle from the viewpoint of thermodynamics. This paper reviews and compares previous studies in the literature to survey different cycle layouts, operating parameters, and working fluids of the sCO${}_2$ cycle. Performance enhancement approaches are categorized into three classes according to characteristics: conventional methods, CO${}_2$ mixtures, and combined cycles. The strengths, weaknesses, and limitations of each categorized method are discussed. This research is expected to provide a roadmap for performance improvement that meets the interests of researchers. Full article

The reliability of an RMT can be regarded as an important indicator customers can use to recognize its quality; however, it is difficult to implement a full-state reliability analysis of an RMT due to its complicated structural functions. Therefore, a full-state reliability analysis model is proposed herein based on meta action (MA) and a Markov chain for remanufactured exercise machine tools (REMTs). First, an analysis was carried out on individual levels by integrating the MAU decomposition method, and an MAU fault tree model was established layer by layer for the REMT. Second, full-state modeling was performed in view of the MAU characteristics of the REMT, whose operation processes are divided into MAU normal and failure states. A Markov decision-making process was introduced to integrate MAU states and establish our model, which was solved by means of an analytical method for the evaluation of reliability. Finally, an example of a remanufactured machine tool spindle is given to verify the effectiveness of the method. Full article

Tuberculosis (TB) is a bacterial disease that remains a global health threat due to the millions of deaths attributed to it each year. The emergence of drug resistance has exacerbated and further increased the challenges in the fight against this illness. Despite the preventive measures using the application of the Bacillus Calmette-Guérin vaccine, the desired immunization outcome is not as high as expected. Conventional TB treatments exhibit serious limitations, such as adverse effects and prolonged duration, leading to a pressing need for alternative and more effective treatment options. Despite significant efforts, it took nearly four decades for diarylquinoline to become the most recently approved medicine for this disease. In addition, various possibilities, such as the usage of medications used for many other conditions (repurposed drugs), have been explored in order to speed up the process of achieving faster outcomes. Natural compounds derived from various sources (microorganisms, plants, and animals) have emerged as potential candidates for combating TB due to their chemical diversity and their unique modes of action. Finally, efforts towards the generation of novel vaccines have received considerable attention. The goal of this paper was to perform an analysis of the current state of treating drug-resistant TB and to evaluate possible approaches to this complicated challenge. Our focus is centered on highlighting new alternatives that can be used to combat resistant strains, which have potentiated the health crisis that TB represents. Full article

The increasing antimicrobial resistance (AMR) of pathogens is a significant threat to human and animal health, but it is also an environmental challenge for water resources. The present study aimed to quantify heterotrophic bacteria resistant to five groups of antibiotics (ABs) in a selected Yantra River stretch (including its tributary, the Belitsa River); to assess AMR prevalence among Enterobacteriaceae; and to assess the impact of urban effluents or rural runoff on AMR prevalence along the river course at eight sampling points. Culture-dependent methods were used in a population-based study of total AMR and for AB susceptibility testing of Enterobacteriaceae isolates. The data reveal significant differences in AMR dissemination and a lower (up to 10%) proportion of different types of antibiotic-resistant bacteria (ARB) in the Yantra River water compared to the Belitsa River (up to 20%). The incidence of resistant Enterobacteriaceae isolates was in the range of 1% to gentamicin to 36% to ampicillin, including multidrug resistance of 19%, and different AMR patterns of isolates from each river. The prevalence of AMR among aquatic bacteria highlights the need for adequate waste water treatment and for management, monitoring and control of treatment processes to limit anthropogenic pressure through discharge of untreated or incompletely treated waste water and to ensure the ecological well-being of receiving waters. Full article

The Ordovician Wulalike Formation in the northwestern Ordos Basin is a new prospect for exploring marine shale gas in China, facing prominent problems such as unclear reservoir conditions and the distribution of enrichment areas. The types of reservoir space, fracture development, porosity composition, and physical properties of the lower Wulalike Formation are discussed through the multi-method identification and quantitative evaluation of reservoir space for appraisal wells. The Wulalike Formation in the study area contained fractured shale reservoirs with matrix pores (mainly inorganic pores) and permeable fractures. The fracture system of the lower Wulalike Formation is dominated by open bed-parallel fractures that are intermittent or continuous individually, with a width of 0.1–0.2 mm and spacing of 0.5–14.0 cm. The fracture-developed intervals generally exhibit bimodal or multimodal features on NMR T2 spectra and have a dual-track feature with a positive amplitude difference in deep and shallow resistivity logs. The length and fracture porosity of fracture-developed intervals varied greatly in different parts of the study area. In the Majiatan-Gufengzhuang area in the southern part of the study area, the fracture development degree generally decreased from west to east. In the Shanghaimiao area in the central part of the study area, fractures were extremely developed, the continuous thickness of the fracture-developed interval was generally more than 20 m, and the average fracture porosity was higher than 1.3%. In the Tiekesumiao area in the northern part of the study area, the fracture development degree was generally lower than that in the central and southern parts of the study area and also showed a decreasing trend from west to east. The lower Wulalike Formation had a total porosity of 2.46–7.08% (avg. 4.71%), roughly similar to the Longmaxi Formation in the Sichuan Basin, of which matrix porosity accounts for 34.0–90.0% (avg. 61.1%) and fracture porosity accounts for 10.0–66.0% (avg. 38.9%). From this, it could be inferred that the shale gas accumulation type of the lower Wulalike Formation in the northwest margin of the basin is mainly a fractured shale gas reservoir controlled by structure, and its “sweet spot area” is mainly controlled by tectonic setting and preservation conditions. This indicates that the Wulalike Formation in the northwestern Ordos Basin has good shale gas exploration prospects, and a large number of fault anticlines or fault noses formed by reverse dipping faults have the potential of favorable exploration targets. Full article

In this study, a Computational Fluid Dynamics (CFD) approach using Ansys Fluent 15.0 and FLIC software was employed to simulate the combustion process of a 750 t/d grate-type waste incinerator. The objective was to assess the performance of Selective Non-Catalytic Reduction (SNCR) technology in reducing nitrogen oxide (NO_x) emissions. Two-stage simulations were conducted, predicting waste combustion on the bed and volatile matter combustion in the furnace. The results effectively depicted the temperature and gas concentration distributions on the bed surface, along with the temperature, velocity, and composition distributions in the furnace. Comparison with field data validated the numerical model. The findings serve as a reference for optimizing large-scale incinerator operation and parameter design through CFD simulation. Full article

The quality of borehole sealing is a key factor affecting the efficiency of gas production. A new water-rich grouting material (RW) with composite coagulant and other additives was prepared in this study to overcome the disadvantages of long setting time and low stone rate of traditional cement materials. When the coagulants A is 4 g and coagulants B is 2 g, the setting time of RW material was reduced by 60.85% and 50.62%, which significantly shortened the setting time of the RW material, respectively. Based on the orthogonal method, 29 groups of comparative experiments were designed to investigate the interaction mechanism between different additives on the performance index of RW, including setting time, water secretion rate, and compressive strength. Quadratic regression equations were fitted using the response surface method. All the correlation coefficients R² of each response model were greater than 0.97, R² and R²_adj were less than 0.2 through variance analysis, indicating a high correlation between the actual and prediction results. The water–cement ratio had the most significant effect among all factors on setting time, water secretion rate, and compressive strength of the RW material. The scanning electron microscope (SEM) was used to compared the micromorphological characteristics of RW and conventional Portland cement material (PC). The results showed that the hydration products of RW were mostly smack ettringite, calcium silicate hydrate gel, and calcium hydroxide, which interweaved with each other to form a network structure that was denser than the PC material. Furthermore, the interface bonding degree between RW and injected coal was tighter than that of PC, without obvious cracks at the slurry–coal interface. The results indicate that the addition of composite coagulant can significantly accelerate the hydration process of RW material and also enhance the interface strength of injected coal, which is conducive to improving the grouting quality and sealing effect of the extraction borehole. Full article

Manufacturing parts made of thin steel in small batches is a challenging task in terms of reaching the proper balance between the productivity, the cost, and the dimensional precision. This paper presents the results of experimental research about manufacturing electrical steel thin parts using abrasive waterjet cutting. For a certain increase of productivity and a more efficient process, the parts were cut using multilayer packages of steel strips. The main objective was to analyze the influence of the number of layers on the dimensional precision of parts. Preliminary tests were performed, followed by a full factorial experiment using two independent parameters, the number of layers and the traverse speed. The parts were measured on a noncontact vision measurement machine and mathematical models were determined to predict the parts deviations depending on the independent parameters used. A practical validation of the models was performed. The main conclusion is that the number of layers has a certain influence on the accuracy of dimensions, but this influence can be predicted with a satisfactory level of confidence using mathematical models. Full article

In response to the issue of the hydropower consumption of run-of-river hydropower stations in Southwest China, the district cooling system can provide regulation capacity for hydropower utilization and suppress fluctuations caused by the uncertainty of hydropower. The innovative method is to utilize the thermal characteristics of pipelines and buildings, as well as the thermal comfort elasticity to shift the cooling and electricity loads, which helps to consume the surplus hydroelectric power generation. Taking the minimum total cost of coal consumption in thermal power units, hydropower abandonment penalty, and the carbon trading cost as the objective function, models were established for power supply balance constraints, heat transport constraints, and unit output constraints. The hybrid integer linear programming algorithm was used to achieve the low-carbon economic dispatch of the electric-cooling system. The calculation examples indicate that compared to the traditional real-time balance of cooling supply, the comprehensive consideration of thermal characteristics in a cooling system and flexible thermal comfort have a better operational performance. The carbon trading cost, coal consumption cost, and abandoned hydropower rate of a typical day was reduced by 4.25% (approximately CNY 7.55 × 10⁴), 4.47% (approximately CNY 22.23 × 10⁴), and 3.66%, respectively. Therefore, the electric-cooling dispatch model considering the thermal characteristics in cooling networks, building thermal inertia, and thermal comfort elasticity is more conducive to the hydropower utilization of run-of-river stations. Full article

Porosity, permeability, and wettability are crucial factors that affect the oil–water displacement process in reservoirs. Under subsurface conditions, the integral effects of these factors are extremely difficult to document. In this paper, waterflooding experiments were carried out using a core flooding system monitored with X-ray dual-energy CT. The mesoscale, three-dimensional characteristics of water displacing oil were obtained in real time. The integral effects of porosity, permeability, and wettability on the waterflooding in the low-permeability sandstone reservoirs were investigated. It was found that if the reservoir rock is water-wet, then the residual oil saturation decreases gradually with increasing porosity and permeability, showing an increasing waterflooding efficiency. On the contrary, if the reservoir rock is oil-wet, the residual oil saturation gradually increases with improving porosity and permeability, showing a decreasing waterflooding efficiency. The porosity, permeability, and wettability characteristics of reservoirs should be comprehensively evaluated before adopting technical countermeasures of waterflooding or wettability modification during oilfield development. If the porosity and permeability of the reservoir are high, water-wet reservoirs can be directly developed with waterflooding. However, it is better to make wettability modifications first before the waterflooding for oil-wet reservoirs. If the porosity and permeability of the reservoir are poor, direct waterflooding development has a better effect on oil-wet reservoirs compared with the water-wet reservoirs. Full article

In this work, one improved symmetric time-variant logarithmic barrier, Lyapunov function (BLF), is developed for the first time to handle the state constraint problem of nonlinear systems. It is universal in the sense that the improved barrier function is a general one that can be used not only in systems with constrained requirements but also in systems without constrained requirements, without altering the designed controller. First of all, the n-link robotic system is transformed into a kind of multi-input and multi-output (MIMO) system. Then, a trajectory tracking control scheme is designed by combining the improved time-variant logarithmic BLF with the disturbance observer to solve the problems of model uncertainty and position constraint for the robotic system. We give that under the proposed controller, all the robotic system’s error vectors can trend to the equilibrium point asymptotically while the constraint conditions on the position are always met. Finally, the effectiveness of the presented scheme is indicated by completing two simulation experiment cases. Full article

The EDEM software (Altair EDEM 2022.0 professional version 8.0.0) was used to create a discrete element model of silage to address the lack of silage evidence parameters and contact parameters between silage and conveying equipment when using the discrete element method to simulate and analyze crucial aspects of silage conveying and feeding. Physical tests and simulations were used to calibrate the significant parameters, and the silage stacking angle obtained from simulation and tests was then validated. The response value of the stacking angle (38.65°) obtained from the physical examination was used as the response value. The response surface (RSM) finding and the GA finding based on the genetic algorithm (GA) artificial neural network (BP) model were used to compare the significance parameters. The PB and steepest climb tests were used to screen the significant factors. Results indicate that the static friction coefficient between silage and silage, the rolling friction coefficient between silage and silage, and the static friction coefficient between silage and the steel body are significant factors affecting the stacking angle of numerical simulation; the parameter optimization effect of GA-BP-GA is superior to that of RSM; the optimal parameter combinations are as follows: 0.495, 0.194, and 0.420, respectively, and the simulated stacking angle is 39.1510°, which matches the empirical test result. The relative error between the simulated and stacking angles derived from the physical test was 1.3%. The results demonstrate that the silage model is reliable within the parameters derived from the calibration, and that the calibrated parameters can be used in other discrete element simulation studies of silage. Full article

To eliminate or reduce stick–slip vibration in torsional vibration of the drilling string and improve the rate of penetration (ROP), a stick–slip vibration model of the drilling string considering the ROP was established based on the multidimensional torsional vibration model of the drilling string. The model was verified by simulation analysis. The characteristics of the drilling string stick–slip vibration in the three stages of stationary, slip, and stick were analyzed. This paper investigated the influence of rotary torque, rotary speed, and weight on bit (WOB) on stick–slip vibrations in the drill string. Based on this, the relationship between the drilling parameters and ROP was established. Drilling parameter optimization was completed for soft, medium-hard, and hard formations. Results showed that appropriately increasing torque and decreasing WOB can reduce or even eliminate stick–slip vibrations in the drill string and increase the ROP. The parameter optimization increased the ROP by 11.5% for the soft formation, 13.7% for the medium-hard formation, and 14.3% for the hard formation. The established drill string stick–slip vibration model provides theoretical guidance for optimizing drilling parameters in different formations. Full article

Existing power anomaly detection is mainly based on analyzing static offline data. But this method takes a long time and has low identification accuracy when detecting timing and frequency anomalies, since this method requires offline screening, classification and preprocessing of the collected data, which is very laborious. Anomaly detection with supervised learning requires a large amount of abnormal data and cannot detect unknown anomalies. So, this paper innovatively proposes the idea of applying Time-series Generative Adversarial Networks (Time-GAN) in a dispatching automation system for the identification, diagnosis and prediction of massive data flow anomalies. First of all, regarding the problem of insufficient abnormal data, we use Time-GAN to generate a large number of reliable datasets for training fault diagnosis models. In addition, Time-GAN can ameliorate the imbalance between various types of data. Secondly, unsupervised learning methods such as Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and K-means are used to detect unknown anomalies that may exist in the power grid. Finally, some supervised learning methods are selected to compare with unsupervised learning methods. Experimental results show that the proposed algorithm has a higher recognition rate of known anomalies than other benchmark algorithms and it can find new unknown anomalies. It lays a good foundation for the safe, stable, high-quality and economical operation of the power grid. Full article

Multicell constructed wetlands (MCWs) on lakeshores are a prospective treatment technique. However, the factors affecting the nutrient removal performance of lakeshore MCWs at the field scale are unclear. This study chose a field-scale lakeshore MCW with the highest mass removal efficiency (approximately 49,175.12 mg m⁻² day⁻¹) for total nitrogen removal in the wet season to investigate the response of nitrogen removal and microbial distribution to seasonal shock nutrients load. The mass loading rates in the wet season were as high as 43~72 times over those in the dry season. Hence, a storage pond (SP), as a forebay retention cell, was necessary to mitigate the shock loads of the influent, which is beneficial to nitrogen removal of the MCW system. The two major genera in the sediments are heterotrophic nitrification–aerobic denitrification bacteria, and the abundance and species of the nitrogen-related functional genera were higher in the wet season than the dry season. According to the results of redundancy analysis, the hydraulic residence time (29.4%, F = 2.2, p < 0.1) and hydraulic loading rate (85.9, F = 36.5, p < 0.05) were the major factors explaining microbial community variation, instead of environmental factors (temperature, pH, and dissolved oxygen). The shock loads of influent and the periodic saturation in sediments contributed to a complicated oxygen and nitrogen nutrient exchange environment resulting in higher abundance and species of nitrogen-related microbes, which is beneficial to nitrogen removal in lakeshore MCWs. The results provided a scientific basis for the optimal design of constructed wetlands on lakeshores. Full article

Lightweight service identification models are very important for resource-constrained distribution grid systems. To address the increasingly larger deep learning models, we provide a method for the lightweight identification of complex power services based on knowledge distillation and network pruning. Specifically, a pruning method based on Taylor expansion is first used to rank the importance of the parameters of the small-scale network and delete some of the parameters, compressing the model parameters and reducing the amount of operation and complexity. Then, knowledge distillation is used to migrate the knowledge from the large-scale network ResNet50 to the small-scale network so that the small-scale network can fit the soft-label information output from the large-scale neural network through the loss function to complete the knowledge migration of the large-scale neural network. Experimental results show that this method can compress the model size of the small network and improve the recognition accuracy. Compared with the original small network, the model accuracy is improved by 2.24 percentage points to 97.24%. The number of model parameters is compressed by 81.9% and the number of floating-point operations is compressed by 92.1%, making it more suitable for deployment in resource-constrained devices. Full article