Processes, Volume 12, Issue 4 (April 2024) – 219 articles

In response to the challenges of global warming and the development of A low-carbon economy, the integrated electricity and natural gas energy system (IEGES) is known as an important structure for future energy supply; thus, its planning and design must take low-carbon and environmental protection factors into account. Regarding carbon emissions as an optimization criterion, this paper built life-cycle carbon emission models of IEGES components. Then, taking the capacities of the energy resources, storage and conversion units of IEGES as the optimization variables, a multi-objective optimization configuration model was established considering the annual investment operation cost and the life-cycle carbon emissions. The multi-objective model was transformed into a single-objective one by an ε-constraint approach and the polynomial fitting method was employed to obtain the value of ε for obtaining uniformly distributed Pareto sets. Based on the fuzzy entropy weight method and the fuzzy affiliation degree approach, the obtained Pareto sets were ranked and the solution with the highest ranking value was selected as the optimal solution for the original problem. Finally, the configuration schemes were analyzed from the perspectives of economy, carbon emission and renewable energy utilization, and the effectiveness and rationality of the proposed optimization method were verified through MATLAB simulation. Full article

Polyethylene terephthalate (PET) microplastics constitute a significant portion of plastic pollution in the environment and pose substantial environmental challenges. In this study, the effectiveness of the Fenton process and post-oxidation coagulation for the removal of non-weathered and UV-weathered PET microplastics (PET MPs) were investigated. A response surface methodology was used to investigate the interplay between PET concentration and ferrous ion (Fe²⁺) concentration. The models revealed an intricate interplay between these variables, highlighting the need for a balanced system for optimal PET MP removal. For non-weathered PET, the simultaneous increase in the concentrations of both PET microplastics and Fe²⁺ was found to enhance the removal efficiency. However, this synergistic effect was not observed in UV-weathered PET, which also demonstrated a more pronounced effect from the Fe²⁺ concentration. The statistical analysis provided a strong basis for the validity of the models. X-ray photoemission spectroscopy (XPS) further elucidated the mechanisms behind these findings, revealing that UV weathering results in surface changes, which facilitate hydroxyl radical oxidation. These findings underline the complexity of the Fenton process in PET microplastic removal and the different behavior of non-weathered and UV-weathered microplastics. This has significant implications for tailoring remediation strategies and underscores the importance of considering environmental weathering in these strategies. Full article

Atomic Force Microscopy (AFM) nanoindentation is a powerful technique for determining the mechanical properties of soft samples at the nanoscale. The Hertz model is typically used for data processing when employing spherical indenters for small indentation depths (h) compared to the radius of the tip (R). When dealing with larger indentation depths, Sneddon’s equations can be used instead. In such cases, the fitting procedure becomes more intricate. Nevertheless, as the h/R ratio increases, the force–indentation curves tend to become linear. In this paper the potential of using the linear segment of the curve (for h > R) to determine Young’s modulus is explored. Force–indentation data from mouse and human lung tissues were utilized, and Young’s modulus was calculated using both conventional and linear approximation methods. The linear approximation proved to be accurate in all cases. Gaussian functions were applied to the results obtained from both classic Sneddon’s equations and the simplified approach, resulting in identical distribution means. Moreover, the simplified approach was notably unaffected by contact point determination. The linear segment of the force–indentation curve in deep spherical indentations can accurately determine the Young’s modulus of soft materials at the nanoscale. Full article

Using slow-release fertilizer is one of the sustainable strategies to improve the effectiveness of fertilizers and mitigate the environmental pollution caused by excess usage of fertilizer. In this study, a slow-release urea fertilizer with water retention and photosensitivity properties was prepared by a two-step method. It was characterized by Fourier transform infrared spectroscopy, thermogravimetric analysis, scanning electron microscopy and an infrared camera. This fertilizer can prolong the release period of urea, improve water-retention capacity of soil, and carry out photothermal conversion under illumination. Comparing four release kinetics models, the Ritger–Peppas model was the best fitting model for releasing behavior in soil, and diffusion followed the Fickian mechanism. The application of fertilizer on winter wheat was carried out to intuitively evaluate the fertilizer’s effects on promoting plant growth and resisting water stress. Thus, this study provides a new strategy for improving fertilizer utilization rate and maintaining soil moisture, which will be beneficial for sustainable agriculture. Full article

To characterize the failure of rock mass surrounding underground tunnels, biaxial compression tests were conducted on a real sandstone model with a straight-walled arched hole. The acoustic emission (AE) system and digital image correlation (DIC) optical inspection equipment were used to investigate the crack evolution process and failure precursors of the tunnel. A two-dimensional particle flow code (PFC2D) was used to conduct numerical simulations on the sample, so as to investigate the mesoscopic failure mechanism of rock mass. The results show that the failure of the single tunnel constructed in sandstone occurs mainly in the walls on both sides (between the spandrels and arch feet), showing slabbing failure characteristics and a certain abruptness. The crack initiation in sandstone in early stage is not obvious, and the crack propagation in rock mass is rapid when acoustic emissions are enhanced. The small increments in the AE count and amplitude and the continuous reduction in the b-value can be used as precursors for the failure of rock mass. When the height–span ratio is 0.8 and 1.0, the stress distribution around the chamber is more uniform, and when the height–span ratio is greater than 1.0, the stress is mainly concentrated in the vault and arch bottom. In the PFC simulations, tensile fractures firstly initiate in the middle of walls and at the arch feet, arcuate fracture concentration zones are then formed, in which shear fractures appear and a few particles spall from the surfaces. When approaching the ultimate bearing capacity, rock masses on both sides of the tunnel are fractured over large areas, and the slender coalesced fractured zone develops to the deep part of rock mass, causing failure of the sample. Full article

As the proportion of renewable energy installations in modern power systems increases, major weather events can easily trigger significant fluctuations in new energy generation and electricity load, presenting the system with the dual challenges of ensuring power supply and renewable energy consumption. Traditional dispatch models need more coordination and optimization of flexible resources under major weather events and risk management of system operations. This study focuses on provincial-level transmission systems, aiming to achieve the coordinated and optimized dispatch of flexible resources across multiple time scales in response to the complex and variable environments faced by the system. Firstly, by profoundly analyzing the response mechanisms of power systems during major weather events, this study innovatively proposes an event-driven day-ahead and intra-day optimal dispatch strategy for power systems. This strategy can sense and respond to major weather events in the day-ahead phase and adjust dispatch decisions in real time during the intra-day phase, thereby comprehensively enhancing the adaptability of power systems to sudden weather changes. Secondly, by considering the variability of renewable energy sources and electricity demand in the day-ahead and intra-day dispatch plans, the strategy ensures efficient and reliable power system operation under normal and major weather event scenarios. Finally, the method’s effectiveness is validated using actual data from a provincial-level power grid in China. The proposed dispatch strategy enhances the resilience and adaptability of power systems to major weather events, which are becoming increasingly frequent and severe due to climate change. The research demonstrates that an event-driven day-ahead and intra-day optimal dispatch strategy can enhance the economic efficiency and robustness of power system operations through the coordinated dispatch of flexible resources during major weather events, thereby supporting the transition toward sustainable energy systems that are resilient against the challenges of a changing climate. Full article

It is of great significance to investigate the flow rate and stress distribution of multi-fracture propagation for the optimization of perforation parameters and fracture parameters. Considering the coupling of rock deformation, fracture direction and fluid flow in multi-fracture scenarios, a mathematical model and solution program for the flow and stress distribution of multiple fractures are established, and the analytical model is used for comparison and verification. The effects of perforation cluster number, cluster spacing, perforation diameter on fracture extension trajectory, fracture width, flow rate of each fracture and stress field are studied by the model. The results show that, as the number of perforating clusters increases, the inner fracture is inhibited more severely with less width, length and flow distribution, as well as lower bottom hole pressure. With the increase in cluster spacing, the stress interference between whole fractures is weakened and the flow distribution of the inner fracture is increased with lower bottom hole pressure. With the decrease in perforation diameter, the inhibition effect of inside fractures is weakened, while the inhibition effect of outside fractures, the flow distribution of inside fractures and the bottom hole pressure are increased. The uniform propagation of multiple fractures can be promoted by decreasing the perforation clusters’ number and perforation diameter or increasing fracture spacing. Full article

Pump-turbines experience complex flow phenomena and fluid–structure interactions during transient operations, which can significantly impact their stability and performance. This paper presents a comprehensive field test study of the pump mode startup process for a 150 MW prototype pump-turbine. By analyzing pressure fluctuations, structural vibrations, and their short-time Fourier transform (STFT) results, multiple stages were identified, each exhibiting distinct characteristics. These characteristics were influenced by factors such as runner rotation, free surface sloshing in the draft tube, and rotor–stator interactions. The natural frequencies of the metallic components varied during the speed-up and water-filling stages, potentially due to gyroscopic effects or stress-stiffening phenomena. The opening of the guide vanes and dewatering valve inside the guide vanes significantly altered the amplitude of the rotor–stator interaction frequency, transitioning the vibration behavior from forced to self-excited regimes. Interestingly, the draft tube pressure fluctuations exhibited sloshing frequencies that deviated from existing prediction methods. The substantial phenomena observed in this study can help researchers in the field to deepen the understanding of the complex behavior of pump-turbines during transient operations and identify more meaningful research directions. Full article

The primary function of a mine hoist is the transportation of personnel and equipment, serving as a crucial link between underground and surface systems. The proper functioning of key components such as work braking and safety braking is essential for ensuring the safety of both personnel and equipment, thereby playing a critical role in the safe operation of coal mines. As coal mining operations extend to greater depths, they introduce heightened challenges for safe transportation, compounded by increased equipment loss. Consequently, there is a pressing need to enhance safety protocols to safeguard personnel and materials. Traditional maintenance and repair methods, characterized by routine equipment inspections and scheduled downtime, often fall short in addressing emerging issues promptly, leading to production delays and heightened risks for maintenance personnel. This underscores the necessity of adopting predictive maintenance strategies, leveraging digital twin models to anticipate and prevent potential faults in mine hoists. In summary, the implementation of predictive maintenance techniques grounded in digital twin technology represents a proactive and scientifically rigorous approach to ensuring the continued safe operation of mine hoists amidst the evolving challenges of deepening coal mining operations. In this study, we propose the integration of a CNN-LSTM algorithm within a digital twin framework for predicting faults in mine hoist braking systems. Utilizing software such as AMESim 2019 and MATLAB 2016b, we conduct joint simulations of the hoist braking digital twin system. Subsequently, leveraging the simulation model, we establish a fault diagnosis platform for the hoist braking system. Finally, employing the CNN-LSTM network model, we forecast failures in the mine hoist braking system. Experimental findings demonstrate the effectiveness of our proposed algorithm, achieving a prediction accuracy of 95.35%. Comparative analysis against alternative algorithms confirms the superior performance of our approach. Full article

The Pressure Swing Adsorption (PSA) technique is a widely embraced automated method for gas separation within the industrial sector, prized for its operational simplicity and substantial economic benefits. In practice, the process typically involves the use of multiple towers to facilitate the completion of the PSA cycle. However, with the increasing number of towers in a PSA system, the intricacies of the cyclic process tend to amplify, posing challenges for novices attempting to grasp the mechanics of a six-tower PSA cycle. Utilizing animation can facilitate the process of comprehending these complex techniques by presenting them in a simplified and visually engaging format. Therefore, our research group has designed an animated depiction of a six-tower PSA device, predicated on the prototype established in our laboratory. This animation furnishes an inclusive demonstration of a complete cycle, encompassing twelve steps, pertaining to the operation of a six-tower PSA. It is our aspiration that this tool will prove advantageous for those who are embarking on the journey of understanding multi-tower PSA, as well as for seasoned professionals engaged in the field of pressure swing adsorption. Full article

In order to reduce the failure accidents caused by the insufficient strength of fracturing string joints, theoretical calculation and string design methods were adopted to conduct finite element calculations on commonly used long circular threads. The distribution laws of stress and contact pressure of long round threads were obtained, a non-standard special thread was designed, and a finite element model of the joint of the casing was established. Considering different make-up torques, tensile loads, and tensile torque loads within a certain range, the stress variation law of the special casing threaded joint under this design size was analyzed. Finally, the stress and contact pressure variation law on the threaded tooth was analyzed under different structures, working conditions, and wall thickness parameters. The thread strength and sealing function were compared under various parameters. The results showed that the smaller the wall thickness of the joints, the greater the contact pressure at the threaded tooth. Among them, the contact pressure of the external threaded tooth is too high, and is prone to the sticking phenomenon. The distribution of contact pressure in the middle section is relatively reasonable. Compared with the original structure, the new structure significantly reduces the contact pressure at the head and tail ends of the threaded connection, reducing the risk of sticking. Full article

Media thermal conductivity is important in various heat-transfer processes. Many conventional fluid conductors suffered low conductivity and environmental issues. Therefore, research was active in finding out alternative systems, mostly relying on aqueous liquids that are low-cost and ecofriendly. After the emergence of carbon nanotubes (CNTs), with their many special structural, electrical and thermal properties, they have been examined for many applications, including heat-transfer processes. Adding CNTs to water yields CNT aqueous nanofluids that have been widely investigated as heat-transfer media. The literature shows that CNT addition improves water thermal conductivity and other water properties, such as viscosity, surface tension, freezing point and boiling point. The literature also shows that nanofluid thermal conductivity improvement is affected by CNT type and concentration, in addition to other factors such as surfactant addition. All these subjects were widely described in literature, focusing on experimental, modelling and theoretical accounts. Despite the wide literature, there exist inconsistencies and discrepancies between reports that need to be justified. In addition to technical papers, many reviews were published on various aspects of the subject including experimental results and mathematical modeling. However, the very basic question here is as follows: Why does adding CNT to water affect its thermal conductivity? In spite of the wide published literature, this issue was not targeted in a simple qualitative approach. This review provides a clear understanding of how CNTs improve thermal conductivity of aqueous nanofluids. A qualitative model is presented to explain mechanisms behind improvement as presented in the literature. CNT type effects are discussed with other factors such as aspect ratio, Reynold number, dispersion quality, composition, temperature and additives. CNT functionalization is described. Relations to estimate nanofluid thermal conductivity are discussed. The model will help specialists to tailor CNT aqueous nanofluid characteristics as desired by varying types and concentrations of CNT and surfactant, and other factors. Full article

Phytoremediation, an ecological approach aimed at addressing polymetal(loid)lic-contaminated mining soils, has encountered adaptability challenges. Dominant plant species, well-suited to the local conditions, have emerged as promising candidates for this purpose. This study focused on assessing the phytoremediation potential of ten plant species that thrived in heavy metal(loid)-contaminated mining soils. This investigation covered nine heavy metal(loid)s (As, Cu, Cd, Cr, Hg, Ni, Pb, Sn, and Zn) in both plants and rhizosphere soils. The results revealed a significant impact of mining activities, with heavy metal(loid) concentrations surpassing the Yunnan Province’s background levels by 1.06 to 362 times, highlighting a significant concern for remediation. The average levels of the heavy metal(loid)s followed the order of As (3.98 × 10³ mg kg⁻¹) > Cu (2.83 × 10³ mg kg⁻¹) > Zn (815 mg kg⁻¹) > Sn (176 mg kg⁻¹) > Pb (169 mg kg⁻¹) > Cr (68.1 mg kg⁻¹) > Ni (36.2 mg kg⁻¹) > Cd (0.120 mg kg⁻¹) > Hg (0.0390 mg kg⁻¹). The bioconcentration factors (BCFs), bioaccumulation factors (BAFs), and translocation factors (TFs) varied among the native plants, indicating diverse adaptation strategies. Low BCFs and BAFs (ranging from 0.0183 to 0.418 and 0.0114 to 0.556, respectively) suggested a low bioavailability of heavy metal(loid)s. Among the species, both J. effusus and P. capitata showed remarkable abilities for As accumulation, while A. adenophora demonstrated a notable accumulation ability for various heavy metal(loid)s, especially Cd, with relatively high BCFs (1.88) and BAFs (3.11), and the TF at 1.66 further underscored the crucial role of translocation in preventing root toxicity. These findings emphasized the potential of these plant species in mine ecological restoration and phytoremediation, guiding targeted environmental rehabilitation strategies. Full article

Waste biogenic materials derived from seafood exploitation represent valuable resources of new compounds within the blue bioeconomy concept. Here, we describe the effectiveness of Raman technology implementation as an in-line tool for the demineralization process control of crustaceans or gastropods. Transparent chitin polymeric foils and calcium acetate by-products were obtained from three waste crustacean shells (C. sapidus, S. mantis, and M. squinado) using a slow, green chemical approach employing acetic acid. Progressive mineral dissolution and increasing of the Raman characteristic signal of chitin is shown in a time-dependent manner using NIR-Raman spectroscopy, while resonance Raman shows intact carotenoids in reacted shells after 2 weeks. Chitin foil products are species-specific, and the demineralization bath of the waste shell mixture can be effectively tracked by Raman tools for solvent control and decision making for the recovery of calcium acetate by-products. Comparatively obtained calcium acetate from Rapana venosa snail shells, the subject of Raman analyses, allowed assessing by-product identity, hydration status, purity, and suitability as recrystallized material for further use as a pharmaceutical compound derived from different crustaceans or gastropod species. Cross validation of the results was done using FT-IR, XRD, and SEM-EDX techniques. A hand-held flexible TacticID Raman system with 1064 nm excitation demonstrated its effectiveness as a rapid, in-line decision making tool during process control and revealed excellent reproducibility of the lab-based instrument signal, suitable for in situ evaluation of the demineralization status and solvent saturation control. Full article

Autostrainer is used for the purpose of debris removal in order to increase the efficiency of the heat exchanger by taking the required raw water as a heat source for the pre-cooling hydrothermal system. During the operation of the autostrainer, a pressure drop occurs due to the blockage of the screen in the autostrainer. As a result, the resistance of the pipe network for the intake system is changed, and the operating efficiency point of the pump, valve, heat exchanger, etc., is altered. By calculating the system resistance taking into account the pressure drop caused by the blockage rate of the screen in the autostrainer, the optimum operating efficiency can be expected when the intake system such as a pump, valve or heat exchanger, etc. is constructed. In this study, Computational Fluid Dynamics (CFD) was used to construct a scenario in which screen blockage may occur, predicting pressure drop for the slot cross-section of the screen in the autostrainer to derive a resistance coefficient value. The resistance coefficient value was applied to the porous region corresponding to the screen in the autostrainer’s 3D shape and compared with the experimental value for the pressure drop and headloss coefficient. By predicting the pressure drop for the autostrainer’s screen blockage rate of 0% to 50%, the coefficient of headloss required for the design of the intake system was calculated. Additionally, in order to predict the debris removal rate, which is the original role of the autostrainer, the debris was assumed to be particles, and sedimentation rate was predicted according to the size and weight of the particles. Building on this, when introducing the autostrainer used in pre-cooling into the membrane filtration process, due to the pressure loss caused by the inflow of debris during the use of the autostrainer, this study aims to utilize Computational Fluid Dynamics (CFD) to derive the head loss coefficients according to the screen blockage rate, and use these coefficients to calculate the system’s resistance curve. Additionally, in this study, the term “autostrainer” is used instead of the term “membrane strainer” to align with more popular terminology. Full article

Hot air-assisted radio frequency (HARF) is considered a rapid heating process. In order to improve the circular economy of agricultural byproducts, this study used different proportions of HARF stabilized rice bran (R) from milling rice, HARF dried ginseng residue (G) from ultrasonic extraction, and peanut residue (P) from HARF roasting and oil extraction as the Hericium erinaceus solid-state fermented media. Then, the whitening effects of water extracts from media and fermented products were analyzed. First, the surface temperature of 1 kg rice bran exceeded 90 °C after 3 min of 5 kW HARF heating, effectively deactivating lipase. The combinations of 1 kg of rice bran with 0.5, 1, 1.5, and 2 kg of ginseng residue (85% moisture content) were dried using 5 kW HARF. Each of the drying rates was about 27 g/min, and the drying periods were 14, 30, 46, and 62 min, respectively, which were used to reduce the moisture content below 10%. Compared to traditional air drying for ginseng residue, HARF drying may save up to 96% of time and 91% of energy consumption. Then, the ratio of dried R, G, and P was 4:1:1, mixed with 45% moisture as solid-state media for Hericium erinaceus and 5 weeks of cultivation at 25 °C. In comparison to the control group, the water extracts at 100 µg/mL from media R4G1, R4G1P1, and fermented HER4G1P1 products exhibited tyrosinase inhibition of 29.7%, 52.4%, and 50.7%, respectively. These extracts also reduced the relative melanin area of 78 hpf zebrafish embryos by 21.57%, 40.20%, and 58.03%, respectively. Therefore, HARF can quickly dry agricultural byproducts as media for Hericium erinaceus solid-state fermentation while also providing a significant whitening effect for cosmetic applications. Full article

“Aging” is a practice that allows alcoholic beverages to mature and gives them particular flavors and colors. In this context, oak or durmast wooden barrels are used in this process, thus providing different types of aging. This conventional process produces a slow enrichment of organic compounds in the spirit inside the barrels. Organic substances present in the internal part of the barrels slowly undergo the phenomenon of extraction by the liquid phase (solid–liquid extraction). In this work, a new procedure based on rapid solid–liquid dynamic extraction (RSLDE) was used to evaluate the potential of obtaining the effects of aging in spirits in shorter times than conventional methods. For this purpose, a comparison between two solid–liquid extraction techniques, RSLDE and conventional maceration, was made. Four water/ethanol 60:40 (v/v) model solutions were prepared and put in contact with medium-toasted chips using the two extraction procedures (conventional and non-conventional) and determining dry residue and total polyphenol content. Reversed phase high-performance liquid chromatography (RP-HPLC) analyses allowed the identification and quantification of furfural, ellagic acid and phenolic aldehydes (vanillin, syringaldehyde, coniferaldehyde and sinapaldehyde). The aging procedure with medium-toasted chips was tested on a young commercial grappa using maceration and RLSDE. Full article

The seepage effect of rock and soil in the process of encountering water follows a nonlinear coupling law between water and rock. According to the permeability of rock and soil during softening with water, changes in particles in rock and soil are related to permeability mechanisms. Based on the assumption of connection between particles in rock and soil, changes in particles before and after water infiltration, the mechanism of water–rock interaction, and the damage to rock and soil are analyzed herein. Combined with fractal theory and percolation theory, the random failure characteristics and nonlinear behavior of water in rock and soil are studied. At the same time, with the help of Fluent 17.0 software, the seepage process of rock samples in water is numerically simulated and analyzed. Taking the permeability coefficient of rock samples, the mass flow rate of water, and the internal pore water pressure of rock samples as tracking objects, it is found that there are obvious nonlinear characteristics in the process of water–rock interaction. The seepage–stress coupling between water and rock forms negative resistance to water seepage. The water infiltration is a slow and then accelerated process and tends to be stable. Research has shown that the coupling effect of seepage between water and rock increases the damage inside the rock and soil, and its permeability fluctuates randomly at different time steps. This feature is a common manifestation of fractal properties and percolation within rock and soil particles. At the same time, there is a non-equilibrium variation law of pore water pressure inside the rock and soil. This leads to a continuous strengthening of the seepage effect, reaching a stable state. The results of this study are crucial. It not only reveals the mechanism of interaction between water and rock but also correlates the degree of internal damage in rock and soil based on the seepage characteristics between water and rock. The conclusions can provide some reference value for relevant construction methods in the analysis of the formation of water flow characteristics, the prevention of rock slope seepage disasters, and the control of water inrush in tunnel excavation. Full article

This study evaluated the changes in microbial activity in the course of time following the joint application of the herbicides S-metolachlor, foramsulfuron, and thiencarbazone-methyl to two soils (S1 and S2) under conventional tillage (CT) and non-tillage (NT) management in field conditions. The biochemical parameters of soil respiration (RES), dehydrogenase activity (DHA), microbial biomass (BIO), and the phospholipid fatty acid (PLFA) profile were determined at 1, 34, and 153 days during herbicide dissipation. In the absence of herbicides, all microbial activity was higher under NT than CT conditions, with higher or similar mean values for S1 compared to S2. A continuous decrease was detected for RES, while DHA and BIO recovered over time. In the presence of herbicides, a greater decrease in all microbial activity was detected, although the changes followed a similar trend to the one recorded without herbicides. In general, a greater decrease was observed in S1 than in S2, possibly due to the higher adsorption and/or lower bioavailability of herbicides in this soil with a higher organic carbon content. The decrease was also greater under CT conditions than under NT conditions because the herbicides can be intercepted by the mulch, with less reaching the soil. These changes involved evolution of the structure of the microbial community. Full article

The dynamic model of cavitation bubbles serves as the foundation for the study of all cavitation phenomena. Solving the cavitation bubble dynamics equation can better elucidate the physical principles of bubble dynamics, assisting with the design of hydraulic machinery and fluid control. This paper employs a fourth-order explicit Runge–Kutta numerical method to solve the translational Keller–Miksis model for cavitation bubbles. It analyzes the collapse time, velocity, as well as the motion and force characteristics of bubbles under different wall distances γ values. The results indicate that as the distance between the cavitation bubble and the wall decreases, the cavitation bubble collapse time increases, the displacement of the center of mass and the amplitude of translational velocity of the cavitation bubble increase, and the minimum radius of the cavitation bubble gradually decreases linearly. During the stage when the cavitation bubble collapses to its minimum radius, the Bjerknes force and resistance experienced by the bubble also increase as the distance to the wall decreases. Especially in the cases where γ = 1.3 and 1.5, during the rebound stage of the bubble, the Bjerknes force and resistance increase, causing the bubble to move away from the wall. Meanwhile, this study proposes a radiation pressure coefficient to characterize the radial vibration behavior of cavitation bubbles when analyzing the radiation sound pressure. It is found that the wall distance has a relatively minor effect on the radiation pressure coefficient, providing an important basis for future research on the effects of different scale bubbles and multiple bubbles. The overall idea of this paper is to numerically solve the bubble dynamics equation, explore the characteristics of bubble dynamics, and elucidate the specific manifestations of physical quantities that affect bubble motion. This provides theoretical references for further engineering applications and flow analysis. Full article

The complexity and heterogeneity of pore structures in carbonate reservoirs pose significant challenges for accurately characterizing the influence of different pore micro-parameters on reservoir physical properties. Drawing upon the principles of fractal geometry theory applied to reservoir rocks, this study combines mercury intrusion porosimetry (MIP) and nuclear magnetic resonance (NMR) T₂ spectrum methods to explore the relationship between the fractal dimension and micro-parameters of pore throats at various scales. Additionally, it clarifies how the fractal dimension of pores at different scales impacts reservoir physical properties. Moreover, a permeability prediction model that incorporates fractal dimensions is developed. The findings demonstrate that the fractal dimension effectively captures the complexity and multi-scale nature of reservoir microstructures, leading to higher reliability in predicting permeability when using the model incorporating the fractal dimension. It provides a theoretical basis for predicting the absolute permeability of fractured carbonate rocks in dual media. Full article

With the introduction of numerous technologies and equipment, the volume of data in smart substations has undergone exponential growth. In order to enhance the intelligent management level of substations and promote their efficient and sustainable development, the one-key sequential control system of smart substations is being renovated. In this study, firstly, the intelligent substation is defined and compared with the traditional substation. The one-key sequential control system is introduced, and the main issues existing in the system are analyzed. Secondly, experiments are conducted on the winding temperature, insulation oil temperature, and ambient temperature of power transformers in the primary equipment. Combining data fusion technology and transformer neural network models, a Power Transformer-Transformer Neural Network (PT-TNNet) model based on data fusion is proposed. Subsequently, comparative experiments are conducted with multiple algorithms to validate the high accuracy, precision, recall, and F1 score of the PT-TNNet model for equipment state monitoring and fault diagnosis. Finally, using the efficient PT-TNNet, Random Forest, and Extra Trees models, the cross-validation of the accuracy of winding temperature and insulation oil temperature of transformers is performed, confirming the superiority of the PT-TNNet model based on transformer neural networks for power transformer state monitoring and fault diagnosis, its feasibility for application in one-key sequential control systems, and the optimization of one-key sequential control system performance. Full article

In the case of strong non-Gaussian noise in the measurement information of the distribution network, the strong non-Gaussian noise significantly interferes with the filtering accuracy of the state estimation model based on deep learning. To address this issue, this paper proposes an enhanced kernel ridge regression state estimation method based on ensemble empirical mode decomposition. Initially, ensemble empirical mode decomposition is employed to eliminate most of the noise data in the measurement information, ensuring the reliability of the data for subsequent filtering. Subsequently, the enhanced kernel ridge regression state estimation model is constructed to establish the mapping relationship between the measured data and the estimation residuals. By inputting the measured data, both estimation results and estimation residuals can be obtained. Finally, numerical simulations conducted on the standard IEEE-33 node system and a 78-node system in a specific city demonstrate that the proposed method exhibits high accuracy and robustness in the presence of strong non-Gaussian noise interference. Full article

Fractured-vuggy reservoirs are crucial for increasing unconventional oil storage and production, but the controlling mechanism of this dominant flow channel remains vague, and the jamming mechanism of modulator particles is unclear. This study explores the filling and jamming processes of particles in the fractures by conducting a computational fluid dynamics−discrete element method (CFD−DEM) coupled simulation, considering the variation of fracture width, fluid velocity, particle size, and concentration. Results suggest that four sealing modes are proposed: normal filling, local jamming, complete sealing, and sealing in the main fracture. The ratio of particle size to the main fracture width exerts the primary role, with the ratio having a range of 0.625 < D/W ≤ 0.77 revealing complete jamming. Furthermore, an optimal particle size for achieving stable sealing is observed when the particle size varies from 2 to 2.5 mm. A higher concentration of particles yields better results in the fracture-shrinking model. Conversely, a greater velocity worsens the sealing effect on fractures. This research can offer technical support for the large-scale dissemination of flow regulation technology. Full article

The paper shows the expediency of supplementing the balance simplex method by calculating the number of free variables of separation flowsheets containing recycle flows. The need to determine and set the free variables that provide lower energy consumption when calculating the material balance of flowsheets with recycling is justified. The problem of material balance multivariance is illustrated, and ways to solve it are shown with the example of separation flowsheets for two ternary mixtures: n-butanol + water + toluene and n-butanol + butyl acetate + water. Separation flowsheets containing three distillation columns and a liquid–liquid separator are proposed for both systems. The dependence of the recycle flow values and the energy consumption of distillation columns and separation flowsheets on the selection and setting of values of free variables in solving the balance problem is shown. The dependence of energy consumption on the composition of the original mixture is studied for an n-butanol + butyl acetate + water system. Recommendations for setting free variables for flowsheets of the separation of ternary mixtures with three binary (and one ternary) azeotropes are formulated. The technique of highlighting the region of separation flowsheet operability is illustrated. The column operating parameters that ensure the production of products of a given quality with minimal energy consumption are determined. It is shown that with the incorrect selection and setting of variables (during balance task solvation), the energy consumption for mixture separation can be overestimated by more than 40%. Full article

The research on the deep coalbed methane (CBM) in the Ordos Basin is mostly concentrated on the eastern margin of the basin. The geological resources of the Benxi Formation in the Yulin area, located in the central-eastern part, cover 15,000 × 10⁸ m³, indicating enormous resource potential. However, the characteristics of the reservoir distribution and the favorable areas are not yet clear. This research comprehensively performed data logging, coal rock experiments, and core observations to identify the geological characteristics of the #8 coal seam, using a multi-level fuzzy mathematics method to evaluate the favorable area. The results indicate the following: (1) The thickness of the #8 coal in the Yulin Block ranges from 2.20 m to 11.37 m, with depths of between 2285.72 m and 3282.98 m, and it is mainly underlain by mudstone; the gas content ranges from 9.74 m³/t to 23.38 m³/t, showing a northwest–low and southeast–high trend. The overall area contains low-permeability reservoirs, with a prevalence of primary structural coal. (2) A multi-level evaluation system for deep CBM was established, dividing the Yulin Block into three types of favorable areas. This block features a wide range of Type I favorable areas, concentrated in the central-eastern, northern, and southwestern parts; Type II areas are closely distributed around the edges of Type I areas. The subsequent development process should prioritize the central-eastern part of the study area. The evaluation system established provides a reference for selecting favorable areas for deep CBM and offers theoretical guidance for targeted exploration and development in the Yulin area. Full article

Traditional batch ethanol fermentation poses the problems of poor production and economic viability because the lag and stationary phase always demand considerable fermentation time; plus, downtime between batches is requested to harvest, clean, and sterilize, decreasing the overall productivity and increasing labor cost. To promote productivity and prolong the production period, avoid process instability, and assure a substantial production of ethanol and a minimal quantity of residual substrate, this paper proposed a nonlinear adaptive control which can realize global stabilizing control of the process starting from batch mode to achieve batch/washout avoidance. Due to the dynamic nature and complexity of the process, novel estimation and control schemes are designed and tested on an ethanol fermentation model. These schemes are global stabilizing control laws including adaptive control to avoid input saturation, nonlinear estimation of the unknown influential concentration through a higher-order sliding mode observer, and state observers and parameter estimators used to estimate the unknown states and kinetics. Since the temperature is an important factor for an efficient operation of the process, a split ranging control framework is also developed. To verify the process performance improvement by continuous fermentation, tests performed via numerical simulations under realistic conditions are presented. Full article

This research introduces a new data-driven methodology for fault detection and isolation in dynamic systems, integrating fuzzy/Bayesian change point detection and decision trees induced by genetic programming for pattern classification. Tracking changes in sensor signals enables the detection of faults, and using decision trees generated by genetic programming allows for accurate categorization into specific fault classes. Change point detection utilizes a combination of fuzzy set theory and the Metropolis–Hastings algorithm. The primary contribution of the study lies in the development of a distinctive classification system, which results in a comprehensive and highly effective approach to fault detection and isolation. Validation is carried out using the Tennessee Eastman benchmark process as an experimental framework, ensuring a rigorous evaluation of the efficacy of the proposed methodology. Full article

The pyrolysis of three different biomasses, rice husk (RH), zoita wood sawdust (ZW) and pine wood sawdust (PW), was studied at 500 °C in a multipurpose unit at the bench scale to determine the yields of the different products and the compositions and properties of the liquid products, with particular emphasis given to the alquitranous fractions (tars). It was possible to link the characteristics of the tars with the compositions of the raw biomasses and verify their potential in various applications. The analytical techniques employed in the characterization of biomasses included lignin, celulose and hemicellulose analysis, ultimate and proximate analysis and thermogravimetry–mass spectrometry analysis (TG-MS). Elemental analysis, gas chromatography–mass spectrometry (GC-MS), nuclear magnetic resonance spectroscopy (¹H NMR), Fourier transform infrared spectroscopy (FTIR) and size exclusion chromatography (SEC) were used to characterize the tars. The tar yields were 1.8, 7.4 and 4.0 %wt. in the cases of RH, ZW and PW, respectively. The tars showed higher carbon content, between 60.3 and 62.2 %wt., and lower oxygen content, between 28.8 and 31.6 %wt., than the corresponding raw biomasses. The main components of the tars had aromatic bases, with phenols representing more than 50%. Tar RH included more guaiacols, while Tars ZW and PW included more phenols and alkylated phenols. Full article

The power battery constitutes the fundamental component of new energy vehicles. Rapid and accurate fault diagnosis of power batteries can effectively improve the safety and power performance of the vehicle. In response to the issues of limited generalization ability and suboptimal diagnostic accuracy observed in traditional power battery fault diagnosis models, this study proposes a fault diagnosis method utilizing a Convolutional Block Attention Capsule Network (CBAM-CapsNet) based on a stacked sparse autoencoder (SSAE). The reconstructed dataset is initially input into the SSAE model. Layer-by-layer greedy learning using unsupervised learning is employed, combining unsupervised learning methods with parameter updating and local fine-tuning to enhance visualization capabilities. The CBAM is then integrated into the CapsNet, which not only mitigates the effect of noise on the SSAE but also improves the model’s ability to characterize power cell features, completing the fault diagnosis process. The experimental comparison results show that the proposed method can diagnose power battery failure modes with an accuracy of 96.86%, and various evaluation indexes are superior to CNN, CapsNet, CBAM-CapsNet, and other neural networks at accurately identifying fault types with higher diagnostic accuracy and robustness. Full article