Processes, Volume 12, Issue 2 (February 2024) – 185 articles

The thermal characteristics of the spindle system for CNC machine tools are influenced by multiple factors which are nonlinear and time-varying. In this paper, a nonlinear time-varying thermal characteristics solving model for the spindle system was established based on the numerical solution method. Through theoretical deduction and data fitting, mathematical models of nonlinear time-varying factors including the friction torque generated by lubricants, convective heat transfer coefficient, and coolant and ambient temperature are constructed. The temperature and displacement of the spindle system at each time step are solved by considering the comprehensive effect of multiple nonlinear time-varying factors. And the actual temperature and axial deformation data of the spindle system are obtained through thermal characteristics detection experiments. By comparing solution results affected by multiple nonlinear time-varying factors and by non time-varying factors with experimental data, it can be concluded that the nonlinear time-varying thermal characteristics model has advantages in reflecting the trend of numerical changes and the accuracy of result solving over a method considering non time-varying factors and the solution values of temperature affected by multiple nonlinear time-varying factors are almost consistent with detection values and the relative errors are all within ±3%. The relative error of axial deformation between the value solved by the model and the detection value is close to −1%. This conclusion demonstrates the rationality and accuracy of the thermal characteristics solving model and the construction of nonlinear time-varying factors. This study is of great significance for exploring the thermal characteristics of the spindle system and improving CNC machine tool performance in depth. Full article

Aiming at the problem that the energy consumption of the boiler system varies greatly under the flexible peaking requirements of coal-fired units, an energy consumption prediction model for the boiler system is established based on a Least-Squares Support Vector Machine (LSSVM). First, the Mean Impact Value (MIV) algorithm is used to simplify the input characteristics of the model and determine the key operating parameters that affect energy consumption. Secondly, the Snow Ablation Optimizer (SAO) with tent map, adaptive t-distribution, and the opposites learning mechanism is introduced to determine the parameters in the prediction model. On this basis, based on the operation data of an ultra-supercritical coal-fired unit in Xinjiang, China, the boiler energy consumption dataset under variable load is established based on the theory of fuel specific consumption. The proposed prediction model is used to predict and analyze the boiler energy consumption, and a comparison is made with other common prediction methods. The results show that compared with the LSSVM, BP, and ELM prediction models, the average Relative Root Mean Squared Errors (aRRMSE) of the LSSVM model using ISAO are reduced by 2.13%, 18.12%, and 40.3%, respectively. The prediction model established in this paper has good accuracy. It can predict the energy consumption distribution of the boiler system of the ultra-supercritical coal-fired unit under variable load more accurately. Full article

The well productivity of high-waxy reservoirs is highly influenced by temperature changes. A decrease in temperature can cause the precipitation of wax from the crude oil, leading to a decrease in the formation’s drainage capacity and a drop in oil production. In this study, the wax precipitation of crude oil is characterized by rheological properties tests and differential scanning calorimetry (DSC) thermal analysis. The wax damage characteristics of cores and the relative permeability curves at different temperatures were investigated through coreflood experiments. Furthermore, nanoemulsion is selected as a chemical agent for injection fluid. The nuclear magnetic resonance (NMR) scanning technique is used to investigate the effects of oil recovery enhancement at different pores by increasing temperature and adding nanoemulsion. By comparing the changes in T₂ spectra and the distribution pattern of residual oil before and after liquid injection, the results have shown that both increasing temperature and adding nanoemulsion have a significant effect on oil recovery. The improvement of micropores is less pronounced compared to macropores. The produced oil mainly comes from the large pores. When the temperature is lower than the crude oil dewaxing point temperature, there is a serious dewaxing plugging phenomenon in the pores. Additionally, by observing the pattern of residual oil distribution at the end of the NMR online drive, it is hereby classified into wax deposition retention type, weak water washing retention type, and immobilized type, each with its own distinct characteristics. Wettability alteration and interfacial tension reduction can help to improve the drainage capacity of high-wax oil reservoirs, which is the main mechanism of nanoemulsion for enhanced oil recovery. These findings are highly valuable for enhancing the comprehension of the impact of highly waxed crude oils on drainage capacity and the ultimate oil recovery rate, particularly in relation to wax precipitation deposition. Full article

At present, there have been a number of hydrogen storage tank explosions in hydrogen filling stations, causing casualties and property losses, and having a bad social impact. This has made people realize that the risk assessment and preventive maintenance of hydrogen storage tanks are crucial. Therefore, this paper innovatively proposes a comprehensive risk assessment model based on connection coefficient algorithms and quintuple subtractive set pair potential. First of all, the constructed index system contains five aspects of corrosion factors, material factors, environmental factors, institutional factors and human factors. Secondly, a combined weighting analysis method based on FAHP and CRITIC is proposed to determine the weight of each indicator. The basic indicators influencing hydrogen storage tanks are analyzed via the quintuple subtraction set pair potential and full partial connection coefficient. Finally, the risk level and development trend of hydrogen storage tanks in hydrogen filling stations are determined by a combination of the three-category connection coefficient algorithms and the risk level eigenvalue method. The results of our case analysis show that the proposed risk assessment model can identify the main weak indicators affecting the safety of hydrogen storage tanks, including installation quality, misoperation and material quality. At the same time, it is found that the risk of high-pressure hydrogen storage tanks is at the basic safety level, and the development trend of safety conditions holds a critical value. The evaluation results can help establish targeted countermeasures for the prevention and maintenance of hydrogen storage tanks. Full article

Bioglycerol is a major by-product of the biodiesel manufacturing process. Various chemical derivatives from bioglycerol would enhance its economic value. An antifreeze of glycerine acetate was chemically converted from an esterification reaction of bioglycerol with acetic acid. The photocatalyst TiO₂/SO₄²⁻ irradiated with ultraviolet light assisted the chemical conversion reaction. The molar ratio of acetic acid/bioglycerol was varied to obtain the optimum composition of the derived antifreeze product. Different cosolvents were considered to enhance the homogeneous extent between the antifreeze of glycerine acetate and biodiesel, and thus, the anti-freezing effect. The cosolvent/glycerine acetate, at various volumetric ratios from 0 to 0.25 vol.%, was blended into a commercial biodiesel. After 5 vol.% antifreeze of the glycerine acetate/cosolvent mixture of the biodiesel was added to the commercial biodiesel, the fuel properties of the biodiesel were analyzed. The effects of the cosolvent types and the blended volumetric ratio of cosolvent to the antifreeze of glycerine acetate on the fuel properties of the commercial biodiesel were analyzed to determine the optimum cosolvent type and volumetric composition of the cosolvent/glycerine acetate. The experimental results show that the antifreeze of glycerine acetate produced from the reaction of acetic acid/glycerol at a molar ratio equal to 8 under UV-light irradiation appeared to have the lowest freezing point. The UV-light irradiation on the TiO₂/SO₄²⁻ catalyst also caused higher triacylglycerol (TAG) and diacylglycerol (DAG) and lower monoacylglycerol (MAG) formation. In addition, the low-temperature fluidity was the most excellent when the volumetric percentage of the methanol/glycerine acetate was equal to 0.25 vol.%, at which the cold filter plugging point (CFPP) of the biodiesel was reduced from 3 °C for the neat biodiesel to −2 °C for the biodiesel blended with the mixture. In contrast, the effect of adding the antifreeze on the CFPP of the biodiesel was inferior; it was reduced from 3 °C for the neat biodiesel to 1 °C for the biodiesel when butanol cosolvent was added. The increase in the volumetric ratio of cosolvent/antifreeze increased the acid value and cetane index while it decreased the kinematic viscosity and CFPP. The heating value was observed to increase for butanol while decreasing for methanol with the increase in the volumetric ratio of cosolvent/antifreeze. In comparison to butanol, the cosolvent methanol caused a higher cetane index and acid value but a lower kinematic viscosity, heating value, and CFPP of the blended commercial biodiesel. Full article

The impact of particle addition jets on the flow field in natural gas pipelines was investigated, and the structural information of the flow field at different flow velocities in a symmetric jet flow was analyzed via numerical simulation. The results of coherent structures in the high-pressure natural gas pipeline reveal vortex structures of varying sizes both upstream and downstream of the jet flow. To determine the spatial distribution of the main vortex structures in the flow field, proper orthogonal decomposition (POD) mode analysis was performed on the unsteady numerical results. Moreover, the detailed spatial characteristics of the coherent vortex structures represented by each mode were obtained. The results indicate that the large-scale vortex structures within the pipeline are balanced and stable, with their energy increasing as the jet flow velocity increases. Additionally, higher-order modes exhibit significant shedding of small-scale vortex structures downstream of the jet flow. In this research, coherent structures present in symmetric particle addition jets are provided, offering theoretical support for future investigations on the distribution of particle image velocimetry (PIV) flowmeters. Full article

Dry machining has gained significant importance in the last few years due to its promising contribution towards sustainability. This review study introduces dry machining, presents its benefits, and summarizes the recent technological developments that can facilitate dry machining. It aims to provide a concise overview of the current state of the art in dry machining to promote sustainability. This article synthesizes and emphasizes the useful information from the existing literature, and summarizes the methods and tools used to implement it. It also identifies some of the major problems and challenges and their potential solutions to make dry machining more viable and efficient. It concludes with some future research directions important for the scholars and researchers to establish the field further. From this review study, the major findings are: (1) tools with textures or patterns can enhance the cutting performance of dry machining for various materials, (2) tool coating is an effective way to lower the tool cost in dry machining and can achieve the required functionality for the cutting tool without affecting its core properties, (3) Alumina-based mixed ceramic tools with SiC whiskers have better fracture toughness, thermal shock resistance, and self-crack healing properties, (4) one effective method to improve the dry cutting of engineering materials is to apply external energy sources to assist the dry machining process, (5) by using microwave sintering, cutting tools with finer microstructures and higher densities can be produced, which improve their hardness, wear resistance, and thermal stability to perform well in dry machining conditions. Full article

Betulinic acid is a naturally occurring pentacyclic triterpene belonging to the lupane-group that exhibits a wide range of pharmacological activities. BA derivatives are continuously being researched due to their improved anticancer efficacy and bioavailability. The current research was conducted in order to determine the antiproliferative potential of three synthesized BA fatty esters using palmitic, stearic and butyric acids and their liposomal nanoformulations. The cytotoxic potential of BA fatty esters (Pal-BA, St-BA, But-BA) and their respective liposomal formulations (Pal-BA-Lip, St-BA-Lip, But-BA-Lip) has been assessed on HaCaT immortalized human keratinocytes and A375 human melanoma cells. Both the esters and their liposomes acted as cytotoxic agents against melanoma cells in a time- and dose-dependent manner. The butyryl ester But-BA outperformed BA in terms of cytotoxicity (IC₅₀ 60.77 μM) while the nanoformulations St-BA-Lip, But-BA-Lip and BA-Lip also displayed IC₅₀ values (60.11, 50.71 and 59.01 μM) lower compared to BA (IC₅₀ 65.9 μM). The morphological evaluation revealed that the A375 cells underwent morphological changes consistent with apoptosis following 48 h treatment with the tested compounds, while the HaCaT cells’ morphology remained unaltered. Both the esters and their liposomal formulations were able to inhibit the migration of the melanoma cells, suggesting a significant antimetastatic effect. The quantitative real-time PCR revealed that all tested samples were able to significantly increase the expression of the pro-apoptotic Bax and inhibit the anti-apoptotic Bcl-2 proteins. This effect was more potent in the case of liposomal nanoformulations versus non-encapsulated compounds, and overall, But-BA and its formulation exhibited the best results in this regard. Full article

With the adjustment of energy structure, the utilization of hydrogen energy has been widely attended. China’s carbon neutrality targets make it urgent to change traditional coal-fired power generation. The paper investigates the combustion of pulverized coal blended with hydrogen to reduce carbon emissions. In terms of calorific value, the pulverized coal combustion with hydrogen at 1%, 5%, and 10% blending ratios is investigated. The results show that there is a significant reduction in CO₂ concentration after hydrogen blending. The CO₂ concentration (mole fraction) decreased from 15.6% to 13.6% for the 10% hydrogen blending condition compared to the non-hydrogen blending condition. The rapid combustion of hydrogen produces large amounts of heat in a short period, which helps the ignition of pulverized coal. However, as the proportion of hydrogen blending increases, the production of large amounts of H₂O gives an overall lower temperature. On the other hand, the temperature distribution is more uniform. The concentrations of O₂ and CO in the upper part of the furnace increased. The current air distribution pattern cannot satisfy the adequate combustion of the fuel after hydrogen blending. Full article

Damage localization in GFRP (glass-fiber-reinforced polymer) composite plates is a crucial research area in marine engineering. This study introduces a feedback-based damage index (DI) combined with multi-label classification to enhance the accuracy of damage localization and address scenarios involving multiple damages. The research begins with the creation of a modal database for yachts’ GFRP composite plates using finite element modeling (FEM). A method for deriving a feedback-weighted matrix, based on the accuracy of the DI, is then developed. Sensitivity analysis reveals that the feedback DI is 50% more sensitive than the traditional DI, reducing false positives and missed detections. The associated feedback-weighted matrix depends solely on the structural shape, ensuring its transferability. To address the challenge for localizing multiple damages, a multi-label classification approach is proposed. The synergy between the feedback optimization and multi-label classification enables the rapid and precise localization of multiple damages in GFRP composite plates. Modal testing on damaged GFRP plates confirms the enhanced accuracy for combining the feedback DI with multi-label classification for pinpointing damage locations. Compared with traditional methods, this feedback DI method improves sensitivity, while multi-label classification effectively handles multiple damage scenarios, enhancing the overall efficiency of the damage diagnosis. The effectiveness of the proposed methods is validated through experimentation, offering robust theoretical support for composite plate damage diagnostics. Full article

This article is devoted to the further development of a viable technology for low-temperature cryopreservation of reproductive cells of sturgeon fish using acoustic–mechanical fields and intelligent control of the freezing process. Before vitrification begins, the piezoactuator acts on a mixture of cryoprotectant and reproductive cells. This promotes intensive mixing of the cryoprotector and its diffusion through the cell membrane. When vitrification is carried out directly, a phase transition phenomenon is observed, accompanied by crystal formation. This article presents a new mathematical model describing this process as developed by the authors. The corresponding boundary conditions are formulated. Numerical experiments were carried out using the finite element method. It has been established that during vitrification without the use of a cryoprotectant, a sharp temperature jump is observed at the front of the crystalline formation boundary. The use of a cryoprotectant leads to a slowdown in the process of crystal formation, that is, to a weakening of the effect of one of the most important cryoprotective factors. The comparison with full-scale experiments showed qualitative agreement with the experimental results, which indicates the adequacy of the proposed model. The results obtained can be used in the future during the vitrification process and the evaluation of the quality of cryofreezing. The application of a new methodological approach to methods of long-term preservation at low temperatures of the genetic and reproductive material of hydrobionts using acoustic and mechanical effects and an intelligent control module opens up great opportunities for the creation of new cost-effective biotechnologies that make it possible to make the transition to a new type of aquatic farms, increase the stability of aquaculture, in general, to make environmental protection measures to save rare and endangered species more effective. Full article

Hydraulic fracturing is one of the most important enhanced oil recovery technologies currently used to develop unconventional oil and gas reservoirs. During hydraulic fracture initiation, fluid seeps into the reservoir rocks surrounding the wellbore, inducing rock deformation and changes in the stress field. Analyzing the fluid–solid coupling mechanism around the wellbore is crucial to the construction design of fracturing technologies such as pulse fracturing and supercritical carbon dioxide fracturing. In this study, a new transient fluid–solid coupling model, capable of simulating the pore pressure field and effective stress field around the wellbore, was established based on the Biot consolidation theory combined with the finite difference method. The numerical results are in excellent agreement with the analytical solutions, indicating the reliability of the model and the stability of the computational approach. Using this model, the influence of seepage parameters and reservoir properties on the fluid–solid coupling around the open-hole wellbore was investigated. The simulation results demonstrate that, during wellbore pressurization, significant changes occur in the pore pressure field and effective stress field near the wellbore. The fluid–solid coupling effect around the wellbore returns to its initial state when the distance exceeds four times the radius away from the wellbore. As the fluid viscosity and wellbore pressurization rate decrease, the pore pressure field and effective circumferential stress (ECS) field around the wellbore become stronger. Adjusting the fluid viscosity and wellbore pressurization rate can control the effect of seepage forces on the rock skeleton during wellbore fluid injection. For the same injection conditions, rocks with q higher Young’s modulus and Poisson’s ratio exhibit stronger pore pressure fields and ECS fields near the wellbore. This model furnishes a dependable numerical framework for examining the fluid–solid coupling mechanism surrounding the open-hole wellbore in the initiation phase of hydraulic fractures. Full article

The occurrence of slope instability disasters seriously endangers the safety of people’s lives and property in China. Therefore, it is essential to study the slope instability process and the interaction between soil and retaining walls. In this paper, the smoothed-particle hydrodynamics (SPH) method, based on the elastoplastic constitutive model of rock and soil, was used to simulate the entire process of slope instability and the interaction between soil and retaining walls. The model, based on the classical elastic–plastic theory, includes linear elastic deformation and plastic deformation following the non-associated flow rule under the Drucker–Prager (DP) yield criterion. By considering the plastic characteristics of geotechnical materials, this method can accurately simulate the slope movement process. The model was established, calculated, and compared with a slope example, thus verifying its feasibility. Furthermore, the motion response of the retaining wall under different conditions was studied, which provides a new numerical simulation platform for the stability checking of the retaining wall and motion analysis after the interaction between the retaining wall and slope soil. Full article

The shape and convexity are crucial quality assessment indicators for hot-rolled electrical steel strips. Besides bending rolls, shifting rolls, and the original roll profile, the thermal roll profile also plays a significant role in controlling the shape and convexity during the hot-rolling process. However, it is always overlooked due to its dynamic uncertainty. To solve this problem, it is necessary to achieve online cooling-status control for the local thermal expansion of rolls. Based on the existing structure of a mill, a pair of special partition-cooling beams with an intelligent cooling system was designed. For high efficiency and practicality, a new online predictive model was established for the dynamic temperature field of the hot-rolling process. An equivalent treatment was applied to the boundary condition corresponding to the practical cooling water flow. In addition, by establishing the corresponding target distribution curve for the partitioned water flow cooling, online water-flow-partitioning control of the thermal roll profile was achieved. In the practical application process, a large number of onsite results exhibited that the predicted error was within 5% compared to the experimental results. The temperature difference between the upper and lower rolls was within 5 °C, and the temperature difference on both sides of the rolls was controlled within 0.7 °C. The hit rate of convexity (C40) increased by 33%. It was demonstrated that the partition-cooling processes of hot rolling are effective for the local shape and special convexity. They are able to serve as a better control method in the hot-rolling process. Full article

Granite residual soil typically forms complex pore structures and exhibits high water sensitivity due to physical and chemical weathering processes. Changes in initial compaction conditions significantly affect the mechanical and hydraulic properties of in situ granite residual soil subgrades, with these variations fundamentally related to changes in pore structure and soil–water characteristics. This study investigates the pore structure and bimodal soil–water characteristic curve (SWCC) of a compacted granite residual soil through laboratory tests and mercury intrusion porosimetry tests. Nine initial conditions were selected based on potential in situ compaction conditions of subgrades, and their effects on the pore size distribution (PSD) and SWCC were thoroughly analyzed. The results show strong correlations between bimodal pore structure and SWCC. The size and volume of inter-aggregate pores exhibit noticeable changes with initial conditions, affecting SWCC within the low and middle suction range. Conversely, the intra-aggregate pores, which constitute over 60% of the pore structures, remain nearly intact across different initial conditions, resulting in similar SWCCs within the high suction range. As the compaction energy increases, the inter-aggregate pores are compressed and lead to a higher water retention capacity. In addition, as the compaction water content increases, the SWCC becomes less sensitive to compaction energy after the aggregates in the pore structure are fully saturated. Additionally, a three-dimensional bimodal SWCC equation is proposed and validated using test data with an R² value above 0.98. These findings offer valuable insights for the design and quality control of granite residual soil subgrades. Full article

The moving bed heat exchanger (MBHE) has been widely applied in the recovery of waste heat of industrial particles. Currently, investigations focus on uniform-size particles in the MBHE, but few studies are conducted on multi-size particles produced by industrial granulation. Therefore, based on the discrete element method (DEM), the heat transmission model of multi-size particles is established, and flow and heat transmission processes of typically normal distribution particles in the MBHE are studied. In conclusion, there are significant differences in particles tangential velocity and contact number in local regions of a heat exchanger pipe, resulting in different local heat transmission coefficients. In addition, the increases in outlet particle velocity and inlet particle temperature significantly enhance the heat transmission. When the outlet particle velocity grows from 1 mm/s to 5 mm/s, the overall heat transmission coefficient increases by 36.4%, and as the inlet particle temperature rises from 473 K to 873 K, the overall heat transmission coefficient increases by 16.1%. Full article

The critical role of energy in contemporary life and the environmental challenges associated with its production imply the need for research and exploration of its novel resources. The present review paper emphasizes the continuous exploitation of non-renewable energy sources, suggesting the transition toward renewable energy sources, termed ‘green energy’, as a crucial step for sustainable development. The research methodology involves a comprehensive review of articles, statistical data analysis, and examination of databases. The main focus is biomass, a valuable resource for bioenergy and biopesticide production, highlighting not only its traditional diverse sources, such as agricultural waste and industrial residues, but also non-edible invasive alien plant species. This study explores the utilization of invasive alien species in circular economy practices, considering their role in bioenergy and biopesticide production. The potential conflict between bioproduct acquisition and food sector competition is discussed, along with the need for a shift in approaching non-edible biomass sources. The paper emphasizes the untapped potential of under-explored biomass resources and the necessity for policy alignment and public awareness. Species with a significant potential for these sustainable strategies include Acer negundo L., Ailanthus altisima (Mill.) Swingle., Amorpha fruticosa L., Elaengus angustifolia L., Falopia japonica (Houtt.) Ronse Decr., Hibiscus syriacus L., Koelreuteria paniculata Laxm., Paulownia tomentosa Siebold and Zucc., Partenocissus quenquefolia (L.) Planch., Rhus typhina L., Robinia pseudoacacia L. and Thuja orientalis L. In conclusion, the paper highlights the intertwined relationship between energy, environmental sustainability, and circular economy principles, providing insights into Serbia’s efforts and potential in adopting nature-based solutions for bioenergy and biopesticides acquisition. Full article

Optimization algorithms play a crucial role in a wide range of fields, from designing complex systems to solving mathematical and engineering problems. However, these algorithms frequently face major challenges, such as convergence to local optima, which limits their ability to find global, optimal solutions. To overcome these challenges, it has become imperative to explore more efficient approaches by incorporating chaotic maps within these original algorithms. Incorporating chaotic variables into the search process offers notable advantages, including the ability to avoid local minima, diversify the search, and accelerate convergence toward optimal solutions. In this study, we propose an improved Archimedean optimization algorithm called Chaotic_AO (CAO), based on the use of ten distinct chaotic maps to replace pseudorandom sequences in the three essential components of the classical Archimedean optimization algorithm: initialization, density and volume update, and position update. This improvement aims to achieve a more appropriate balance between the exploitation and exploration phases, offering a greater likelihood of discovering global solutions. CAO performance was extensively validated through the exploration of three distinct groups of problems. The first group, made up of twenty-three benchmark functions, served as an initial reference. Group 2 comprises three crucial engineering problems: the design of a welded beam, the modeling of a spring subjected to tension/compression stresses, and the planning of pressurized tanks. Finally, the third group of problems is dedicated to evaluating the efficiency of the CAO algorithm in the field of signal reconstruction, as well as 2D and 3D medical images. The results obtained from these in-depth tests revealed the efficiency and reliability of the CAO algorithm in terms of convergence speeds, and outstanding solution quality in most of the cases studied. Full article

The cement strength between the cement and the formation is a key factor in determining the cementation sealing capacity. In the shale formation, due to the organic matter content, the cementing quality between the formation and the cement ring is poor, which affects the quality of cementing. It is easy to cause problems such as annulus pressure. To improve the quality of cementing, this paper investigates the effect of amino silane coupling agents, vinyl silane coupling agents and aluminium–zirconate coupling agents on the interface cementation of rock and cement under different conditions. Meanwhile, the effects of different coupling agent compounding on improving the cementation interface cement strength under different temperature and concentration conditions were investigated. This led to the development of a composite interface enhancer. The composite interface enhancer can improve the bond strength between cement and rock by 189.22%. A preflush fluid system was developed to effectively improve the cementation strength of mud shale formations, and its performance was evaluated. The density of the preflush fluid system is 1.15 g·cm⁻³, and it has good rheology, settlement stability, and filtration loss. In addition, it improves the cementing interface cementing strength between the cement and shale formation. Full article

This paper proposes a new method for assessing the state of charge (SoC) and identifying the types of different lithium-ion cells used in the battery systems of light electric vehicles. A particular challenge in the development of this method was the SoC estimation time, as the method is intended for implementation in the control system of a bicycle charging station, where the state of charge must be determined immediately after the bicycle is plugged in in order to start the charging process as quickly as possible according to the appropriate charging algorithm. The method is based on the identification of the transfer function, i.e., the dynamic response of the battery voltage to the current pulse. In the learning phase of this method, a database of reference transfer functions and corresponding SoCs for a specific type of battery cell is created. The transfer functions are described by coefficients determined through the optimization procedure. The algorithm for estimating the unknown battery cell SoCs is based on the comparison of the measured voltage response with the responses of the reference transfer functions from the database created during the learning process to the same current signal. The comparison is made by calculating the integral of the square error (ISE) between the response of the specific reference transfer function and the measured voltage response of the battery cell. Each transfer function corresponds to a specific SoC and cell type. The specific SoC of the unknown battery is determined by quadratic interpolation of the SoC near the reference point with the smallest ISE for each battery type. The cell type detection algorithm is based on the fact that the integral squared error criterion near the actual SoC for the actual cell type changes less than the squared error criterion for any other battery cell type with the same SoC. An algorithm for estimating the SoC and cell type is described and tested on several different cell types. The relative error between the estimated SoC and the actual SoC was used as a measure of the accuracy of the algorithm, where the actual SoC was calculated using the Coulomb counting method. Full article

Vehicle fuel leaks can adversely affect the performance of asphalt pavements. To study the mechanisms of fuel corrosion damage in asphalt, four asphalt binders were selected in this study, and the evolution of their rheological and microscopic properties was investigated. Fuel corrosion caused continuous mass loss in asphalt binders. Base asphalt lost more than 50% of its mass after 24 h of fuel corrosion, while modified asphalts had better resistance. According to dynamic shear rheometer tests and multiple stress creep recovery tests, modifiers improved the high-temperature rheological properties of these asphalt binders. As the degree of fuel corrosion deepened, the indexes characterizing the high-temperature performance deteriorated. Rubber-modified asphalt showed the best resistance to high-temperature deformation, while the performance of LDPE-modified asphalt was more stable. In contrast, fuel corrosion improved the resistance of asphalt binders to low-temperature cracking to some extent: the creep strength (S) decreased as the creep rate (m) increased, and the resistance of SBS-modified asphalt to low-temperature cracking was optimal, with a 36% decrease in S-value after 24 h of fuel corrosion. Fourier transform infrared spectroscopy tests showed that diesel corrosion was a process of this physical dissolution, with no change in the chemical functional groups. Meanwhile, by using fluorescence images and analyzing the four-component test results, we found that fuel corrosion disrupted the stabilized structure formed by the modifiers, and the heavy components in the asphalt binders were converted into light components. This study reveals the evolution of the rheological and microscopic properties of asphalt under fuel corrosion, which can provide a reference for the optimization of fuel corrosion resistance in asphalt pavement. Full article

In response to the urgent need to address climate change and reduce carbon emissions, there has been a growing interest in innovative approaches that integrate AI and CDR technology. This article provides a comprehensive review of the current state of research in this field and aims to highlight its potential implications with a clear focus on the integration of AI and CDR. Specifically, this paper outlines four main approaches for integrating AI and CDR: accurate carbon emissions assessment, optimized energy system configuration, real-time monitoring and scheduling of CDR facilities, and mutual benefits with mechanisms. By leveraging AI, researchers can demonstrate the positive impact of AI and CDR integration on the environment, economy, and energy efficiency. This paper also offers insights into future research directions and areas of focus to improve efficiency, reduce environmental impact, and enhance economic viability in the integration of AI and CDR technology. It suggests improving modeling and optimization techniques, enhancing data collection and integration capabilities, enabling robust decision-making and risk assessment, fostering interdisciplinary collaboration for appropriate policy and governance frameworks, and identifying promising opportunities for energy system optimization. Additionally, this paper explores further advancements in this field and discusses how they can pave the way for practical applications of AI and CDR technology in real-world scenarios. Full article

The purpose of this article was to develop a method of analyzing the manufacturing process with variables indicating product competitiveness and technological capabilities in metric space as a cognitive source. The presented method will facilitate the identification of key development factors within the manufacturing processes that have the greatest impact on the adaptation of the manufacturing enterprise to Industry 4.0. The presented method of manufacturing process analysis integrates a number of tools (SMART method, brainstorming, BOST analysis, 3 × 3 metrics) that enable the implementation of statistical analysis. The model developed makes it possible to apply known mathematical methods in areas new to them (adaptation in the manufacturing area), which makes it possible to use scientific information in a new way. The versatility of the method allows it to be used in manufacturing companies to identify critical factors in manufacturing processes. A test of the developed method was carried out in one of the foundry enterprises, which allowed us to build a series of importance factors affecting effective production management. The methodology is addressed to the management of manufacturing enterprises as a method to assist in analyzing data and building (on the basis of improved manufacturing processes) a competitive strategy. Full article

Particle swarm optimization (PSO) has been extensively used to solve practical engineering problems, due to its efficient performance. Although PSO is simple and efficient, it still has the problem of premature convergence. In order to address this shortcoming, an adaptive particle swarm optimization with state-based learning strategy (APSO-SL) is put forward. In APSO-SL, the population distribution evaluation mechanism (PDEM) is used to evaluate the state of the whole population. In contrast to using iterations to just the population state, using the population spatial distribution is more intuitive and accurate. In PDEM, the population center position and best position for calculation are used for calculation, greatly reducing the algorithm’s computational complexity. In addition, an adaptive learning strategy (ALS) has been proposed to avoid the whole population’s premature convergence. In ALS, different learning strategies are adopted according to the population state to ensure the population diversity. The performance of APSO-SL is evaluated on the CEC2013 and CEC2017 test suites, and one engineering problem. Experimental results show that APSO-SL has the best performance compared with other competitive PSO variants. Full article

The global shale gas resources are huge and have good development prospects, but shale is mainly composed of nanoscale pores, which have the characteristics of low porosity and low permeability. Horizontal drilling and volume fracturing techniques have become the effective means for developing the shale reservoirs. However, a large amount of mining data indicate that the fracturing fluid trapped in the reservoir will inevitably cause hydration interaction between water and rock. On the one hand, the intrusion of fracturing fluid into the formation causes cracks to expand, which is conducive to the formation of complex fracture networks; on the other hand, the intrusion of fracturing fluid into the formation causes the volume expansion of clay minerals, resulting in liquid-phase trap damage. At present, the determination of well closure time is mainly based on experience without theoretical guidance. Therefore, how to effectively play the positive role of shale hydration while minimizing its negative effects is the key to optimizing the well closure time after fracturing. This paper first analyzes the shale pore characteristics of organic pores, clay pores, and brittle mineral pores, and the multi-pore self-absorption model of shale is established. Then, combined with the distribution characteristics of shale hydraulic fracturing fluid in the reservoir, the calculation model of backflow rate and shut-in time is established. Finally, the model is validated and applied with an experiment and example well. The research results show that the self-imbibition rate increases with the increase in self-imbibition time, and the flowback rate decreases with the increase in self-imbibition time. The self-imbibition of slick water is the maximum, the self-imbibition of breaking fluid is the minimum, and the self-imbibition of mixed fluid is the middle, and the backflow rates of these three liquids are in reverse order. It is recommended the shut-in time of Longmaxi Formation shale is 17 days according to the hydration and infiltration model. Full article

A new approach to determining the friabilin content of wheat grain was proposed. Electropherograms were taken, and the intensity of the friabilin bands was compared in the analyzed wheat cultivars and the cv. Chinese Spring. The friabilin content indicator was calculated in the grain of 17 common wheat cultivars, which differed mostly in their crude protein content and hardness index (HI). The basic properties of the kernels were measured in each wheat cultivar, and the correlations between the measured parameters and the friabilin content indicator were determined. In the analyzed wheat cultivars, the friabilin content indicator ranged from around 0.21 to around 0.77. This indicator was significantly correlated with the kernel length, thickness, mass, vitreousness, HI, and rupture force. The strongest correlation was observed between the friabilin content indicator and kernel length. An increase in the mean kernel length from around 5.4 mm to around 8.0 mm decreased the friabilin content indicator by approximately 51%. After the mean kernel length had been calculated in a given wheat cultivar, a certain value of the friabilin content indicator could be ascribed to this cultivar, and the energy consumption during grain grinding or milling could be partly predicted. In the group of analyzed wheat cultivars, the process of grain grinding would be the most energy-intensive in the cvs. Ceres, SMH200, and SMH214 and the least energy-intensive in the cvs. Chinese Spring, Julius, and Askalon. Full article

The iron and steel industry is the leading industry supporting China’s industrial sector. Currently, there is less assessment work on green and low-carbon technologies for the iron and steel industry. This study clarifies the overall strategy of technology assessment by researching the relevant theories and methods of technology assessment. The study further establishes a scientific and reasonable comprehensive assessment index system of green and low-carbon technologies for the iron and steel industry from the aspects of technology index, economy and promotion, and application, including factors such as 11 indexes, the amount of energy saving, carbon dioxide emission reduction, and the resource recovery rate by utilising analytical and comprehensive methods and combining with the characteristics of the technologies. By analysing and comparing the advantages and disadvantages of the commonly used assessment methods, the entropy weighting method, grey correlation analysis method, and TOPSIS (technique for order preference by similarity to an ideal solution) method are combined and optimised to construct a comprehensive assessment model. The Latin hypercube sampling method is also introduced to analyse the technical parameters in combination with the evaluation model. Finally, fourteen iron and steel green and low-carbon technologies were selected for case assessment and uncertainty analysis of technical parameters, and it was found that the comprehensive assessment result of gas combined cycle power generation technology was optimal. After determining the weights of each assessment indicator through the entropy weighting method, it is concluded that the technical performance indicator > economic indicator > promotional indicator. A comparative analysis of the results under the three preference decisions concludes that technical performance is the main obstacle to improving the comprehensive assessment score of the technology, followed by the economics of the technology. Finally, the uncertainty analysis of the technical parameters shows that the fluctuation of the technical parameters not only affects the performance of the technology, but also affects the weights of the indicators and the comprehensive evaluation results of the technology. Full article

The increased concentration of CO₂ in the atmosphere has a strong impact on global warming. Therefore, efficient technologies must be used to reduce CO₂ emissions. One of the methods is the biofixation of CO₂ by microalgae and cyanobacteria. This is now a widely described technology that can improve the economics of biomass production and reduce CO₂ emissions. There are no reports on the possibility of using it to clean exhaust gases from biogas combustion. The aim of the research was to determine the possibility of using Arthrospira platensis cultures to remove CO₂ from biogas combustion. The efficiency of biomass production and the effectiveness of biological CO₂ fixation were evaluated. The use of exhaust gases led to a more efficient increase in cyanobacterial biomass. The growth rate in the exponential phase was 209 ± 17 mgVS/L·day, allowing a biomass concentration of 2040 ± 49 mgVS/L. However, the use of exhaust gases led to a decrease in the pH of the culture medium and a rapid decline in the Arthrospira platensis population. The cyanobacteria effectively fixed CO₂, and its concentration was limited from 13 ± 1% to 1.3 ± 0.7%. There was no influence of the exhaust gases on changes in the qualitative composition of the cyanobacterial biomass. In the culture fed with exhaust gas, the A. platensis population quickly entered the death phase, which requires close monitoring. This is an important indication for potential operators of large-scale photobioreactors. Full article

In the dynamic optimization problem of the distribution network, a dynamic reconstruction method based on a stochastic probability model and optimized beetle antennae search is proposed. By implementing dynamic reconstruction of distributed energy distribution networks, the dynamic regulation and optimization capabilities of the distribution network can be improved. In this study, a random probability model is used to describe the uncertainty in the power grid. The beetle antennae search is used for dynamic multi-objective optimization. The performance of the beetle antennae search is improved by combining it with the simulated annealing algorithm. According to the results, the optimization success rate of the model was 98.7%. Compared with the discrete binary particle swarm optimization algorithm and bacterial foraging optimization algorithm, it was 9.3% and 26.1% faster, respectively. For practical applications, this model could effectively reduce power grid transmission losses, with a reduction range of 16.7–18.6%. Meanwhile, the charging and discharging loads were effectively reduced, with a reduction range of 16.2–19.7%. Therefore, this method has significant optimization effects on actual power grid operation. This research achievement contributes to the further development of dynamic reconstruction technology for distribution networks, improving the operational efficiency and stability of the power grid. This has important practical significance for achieving green and intelligent operation of the power system. Full article

Mobile pipelines are the most efficient and reliable way to transport large quantities of oil over long distances in warfare, rescue and disaster relief. The oil in the pipe must be discharged and recovered when the oil transfer task is completed, usually via gas cap evacuation. Gas cap evacuation is the main method to evacuate mobile pipelines. During evacuation, due to the influence of topography, working conditions and gravitational forces, the oil in an up-hill pipeline is gradually deposited in the low-lying part of the pipeline to form a liquid, resulting in the incomplete emptying of the pipeline which directly affects the recovery efficiency of the pipeline. Focusing on the analysis of the gas carrying oil flow process in an up-hill pipeline during the evacuation of gas displacing oil in the mobile pipeline, the tail and head of the liquid accumulation were analyzed, and the liquid accumulation flow model was established based on the gas–liquid two-phase stratified flow theory. This model was used to analyze the flow law of the accumulated liquid under different pipe inclination angles, initial accumulation thicknesses and pipe diameters. It was found that the stagnant oil in the pipeline is carried by the gas flow into the upward tilting pipeline due to the influence of the axial gravity force of the pipeline. The gas flow can be divided into three phases: the initial discharge stage, the oscillation stage and the final discharge (reflux) stage. Full article