Processes, Volume 12, Issue 5 (May 2024) – 149 articles

Tire recycling is becoming an increasingly important problem due to the growing number of end-of-life tires (ELTs). World-wide, ELTs account for more than 80 million tons. ELTs contribute to environmental pollution in the long term. They are flammable, toxic and non-biodegradable. At the same time, ELTs contain rubber, metal and textile cord, which are valuable raw materials. ELTs are buried in landfills, burned, crushed and restored. Most of these methods have a negative impact on the environment. From an environmental point of view, the most preferred ways to recycle tires are retreading and shredding. Rubber powder (RP) or crumb is mainly used for rubber pavers production, waterproofing, curbs, road slabs and various surfaces. An alternative method for RP processing, eliminating the disadvantages of the above approaches, is plasma gasification and pyrolysis. The paper presents a thermodynamic and kinetic analysis and an experiment on plasma processing of RP from worn tires to produce flammable gas. At a mass-average temperature of 1750 K, the yield of synthesis gas from plasma-air gasification of RP was 44.6% (hydrogen—19.1, carbon monoxide—25.5), and 95.6% of carbon was gasified. The experimental and calculated results satisfactorily agreed. It was found that plasma products from RP did not contain harmful impurities, either in calculations or experiments. Plasma gasification allows for recycling ELTs in an environmentally friendly way while also generating flammable gases that are valuable commodities. In this research, plasma technology was demonstrated to be effective for gasifying RP to produce flammable gas. Full article

The studies carried out address an important problem for the concrete and asphalt industry, referring to the wear phenomena that affect the elements (flights) of rotary dryers used to dry mineral aggregates. In this article, the authors propose a lifetime estimation method for rotary dryer flights. In order to benefit from greater credibility, the proposed method was applied based on the experimental results obtained, by the authors, in the laboratory, on a stand that reproduces a portion of the real equipment. Starting from these results, the authors identified the mathematical functions used to model the failure rates (wear) of the flights by referring to characteristic quantities for wear evaluation: mass loss of material; reduction in the thickness of the part; surface affected by wear. The experimental data—the input data for the proposed algorithm—correspond to six steels used in industrial applications. The wear phenomenon was modeled considering both the situation of uniform wear and the situation of differentiated wear on the flight surface. Therefore, the steel type with the highest service life values could be identified, namely, steel grades E and G. The method proposed in this paper can be extended to any category of material or part provided that the failure rate function is identified beforehand, possibly based on a laboratory experiment. Full article

As a functional extraction medium, natural deep eutectic solvents (NADESs) can dissolve various plant metabolites. Those solvents provide untapped potential for creating novel green extracts with distinctive phytochemical signatures and unique biological activities. This is particularly relevant given the rising need for eco-friendly and sustainable skin care products. The main aim of this work was to optimize the most efficient natural deep eutectic solvents (NADESs) for extracting bioactives from 18 medicinal herbs applicable to the cosmetic industry. Selection of the most potent herbs involved assessing their conventional extracts for tyrosinase inhibition, antioxidant activity, and keratinocyte cytotoxicity. Moreover, we analyzed the phenolic profile using ultra-high-pressure liquid chromatography/mass spectrometry (UHPLC/MS) and spectrophotometric assays such as total phenolic (TPC) and flavonoid content (TFC). Using the COSMO-RS method, we modeled the solubility of 12 phenolics in 64 virtual NADESs and selected the 7 most promising ones for further experimental validation. NADESs, including betaine-urea, betaine-proline, and betaine-lysine, were computationally chosen and demonstrated the highest levels of TPC and antioxidative capacity, as confirmed by in vitro assays. The proposed combination of NADES herbal extracts represents a promising natural constituent for the cosmetic industry. Full article

Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations of the PM, there is a big computational effort that leads to a large controller execution time. The main motivation of this work is to decrease the computational effort and, consequently, the controller execution time. This paper proposes to replace the PSO predictor with a machine learning model that has “learned” the quasi-optimal behavior of the couple (PSO and PM); the training data are obtained through closed-loop simulations over the control horizon. The new controller should preserve the process’s quasi-optimal control. In identical conditions, the process evolutions must also be quasi-optimal. The multiple linear regression and the regression neural networks were considered the predicting models. This paper first proposes algorithms for collecting and aggregating data sets for the learning process. Algorithms for constructing the machine learning models and implementing the controllers and closed-loop simulations are also proposed. The simulations prove that the two machine learning predictors have learned the PSO predictor’s behavior, such that the process evolves almost identically. The resulting controllers’ execution time have decreased hundreds of times while keeping their optimality; the performance index has even slightly increased. Full article

The objective of this study was to determine the effect of XG addition on low-fat yogurt (LFY) properties. Pasteurized skimmed buffalo milk (SBM) was heated to 95 ± 2 °C for 16 s, cooled to 40 ± 1 °C, and then divided into six treatment lots. The treatments included the following: T1 (control), T2 (0.2% XG), T3 (0.4% XG), T4 (0.6% XG), T5 (0.8% XG), and T6 (1% XG). A proportion of 2% of a mixed starter culture from Streptococcus thermophilus (ST), Lactobacillus bulgaricus (LB), and Bifidobacterium bifidum (BB) in the ratio 1:1:1 was added. Yogurt was manufactured following the standard manufacturing protocol. Chemical composition and texture were determined at fresh time, while water-holding capacity (WHC), viscosity, and syneresis % were determined at 0, 7, 14, and 21 days of storage. Total bacterial counts (TBC), lactobacilli, streptococci, and bifidobacteria counts were determined at 0, 7, 14, and 21 days of storage. Sensory analysis was performed immediately upon the cooling stage (time zero) and then after 14 and 21 days of storage. The experiment was performed in trice. The results obtained showed that the addition of XG in LFY significantly (p < 0.05) decreases the pH, total protein (TP), and ash, and significantly (p < 0.05) increased the total solids (TS). Additionally, the addition of XG led to a significant (p < 0.05) increase in hardness, WHC, and viscosity; however, syneresis significantly (p < 0.05) decreased. The addition of higher amounts of XG led to a significant (p < 0.05) decrease in the TBC and led to a significant (p < 0.05) increase in counts of ST, LB, and BB during the first two weeks of the storage period. Sensory evaluation revealed that increasing the XG concentration up to 0.8% increased the product’s acceptability among panelists; however, further increasing the concentration to 1% had a detrimental impact on its acceptability. To conclude, this study showed that XG can be used as a stabilizer in the manufacturing of LFY as well as a prebiotic for starter culture and improve the quality of LFY. Full article

The interactions of metal ions with fulvic acids were investigated from the point of view of the thermodynamic aspects of complexation as well as the size and charge of the formed complexes. Thermodynamic aspects were studied by means of isothermal titration calorimetry. Particle size distribution was determined by the method of dynamic light scattering and charge by the measurement of zeta potential. Complexation resulted in changes in particle size and charge. The particle size distribution was trimodal for fulvic acids and bimodal for fulvic complexes with calcium and magnesium, while copper–fulvic complexes had only one size fraction. The compensation of the negative charge of carboxylic and phenolic functional groups by positively charged metal ions resulted in an increase in zeta potential which became closer to zero in the case of copper–fulvic complexes. However, all metal–humic complexes behaved as colloidally unstable, which resulted in visually observable sedimentation. Calorimetric measurements provided positive values for changes in enthalpy, which indicated endothermic processes. In contrast, quantum chemical calculations as well as experiments with model compounds provided negative values indicating exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive. Full article

The advancement of photovoltaic module (PV) enhancer technology shows significant promise due to its rapid growth. Nevertheless, there remains a requirement for ongoing research to refine the evaluation techniques for this technology. In a prior investigation, the concept of the area and cost-effectiveness factor, denoted as ${\mathrm{F}}_{\mathrm{C}\mathrm{A}\mathrm{E}}$, was introduced to analyze the economic impact of enhancing the PV through techniques such as reflectors or coolers. This metric relates the surface area and manufacturing expenses of a PV enhancer to its capacity for improving the PV output power, aiding in the comparison of different enhancer types. However, this assessment approach is costly, requiring a set of PVs without enhancers to be compared with an equal number of modules fitted with enhancers. This paper introduces a modified version of this metric, termed the modified area and cost-effectiveness factor (${\mathrm{F}}_{\mathrm{M}\mathrm{C}\mathrm{A}\mathrm{E}}$), along with its minimum value (${\mathrm{F}}_{\mathrm{M}\mathrm{C}\mathrm{A}\mathrm{E},\min }$), with the aim of reducing the assessment expenses associated with PV enhancers. This modification hinges on knowing the output power from a single solar cell without an enhancer, as well as from a PV with an enhancer containing a known number of solar cells. Additionally, it relies on data regarding the manufacturing cost of the PV enhancer, the cost of one watt of PV power, and the combined surface area of the PV and its enhancer. The equations for computing the total number of solar cells and the associated costs in addition to the expenses cost are also proposed for ${\mathrm{F}}_{\mathrm{CAE}}$ and ${\mathrm{F}}_{\mathrm{MCAE}}$. The results of the present study using ${\mathrm{F}}_{\mathrm{MCAE}}$ show that there is a proportional relationship between the percentage of solar cell saving and the number of solar cells. As the solar cells increase, the percentage of solar sell saving increases. The findings reveal that utilizing ${\mathrm{F}}_{\mathrm{MCAE}}$ leads to a 48.33% increase in the proportion of solar cells saved compared to the existing method. It can be concluded that the proposed method is cost-efficient and holds promise for adoption by PV enhancer designers and manufacturers. Full article

The development of sustainable biofuels can help to reduce the reliance on fossil fuels and mitigate the impact of climate change. This study analyzes bioethanol production from agro-forestry residual biomass, namely eucalyptus residues and corn stover. The study includes process simulation using Aspen Plus software, followed by economic analysis and life cycle assessment (LCA) with the help of SimaPro software and by applying the environmental footprint (EF) 3.0 method. The economic analysis on the biorefinery’s economic viability, equipment, and production costs reveals a positive decision for bioethanol production from eucalyptus residues due to logistical and transportation costs. The minimum ethanol selling price (MESP) obtained was 2.19 €/L and 2.45 €/L for eucalyptus residues and corn stover, respectively. From the LCA with a functional unit of 1 MJ of ethanol, bioethanol production from eucalyptus residues results in a single score impact of 37.86 µPt, whereas for corn stover, it is 33.47 µPt. In the climate change impact category, the eucalyptus residues scenario has an impact of 0.264 kg CO₂ eq/MJ ethanol while corn stover leads to 0.254 kg CO₂ eq/MJ ethanol. In-situ enzyme production, heat integration, and the use of renewable energy sources were also analyzed. Combining in situ enzyme production with renewable energy sources lowers CO₂ equivalent emissions by 89% for both feedstocks, in comparison to the base-case scenario. Full article

This study introduces a novel process identification method aimed at overcoming the challenge of accurately estimating process models when faced with deterministic disturbances, a common limitation in conventional identification methods. The proposed method tackles the difficult modeling problems due to deterministic disturbances by representing the disturbances as a linear combination of Laguerre polynomials and applies an integral transform with frequency weighting to estimate the process model in a numerically robust and stable manner. By utilizing a least squares approach for parameter estimation, it sidesteps the complexities inherent in iterative optimization processes, thereby ensuring heightened accuracy and robustness from a numerical analysis perspective. Comprehensive simulation results across various process types demonstrate the superior capability of the proposed method in accurately estimating the model parameters, even in the presence of significant deterministic disturbances. Moreover, it shows promising results in providing a reasonably accurate disturbance model despite structural disparities between the actual disturbance and the model. By improving the precision of process models under deterministic disturbances, the proposed method paves the way for developing refined and reliable control strategies, aligning with the evolving demands of modern industries and laying solid groundwork for future research aimed at broadening application across diverse industrial practices. Full article

This study aims to develop a fault detection system designed specifically for wind turbine gearboxes. It proposes a hybrid fault diagnosis algorithm that combines scatter plot analysis with the visual geometric group (VGG) technique to identify various fault types, including gear rust, chipping, wear, and aging. To capture vibration signals, a three-axis vibration sensor was integrated with a NI-9234 DAQ card. Digital signal processing techniques were employed to actively filter out noise from the captured signals. Gaussian white noise was incorporated into the training data to enhance the noise resistance of the network model, which was then utilized for scatter plot generation. The VGG technique was subsequently applied to identify faults. The testing data were collected at two different speeds, with 1500 samples taken at each speed, totaling 3000 samples. For both training and testing, 400 samples of each fault type were employed for training, while 200 samples were allocated for testing. The test results demonstrated an overall identification accuracy of 97.7% for both the no-fault gearbox and the four-fault states, underscoring the effectiveness of the proposed methodology. Full article

Local path planning is a necessary ability for mobile robot navigation, but existing planners are not sufficiently effective at dynamic obstacle avoidance. In this article, an improved timed elastic band (TEB) planner based on the requirements of mobile robot navigation in dynamic environments is proposed. The dynamic obstacle velocities and TEB poses are fully integrated through two-dimensional (2D) lidar and multi-obstacle tracking. First, background point filtering and clustering are performed on the lidar points to obtain obstacle clusters. Then, we calculate the data association matrix of the obstacle clusters of the current and previous frame so that the clusters can be matched. Thirdly, a Kalman filter is adopted to track clusters and obtain the optimal estimates of their velocities. Finally, the TEB poses and obstacle velocities are associated: we predict the obstacle position corresponding to the TEB pose through the detected obstacle velocity and add this constraint to the corresponding TEB pose vertex. Then, a pose sequence considering the future positions of obstacles is obtained through a graph optimization algorithm. Compared with the original TEB, our method reduces the total running time by 22.87%, reduces the running distance by 19.23%, and increases the success rate by 21.05%. Simulations and experiments indicate that the improved TEB enables robots to efficiently avoid dynamic obstacles and reach the goal as quickly as possible. Full article

The low-permeability argillaceous rock mass is an unfavorable geological body commonly found in the construction process of underground engineering conditions such as roadways and tunnels. Due to the compact structure and low permeability of the rock mass, grouting with conventional materials cannot effectively seal the micro-cracks of the rock mass. Based on the low efficiency of high-pressure grouting of nano-silica sol, this paper preliminarily explores the regularities and mechanism of grouting and pore sealing of low-permeability rock mass under the action of silica sol imbibition from the aspects of gelling properties of silica sol, core pore structure, imbibition law, and pore sealing characteristics. The results show the following: (1) The increase in particle size during the gel process reduced the injectability and wettability of the silica sol. The imbibition properties of silica sol were time-varying, and the deterioration inflection points of injectability and wettability appeared at 10 h and 9 h, respectively. (2) Catalyst, temperature, gel process, and rock mass permeability will affect the law of core imbibition, and the injectability and capillary force of the grouting material and rock mass will jointly affect the imbibition process of silica sol. (3) Silica sol imbibition changed the pore size distribution of the core, the pore volume above 50 nm decreased, and the pore volume below 50 nm increased. Silica sol has multiple effects such as filling, adsorption, and percolation in the imbibition process of the micro-pores of rock mass, and the adsorption and percolation of silica are related to the nano micro-pores. Full article

The biflavonoid extraction from ginkgo (Ginkgo biloba L.) leaves using solvent-based extraction with 70% ethanol, alone and in combination with enzyme-assisted, ultrasound-assisted, mechanical-assisted, and chemically assisted methods was investigated and the influence of extraction duration was explored. The total content of polyphenols, flavonoids, and phenolic acids in the extracts was determined spectrophotometrically, while individual biflavonoids were identified and quantified using HPLC-DAD. Amentoflavone, bilobetin, ginkgetin, isoginkgetin, and sciadopitysin were identified in all our extracts. Among these, sciadopitysin emerged as the most prevalent biflavonoid with an amount above 1 mg g⁻¹ dw, followed by isoginkgetin. Comparative analysis of the extraction methods revealed that, except for chemically assisted extraction, similar levels of compounds were obtained after 45 min of extraction. However, enzymatic (EAE) and mechanical-assisted extraction (MAE) exhibited significantly higher individual (EAE: 19–41% higher; MAE: 22–67% higher) and total biflavonoid (EAE: 29% higher; MAE 50% higher) levels after just 5 min, suggesting their potential to abbreviate extraction duration and facilitate the efficient retrieval of target compounds. However, as extraction efficiency varies between individual biflavonoids, our findings also underscore the importance of considering specific compounds and extraction kinetics in the optimization of ginkgo leaf extraction processes. Full article

Protection from nuclear biochemical aerosol and air pollution pays attention to aerosol mass concentration. The concentration of upstream aerosol of the commonly used filtration efficiency detection device for high-efficiency filter materials is low, making it insufficient for detecting the filtration efficiency of high-efficiency filter materials. This study designed and built a set of filtration efficiency detection devices for high-efficiency filter materials based on mass concentration. By adjusting the oil bath temperature, injection pressure, the degree of spiral-separator separation, as well as the number and size of nozzles, we investigated the effects of each condition on the concentration and particle size distribution of aerosol generation. As a result, the oil mist generator of the device can stably generate high-concentration aerosol with a mass concentration of up to 1587.9 mg/m³ and a number concentration of up to 10⁷–10⁸ P/cm³. The high-concentration aerosol generated can meet the E11–U15 filter material performance requirements. Full article

A series of COMSOL numerical models were developed to explore how confining pressure impacts the microscopic structure and hydraulic conductivity of Geosynthetic Clay Liners (GCLs), taking into account the bentonite swelling ratio, mobile porosity, pore size, and tortuosity of the main flow path. The study reveals that the mobile porosity and pore size are critical factors affecting GCL hydraulic conductivity. As confining pressure increases, the transition of mobile water to immobile water occurs, resulting in a reduction in mobile water volume, the narrowing of pore channels, decreased flow velocity, and diminished hydraulic conductivity within the GCL. Mobile porosity undergoes a slight decrease from 0.273 to 0.104, while the ratio of mobile porosity to total porosity in the swelling process decreases significantly from 0.672 to 0.256 across the confining pressure range from 50 kPa to 500 kPa, which indicates a transition of mobile water toward immobile water. The tortuosity of the main flow path shows a slight increase, fluctuating within the range of 1.30 to 1.36, and maintains a value of around 1.34 as the confining pressure rises from 50 kPa to 500 kPa. At 50 kPa confining pressure, the minimum pore width measures 5.2 × 10⁻⁵ mm, with a corresponding hydraulic conductivity of 6.2 × 10⁻¹¹ m/s. With an increase in confining pressure to 300 kPa, this compression leads to a narrower minimum pore width of 1.81 × 10⁻⁵ mm and a decrease in hydraulic conductivity to 5.11 × 10⁻¹² m/s. The six-fold increase in confining pressure reduces hydraulic conductivity by one order of magnitude. A theoretical equation was derived to compute the hydraulic conductivity of GCLs under diverse confining pressure conditions, indicating a linear correlation between the logarithm of hydraulic conductivity and confining pressure, and exhibiting favorable agreement with experimental findings. Full article

Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder characterized by the insufficient production of the AAT protein. Due to availability limitations, not all AATD patients receive protein therapy treatment. In this study, the technoeconomic analysis of different processes (conventional and intensified) producing 200 kg/year of PEGylated recombinant AAT (PEG-AAT) using a Chinese hamster ovary cell line was investigated. All bioprocesses consist of upstream, downstream, and PEGylation sections. A base-case model (process A) of the conventional fed-batch production bioreactor was developed using SuperPro Designer software (Version 13) to evaluate the economic feasibility of the process. The cost of goods (COG) was estimated to be approximately USD 387.6/g. Furthermore, an intensified process (B) was modeled and evaluated to reduce the COG. Process intensification was implemented in the process (N-1 perfusion bioreactor). The specific operating COG for process B was found to be 10% less than that of process A. Scenario analysis was performed to assess the impact of process capacity (100–1000 kg/year) and cell-specific productivity (30–90 pg/cell/day). With an increase in process capacity, the specific operating COG was reduced for all processes. Increasing cell-specific productivity decreases the specific operating COG at different rates for each process, depending on the titer level. Future investigations into the PEGylation section are required since it has the highest COG of all the sections. Full article

Sugarcane bagasse (SCB), an agro-industrial byproduct generated by a sugar mill, holds a substantial carbohydrate content of around 70 wt.%, comprising cellulose and hemicellulose. Saccharification plays a pivotal role in the conversion of SCB into second-generation (2G)-ethanol and valuable compounds, which is significantly aided by thermochemical pretreatments. In this study, SCB underwent diluted sulfuric acid pretreatment (2% H₂SO₄, 80 rpm, 200 °C, 20 min), resulting in the removal of 77.3% of the xylan. The hemicellulosic hydrolysate was analyzed to identify the sugars and degraded products acting as microbial inhibitors. The acid hydrolysate showed a xylose yield of 68.0% (16.4 g/L) and a yield of 3.8 g/L of acetic acid. Afterward, the hemicellulosic hydrolysate was concentrated 2.37 times to obtain a xylose-rich stream (39.87 g/L). The sequential detoxification, employing calcium oxide and activated carbon, removed the inhibitory compounds, including acetic acid, while preserving the xylose at 38.10 g/L. The enzymatic saccharification of cellulignin at 5% and 10% of the total solids (TSs) yielded comparable reducing sugar (RS) yields of 47.3% (15.2 g/L) and 47.4% (30.4 g/L), respectively, after 96 h, employing a 10 FPU/g enzyme loading of Cellic^® CTec3 (Novozymes Inc. Parana, Brazil). In summary, these findings outline an integrated green chemistry approach aimed at addressing the key challenges associated with pretreatment, concentration, detoxification, and enzymatic hydrolysis to produce fermentable sugars. Full article

The precise control of a greenhouse environment is vital in production. Currently, environmental control in traditional greenhouse production relies on experience, making it challenging to accurately control it, leading to environmental stress, resource waste, and pollution. Hence, this paper proposes a decision-making greenhouse environment control strategy that employs an existing monitoring system and intelligent algorithms to enhance greenhouse productivity and reduce costs. Specifically, a model library is created based on machine learning algorithms, and an intelligent optimization algorithm is designed based on the Non-Dominated Sorting Genetic Algorithm III (NSGA-3) and an expert experience knowledge base. Then, optimal environmental decision-making solutions under different greenhouse environments are obtained by adjusting the greenhouse environmental parameters. Our method’s effectiveness is verified through a simulated fertilization plan that was simulated for a real greenhouse tomato environment. The proposed optimization solution can reduce labor and time costs, enable accurate decision-making in the greenhouse environment, and enhance agricultural production efficiency. Full article

In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation methods that mainly rely on seismic, logging, and core data, which are difficult to meet the timeliness and accuracy of drilling operations. Firstly, the box method and normalization formula are used to process and normalize the abnormal data of element logging and engineering logging, and then the stepwise regression analysis method is used to optimize the sensitive parameters of element logging and engineering logging. The Light Gradient Boosting Machine (LightGBM) algorithm, deep neural network (DNN), and support vector machine (SVM) are used to establish a new method for predicting the development pattern of buried hill reservoirs. Lastly, a comprehensive evaluation index F1 score for the model is established to evaluate the prediction model for the development pattern of buried hill reservoirs. The F1 score value obtained from this model’s comprehensive evaluation index indicates that the LightGBM model achieves the highest accuracy, with 96.7% accuracy in identifying weathered zones and 95.8% accuracy in identifying interior zones. The practical application demonstrates that this method can rapidly and accurately predict the development mode of buried hill reservoirs while providing a new approach for efficient on-site exploration and decision-making in oil and gas field developments. Consequently, it effectively promotes exploration activities as well as enhances the overall process of oil and gas reservoir exploration. Full article

The performance and quality of steel products are significantly impacted by the alloying element control. The efficiency of alloy utilization in the steelmaking process was directly related to element yield. This study analyses the factors that influence the yield of elements in the steelmaking process using correlation analysis. A yield prediction model was developed using a t-distributed stochastic neighbor embedding (t-SNE) algorithm, a whale optimization algorithm (WOA), and a long short-term memory (LSTM) neural network. The t-SNE algorithm was used to reduce the dimensionality of the original data, while the WOA optimization algorithm was employed to optimize the hyperparameters of the LSTM neural network. The t-SNE-WOA-LSTM model accurately predicted the yield of Mn and Si elements with hit rates of 71.67%, 96.67%, and 99.17% and 57.50%, 89.17%, and 97.50%, respectively, falling within the error range of ±1%, ±2%, and ±3% for Mn and ±1%, ±3%, and ±5% for Si. The results demonstrate that the t-SNE-WOA-LSTM model outperforms the backpropagation (BP), LSTM, and WOA-LSTM models in terms of prediction accuracy. The model was applied to actual production in a Chinese plant. The actual performance of the industrial application is within a ±3% error range, with an accuracy of 100%. Furthermore, the elemental yield predicted by the model and then added the ferroalloys resulted in a reduction in the elemental content of the product by 0.017%. The model enables accurate prediction of alloying element yields and was effectively applied in industrial production. Full article

This article presents the results of cyanide leaching of gold-containing concentrate using the trichlorocyanuric acid (TCCA) oxidizer. Gold-containing concentrate was obtained from a gold tailings sample from a gold recovery factory (GRF) in one of the deposits of Kazakhstan that have not previously been studied for concentrability. According to X-ray phase analysis and energy dispersive spectrometry (DSM) data, the main compounds in the tailings sample under study are pyrite FeS₂, quartz SiO₂, calcite CaCO₃, albite NaAlSi₃O₈, muscovite KAl₂Si₃AlO₁₀(OH)₈, dolomite CaMg(CO₃)₂, and oxidized iron compounds. Microscopic studies of the concentrate have established the presence of ultrafine gold with sizes from Au 0.9 to 10.2 μm in pyrite. Obtaining the gold-containing concentrate with a gold content of 15.95 g/t is possible according to the enrichment scheme, which includes centrifugal separation, classification according to the fineness class −0.05 mm, additional grinding of hydrocyclone sands to a fineness of 90.0–95.0% of the class finer than 0.050 mm, and control centrifugal separation. Since pyrite in technogenic raw materials is the main gold-containing mineral, this paper presents studies on the oxidizability of pyrite with the TCCA oxidizer. The results of studies on the oxidation of pyrite using the TCCA oxidizer show the products of its hydrolysis oxidize pyrite with the formation of various iron compounds on its surface. Pretreatment of gold-containing concentrate with oxidizer TCCA for 3 h before the cyanidation process (20 h) allows for an increase in the recovery of gold in the solution by 5.8%. Full article

Due to its unique chemical structure, hydrogen energy inherently has a high calorific value without reinforcing global warming, so it is expected to be a promising alternative energy source in the future. In this work, we focus on nanoconfined hydrogen flow performance, a critical issue in terms of geological hydrogen storage. For nanopores where the pore scale is comparable to hydrogen’s molecular size, the impact on hydrogen molecules exerted by the pore surface cannot be neglected, leading to the molecules near the surface gaining mobility and slipping on the surface. Furthermore, hydrogen adsorption takes place in the nanopores, and the way the adsorption molecules move is completely different from the bulk molecules. Hence, the frequently applied Navier–Stokes equation, based on the no-slip boundary condition and overlooking the contribution of the adsorption molecules, fails to precisely predict the hydrogen flow capacity in nanopores. In this paper, hydrogen molecules are classified as bulk molecules and adsorption molecules, and then models for the bulk hydrogen and the adsorption hydrogen are developed separately. In detail, the bulk hydrogen model considers the slip boundary and rarefaction effect characterized by the Knudsen number, while the flow of the adsorption hydrogen is driven by a chemical potential gradient, which is a function of pressure and the essential adsorption capacity. Subsequently, a general model for the hydrogen flow in nanopores is established through weight superposition of the bulk hydrogen flow as well as the adsorption hydrogen, and the key weight coefficients are determined according to the volume proportion of the identified area. The results indicate that (a) the surface diffusion of the adsorption molecules dominates the hydrogen flow capacity inside nanopores with a pore size of less than 5 nm; (b) improving the pressure benefits the bulk hydrogen flow and plays a detrimental role in reducing surface diffusion at a relatively large pressure range; (c) the nanoconfined hydrogen flow conductance with a strong adsorption capacity (P_L = 2 MPa) could reach a value ten times greater than that with a weak adsorption capacity (P_L = 10 MPa). This research provides a profound framework for exploring hydrogen flow behavior in ultra-tight strata related to adsorption phenomena. Full article

Horizontal-well multi-cluster fracturing is one of the most important techniques for increasing the recovery rate in unconventional oil and gas reservoir development. However, under the influence of complex induced stress fields, the mechanism of interaction and propagation of fractures within each segment remains unclear. In this study, based on rock fracture criteria, combined with the boundary element displacement discontinuity method, a two-dimensional numerical simulation model of hydraulic fracturing crack propagation in a planar plane was established. Using this model, the interaction and propagation process of inter-cluster fractures under different fracturing sequences within horizontal well segments and the mechanism of induced stress field effects were analyzed. The influence mechanism of cluster spacing, fracture design length, and fracture internal pressure on the propagation morphology of inter-cluster fractures was also investigated. The research results indicate that, when using the alternating fracturing method, it is advisable to appropriately increase the cluster spacing to weaken the inhibitory effect of induced stress around the fractures created by prior fracturing on subsequent fracturing. Compared to the alternating fracturing method, the propagation morphology of fractures under the symmetrical fracturing method is more complex. At smaller cluster spacing, fractures created by prior fracturing are more susceptible to being captured by fractures from subsequent fracturing. The findings of this study provide reliable theoretical support for the optimization design of fracturing sequences and fracturing processes in horizontal well segments. Full article

A wide range of gluten-free bakery products are already available on the market. However, they often have a low proportion of fiber and inferior sensory properties when compared to classic baked goods. The aim of this work was to evaluate the influence of the addition of different types of fiber and insect powder on selected organoleptic and nutritional properties of gluten-free pieces of bread and to reformulate a recipe for gluten-free bread. Twenty experimental samples were prepared with different types and percentages of fiber, either alone or in combination. Sensory analysis, instrumental texture analysis, and chemical analyses, including predicted glycemic index, were carried out. A total of 16 of the 24 fiber-enriched samples received an average or slightly above-average rating. The samples containing the fiber mixture without insect powder and the sample containing 9% flaxseed performed best in the overall evaluation. The combination of different types of plant fibers simultaneously with the incorporation of insect powder in a low concentration appears to be advantageous, both from the viewpoint of sensory acceptability and also from the viewpoint of the potential for increasing the polyphenol content and antioxidant capacity. This study lists the sensorially acceptable range of fiber concentrations, which can be a guide for the bakery industry. Full article

This study investigates the phase equilibria of the Al-Mo-Hf ternary system at 400 °C and 600 °C using X-ray diffraction (XRD) and electron probe microanalysis (EPMA/WDS) techniques. Seven three-phase and five two-phase regions were identified at 400 °C, while eight three-phase and four two-phase regions were identified at 600 °C. Despite variations in the solid solubility ranges of certain compounds, the distribution of phase zones in the isothermal cross-section remained consistent at both temperatures. Using the experimental results and logical deductions, isothermal cross-sections were constructed for the Al-Mo-Hf ternary system at 600 °C and 400 °C. Full article

This paper presents a method to design a static output feedback active suspension controller for ride comfort improvement and motion sickness reduction in a real vehicle system. Full-state feedback controller has shown good performance for active suspension control. However, it requires a lot of states to be measured, which is very difficult in real vehicles. To avoid this problem, a static output feedback (SOF) controller is adopted in this paper. This controller requires only three sensor outputs, vertical velocity, roll and pitch rates, which are relatively easy to measure in real vehicles. Three types of SOF controller are proposed and optimized with linear quadratic optimal control and the simulation optimization method. Two of these controllers have only three gains to be tuned, which are much smaller than those of full-state feedback. To validate the performance of the proposed SOF controllers, a simulation is carried out on a vehicle simulation package. From the results, the proposed SOF controllers are quite good at improving ride comfort and reducing motion sickness. Full article

Further exploitation of the residual oil underground in post-polymer flooded reservoirs is attractive and challenging. Microbial-enhanced oil recovery (MEOR) is a promising strategy to enhance the recovery of residual oil in post-polymer flooded reservoirs. Identifying and selectively activating indigenous microorganisms with oil displacement capabilities is an urgent requirement in the current design of efficient microbial-enhanced oil recovery technologies. This study combines high-throughput sequencing with functional network analysis to identify the core functional microbes within the reservoirs. Concurrently, it devises targeted activation strategies tailored to oligotrophic conditions through an analysis of environmental factor influences. The feasibility of these strategies is then validated through physical simulation experiments. With nutrient stimulation, the overall diversity of microorganisms decreases while the abundance of functional microorganisms increases. The core displacement results showed that the oil recovery factor increased by 3.82% on the basis of polymer flooding. In summary, this research has established a system for the efficient activation of functional microorganisms under oligotrophic conditions by utilizing bioinformatics, network analysis, and indoor simulation systems. This achievement will undoubtedly lay a solid foundation for the practical implementation of microbial enhancement techniques in the field. Full article

The accurate calculation of the hotspot temperature of the cable intermediate joint can effectively guarantee the safe operation of the transmission and distribution network. This paper addresses the limitations of the current method of estimating hotspot temperature solely from surface temperature measurements. Specifically, we focus on a 110 kV single-core cable as our subject of study. We started by establishing a simulation model for the temperature field at the intermediate joint to generate data samples. Subsequently, the NCA (neighborhood component analysis) algorithm was employed to select the optimal measurement points on the cable’s surface. This allowed determination of the quantity and location of characteristic points. Finally, we developed a cascading inversion model, which consists of a radial inversion model and an axial inversion model, based on the extreme learning machine algorithm. The example results show that the mean squared error of hotspot temperature obtained by cascade inversion and direct inversion is 6.95 and 24.71, respectively, indicating that cascade inversion can effectively improve the inversion accuracy. Full article

Shale oil and gas wells usually experience a rapid decline in production due to their extremely low permeability and strong heterogeneity. As a crucial technique to harness potential and elevate extraction rates in aged wells (formations), refracturing is increasingly employed within oil and gas reservoirs globally. At present, the selection processes for refracturing, both of wells and layers, are somewhat subjective and necessitate considerable field data. However, the status of fracturing technology is difficult to control precisely, and the difference in construction effects is large. In this paper, well selection, formation selection, and the fracturing technology of shale oil and gas refracturing are deeply analyzed, and the technological status and main technical direction of refracturing technology at home and abroad are analyzed and summarized. The applicability, application potential, and main technical challenges of existing technology for different wells are discussed, combined with the field production dynamics. The results show that well and layer selection is the key to the successful application of refracturing technology, and the geological engineering parameters closely related to the remaining reservoir reserves and formation energy should be considered as the screening parameters. General temporary plugging refracturing technology has a low cost and a simple process, but it is difficult to accurately control the location of temporary plugging, and the construction effect is very different. Mechanical isolation refracturing technology permits the exact refurbishment of regions untouched by the initial fracturing. However, it is costly and complex in terms of construction. Consequently, cutting the costs of mechanical isolation refracturing technology stands as a pivotal research direction. Full article