Processes, Volume 12, Issue 6 (June 2024) – 176 articles

Surface acoustic wave (SAW) sensors in tunable oscillator configuration, with a deposited polymeric layer, were used to investigate the layer’s impact on the oscillator’s resonant frequency. The SAW oscillators were tuned by means of variable loop amplification. Full-range amplification variation led to a resonant frequency increase of ~1.7 MHz due to the layer’s nonlinear reaction. The layer’s morphology and location resulted in a specific resonant frequency–amplitude dependence. Five types of layers were used to test the causal linkage between the layers’ morphological parameters or positioning and the SAW oscillator’s resonant frequency. The frequency variation trend is almost linear, with a complex minute variation. Small amplitude sigmoids occur at certain attenuation values, due to layer acoustic resonances. Multiple sigmoids were linked with layer resonances of different orders. A good correlation between the layer’s thickness and resonance position was found. Full article

Resveratrol is a natural compound that can be found in red wine, grapes, and berries. It has attracted attention due to its potential health benefits. The aim of this review was to align ways of retaining resveratrol contents in berries and products made of berries, and to show which agricultural and processing techniques can maximize the content in the berries and their products and how this can be achieved. The scientific literature has revealed that resveratrol concentration in berries and berry-derived products varies significantly depending on the source and the processing techniques applied. Resveratrol content can range from 0.03–0.06 mg/kg in blueberries to 5–10 mg/kg in grape skins. Agricultural techniques such as controlled water stress (e.g., increasing resveratrol in grapes to 8.3–11.5 mg/kg), optimal sun exposure (e.g., enhancing blueberries to 1.5–2.1 mg/kg), balanced nutrient management, and selecting high-resveratrol cultivars (e.g., up to 15 mg/kg in certain grapes) can substantially increase resveratrol content. Processing methods like cold pressing, centrifugation, ultrafiltration, and freeze-drying are effective in preserving resveratrol levels, while traditional pasteurization tends to reduce its concentration. For instance, high-temperature short-time pasteurization can reduce resveratrol in juice from 1.5 mg/kg to 0.8 mg/kg, whereas cold pressing retains more resveratrol (1.5 mg/kg to 1.4 mg/kg). By optimizing these agricultural and processing techniques, manufacturers can enhance the resveratrol content in berry-derived products, meeting the growing consumer demand for health-enhancing natural products and supporting a healthier society. This approach aligns with the commitment to overcoming the technical challenges associated with resveratrol use, ensuring its potential is fully realized in both health-related and non-health-related applications. Full article

To improve the accuracy of offshore wind power foundation corrosion rate prediction and grasp the operation status of equipment in time, an offshore wind power foundation corrosion rate prediction model based on an improved spotted hyena optimization (SHO) algorithm is proposed in this paper. Firstly, in order to reduce the modeling workload of the offshore wind power foundation corrosion prediction model, kernel principal component analysis (KPCA) is used to extract the principal elements of the offshore wind power foundation corrosion rate. Secondly, for the problems in the SHO algorithm, it is easy to fall into local optimums, and the solution accuracy is not high; the SHO algorithm is improved by the convergence factor and Levy flight strategy, which gives the SHO algorithm stronger global search ability and convergence speed. Finally, based on the improved SHO algorithm, an offshore wind power base corrosion rate prediction model is established by optimizing the penalty parameter and kernel function parameter. Simulation results show that the average relative error, root mean square error, and global maximum relative error assimilation coefficient of the combined prediction model in this paper are 2.86%, 0.15, 3.74%, and 0.995, respectively, which are better than other corrosion prediction models. Full article

Understanding the degradation behavior of polymer composites is crucial for their practical application, especially in areas such as biomedicine and environmental engineering. In this study, we investigated the influence of titanium dioxide (TiO₂) particle size and content, containing 0.5, 1, 2, 5, and 10 wt% m/nTiO₂, on the degradation mechanism of biodegradable polycaprolactone (PCL) biocomposites. The degradation kinetics of the prepared biocomposites were evaluated using the Friedman method in conjunction with multivariate nonlinear regression facilitated by the Netzsch Thermokinetics software. The results indicate different degradation mechanisms for PCL biocomposites containing TiO₂ microparticles compared to biocomposites containing TiO₂ nanoparticles. However, the PCL biocomposites with TiO₂ microparticles showed a three-step degradation process, and the PCL biocomposites with TiO₂ nanoparticles exhibited a four-step degradation process. This difference can be attributed to the observed agglomeration of TiO₂ nanoparticles within the PCL matrix, which leads to an additional diffusion step in the degradation process. Interestingly, the addition of TiO₂ particles did not change the basic degradation mechanism of PCL but prolonged the degradation process to a higher conversion range. These findings shed light on the complicated interplay between the properties of the filler particles and the behavior of the polymer matrix and provide valuable clues for the design and optimization of biodegradable biocomposites. Full article

The goal of the present work was to study the recovery of copper, nickel, and platinum group metals (PGMs) (Pt and Pd) from low-grade copper–nickel ore containing pyrrhotite, pentlandite, and chalcopyrite by column bioleaching followed by cyanidation. The ore sample contained the following: Ni—0.74%, Cu—0.23%, Fe—14.8%, S_total—8.1%, and S_sulfide—7.8%. The Pt and Pd contents in the ore sample were 0.2535 and 0.515 g/t, respectively. Biological leaching in columns was carried out at 25, 35, and 45 °C for 140 days. A mixed culture of acidophilic microorganisms was used as an inoculum. Cu and Ni extraction depended on temperature, and at 45 °C, copper and nickel recovery was the highest, being 2.1 and 1.8 times higher than that at 25 °C, respectively. As a result, up to 35% of nickel and up to 10% of copper were recovered by bioleaching within 140 days. Bioleaching resulted in an increase in Pt and Pd recovery by cyanidation, but the effect on Pd recovery was insignificant. Pt recovery varied in the range of 3–40% depending on process conditions; Pd recovery was 44–55%. Full article

The goal of this research is to optimize the input parameters utilized in dry CNC drilling of forging steel to attain sustainable machining. Particular emphasis will be placed on achieving high productivity while minimizing the impact on surface quality. To achieve the aforementioned goal, three Taguchi-based multi-criteria decision-making (MCDM) approaches, such as traditional gray relational analysis (GRA), weighted gray relational analysis (WGRA), and data envelopment analysis ranking (DEAR), were used for simultaneous optimization of the MRR and Ra. In Taguchi’s L12 (2⁴) orthogonal array design, the cutting mode parameters—such as cutting speed, depth of cut, feed rate, and point angle—have been chosen as the input parameters for the modeling and analysis of the drilling process characteristics. The process of determining the effect of the input parameters on the output parameters was carried out with the use of analysis of variance (ANOVA). The best results from the studies were Ra = 2.19 and MRR = 375 mm³/s, which corresponded to Taguchi’s single optimization levels, S₂F₁D₁A₂ and S₂F₂D₂A₁, respectively. In the next step, the performance values obtained for each MCDM technique were reoptimized using the Taguchi method, and the optimal levels were obtained: for traditional GRA, the level S₂F₁D₂A₁ (Ra = 2.52 µm, MRR = 125 mm³/s); for WGRA, the level S₂F₁D₁A₁ (Ra = 2.31 µm, MRR = 83 mm³/s); and for DEAR, the level S₂F₂D₂A₁ (Ra = 4.42 µm, MRR = 375 mm³/s), respectively. Lastly, in order to compare the experiments’ performance, validation tests were carried out. The results of the experiments using multi-objective optimization show that traditional GRA improved the overall quality response characteristics by 29.86% compared to the initial setup parameters, while weighted GRA improved them by 34.48%, with the DEAR method providing an improvement of 96%. Based on the findings of this investigation, the DEAR optimization method outperforms the GRA method. As a result, the proposed methods are useful tools for multi-objective optimization of cutting parameters. Full article

Railway transportation is one of the main modes of long-distance coal transportation, and it inevitably causes environmental pollution during the transportation process. In order to improve the environment along the railway and increase the utilization rate of coal resources, this paper proposes a detection algorithm for the scattered coal solidification layer during transportation based on the YOLOv8 model and designs an intelligent recognition model suitable for coal solidification layer detection devices by combining fluorescence detection methods. Through experimental analysis, we found that the model meets the requirements of practical detection and can play a crucial role in environmental protection, with high practical application value. Full article

At present, the methods for sulfur solubility testing of high-sulfur natural gas generally use laboratory proportioning gas samples and then connect equipment to test the sulfur solubility of the gas samples based on the adsorption deposition mechanism. However, these testing methods generally have the following problems: (1) The equipment used in these test methods has safety hazards such as leakage at pipe and valve connections. (2) The sulfur solubility of real gas samples cannot be measured directly. (3) The equipment is difficult to clean, and it is especially difficult to clean the sulfur deposited at pipe elbows and valve connections. This will lead to low sulfur solubility test results. (4) The thermal insulation performance during the test process is not good, and temperature changes have a great impact on gas volume measurement. In order to solve the above problems, a testing method and comprehensive experimental device for the solubility of elemental sulfur in high-sulfur natural gas were established. This test method wraps the entire experimental device with a metal shell, which has good safety and thermal insulation performance, and it uses customized pipeline connections, which have high flushing efficiency, less sulfur deposition, and more accurate experimental results. The upgraded filtration system can directly measure the sulfur dissolution of real gas samples, and a CS₂ solution recovery process is added to reduce the risk of leakage and environmental pollution. This method and equipment were used to test the elemental sulfur solubility determination of real gas samples from a high-sulfur gas well. The research results show that the solubility of elemental sulfur is related to temperature, pressure, and H₂S concentration and increases with the increase in temperature, pressure, and H₂S concentration. Compared with the previous method, this method has less residual sulfur during the test process, the measured sulfur solubility is 2.13% greater, and the test results are more accurate and reliable. This research result provides important basic data support for accurately measuring the elemental sulfur solubility of real gas samples in high-sulfur gas reservoirs and dealing with sulfur deposition problems. Full article

In the present paper, we describe a series of laboratory experiments on the friction between rigid indenters with different geometrical forms and an elastic sheet of elastomer as a function of the normal load. We show that the law of friction can be controlled by the shape of the surface profile. Since the formulation of the adhesive theory of friction by Bowden and Tabor, it is widely accepted and confirmed by experimental evidence that the friction force is roughly proportional to the real contact area. This means that producing surfaces with a desired dependence of the real contact area on the normal force will allow to “design the law of friction”. However, the real contact area in question is that during sliding and differs from that at the pure normal contact. Our experimental studies show that for indenters having a power law profile f(r) = c_nrⁿ with an index n < 1, the system exhibits a constant friction coefficient, which, however, is different for different values of n. This opens possibilities for creating surfaces with a predefined coefficient of friction. Full article

Ultrasound-assisted extraction is an interesting tool for obtaining bioactive compounds from plant matrices applicable as agricultural bio-inputs, as it increases the extraction efficiency, reducing the process time and the use of solvents. This technique uses ultrasonic waves to break down plant cell walls, releasing bioactive compounds quickly and effectively and promoting a sustainable path to obtaining bio-inputs. Accordingly, this research study reports pioneering results regarding the herbicidal and fungicidal potential of different extracts obtained from Senecio brasiliensis (samples from flowers, leaves, and stalks) and Solanum viarum (samples from fruits and roots), two weeds typically found in rural areas of South America. The fungicidal activity of the samples was tested on two fungi, i.e., Fusarium graminearum and Sclerotinia sclerotiorum, while the herbicidal action of the extracts was evaluated in pre-emergence tests in cucumber (Cucumis sativus) seeds. The successful results indicated a high antifungal and herbicidal potential of the extracts obtained for both weeds, with the inhibitory effect against both fungi achieving up to 82%, and the inhibition of C. sativus seed germination reaching 100% for all samples. Full article

For low costs, numerical simulation is an effective method to reveal the internal mechanisms inside a thermal plasma torch. Various simulation models for studying the inside or outside characteristics of thermal plasma torches have been built and discussed. However, to reveal the inside mechanisms of thermal plasma torches under various working conditions to support the materials processing, more attention should be paid to building precise models of laminar plasma torches. Thus, based on the user-defined function (UDF) and user-defined scalar (UDS) of ANSYS Fluent software, the assumptions, governing equations, boundary conditions, and solving method were discussed in detail, and a corresponding numerical model of a homemade laminar plasma torch was first built. For verifying the effectiveness of the proposed numerical model and studying the influence of the gas components on the arc characteristics, the working conditions and experimental setups were introduced in sequence. Finally, the numerical and experimental results of the homemade laminar plasma torch were obtained and discussed in detail. The study results show that: ① The axial temperature of the plasma torch could be divided into three sections along the axis: peak temperature area (10 mm < x < 20 mm), stable temperature area (20 mm < x < 62 mm) and decrease temperature area (62 mm < x < 95 mm). Under the same input conditions, when pure argon gas was used, the peak temperature at the outlet was reached at approximately 7590 K, while for pure nitrogen and 50%Ar + 50%N₂, the corresponding peak temperatures were 6785 K and 7402.2 K, respectively. ② The axial velocity of pure nitrogen is much higher than that of pure argon and 50%Ar + 50%N₂, while that of pure argon and 50%Ar + 50%N₂ has little difference. In addition, when nitrogen gas was used, the peak velocity at the outlet reached 185 m/s, whereas, for argon gas and 50%Ar + 50%N₂, the corresponding peak velocities were 146 m/s and 169 m/s, respectively. ③ The simulated arc voltage trends under different working conditions are well in accordance with the experimental arc voltage trends. Full article

Lipase is one of the most commonly used biocatalysts in the food, pharmaceutical and cosmetic industries, and can be produced by Yarrowia lipolytica yeast. Despite the intensive studies of lipase from Yarrowia, there are still many open questions regarding the enzyme secretion process, especially by new isolates of this genus as well as the effect of substrates or surfactants, or both on the production of lipase. This research focused on the effect of olive oil and surfactant Tween 80 including the optimisation of the concentration of these compounds on the production of lipase by some novel Yarrowia isolates. Moreover, the optimal environmental parameters (pH, temperature) of crude enzyme synthetised by Yarrowia strains were determined. All investigated strains were able to produce lipase in both intracellular and extracellular fractions. The extracellular lipase activities were higher than the intracellular ones (Y. divulgata Y.02062 and Yarrowia lipolytica 854/4 147 U/L, 80 U/L and 474 U/L, 122 U/L, respectively). In the case of extracellular lipase, supplementing olive oil and Tween 80 enhanced significantly the synthesis and secretion of the enzyme. The lipase activity can even be enhanced by 20 times higher from 25 U/L to 474 U/L in the case of Yarrowia lipolytica 854/4 strain. In the case of intracellular, supplementation of Tween 80 generally reduces lipase activity except for the Y. lipolytica 1/4 strain, which was affected by two times the increase. The optimised concentration of olive oil and Tween 80 were determined for Y. divulgata Y.02062, Y. divulgata 5257, Y. lipolytica 1/4, and Yarrowia lipolytica 854/4 strains as 1.6% olive oil and 0.09% Tween 80, 1.6% olive oil and 0.06% Tween 80, 1.4% olive oil and 0.09% Tween 80 as well as 1.6% olive oil and 0.065% Tween 80, respectively. The optimum pH and temperature of crude lipases (intra and extracellular) synthetised by the tested Yarrowia lipolytica and Y. divulgata yeast strains were found to be pH 7.2 and 37 °C, respectively. Our results confirmed that the new isolate Y. divulgata is a very promising species for further development for industrial use as Y. lipolytica. Full article

The precise forecasting of rockburst is fundamental for safeguarding human lives and property, upholding national energy security, and protecting social welfare. Traditional methods for predicting rockburst suffer from poor accuracy and extended model training durations. This paper proposes a distributed training rockburst prediction method called Distriformer, which uses deep learning technology combined with distributed training methods to predict rockburst. To assess the efficacy of the Distriformer rockburst model proposed herein, five datasets were used to compare the proposed method with Transformer and Informer. The experimental results indicate that, compared with Transformer, the proposed method reduces the absolute error by 44.4% and the root mean square error by 30.7% on average. In terms of training time, the proposed method achieves an average speedup ratio of 1.72. The Distriformer rockburst model enhances the accuracy of rockburst prediction, reduces training time, and serves as a reference for developing subsequent real-time prediction models for extensive rockburst data. Full article

The high production rate of fossil-based plastics, coupled with their accumulation and low degradability, is causing severe environmental problems. As a result, there is a growing interest in the use of renewable and natural sources in the polymer industry. Specifically, rice bran is a highly abundant by-product of the agro-food industry, with variable amounts of protein and starch within its composition, which are usually employed for bioplastic development. This study aims to valorize rice bran through the production of nanofiber membranes processed via electrospinning. Due to its low solubility, the co-electrospinning processing of rice bran with potato starch, known for its ability to form nanofibers through this technique, was chosen. Several fiber membranes were fabricated with modifications in solution conditions and electrospinning parameters to analyze their effects on the synthesized fiber morphology. This analysis involved obtaining micrographs of the fibers through scanning electron microscopy (SEM) and fiber diameter analysis. Potato starch membranes were initially investigated, and once optimal electrospinning conditions were identified, the co-electrospinning of rice bran and potato starch was conducted. Attempts were made to correlate the physical properties of the solutions, such as conductivity and density, with the characteristics of the resulting electrospun fibers. The results presented in this study demonstrate the potential valorization of a rice by-product for the development of bio-based nanofibrous membranes. This not only offers a solution to combat current plastic waste accumulation but also opens up a wide range of applications from filtration to biomedical devices (i.e., in tissue engineering). Full article

The reservoir type of the MH oil field in the Junggar Basin is a typical low-permeability conglomerate reservoir. The MH oilfield was developed by water injection in the early stage. Nowadays, the reservoir damage is serious, and water injection is difficult. There is an urgent need to carry out conversion injection flooding research to improve oil recovery. The use of CO₂ oil-flooding technology can effectively supplement formation energy, reduce greenhouse gas emissions, and improve economic benefits. In order to clarify the feasibility of CO₂ flooding to improve oil recovery in conglomerate reservoirs with low permeability, strong water sensitivity, and severe heterogeneity, this paper researched the impact of CO₂ miscibility on production characteristics and mechanisms through multi-scale experiments. The aim was to determine the feasibility of using CO₂ flooding to enhance oil recovery. This study initially elucidated the oil displacement characteristics of varying degrees of miscibility in different dimensions using slim tube experiments and long core experiments. Subsequently, mechanistic research was conducted, focusing on the produced oil components, changes in interfacial tension, and conditions for pore mobilization. The results indicate that the minimum miscibility pressure (MMP) of the block is 24 MPa. Under the slim tube scale, the increase in the degree of miscibility can effectively delay the gas breakthrough time; under the core scale, once the pressure reaches the near mixing phase, the drive state can transition from a non-mixed “closed-seal” to a “mixed-phase” state. Compared to the immiscible phase, the near-miscible and completely miscible phase can improve the final recovery efficiency by 9.27% and 18.72%. The component differences in the displacement products are mainly concentrated in the high-yield stage and gas breakthrough stage. During the high-yield stage, an increase in miscibility leads to a higher proportion of heavy components in the produced material. Conversely, in the gas breakthrough stage, extraction increases as the level of mixing increases, demonstrating the distinct extracting characteristics of different degrees of mixed phases. The core experiences significant variations in oil saturation mostly during the pre-gas stage. CO₂ miscible flooding can effectively utilize crude oil in tiny and medium-sized pores during the middle stage of flooding, hence reducing the minimum threshold for pore utilization to 0.3 μm. Full article

Due to the time-varying, hysteresis and nonlinear characteristics of fertilizer concentration control in the water–fertilizer ratio control system, common control algorithms such as PID and fuzzy PID cannot obtain the expected control effect. In order to accurately control the cotton field water–fertilizer ratio regulation system drip irrigation process of the water–fertilizer ratio that will be controlled within a reasonable range, it is needed to design a bat-optimized variable-domain fuzzy PID water–fertilizer ratio control strategy, through the use of bat algorithm to find out the optimal expansion factor and the best domain of the current conditions, and then according to the changes in working conditions to automatically adjust the fuzzy control of the domain, through the control of the valve openings to change the fertilizer pump back to the amount of water. Realize the fast and precise control of fertilizer concentration in the water–fertilizer ratio control system. Comparative tests were conducted to verify the traditional PID, fuzzy PID, variable domain fuzzy PID and bat-optimized variable-domain fuzzy PID control algorithms. The results show that: if the water–fertilizer ratio is adjusted to 50:1 from the startup, the adjustment time required to reach the target water–fertilizer ratio under the bat-optimized variable-domain fuzzy PID control is 15.29 s, and the maximum overshooting amount is 16.28%, which is a smaller adjustment time and overshooting amount; if the water–fertilizer ratio is adjusted to 40:1 from 50:1, the advantages of bat-optimized variable-domain fuzzy PID are more obvious, with the best balance of response speed, overshooting amount and optimal control effect. In terms of response speed, overshooting amount and regulation time, the optimal balance is achieved, showing the optimal control effect. It is proved that the performance of the water–fertilizer ratio regulation system in cotton field under bat-optimized variable-domain fuzzy PID control designed in this paper can meet the actual production requirements, and these findings can help to develop precise irrigation technology for cotton cultivation under drip irrigation conditions. Full article

Utilizing renewable energy sources to produce hydrogen is essential for promoting cleaner production and improving power utilization, especially considering the growing use of fossil fuels and their impact on the environment. Selecting the most efficient method for distributing power and capacity is a critical issue when developing hybrid systems from scratch. The main objective of this study is to determine how a backup system affects the performance of a microgrid system. The study focuses on power and hydrogen production using renewable energy resources, particularly solar and wind. Based on photovoltaics (PVs), wind turbines (WTs), and their combinations, including battery storage systems (BSSs) and hydrogen technologies, two renewable energy systems were examined. The proposed location for this study is the northwestern coast of Saudi Arabia (KSA). To simulate the optimal size of system components and determine their cost-effective configuration, the study utilized the Hybrid Optimization Model for Multiple Energy Resources (HOMER) software (Version 3.16.2). The results showed that, when considering the minimum cost of energy (COE), the integration of WTs, PVs, a battery bank, an electrolyzer, and a hydrogen tank brought the cost of energy to almost 0.60 USD/kWh in the system A. However, without a battery bank, the COE increased to 0.72 USD/kWh in the same location because of the capital cost of system components. In addition, the results showed that the operational life of the fuel cell decreased significantly in system B due to the high hours of operation, which will add additional costs. These results imply that long-term energy storage in off-grid energy systems can be economically benefited by using hydrogen with a backup system. Full article

It is essential to determine the most suitable machining method for magnesite-reinforced Aluminium 6061 composites, which possess excellent mechanical properties, especially notable tensile strength and hardness. The composites were produced using a stir-casting technique, incorporating reinforcements of lightly-calcined magnesite, dead burnt magnesite, and waste magnesite in weight fractions of 2.5%, 5%, and 7.5% within an aluminium 6061 matrix. Wire electrical discharge machining was employed to investigate the machining characteristics of these composites, using controllable process parameters such as cutting speed, pulse-on and pulse-off times, and the weight fraction of magnesites. Two performance indicators such as surface roughness and material removal rate were tested for various parameter combinations by central composite design. To comprehend the impact of the study parameters, contour charts were drawn. MRR increases at a high cutting speed of 2 mm/min when the pulse-on time changes from 120 μs to 125 μs. SR increases when the pulse-on times above 120 μs at all cutting speeds. High cutting speeds make high MRR irrespective of the weight fractions of reinforcement. High pulse-on times make the material melt more, which increases the material removal rate. Because specimen surface material erodes quickly and forms microcracks, high pulse-on time also results in high surface roughness. To optimize the WEDM machining conditions for each composite, hybrid SSO-DF and DFO-DF optimizers were developed by combining the desirability function with Salp-swarm optimization and Dragonfly optimization algorithms. The cutting speed of 2 mm/min and the pulse-on time of 114 μs produce the best performances on the composites. Full article

In this article, we present a modification to the Economic Dispatch (ED) model that addresses the non-convex nature of the cost curves associated with a Combined Cycle Power Plant (CCPP). Incorporating a binary variable provides greater precision in solving the combinatorial problem in only one simulation and, most importantly, demonstrates cost minimization among the three different cost curve models for dispatching the CCPP. Our results highlight the importance of considering different demand scenarios based on a reference forecast for one day ahead. Therefore, piecewise modeling is more feasible for solving the non-convex problem, showing greater accuracy regarding the operational state of the CCPP and avoiding the cost overestimation that occurs with traditional models. Moreover, it allows the operators to manage costs better and optimize generation potential, ultimately showing economic benefits for the system operator. Full article

This research focuses on the drying kinetics of industrial pineapple processing waste on a flat plate, revealing a two-phase drying process: an initial phase with a constant drying rate followed by a phase with a decreasing drying rate. During the constant rate phase, the convective mass transfer coefficient, influenced by temperature variations from 40 to 70 °C, ranged from 5.69 × 10⁻⁷ to 2.79 × 10⁻⁷ m s⁻¹. The study introduced a novel approach to modeling the decreasing drying rate phase, applying equations derived from the Fick equation. This process involved determining the activation energy and thermodynamic properties of drying using an experimental forced convection dryer at temperatures of 40, 50, 60, and 70 °C, and an air velocity of 1.5 m/s. Data were fitted to several mathematical models, including Fick’s with four series terms, and versions of the Henderson–Pabis and Page models modified by Cavalcanti-Mata, among others. The Cavalcanti-Mata and modified Page models provided the most accurate fit to the experimental data. Results showed that diffusion coefficients vary per model yet align with literature values. Additionally, enthalpy (ΔH) and entropy (ΔS) values decreased with temperature, while Gibbs free energy (ΔG) increased, indicating that drying is an energy-dependent, non-spontaneous process. Full article

Failure Mode and Effect Analysis (FMEA) is an essential risk analysis tool that is widely applicable in various industrial sectors. This structured technique allows us to identify and assign priority levels to potential failures that violate the reliability of a system or process. Failure evaluation occurs in a decision-making environment with uncertainty. This study proposes a probabilistic fuzzy system that integrates linguistic and stochastic uncertainty based on a Mamdani-type model to strengthen the FMEA technique. The system is based on analyzing the frequency of failures and obtaining the parameters to determine the probability of occurrence through the Poisson distribution. In addition, the severity and detection criteria were evaluated by the experts and modeled using the Binomial distribution. The evaluation result is a discrete value analogous to the process of obtaining the success or failure of the expert generating the evaluation of 10 Bernoulli experiments. Three fuzzy inference expert systems were developed to combine multiple experts’ opinions and reduce linguistic subjectivity. The case study was implemented in the knitting area of a textile company in the south of Guanajuato to validate the proposed approach. The potential failure of the knitting machinery, which compromises the top tension subsystem’s performance and the product’s quality, was analyzed. The proposed system, which is based on a robust mathematical model, allows for reliable fault evaluation with a simple scale. The classification performed by the system and the one performed by the experts has similar behavior. The results show that the proposed approach supports decision-making by prioritizing failure modes. Full article

The emerging concept of hybrid nanofluids has grabbed the attention of researchers and scientists due to improved thermal performance because of their remarkable thermal conductivities. These fluids have enormous applications in engineering and industrial sectors. Therefore, the present research study examines thermal and mass transportation in hybrid nanofluid past an inclined linearly stretching sheet using the Maxwell fluid model. In the current problem, the hybrid nanofluid is engineered by suspending a mixture of aluminum oxide Al₂O₃ and copper Cu nanoparticles in ethylene glycol. The fluid flow is generated due to the linear stretching of the sheet and the sheet is kept inclined at the angle ζ = π/6 embedded in porous medium. The current proposed model also includes the Lorentz force, solar radiation, heat generation, linear chemical reactions, and permeability of the plate effects. Here, in the current simulation, the cylindrical shape of the nanoparticles is considered, as this shape has proven to be excellent for the thermal performance of the nanomaterials. The governing equations transformed into ordinary differential equations are solved using MATLAB bvp4c solver. The velocity field declines with increasing magnetic field parameter, Maxwell fluid parameter, volume fractions of nanoparticles, and porosity parameter but increases with growing suction parameter. The temperature drops with increasing magnetic field force and suction parameter values but increases with increasing radiation parameter and volume fraction values. The concentration profile increases with increasing magnetic field parameters, porosity parameters, and volume fractions but reduces with increasing chemical reaction parameters and suction parameters. It has been noted that the purpose of the inclusion of thermal radiation is to augment the temperature that is serving the purpose in the current work. The addition of Lorentz force slows down the speed of the fluid and raises the boundary layer thickness, which is visible in the current study. It has been concluded that, when heat generation parameters increase, the temperature field increases correspondingly for both nanofluids and hybrid nanofluids. The increase in the volume fraction of the nanoparticles is used to enhance the thermal performance of the hybrid nanofluid, which is evident in the current results. The current results are validated by comparing them with published ones. Full article

Adsorbent materials have long been used for remediating environmental contaminants. There is an increasing focus on developing sustainable adsorbent materials for long-term use in environmentally friendly and cost-effective remediation. “Green” or “eco-friendly” sorbent materials are generally prepared from renewable or recycled resources, have minimal toxic effects, involve synthesis processes with minor chemical or energy footprints, have high reusability, and do not contribute to additional waste or contamination. Thus, it is essential for materials to have high sorption capacity, high stability, and reusability. The literature focuses on using low-cost or waste materials to produce sorbent materials for the immobilization of contaminants from soil and water systems. The regeneration possibilities of adsorbents are used to evaluate their cost effectiveness and long-term environmental impact once they are applied at field-scale. This review evaluates sustainable sorbent materials, highlighting their green and eco-friendly qualities for a circular economy, and their contribution to the United Nations Sustainable Development Goals (UNSDG). The synthesis techniques, ecotoxicity, and prospect of reusing adsorbents are highlighted. Further, the review provides insights for researchers and practitioners interested in developing and applying green adsorbents, including bio-based carbon, char, and fibrous materials for soil and water remediation. Full article

To address the significant challenges in determining the single-well production of tight gas and shale gas after hydraulic fracturing, artificial intelligence (AI) methods were implemented. Machine learning (ML) algorithms such as random forest (RF), extremely randomized trees (ET), lightweight gradient boosting machines (LightGBM), gradient boosting regression (GBR), and linear regression (LR) were utilized in conjunction with reservoir geology, engineering parameters, and production data to develop several foundational models for forecasting the production of unconventional gas wells. The accuracy of these models was evaluated. Based on this, improvements in the models’ predictive accuracy and generalizability were achieved through the ensemble of machine learning models. Furthermore, this paper selected two representative tight and shale gas reservoirs to demonstrate the application of the ensemble model for well production forecasting, and a comparative analysis with actual production data was conducted. For tight gas reservoir A, the blending model achieved an MAE of 0.8419 and an MSE of 1.0930, with an R² score of 0.8812. For shale gas reservoir B, the blending model achieved an MAE of 1.4841 and an MSE of 3.1629, with an R² score of 0.9524. The results of the case studies indicate that the ensemble model approach employed in this study has a higher predictive accuracy and reliability than a single machine learning algorithm, and is capable of handling high-dimensional, large-scale, and imbalanced data, offering scientific validation and technical support for the assessment of the well productivity in tight and shale gas wells. Full article

Ventilation air methane (VAM) from coal mining is a low-grade energy source that can be used in combustion systems to tackle the energy crisis. This work presents a numerical analysis of the thermal and stabilization performance of a VAM-fueled thermal reversal reactor with three fixed beds. The effects of the combustion chamber/regenerator height ratio (β), heat storage materials, and porosity on the oxidation characteristics are evaluated in detail. It is shown that the regenerator temperature tends to vary monotonically with β due to the coupling effect of the gas residence time and heat transfer intensity. The optimal β is determined to be 4/6, above which the system may destabilize. Furthermore, it is found that regardless of the methane volume fraction, the regenerator with mullite inserted has the highest temperature among the heat storage materials investigated. In contrast, the temperature gradually decreases and the system becomes unstable as SiC is adopted, signifying the importance of choosing proper thermal diffusivity. Further analysis reveals that the porosity of the heat storage materials has little effect on the system stability. Decreasing the porosity can effectively reduce the oscillation amplitude of the regenerator temperature, but it also results in greater pressure losses. Full article

Lactic acid bacteria can synthesize extracellular exopolysaccharides (EPSs) that have versatile physicochemical and biological properties. In this paper, the EPSs synthesized by Lacticaseibacillus rhamnosus ŁOCK 0943 were characterized. Their structure, biological, and technological activity, as well as application potential, were analyzed. Chemical analysis showed that this strain produces mannan and β-1,6-glucan. Their emulsifying, antagonistic, and antioxidant properties, along with their prebiotic potential, were assessed. The analysis of the tested polymers’ ability to create a stable emulsion showed that their emulsifying activity depends mainly on the type of oily substance used. The analysis of the antagonistic activity revealed that these EPSs can inhibit the growth of yeasts (e.g., Candida albicans ATCC 10231) and potentially pathogenic bacteria (e.g., Clostridium acetobutylicum ŁOCK 0831, Enterococcus faecalis ATCC 29212). Moreover, EPSs positively influenced the growth of all tested probiotic bacteria. Furthermore, EPSs can be successfully used as a preservative in cosmetic products. The most effective results were obtained with the use of a 0.05% solution of a chemical preservative (bronopol) and 0.25 mg/mL of the EPSs. Full article

Mishrif (M) reservoir of Faihaa (F) oilfield in Iraq is a heterogeneous porous carbonate reservoir. The reservoir properties of each reservoir unit differ greatly, and the distribution of porosity and permeability is non-uniform. Some reservoir units have the problem that the expected production cannot be achieved or the production decline rate is too fast after matrix acidification. This work optimized and compared the process of acid fracturing and hydraulic fracturing techniques. The Mishrif B (MB) and Mishrif C (MC) layers are selected as the target units for fracturing and the perforation intervals are optimized. The acid fracturing process adopted the acid fracturing technology of guar gum pad fluid and gelled acid multi-stage injection. According to the wellhead pressure limit and fracture propagation geometry, the pumping rate is optimized. The recommended maximum pumping rate of acid fracturing is 5.0 m³/min, and the optimized acid volume is 256.4 m³. The pressure changes during hydraulic fracturing and acid fracturing are different. It is recommended that the maximum hydraulic fracturing pump rate is 4.5 m³/min for MB and MC layers, and the amount of proppant in MB and MC layers is 37.5 m³ and 43.7 m³, respectively. The production prediction of two optimized processes is carried out. The results showed that the effect of acid fracturing in MB and MC layers is better than hydraulic fracturing, and it is recommended to adopt acid fracturing technology to stimulate MB and MC layers. Acid fracturing operation is carried out in the X-13 well, and better application results are achieved. The results of this study provide optimized reference ideas for reservoir stimulation in heterogeneous porous reservoirs. Full article

In the field of oilfield fracturing development, a profound understanding of the evolution and propagation of damage during the fracturing process is crucial for preventing well water coning and channeling. This study aimed to unravel the complexity of damage evolution during fracturing and elucidate the causes of well water flooding phenomena. To accurately describe the damage propagation laws, a damage constitutive model considering compaction and post-peak correction parameters was established in this research. The model, through parameter adjustment, enhances the precision of stress calculation during the rock compaction phase and accounts for the stress degradation pattern subsequent to damage. This model was applied to simulate the damage evolution under various conditions in oil layer profiles and wellbore cross-sections, including the impact of different perforation angles, natural fracture patterns, and the ratio of longitudinal to transverse boundary pressures. The research concludes that well water channeling and flooding are primarily caused by damage propagation and the connectivity with adjacent water-bearing formations. The proposed rock damage constitutive model demonstrated an accuracy improvement of more than 3% compared to previous studies. Additionally, the study discovered that when the angle between the perforation section and the formation exceeds 30°, the risk of fracture propagation into adjacent layers increases, leading to an elevated risk of post-fracturing water flooding. The presence of natural fractures in the oil layer provides a conduit for damage propagation, accelerating the process of damage in the oil layer. Furthermore, the perforation angle and the ratio of boundary pressure loads during the fracturing process were identified as the main factors influencing the direction change of fracture propagation. The conclusions drawn from this study provide a scientific basis for preventing post-fracturing water channeling and flooding issues and offer new perspectives for the development of well fracturing technology, aiding in the resolution of water flooding problems associated with well fracturing. Full article

Heavy metals such as copper, often discharged from industrial processes and agricultural activities, pose significant environmental and health risks due to their toxicity, particularly in the soluble form of Cu (II). This study investigates the effectiveness of biochar produced from date palm leaf midrib waste via a two-step pyrolysis process, as a sustainable and economical adsorbent for removing Cu (II) from aqueous solutions The biochar was characterized using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), Fourier-transform infrared spectroscopy (FTIR), and Brunauer–Emmett–Teller (BET) surface area analysis. Adsorption experiments were conducted to evaluate the effects of pH, adsorbent dosage, contact time, and initial Cu (II) concentration. The maximum adsorption capacity was observed at pH 6, with a capacity of 70 mg/g. The adsorption data were best described by the pseudo-second-order kinetic model, indicating chemisorption as the primary mechanism. Thermodynamic studies indicated that the adsorption process was spontaneous and exothermic, with a Gibbs free energy change (ΔG) of −1.245 kJ/mol at 25 °C, enthalpy change (ΔH) of −15.71 kJ/mol, and entropy change (ΔS) of 48.36 J/mol·K. Reusability tests demonstrated that the biochar retained over 85% of its initial adsorption capacity after five cycles, with capacities of 60 mg/g in the first cycle, decreasing to 52 mg/g by the fifth cycle. This study highlights the potential of biochar derived from date palm waste as an efficient, sustainable adsorbent for the removal of Cu (II) from wastewater, contributing to both environmental management and waste valorization. Future research should focus on optimizing the biochar production process and exploring its application for the removal of other contaminants. Full article

This article is devoted to the problem of signal decomposition into periodic and aperiodic components. According to the proposed approach, there is no need to evaluate the aperiodic component as a difference between the total signal of its periodic components. This research aims to create a general analytical approach that combines the Fourier and Maclaurin series methodologies into a single comprehensive series. As a result, analytical expressions for determining deposition coefficients were established for an aperiodic signal with a monoharmonic overlay. Recurrence relations were established to determine the coefficients of this series. These relations allow direct integrations of the obtained values of integrals to be avoided. The evaluated numerical values of the coefficients are also presented graphically and tabulated. It was proven that the values of these coefficients are universal numbers since they do not depend on the period/frequency of oscillations. The reliability of the proposed approach was confirmed by the fact that the evaluated coefficients are equal to the Fourier series coefficients in the case of a periodic signal. Also, for an aperiodic signal, these coefficients were reduced to the coefficients of the Maclaurin series. The usability of the proposed generalized analytical approach for signal decomposition is for control and monitoring systems of processes. Full article