Processes, Volume 12, Issue 5 (May 2024) – 90 articles

The formation of solid deposits in the process of supercritical water gasification (SCWG) is one of the main problems hindering the commercial application of the process. Seven experiments were conducted with the grass Reed Canary Grass with different preheating temperatures, but all ended early due to the formation of solid deposits (maximum operation of 3.8 h). The position of solid deposits in the lab plant changed with the variation in the temperature profile. Since the formation of solid deposits consisting of salts, coke, and corrosion products is a severe issue that needs to be resolved in order to enable long-time operation, inner temperature measurements were conducted to determine the temperature range that corresponds with the zone of solid formation. The temperature range was found to be 400 to 440 °C. Wherever this temperature was first reached solid deposits occurred in the system that led to blockage of the flow. Additional to the influence of the temperature, the influence of the flow direction (up-flow or down-flow) on the operation of the continuous SCWG plant was examined. If salts are not separated from the system sufficiently, up-flow reactors should be avoided because they amplify the accumulation of solid deposits leading to a shortened operation time. The heating concept coupled with the salt separation needs to be redesigned in order to separate the salts before entering the gasification reactors. Outside of the determined temperature zone no deposition was visible. Thus, even though the gasification efficiency was low it could be shown that the operation was limited to the deposits forming in the heating section and not by incomplete gasification in the reactor where T > 600 °C. Full article

During the operation of non-clogging pumps, the flexible long fiber is prone to clogging and winding during the flow process, which can result in damage to the non-clogging pump, so a numerical simulation method of a solid–liquid two-phase flow in a non-clogging pump with a flexible long fiber is proposed in this paper. The unsteady numerical simulation of the two-phase flow of a single flexible fiber with different densities, lengths and diameters in a double-blade non-clogging pump was carried out to study the influence of fiber parameters on fiber transport capability. The results show that at a density of 920 kg/m³, 300 kg/m³ and 732 kg/m³, the transport capability of flexible fibers decreases successively, and the transport time T₀ is 0.32 s, 0.36 s and 0.48 s, respectively. The transport capability of flexible fibers with a length of 150 mm, 200 mm and 250 mm decreases successively, and the transport time T₀ is 0.34 s, 0.48 s and 0.96 s, respectively. The transport time T₀ is 0.48 s when the fiber diameter d_p is 5 mm. When the fiber diameter d_p is 7.5 mm, the transport time T₀ is 0.51 s. When the fiber diameter d_p is 10 mm, the fiber transport capability of the non-clogging pump decreased significantly, and the transport time T₀ is 0.68 s. The fiber length has the most obvious effect on fiber transport capability, followed by the fiber diameter and fiber density. Full article

Plasma technology is increasing its applications in the textile industry for conferring surface functionalities through greener processes. In this study, plasma treatments are studied to improve the wettability of mycelium-based material, an emerging material with a lot of potential in the near future. The plasma effect was characterized by assessing the added functionality (wettability) and inspecting surface modifications with different techniques, such as scanning electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS). Low pressure plasma (LPP) treatments were successfully applied into the mycelium-based material and optimal power of discharge and treatment time were set for this material (750 W, 17.5 min). With the optimized LPP treatments, the water absorption capacity of mycelium-based material was improved by 2000% and some surface morphological modifications were observed by SEM analysis. On the other hand, XPS analysis demonstrated how the plasma treatment changes the surface composition. Full article

The accurate prediction of gas well production is one of the key factors affecting the economical and efficient development of tight gas wells. The traditional oil and gas well production prediction method assumes strict conditions and has a low prediction accuracy in actual field applications. At present, intelligent algorithms based on big data have been applied in oil and gas well production prediction, but there are still some limitations. Only learning from data leads to the poor generalization ability and anti-interference ability of prediction models. To solve this problem, a production prediction method of tight gas wells based on the decline curve and data-driven neural network is established in this paper. Based on the actual production data of fractured horizontal wells in three tight gas reservoirs in the Ordos Basin, the prediction effect of the Arps decline curve model, the SPED decline curve model, the MFF decline curve model, and the combination of the decline curve and data-driven neural network model is compared and analyzed. The results of the case analysis show that the MFF model and the combined data-driven model have the highest accuracy, the average absolute percentage error is 14.11%, and the root-mean-square error is 1.491, which provides a new method for the production prediction of tight gas wells in the Ordos Basin. Full article

The goal of steel defect detection is to enhance the recognition accuracy and accelerate the detection speed with fewer parameters. However, challenges arise in steel sample detection due to issues such as feature ambiguity, low contrast, and similarity among inter-class features. Moreover, limited computing capability makes it difficult for small and medium-sized enterprises to deploy and utilize networks effectively. Therefore, we propose a novel lightweight steel detection network (SCFNet), which is based on spatial channel reconstruction and deep feature fusion. The network adopts a lightweight and efficient feature extraction module (LEM) for multi-scale feature extraction, enhancing the capability to extract blurry features. Simultaneously, we adopt spatial and channel reconstruction convolution (ScConv) to reconstruct the spatial and channel features of the feature maps, enhancing the spatial localization and semantic representation of defects. Additionally, we adopt the Weighted Bidirectional Feature Pyramid Network (BiFPN) for defect feature fusion, thereby enhancing the capability of the model in detecting low-contrast defects. Finally, we discuss the impact of different data augmentation methods on the model accuracy. Extensive experiments are conducted on the NEU-DET dataset, resulting in a final model achieving an mAP of 81.2%. Remarkably, this model only required 2.01 M parameters and 5.9 GFLOPs of computation. Compared to state-of-the-art object detection algorithms, our approach achieves a higher detection accuracy while requiring fewer computational resources, effectively balancing the model size and detection accuracy. Full article

In industrial manufacturing, bearings are crucial for machinery stability and safety. Undetected wear or cracks can lead to severe operational and financial setbacks. Thus, accurately identifying bearing defects is essential for maintaining production safety and equipment reliability. This research introduces an improved bearing defect detection model, YOLOv8-LMG, which is based on the YOLOv8n framework and incorporates four innovative technologies: the VanillaNet backbone network, the Lion optimizer, the CFP-EVC module, and the Shape-IoU loss function. These enhancements significantly increase detection efficiency and accuracy. YOLOv8-LMG achieves a [email protected] of 86.5% and a [email protected]–0.95 of 57.0% on the test dataset, surpassing the original YOLOv8n model while maintaining low computational complexity. Experimental results reveal that the YOLOv8-LMG model boosts accuracy and efficiency in bearing defect detection, showcasing its significant potential and practical value in advancing industrial inspection technologies. Full article

The selection of growth substrate geometries for the mechanical dry transfer of carbon nanotubes to device substrates depends on the precision of the assembly equipment. Since these geometries play a decisive role in the overall efficiency of the process, an investigation of the most important geometry parameters is carried out. The substrate geometry affects the number of carbon nanotubes suspended during the growth process and the speed of mechanical assembly at the same time. Since those two criteria are interlinked and affect productivity, a meta-model for the growth and selection of the nanotubes is simulated and a time study of the resulting assembly motions is subsequently performed. The geometry parameters are then evaluated based on the total number of suspended carbon nanotubes and the throughput rate, measured in transfers per hour. The accuracy specifications are then taken into account. Depending on the overall accuracy that can be achieved, different offset angles and overlaps between the growth and receiving substrate can be reached, which affect productivity differently for different substrate geometries. To increase the overall productivity, growth substrate designs are adapted to allow fully automated operation. This measure also reduces the frequency of substrate exchanges once all carbon nanotubes have been harvested. The introduction of substrates with multiple, polygonally arranged edges increases the total number of nanotubes that can be harvested. The inclusion of polygonally arranged edges in the initial analysis shows a significant increase in overall productivity. Full article

Textiles are often used to protect people from cold environments. While most garments are designed for temperatures not far below 0 °C, very cold regions on the earth near the poles or on mountains necessitate special clothing. The same is true for homeless people who have few possibilities to warm up or workers in cooling chambers and other cold environments. Passive insulating clothing, however, can only retain body heat. Active heating, on the other hand, necessitates energy, e.g., by batteries, which are usually relatively heavy and have to be recharged regularly. This review gives an overview of energy-self-sufficient textile solutions for cold environments, including energy harvesting by textile-based or textile-integrated solar cells; piezoelectric sensors in shoes and other possibilities; energy storage in supercapacitors or batteries; and heating by electric energy or phase-change materials. Full article

This paper addresses the challenging scheduling of crude oil operations (SCOO) problem, characterized by the intricate sequencing of activities involving discrete events and continuous variables. Given the NP-Hard nature of scheduling problems due to their combinatorial complexity, this study employs a data-driven optimization approach. Initially, historical operational data relevant to the SCOO are scrutinized; however, due to data limitations, small-scale instances are solved using a mathematical programming model to generate data. Subsequently, operational solution data are processed using the Apriori algorithm, a renowned data mining technique. The insights gained are translated into heuristic rules, laying the groundwork for a novel data-driven heuristic algorithm tailored for the SCOO problem. This algorithm is then applied to a 45-day scheduling scenario, demonstrating the efficacy of the proposed approach. Full article

Hydraulic fracturing is extensively utilized for the prevention and control of gas outbursts and rockbursts in the deep sections of coal mines. The determination of fracturing construction parameters based on the coal seam conditions and stress environments merits further investigation. This paper constructs a damage analysis model for coal under hydraulic loads, factoring in the influence of the intermediate principal stress, grounded in the unified strength theory analysis approach. It deduces the theoretical analytical equation for the damage distribution of a coal medium subjected to small-flow-rate hydraulic fracturing in underground coal mines. Laboratory experiments yielded the mechanical parameters of coal in the study area and facilitated the fitting of the intermediate principal stress coefficient. Leveraging these datasets, the study probes into the interaction between hydraulic loads and damage radius under assorted influence ranges, porosity, far-field crustal stresses, and brittle damage coefficients. The findings underscore that hydraulic load escalates exponentially with the damage radius. Within the variable range of geological conditions in the test area, the effects of varying influence range, porosity level, far-field stress, and brittle damage coefficient on the outcomes intensify one by one; a larger hydraulic load diminishes the impact of far-field stress variations on the damage radius, inversely to the influence range, porosity, and brittle damage. The damage radius derived through the gas pressure reduction method in field applications corroborates the theoretical calculations, affirming the precision of the theoretical model. These findings render pivotal guidance for the design and efficacy assessment of small-scale hydraulic fracturing in underground coal mines. Full article

Compliant physical interactions, interactive learning, and robust position control are crucial to improving the effectiveness and safety of rehabilitation robots. This paper proposes a human–robot cooperation control strategy (HRCCS) for lower limb rehabilitation robots. The high-level trajectory planner of the HRCCS consists of a trajectory generator, a trajectory learner, a desired trajectory predictor, and a soft saturation function. The trajectory planner can predict and generate a smooth desired trajectory through physical human–robot interaction (pHRI) in a restricted joint space and can learn the desired trajectory using the locally weighted regression method. Moreover, a triple-step controller was designed to be the low-level position controller of the HRCCS to ensure that each joint tracks the desired trajectory. A nonlinear disturbance observer is used to observe and compensate for total disturbances. The radial basis function neural networks (RBFNN) approximation law and robust term are adopted to compensate for observation errors. The simulation results indicate that the HRCCS is robust and can achieve compliant pHRI and interactive trajectory learning. Therefore, the HRCCS has the potential to be used in rehabilitation robots and other fields involving pHRI. Full article

A series of experiments has been conducted to investigate the tribological properties of a TiN film sliding against GCr15 steel balls in ambient air, low vacuum and high vacuum environments. Various friction loads and sliding velocities were also applied. The TiN film displays a steady-state friction stage after the running-in stage in all the above environments, while the durations of running-in stages are different. The steady-state friction coefficients of the TiN film were around 0.56 in ambient air and 0.3 in the high vacuum environment (1 × 10⁻⁵ mbar). In the low vacuum (1 × 10⁻² mbar) environment, a low friction coefficient (around 0.19) was attained for all the friction tests on TiN film, irrespective of the applied load and sliding velocity. In the meantime, it was noticed that the applied loads and the sliding velocities would change the duration of the running-in stage before reaching the low friction coefficient. It is revealed by the analysis of wear tracks that the metal oxides induced by the tribo-chemical effect at the friction interface play an important role in affecting the tribological behaviors of the TiN films in different environments. The Raman results show that the main component of the metal oxides is hematite (α-Fe₂O₃), and the amount of iron oxide is related to the friction environment. The composition and quantity of iron oxides produced by the interfacial tribo-chemical effect affect the tribological behavior. The results also show that the mechanical wear process at the friction interface displays a polishing effect, which would reduce the surface roughness. The mechanical wear performance varies under different loads and velocities. The tribological tests results indicate that the interfacial tribo-chemical effect and mechanical wear process should be considered together rather than individually to interpret the tribological behaviors of TiN films in different environments. Full article

The aim of this study is to purify industrial textile effluents by treating two types of commonly encountered dyes: blue maxilon (BM), of cationic nature, and black eriochrome (NE), of anionic nature. We intend to employ an innovative approach based on the adsorption of these dyes onto a novel vegetal biomaterial derived from Aleppo pine fibers (FPAs). A kinetic and thermodynamic study was conducted. The effect of some physicochemical parameters on both dye adsorption and FPAs was also evaluated. The modeling of the adsorption results was performed using Langmuir, Freundlich, Temkin, and Dubinin Radushkevich (D-R) isotherms. The results indicate that the equilibrium time strongly depends on the initial concentration of the two dyes, being 60 min with pseudo-second-order adsorption kinetics for both dyes. Adsorption isotherms under the optimal conditions of adsorbent mass, temperature, medium pH, and dye concentration were used to determine the maximum adsorption efficiency, which was close to 93% and 98% for BM and NE, respectively. The results also show that the adsorption of both dyes on FPAs fits well with Langmuir’s model. The thermodynamic study indicates that the adsorption of both dyes on FPAs is spontaneous and exothermic in nature for BM and endothermic for NE. Full article

Within the domain of industrial control systems, safeguarding data integrity stands as a pivotal endeavor, especially in light of the burgeoning menace posed by malicious tampering and potential data loss. Traditional data storage paradigms, tethered to physical hard disks, are fraught with inherent susceptibilities, underscoring the pressing need for the deployment of resilient preservation frameworks. This study delves into the transformative potential offered by distributed ledger technology (DLT), with a specific focus on IOTA, within the expansive landscape of the Internet of Things (IoT). Through a meticulous examination of the intricacies inherent to data transmission protocols, we present a novel paradigm aimed at fortifying data security. Our approach advocates for the strategic placement of IOTA nodes on lower-level devices, thereby streamlining the transmission pathway and curtailing vulnerabilities. This concerted effort ensures the seamless preservation of data confidentiality and integrity from inception to storage, bolstering trust in the convergence of IoT and DLT technologies. By embracing proactive measures, organizations can navigate the labyrinthine terrain of data management, effectively mitigate risks, and cultivate an environment conducive to innovation and progress. Full article

We aimed to investigate the corrosion patterns and the main controlling factors of N80 steel and P110 steel tubing under different sections. Conducting weight loss corrosion experiments for 168 h using high-temperature and high-pressure autoclaves to simulate the corrosion behavior of two types of casing materials, N80 steel and P110 steel, in different well sections under specific conditions of CO₂ content, chloride ion concentration, temperature, pressure, and sulfate-reducing bacteria population in highly mineralized formation water. X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray spectroscopy (EDS) were used to analyze the corrosion products, surface morphology, and elemental composition of the two steel pipes. Additionally, 3D microscopy was employed to observe the morphology and measure the dimensions of localized corrosion pits. Under different well sections, the corrosion products formed on N80 steel and P110 steel mainly consist of FeCO_3, and crystalline salts of chlorides present in the solution medium. Under low-water-cut conditions, narrow and deep corrosion defects were observed, while narrow and shallow corrosion defects were found under high-water-cut conditions. In the upper wellbore section, both steel pipes exhibited dispersed and thin corrosion product films that suffered from rupture and detachment, resulting in severe localized corrosion. In the middle wellbore section, the corrosion product film on N80 steel comprised irregularly arranged polygonal grains, some of which exhibited significant gaps, leading to extremely severe corrosion. For P110 steel, the corrosion product film was also dispersed and thin, with extensive detachment and extremely severe corrosion. In the lower wellbore section, both steel pipes were covered with a dense layer of grains, with smaller gaps between them, effectively protecting the metal matrix from corrosion. Consequently, the corrosion rate decreased compared to the middle section but still exhibited severe corrosion. In low-water-cut conditions, attention should be given to the risk of column safety due to corrosion from condensate water and CO₂, as well as the size of narrow and deep corrosion defects in the middle wellbore section. In high-water-cut conditions, it is recommended to use corrosion inhibitors in combination while focusing on SRB bacteria corrosion in the upper wellbore section, condensate water in the middle section, CO₂ content and chloride ion coupling in the lower section, and the size of narrow and shallow corrosion defects causing column safety risks. Full article

The co-gasification of coal and biomass offers numerous benefits, including improved gasification efficiency, reduced pollution emissions, and the utilization of renewable resources. However, there is a lack of comprehensive research on the synergistic effects of, and influence parameters on, coal–biomass co-gasification. This study employs Aspen Plus simulations to investigate the co-gasification behavior of coal and corn straw, focusing on the synergistic effects and the impact of various operating conditions. A synergistic coefficient is defined to quantify the interactions between the feedstocks. Sensitivity analyses explore the effects of gasification temperature (800–1300 °C), coal rank (lignite, bituminous, anthracite), biomass mass fraction (0–50%), oxygen-to-carbon ratio, and steam-to-carbon ratio on the synergistic coefficients of effective syngas content (CO + H₂), specific oxygen consumption, specific fuel consumption, and cold gas efficiency. The results reveal an optimal biomass mass fraction of 10% for maximizing cold gas efficiency, with the syngas primarily consisting of H₂ (36.8%) and CO (61.6%). Higher gasification temperatures (up to 1200 °C) improve syngas quality and process efficiency, while higher-rank coals exhibit better gasification performance compared to lignite. Optimal oxygen-to-carbon and steam-to-carbon ratios are identified for maximizing syngas yield and quality. These findings provide valuable guidance for the design and optimization of industrial coal–biomass co-gasification processes, enabling the maximization of syngas quality, process efficiency, and resource utilization. Full article

Abnormal conditions greatly reduce the efficiency of hydraulic fracturing of unconventional gas reservoirs. Optimizing the fracturing scheme is crucial to minimize the likelihood of abnormal operational conditions, such as pressure channeling, casing deformation, and proppant plugging. This paper proposes a novel machine learning-based method for optimizing abnormal conditions during hydraulic fracturing of unconventional natural gas reservoirs. Firstly, the main controlling factors of abnormal conditions are selected through a hybrid controlling analysis, upon which a surrogate model is established for predicting the occurrence probability of abnormal conditions, rather than whether abnormal conditions happen or not. Subsequently, a machine learning-based optimization algorithm is developed to minimize the occurrence probability of abnormal conditions, acknowledging their inevitability during the fracturing process. The optimal results demonstrate the proposed method outperforms traditional methods, on average. The proposed methodology is more in line with the needs of practical operation in an environment full of uncertainty. Full article

Many studies have used fractal theory to characterize pore structure distribution heterogeneity through mercury intake curves. However, there is relatively little research on the fractal model calculation of mercury removal curves. In this study, a high-pressure mercury intrusion test is used to describe the pore and fracture distribution heterogeneity (PFDH). The fractal physical meaning of the mercury removal curve was determined by calculating the change in the curve’s fractal dimension value. The results are as follows. (1) According to mercury removal efficiency and porosity, samples can be divided into types A (mercury removal efficiency above 35%) and B (mercury removal efficiency below 35%). In general, type A sample belongs to micro-pore-developed types, and type B samples belong to the macro-pore-developed type. (2) The Menger model (M) represents the complexity of a specific surface area, while the Sierpinski model (S) represents the roughness of the pore volume. Among all the samples, the lower-pore-volume region controls PFDH. (3) According to the calculation results of the single fractal model, it can be seen that the PFDH of type B is stronger than that of type A, which is similar to the results of mercury intrusion. According to the calculation structure of the multifractal model, it can be seen that the volume distribution heterogeneity of type B under various pores is significantly stronger than that of type A. This is opposite to the result of mercury injection. (4) D_M has a relationship with the pore volume percentage at different stages, so the M model at the mercury inlet stage can better characterize PFDH at the mercury inlet stage. Full article

For over four decades, carbon dioxide (CO₂) has been instrumental in enhancing oil extraction through advanced recovery techniques. One such method, water alternating gas (WAG) injection, while effective, grapples with limitations like gas channeling and gravity segregation. To tackle the aforementioned issues, this paper proposes an upgrade coupling method named alkaline-surfactant-polymer alternating gas (ASPAG). ASP flooding and CO₂ are injected alternately into the reservoir to enhance the recovery of the WAG process. The uniqueness of this method lies in the fact that polymers could help profile modification, CO₂ would miscible mix with oil, and alkaline surfactant would reduce oil–water interfacial tension (IFT). To analyze the feasibility of ASPAG, a couples model considering both gas flooding and ASP flooding processes is established by using the CMG-STARS (Version 2021) to study the performance of ASPAG and compare the recovery among ASPAG, WAG, and ASP flooding. Our research delved into the ASPAG’s adaptability across reservoirs varying in average permeability, interlayer heterogeneity, formation rhythmicity, and fluid properties. Key findings include that ASPAG surpasses the conventional WAG in sweep and displacement efficiency, elevating oil recovery by 12–17%, and in comparison to ASP, ASPAG bolsters displacement efficiency, leading to a 9–11% increase in oil recovery. The primary flooding mechanism of ASPAG stems from the ASP slug’s ability to diminish the interfacial tension, enhancing the oil and water mobility ratio, which is particularly efficient in medium-high permeability layers. Through sensitivity analysis, ASPAG is best suited for mid-high-permeability reservoirs characterized by low crude oil viscosity and a composite reverse sedimentary rhythm. This study offers invaluable insights into the underlying mechanisms and critical parameters that influence the alkaline-surfactant-polymer alternating gas method’s success for enhanced oil recovery. Furthermore, it unveils an innovative strategy to boost oil recovery in medium-to-high-permeability reservoirs. Full article

Intuitionistic fuzzy sets provide a viable framework for modelling lifetime distribution characteristics, particularly in scenarios with measurement imprecision. This is accomplished by utilizing membership and non-membership degrees to accurately express the complexities of data uncertainty. Nonetheless, the complexities of some cases necessitate a more advanced approach of imprecise data, motivating the use of generalized intuitionistic fuzzy sets (GenIFSs). The use of GenIFSs represents a flexible modeling strategy that is characterized by the careful incorporation of an extra level of hesitancy, which effectively clarifies the underlying ambiguity and uncertainty present in reliability evaluations. The study employs a methodology based on generalized intuitionistic fuzzy distributions to thoroughly examine the uncertainty related to the parameters and reliability characteristics present in the Burr XII distribution. The goal is to provide a more accurate evaluation of reliability measurements by addressing the inherent ambiguity in the distribution’s shape parameter. Various reliability measurements, such as reliability, hazard rate, and conditional reliability functions, are derived for the Burr XII distribution. This extensive analysis is carried out within the context of the generalized intuitionistic fuzzy sets paradigm, improving the understanding of the Burr XII distribution’s reliability measurements and providing important insights into its performance for the study of various types of systems. To facilitate understanding and point to practical application, the findings are shown graphically and contrasted across various cut-set values using a valuable numerical example. Full article

The aim of this study was to evaluate the effects of different drying methods on bioactive compounds and to analyze their composition in Verbascum sinaiticum (V. sinaiticum) leaf extracts using UHPLC-ESI-QTOF-MS/MS. V. sinaiticum is traditionally used as an herbal medicine, yet it has undergone limited scientific investigations regarding its secondary metabolites. V. sinaiticum leaves were dried using oven dryers at 50 °C, 60 °C, and 70 °C, as well as a freeze dryer. The leaves were then extracted using 50% and 70% aqueous ethanol and 100% aqueous solutions. The results showed that the highest contents of TPC and TFC were observed when 70% aqueous ethanol was used during freeze drying, reaching 181.73 mg GAE/g dw and 78.57 mg CE/g dw, respectively. The strongest correlations were observed between the TFC and DPPH radical scavenging activity (0.9082), followed by TPC and ABTS assays (0.8933) and TPC and DPPH (0.8272). In the FTIR analysis, freeze drying exhibited a lower intensity of the phenolic -OH functional groups, contrasting with significant denaturation observed during oven drying at 70 °C. Metabolite analysis identified 29 compounds in V. sinaiticum leaves, further confirming the presence of 14 phenolic and flavonoid compounds, including kaempferol, catechin, gallic acid, and myricetin derivatives, consistent with the experimentally observed antioxidant capacity. This study highlights the impact of drying methods on the bioactive composition of V. sinaiticum and underscores its potential as a source of antioxidants for food, nutraceutical, and pharmaceutical applications. Full article

Pepper processing waste has the potential to be used as a substrate in the process of anaerobic digestion, but because of its high polyphenol content, certain limitations are expected. During the determination of the biodegradability of pepper samples, a biogas potential of 687 L/kg DM was observed, as well as a biomethane potential of 401 L/kg DM. While both the testing of biodegradability and the process in the pilot scale progressed, it was observed that total polyphenol content in both cases decreased. Also, as far as individual polyphenols during the process in the pilot scale are concerned, it can be observed that at the end of the process no procyanidin A2, epicatechin, myricetin, and quercetin were detected. The observed concentration of the ferulic acid on the last day of the process was 0.09 µg/g. Finally, it can be concluded that the presence of polyphenols did not significantly affect the biogas potential of pepper waste. Due to its relatively stable biogas production, as far as biogas production on the pilot scale is concerned, it can be concluded that pepper processing waste has the potential to be used as a substrate for biogas production. Full article

The physical properties of shale reservoirs are typically poor, necessitating the use of fracturing technology for effective development. However, the high clay content prevalent in shale formations poses significant challenges for conventional hydraulic fracturing methods. To address this issue, CO₂-based fracturing fluid has been proposed as an alternative to mitigate the damage caused by water-based fracturing fluids. In this paper, the applicability of quasi-dry CO₂ fracturing in shale reservoirs is examined from three key perspectives: the viscosity of CO₂ fracturing fluid, the fracture characteristics induced by the CO₂ fracture fluid, and the potential reservoir damage caused by the fracturing fluid. Firstly, the viscosity of CO₂ fracturing fluid was determined by a rheological experiment. Rheological tests revealed that the viscosity of CO₂ fracturing fluid was significantly influenced by the water–carbon ratio. Specifically, when the water–carbon ratio was 30:70, the maximum viscosity observed could reach 104 mPa·s. Moreover, increasing reservoir temperature resulted in decreased fracturing fluid viscosity, with a 40 °C temperature rise causing a 20% viscosity reduction. Secondly, matrix permeability tests were conducted to investigate permeability alteration during CO₂ fracturing fluid invasion. Due to the weak acidity of CO₂-based fracturing fluid, the permeability reduction induced by clay hydration was inhibited, and an increase in permeability was observed after a 3-day duration. However, the matrix permeability tends to decrease as the interaction time is prolonged, which means prolonged soaking time can still cause formation damage. Finally, triaxial fracturing experiments facilitated by a three-axis servo pressure device were conducted. The fracture properties were characterized using computed tomography (CT), and 3D reconstruction of fractured samples was conducted based on the CT data. The results demonstrate that CO₂ fracturing fluid effectively activates weak cementation surfaces in the rock, promoting the formation of larger and more complex fractures. Hence, CO₂ quasi-dry fracturing technology emerges as a method with significant potential, capable of efficiently stimulating shale reservoirs, although a reasonable soaking time is necessary to maximize hydrocarbon production. Full article

Designs for remanufacturing (DfRem) consider the remanufacturability of the product in the early stages of product design, which can greatly increase the reusability of the products. However, product design schemes lack reasonable evaluation indicators for remanufacturability, and the decision-makers of the design scheme have subjective preferences and vague hesitation. These result in inaccurate decision making on DfRem schemes that will affect the successful implementation of product remanufacturing. In order to improve the accuracy of the DfRem scheme decision, a fuzzy decision-making method for green design for remanufacturability is proposed. Firstly, an evaluation indicator system for green design schemes was established that takes into account remanufacturability, reliability, cost, and the environment, and the entropy weighting method is used to quantify and weigh the design scheme evaluation indicators. Then, the hesitation fuzzy set is applied to construct the set of evaluations and the optimal design scheme is selected by applying the comprehensive evaluation method. Finally, the feasibility of the above method is verified by using the green design of an injection mold as an example, and the results show that the above method is able to make accurate and effective design scheme decisions. This method has been implemented in a prototype system using Visual Studio 2022 and Microsoft SQL Server2022. The results show that the fuzzy decision-making system is accurate and effective for rapidly generating a rational green design scheme for remanufacturability. Full article

Kuwait stands as one of the hottest locations globally, experiencing scorching temperatures that can soar to 50 °C during the summer months. Conversely, in the winter months of December and January, temperatures may plummet to less than 10 °C. Maintaining a comfortable temperature indoors necessitates a substantial amount of energy, particularly during the scorching summer seasons. In Kuwait, most of the electrical energy required for functions such as air conditioning and lighting is derived from fossil fuel resources, contributing to escalating air pollution and global warming. To reduce dependence on conventional energy sources for heating and cooling, this article presents a case study to explore the potential of using geothermal energy for space heating and cooling in Kuwait. The case study involves utilizing a geothermal heat pump (water-sourced heat pump) in conjunction with a vertical-borehole ground heat exchanger (VBGHE). The mentioned system is deployed to regulate the climate in a six-floor apartment block comprising a small two-bedroom apartment on each level, each with a total floor area of 57 m². Two geothermal heat pumps, each with a cooling capacity of 2.58 kW and a heating capacity of 2.90 kW, connected to two vertical-borehole heat exchangers, were deployed for each apartment to maintain temperatures at 22 °C in summer and 26 °C in winter. The findings indicate that the estimated annual energy loads for cooling and heating for the apartment block are 42,758 kWh and 113 kWh, respectively. The corresponding electrical energy consumption amounted to 9294 kWh for space cooling and 113 kWh for space heating. The observed peak cooling load was approximately 9300 kJ/h (2.58 kW) per apartment, resulting in a power density of 45 W/m². Moreover, the HP system achieved a 22% reduction in annual electric energy consumption compared to conventional air conditioning systems. This reduction in electric energy usage led to an annual CO₂ reduction of 6.6 kg/m². Full article

Proppant transport and distribution law in hydraulic fractures has important theoretical and field guidance significance for the optimization design of hydraulic fracturing schemes and accurate production prediction. Many studies aim to understand proppant transportation in complex fracture systems. Few studies, however, have addressed the flow path mechanism between the transverse fracture and horizontal well, which is often neglected in practical design. In this paper, a series of mathematical equations, including the rock elastic deformation equation, fracturing fluid continuity equation, fracturing fluid flow equation, and proppant continuity equation for the proppant transport, were established for the transverse fracture of a horizontal well, while the finite element method was used for the solution. Moreover, the two-dimensional radial flow was considered in the proppant transport modeling. The results show that proppant breakage, embedding, and particle migration are harmful to fracture conductivity. The proppant concentration and fracture wall roughness effect can slow down the proppant settling rate, but at the same time, it can also block the horizontal transportation of the proppant and shorten the effective proppant seam length. Increasing the fracturing fluid viscosity and construction displacement, reducing the proppant density and particle size, and adopting appropriate sanding procedures can all lead to better proppant placement and, thus, better fracturing and remodeling results. This paper can serve as a reference for the future study of proppant design for horizontal wells. Full article

Aiming at the high accuracy and high robustness position control of servo pump control in the pitch system of a wind turbine generator, this paper proposes an active disturbance rejection controller (ADRC). The ADRC considers pitch angular velocity and acceleration limits. According to the kinematics principle of the pump-controlled pitch system, the relationship between the pitch angular velocity and acceleration limit and the displacement of the hydraulic cylinder is established. Through the method of theoretical analysis, the nonlinear relationship expression between pitch angle and hydraulic cylinder displacement is obtained, and the linearization of pitch angular velocity control is realized; the formula for b₀ (the estimated value of the input gain of the system) of the pump-controlled pitch system is obtained by the method of modeling and analysis, b₀ is the key parameter for the design of the ADRC; the stability of the controller parameters is proved through the stability analysis and simulation analysis, and the design of the self-immobilizing controller with pitch angular velocity and acceleration limitation is the completed ADRC design. Finally, a joint simulation platform of AMESim and MATLAB as well as a physical experiment platform of electro-hydraulic servo pump-controlled pitch control is constructed, and the effectiveness of the proposed control method is verified through simulation and experiment. The results show that compared with the unrestricted ADRC and PID, the velocity-acceleration-limited ADRC can effectively improve the control effect of the angular velocity and acceleration of the paddle, smooth the startup process, improve the safety of the system, and have better position control accuracy and anti-jamming ability. Full article

An ion-exchange procedure of synthetic zeolite ZSM-5 (Si/Al = 15) was used to prepare three cobalt ZSM-5 zeolites (CoM-ZSM5 (M = Zn and Ni)) that were examined for OERs in alkaline media. The structural, morphological, and surface properties of the prepared materials were studied by X-ray powder diffraction, Fourier transform infrared spectroscopy, scanning electron microscopy with energy dispersive spectroscopy, and low-temperature nitrogen adsorption. All three electrocatalysts showed OER activity where CoNi-ZSM5 presented the highest current density (9.5 mA cm⁻² at 2 V), the lowest Tafel slope (134 mV dec⁻¹), and the lowest resistances of the charge transfer reaction (31.5 Ω). Overpotential (η_onset) at an onset potential of 410 mV for both CoNi-ZSM5 and Co-ZSM5 and 440 mV for CoZn-ZSM5 electrodes was observed. Co-ZSM5 showed somewhat lower OER catalytic activity than CoNi-ZSM5, while CoZn-ZSM5 demonstrated the lowest OER catalytic activity. The R_ct of CoZn-ZSM5 is significantly higher than the Rct of CoNi-ZSM5, which could lead to their different OER activities. Good OER stability and low price are the main advantages of the synthesized CoM-ZSM5 samples in this study. Full article

A sensorless vector active disturbance rejection control (ADRC) method for permanent magnet synchronous motors (PMSM) utilizing a Luenberger observer is presented. This method aims to address the challenges associated with weak active disturbances, substantial steady-state speed amplitude fluctuations, and difficulty in achieving a balance between overshoot and speed control in the sensorless PMSM control system. Mathematical models of the Luenberger observer and the ADRC were analyzed, leading to the proposal of a second-order ADRC control method based on the Luenberger observer. A mathematical model of the permanent PMSM has been introduced. Additionally, the necessary conditions for the convergence of the Luenberger observer were derived and examined. The allowable range of error feedback gain values was determined, and rotor position data were acquired using a phase-locked loop. The principle of the ADRC was analyzed, and the ADRC simulation results, along with the PI simulation results, were detailed. When the target speed is 1000 r/min, the steady-state error and load disturbance resistance of the ADRC control method outperform those of the PI control method. Finally, the control method was experimentally tested on an STM32F4 chip, demonstrating the advantages of small steady-state error and strong active disturbance ability. Full article