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Processes, Volume 12, Issue 6 (June 2024) – 240 articles

Cover Story (view full-size image): This study addresses the synthesis of sol–gel nanostructured cerium-doped TiO2 (Ce-TiO2) films with the addition of different amounts of cerium (0.00, 0.08, 0.40, 0.80, 2.40, and 4.10 wt. %) on a borosilicate glass substrate. The influence of the amount of Ce in TiO2 films, the duration of the photocatalytic decomposition, and the irradiation type (UV-A and simulated solar light) on the ciprofloxacin degradation were monitored. The best photocatalytic activity was achieved by the TiO2 film doped with 0.08 wt.% Ce, under both UV-A and solar irradiation. The immobilized catalyst was successfully reused for three cycles under solar light simulator radiation. View this paper
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18 pages, 4705 KiB  
Article
Micro-Groove Optimisation of High-Speed Inner Ring Micro-Grooved Pumping Seal for New Energy Electric Vehicles
by Hanqing Chen, Ruqi Yan, Xianzhi Hong, Xin Bao and Xuexing Ding
Processes 2024, 12(6), 1281; https://doi.org/10.3390/pr12061281 - 20 Jun 2024
Viewed by 568
Abstract
Traditional oil seals are insufficient for the high-speed and bi-directional rotation of new energy electric vehicles. Therefore, we developed a Python program focusing on micro-groove pump seals and examined the unexplored non-contact oil–air biphasic internal end-face seals. Real gas effects were described using [...] Read more.
Traditional oil seals are insufficient for the high-speed and bi-directional rotation of new energy electric vehicles. Therefore, we developed a Python program focusing on micro-groove pump seals and examined the unexplored non-contact oil–air biphasic internal end-face seals. Real gas effects were described using the virial and Lucas equations. We introduced an oil–air ratio to determine the equivalent density and viscosity of the two-phase fluid in the seal. Furthermore, we solved the compressible steady-state Reynolds equation using the finite difference method. Analysing the seal’s pumping mechanisms and the effects of operating parameters on sealing performance, we assessed 17 types of hydrodynamic grooves. The results demonstrate that inverse fir tree-like grooves perform well under typical sealing conditions. Under the conditions given in this study, the pumping rate of the optimal groove type compared to other groove types even reached 633.54%. In the oil–air biphasic state, the micro-groove pump seal exerts significant dynamic pressure on the sealing surface. Seal opening force increases with rotational velocity, oil–air ratio, and inlet pressure but decreases with temperature. The pumping rate first increases and then decreases with rotational velocity, increases with oil–air ratio and temperature, and then decreases with inlet pressure. Some special working points require consideration in sealing design. Our results provide insights into designing micro-grooved pumping seals for new energy electric vehicles. Full article
(This article belongs to the Section Energy Systems)
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14 pages, 19402 KiB  
Article
Properties of Ni-B/B Composite Coatings Produced by the Electroless Method under Semi-Technical Line Conditions
by Grzegorz Cieślak, Marta Gostomska, Adrian Dąbrowski, Tinatin Ciciszwili-Wyspiańska, Katarzyna Skroban, Anna Mazurek, Edyta Wojda, Michał Głowacki, Tomasz Rygier and Anna Gajewska-Midziałek
Processes 2024, 12(6), 1280; https://doi.org/10.3390/pr12061280 - 20 Jun 2024
Viewed by 459
Abstract
Composite coatings have been successfully fabricated at the laboratory scale in many research centers around the world; however, it is still a major challenge to transfer the positive results of the work to the industrial scale. This paper presents the technology for the [...] Read more.
Composite coatings have been successfully fabricated at the laboratory scale in many research centers around the world; however, it is still a major challenge to transfer the positive results of the work to the industrial scale. This paper presents the technology for the production of Ni-B and Ni-B/B composite coatings on a pilot experimental semi-technical line by chemical reduction. A process scheme for the fabrication of Ni-B layers and composite coatings with a nickel–boron matrix and a dispersive phase in the form of boron nanoparticles was developed. All stages of the fabrication process were described in detail. The dispersion phase of the boron particles was characterized, and the performance properties of the Ni-B and Ni-B/B composite coatings produced on a pilot electroplating line were studied. The structure and morphology of the Ni-B/B composite coatings were characterized for comparison with nickel–boron coatings. Their mechanical and tribological properties and adhesion to the substrate were studied. The influence of the dispersion phase of boron particles on the structure and functional properties of the composite coatings was evaluated. In order to improve the performance of the fabricated coatings, a heating process at 400 °C was carried out, and the performance of Ni-B and composite Ni-B/B coatings was studied after the heat treatment operation. Full article
(This article belongs to the Special Issue Recent Advances in Functional Materials Manufacturing and Processing)
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13 pages, 291 KiB  
Article
Utilizing Used Cooking Oil and Organic Waste: A Sustainable Approach to Soap Production
by Leila Zayed, Natalia Gablo, Ludmila Kalcakova, Simona Dordevic, Ivan Kushkevych, Dani Dordevic and Bohuslava Tremlova
Processes 2024, 12(6), 1279; https://doi.org/10.3390/pr12061279 - 20 Jun 2024
Viewed by 496
Abstract
This research examined the potential for utilizing waste materials generated during the production of dishes/meals and organic waste. Specifically, it evaluated the use of orange peel (OP), spent coffee grounds (SCG), and waste cooking oil in the production of soaps. For the purposes [...] Read more.
This research examined the potential for utilizing waste materials generated during the production of dishes/meals and organic waste. Specifically, it evaluated the use of orange peel (OP), spent coffee grounds (SCG), and waste cooking oil in the production of soaps. For the purposes of this study, homemade soaps were made from used food oils using the cold saponification method using sodium hydroxide. During the soap preparation, spent coffee grounds and orange peel were added to the samples in increasing concentrations of 1%, 2.5%, and 5%. The quality of the individual types of homemade soaps was evaluated on the basis of physicochemical properties such as pH, moisture, total alkalinity, total fatty matter, malondialdehyde content, fat content, foaminess, and hardness. All soaps produced using the cooking oil met the ISO quality criteria and reveal a high TFM content, low moisture content, and also very good foam stability and satisfactory foaming stability. However, no relationship was observed between the use of OP and SCG in soap production and these parameters. However, according to the ABTS test, OP and SCG significantly contributed to the antioxidant properties of the soaps, while SCG-impregnated soaps performed slightly better in this respect. Soaps with SCG also had the highest levels of flavonoids. On the other hand, the fillers used for the soap formulation reduced their hardness. All soaps showed 100% solubility in water, thus confirming the biodegradability of the product. This study demonstrated the novel potential of incorporating waste products like orange peel, spent coffee grounds, and waste cooking oil into homemade soaps, highlighting their contributions to its antioxidant properties and water solubility while ensuring high quality standards. Full article
(This article belongs to the Special Issue Green Chemistry: From Wastes to Value-Added Products (2nd Edition))
16 pages, 2327 KiB  
Article
Optimal Scheduling of Microgrids Considering Offshore Wind Power and Carbon Trading
by Jian Fang, Yu Li, Hongbo Zou, Hengrui Ma and Hongxia Wang
Processes 2024, 12(6), 1278; https://doi.org/10.3390/pr12061278 - 20 Jun 2024
Viewed by 461
Abstract
Offshore wind energy entering the grid in coastal areas creates issues with the safe and stable operation of power systems. To control the carbon emission of power systems and increase the proportion of offshore wind consumption, a microgrid optimization model considering offshore wind [...] Read more.
Offshore wind energy entering the grid in coastal areas creates issues with the safe and stable operation of power systems. To control the carbon emission of power systems and increase the proportion of offshore wind consumption, a microgrid optimization model considering offshore wind power and carbon trading is proposed in this paper. To avoid the defect of Particle Swarm Optimization (PSO) falling into the local optimum prematurely, the PSO algorithm is improved by dynamically decreasing inertia weights and chaos factors. Combined with the powerful optimization capability of the genetic algorithm (GA), the improved PSO-GA algorithm is used to solve the model. The simulation results show that the improved algorithm iterates 11 times before the parameters reach the optimal value, with high convergence accuracy. The proposed approach can increase the proportion of offshore wind consumption and ensure the optimal economic performance of the system while reducing the carbon emission. Full article
(This article belongs to the Special Issue Optimal Design for Renewable Power Systems)
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13 pages, 1446 KiB  
Article
Operation Strategy for an Integrated Energy System Considering the Slow Dynamic Response Characteristics of Power-to-Gas Conversion
by Shuangquan Teng, Fei Long and Hongbo Zou
Processes 2024, 12(6), 1277; https://doi.org/10.3390/pr12061277 - 20 Jun 2024
Viewed by 448
Abstract
Power-to-gas technology provides an emerging pathway for promoting green and low-carbon transformation of energy systems. Through the processes of electrolyzing water and the methanation reaction, it converts surplus renewable energy into hydrogen and natural gas, offering an effective approach for large-scale integration of [...] Read more.
Power-to-gas technology provides an emerging pathway for promoting green and low-carbon transformation of energy systems. Through the processes of electrolyzing water and the methanation reaction, it converts surplus renewable energy into hydrogen and natural gas, offering an effective approach for large-scale integration of renewable energy sources. However, the optimization of existing integrated energy systems has yet to finely model the operational characteristics of power-to-gas technology, severely limiting the energy conversion efficiency of systems. To address this issue, this paper proposes an integrated energy system operation strategy considering the slow dynamic response characteristics of power-to-gas. Firstly, based on the technical features of power-to-gas, an operational model for electrolyzing water to produce hydrogen is constructed, considering the transition relationships among cold start-up, hot start-up, and production states of a methanation reaction, thereby building a power-to-gas operation model considering slow dynamic response characteristics. This model finely reflects the impact of power-to-gas operational states on methanation, facilitating accurate representation of the operational states of methanation. Then, considering the energy conversion constraints and power balance of various coupled devices within integrated energy systems, an optimization model for the operation of the integrated energy system is constructed with the total daily operation cost of the system as the optimization objective. Finally, simulation comparisons are conducted to demonstrate the necessity of considering the slow dynamic response characteristics of power-to-gas technology for integrated energy system operation. The case study results indicate that the proposed power-to-gas operation model can accurately simulate the methanation process, facilitating the rational conversion of surplus renewable energy into natural gas energy and avoiding misjudgments in system operation costs and energy utilization efficiency. Full article
(This article belongs to the Section Energy Systems)
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18 pages, 3483 KiB  
Article
Effects of Vegetation Cover Varying along the Hydrological Gradient on Microbial Community and N-Cycling Gene Abundance in a Plateau Lake Littoral Zone
by Jing Yuan, Jing Cao, Wanxue Liao, Feng Zhu, Zeying Hou and Zhaosheng Chu
Processes 2024, 12(6), 1276; https://doi.org/10.3390/pr12061276 - 20 Jun 2024
Viewed by 449
Abstract
The lake littoral zone is periodically exposed to water due to water level fluctuations, driving the succession and distribution of littoral vegetation covers, which complexly affect nutrient biogeochemical transformation. However, the combined effects of water level fluctuations and other environmental factors on microbial [...] Read more.
The lake littoral zone is periodically exposed to water due to water level fluctuations, driving the succession and distribution of littoral vegetation covers, which complexly affect nutrient biogeochemical transformation. However, the combined effects of water level fluctuations and other environmental factors on microbial characteristics and functions at the regional scale remain unclear. In this study, typical vegetation cover types along various water levels were chosen to investigate the effects of water level and vegetation cover on the microbial community and functional genes in the Lake Erhai littoral zone. The results showed that water level fluctuations influenced oxygen and nitrogen compound contents due to oxic–anoxic alternations and intensive material exchange. Meanwhile, vegetation cover affected the organic matter and total nitrogen content through plant residues and root exudation supplying exogenous carbon and nitrogen. Along the hydrological gradient, the high microbial diversity and abundant microbes related to nitrogen cycling were observed in interface sediments. It was attributed to the alternating aerobic–anaerobic environments, which filtered adaptable dominant phyla and genera. The abundances of amoA AOA, nirS, and amx were higher than those of the other genes and were strongly related to flooding days and water content. In conclusion, water level fluctuations and vegetation type jointly affect microbial community structure and nitrogen-related functional genes. Full article
(This article belongs to the Special Issue State-of-the-Art Wastewater Treatment Techniques)
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16 pages, 3092 KiB  
Article
Monitoring, Control and Optimization of Laser Micro-Perforation Process for Automotive Synthetic Leather Parts
by Alexandru-Nicolae Rusu, Dorin-Ion Dumitrascu and Adela-Eliza Dumitrascu
Processes 2024, 12(6), 1275; https://doi.org/10.3390/pr12061275 - 20 Jun 2024
Viewed by 464
Abstract
This paper presents a comparative analysis of the laser operating power (P1 and P2) and synthetic leather thickness to achieve the optimal quality of components in the airbag area, produced through micro-perforation laser processing. Within the study, various laser power settings and material [...] Read more.
This paper presents a comparative analysis of the laser operating power (P1 and P2) and synthetic leather thickness to achieve the optimal quality of components in the airbag area, produced through micro-perforation laser processing. Within the study, various laser power settings and material thicknesses were investigated to determine the combinations that ensure the best component performance. The experimental results indicate that setting the laser to 25% of its total power (P1, P2) of two kilowatts (kW) represents the optimal parameter setup to achieve parts of superior quality. This configuration is not significantly influenced by the material thickness, suggesting important versatility in practical applications. The overall results indicate the significant influence of the laser power level on micro-perforation processing. The normal analysis of means (ANOM) and factorial design (DOE) provide significant evidence for an interaction, highlighting that the effects of one laser power factor depend on the level of the other laser power factor. These findings are essential in improving production processes, as they allow for the manufacture of airbag components with high precision and consistency, minimizing the risks of material deformation or damage. Thus, not only is compliance with safety standards ensured, but the economic efficiency of the production process is also enhanced. Full article
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21 pages, 4770 KiB  
Article
Ammoides pusilla Aerial Part: GC-MS Profiling and Evaluation of In Vitro Antioxidant and Biological Activities
by Meriam Belaiba, Mohamed Marouane Saoudi, Manef Abedrabba and Jalloul Bouajila
Processes 2024, 12(6), 1274; https://doi.org/10.3390/pr12061274 - 20 Jun 2024
Viewed by 517
Abstract
The study of Ammoides pusilla, a Tunisian medicinal plant, explored its chemical composition and biological activities, highlighting its under-exploited therapeutic potential. The essential oil, obtained by steam distillation, reveals twenty major compounds, including perilic aldehyde, β-phellandrene, and o-cymene. Two new natural constituents [...] Read more.
The study of Ammoides pusilla, a Tunisian medicinal plant, explored its chemical composition and biological activities, highlighting its under-exploited therapeutic potential. The essential oil, obtained by steam distillation, reveals twenty major compounds, including perilic aldehyde, β-phellandrene, and o-cymene. Two new natural constituents were identified in the cyclohexane extract and four in the dichloromethane extract. DPPH and ABTS tests showed that methanol extract exhibited the highest antioxidant activity, giving values of 78.9% and 65.5%, respectively, at 50 µg/mL. Its anti-diabetic activity (IC50 = 25.0 µg/mL) exceeds that of acarbose. The anti-SOD activity of methanol extract also showed promise, at 73.3% at 50 µg/mL. Essential oil and ethyl acetate extract showed notable inhibition of xanthine oxidase activity, reaching 69.0%. In addition, the essential oil demonstrated strong anti-AChE (63.23% at 50 µg/mL) and anti-inflammatory (IC50 = 31.0 µg/mL) activity. In terms of cytotoxicity, the methanol extract was effective against the HCT116 cell line (IC50 = 20.9 µg/mL), and all extracts showed activity against MCF7, OVCAR-3, and IGROV-1 cells, with IC50 values ranging from 4.0 to 25.0 µg/mL. This result underlines the potential of Ammoides pusilla extracts as important sources of bioactive compounds for therapeutic applications. Further research is needed to fully exploit these activities in drug development. Full article
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17 pages, 4847 KiB  
Article
Inverse Method-Based Kinetic Modelling and Process Optimization of Reverse-Phase Chromatography for Molnupiravir Synthesis
by Athanasios Kritikos, Ravendra Singh, Fernando Muzzio and George Tsilomelekis
Processes 2024, 12(6), 1273; https://doi.org/10.3390/pr12061273 - 20 Jun 2024
Viewed by 623
Abstract
Our research addresses the shift towards continuous manufacturing in the pharmaceutical industry, focusing on optimizing chromatographic separation for the synthesis of molnupiravir. Using an inverse method with six different inlet concentrations for a single objective function, we systematically evaluated the adsorption of key [...] Read more.
Our research addresses the shift towards continuous manufacturing in the pharmaceutical industry, focusing on optimizing chromatographic separation for the synthesis of molnupiravir. Using an inverse method with six different inlet concentrations for a single objective function, we systematically evaluated the adsorption of key intermediates, i.e., hydroxylamine and isobutyrate, in an isocratic solvent, determining the relevant isotherm constants. The study systematically evaluates the effects of operational variables, including flowrate, column geometry, dispersivity coefficient, and injection volume, on chromatographic performance. Findings reveal that specific operational adjustments, such as reducing flowrates or altering column dimensions, significantly influence retention times and peak profiles, thus potentially impacting the efficiency of molnupiravir production. Utilizing the inverse method, we efficiently determined equilibrium isotherms by integrating a nonlinear chromatography model and adjusting isotherm parameters to match the observed band profiles. Our research offers critical insights into optimizing chromatographic separation performance through precise operational control, leveraging computational tools for rapid and adaptable drug development. Full article
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26 pages, 961 KiB  
Review
A Review of Collaborative Trajectory Planning for Multiple Unmanned Aerial Vehicles
by Li Wang, Weicheng Huang, Haoxin Li, Weijie Li, Junjie Chen and Weibin Wu
Processes 2024, 12(6), 1272; https://doi.org/10.3390/pr12061272 - 20 Jun 2024
Viewed by 567
Abstract
In recent years, the collaborative operation of multiple unmanned aerial vehicles (UAVs) has been an important advancement in drone technology. The research on multi-UAV collaborative flight path planning has garnered widespread attention in the drone field, demonstrating unique advantages in complex task execution, [...] Read more.
In recent years, the collaborative operation of multiple unmanned aerial vehicles (UAVs) has been an important advancement in drone technology. The research on multi-UAV collaborative flight path planning has garnered widespread attention in the drone field, demonstrating unique advantages in complex task execution, large-scale monitoring, and disaster response. As one of the core technologies of multi-UAV collaborative operations, the research and technological progress in trajectory planning algorithms directly impact the efficiency and safety of UAV collaborative operations. This paper first reviews the application and research progress of path-planning algorithms based on centralized and distributed control, as well as heuristic algorithms in multi-UAV collaborative trajectory planning. It then summarizes the main technical challenges in multi-UAV path planning and proposes countermeasures for multi-UAV collaborative planning in government, business, and academia. Finally, it looks to future research directions, providing ideas for subsequent studies in multi-UAV collaborative trajectory planning technology. Full article
(This article belongs to the Section Advanced Digital and Other Processes)
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12 pages, 3587 KiB  
Article
Research on Mechanism of Surfactant Improving Wettability of Coking Coal Based on Molecular Dynamics
by Ren Liu, Shilin Li, Yuping Ling, Yuanpei Zhao and Wei Liu
Processes 2024, 12(6), 1271; https://doi.org/10.3390/pr12061271 - 20 Jun 2024
Viewed by 411
Abstract
Coal dust is a major safety hazard in the process of coal mining and is of great importance to ensure production safety and maintain the health of operators. In order to understand the microscopic mechanism during coal seam water injection and reveal the [...] Read more.
Coal dust is a major safety hazard in the process of coal mining and is of great importance to ensure production safety and maintain the health of operators. In order to understand the microscopic mechanism during coal seam water injection and reveal the mechanism of surfactants in improving the wettability of coal dust, coking coal was selected as the research object. Three surfactants, SDBS, AEO-9, and CAB-35, were chosen for molecular dynamics simulation research on the wetting and adsorption properties of water/coal/surfactants. The results show that surfactant molecules can cover the hydrophobic groups on the surface of coking coal, forming a hydrophilic adsorption layer, changing the coal surface from hydrophobic to hydrophilic, and enhancing the wettability. After adding surfactants, the thickness of the adsorption layer in the z-axis direction increases, expanding the contact area between coking coal and water molecules, thereby improving the wettability. When surfactants tightly cover the surface of coking coal, their binding strength increases, forming a more stable hydrophilic layer and further improving the wettability. At the same time, surfactants promote the diffusion of water molecules and enhance the interaction between hydrophobic alkyl chains and water molecules, further enhancing the wetting effect. Full article
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15 pages, 1068 KiB  
Article
Technical Support System for High Concurrent Power Trading Platforms Based on Microservice Load Balancing
by Ping Shao, Longda Huang, Liguo Weng and Ziheng Liu
Processes 2024, 12(6), 1270; https://doi.org/10.3390/pr12061270 - 20 Jun 2024
Viewed by 386
Abstract
With the booming development of the electricity market, market factors such as electricity trading varieties are growing rapidly. The frequency of transactions has become increasingly real-time, and transaction clearing and settlement tasks have become more complex. The increasing demands for concurrent access and [...] Read more.
With the booming development of the electricity market, market factors such as electricity trading varieties are growing rapidly. The frequency of transactions has become increasingly real-time, and transaction clearing and settlement tasks have become more complex. The increasing demands for concurrent access and carrying capacity in trading systems have made it increasingly difficult for existing systems to support business. This article proposes a transaction support system for large-scale electricity trading market entities, which solves the problems of high concurrency access and massive access data calculation while ensuring system security through business isolation measures. The system uses microservices to treat various functional modules as independent service modules, thus making service segmentation and composition more flexible. By using read–write separation, caching mechanisms, and several data reliability assurance measures, data can be stored and accessed quickly and securely. The use of a three-layer load balancing module consisting of an OpenResty access entry layer, a gateway routing gateway layer, and a WebClient service inter-resource invocation layer can effectively improve the system’s ability to handle concurrent access. Full article
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23 pages, 7623 KiB  
Article
Geological Controls on Gas Content of Deep Coal Reservoir in the Jiaxian Area, Ordos Basin, China
by Shaobo Xu, Qian Li, Fengrui Sun, Tingting Yin, Chao Yang, Zihao Wang, Feng Qiu, Keyu Zhou and Jiaming Chen
Processes 2024, 12(6), 1269; https://doi.org/10.3390/pr12061269 - 20 Jun 2024
Viewed by 402
Abstract
Deep coalbed methane (DCBM) reservoirs hold exceptional potential for diversifying energy sources. The Ordos Basin has attracted much attention due to its enormous resource reserves of DCBM. This work focuses on the Jiaxian area of the Ordos basin, and the multi-factor quantitative evaluation [...] Read more.
Deep coalbed methane (DCBM) reservoirs hold exceptional potential for diversifying energy sources. The Ordos Basin has attracted much attention due to its enormous resource reserves of DCBM. This work focuses on the Jiaxian area of the Ordos basin, and the multi-factor quantitative evaluation method on the sealing of cap rocks is established. The abundant geologic and reservoir information is synthesized to explore variable factors affecting the gas content. Results indicate that the sealing capacity of the coal seam roof in the Jiaxian area, with a mean sealing index of 3.12, surpasses the floor’s sealing capacity by 13.87%, which averages 2.74. The sealing of the coal seam roof has a more positive impact on the enrichment of coalbed methane (CBM). In addition, the conditions for preserving gas would be boosted as coal seam thickness increased, leading to enhanced gas content in coal seams. The CH4 content increases by an average of ~2.38 m3/t as coal seam thickness increases with the interval of 1 m. The increasing burial depth represents the incremental maturity of organic matter and the gas generation ability in coal seams, which contributes to improving the gas content in coal seams. There is a positive correlation between the degree of coal fragmentation and the gas content of the coal seam to a certain extent. These findings provide valuable insights for targeted drilling strategies and enhancing natural gas production capacity in the Jiaxian area of the Ordos Basin. Full article
(This article belongs to the Special Issue Shale Gas and Coalbed Methane Exploration and Practice)
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14 pages, 5974 KiB  
Article
Research on the Temperature Field Distribution Characteristics of Bottomhole PDC Bits during the Efficient Development of Unconventional Oil and Gas in Long Horizontal Wells
by Li Fu, Henglin Yang, Chunlong He, Yuan Wang, Heng Zhang, Gang Chen and Yukun Du
Processes 2024, 12(6), 1268; https://doi.org/10.3390/pr12061268 - 19 Jun 2024
Viewed by 462
Abstract
Unconventional tight oil and gas resources, including shale oil and gas, have become the main focus for increasing reserves and production. The safe and efficient development of unconventional oil and gas is a crucial demand for the energy development strategy. Deep tight oil [...] Read more.
Unconventional tight oil and gas resources, including shale oil and gas, have become the main focus for increasing reserves and production. The safe and efficient development of unconventional oil and gas is a crucial demand for the energy development strategy. Deep tight oil and gas resource development generally adopts horizontal well drilling methods. During drilling, especially in long horizontal sections, the high temperature frequently causes failures of downhole drilling tools and rotary steering tools. The temperature rises sharply during rock breaking with the drill bit. Existing wellbore heat transfer models do not fully consider the impact of heat generated by the drill bit on the wellbore temperature field. This paper aims to experimentally study the temperature rise law of the cutting tooth of the bottom polycrystalline diamond compact (PDC) bit during rock breaking. A set of evaluation devices was developed to study the temperature field distribution characteristics at the bottom of the PDC bit during rock breaking under different experimental conditions. The results indicate that the flow rate of drilling fluid, bit rotation speed, and weight on bit (WOB) significantly affect the distribution of the temperature field at the well bottom. This experimental research on the temperature field distribution characteristics at the bottom of the PDC bit during rock breaking helps reveal the heat transfer characteristics of the long horizontal section wellbore, guide the optimization of drilling parameters, and develop temperature control methods. It is of great significance for the advancement of efficient development technologies for unconventional resources in long horizontal wells. Full article
(This article belongs to the Section Energy Systems)
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18 pages, 9234 KiB  
Article
High-Density Polyethylene Pipe Butt-Fusion Joint Detection via Total Focusing Method and Spatiotemporal Singular Value Decomposition
by Haowen Zhang, Qiang Wang, Juan Zhou, Linlin Wu, Weirong Xu and Hong Wang
Processes 2024, 12(6), 1267; https://doi.org/10.3390/pr12061267 - 19 Jun 2024
Viewed by 406
Abstract
High-density polyethylene (HDPE) pipes are widely used for urban natural gas transportation. Pipes are usually welded using the technique of thermal butt fusion, which is prone to manufacturing defects that are detrimental to safe operation. This paper proposes a spatiotemporal singular value decomposition [...] Read more.
High-density polyethylene (HDPE) pipes are widely used for urban natural gas transportation. Pipes are usually welded using the technique of thermal butt fusion, which is prone to manufacturing defects that are detrimental to safe operation. This paper proposes a spatiotemporal singular value decomposition preprocessing improved total focusing method (STSVD-ITFM) imaging algorithm combined with ultrasonic phased array technology for non-destructive testing. That is, the ultrasonic real-value signal data are first processed using STSVD filtering, enhancing the spatiotemporal singular values corresponding to the defective signal components. The TFM algorithm is then improved by establishing a composite modification factor based on the directivity function and the corrected energy attenuation factor by adding angle variable. Finally, the filtered signal data are utilized for imaging. Experiments are conducted by examining specimen blocks of HDPE materials with through-hole defects. The results show the following: the STSVD-ITFM algorithm proposed in this paper can better suppress static clutter in the near-field region, and the average signal-to-noise ratios are all higher than the TFM algorithm. Moreover, the STSVD-ITFM algorithm has the smallest average error among all defect depth quantification results. Full article
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18 pages, 3246 KiB  
Article
Mathematical Models for Estimating Diffusion Coefficients in Concentrated Polymer Solutions from Experimental Data
by Adriana Mariana Asoltanei, Eugenia Teodora Iacob-Tudose, Marius Sebastian Secula and Ioan Mamaliga
Processes 2024, 12(6), 1266; https://doi.org/10.3390/pr12061266 - 19 Jun 2024
Viewed by 515
Abstract
Diffusion processes in operations involving polymeric materials are of significant interest. Determining experimental values for diffusion coefficients is often challenging. Estimating these coefficients in concentrated polymer solution, polymer films, and membranes relies on experimental tests where the polymer is brought into contact with [...] Read more.
Diffusion processes in operations involving polymeric materials are of significant interest. Determining experimental values for diffusion coefficients is often challenging. Estimating these coefficients in concentrated polymer solution, polymer films, and membranes relies on experimental tests where the polymer is brought into contact with certain components/solvents. The diffusion coefficient values depend on the diffusion type, which is affected mainly by the nature of the polymer, concentration, and temperature. The literature presents an extensive amount of information regarding the diffusion phenomenon. This paper makes a particular contribution by showing how experimental data obtained from different applications can be processed to determine diffusion coefficients. The manuscript addresses some aspects regarding solvent diffusion in polymers, and illustrates how to determine the diffusion coefficients from experimental data. For specific cases of diffusion, several models for the predictive estimation of diffusion coefficients are also presented. Polymer–solvent systems such as polyvinyl alcohol (PVA)–water, cellulose acetate (CA)–tetrahydrofuran (THF) and cellulose triacetate (CTA)–dichloromethane (DCM) are investigated, with their diffusion mechanisms influenced by changes in structure caused by variations in concentration and temperature. The experimental data obtained through a gravitational technique allow for the highlighting of the diffusion mechanism and the selection of an appropriate mathematical model. A change in the structure of the polymer during the experiment leads to diffusion anomalies. Modeling the experimental data yielded diffusion coefficient values that vary based on the type of system investigated, composition and temperature. Thus, in the case of the CTA-DCM system, the diffusion coefficient at 303 K, at various concentration values, is in the range of 4.5 and 8·10−11 m2/s; for the PVA-H2O system, D = 4.1·10−12 m2/s at 303 K, and D = 6.5·10−12 m2/s at 333 K; while for the CA-THF system, the solvent–polymer diffusion coefficient has a value of 2.5∙10−12 m2/s at 303 K, and D = 1.75∙10−11 m2/s at 323 K. Mathematical models can be useful in studies regarding the drying of polymer films with complex structures, providing knowledge for designing or selecting suitable equipment. Full article
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12 pages, 2184 KiB  
Article
Mineral Water as a Sustainable Raw Material for Skincare Products and Protective Natural Antioxidant from Solar Irradiation: Stability of Vitamin C and In Vitro Antioxidant Assessments
by Szabolcs Bognár, Daniela Šojić Merkulov, Nina Finčur, Predrag Putnik, Gabor Katona, Slađana Vojvodić, Marina Kalić, Nataša Nastić and Nataša Jovanović Lješković
Processes 2024, 12(6), 1265; https://doi.org/10.3390/pr12061265 - 19 Jun 2024
Viewed by 608
Abstract
Oxygen is crucial for life, but its reactive species, like free radicals, can damage health and accelerate aging. Antioxidants from natural and synthetic sources mitigate these effects. Kanjiža Spa’s mineral-rich thermal water is renowned for its therapeutic benefits and potential in eco-friendly pharmaceuticals [...] Read more.
Oxygen is crucial for life, but its reactive species, like free radicals, can damage health and accelerate aging. Antioxidants from natural and synthetic sources mitigate these effects. Kanjiža Spa’s mineral-rich thermal water is renowned for its therapeutic benefits and potential in eco-friendly pharmaceuticals and cosmetics. Hence, the utilization of mineral water in pharmaceutical and cosmetic applications when exposed to artificially generated free radicals under simulated solar irradiation and different experimental conditions (pH values and mineral concentrations in the thermal water) was researched. Three different dermocosmetic products designed with raw minerals and water from Kanjiža Spa were tested. Our findings confirmed the protective effect of mineral water, as evidenced by the higher stability of vitamin C in thermal water. The degradation of vitamin C was significantly reduced in the presence of mineral water, with the least degradation occurring at pH = 7, which closely matches human skin pH. These results were further validated using 2,2-diphenyl-1-picrylhydrazyl and ABTS tests. Overall, the obtained results underscore the therapeutic and commercial potential of Kanjiža Spa’s mineral water, suggesting that it could be a valuable ingredient in next-generation skincare and pharmaceutical products. Full article
(This article belongs to the Section Food Process Engineering)
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21 pages, 7636 KiB  
Article
Primary-Side Indirect Control of the Battery Charging Current in a Wireless Power Transfer Charger Using Adaptive Hill-Climbing Control Technique
by Abdellah Lassioui, Marouane El Ancary, Zakariae El Idrissi, Hassan El Fadil, Kamal Rachid and Aziz Rachid
Processes 2024, 12(6), 1264; https://doi.org/10.3390/pr12061264 - 19 Jun 2024
Viewed by 457
Abstract
This paper addresses the control task of a wireless power transfer (WPT) charger designed for electric vehicles (EVs). The challenge is to maintain a constant battery charging current when the WPT is controlled on the ground side. Indeed, the intermittent latency involved in [...] Read more.
This paper addresses the control task of a wireless power transfer (WPT) charger designed for electric vehicles (EVs). The challenge is to maintain a constant battery charging current when the WPT is controlled on the ground side. Indeed, the intermittent latency involved in the wireless data communication between the ground and vehicle sides leads to system instability. To overcome this issue, a new control approach has been proposed in this paper. The proposed technique ensures indirect control of the battery charging current through control of the current on the ground side. The control technique relies on an adaptive hill-climbing algorithm in conjunction with a PI-based controller. The adaptive parameter is adjusted online, during the operation of the charger, only when a new measure of the battery charging current is received on the primary side. This makes it possible to avoid the need for real-time wireless data communication. It should be noted that this aspect is crucial in ensuring the controller’s robustness and stability of the system regardless of potential delays in wireless communication and large misalignments between the coils. The validity of the proposed control technique has been confirmed through simulation. In addition, experimental validation, using a laboratory test bed, demonstrated satisfactory results. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control in Energy Systems)
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27 pages, 3371 KiB  
Article
Onion Peel: A Promising, Economical, and Eco-Friendly Alternative for the Removal of Divalent Cobalt from Aqueous Solutions
by Yehudy Yelitza Lizcano-Delgado, Osiris Tais Martínez-Vázquez, Eliseo Cristiani-Urbina and Liliana Morales-Barrera
Processes 2024, 12(6), 1263; https://doi.org/10.3390/pr12061263 - 19 Jun 2024
Viewed by 674
Abstract
There is a growing need for an economical and efficient method capable of removing heavy metals from residual water. The current contribution aimed to evaluate the capacity of onion peel, an abundant agroindustrial waste product, to remove divalent cobalt (Co2+) from [...] Read more.
There is a growing need for an economical and efficient method capable of removing heavy metals from residual water. The current contribution aimed to evaluate the capacity of onion peel, an abundant agroindustrial waste product, to remove divalent cobalt (Co2+) from aqueous solutions. Onion peel was submitted to proximal chemical analysis, and various operational factors involved in biosorption were tested. The most suitable temperature (30 °C), pH (7.0), and biosorbent particle size (300–800 µm) were found. With an initial Co2+ concentration of 380 mg L−1, the maximum capacity of Co2+ removal was 59.88 mg g−1 in 120 min. The pseudo-second order and Langmuir models provided the best fit to the experimental kinetics and equilibrium of Co2+ biosorption, respectively. The thermodynamic study evidenced an exothermic, non-spontaneous, and favorable reaction (ΔH0 = −5.78 kJ mol−1; ΔS0 = −21.13 J mol−1 K−1), suggesting the formation of stable bonds in the biosorbent-Co2+ complex. The carbonyl and hydroxyl groups apparently play a fundamental role in Co2+ removal, and electrostatic attraction, ion exchange, and chemisorption are the principal mechanisms. Thus, the biosorption of Co2+ by onion peel has potential as an economical, eco-friendly, efficient, and sustainable treatment for wastewater. Full article
(This article belongs to the Section Food Process Engineering)
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16 pages, 3200 KiB  
Article
Learning More with Less Data in Manufacturing: The Case of Turning Tool Wear Assessment through Active and Transfer Learning
by Alexios Papacharalampopoulos, Kosmas Alexopoulos, Paolo Catti, Panagiotis Stavropoulos and George Chryssolouris
Processes 2024, 12(6), 1262; https://doi.org/10.3390/pr12061262 - 19 Jun 2024
Viewed by 434
Abstract
Monitoring tool wear is key for the optimization of manufacturing processes. To achieve this, machine learning (ML) has provided mechanisms that work adequately on setups that measure the cutting force of a tool through the use of force sensors. However, given the increased [...] Read more.
Monitoring tool wear is key for the optimization of manufacturing processes. To achieve this, machine learning (ML) has provided mechanisms that work adequately on setups that measure the cutting force of a tool through the use of force sensors. However, given the increased focus on sustainability, i.e., in the context of reducing complexity, time and energy consumption required to train ML algorithms on large datasets dictate the use of smaller samples for training. Herein, the concepts of active learning (AL) and transfer learning (TL) are simultaneously studied concerning their ability to meet the aforementioned objective. A method is presented which utilizes AL for training ML models with less data and then it utilizes TL to further reduce the need for training data when ML models are transferred from one industrial case to another. The method is tested and verified upon an industrially relevant scenario to estimate the tool wear during the turning process of two manufacturing companies. The results indicated that through the application of the AL and TL methodologies, in both companies, it was possible to achieve high accuracy during the training of the final model (1 and 0.93 for manufacturing companies B and A, respectively). Additionally, reproducibility of the results has been tested to strengthen the outcomes of this study, resulting in a small standard deviation of 0.031 in the performance metrics used to evaluate the models. Thus, the novelty presented in this paper is the presentation of a straightforward approach to apply AL and TL in the context of tool wear classification to reduce the dependency on large amounts of high-quality data. The results show that the synergetic combination of AL with TL can reduce the need for data required for training ML models for tool wear prediction. Full article
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17 pages, 11524 KiB  
Article
Study on the Law of Rock Drillability under High-Temperature and High-Pressure Conditions in the Western Margin of the Ordos Basin
by Liang Zhu, Zelong Xie, Xiaoming Li, Yipeng Zhao, Tianyi Wang and Ximing Yang
Processes 2024, 12(6), 1261; https://doi.org/10.3390/pr12061261 - 19 Jun 2024
Viewed by 354
Abstract
The deep strata in the Ordos Basin exhibit characteristics of high temperature and high stress. Conventional methods for assessing drillability (normal temperature and pressure) fail to accurately understand the drilling resistance characteristics of deep rocks in this region, leading to improper guidance for [...] Read more.
The deep strata in the Ordos Basin exhibit characteristics of high temperature and high stress. Conventional methods for assessing drillability (normal temperature and pressure) fail to accurately understand the drilling resistance characteristics of deep rocks in this region, leading to improper guidance for selecting formation drilling tools and prolonging drilling cycles. This study employs physical experiments and numerical simulations to conduct drillability tests on core samples taken from the region under high-temperature and high-pressure conditions, simultaneously simulating the rock breaking process under different temperature and pressure conditions. The study investigates the variation patterns of rock drillability grade values and von Mises stress values during rock breaking under single-factor and multi-factor analyses of temperature and pressure conditions. Combining these variation patterns, an optimization analysis of the back rake angle of PDC drill bits used in drillability experiments is conducted to guide the selection of drill bits on site. The results indicate that the variation patterns of von Mises values from finite element simulations are consistent with the drillability grade values under high-temperature and high-pressure conditions. Under single-factor conditions, von Mises stress and drillability grade values generally increase with rising temperature before decreasing, while they increase with increasing confining pressure. Under multi-factor conditions, confining pressure is the primary influencing factor within the range of 0 to 50 MPa, while the influence of temperature becomes prominent between 180 °C to 200 °C, with a weakening effect of confining pressure. Model application: Selecting a back rake angle of 30° for PDC drill bits yields optimal rock-breaking results. The research findings hold significant implications for understanding the low rock-breaking efficiency of deep strata, optimizing drill bit parameters, and enhancing drilling efficiency. Full article
(This article belongs to the Section Energy Systems)
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34 pages, 14147 KiB  
Article
Dynamic Numerical Simulation and Transfer Learning-Based Rapid Rock Identification during Measurement While Drilling (MWD)
by Yuwei Fang, Zhenjun Wu, Lianghua Jiang, Hua Tang, Xiaodong Fu and Junxin Shen
Processes 2024, 12(6), 1260; https://doi.org/10.3390/pr12061260 - 19 Jun 2024
Viewed by 439
Abstract
In constructing rapid rock identification models for measurement while drilling (MWD) via neural network methods, collecting actual drilling data to train the model is extremely time-consuming and labor-intensive. This requires extensive drilling experiments in various rock types, resulting in limited neural network training [...] Read more.
In constructing rapid rock identification models for measurement while drilling (MWD) via neural network methods, collecting actual drilling data to train the model is extremely time-consuming and labor-intensive. This requires extensive drilling experiments in various rock types, resulting in limited neural network training data for rock identification that covers a limited range of rock types. To suitably address this issue, a dynamic numerical simulation model for rock drilling is established that generates extensive drilling data. The input parameters for the simulations include torque, drill bit rotation speed, and drilling speed. A neural network model is then developed for rock classification using large datasets from dynamic numerical simulations, specifically those of granite, limestone, and sandstone. Building upon this model, transfer learning is appropriately applied to store the knowledge obtained in the rock identification based on the neural network model. Further training through transfer learning is conducted with smaller datasets obtained during actual drilling, making the model suitable for practical rock identification and prediction in the drilling processes. The neural network rock classification model, incorporating dynamic numerical simulation and transfer learning, achieves a prediction accuracy of 99.36% for granite, 99.53% for sandstone, and 99.82% for limestone. This reveals an enhancement in prediction accuracy of up to 22.94% compared to the models without transfer learning. Full article
(This article belongs to the Section Energy Systems)
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15 pages, 3133 KiB  
Article
Development and Validation of Ultra-Performance Liquid Chromatography (UPLC) Method for Simultaneous Quantification of Hydrochlorothiazide, Amlodipine Besylate, and Valsartan in Marketed Fixed-Dose Combination Tablet
by Doaa Hasan Alshora, Abdelrahman Y. Sherif and Mohamed Abbas Ibrahim
Processes 2024, 12(6), 1259; https://doi.org/10.3390/pr12061259 - 19 Jun 2024
Viewed by 479
Abstract
Fixed-dose combination therapy is considered a practical approach in the treatment of various diseases, as it can simultaneously target different mechanisms of action that achieve the required therapeutic efficacy through a synergistic effect. A combination of hydrochlorothiazide (HTZ), amlodipine (AMD), and valsartan (VLS) [...] Read more.
Fixed-dose combination therapy is considered a practical approach in the treatment of various diseases, as it can simultaneously target different mechanisms of action that achieve the required therapeutic efficacy through a synergistic effect. A combination of hydrochlorothiazide (HTZ), amlodipine (AMD), and valsartan (VLS) has been created for the treatment of hypertension. Therefore, the aim of this study was to develop an optimized UPLC method for the simultaneous quantification of this combination. A DoE at a level of 32 was used to investigate the effects of column temperature (20, 30, and 40 °C) and formic acid concentration (0.05, 0.15, and 0.25%) on the retention time of each active pharmaceutical ingredient (API), the peak area, and the peak symmetry, as well as the resolution between HTZ-AMD and AMD-VLS peaks. The optimized analytical method was validated and used to extract the three APIs from the marketed product. The optimized analytical condition with a column temperature of 27.86 °C and a formic acid concentration of 0.172% showed good separation of the three APIs in 1.62 ± 0.006, 3.59 ± 0.002, and 3.94 ± 0.002 min for HTZ, AMD, and VST, respectively. The developed method was linear with the LOQ for a HTC, AMD, and VST of 0.028, 0.038, and 0.101 ppm, respectively. Moreover, the developed assay was sustainable and robust, with an RSD % of less than 2%. The application of this method in the extraction of HTZ, AMD, and VST from the Exforge® marketed product showed good separation with a measurable drug content of 23.5 ± 0.7, 9.68 ± 0.1, and 165.2 ± 5.2 mg compared to the label claims of 25/10/160 for HTZ, AMD, and VST, respectively. Full article
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15 pages, 5302 KiB  
Article
Image Analysis Techniques Applied in the Drilling of a Carbon Fibre Reinforced Polymer and Aluminium Multi-Material to Assess the Delamination Damage
by Rúben D. F. Sousa Costa, Marta L. S. Barbosa, Filipe G. A. Silva, Tiago E. F. Silva, Abílio M. P. de Jesus, Francisco J. G. Silva, Luís M. P. Durão and João Manuel R. S. Tavares
Processes 2024, 12(6), 1258; https://doi.org/10.3390/pr12061258 - 19 Jun 2024
Viewed by 572
Abstract
Due to the high abrasiveness and anisotropic nature of composites, along with the need to machine different materials at the same time, drilling multi-materials is a difficult task, and usually results in material damage, such as uncut fibres and delamination, hindering hole functionality [...] Read more.
Due to the high abrasiveness and anisotropic nature of composites, along with the need to machine different materials at the same time, drilling multi-materials is a difficult task, and usually results in material damage, such as uncut fibres and delamination, hindering hole functionality and reliability. Image processing and analysis algorithms can be developed to effectively assess such damage, allowing for the calculation of delamination factors essential to the quality control of hole inspection in composite materials. In this study, a digital image processing and analysis algorithm was developed in Python to perform the delamination evaluation of drilled holes on a carbon fibre reinforced polymer (CFRP) and aluminium (Al) multi-material. This algorithm was designed to overcome several limitations often found in other algorithms developed with similar purposes, which frequently lead to user mistakes and incorrect results. The new algorithm is easy to use and, without requiring manual pre-editing of the input images, is fully automatic, provides more complete and reliable results (such as the delamination factor), and is a free-of-charge software. For example, the delamination factors of two drilled holes were calculated using the new algorithm and one previously developed in Matlab. Using the previous Matlab algorithm, the delamination factors of the two holes were 1.380 and 2.563, respectively, and using the new Python algorithm, the results were equal to 3.957 and 3.383, respectively. The Python results were more trustworthy, as the first hole had a higher delamination area, so its factor should be higher than that of the second one. Full article
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21 pages, 5497 KiB  
Article
Study on Activation and Restructuring of Key Strata in Shallowly Buried Coal Seam Bearing Structure and Load Characteristics
by Yifeng He, Jie Zhang, Hui Liu, Tao Yang and Jianping Sun
Processes 2024, 12(6), 1257; https://doi.org/10.3390/pr12061257 - 18 Jun 2024
Viewed by 542
Abstract
The mining of shallow coal seam groups triggers the activation of overlying strata, leading to increased pressure and support difficulties, thereby posing a threat to the safe extraction of underlying coal seams. Against the backdrop of Longhua Coal Mine, this study utilized physical [...] Read more.
The mining of shallow coal seam groups triggers the activation of overlying strata, leading to increased pressure and support difficulties, thereby posing a threat to the safe extraction of underlying coal seams. Against the backdrop of Longhua Coal Mine, this study utilized physical similarity simulation experiments to obtain the activated, restructured load-bearing structure and the migration characteristics of overlying strata. Theoretical calculations were employed to establish both a rolling friction mechanics model for the activated load-bearing structure and a mechanical model for the combined load-bearing structure of key strata. The research indicates that during the initial activation phase, the load-bearing structure exhibits a V-shaped hinged arch, with directly collapsed rock masses transitioning towards spherical shapes, resulting in the sub-key strata shifting from sliding friction to rolling friction. Based on the rolling friction mechanics model of the activated load-bearing structure, we derived the rolling friction coefficient of key blocks in the sub-key strata and the instability criterion of the load-bearing structure under rolling friction conditions. Considering the migration characteristics of the activated restructured load-bearing structure, four types of combined load-bearing structures were identified, and the load calculation formulas in the mechanical model were derived, with the rationality of these formulas verified through case analysis. Full article
(This article belongs to the Section Energy Systems)
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28 pages, 4239 KiB  
Review
Advancing Wastewater Treatment: A Comparative Study of Photocatalysis, Sonophotolysis, and Sonophotocatalysis for Organics Removal
by Szabolcs Bognár, Dušica Jovanović, Vesna Despotović, Nina Finčur, Predrag Putnik and Daniela Šojić Merkulov
Processes 2024, 12(6), 1256; https://doi.org/10.3390/pr12061256 - 18 Jun 2024
Viewed by 369
Abstract
Clear and sanitarily adequate water scarcity is one of the greatest problems of modern society. Continuous population growth, rising organics concentrations, and common non-efficient wastewater treatment technologies add to the seriousness of this issue. The employment of various advanced oxidation processes (AOPs) in [...] Read more.
Clear and sanitarily adequate water scarcity is one of the greatest problems of modern society. Continuous population growth, rising organics concentrations, and common non-efficient wastewater treatment technologies add to the seriousness of this issue. The employment of various advanced oxidation processes (AOPs) in water treatment is becoming more widespread. In this review, the state-of-the-art application of three AOPs is discussed in detail: photocatalysis, sonophotolysis, and sonophotocatalysis. Photocatalysis utilizes semiconductor photocatalysts to degrade organic pollutants under light irradiation. Sonophotolysis combines ultrasound and photolysis to generate reactive radicals, enhancing the degradation of organic pollutants. Sonophotocatalysis synergistically combines ultrasound with photocatalysis, resulting in improved degradation efficiency compared to individual processes. By studying this paper, readers will get an insight into the latest published data regarding the above-mentioned processes from the last 10 years. Different factors are compared and discussed, such as degradation efficiency, reaction kinetics, catalyst type, ultrasound frequency, or water matrix effects on process performance. In addition, the economic aspects of sonophotolysis, photocatalysis, and sonophotocatalysis will be also analyzed and compared to other processes. Also, the future research directions and potential applications of these AOPs in wastewater treatment will be highlighted. This review offers invaluable insights into the selection and optimization of AOPs. Full article
(This article belongs to the Special Issue 2nd Edition of Innovation in Chemical Plant Design)
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15 pages, 2009 KiB  
Article
Hydrophobic Deep Eutectic Solvents for Ethanol, Propan-1-ol, and Propan-2-ol Recovery from Aqueous Solutions
by Dalal J. S. A. Audeh, Adriano Carniel, Cristiano Piacsek Borges, Maria Alice Zarur Coelho, Filipe Smith Buarque and Bernardo Dias Ribeiro
Processes 2024, 12(6), 1255; https://doi.org/10.3390/pr12061255 - 18 Jun 2024
Viewed by 609
Abstract
Separating hydroalcoholic mixtures remains a significant challenge in engineering. Liquid–liquid extraction has emerged as an appealing alternative method, because it avoids the need for the large energy inputs, volatile organic compounds, and high pressures that are typically required by other separation processes. This [...] Read more.
Separating hydroalcoholic mixtures remains a significant challenge in engineering. Liquid–liquid extraction has emerged as an appealing alternative method, because it avoids the need for the large energy inputs, volatile organic compounds, and high pressures that are typically required by other separation processes. This study explores the use of hydrophobic deep eutectic solvents (HDESs) composed of terpenes and 10-undecenoic acid as extraction agents for the liquid–liquid separation of hydroalcoholic mixtures composed of alcohols (ethanol, propan-1-ol, and propan-2-ol) and water. The water content in the solvents studied was notably low, reflecting their hydrophobic nature. For the dried HDES samples, the water content ranged from 553 to 4901 ppm. In contrast, the water-saturated samples exhibited higher water contents, ranging from 7250 to 20,864 ppm. The HDES based on thymol, DL-menthol, and L-menthol displayed a eutectic point at an xterpenes of approximately 0.67. These mixtures maintained a liquid state up to a mole fraction of terpenes around 0.75. In contrast, the HDES composed of carvacrol, fenchyl alcohol, and α-terpineol exhibited their eutectic point at an xterpenes near 0.5. Notably, these mixtures remained in a liquid state across the entire composition range studied. The 2:1 molar ratio (HBA:HBD) presented the best values for extracting alcohols, reaching 34.04%, 36.59%, and 39.78% for ethanol, propan-2-ol, and propan-1-ol, respectively. These results show that HDES can be applied to overcome issues with existing extraction solvents, increasing the separation efficiency and making the process eco-friendly. Full article
(This article belongs to the Special Issue Green Separation and Purification Processes)
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23 pages, 9966 KiB  
Article
Rapid Classification and Diagnosis of Gas Wells Driven by Production Data
by Zhiyong Zhu, Guoqing Han, Xingyuan Liang, Shuping Chang, Boke Yang and Dingding Yang
Processes 2024, 12(6), 1254; https://doi.org/10.3390/pr12061254 - 18 Jun 2024
Viewed by 538
Abstract
Conventional gas well classification methods cannot provide effective support for gas well routine management, and suffer from poor timeliness. In order to guide the on-site operation in liquid loading gas wells and improve the timeliness of gas well classification, this paper proposes a [...] Read more.
Conventional gas well classification methods cannot provide effective support for gas well routine management, and suffer from poor timeliness. In order to guide the on-site operation in liquid loading gas wells and improve the timeliness of gas well classification, this paper proposes a production data-driven gas well classification method based on the LDA-DA (Linear Discriminant Analysis–Discriminant Analysis) combination model. In this method, considering the requirements of routine management, gas wells are evaluated from two aspects: liquid drainage capacity (LDC) and liquid production intensity (LPI), and are classified into six types. Domain knowledge is used to perform the feature engineering on the on-site production data, and five features are set up to quantitatively evaluate the gas well and to create classification samples. On this basis, in order to specify the optimal data processing flow to establish the gas well classification map, four linear dimensionality reduction techniques, LDA, PCA, LPP, and ICA, are used to reduce the dimensionality of original classification samples, and then, four classical classification algorithms, NB, DA, KNN, and SVM, are trained and evaluated on the low-dimensional samples, respectively. The results show that the LDA space achieves the optimal sample separation and is chosen as the decision space for gas well classification. The DA algorithm obtains the top performance, i.e., the highest Average Macro F1-score of 95.619%, in the chosen decision space, and is employed to determine the classification boundaries in the decision space. At this point, the LDA-DA combination model for sample data processing is developed. Based on this model, gas well classification maps can be established by data mining, and the rapid evaluation and diagnosis of gas wells can be achieved. This method realizes instant and efficient production data-driven gas well classification, and can provide timely decision-making support for gas well routine management. It introduces new ideas for performing gas well classification, expanding the content and scope of the classification work, and presenting valuable insights for further research in this field. Full article
(This article belongs to the Section Energy Systems)
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18 pages, 14278 KiB  
Article
Research on Thread Seal Failure Mechanism of Casing Hanger in Shale Gas Wells and Prevention Measures
by Yisheng Mou, Yonggang Xie, Fengqi Wei, Han Zhao and Lihong Han
Processes 2024, 12(6), 1253; https://doi.org/10.3390/pr12061253 - 18 Jun 2024
Viewed by 362
Abstract
The strength and sealing failure of the connecting thread of the casing head mandrel hanger causes huge economic losses. One of the major challenges is the thread seal failure mechanism of the casing hanger in the wellhead during pressure testing in shale gas [...] Read more.
The strength and sealing failure of the connecting thread of the casing head mandrel hanger causes huge economic losses. One of the major challenges is the thread seal failure mechanism of the casing hanger in the wellhead during pressure testing in shale gas wells. In order to analyze the failure causes of connecting threads and put forward improvement measures, a typical case of a well accompanied by a hanger seal failure is analyzed in this paper, and a series of material tests are carried out. The microstructure and mechanical properties of casing materials and hanger materials could meet the field requirements. It is concluded that both the hanger material and casing material are characterized with significant ductile fracture. A three-dimensional model of the hanger and casing system is established, and the mechanical behavior is calculated for the connecting thread under different working conditions. The results showed that the connection degree of the hanger–casing is insufficient at the torque recommended by the manufacturer because of the difference in wall thickness between the box thread of the hanger and the box thread of the joint according to the connection degree of the coupling casing. It is seen that the high contact pressure ring of zone three on the sealing surface plays an effective sealing role under the manufacturer’s recommended torque (20,465 N·m). Finally, when the torque is increased by 25%, the maximum contact pressure between the pin thread of the casing and the box thread of the hanger can fully meet the internal pressure from the wellbore pressure test and the internal pressure strength required for subsequent operations. Full article
(This article belongs to the Special Issue Risk Assessment and Reliability Engineering of Process Operations)
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14 pages, 1652 KiB  
Article
Demand Management for Manufacturing Loads Considering Temperature Control under Dynamic Electricity Prices
by Yan Yang, Junhui Yu and Hengrui Ma
Processes 2024, 12(6), 1252; https://doi.org/10.3390/pr12061252 - 18 Jun 2024
Viewed by 314
Abstract
Demand response (DR) can provide extra scheduling flexibility for power systems. Different from industrial and residential loads, the production process of manufacturing loads includes multiple production links, and complex material flow and energy flow are closely coupled, which can be seen as a [...] Read more.
Demand response (DR) can provide extra scheduling flexibility for power systems. Different from industrial and residential loads, the production process of manufacturing loads includes multiple production links, and complex material flow and energy flow are closely coupled, which can be seen as a typical nondeterministic polynomial-time (NP) hard problem. In addition, there is a coupling effect between the temperature-controlled loads (TCLs) and the manufacturing loads, which has often been ignored in previous research, resulting in conservative electricity consumption planning. This paper proposes an optimal demand management for the manufacturing industry. Firstly, the power consumption characteristics of manufacturing loads are analyzed in detail. A state task network (STN) is introduced to decouple the relationship between energy and material flow in each production link. Combining STN and production equipment parameters, a general MILP model is constructed to describe the whole production process of the manufacturing industry. Then, a mathematical model of the TCLs considering a comfortable human degree is established. Fully considering the electricity consumption behavior of equipment and TCLs, the model predictive control (MPC) method is adopted to generate the optimal scheduling plan. Finally, an actual seat production enterprise is used to verify the feasibility and effectiveness of the proposed demand management strategy. Full article
(This article belongs to the Section Energy Systems)
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