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Volume 12
Issue 10
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Processes, Volume 12, Issue 10 (October 2024) – 249 articles

Cover Story (view full-size image): A morphological study of the MnTe-like structures is carried out by the evaluation of the tortuosity tensor and other related parameters using a computational fluid dynamics approach. Such a study focuses on all possible crystals–existing or not yet developed–having the same structure as the MnTe crystal. This analysis provides new information not present yet in the open literature. The structures are created by tuning two independent geometrical parameters, allowing for the inter-penetration of particles in order to enlarge the study’s applicability. The results are mainly obtained in terms of tortuosity tensor, anisotropy, connectivity and principal diffusion directions, which enable the establishment of a structure orientation to maximise or minimise the permeating flux through the considered structure. View this paper
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15 pages, 2840 KiB  
Article
Rapid Detection of Adulteration in Minced Lamb Meat Using Vis-NIR Reflectance Spectroscopy
by Xiaojia Zuo, Yanlei Li, Xinwen Chen, Li Chen and Chang Liu
Processes 2024, 12(10), 2307; https://doi.org/10.3390/pr12102307 - 21 Oct 2024
Viewed by 855
Abstract
In view of the phenomenon that adulterated lamb with other animal-derived meats in the market could not be quickly identified, this study used visible near-infrared spectroscopy combined with chemometric methods to quickly identify and quantify lamb rolls adulterated with chicken, duck, and pork. [...] Read more.
In view of the phenomenon that adulterated lamb with other animal-derived meats in the market could not be quickly identified, this study used visible near-infrared spectroscopy combined with chemometric methods to quickly identify and quantify lamb rolls adulterated with chicken, duck, and pork. The spectra of the visible–near-infrared band (350–1000 nm) and near-infrared band (1000–1700 nm) of 360 lamb samples, which were mixed with chicken, duck, pork, and 10% lamb oil separately in different increasing proportions, were collected. It was found that the qualitative models of heterogeneous meat (adulterated with chicken, duck, and pork) in lamb were constructed by the combination of first derivative and multiplicative scatter correction (MSC); the accuracy of the validation set reached 100%; the meantime accuracy of the cross-validation set reached 100% (pure lamb), 98.3% (adulterated with chicken), 98.7% (adulterated with duck), and 97.3% (adulterated with pork). Furthermore, the correlation coefficient (R2c) of the adulterated chicken, pork, and duck quantitative prediction models reached 0.972 (chicken), 0.981 (pork), and 0.985 (duck). In summary, the use of Vis NIR can identify lamb meat mixed with chicken, duck, and pork and can quantitatively predict the content of adulterated meat. Full article
(This article belongs to the Special Issue Processing Foods: Process Optimization and Quality Assessment, 3rd Edition)
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19 pages, 8515 KiB  
Article
Prediction of Capillary Pressure Curves Based on Particle Size Using Machine Learning
by Xinghua Qi, Yuxuan Wei, Shimao Wang, Zhuwen Wang and Mingyu Zhou
Processes 2024, 12(10), 2306; https://doi.org/10.3390/pr12102306 - 21 Oct 2024
Viewed by 968
Abstract
Capillary pressure curves are usually obtained through mercury injection experiments, which are mainly used to characterize pore structures. However, mercury injection experiments have many limitations, such as operation danger, a long experiment period, and great damage to the sample. Therefore, researchers have tried [...] Read more.
Capillary pressure curves are usually obtained through mercury injection experiments, which are mainly used to characterize pore structures. However, mercury injection experiments have many limitations, such as operation danger, a long experiment period, and great damage to the sample. Therefore, researchers have tried to predict capillary pressure data based on NMR data, but NMR data are expensive and unstable to obtain. This study aims to accurately predict capillary pressure curves. Based on rock particle size data, various machine learning methods, such as traditional machine learning and artificial neural networks, are used to build prediction models and predict different types of capillary pressure curves, aiming at studying the best prediction algorithm. In addition, through adjusting the amount of particle size characteristic data, the best amount of particle size characteristic data is explored. The results show that three correlation coefficients of the four optimal algorithms can reach more than 0.92, and the best performance is obtained using the Levenberg–Marquardt method. The prediction performance of this algorithm is excellent, with the three correlation coefficients being all higher than 0.96 and the root mean square error being only 5.866. When partial particle size characteristics are selected, the training performance is gradually improved with an increase in the amount of feature data, but it is far less than the performance of using all the features. When the interpolation increases the particle size characteristics, the best performance is achieved when the feature data volume is 50 groups and the root mean square error is the smallest, but the Kendall correlation coefficient decreases. This study provides a new way to obtain capillary pressure data accurately. Full article
(This article belongs to the Special Issue Rock Physics, Well Logging, and Formation Evaluation in Energy Exploration Systems)
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18 pages, 3810 KiB  
Article
Continuous Biological Ex Situ Methanation of CO2 and H2 in a Novel Inverse Membrane Reactor (IMR)
by Fabian Haitz, Oliver Jochum, Agnieszka Lasota, André Friedrich, Markus Bieri, Marc Stalder, Martin Schaub, Ulrich Hochberg and Christiane Zell
Processes 2024, 12(10), 2305; https://doi.org/10.3390/pr12102305 - 21 Oct 2024
Viewed by 1127
Abstract
A promising approach for carbon dioxide (CO2) valorization and storing excess electricity is the biological methanation of hydrogen and carbon dioxide to methane. The primary challenge here is to supply sufficient quantities of dissolved hydrogen. The newly developed Inverse Membrane Reactor [...] Read more.
A promising approach for carbon dioxide (CO2) valorization and storing excess electricity is the biological methanation of hydrogen and carbon dioxide to methane. The primary challenge here is to supply sufficient quantities of dissolved hydrogen. The newly developed Inverse Membrane Reactor (IMR) allows for the spatial separation of the required reactant gases, hydrogen (H2) and carbon dioxide (CO2), and the degassing area for methane (CH4) output through commercially available ultrafiltration membranes, enabling a reactor design as a closed circuit for continuous methane production. In addition, the Inverse Membrane Reactor (IMR) facilitates the utilization of hydraulic pressure to enhance hydrogen (H2) input. One of the process’s advantages is the potential to utilize both carbon dioxide (CO2) from conventional biogas and CO2-rich industrial waste gas streams. An outstanding result from investigating the IMR revealed that, employing the membrane gassing concept, methane concentrations of over 90 vol.% could be consistently achieved through flexible gas input over a one-year test series. Following startup, only three supplemental nutrient additions were required in addition to hydrogen (H2) and carbon dioxide (CO2), which served as energy and carbon sources, respectively. The maximum achieved methane formation rate specific to membrane area was 87.7 LN of methane per m2 of membrane area per day at a product gas composition of 94 vol.% methane, 2 vol.% H2, and 4 vol.% CO2. Full article
(This article belongs to the Special Issue Innovations in Gaseous, Liquid and Solid Products during Biogas Generation and Utilization)
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18 pages, 4013 KiB  
Article
Development of Fruit-Based Carbohydrate Gel for Endurance Athletes
by Renata Assis, Ashley Valentim, Isabele Barbosa, Julyana Silva, Andrea Aquino, José Viana, Claisa Rabelo, Paulo Sousa, Carla Maia, Victor Fernandes, Ícaro Vieira and Carlucio Alves
Processes 2024, 12(10), 2304; https://doi.org/10.3390/pr12102304 - 21 Oct 2024
Viewed by 809
Abstract
The aim of this study was to produce a carbohydrate gel based on genipap and banana and analyze its physico-chemical, rheological, and sensory quality, as well as its proximate composition and antioxidant activity. Three gel samples were formulated containing different concentrations of genipap [...] Read more.
The aim of this study was to produce a carbohydrate gel based on genipap and banana and analyze its physico-chemical, rheological, and sensory quality, as well as its proximate composition and antioxidant activity. Three gel samples were formulated containing different concentrations of genipap and clarified banana juice. The formulated samples followed the minimum parameters required and were subjected to analyses of their pH, soluble solids, titratable acidity, moisture, ash, lipids, proteins, glucose, fructose, sucrose, polyphenols, antioxidant activity, and rheology. Commercial carbohydrate gel was used as a control sample. It can be concluded that the gel formulations were formulated following the minimum parameters required, with a moderate sensory acceptance. The physico-chemical parameters and proximate composition the developed gels were similar to the commercial gel, while their glucose, sucrose, fructose, polyphenol, and antioxidant activity contents were higher and their rheological properties were within the expected range for this category of commonly marketed products. In the two blocks of analysis mentioned above, data variability was mostly explained by PC1–PC3 at almost 100%. Rheologically, the commercial gel is considered to be a Newtonian fluid, and the developed formulations can be considered as pseudoplastic fluids due to the insoluble solids still present. Full article
(This article belongs to the Special Issue Advances in Rheology, Biodegradability and Mechanical Properties of Polymers)
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16 pages, 4467 KiB  
Article
Mechanism Analysis of Low-Frequency Oscillation Caused by VSG from the Perspective of Vector Motion
by Hongqiang Zhang, Yunpeng Zhou, Wei He, Jiabing Hu, Wei Huang, Wenyun Li and Suwei Zhai
Processes 2024, 12(10), 2303; https://doi.org/10.3390/pr12102303 - 21 Oct 2024
Viewed by 586
Abstract
Virtual synchronous generators (VSGs) have attracted widespread attention due to their advantage in supporting voltage and frequency of power systems. However, relevant studies have shown that a VSG has similar low-frequency oscillation as synchronous generators, which is more likely to occur under strong [...] Read more.
Virtual synchronous generators (VSGs) have attracted widespread attention due to their advantage in supporting voltage and frequency of power systems. However, relevant studies have shown that a VSG has similar low-frequency oscillation as synchronous generators, which is more likely to occur under strong grid conditions. In this paper, the linearized mathematical model of a VSG is established by using small-signal analysis; based on this, the physical process of low-frequency oscillation of a VSG is explained from the perspective of vector motion. Firstly, the amplitude and phase motion of the current vector of a VSG under small disturbance are analyzed, then the mechanism of negative damping caused by terminal voltage control is revealed, and the reason why a VSG is more prone to instability under strong grid conditions is explained. Based on these, the influence of control and grid strength on the low-frequency oscillation of a VSG is analyzed. Studies show that the amplitude motion of the output current is the main cause of negative damping, and the oscillation can be suppressed by optimizing the value of key parameters. Full article
(This article belongs to the Special Issue Operation and Control of New Power System with Large-Scale Renewable Energy Integration)
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26 pages, 5210 KiB  
Article
Use of Deep-Learning-Accelerated Gradient Approximation for Reservoir Geological Parameter Estimation
by Cong Xiao, Ting Liu, Lufeng Zhang and Zhun Li
Processes 2024, 12(10), 2302; https://doi.org/10.3390/pr12102302 - 21 Oct 2024
Viewed by 658
Abstract
The estimation of space-varying geological parameters is often not computationally affordable for high-dimensional subsurface reservoir modeling systems. The adjoint method is generally regarded as an efficient approach for obtaining analytical gradient and, thus, proceeding with the gradient-based iteration algorithm; however, the infeasible memory [...] Read more.
The estimation of space-varying geological parameters is often not computationally affordable for high-dimensional subsurface reservoir modeling systems. The adjoint method is generally regarded as an efficient approach for obtaining analytical gradient and, thus, proceeding with the gradient-based iteration algorithm; however, the infeasible memory requirement and computational demands strictly prohibit its generic implementation, especially for high-dimensional problems. The autoregressive neural network (aNN) model, as a nonlinear surrogate approximation, has gradually received increasing popularity due to significant reduction of computational cost, but one prominent limitation is that the generic application of aNN to large-scale reservoir models inevitably poses challenges in the training procedure, which remains unresolved. To address this issue, model-order reduction could be a promising strategy, which enables us to train the neural network in a very efficient manner. A very popular projection-based linear reduction method, i.e., propel orthogonal decomposition (POD), is adopted to achieve dimensionality reduction. This paper presents an architecture of a projection-based autoregressive neural network that efficiently derives an easy-to-use adjoint model by the use of an auto-differentiation module inside the popular deep learning frameworks. This hybrid neural network proxy, referred to as POD-aNN, is capable of speeding up derivation of reduced-order adjoint models. The performance of POD-aNN is validated through a synthetic 2D subsurface transport model. The use of POD-aNN significantly reduces the computation cost while the accuracy remains. In addition, our proposed POD-aNN can easily obtain multiple posterior realizations for uncertainty evaluation. The developed POD-aNN emulator is a data-driven approach for reduced-order modeling of nonlinear dynamic systems and, thus, should be a very efficient modeling tool to address many engineering applications related to intensive simulation-based optimization. Full article
(This article belongs to the Section Energy Systems)
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17 pages, 15627 KiB  
Article
Enhanced Carbon/Oxygen Ratio Logging Interpretation Methods and Applications in Offshore Oilfields
by Wei Zhou, Yaoting Lin, Gang Gao and Peng Wang
Processes 2024, 12(10), 2301; https://doi.org/10.3390/pr12102301 - 21 Oct 2024
Viewed by 561
Abstract
As the development of most domestic and international oilfields progresses, many fields have entered a mature phase characterized by high water cut and high recovery, with water cut levels often exceeding 90%. Carbon/oxygen ratio logging has proven to be an indispensable tool for [...] Read more.
As the development of most domestic and international oilfields progresses, many fields have entered a mature phase characterized by high water cut and high recovery, with water cut levels often exceeding 90%. Carbon/oxygen ratio logging has proven to be an indispensable tool for distinguishing oil layers from water layers in complex environments, especially where salinity is low, unknown, or highly variable. This logging method has become one of the most effective techniques for determining residual oil saturation in cased wells, providing critical insights into the oil–water interface. In this study, we evaluate two key interpretation models for carbon/oxygen ratio logging: the fan chart method and the ratio chart method. We optimize the interpretation parameters in the ratio chart model using an improved genetic algorithm, which significantly enhances interpretation precision. The optimized parameters enable a more seamless integration of logging results with reservoir and conventional logging data, reducing the influence of lithological variations and physical property differences on the measurements. This research establishes a robust theoretical foundation for enhancing the interpretation accuracy of carbon/oxygen ratio logging, which is crucial for effectively identifying water-flooded layers. These advancements provide vital technical support for monitoring oil–water dynamics, optimizing reservoir management, and improving production efficiency in oilfield development. Full article
(This article belongs to the Section Energy Systems)
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23 pages, 3344 KiB  
Article
Comparative Analysis of Human and Artificial Intelligence Planning in Production Processes
by Matjaž Roblek, Tomaž Kern, Eva Krhač Andrašec and Alenka Brezavšček
Processes 2024, 12(10), 2300; https://doi.org/10.3390/pr12102300 - 21 Oct 2024
Viewed by 794
Abstract
Artificial intelligence (AI) has found applications in enterprises′ production planning processes. However, a critical question remains: could AI replace human planners? We conducted a comparative analysis to evaluate the main task of planners in an intermittent process: planning the duration of production orders. [...] Read more.
Artificial intelligence (AI) has found applications in enterprises′ production planning processes. However, a critical question remains: could AI replace human planners? We conducted a comparative analysis to evaluate the main task of planners in an intermittent process: planning the duration of production orders. Specifically, we analysed the results of a human planner using master data and those of an AI algorithm compared to the actual realisation. The case study was conducted in a large production company using a sample of production products and machines. We were able to confirm two of the three research questions (RQ1 and RQ3), while the results of the third question (RQ2) did not meet our expectations. The AI algorithms demonstrated significant improvement with each iteration. Despite this progress, it is still difficult to determine the exact threshold at which AI outperforms human planners due to the unpredictability of unexpected events. Even though AI significantly improves prediction accuracy, the inherent variability and incomplete input data pose a major challenge. As progress is made, robust data collection and management strategies need to be integrated to bridge the gap between the potential of AI and its practical application, fostering the symbiosis between human expertise and AI capabilities in production planning. Full article
(This article belongs to the Special Issue Dynamics Analysis and Intelligent Control in Industrial Engineering)
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17 pages, 12242 KiB  
Article
Efficient Optimization: Unveiling the Application of Ensemble Learning Combined with the CMA-ES Algorithm in Hydraulic Fracturing Design
by Jianmin Fu, Xiaofei Sun, Zhengchao Ma, Jiansheng Yu, Qilong Zhang, Bo Hao, Qiang Wang, Hao Hu and Tianyu Wang
Processes 2024, 12(10), 2299; https://doi.org/10.3390/pr12102299 - 21 Oct 2024
Viewed by 762
Abstract
Optimizing fracturing parameters is crucial for enhancing production and reducing costs in oil and gas exploration and development. Effectively integrating geological and engineering parameters for the automated optimization of fracturing design continues to pose challenges. This study utilizes the cluster-based local outlier factor [...] Read more.
Optimizing fracturing parameters is crucial for enhancing production and reducing costs in oil and gas exploration and development. Effectively integrating geological and engineering parameters for the automated optimization of fracturing design continues to pose challenges. This study utilizes the cluster-based local outlier factor method for anomaly detection and removal from the dataset, significantly enhancing data quality. By integrating diverse models, including tree-based models and neural networks, an ensemble model for production prediction was developed. This approach successfully addresses the limitations of relying on a single model and achieves high-precision production forecasting. Furthermore, a Covariance Matrix Adaptation Evolution Strategy (CMA-ES)-based framework was established to comprehensively optimize the design parameters of fracturing projects. Optimization practices for two selected wells resulted in a 168.54% increase in production and identified the optimal design parameter configuration for all cases studied. The results of this study demonstrate the feasibility and effectiveness of the proposed ensemble prediction model and optimization framework in practical applications. Data-driven optimization strategies are expected to play a larger role in future oil and gas development, driving technological innovation and advancement in the field. Full article
(This article belongs to the Section Energy Systems)
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19 pages, 4339 KiB  
Article
Conceptual Design and Economic Optimization of Different Valorization Routes for Orange Peel Waste: The Application of the Biorefinery Concept for an Integral Use of Raw Material
by Sergio Arango-Manrique, Tatiana Agudelo Patiño, Luis Gerónimo Matallana Pérez, Mariana Ortiz-Sanchez and Carlos Ariel Cardona Alzate
Processes 2024, 12(10), 2298; https://doi.org/10.3390/pr12102298 - 21 Oct 2024
Viewed by 1006
Abstract
Biorefineries are novel biotechnological routes designed to generate sustainable processes from renewable raw materials. The valorization of orange peel waste (OPW) provides high-value products based on their composition. The economic optimization of biorefineries through conceptual design and generation of superstructures based on the [...] Read more.
Biorefineries are novel biotechnological routes designed to generate sustainable processes from renewable raw materials. The valorization of orange peel waste (OPW) provides high-value products based on their composition. The economic optimization of biorefineries through conceptual design and generation of superstructures based on the analysis of processing units is a topic of great interest. This work aimed to obtain the most profitable biorefinery through economic optimization strategies based on high-value-added products from OPW. Two stages were considered: The first stage consisted of the conceptual design of multiple OPW processing units (production of essential oil, mucic acid, phenolic compounds, biogas, among others). An OPW flow rate of 140 kg/h was selected as the base case. From the stand-alone units, a biorefinery superstructure (second stage) was designed. Finally, the units with the best mass and energy results were selected in order to maximize the net present value (NPV) and obtain an optimal biorefinery configuration. The results evidenced that the production of essential oil and biogas presented the best yields (2.61 mL and 0.028 m3 per kg OPW, respectively). This biorefinery configuration obtained an NPV of −7.7 mUSD from the base case. Through the evaluation of the different superstructure configurations, the combined production of essential oil, biogas, and mucic acid and a scale-up of over 22 times the base case generated the minimum processing scale. Under a Colombian context, the implementation of the biorefineries analyzed are promising since the minimum processing scale contemplated only 8.8% of the OPW production. Efforts to increase yields and decrease capital and operating expenses while keeping environmental impacts low should be pursued. Full article
(This article belongs to the Special Issue Design of Food Processing and Technologies: Studies on Physical Properties, Thermodynamics, Rheology and Emulsification)
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17 pages, 820 KiB  
Article
Phenolic Class Analysis in Honey: Comparison of Classical and Single UV Spectrum Methodologies
by Vanessa B. Paula, Miguel L. Sousa-Dias, Natália L. Seixas, Patricia Combarros-Fuertes, Letícia M. Estevinho and Luís G. Dias
Processes 2024, 12(10), 2297; https://doi.org/10.3390/pr12102297 - 20 Oct 2024
Viewed by 815
Abstract
The analytical results from a study of 16 honey samples (extra white to dark honey color range) of phenolic compounds obtained using the single UV spectrum methodology and classical spectrophotometric methods (Folin–Ciocalteu and AlCl3 methods) are presented. The first method quantified all [...] Read more.
The analytical results from a study of 16 honey samples (extra white to dark honey color range) of phenolic compounds obtained using the single UV spectrum methodology and classical spectrophotometric methods (Folin–Ciocalteu and AlCl3 methods) are presented. The first method quantified all classes of phenolic compounds in honey’s SPE-C18 extract: the total hydroxybenzoic acid content (concentrations between 0.37 ± 0.05 and 4.46 ± 0.37 mg of gallic acid/g of honey), total hydroxycinnamic acid content (0.13 ± 0.03 and 2.76 ± 0.13 mg of ferulic acid/g of honey), and total flavonoid content (0.15 ± 0.03 and 1.63 ± 0.17 mg of quercetin/g of honey). The total phenolic contents were, on average, 1.86 ± 0.72 and 1.78 ± 0.79 times higher than the results obtained for raw honey and the SPE-C18 extract, respectively, using the classical Folin–Ciocalteu method. The total flavonoid contents, on average, were 6.02 ± 3.14 times larger and 0.66 ± 0.33 times smaller than the results obtained using the classical AlCl3 method for raw honey and SPE-C18 extract, respectively. Full article
(This article belongs to the Special Issue Phenolic Profiling and Antioxidant Capacity in Agrifood Products (Volume II))
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17 pages, 6804 KiB  
Article
Prediction of Heat Transfer in a Hybrid Solar–Thermal–Photovoltaic Heat Exchanger Using Computational Fluid Dynamics
by Sandro Guadalupe Pérez Grajales, Teresa Hernández Ortíz, Rogelio Martinez-Oropeza, Tabai Torres, López-Pérez Luis Adrián, Javier Delgado-Gonzaga, Armando Huicochea and David Juárez-Romero
Processes 2024, 12(10), 2296; https://doi.org/10.3390/pr12102296 - 20 Oct 2024
Viewed by 866
Abstract
Solar energy is one of the main renewable energy resources due to its abundance. It can be used for two purposes, thermal or photovoltaic applications. However, when the resource obtained is mixed, it is called photovoltaic thermal hybrid, where the solar panels generate [...] Read more.
Solar energy is one of the main renewable energy resources due to its abundance. It can be used for two purposes, thermal or photovoltaic applications. However, when the resource obtained is mixed, it is called photovoltaic thermal hybrid, where the solar panels generate electricity and are provided with a heat exchanger to absorb energy through a water flow. This is one of the techniques used by the scientific community to reduce the excess temperature generated by solar radiation in the cells, improving the electrical efficiency of photovoltaic systems and obtaining fluid with higher temperature. In this work, the thermal behavior of a heat exchanger equipped with fins in its interior to increase the thermal efficiency of the system was analyzed using CFD (Computational Fluid Dynamics). The results showed that the average fluid outlet temperature was 75.31 °C, considering an incident irradiance of 1067 W/m2 and a fluid inlet temperature of 27 °C. The operating conditions were obtained from published experimental studies, achieving 97.7% similarity between the two. This was due to the boundary conditions of the heat flux (1067 W/m2) impinging directly on the coupled cells and the heat exchanger in a working area of 0.22 m2. Full article
(This article belongs to the Special Issue Solar Technologies and Photovoltaic Systems)
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15 pages, 1437 KiB  
Article
Ultrasonic-Assisted Extraction and Antioxidant Evaluation of Resveratrol from Peanut Sprouts
by Xianmeng Xu, Dandan Zhang, Xiaohua Liu, Rong Zheng and Tingqi Jiang
Processes 2024, 12(10), 2295; https://doi.org/10.3390/pr12102295 - 19 Oct 2024
Viewed by 1013
Abstract
The orthogonal array design method was used to optimize ultrasonic-assisted extraction of resveratrol from peanut sprouts. The results showed that the highest extraction yield of resveratrol using ultrasonic-assisted extraction could be up to 1.1%. The optimal extraction conditions were liquid to solid ratio [...] Read more.
The orthogonal array design method was used to optimize ultrasonic-assisted extraction of resveratrol from peanut sprouts. The results showed that the highest extraction yield of resveratrol using ultrasonic-assisted extraction could be up to 1.1%. The optimal extraction conditions were liquid to solid ratio of 30:1 (mL/g) and ethanol concentration of 80% (v/v) as solvent for 40 min at the temperature of 70 °C. AB-8 macroporous adsorption resin was used to purify the crude extract and the resveratrol content increased to 47.5% after one treatment run. The optimal adsorption parameters were initial concentrations in the sample solution of 2 mg/mL, a pH of 5.0, a flow rate of 2 mL/min, and a temperature of 25 °C. The optimal desorption parameters were 60% ethanol and a flow rate of 1 mL/min. The chemical composition of the peanut sprout’s resveratrol sample was investigated via HPLC, and the predominant constituents were found to be protocatechuic acid, catechins, caffeic acid, epicatechuic acid, resveratrol, and rutin. The antioxidant activities of the resveratrol were measured via the following different analytical methods: reducing power, 2,2-diphenyl-1-picrylhdrazyl (DPPH), hydroxyl radical-scavenger activity, superoxide radical-scavenger activity, the β-carotene bleaching test, and the scavenging nitrite test. The results indicated that the resveratrol in peanut sprouts have significant antioxidant activities and can be used as a source of potential antioxidant. And peanut sprout’s resveratrol has the potential and valuable application to be used as a new type of resveratrol resource. The finding of this study can provide some theoretical reference for the comprehensive utilization of peanut resources in the development of antioxidant health foods. Full article
(This article belongs to the Special Issue Production Planning, Modeling and Control of Food Industry Processes)
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19 pages, 7007 KiB  
Article
Numerical Study of the Combustion Process in the Vertical Heating Flue of Air Staging Coke Oven
by Xiaolei Hu, Jiale Zhang, Zihan Yu, Zhenzhen Liu, Jiayi Guo and Changhua Xu
Processes 2024, 12(10), 2294; https://doi.org/10.3390/pr12102294 - 19 Oct 2024
Viewed by 692
Abstract
To investigate the combustion process and reduce Nitric Oxide (NO) emissions in the vertical heating flue of air-staged coke ovens, a three-dimensional computational fluid dynamics method was applied to simulate the combustion process. The model integrates the k-ε turbulence model with a multi-component [...] Read more.
To investigate the combustion process and reduce Nitric Oxide (NO) emissions in the vertical heating flue of air-staged coke ovens, a three-dimensional computational fluid dynamics method was applied to simulate the combustion process. The model integrates the k-ε turbulence model with a multi-component transport combustion model. The impact of air staging on the flow field and NO emissions in the vertical fire chamber was assessed through comparative validation with experimental data. The impact of air staging on the flow field and NO emissions in the vertical fire chamber was assessed through comparative validation with experimental data. Based on this research, the effects of the excess air coefficient and air inlet distribution ratio on NO emission levels at the flue gas outlet were further investigated. Analysis of the flow field structure, temperature at the center cross-section, component concentration, and NO emission levels indicates that as the excess air coefficient increases, the NO emission levels at the flue gas outlet initially decrease and then increase, accompanied by corresponding changes in outlet temperature. At an air excess factor of 1.3 and an air inlet distribution ratio of 7:3, NO emission levels are at their lowest—53% lower than those in a conventional coke oven—and the temperature distribution in the riser channel is more uniform. These results provide a theoretical foundation for designing the air-staged coke oven standing fire channel structure. Full article
(This article belongs to the Section Chemical Processes and Systems)
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27 pages, 3503 KiB  
Article
Thermodynamic Model-Based Synthesis of Heat-Integrated Work Exchanger Networks
by Aida Amini-Rankouhi, Abdurrafay Siddiqui and Yinlun Huang
Processes 2024, 12(10), 2293; https://doi.org/10.3390/pr12102293 - 19 Oct 2024
Viewed by 744
Abstract
Heat integration has been widely and successfully practiced for recovering thermal energy in process plants for decades. It is usually implemented through synthesizing heat exchanger networks (HENs). It is recognized that mechanical energy, another form of energy that involves pressure-driven transport of compressible [...] Read more.
Heat integration has been widely and successfully practiced for recovering thermal energy in process plants for decades. It is usually implemented through synthesizing heat exchanger networks (HENs). It is recognized that mechanical energy, another form of energy that involves pressure-driven transport of compressible fluids, can be recovered through synthesizing work exchanger networks (WENs). One type of WEN employs piston-type work exchangers, which demonstrates techno-economic attractiveness. A thermodynamic-model-based energy recovery targeting method was developed to predict the maximum amount of mechanical energy feasibly recoverable by piston-type work exchangers prior to WEN configuration generation. In this work, a heat-integrated WEN synthesis methodology embedded by the thermodynamic model is introduced, by which the maximum mechanical energy, together with thermal energy, can be cost-effectively recovered. The methodology is systematic and general, and its efficacy is demonstrated through two case studies that highlight how the proposed methodology leads to designs simpler than those reported by other researchers while also having a lower total annualized cost (TAC). Full article
(This article belongs to the Special Issue Industrial IoT-Enabled Modeling and Optimization for the Process Industry)
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16 pages, 2729 KiB  
Review
Research and Application Progress of Crude Oil Demulsification Technology
by Longhao Tang, Tingyi Wang, Yingbiao Xu, Xinyi He, Aobo Yan, Zhongchi Zhang, Yongfei Li and Gang Chen
Processes 2024, 12(10), 2292; https://doi.org/10.3390/pr12102292 - 19 Oct 2024
Viewed by 1116
Abstract
The extraction and collection of crude oil will result in the formation of numerous complex emulsions, which will not only decrease crude oil production, raise the cost of extraction and storage, and worsen pipeline equipment loss, but also seriously pollute the environment because [...] Read more.
The extraction and collection of crude oil will result in the formation of numerous complex emulsions, which will not only decrease crude oil production, raise the cost of extraction and storage, and worsen pipeline equipment loss, but also seriously pollute the environment because the oil in the emulsion can fill soil pores, lower the soil’s permeability to air and water, and create an oil film on the water’s surface to prevent air–water contact. At present, a variety of demulsification technologies have been developed, such as physical, chemical, biological and other new emulsion breaking techniques, but due to the large content of colloid and asphaltene in many crude oils, resulting in the increased stability of their emulsions and oil–water interfacial tension, interfacial film, interfacial charge, crude oil viscosity, dispersion, and natural surfactants have an impact on the stability of crude oil emulsions. Therefore, the development of efficient, widely applicable, and environmentally friendly demulsification technologies for crude oil emulsions remains an important research direction in the field of crude oil development and application. This paper will start from the formation, classification and hazards of crude oil emulsion, and comprehensively summarize the development and application of demulsification technologies of crude oil emulsion. The demulsification mechanism of crude oil emulsion is further analyzed, and the problems of crude oil demulsification are pointed out, so as to provide a theoretical basis and technical support for the development and application of crude oil demulsification technology in the future. Full article
(This article belongs to the Section Energy Systems)
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16 pages, 1023 KiB  
Article
The Role of Fermentation and Drying on the Changes in Bioactive Properties, Seconder Metabolites, Fatty Acids and Sensory Properties of Green Jalapeño Peppers
by Isam A. Mohamed Ahmed, Fahad AlJuhaimi, Mehmet Musa Özcan, Nurhan Uslu and Noman Walayat
Processes 2024, 12(10), 2291; https://doi.org/10.3390/pr12102291 - 19 Oct 2024
Viewed by 582
Abstract
In this study, the influence of fermentation and different drying techniques on the bioactive components, antioxidant activity, phenolic components, fatty acids, nutrients and sensory characteristics of fresh and processed jalapeño peppers was investigated. At the end of the fermentation, the pH, acidity and [...] Read more.
In this study, the influence of fermentation and different drying techniques on the bioactive components, antioxidant activity, phenolic components, fatty acids, nutrients and sensory characteristics of fresh and processed jalapeño peppers was investigated. At the end of the fermentation, the pH, acidity and salt values of the brine were determined as 3.38, 0.09% and 6.02 g/100 mL, respectively. The oil results of pepper samples were found between 2.0% (microwave and air) and 2.60% (oven). Total carotenoid and total phenolic amounts of fresh (control) and processed peppers (air, conventional, microwave and fermentation) were characterized to be between 3.38 (fermented) and 65.68 µg/g (air) to 45.81 (fermented) and 350.69 mg GAE/100 g (microwave), respectively. Total flavonoid quantities of fresh and processed pepper samples were defined to be between 14.17 (fresh) and 482.74 mg/100 g (microwave). 3,4-dihydroxybenzoic acid and catechin amounts in fresh and processed jalapeño peppers were defined to be between 0.43 (fermented) and 11.0 mg/100 g (microwave) to 1.36 (fermented) and 44.87 mg/100 g (microwave), respectively. The predominant fatty acids of pepper oils were palmitic, oleic and linoleic acid. The oleic acid amounts of fresh and processed jalapeño pepper oils were specified to be between 9.52% (air drying) and 29.77% (fermented), while the linoleic acid values of pepper oils vary between 10.84% (fermented) and 68.38% (air drying). The major elements of fresh and processed peppers were K, P, S, Ca, Mg, Fe and Zn in decreasing order. Protein amounts in fresh and processed jalapeño peppers were characterized to be between 8.59 (fermented) and 12.22% (oven). As a result of panelist evaluations, the most appreciated features (4.83 score) were the flavor, color and texture feature. Full article
(This article belongs to the Special Issue Synthesis and Extraction Processes of Biotechnological Drugs of Plant Origin)
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15 pages, 4237 KiB  
Article
Maleic Anhydride-Modified Water Hyacinth for Adsorption of Methylene Blue and Methyl Violet
by Liya Shen, Jing Xu, Xinru Wang and Yuanli Liu
Processes 2024, 12(10), 2290; https://doi.org/10.3390/pr12102290 - 19 Oct 2024
Viewed by 852
Abstract
Removal of toxic pollutants is of the greatest concerns facing wastewater treatment. In this study, a chemical modification method was used to prepare the maleic anhydride-modified water hyacinth (MA-EC) for the removal of methylene blue (MB) and methyl violet (MV) from water. The [...] Read more.
Removal of toxic pollutants is of the greatest concerns facing wastewater treatment. In this study, a chemical modification method was used to prepare the maleic anhydride-modified water hyacinth (MA-EC) for the removal of methylene blue (MB) and methyl violet (MV) from water. The maleic anhydride-modified water hyacinth biosorbent was characterized and adsorption experiments were conducted. The prepared MA-EC demonstrated considerable adsorptive efficiency toward MV and MB. It was confirmed that the maximum adsorptive capacities were 1373.58 and 434.70 mg/g for MV and MB, respectively. The adsorptive data were also fitted using Langmuir and Freundlich isotherms, and the results showed that the Langmuir isotherm adsorption model could better describe the adsorptive process. Adsorption–desorption cycling experiments demonstrated that the MA-EC adsorbent had good reusability, with adsorptive capacities of 538.88 mg/g for MV and 215.56 mg/g for MB after four cycles of desorption–adsorption. Full article
(This article belongs to the Special Issue Energy and Water Treatment Processes)
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16 pages, 811 KiB  
Article
Use of Mucilage from Opuntia ficus-indica in the Manufacture of Probiotic Cream Cheese
by Pamela Dutra Rodrigues, Isabela de Andrade Arruda Fernandes, Annecler Rech de Marins, Andresa Carla Feihrmann and Raquel Guttierres Gomes
Processes 2024, 12(10), 2289; https://doi.org/10.3390/pr12102289 - 18 Oct 2024
Viewed by 1183
Abstract
Cream cheese is a type of fresh cheese with a thin consistency with great potential for adding probiotics. However, artificial thickeners have been used in its production, decreasing consumer satisfaction. This study suggests natural mucilage, specifically from the Cactaceae Opuntia ficus-indica, as [...] Read more.
Cream cheese is a type of fresh cheese with a thin consistency with great potential for adding probiotics. However, artificial thickeners have been used in its production, decreasing consumer satisfaction. This study suggests natural mucilage, specifically from the Cactaceae Opuntia ficus-indica, as a replacement for artificial thickeners due to its thick gelatinous properties. This study evaluated different cream cheese formulations by adding varying concentrations of Opuntia ficus-indica mucilage and the probiotic Lactobacillus acidophilus (L. acidophilus). Four formulations were created: formulation C (control, without mucilage), F1 (containing 1 mL/kg mucilage), F2 (2 mL/kg), and F3 (3 mL/kg mucilage). The physicochemical characteristics (pH, 4.90–5.57; 0.15–0.20% acidity; 1.78–2.42% protein; 29.98–30.88% fat; 38.27–41.63% moisture; and 1.25–1.63% ash) and microbiological analysis met the quality standards required by Brazilian legislation, and the cream cheese showed probiotic potential, with L. acidophilus counts above 108 CFU/mL within four weeks of storage. Regarding sensory evaluation, the texture received one of the highest scores (7.89), followed by aroma (7.11). Therefore, the Cactaceae mucilage has proven to be a viable alternative to replace artificial thickeners in cream cheese, making it an excellent option for probiotic supplementation. Full article
(This article belongs to the Section Food Process Engineering)
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22 pages, 6645 KiB  
Article
Comparative Analysis of Boron-Al Metal Matix Composite and Aluminum Alloy in Enhancing Dynamic Performance of Vertical-Axis Wind Turbine
by Abhishek Agarwal and Linda Mthembu
Processes 2024, 12(10), 2288; https://doi.org/10.3390/pr12102288 - 18 Oct 2024
Cited by 1 | Viewed by 870
Abstract
This study aims to assess the dynamic performance of the vertical-axis wind turbine (VAWT) with the help of conventional aluminum (Al) and the boron Al metal matrix composite (MMC). The simulations were conducted using ANSYS software and involved natural frequencies, mode shapes, a [...] Read more.
This study aims to assess the dynamic performance of the vertical-axis wind turbine (VAWT) with the help of conventional aluminum (Al) and the boron Al metal matrix composite (MMC). The simulations were conducted using ANSYS software and involved natural frequencies, mode shapes, a mass participation factor, and Campbell plots. The results of static structural analysis show that the boron Al MMC is vastly superior to the aluminum alloy because there is a 65% reduction of equivalent stress with a 70% reduction of deformation compared to the aluminum alloy. These results show that boron Al MMC can withstand higher loads with lesser stress; the structure remains compact and rigid in its working conditions. From the findings, it can be ascertained that employing boron Al MMC improves VAWT power, efficiency, and robustness. However, the critical speed that was established in the dynamic analysis of boron Al MMC requires extraordinary control and the use of dampening systems, thereby avoiding resonance. Overall, boron Al MMC contributes to significant enhancements in the VAWTs’ mechanical and operational characteristics; however, the material’s complete potential can be achieved only with proper maintenance and employing the correct damping techniques. Information about these two materials will allow for a better understanding of their comparative efficacy and their potential application in the further development of VAWTs. Full article
(This article belongs to the Special Issue Processing, Manufacturing and Properties of Metal and Alloys)
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25 pages, 6350 KiB  
Article
Optimization and Efficiency of Novel Magnetic-Resin-Based Approaches for Enhanced Nickel Removal from Water
by Marija Maletin, Jasmina Nikić, Vesna Gvoić, Jovana Pešić, Željka Cvejić, Aleksandra Tubić and Jasmina Agbaba
Processes 2024, 12(10), 2287; https://doi.org/10.3390/pr12102287 - 18 Oct 2024
Viewed by 639
Abstract
Nickel contamination in water is a critical issue due to its toxicity and persistence. This study presents a novel magnetic resin, developed by modifying Lewatit® MonoPlus TP 207 with magnetite nanoparticles, to enhance adsorption capacity and facilitate efficient separation. A Definitive Screening [...] Read more.
Nickel contamination in water is a critical issue due to its toxicity and persistence. This study presents a novel magnetic resin, developed by modifying Lewatit® MonoPlus TP 207 with magnetite nanoparticles, to enhance adsorption capacity and facilitate efficient separation. A Definitive Screening Design (DSD) was employed to identify and optimize key parameters affecting nickel adsorption, including pH, resin dosage, initial nickel concentration, and the presence of competing ions (calcium and magnesium). The DSD analysis revealed that pH and magnesium concentration were the most significant factors influencing nickel removal. Optimal conditions were determined as pH 7, 270 min contact time, resin dosage of 0.5 mL/L, initial nickel concentration of 110 µg/L, calcium concentration of 275 mg/L, and magnesium concentration of 52.5 mg/L, achieving a maximum removal efficiency of 99.21%. The magnetic resin exhibited enhanced adsorption capacity and faster kinetics compared to the unmodified resin, leading to more efficient nickel removal. Moreover, its magnetic properties facilitated rapid separation from treated water, offering practical advantages for real-world applications. This study demonstrates the effective use of DSD in optimizing adsorption parameters and underscores the potential of magnetic resin as a sustainable and efficient adsorbent for water treatment. Full article
(This article belongs to the Special Issue Innovation of Heavy Metal Adsorption Process)
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7 pages, 1616 KiB  
Article
Determination of Hafnium in Zirconium by Spectrophotometry
by Xiuhao Jiao, Xiaotao Lv, Shaolong Li, Zepeng Lv and Jianxun Song
Processes 2024, 12(10), 2286; https://doi.org/10.3390/pr12102286 - 18 Oct 2024
Viewed by 526
Abstract
Zirconium and hafnium have opposite nuclear properties and are used very differently in the nuclear industry. However, hafnium is a common metal impurity in zirconium, and the chemical properties of the two are very similar except for nuclear properties, and it is difficult [...] Read more.
Zirconium and hafnium have opposite nuclear properties and are used very differently in the nuclear industry. However, hafnium is a common metal impurity in zirconium, and the chemical properties of the two are very similar except for nuclear properties, and it is difficult to separate and detect them. At present, the detection of hafnium content in zirconium is usually achieved by using an inductively coupled plasma (ICP) spectrometer, but ICP equipment is expensive, and the detection cost is high. Therefore, it is necessary to develop a simple and low-cost method for the determination of hafnium content in zirconium. Based on this, this paper takes the spectrophotometric method as a starting point. Through a series of experiments on the influence of pH and concentrations of the color-developing agent xylenol orange sodium salt on the absorbance of zirconium and hafnium ions, the appropriate variables are selected to detect the content of hafnium in zirconium. Finally, according to the measured absorbance and total ion concentration, by comparing the working curve of zirconium and hafnium ions, the content of hafnium in zirconium is calculated based on the lever principle. Full article
(This article belongs to the Section Chemical Processes and Systems)
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13 pages, 2051 KiB  
Article
Artificial Neural Networks for Mineral Production Forecasting in the In Situ Leaching Process: Uranium Case Study
by Daniar Aizhulov, Madina Tungatarova, Maksat Kurmanseiit and Nurlan Shayakhmetov
Processes 2024, 12(10), 2285; https://doi.org/10.3390/pr12102285 - 18 Oct 2024
Viewed by 676
Abstract
This study was conducted to assess the applicability of artificial neural networks (ANN) for forecasting the dynamics of uranium extraction over exploitation time during the process of In Situ Leaching (ISL). Currently, ISL process simulation involves multiple steps, starting with geostatistical interpolation, followed [...] Read more.
This study was conducted to assess the applicability of artificial neural networks (ANN) for forecasting the dynamics of uranium extraction over exploitation time during the process of In Situ Leaching (ISL). Currently, ISL process simulation involves multiple steps, starting with geostatistical interpolation, followed by computational fluid dynamics (CFD) and reactive transport simulation. While extensive research exists detailing each of these steps, machine learning techniques may offer the potential to directly obtain extraction curves (i.e., the concentration of the mineral produced over the exploitation time of the deposit), thereby bypassing these computationally expensive steps. As a basis, both an empirical experimental configuration and reactive transport simulations were used to generate training data for the neural network model. An ANN was constructed, trained, and tested on several test cases with different initial parameters, then the expected outcomes were compared to those derived from conventional modeling techniques. The results indicate that for the employed experimental configuration and a limited number of features, artificial intelligence technologies, specifically regression-based neural networks can model the recovery rate (or extraction degree) of the ISL process for mineral production, achieving a high degree of accuracy compared to traditional CFD and mass transport models. Full article
(This article belongs to the Section Energy Systems)
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25 pages, 6153 KiB  
Article
State of Health Estimation of Lithium-Ion Battery Using Multi-Health Features Based on Savitzky–Golay Filter and Fitness-Distance Balance- and Lévy Roulette-Enhanced Coyote Optimization Algorithm-Optimized Long Short-Term Memory
by Hongbiao Li, Dengke Gao, Linlong Shi, Fei Zheng and Bo Yang
Processes 2024, 12(10), 2284; https://doi.org/10.3390/pr12102284 - 18 Oct 2024
Viewed by 684
Abstract
Accurate and reliable state of health (SOH) estimation is extremely crucial for the safe and stable operation of lithium-ion batteries (LIBs). In this paper, a method based on Lévy roulette- and fitness-distance balance-enhanced coyote optimization algorithm-optimized long short-term memory (LRFDBCOA-LSTM) is employed for [...] Read more.
Accurate and reliable state of health (SOH) estimation is extremely crucial for the safe and stable operation of lithium-ion batteries (LIBs). In this paper, a method based on Lévy roulette- and fitness-distance balance-enhanced coyote optimization algorithm-optimized long short-term memory (LRFDBCOA-LSTM) is employed for SOH estimation of LIB. Firstly, six health features are extracted from battery charging and discharging data, and Savitzky–Golay is used to filter the feature data to improve correlation between feature and SOH. Then, Lévy roulette and fitness-distance balance (FDB) strategies are used to improve the coyote optimization algorithm (COA), i.e., LRFDBCOA. Meanwhile, the improved algorithm is used to optimize the internal parameters of long short-term memory (LSTM) neural network. Finally, the effectiveness of the proposed model is comprehensively validated using five evaluation indicators based on battery data obtained under three different testing conditions. The experimental results manifest that after algorithm improvement and network parameter optimization, the performance of the model is significantly improved. In addition, the method has high estimation accuracy, strong generalization, and strong robustness for SOH estimation with a maximum R2 of 0.9896 and minimum R2 of no less than 0.9711. Full article
(This article belongs to the Topic Advances in Power Science and Technology, 2nd Edition)
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22 pages, 1846 KiB  
Article
An Evaluation of Biochar Derived from Agro-Industrial Waste as an Alternative Material for the Elimination of Pathogenic Load from Water
by Diana V. Delgado-Rebolledo, Edwin Chica and Ainhoa Rubio-Clemente
Processes 2024, 12(10), 2283; https://doi.org/10.3390/pr12102283 - 18 Oct 2024
Viewed by 961
Abstract
The contamination of water bodies is becoming more frequent due to uncontrolled discharges into them, including those of domestic or industrial wastewater (WW) characterized by the presence of heavy metals, a high pathogenic load, pesticides, and pharmaceuticals, among other pollutants, which represent a [...] Read more.
The contamination of water bodies is becoming more frequent due to uncontrolled discharges into them, including those of domestic or industrial wastewater (WW) characterized by the presence of heavy metals, a high pathogenic load, pesticides, and pharmaceuticals, among other pollutants, which represent a risk to both humans and the health of the ecosystem. Consequently, conventional water treatment processes have been implemented. However, they are not efficient enough. In this regard, exploring and analyzing new alternatives and sustainable systems that efficiently degrade the different pollutants found in WW are required, and biochar can be considered as an attractive treatment option, since it is an adsorbent carbonaceous material that allows for the removal of several pollutants. The generation and use of biochar contribute to the promotion of the circular bioeconomy and the achievement of sustainable development goals by enhancing the reuse and recycling of agricultural and agro-industrial waste as raw material for its production. The objective of this work is to evaluate the utilization of biochar as an alternative material for the elimination of the pathogenic load in water. Full article
(This article belongs to the Special Issue Emerging Technologies for Renewable Energy Utilization to Diversify the Energy Matrix)
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12 pages, 4184 KiB  
Article
Numerical Investigation on the Effect of Air Humidification and Oxygen Enrichment on Combustion and Emission Characteristics of Gas Boiler
by Haoyu Wang, Xiong Yang, Ziyi Li, Chuanzhao Zhang, Xianqiang Zhu, Ruijuan Zhang, Jing Du and Shuyuan Zhang
Processes 2024, 12(10), 2282; https://doi.org/10.3390/pr12102282 - 18 Oct 2024
Viewed by 600
Abstract
Gas boilers exhibit thermal inefficiency and unsatisfying pollutant emissions. In this study, numerical simulations were conducted to examine the effect of humidified oxygen-enriched air on methane combustion in a furnace and the effects of different premixed ratios of air on the temperature field [...] Read more.
Gas boilers exhibit thermal inefficiency and unsatisfying pollutant emissions. In this study, numerical simulations were conducted to examine the effect of humidified oxygen-enriched air on methane combustion in a furnace and the effects of different premixed ratios of air on the temperature field inside the furnace, intermediate product OH groups, component concentration distribution, and pollutants. Although humidification of ambient air effectively reduced the flame center temperature and mass concentration of the NOx generated during combustion in the furnace, the highest growth rate of CO concentration at the furnace outlet was 18.6%. Humidification of oxygen-enriched air increased the center temperature and outlet NO concentration of the furnace compared with those during no oxygen enrichment, but the outlet CO concentration showed a decreasing trend, with the highest decrease rate of 34.6%. This study determined an optimal CO–air premix ratio with a moisture concentration of 50 g/kg dry air and an oxygen concentration of 23%. The air humidification and oxygen enrichment technology proposed in this article provides a technical reference for low nitrogen transformation of existing gas boilers. Full article
(This article belongs to the Section Chemical Processes and Systems)
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16 pages, 10028 KiB  
Article
The Formation Mechanism of Residual Oil and Methods of Enhanced Oil Recovery in a Fractured Low-Permeability Metamorphic Rock Reservoir in Bohai Bay
by Jianchong Gao, Xianming Wang, Dingxue Zhang and Jie Wang
Processes 2024, 12(10), 2281; https://doi.org/10.3390/pr12102281 - 18 Oct 2024
Viewed by 625
Abstract
The oil reservoirs of the metamorphic rocks in Bohai Bay have geological characteristics such as low matrix porosity and permeability, developed natural microfractures, which result in the injection water rapidly advancing along fractures, a fast increase in the water content, and difficulties in [...] Read more.
The oil reservoirs of the metamorphic rocks in Bohai Bay have geological characteristics such as low matrix porosity and permeability, developed natural microfractures, which result in the injection water rapidly advancing along fractures, a fast increase in the water content, and difficulties in extracting the remaining oil. In order to reveal water channeling and the residual oil formation mechanisms in fractured low-permeability reservoirs and solve the water channeling problem, we first analyzed the reservoir development status, then studied the formation mechanism of residual oil using a microfluidic chip device, and formed a method of hierarchical control to effectively control the water channeling problem of fractured reservoirs and maximize the displacement of residual oil. The results show that (1) Due to the low permeability of the reservoir matrix, a large amount of injected water flows along the fracture channel, which leads to the long-term high water cut of some oil wells and the retention of a large amount of crude oil in the matrix. (2) The results of microfluidic experiments show that the distribution of residual oil after water flooding mainly includes five types: blind end of the pore throat, columnar, cluster, flake and film, and residual oil. Among them, sheet-like and clustered residual oil are dominant, accounting for 75~85% and 10~13%, respectively. (3) Based on the characteristics of fracture development in buried-hill reservoirs, a hierarchical control technology of “gel particle + liquid crosslinked gel system” is established. The field application effect predicted that the input–output ratio was 1:3. This study provides a reference for the comprehensive treatment of water channeling in the same type of offshore fractured low-permeability metamorphic rock reservoirs. Full article
(This article belongs to the Section Energy Systems)
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18 pages, 9273 KiB  
Article
Study on Near-Wellbore Fracture Initiation and Propagation with Fixed-Plane Perforation in Horizontal Well for Unconventional Reservoirs
by Maosen Yan, Chi Ai, Jun Zhang, Wenjing Lu and Rui Gao
Processes 2024, 12(10), 2280; https://doi.org/10.3390/pr12102280 - 18 Oct 2024
Viewed by 582
Abstract
At present, in the process of volume fracturing for a tight reservoir, employing the spiral perforation method to induce the fracture propagation direction would always obtain an unsatisfactory effect, which causes the deflection and tortuosity of hydraulic fractures. Therefore, researchers presented the fixed-plane [...] Read more.
At present, in the process of volume fracturing for a tight reservoir, employing the spiral perforation method to induce the fracture propagation direction would always obtain an unsatisfactory effect, which causes the deflection and tortuosity of hydraulic fractures. Therefore, researchers presented the fixed-plane perforation method for enhancing the effect on volume fracturing. In this paper, the three-dimensional discrete lattice method is used to study the initiation and propagation law of horizontal well fixed-plane perforation in unconventional reservoirs under two different stress states. The results show that it is more suitable to use fixed-plane perforation for reducing the initiation pressure. When employing the fixed-plane perforation method, fracture always initiates in the perforation plane, presents as an irregular fan-shaped failure surface, and then propagates along the wellbore. The initiation pressure is highly correlated to the phasing angle between adjacent perforations under different conditions, and the rate of increase in the initiation pressure decreases by around 1.59~6.38% when the phasing angle reaches 30°. The fracturing pressure is inversely correlated with the diameter and tunnel length of the perforations and the horizontal stress difference. When the diameter increases to 17 mm, the tunnel length increases to 25 cm or the horizontal stress difference reaches 8 MPa. These results reveal an insignificant effect of the above parameters on the initiation pressure. Full article
(This article belongs to the Special Issue Advances in Hydraulic Fracturing Technology for Unconventional Reservoirs)
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21 pages, 12004 KiB  
Article
Multi-Task Learning Network-Based Prediction of Hydraulic Fracturing Effects in Horizontal Wells Within the Ordos Yanchang Formation Tight Reservoir
by Pingtian Fan, Hai Yuan, Xiankun Song, Xiaowen Yang, Zhenyu Song, Ping Li, Ziyu Lin, Maozong Gan and Yuetian Liu
Processes 2024, 12(10), 2279; https://doi.org/10.3390/pr12102279 - 18 Oct 2024
Viewed by 652
Abstract
Accurate prediction of fracture volume and morphology in horizontal wells is essential for optimizing reservoir development. Traditional methods struggle to capture the intricate relationships between fracturing effects, geological variables, and operational factors, leading to reduced prediction accuracy. To address these limitations, this paper [...] Read more.
Accurate prediction of fracture volume and morphology in horizontal wells is essential for optimizing reservoir development. Traditional methods struggle to capture the intricate relationships between fracturing effects, geological variables, and operational factors, leading to reduced prediction accuracy. To address these limitations, this paper introduces a multi-task prediction model designed to forecast fracturing outcomes. The model is based on a comprehensive dataset derived from fracturing simulations within the Long 4 + 5 and Long 6 reservoirs, incorporating both operational and geological factors. Pearson correlation analysis was conducted to assess the relationships between these factors, ranking them according to their influence on fracturing performance. The results reveal that operational variables predominantly affect Stimulated Reservoir Volume (SRV), while geological variables exert a stronger influence on fracture morphology. Key operational parameters impacting fracturing performance include fracturing fluid volume, total fluid volume, pre-fluid volume, construction displacement, fracturing fluid viscosity, and sand ratio. Geological factors affecting fracture morphology include vertical stress, minimum horizontal principal stress, maximum horizontal principal stress, and layer thickness. A multi-task prediction model was developed using random forest (RF) and particle swarm optimization (PSO) methodologies. The model independently predicts SRV and fracture morphology, achieving an R2 value of 0.981 for fracture volume predictions, with an average error reduced to 1.644%. Additionally, the model’s fracture morphology classification accuracy reaches 93.36%, outperforming alternative models and demonstrating strong predictive capabilities. This model offers a valuable tool for improving the precision of fracturing effect predictions, making it a critical asset for reservoir development optimization. Full article
(This article belongs to the Section Energy Systems)
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33 pages, 3665 KiB  
Review
Role of Sintering Aids in Electrical and Material Properties of Yttrium- and Cerium-Doped Barium Zirconate Electrolytes
by Shivesh Loganathan, Saheli Biswas, Gurpreet Kaur and Sarbjit Giddey
Processes 2024, 12(10), 2278; https://doi.org/10.3390/pr12102278 - 18 Oct 2024
Viewed by 981
Abstract
Ceramic proton conductors have the potential to lower the operating temperature of solid oxide cells (SOCs) to the intermediate temperature range of 400–600 °C. This is attributed to their superior ionic conductivity compared to oxide ion conductors under these conditions. However, prominent proton-conducting [...] Read more.
Ceramic proton conductors have the potential to lower the operating temperature of solid oxide cells (SOCs) to the intermediate temperature range of 400–600 °C. This is attributed to their superior ionic conductivity compared to oxide ion conductors under these conditions. However, prominent proton-conducting materials, such as yttrium-doped barium cerates and zirconates with specified compositions like BaCe1−xYxO3−δ (BCY), BaZr1−xYxO3−δ (BZY), and Ba(Ce,Zr)1−yYyO3−δ (BCZY), face significant challenges in achieving dense electrolyte membranes. It is suggested that the incorporation of transition and alkali metal oxides as sintering additives can induce liquid phase sintering (LPS), offering an efficient method to facilitate the densification of these proton-conducting ceramics. However, current research underscores that incorporating these sintering additives may lead to adverse secondary effects on the ionic transport properties of these materials since the concentration and mobility of protonic defects in a perovskite are highly sensitive to symmetry change. Such a drop in ionic conductivity, specifically proton transference, can adversely affect the overall performance of cells. The extent of variation in the proton conductivity of the perovskite BCZY depends on the type and concentration of the sintering aid, the nature of the sintering aid precursors used, the incorporation technique, and the sintering profile. This review provides a synopsis of various potential sintering techniques, explores the influence of diverse sintering additives, and evaluates their effects on the densification, ionic transport, and electrochemical properties of BCZY. We also report the performance of most of these combinations in an actual test environment (fuel cell or electrolysis mode) and comparison with BCZY. Full article
(This article belongs to the Section Chemical Processes and Systems)
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