Journal Description
Processes
Processes
is an international, peer-reviewed, open access journal on processes/systems in chemistry, biology, material, energy, environment, food, pharmaceutical, manufacturing, automation control, catalysis, separation, particle and allied engineering fields published monthly online by MDPI. The Systems and Control Division of the Canadian Society for Chemical Engineering (CSChE S&C Division) and the Brazilian Association of Chemical Engineering (ABEQ) are affiliated with Processes and their members receive discounts on the article processing charges. Please visit Society Collaborations for more details.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Chemical) / CiteScore - Q2 (Chemical Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 13.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.5 (2022);
5-Year Impact Factor:
3.4 (2022)
Latest Articles
A Robust Process Identification Method under Deterministic Disturbance
Processes 2024, 12(5), 986; https://doi.org/10.3390/pr12050986 (registering DOI) - 12 May 2024
Abstract
This study introduces a novel process identification method aimed at overcoming the challenge of accurately estimating process models when faced with deterministic disturbances, a common limitation in conventional identification methods. The proposed method tackles the difficult modeling problems due to deterministic disturbances by
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This study introduces a novel process identification method aimed at overcoming the challenge of accurately estimating process models when faced with deterministic disturbances, a common limitation in conventional identification methods. The proposed method tackles the difficult modeling problems due to deterministic disturbances by representing the disturbances as a linear combination of Laguerre polynomials and applies an integral transform with frequency weighting to estimate the process model in a numerically robust and stable manner. By utilizing a least squares approach for parameter estimation, it sidesteps the complexities inherent in iterative optimization processes, thereby ensuring heightened accuracy and robustness from a numerical analysis perspective. Comprehensive simulation results across various process types demonstrate the superior capability of the proposed method in accurately estimating the model parameters, even in the presence of significant deterministic disturbances. Moreover, it shows promising results in providing a reasonably accurate disturbance model despite structural disparities between the actual disturbance and the model. By improving the precision of process models under deterministic disturbances, the proposed method paves the way for developing refined and reliable control strategies, aligning with the evolving demands of modern industries and laying solid groundwork for future research aimed at broadening application across diverse industrial practices.
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(This article belongs to the Section Process Control and Monitoring)
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Open AccessArticle
Fault Diagnosis of Wind Turbine Gearbox Using Vibration Scatter Plot and Visual Geometric Group Network
by
Meng-Hui Wang, Chun-Chun Hung, Shiue-Der Lu, Fu-Hao Chen, Yu-Xian Su and Cheng-Chien Kuo
Processes 2024, 12(5), 985; https://doi.org/10.3390/pr12050985 (registering DOI) - 12 May 2024
Abstract
This study aims to develop a fault detection system designed specifically for wind turbine gearboxes. It proposes a hybrid fault diagnosis algorithm that combines scatter plot analysis with the visual geometric group (VGG) technique to identify various fault types, including gear rust, chipping,
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This study aims to develop a fault detection system designed specifically for wind turbine gearboxes. It proposes a hybrid fault diagnosis algorithm that combines scatter plot analysis with the visual geometric group (VGG) technique to identify various fault types, including gear rust, chipping, wear, and aging. To capture vibration signals, a three-axis vibration sensor was integrated with a NI-9234 DAQ card. Digital signal processing techniques were employed to actively filter out noise from the captured signals. Gaussian white noise was incorporated into the training data to enhance the noise resistance of the network model, which was then utilized for scatter plot generation. The VGG technique was subsequently applied to identify faults. The testing data were collected at two different speeds, with 1500 samples taken at each speed, totaling 3000 samples. For both training and testing, 400 samples of each fault type were employed for training, while 200 samples were allocated for testing. The test results demonstrated an overall identification accuracy of 97.7% for both the no-fault gearbox and the four-fault states, underscoring the effectiveness of the proposed methodology.
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(This article belongs to the Section Automation Control Systems)
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Open AccessArticle
Local Path Planner for Mobile Robot Considering Future Positions of Obstacles
by
Xianhua Ou, Zhongnan You and Xiongxiong He
Processes 2024, 12(5), 984; https://doi.org/10.3390/pr12050984 (registering DOI) - 12 May 2024
Abstract
Local path planning is a necessary ability for mobile robot navigation, but existing planners are not sufficiently effective at dynamic obstacle avoidance. In this article, an improved timed elastic band (TEB) planner based on the requirements of mobile robot navigation in dynamic environments
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Local path planning is a necessary ability for mobile robot navigation, but existing planners are not sufficiently effective at dynamic obstacle avoidance. In this article, an improved timed elastic band (TEB) planner based on the requirements of mobile robot navigation in dynamic environments is proposed. The dynamic obstacle velocities and TEB poses are fully integrated through two-dimensional (2D) lidar and multi-obstacle tracking. First, background point filtering and clustering are performed on the lidar points to obtain obstacle clusters. Then, we calculate the data association matrix of the obstacle clusters of the current and previous frame so that the clusters can be matched. Thirdly, a Kalman filter is adopted to track clusters and obtain the optimal estimates of their velocities. Finally, the TEB poses and obstacle velocities are associated: we predict the obstacle position corresponding to the TEB pose through the detected obstacle velocity and add this constraint to the corresponding TEB pose vertex. Then, a pose sequence considering the future positions of obstacles is obtained through a graph optimization algorithm. Compared with the original TEB, our method reduces the total running time by 22.87%, reduces the running distance by 19.23%, and increases the success rate by 21.05%. Simulations and experiments indicate that the improved TEB enables robots to efficiently avoid dynamic obstacles and reach the goal as quickly as possible.
Full article
(This article belongs to the Special Issue Industrial IoT-Enabled Modeling and Optimization for the Process Industry)
Open AccessArticle
Experimental Study on the Gelling Properties of Nano-Silica Sol and Its Spontaneous Imbibition Grouting Mudstone
by
Yiming Zhao, Zhe Xiang, Nong Zhang and Jingchen Dai
Processes 2024, 12(5), 983; https://doi.org/10.3390/pr12050983 (registering DOI) - 12 May 2024
Abstract
The low-permeability argillaceous rock mass is an unfavorable geological body commonly found in the construction process of underground engineering conditions such as roadways and tunnels. Due to the compact structure and low permeability of the rock mass, grouting with conventional materials cannot effectively
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The low-permeability argillaceous rock mass is an unfavorable geological body commonly found in the construction process of underground engineering conditions such as roadways and tunnels. Due to the compact structure and low permeability of the rock mass, grouting with conventional materials cannot effectively seal the micro-cracks of the rock mass. Based on the low efficiency of high-pressure grouting of nano-silica sol, this paper preliminarily explores the regularities and mechanism of grouting and pore sealing of low-permeability rock mass under the action of silica sol imbibition from the aspects of gelling properties of silica sol, core pore structure, imbibition law, and pore sealing characteristics. The results show the following: (1) The increase in particle size during the gel process reduced the injectability and wettability of the silica sol. The imbibition properties of silica sol were time-varying, and the deterioration inflection points of injectability and wettability appeared at 10 h and 9 h, respectively. (2) Catalyst, temperature, gel process, and rock mass permeability will affect the law of core imbibition, and the injectability and capillary force of the grouting material and rock mass will jointly affect the imbibition process of silica sol. (3) Silica sol imbibition changed the pore size distribution of the core, the pore volume above 50 nm decreased, and the pore volume below 50 nm increased. Silica sol has multiple effects such as filling, adsorption, and percolation in the imbibition process of the micro-pores of rock mass, and the adsorption and percolation of silica are related to the nano micro-pores.
Full article
(This article belongs to the Section Materials Processes)
Open AccessFeature PaperArticle
Comparative Analysis of Enzyme-, Ultrasound-, Mechanical-, and Chemical-Assisted Extraction of Biflavonoids from Ginkgo Leaves
by
Anita Šalić, Lina Šepić, Iva Turkalj, Bruno Zelić and Dunja Šamec
Processes 2024, 12(5), 982; https://doi.org/10.3390/pr12050982 (registering DOI) - 12 May 2024
Abstract
The biflavonoid extraction from ginkgo (Ginkgo biloba L.) leaves using solvent-based extraction with 70% ethanol, alone and in combination with enzyme-assisted, ultrasound-assisted, mechanical-assisted, and chemically assisted methods was investigated and the influence of extraction duration was explored. The total content of polyphenols,
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The biflavonoid extraction from ginkgo (Ginkgo biloba L.) leaves using solvent-based extraction with 70% ethanol, alone and in combination with enzyme-assisted, ultrasound-assisted, mechanical-assisted, and chemically assisted methods was investigated and the influence of extraction duration was explored. The total content of polyphenols, flavonoids, and phenolic acids in the extracts was determined spectrophotometrically, while individual biflavonoids were identified and quantified using HPLC-DAD. Amentoflavone, bilobetin, ginkgetin, isoginkgetin, and sciadopitysin were identified in all our extracts. Among these, sciadopitysin emerged as the most prevalent biflavonoid with an amount above 1 mg g−1 dw, followed by isoginkgetin. Comparative analysis of the extraction methods revealed that, except for chemically assisted extraction, similar levels of compounds were obtained after 45 min of extraction. However, enzymatic (EAE) and mechanical-assisted extraction (MAE) exhibited significantly higher individual (EAE: 19–41% higher; MAE: 22–67% higher) and total biflavonoid (EAE: 29% higher; MAE 50% higher) levels after just 5 min, suggesting their potential to abbreviate extraction duration and facilitate the efficient retrieval of target compounds. However, as extraction efficiency varies between individual biflavonoids, our findings also underscore the importance of considering specific compounds and extraction kinetics in the optimization of ginkgo leaf extraction processes.
Full article
(This article belongs to the Special Issue Recent Advances in Processing Technologies for Substance Extraction, Separation, and Enrichment)
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Open AccessArticle
Construction and Investigation of a Filtration Efficiency Test System for High-Efficiency Filter Materials Based on Mass Concentration
by
Fang Wei, Yun Liang, Hao Wang, Mengxiang Hu, Lingyun Wang, Desheng Wang and Min Tang
Processes 2024, 12(5), 981; https://doi.org/10.3390/pr12050981 (registering DOI) - 12 May 2024
Abstract
Protection from nuclear biochemical aerosol and air pollution pays attention to aerosol mass concentration. The concentration of upstream aerosol of the commonly used filtration efficiency detection device for high-efficiency filter materials is low, making it insufficient for detecting the filtration efficiency of high-efficiency
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Protection from nuclear biochemical aerosol and air pollution pays attention to aerosol mass concentration. The concentration of upstream aerosol of the commonly used filtration efficiency detection device for high-efficiency filter materials is low, making it insufficient for detecting the filtration efficiency of high-efficiency filter materials. This study designed and built a set of filtration efficiency detection devices for high-efficiency filter materials based on mass concentration. By adjusting the oil bath temperature, injection pressure, the degree of spiral-separator separation, as well as the number and size of nozzles, we investigated the effects of each condition on the concentration and particle size distribution of aerosol generation. As a result, the oil mist generator of the device can stably generate high-concentration aerosol with a mass concentration of up to 1587.9 mg/m3 and a number concentration of up to 107–108 P/cm3. The high-concentration aerosol generated can meet the E11–U15 filter material performance requirements.
Full article
(This article belongs to the Section Separation Processes)
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Open AccessArticle
Numerical Investigation of Confining Pressure Effects on Microscopic Structure and Hydraulic Conductivity of Geosynthetic Clay Liners
by
Juan Hou, Yinyu Sun, Chenxi Chu and Rui Sun
Processes 2024, 12(5), 980; https://doi.org/10.3390/pr12050980 (registering DOI) - 12 May 2024
Abstract
A series of COMSOL numerical models were developed to explore how confining pressure impacts the microscopic structure and hydraulic conductivity of Geosynthetic Clay Liners (GCLs), taking into account the bentonite swelling ratio, mobile porosity, pore size, and tortuosity of the main flow path.
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A series of COMSOL numerical models were developed to explore how confining pressure impacts the microscopic structure and hydraulic conductivity of Geosynthetic Clay Liners (GCLs), taking into account the bentonite swelling ratio, mobile porosity, pore size, and tortuosity of the main flow path. The study reveals that the mobile porosity and pore size are critical factors affecting GCL hydraulic conductivity. As confining pressure increases, the transition of mobile water to immobile water occurs, resulting in a reduction in mobile water volume, the narrowing of pore channels, decreased flow velocity, and diminished hydraulic conductivity within the GCL. Mobile porosity undergoes a slight decrease from 0.273 to 0.104, while the ratio of mobile porosity to total porosity in the swelling process decreases significantly from 0.672 to 0.256 across the confining pressure range from 50 kPa to 500 kPa, which indicates a transition of mobile water toward immobile water. The tortuosity of the main flow path shows a slight increase, fluctuating within the range of 1.30 to 1.36, and maintains a value of around 1.34 as the confining pressure rises from 50 kPa to 500 kPa. At 50 kPa confining pressure, the minimum pore width measures 5.2 × 10−5 mm, with a corresponding hydraulic conductivity of 6.2 × 10−11 m/s. With an increase in confining pressure to 300 kPa, this compression leads to a narrower minimum pore width of 1.81 × 10−5 mm and a decrease in hydraulic conductivity to 5.11 × 10−12 m/s. The six-fold increase in confining pressure reduces hydraulic conductivity by one order of magnitude. A theoretical equation was derived to compute the hydraulic conductivity of GCLs under diverse confining pressure conditions, indicating a linear correlation between the logarithm of hydraulic conductivity and confining pressure, and exhibiting favorable agreement with experimental findings.
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(This article belongs to the Special Issue Advances in Solid Waste Treatment Technology and Contamination Remediation)
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Open AccessArticle
Technoeconomic Analysis of Intensified PEGylated Biopharmaceutical Recombinant Protein Production: Alpha Antitrypsin as a Model Case
by
Salem Alkanaimsh, Abdullah M. Alsalal and Hesham El-Touney
Processes 2024, 12(5), 979; https://doi.org/10.3390/pr12050979 (registering DOI) - 10 May 2024
Abstract
Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder characterized by the insufficient production of the AAT protein. Due to availability limitations, not all AATD patients receive protein therapy treatment. In this study, the technoeconomic analysis of different processes (conventional and intensified) producing 200
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Alpha-1 antitrypsin deficiency (AATD) is a genetic disorder characterized by the insufficient production of the AAT protein. Due to availability limitations, not all AATD patients receive protein therapy treatment. In this study, the technoeconomic analysis of different processes (conventional and intensified) producing 200 kg/year of PEGylated recombinant AAT (PEG-AAT) using a Chinese hamster ovary cell line was investigated. All bioprocesses consist of upstream, downstream, and PEGylation sections. A base-case model (process A) of the conventional fed-batch production bioreactor was developed using SuperPro Designer software (Version 13) to evaluate the economic feasibility of the process. The cost of goods (COG) was estimated to be approximately USD 387.6/g. Furthermore, an intensified process (B) was modeled and evaluated to reduce the COG. Process intensification was implemented in the process (N-1 perfusion bioreactor). The specific operating COG for process B was found to be 10% less than that of process A. Scenario analysis was performed to assess the impact of process capacity (100–1000 kg/year) and cell-specific productivity (30–90 pg/cell/day). With an increase in process capacity, the specific operating COG was reduced for all processes. Increasing cell-specific productivity decreases the specific operating COG at different rates for each process, depending on the titer level. Future investigations into the PEGylation section are required since it has the highest COG of all the sections.
Full article
(This article belongs to the Special Issue Application of Process Systems Engineering in Continuous Pharmaceutical and Biopharmaceutical Manufacturing)
Open AccessArticle
Enhanced Production of Clean Fermentable Sugars by Acid Pretreatment and Enzymatic Saccharification of Sugarcane Bagasse
by
Mario Alberto Yaverino-Gutierrez, Lucas Ramos, Jesús Jiménez Ascencio and Anuj Kumar Chandel
Processes 2024, 12(5), 978; https://doi.org/10.3390/pr12050978 (registering DOI) - 10 May 2024
Abstract
Sugarcane bagasse (SCB), an agro-industrial byproduct generated by a sugar mill, holds a substantial carbohydrate content of around 70 wt.%, comprising cellulose and hemicellulose. Saccharification plays a pivotal role in the conversion of SCB into second-generation (2G)-ethanol and valuable compounds, which is significantly
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Sugarcane bagasse (SCB), an agro-industrial byproduct generated by a sugar mill, holds a substantial carbohydrate content of around 70 wt.%, comprising cellulose and hemicellulose. Saccharification plays a pivotal role in the conversion of SCB into second-generation (2G)-ethanol and valuable compounds, which is significantly aided by thermochemical pretreatments. In this study, SCB underwent diluted sulfuric acid pretreatment (2% H2SO4, 80 rpm, 200 °C, 20 min), resulting in the removal of 77.3% of the xylan. The hemicellulosic hydrolysate was analyzed to identify the sugars and degraded products acting as microbial inhibitors. The acid hydrolysate showed a xylose yield of 68.0% (16.4 g/L) and a yield of 3.8 g/L of acetic acid. Afterward, the hemicellulosic hydrolysate was concentrated 2.37 times to obtain a xylose-rich stream (39.87 g/L). The sequential detoxification, employing calcium oxide and activated carbon, removed the inhibitory compounds, including acetic acid, while preserving the xylose at 38.10 g/L. The enzymatic saccharification of cellulignin at 5% and 10% of the total solids (TSs) yielded comparable reducing sugar (RS) yields of 47.3% (15.2 g/L) and 47.4% (30.4 g/L), respectively, after 96 h, employing a 10 FPU/g enzyme loading of Cellic® CTec3 (Novozymes Inc. Parana, Brazil). In summary, these findings outline an integrated green chemistry approach aimed at addressing the key challenges associated with pretreatment, concentration, detoxification, and enzymatic hydrolysis to produce fermentable sugars.
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(This article belongs to the Special Issue Integrated Process Design and Development of Biorefinery)
Open AccessArticle
Investigating Precise Decision-Making in Greenhouse Environments Based on Intelligent Optimization Algorithms
by
Zhenyi Zhu, Chunguang Bi and You Tang
Processes 2024, 12(5), 977; https://doi.org/10.3390/pr12050977 (registering DOI) - 10 May 2024
Abstract
The precise control of a greenhouse environment is vital in production. Currently, environmental control in traditional greenhouse production relies on experience, making it challenging to accurately control it, leading to environmental stress, resource waste, and pollution. Hence, this paper proposes a decision-making greenhouse
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The precise control of a greenhouse environment is vital in production. Currently, environmental control in traditional greenhouse production relies on experience, making it challenging to accurately control it, leading to environmental stress, resource waste, and pollution. Hence, this paper proposes a decision-making greenhouse environment control strategy that employs an existing monitoring system and intelligent algorithms to enhance greenhouse productivity and reduce costs. Specifically, a model library is created based on machine learning algorithms, and an intelligent optimization algorithm is designed based on the Non-Dominated Sorting Genetic Algorithm III (NSGA-3) and an expert experience knowledge base. Then, optimal environmental decision-making solutions under different greenhouse environments are obtained by adjusting the greenhouse environmental parameters. Our method’s effectiveness is verified through a simulated fertilization plan that was simulated for a real greenhouse tomato environment. The proposed optimization solution can reduce labor and time costs, enable accurate decision-making in the greenhouse environment, and enhance agricultural production efficiency.
Full article
(This article belongs to the Section Environmental and Green Processes)
Open AccessEditorial
Special Issue on “Application of Power Electronics Technologies in Power System”
by
Chang-Hua Lin and Jahangir Hossain
Processes 2024, 12(5), 976; https://doi.org/10.3390/pr12050976 (registering DOI) - 10 May 2024
Abstract
Over the years, all countries have agreed to alleviate the greenhouse effect and pro-mote net zero carbon emissions [...]
Full article
(This article belongs to the Special Issue Application of Power Electronics Technologies in Power System)
Open AccessArticle
Prediction Technology of a Reservoir Development Model While Drilling Based on Machine Learning and Its Application
by
Xin Wang, Min Mao, Yi Yang, Shengbin Yuan, Mingyu Guo, Hongru Li, Leli Cheng, Heng Wang and Xiaobin Ye
Processes 2024, 12(5), 975; https://doi.org/10.3390/pr12050975 (registering DOI) - 10 May 2024
Abstract
In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation
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In order to further understand the complex spatial distribution caused by the extremely strong heterogeneity of buried hill reservoirs, this paper proposes a new method for predicting the development pattern of buried hill reservoirs based on the traditional pre-drilling prediction and post-drilling evaluation methods that mainly rely on seismic, logging, and core data, which are difficult to meet the timeliness and accuracy of drilling operations. Firstly, the box method and normalization formula are used to process and normalize the abnormal data of element logging and engineering logging, and then the stepwise regression analysis method is used to optimize the sensitive parameters of element logging and engineering logging. The Light Gradient Boosting Machine (LightGBM) algorithm, deep neural network (DNN), and support vector machine (SVM) are used to establish a new method for predicting the development pattern of buried hill reservoirs. Lastly, a comprehensive evaluation index F1 score for the model is established to evaluate the prediction model for the development pattern of buried hill reservoirs. The F1 score value obtained from this model’s comprehensive evaluation index indicates that the LightGBM model achieves the highest accuracy, with 96.7% accuracy in identifying weathered zones and 95.8% accuracy in identifying interior zones. The practical application demonstrates that this method can rapidly and accurately predict the development mode of buried hill reservoirs while providing a new approach for efficient on-site exploration and decision-making in oil and gas field developments. Consequently, it effectively promotes exploration activities as well as enhances the overall process of oil and gas reservoir exploration.
Full article
(This article belongs to the Special Issue Quantitative Evaluation, Efficient Development, Seepage, and Simulation of Geo-Energy Resources)
Open AccessArticle
Predicting Alloying Element Yield in Converter Steelmaking Using t-SNE-WOA-LSTM
by
Xin Liu, Xihui Qu, Xinjun Xie, Sijun Li, Yanping Bao and Lihua Zhao
Processes 2024, 12(5), 974; https://doi.org/10.3390/pr12050974 (registering DOI) - 10 May 2024
Abstract
The performance and quality of steel products are significantly impacted by the alloying element control. The efficiency of alloy utilization in the steelmaking process was directly related to element yield. This study analyses the factors that influence the yield of elements in the
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The performance and quality of steel products are significantly impacted by the alloying element control. The efficiency of alloy utilization in the steelmaking process was directly related to element yield. This study analyses the factors that influence the yield of elements in the steelmaking process using correlation analysis. A yield prediction model was developed using a t-distributed stochastic neighbor embedding (t-SNE) algorithm, a whale optimization algorithm (WOA), and a long short-term memory (LSTM) neural network. The t-SNE algorithm was used to reduce the dimensionality of the original data, while the WOA optimization algorithm was employed to optimize the hyperparameters of the LSTM neural network. The t-SNE-WOA-LSTM model accurately predicted the yield of Mn and Si elements with hit rates of 71.67%, 96.67%, and 99.17% and 57.50%, 89.17%, and 97.50%, respectively, falling within the error range of ±1%, ±2%, and ±3% for Mn and ±1%, ±3%, and ±5% for Si. The results demonstrate that the t-SNE-WOA-LSTM model outperforms the backpropagation (BP), LSTM, and WOA-LSTM models in terms of prediction accuracy. The model was applied to actual production in a Chinese plant. The actual performance of the industrial application is within a ±3% error range, with an accuracy of 100%. Furthermore, the elemental yield predicted by the model and then added the ferroalloys resulted in a reduction in the elemental content of the product by 0.017%. The model enables accurate prediction of alloying element yields and was effectively applied in industrial production.
Full article
(This article belongs to the Section Energy Systems)
Open AccessArticle
Evaluation of the Efficiency of Using an Oxidizer in the Leaching Process of Gold-Containing Concentrate
by
Bagdaulet Kenzhaliyevich Kenzhaliyev, Nessipbay Kyandykovich Tussupbayev, Gulnar Zhanuzakovna Abdykirova, Aigul Kairgeldyevna Koizhanova, Dametken Yedilovna Fischer, Zhazira Amangeldiyevna Baltabekova and Nazira Orakkyzy Samenova
Processes 2024, 12(5), 973; https://doi.org/10.3390/pr12050973 (registering DOI) - 10 May 2024
Abstract
This article presents the results of cyanide leaching of gold-containing concentrate using the trichlorocyanuric acid (TCCA) oxidizer. Gold-containing concentrate was obtained from a gold tailings sample from a gold recovery factory (GRF) in one of the deposits of Kazakhstan that have not previously
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This article presents the results of cyanide leaching of gold-containing concentrate using the trichlorocyanuric acid (TCCA) oxidizer. Gold-containing concentrate was obtained from a gold tailings sample from a gold recovery factory (GRF) in one of the deposits of Kazakhstan that have not previously been studied for concentrability. According to X-ray phase analysis and energy dispersive spectrometry (DSM) data, the main compounds in the tailings sample under study are pyrite FeS2, quartz SiO2, calcite CaCO3, albite NaAlSi3O8, muscovite KAl2Si3AlO10(OH)8, dolomite CaMg(CO3)2, and oxidized iron compounds. Microscopic studies of the concentrate have established the presence of ultrafine gold with sizes from Au 0.9 to 10.2 μm in pyrite. Obtaining the gold-containing concentrate with a gold content of 15.95 g/t is possible according to the enrichment scheme, which includes centrifugal separation, classification according to the fineness class −0.05 mm, additional grinding of hydrocyclone sands to a fineness of 90.0–95.0% of the class finer than 0.050 mm, and control centrifugal separation. Since pyrite in technogenic raw materials is the main gold-containing mineral, this paper presents studies on the oxidizability of pyrite with the TCCA oxidizer. The results of studies on the oxidation of pyrite using the TCCA oxidizer show the products of its hydrolysis oxidize pyrite with the formation of various iron compounds on its surface. Pretreatment of gold-containing concentrate with oxidizer TCCA for 3 h before the cyanidation process (20 h) allows for an increase in the recovery of gold in the solution by 5.8%.
Full article
(This article belongs to the Topic Advanced Oxidation Processes: Applications and Prospects, 2nd Volume)
Open AccessArticle
The Gaseous Hydrogen Transport Capacity in Nanopores Coupling Bulk Flow Mechanisms and Surface Diffusion: Integration of Profession and Innovation
by
Yanglu Wan, Wei Lu, Zhouman Huang, Rucang Qian and Zheng Sun
Processes 2024, 12(5), 972; https://doi.org/10.3390/pr12050972 - 10 May 2024
Abstract
Due to its unique chemical structure, hydrogen energy inherently has a high calorific value without reinforcing global warming, so it is expected to be a promising alternative energy source in the future. In this work, we focus on nanoconfined hydrogen flow performance, a
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Due to its unique chemical structure, hydrogen energy inherently has a high calorific value without reinforcing global warming, so it is expected to be a promising alternative energy source in the future. In this work, we focus on nanoconfined hydrogen flow performance, a critical issue in terms of geological hydrogen storage. For nanopores where the pore scale is comparable to hydrogen’s molecular size, the impact on hydrogen molecules exerted by the pore surface cannot be neglected, leading to the molecules near the surface gaining mobility and slipping on the surface. Furthermore, hydrogen adsorption takes place in the nanopores, and the way the adsorption molecules move is completely different from the bulk molecules. Hence, the frequently applied Navier–Stokes equation, based on the no-slip boundary condition and overlooking the contribution of the adsorption molecules, fails to precisely predict the hydrogen flow capacity in nanopores. In this paper, hydrogen molecules are classified as bulk molecules and adsorption molecules, and then models for the bulk hydrogen and the adsorption hydrogen are developed separately. In detail, the bulk hydrogen model considers the slip boundary and rarefaction effect characterized by the Knudsen number, while the flow of the adsorption hydrogen is driven by a chemical potential gradient, which is a function of pressure and the essential adsorption capacity. Subsequently, a general model for the hydrogen flow in nanopores is established through weight superposition of the bulk hydrogen flow as well as the adsorption hydrogen, and the key weight coefficients are determined according to the volume proportion of the identified area. The results indicate that (a) the surface diffusion of the adsorption molecules dominates the hydrogen flow capacity inside nanopores with a pore size of less than 5 nm; (b) improving the pressure benefits the bulk hydrogen flow and plays a detrimental role in reducing surface diffusion at a relatively large pressure range; (c) the nanoconfined hydrogen flow conductance with a strong adsorption capacity (PL = 2 MPa) could reach a value ten times greater than that with a weak adsorption capacity (PL = 10 MPa). This research provides a profound framework for exploring hydrogen flow behavior in ultra-tight strata related to adsorption phenomena.
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(This article belongs to the Section Energy Systems)
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Open AccessArticle
Study on the Interaction Propagation Mechanism of Inter-Cluster Fractures under Different Fracturing Sequences
by
Xiaojun Cai, Weixuan Zhao, Tianbao Hu, Xinwei Du, Haiyang Wang and Xiong Liu
Processes 2024, 12(5), 971; https://doi.org/10.3390/pr12050971 - 10 May 2024
Abstract
Horizontal-well multi-cluster fracturing is one of the most important techniques for increasing the recovery rate in unconventional oil and gas reservoir development. However, under the influence of complex induced stress fields, the mechanism of interaction and propagation of fractures within each segment remains
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Horizontal-well multi-cluster fracturing is one of the most important techniques for increasing the recovery rate in unconventional oil and gas reservoir development. However, under the influence of complex induced stress fields, the mechanism of interaction and propagation of fractures within each segment remains unclear. In this study, based on rock fracture criteria, combined with the boundary element displacement discontinuity method, a two-dimensional numerical simulation model of hydraulic fracturing crack propagation in a planar plane was established. Using this model, the interaction and propagation process of inter-cluster fractures under different fracturing sequences within horizontal well segments and the mechanism of induced stress field effects were analyzed. The influence mechanism of cluster spacing, fracture design length, and fracture internal pressure on the propagation morphology of inter-cluster fractures was also investigated. The research results indicate that, when using the alternating fracturing method, it is advisable to appropriately increase the cluster spacing to weaken the inhibitory effect of induced stress around the fractures created by prior fracturing on subsequent fracturing. Compared to the alternating fracturing method, the propagation morphology of fractures under the symmetrical fracturing method is more complex. At smaller cluster spacing, fractures created by prior fracturing are more susceptible to being captured by fractures from subsequent fracturing. The findings of this study provide reliable theoretical support for the optimization design of fracturing sequences and fracturing processes in horizontal well segments.
Full article
(This article belongs to the Special Issue Innovations in Hydraulic Fracturing Technology for Unconventional Reservoirs)
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Open AccessArticle
Effect of Fiber and Insect Powder Addition on Selected Organoleptic and Nutritional Characteristics of Gluten-Free Bread
by
Alexandra Tauferová, Martina Pečová, Aneta Czerniková, Dani Dordević and Bohuslava Tremlová
Processes 2024, 12(5), 970; https://doi.org/10.3390/pr12050970 - 10 May 2024
Abstract
A wide range of gluten-free bakery products are already available on the market. However, they often have a low proportion of fiber and inferior sensory properties when compared to classic baked goods. The aim of this work was to evaluate the influence of
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A wide range of gluten-free bakery products are already available on the market. However, they often have a low proportion of fiber and inferior sensory properties when compared to classic baked goods. The aim of this work was to evaluate the influence of the addition of different types of fiber and insect powder on selected organoleptic and nutritional properties of gluten-free pieces of bread and to reformulate a recipe for gluten-free bread. Twenty experimental samples were prepared with different types and percentages of fiber, either alone or in combination. Sensory analysis, instrumental texture analysis, and chemical analyses, including predicted glycemic index, were carried out. A total of 16 of the 24 fiber-enriched samples received an average or slightly above-average rating. The samples containing the fiber mixture without insect powder and the sample containing 9% flaxseed performed best in the overall evaluation. The combination of different types of plant fibers simultaneously with the incorporation of insect powder in a low concentration appears to be advantageous, both from the viewpoint of sensory acceptability and also from the viewpoint of the potential for increasing the polyphenol content and antioxidant capacity. This study lists the sensorially acceptable range of fiber concentrations, which can be a guide for the bakery industry.
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(This article belongs to the Section Food Process Engineering)
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Open AccessArticle
Experimental Investigation of Phase Equilibria in the Al–Mo–Hf Ternary System at 400 °C and 600 °C
by
Boliang Liu, Zhiqiang Yu, Libin Liu and Ligang Zhang
Processes 2024, 12(5), 969; https://doi.org/10.3390/pr12050969 - 10 May 2024
Abstract
This study investigates the phase equilibria of the Al-Mo-Hf ternary system at 400 °C and 600 °C using X-ray diffraction (XRD) and electron probe microanalysis (EPMA/WDS) techniques. Seven three-phase and five two-phase regions were identified at 400 °C, while eight three-phase and four
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This study investigates the phase equilibria of the Al-Mo-Hf ternary system at 400 °C and 600 °C using X-ray diffraction (XRD) and electron probe microanalysis (EPMA/WDS) techniques. Seven three-phase and five two-phase regions were identified at 400 °C, while eight three-phase and four two-phase regions were identified at 600 °C. Despite variations in the solid solubility ranges of certain compounds, the distribution of phase zones in the isothermal cross-section remained consistent at both temperatures. Using the experimental results and logical deductions, isothermal cross-sections were constructed for the Al-Mo-Hf ternary system at 600 °C and 400 °C.
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(This article belongs to the Section Materials Processes)
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Open AccessFeature PaperArticle
Design of Static Output Feedback Suspension Controllers for Ride Comfort Improvement and Motion Sickness Reduction
by
Jinwoo Kim and Seongjin Yim
Processes 2024, 12(5), 968; https://doi.org/10.3390/pr12050968 - 9 May 2024
Abstract
This paper presents a method to design a static output feedback active suspension controller for ride comfort improvement and motion sickness reduction in a real vehicle system. Full-state feedback controller has shown good performance for active suspension control. However, it requires a lot
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This paper presents a method to design a static output feedback active suspension controller for ride comfort improvement and motion sickness reduction in a real vehicle system. Full-state feedback controller has shown good performance for active suspension control. However, it requires a lot of states to be measured, which is very difficult in real vehicles. To avoid this problem, a static output feedback (SOF) controller is adopted in this paper. This controller requires only three sensor outputs, vertical velocity, roll and pitch rates, which are relatively easy to measure in real vehicles. Three types of SOF controller are proposed and optimized with linear quadratic optimal control and the simulation optimization method. Two of these controllers have only three gains to be tuned, which are much smaller than those of full-state feedback. To validate the performance of the proposed SOF controllers, a simulation is carried out on a vehicle simulation package. From the results, the proposed SOF controllers are quite good at improving ride comfort and reducing motion sickness.
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(This article belongs to the Special Issue Advances in the Control of Complex Dynamic Systems)
Open AccessArticle
Research on the Functional Microbe Activation System in a Post-Polymer Flooded Reservoir
by
Yinsong Liu, Min Wang, Haiwen Wei, Xiaolin Wu, Zhaowei Hou, Xiumei Zhang and Erlong Yang
Processes 2024, 12(5), 967; https://doi.org/10.3390/pr12050967 - 9 May 2024
Abstract
Further exploitation of the residual oil underground in post-polymer flooded reservoirs is attractive and challenging. Microbial-enhanced oil recovery (MEOR) is a promising strategy to enhance the recovery of residual oil in post-polymer flooded reservoirs. Identifying and selectively activating indigenous microorganisms with oil displacement
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Further exploitation of the residual oil underground in post-polymer flooded reservoirs is attractive and challenging. Microbial-enhanced oil recovery (MEOR) is a promising strategy to enhance the recovery of residual oil in post-polymer flooded reservoirs. Identifying and selectively activating indigenous microorganisms with oil displacement capabilities is an urgent requirement in the current design of efficient microbial-enhanced oil recovery technologies. This study combines high-throughput sequencing with functional network analysis to identify the core functional microbes within the reservoirs. Concurrently, it devises targeted activation strategies tailored to oligotrophic conditions through an analysis of environmental factor influences. The feasibility of these strategies is then validated through physical simulation experiments. With nutrient stimulation, the overall diversity of microorganisms decreases while the abundance of functional microorganisms increases. The core displacement results showed that the oil recovery factor increased by 3.82% on the basis of polymer flooding. In summary, this research has established a system for the efficient activation of functional microorganisms under oligotrophic conditions by utilizing bioinformatics, network analysis, and indoor simulation systems. This achievement will undoubtedly lay a solid foundation for the practical implementation of microbial enhancement techniques in the field.
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(This article belongs to the Section Energy Systems)
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Meet Us at the XVI Green Chemistry Postgraduate Summer School 2024, 30 June–5 July 2024, Venice, Italy
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