Processes

15 pages, 2877 KiB

Open AccessFeature PaperArticle

Real-Time Estimation of CO₂ Absorption Capacity Using Ionic Conductivity of Protonated Di-Methyl-Ethanolamine (DMEA) and Electrical Conductivity in Low-Concentration DMEA Aqueous Solutions

by Sang-Jun Han, Joo Young Han and Jung-Ho Wee

Processes 2024, 12(11), 2495; https://doi.org/10.3390/pr12112495 (registering DOI) - 10 Nov 2024

Abstract

The present study investigates the real-time estimation of CO₂ absorption capacity (CAC) based on the electrical conductivity (EC) of low-concentration di-methyl-ethanolamine (DMEA) solutions (0.1–0.5 M). CO₂ absorption experiments are conducted to measure the variation in CAC and EC during CO₂ [...] Read more.

The present study investigates the real-time estimation of CO₂ absorption capacity (CAC) based on the electrical conductivity (EC) of low-concentration di-methyl-ethanolamine (DMEA) solutions (0.1–0.5 M). CO₂ absorption experiments are conducted to measure the variation in CAC and EC during CO₂ absorption, revealing a strong correlation between the two properties. The ionic conductivity of DMEAH⁺ formed during absorption is calculated to be 53.1 S·cm²/(mol·z), which is found to be larger than that of TEAH⁺ and MDEAH⁺. This can be attributed to the smaller molar mass and higher ionic mobility of DMEAH⁺. A significant finding is that the measured EC (EC_M) of the DMEA solutions consistently demonstrates a lower value than the theoretically predicted value. This discrepancy is due to the larger ionic size of DMEAH⁺, which results in a reduction in the real mean ionic activity coefficient. This effect becomes more pronounced with increasing DMEA concentration. Consequently, a higher CAC is required to produce the same change in EC at higher amine concentrations. Based on these findings, an empirical equation is devised to estimate CAC from EC_M in solutions of constant DMEA concentration. This equation will be employed as a practical approach for the in situ monitoring of CO₂ absorption using DMEA aqueous solution. Full article

(This article belongs to the Special Issue CO₂ Capture and Conversion Processes: Recent Trends and Future Perspectives)

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10 pages, 846 KiB

Open AccessArticle

The Pyrolysis Characteristics of Bagasse Were Studied by TG-MS-FTIR

by Songsong Zhang, Yue Gao, Haichuan Tong, Yong Dong, Guoli Qi and Peng Wang

Processes 2024, 12(11), 2494; https://doi.org/10.3390/pr12112494 (registering DOI) - 9 Nov 2024

Abstract

Sugarcane bagasse is rich in cellulose and lignin, and the recycling of bagasse has become an important research field with the increasing global concern for sustainable development and environmental protection. In this paper, TG-MS-FTIR equipment was used to analyze the pyrolysis characteristics of [...] Read more.

Sugarcane bagasse is rich in cellulose and lignin, and the recycling of bagasse has become an important research field with the increasing global concern for sustainable development and environmental protection. In this paper, TG-MS-FTIR equipment was used to analyze the pyrolysis characteristics of bagasse from Guangxi under different heating rates and different atmospheres, which is conducive to the reuse of bagasse from the waste gas produced in the sugar plant. The results showed that the pyrolysis rate of sugarcane bagasse in the air atmosphere was faster than that in the nitrogen atmosphere and showed a double-peak trend, and the Coats–Redfern computational model could more accurately simulate the process of pyrolysis. The lower heating rate could overcome the heat transfer hysteresis phenomenon in the process of pyrolysis. In the air atmosphere, the contact time between oxygen and volatile products was shorter due to the high heating rate, and more and more complex species were precipitated at 10 °C/min than at 20 °C/min. In the nitrogen atmosphere, it was favorable to produce more kinds and quantities of gas products, because it did not react with oxygen. FTIR detected CH₄, CO, H₂O, CO₂, C-O-C, and C=O during pyrolysis in nitrogen, and some of C-O-C and C=O were cracked into small molecule compounds at high temperature. Full article

(This article belongs to the Special Issue Research on High-Temperature Thermochemical Conversion of Biomass)

20 pages, 7643 KiB

Open AccessArticle

Research on Reactivity-Equivalent Physical Transformation Method for Double Heterogeneity in Pressurized Water Reactors Based on Machine Learning

by Song Li, Jiannan Li, Lei Liu, Baocheng Huang, Ling Chen, Yongfa Zhang, Jianli Hao and Yunfei Zhang

Processes 2024, 12(11), 2493; https://doi.org/10.3390/pr12112493 (registering DOI) - 9 Nov 2024

Abstract

Traditional computational methods for pressurized water reactors are unable to handle dispersed fuel particles as the double heterogeneity and the direct volumetric homogenization can result in significant errors. In contrast, reactivity-equivalent physical transformation techniques offer high precision for addressing the double heterogeneity introduced [...] Read more.

Traditional computational methods for pressurized water reactors are unable to handle dispersed fuel particles as the double heterogeneity and the direct volumetric homogenization can result in significant errors. In contrast, reactivity-equivalent physical transformation techniques offer high precision for addressing the double heterogeneity introduced by dispersed fuel particles. This approach converts the double heterogeneity problem into a single heterogeneity problem, which is then subsequently investigated by using the conventional pressurized water reactor computational procedure. However, it is currently empirical and takes a lot of time to obtain the right k_∞. In this paper, we train the RPT model by using the existing dataset of plate-dispersed fuel and rod-dispersed fuel by a machine learning method based on a linear regression model, and we then use the new data to make predictions and derive the corresponding similarity ratios. The burnup verification, density verification, fission rate verification, and neutron energy spectrum analysis are calculated through the OpenMC program. For plate-type fuel elements, the method maintains an accuracy within 200 pcm during depletion, with deviations in the ²³⁵U density and ²³⁵U fission rate within 0.1% and neutron energy spectrum errors within 6%. For rod-type fuel elements, the method maintains an accuracy within 100 pcm during depletion, with deviations in ²³⁵U and ²³⁹Pu density within 1.5% and neutron energy spectrum errors within 1%. The numerical validation indicates that the reactivity-equivalent physical transformation method based on the linear regression model not only greatly improves the computational efficiency, but also ensures a very high accuracy to deal with double heterogeneity in nuclear reactors. Full article

(This article belongs to the Section Advanced Digital and Other Processes)

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20 pages, 5328 KiB

Open AccessArticle

Impact of Acid Rain on Release Characteristics of Heavy Metals in Low-Sulfur Tailings with Strong Acid Neutralization Capacity: A Case Study from Northern Guangxi, China

by Xiaohua Shu, Dinghua Zhang, Qian Zhang, Tao Ai, Xuehong Zhang and Jie Liu

Processes 2024, 12(11), 2492; https://doi.org/10.3390/pr12112492 (registering DOI) - 9 Nov 2024

Abstract

Tailing ponds are major sources of heavy metal pollution. Previous studies primarily focused on tailings with high sulfur content, with limited attention to low-sulfur tailings. This study explored the release behavior of Pb, Zn, and Cd from low-sulfur tailings under simulated acid rain [...] Read more.

Tailing ponds are major sources of heavy metal pollution. Previous studies primarily focused on tailings with high sulfur content, with limited attention to low-sulfur tailings. This study explored the release behavior of Pb, Zn, and Cd from low-sulfur tailings under simulated acid rain conditions, considering factors such as pH, particle size, and weathering degree. Samples were collected from a lead–zinc tailing pond in the karst regions of northern Guangxi, China. Batch leaching experiments indicated that even with high acid neutralization capacity (ANC = 166.57–167.45 kg H₂SO₄/t), substantial heavy metal leaching occurred under acidic conditions (pH 2–3), with Pb, Zn, and Cd concentrations increasing 4–6 times compared to neutral conditions. Leachate concentrations were slightly higher in coarser particles than in finer ones, while weathering further enhanced metal release, particularly for Cd. These findings suggest that acid neutralization alone may not be sufficient to prevent heavy metal leaching in low-sulfur tailings exposed to acid rain. However, due to the laboratory scale of this study, further validation through field-scale or mesocosm experiments is necessary to confirm the observed trends and assess their implications for environmental risk management in karst regions. Full article

(This article belongs to the Special Issue Advances in Remediation of Contaminated Sites: Volume II)

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13 pages, 2366 KiB

Open AccessArticle

Numerical Simulation of the Coal Measure Gas Accumulation Process in Well Z-7 in Qinshui Basin

by Gaoyuan Yan, Yu Song, Fangkai Quan, Qiangqiang Cheng and Peng Wu

Processes 2024, 12(11), 2491; https://doi.org/10.3390/pr12112491 (registering DOI) - 9 Nov 2024

Abstract

The process of coal measure gas accumulation is relatively complex, involving multiple physicochemical processes such as migration, adsorption, desorption, and seepage of multiphase fluids (e.g., methane and water) in coal measure strata. This process is constrained by multiple factors, including geological structure, reservoir [...] Read more.

The process of coal measure gas accumulation is relatively complex, involving multiple physicochemical processes such as migration, adsorption, desorption, and seepage of multiphase fluids (e.g., methane and water) in coal measure strata. This process is constrained by multiple factors, including geological structure, reservoir physical properties, fluid pressure, and temperature. This study used Well Z-7 in the Qinshui Basin as the research object as well as numerical simulations to reveal the processes of methane generation, migration, accumulation, and dissipation in the geological history. The results indicate that the gas content of the reservoir was basically zero in the early stage (before 25 Ma), and the gas content peaks all appeared after the peak of hydrocarbon generation (after 208 Ma). During the peak gas generation stage, the gas content increased sharply in the early stages. In the later stage, because of the pressurization of the hydrocarbon generation, the caprock broke through and was lost, and the gas content decreased in a zigzag manner. The reservoirs in the middle and upper parts of the coal measure were easily charged, which was consistent with the upward trend of diffusion and dissipation and had a certain relationship with the cumulative breakout and seepage dissipation. The gas contents of coal, shale, and tight sandstone reservoirs were positively correlated with the mature hydrocarbon generation of organic matter in coal seams, with the differences between different reservoirs gradually narrowing over time. Full article

(This article belongs to the Special Issue Exploration, Exploitation and Utilization of Coal and Gas Resources, 2nd Edition)

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18 pages, 4669 KiB

Open AccessArticle

Stress Zoning Characteristics of Goaf Side and Quantitative Evaluation of Surrounding Rock Stability

by Hongkai Zhang, Xiaofei Guo and Kunlin Yang

Processes 2024, 12(11), 2490; https://doi.org/10.3390/pr12112490 (registering DOI) - 9 Nov 2024

Abstract

Aiming to maintain the stability of the mining roadway and the next working-face roadway in the goaf side of a coal mine, a systematic study was carried out, through theoretical analysis, numerical simulation, field case analysis, and other methods, of the synergistic change [...] Read more.

Aiming to maintain the stability of the mining roadway and the next working-face roadway in the goaf side of a coal mine, a systematic study was carried out, through theoretical analysis, numerical simulation, field case analysis, and other methods, of the synergistic change mechanism in the stress distribution and plastic zone development morphology of the roadway’s surrounding rock in the goaf side under mining disturbance. It was revealed that, under the influence of mining, the goaf side will form a high-deviatoric-stress environment, which directly affects the shape and stability of the plastic zone of the roadway’s surrounding rock. Based on the characteristics of the principal stress ratio and the morphological development law of the plastic zone of the surrounding rock, the side of the goaf is divided into four regions: unloading zone, high-deviatoric-stress zone, low-deviatoric-stress zone, and original-stress zone. And the corresponding mine pressure behavior zoning is proposed: fracture zone, butterfly failure zone, elliptical failure zone, and circular failure zone. A quantitative evaluation method for the stability of the roadway surrounding rock based on the plastic zone morphology criterion was established, and combined with the division of mine pressure, the stability of the surrounding rock on the side of the goaf was quantitatively evaluated. Full article

(This article belongs to the Special Issue Advances in Coal Processing, Utilization, and Process Safety)

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13 pages, 707 KiB

Open AccessArticle

Preparation of Phosphorus/Hollow Silica Microsphere Modified Polyacrylonitrile-Based Carbon Fiber Composites and Their Thermal Insulation and Flame Retardant Properties

by Xiaohui Zhang, Guangsheng Huang and Guobin Wang

Processes 2024, 12(11), 2489; https://doi.org/10.3390/pr12112489 - 8 Nov 2024

Abstract

Since thermal insulation materials with a single function cannot satisfy the increasing requirements for complex usage, the combination of thermal insulation with flame retardancy is desirable in multiple applications. Herein, phosphorous-containing flame retardant modifier (5.0 wt.%, 9.0 wt.%, and 13.0 wt.%) and hollow [...] Read more.

Since thermal insulation materials with a single function cannot satisfy the increasing requirements for complex usage, the combination of thermal insulation with flame retardancy is desirable in multiple applications. Herein, phosphorous-containing flame retardant modifier (5.0 wt.%, 9.0 wt.%, and 13.0 wt.%) and hollow silica microsphere (130 nm of diameter) were composited with polyacrylonitrile-based carbon nanofibers via electrospinning technique. Electrospun phosphorous/silica/carbon nanofibers (P/HSM/CF) exhibited a uniform and clear fibrous structure (508, 170, and 1550 nm of average fiber diameter) with modified uniform and complete spherical silica. Reduced thermal conductivity (39.9–41.2 mW/m/K) and enhanced limiting oxygen index (29.5–33.5%) were achieved, enabling fire protection grade of fiber membrane from UL-94 V-1 grade to UL-94 V-0 grade efficiently. Moreover, favorable tensile strength (8.64–9.27 MPa) and elongation at break (43.28–48.54%) were obtained, presenting expected applications in structural components. The findings of this work provided a valuable reference for the fabrication of carbon nanofiber-based thermal insulation materials with excellent flame retardant and mechanical properties. Full article

(This article belongs to the Section Materials Processes)

18 pages, 2319 KiB

Open AccessArticle

Application of Machine Learning for the Prediction of Absorption, Distribution, Metabolism and Excretion (ADME) Properties from Cichorium intybus Plant Phytomolecules

by Ayesha Hena Afzal, Ozair Alam, Sherin Zafar, Mohammad Afshar Alam, Kahksha Ahmed, Jalaluddin Khan, Rahmuddin Khan, Abdelaaty A. Shahat and Abdulsalam Alhalmi

Processes 2024, 12(11), 2488; https://doi.org/10.3390/pr12112488 (registering DOI) - 8 Nov 2024

Abstract

Drug discovery is the process by which new drug candidates are discovered and drug development takes place. To enhance the efficiency, accuracy, and speed of the drug discovery process, machine learning (ML) could play a transformative role. For this research study, antidiabetic natural [...] Read more.

Drug discovery is the process by which new drug candidates are discovered and drug development takes place. To enhance the efficiency, accuracy, and speed of the drug discovery process, machine learning (ML) could play a transformative role. For this research study, antidiabetic natural compounds from C. intybus, which is commonly known as chicory, were selected, as they have promising antidiabetic properties that can complement conventional diabetes treatments. A bioactive natural compound dataset was retrieved on the chicory plant using Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) public source information. This collected dataset was analyzed for its absorption, distribution, metabolism, and excretion (ADME) properties using the SwissADME online tool. Principal component analysis (PCA) and correlation analysis were performed using trial-version XLSTAT software 2014.5.03 and Python. The obtained dataset from SwissADME was subjected to cleaning, after that, it was used to develop machine learning models, such as support vacuum (SVM) ML, random forest (RF), Naive Bayes (NB), and decision tree (DT). The Lipinski rule of violation was chosen as the target variable. To improve the vitality of the created ADME dataset, PCA, a biplot graph, and correlation analysis were carried out. A large dataset of naturally occurring antidiabetic compounds was used to predict the drug-likeness of ML models that were effectively deployed on heterogeneous ADME datasets. Among all these ML models, DT performed better than the rest of the models. Full article

(This article belongs to the Special Issue Transfer Learning Methods in Equipment Reliability Management)

17 pages, 3122 KiB

Open AccessArticle

Characteristics of Solid Mineral Phase Transitions During Sulfuric Acid Production from Gaseous-Sulphur-Reduced Gypsum

by Tianqi Wen, Yanxin Chen and Bo Zhao

Processes 2024, 12(11), 2487; https://doi.org/10.3390/pr12112487 (registering DOI) - 8 Nov 2024

Abstract

The acid co-production of cement is a prominent research focus for the large-scale, high-value utilization of phosphogypsum in the context of dual-carbon strategies. This paper builds on extensive research conducted by its authors on the co-production of sulphoaluminate cement clinker through acid production [...] Read more.

The acid co-production of cement is a prominent research focus for the large-scale, high-value utilization of phosphogypsum in the context of dual-carbon strategies. This paper builds on extensive research conducted by its authors on the co-production of sulphoaluminate cement clinker through acid production from gaseous-sulphur-reduced phosphogypsum. The solid mineral phase transformations occurring in the kiln during this process are systematically studied, and the effects of various calcination regimes (temperature, time, and atmosphere) on the evolution of clinker mineral phases are elucidated. This paper provides basic data support for the gas-sulfur-reduced phosphogypsum-acid cogeneration of sulfoaluminate cement clinker processes, and promotes the realization of the large-scale high-value utilization of phosphogypsum resources. The generation of the clinker mineral phase anhydrous calcium sulphoaluminate (C₄A₃S̅) begins at 1100 °C. Increasing the calcination temperature and extending the calcination time promote C₄A₃S̅ formation. However, when the calcination temperature exceeds 1350 °C, C₄A₃S̅ decomposes, leading to the formation of low-activity C₂AS. In a CO atmosphere, the main mineral phases in the clinker transform into C₂AS and 12CaO·7Al₂O₃, owing to the decomposition of CaSO₄, which inhibits C₄A₃S̅ formation. At calcination temperatures exceeding 1300 °C, a significant amount of C₂AS appears in the calcined material, and 12CaO·7Al₂O₃ begins to form. Full article

(This article belongs to the Section Materials Processes)

23 pages, 5031 KiB

Open AccessFeature PaperArticle

The Electrooxidation of Synthetic Bipyridyl Herbicide Wastewaters with Boron-Doped Diamond Electrodes: A Technical and Economic Study to Boost Their Application for Pollution Prevention in the Agricultural Sector

by Elia Alejandra Teutli-Sequeira, Ruben Vasquez-Medrano, Dorian Prato-Garcia and Jorge G. Ibanez

Processes 2024, 12(11), 2486; https://doi.org/10.3390/pr12112486 (registering DOI) - 8 Nov 2024

Abstract

Boron-doped diamond electrodes (BDDEs) offer a highly efficient pathway to mineralize recalcitrant compounds due to their reduced energy requirements, fewer chemical inputs, and mechanical stability. In this work, the electrochemical degradation of paraquat (PQ) and diquat (DQ) was studied using an undivided cell [...] Read more.

Boron-doped diamond electrodes (BDDEs) offer a highly efficient pathway to mineralize recalcitrant compounds due to their reduced energy requirements, fewer chemical inputs, and mechanical stability. In this work, the electrochemical degradation of paraquat (PQ) and diquat (DQ) was studied using an undivided cell (Condiacell^®-type) at circumneutral pH, and under galvanostatic control. The roles of applied current density, volumetric flow rate, and herbicide concentration were systematically studied through a central composite design (CCD) using a closed-flow reaction setup. Under the best operating conditions (i.e., for PQ: 1.6 mA/cm², 80 mL/min, and 70 mL/min, and 70 mg/L; and for DQ: 1.5 mA/cm², 80 mL/min, and 73 mg/L), a spectrophotometric analysis evidenced that the herbicides were satisfactorily removed (ca. 100%) while mineralization degrees were above 90%. Furthermore, the produced effluents yielded significant increases in seed germination and root length, which suggest a reduction in toxicity. Energy consumptions of 0.13 and 0.18 kWh/g of TOC are reported with the electrochemical cells for the PQ and DQ treatments, respectively. The PQ and DQ treatments by electrooxidation are estimated to emit nearly 2.7 and 38.9 kg CO₂/m³ of water treated, with a cost around USD 250/m³. Carbon emissions could be greatly decreased for PQ (0.28 kg CO₂/m³) and DQ (0.40 kg CO₂/m³) if electricity were generated from renewable resources. Although this study suggests that the use of BDDE can be considered as a green alternative for agrochemical removal due to lower carbon emissions, the environmental profile of the process is determined by the degree of renewability of the electrical grid of each country or region. Full article

(This article belongs to the Special Issue Advanced Oxidation Processes in Water Treatment)

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18 pages, 2659 KiB

Open AccessArticle

Small-Sample Short-Term Photovoltaic Output Prediction Model Based on GRA-SSA-GNNM Method

by Qi Wang, Meiheriayi Mutailipu, Qiang Xiong, Xuehui Jing and Yande Yang

Processes 2024, 12(11), 2485; https://doi.org/10.3390/pr12112485 (registering DOI) - 8 Nov 2024

Abstract

The precision of photovoltaic (PV) output forecasting results is crucial to the reliability of the intelligent distribution network and multi-energy supplementary system. This work aims to address problems of insufficient research related to the short-term prediction of small-sample PV power generation and the [...] Read more.

The precision of photovoltaic (PV) output forecasting results is crucial to the reliability of the intelligent distribution network and multi-energy supplementary system. This work aims to address problems of insufficient research related to the short-term prediction of small-sample PV power generation and the low prediction accuracy in the previous research. A hybrid prediction model based on grey relation analysis (GRA) combined with the sparrow search algorithm (SSA) and the grey neural network model (GNNM) is proposed. In this paper, GRA is utilized to reduce the dimension of meteorological features of the samples. Then, the GNNM is used to perform regression analysis on the input features after reducing the dimension of meteorological features of the samples, and the parameters of the GNNM are optimized via SSA. A limited dataset was used to compare several models in different seasons and weather conditions. The prediction results agree well with the data from the PV power plant in Xinjiang, indicating that the GRA-SSA-GNNM model developed in this work effectively achieves a high precision estimation in short-term PV power generation output prediction and has a promising application in this field. Full article

(This article belongs to the Special Issue Advances in Detection, Control and Optimization of Low-Carbon Energy Systems)

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1 pages, 131 KiB

Open AccessCorrection

Correction: Sriseubsai et al. Robust Design of PC/ABS Filled with Nano Carbon Black for Electromagnetic Shielding Effectiveness and Surface Resistivity. Processes 2020, 8, 616

by Wipoo Sriseubsai, Arsarin Tippayakraisorn and Jun Wei Lim

Processes 2024, 12(11), 2484; https://doi.org/10.3390/pr12112484 (registering DOI) - 8 Nov 2024

Abstract

With this correction, the Editorial Office together with the authors are making the following amendments to the published article [...] Full article

(This article belongs to the Special Issue Green Technologies: Bridging Conventional Practices and Industry 4.0)

17 pages, 4329 KiB

Open AccessArticle

Research on Crack Sealing Performance of Polymer Microsphere/Hydrogel Composite System

by Wenjin Liu, Jun Li, Taotao Luo and Xueyuan Long

Processes 2024, 12(11), 2483; https://doi.org/10.3390/pr12112483 (registering DOI) - 8 Nov 2024

Abstract

Owing to their excellent water-absorption and swelling properties, polymer microspheres have been extensively applied as deep profile control agents in oilfields. These microspheres effectively seal large pore-throat channels in reservoirs, optimizing the water-absorption profile. In this study, a composite system was developed, comprising [...] Read more.

Owing to their excellent water-absorption and swelling properties, polymer microspheres have been extensively applied as deep profile control agents in oilfields. These microspheres effectively seal large pore-throat channels in reservoirs, optimizing the water-absorption profile. In this study, a composite system was developed, comprising polymer microspheres and polyacrylamide polymers, with the inclusion of a cross-linking agent. The system leverages the synergistic effects of polymer microspheres and other plugging techniques to efficiently seal fractured reservoirs. Results indicate that the composite system exhibits strong blocking and scour resistance due to enhanced network integrity, higher viscosity, and improved elastic strength. Additionally, the composite system demonstrates a notable self-repairing capability, maintaining a high sealing efficiency even after a waterflood breakthrough. Full article

(This article belongs to the Special Issue Advances in Enhancing Unconventional Oil/Gas Recovery, 2nd Edition)

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20 pages, 7628 KiB

Open AccessArticle

Combined Effect of Multiple Slotting Spatial Parameters on Gas Extraction Efficiency: Numerical Analysis and Field Verification

by Xuexi Chen, Xinyu Ma, Jiaying Hu, Tao Yang, Aitao Zhou, Ruiqing Bi and Jihong Sun

Processes 2024, 12(11), 2482; https://doi.org/10.3390/pr12112482 - 8 Nov 2024

Abstract

Hydraulic slotting is an effective technology that enhances gas extraction operations and prevents gas disasters in coal mines. Slotting parameters and spatial arrangements substantially affect permeability enhancements. The pressure-release range and effective extraction area under different slotting spatial parameters were obtained by constructing [...] Read more.

Hydraulic slotting is an effective technology that enhances gas extraction operations and prevents gas disasters in coal mines. Slotting parameters and spatial arrangements substantially affect permeability enhancements. The pressure-release range and effective extraction area under different slotting spatial parameters were obtained by constructing a hydraulic slotting pressure-release permeability and three-dimensional (3D) slotting numerical models. These models quantitatively characterized the influence rules of multiple slotting spatial arrangement parameters on the extraction efficiency at a 3D scale, clarified the interactions of multiple slottings and their combined effects on pressure relief and permeability enhancement, and verified the results using field engineering tests. The results showed that hydraulic slotting significantly alters local stress and strain distributions, creating high-strain and high-stress zones with clear spatial attenuation. The process enhances fracture development, reducing gas pressure from 1 MPa to 0.08 MPa, thereby improving extraction efficiency. Enlarging the slot dimensions from 1.5 to 2.5 m increases the gas pressure-relief efficiency by up to 41% and nearly triples the impact radius. Wider slot spacing (1.5 m to 3.5 m) and additional slots (from one to three) further reduce the borehole gas pressure by 23% to 25%, optimizing hydraulic slotting technology for practical applications. Full article

(This article belongs to the Special Issue Monitoring, Process Control, Simulation, and Optimization in Coal Mining)

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11 pages, 3757 KiB

Open AccessArticle

Enhancement of Natural Dye-Sensitized Solar Cell Efficiency Through TiO₂ Hombikat UV100 and TiO₂ P25 Photoanode Optimization

by Assohoun Fulgence Kraidy, Abé Simon Yapi, Pierre Saint-Gregoire, Lídice Vaillant-Roca, Samuel Eke, Ruben Mouangue, Arash Jamali and Yaovi Gagou

Processes 2024, 12(11), 2481; https://doi.org/10.3390/pr12112481 - 8 Nov 2024

Abstract

Engineering new photoanode materials to substantially improve the efficiency of natural dye-sensitized solar cells (DSSC-Ns) is a significant challenge in the field of DSSC-Ns. This study utilizes the doctor blade technique to develop novel photoanode materials based on mixtures with different proportions of [...] Read more.

Engineering new photoanode materials to substantially improve the efficiency of natural dye-sensitized solar cells (DSSC-Ns) is a significant challenge in the field of DSSC-Ns. This study utilizes the doctor blade technique to develop novel photoanode materials based on mixtures with different proportions of TiO₂ Hombikat UV100 and TiO₂ P25, two nanometric powders with different grain sizes. The fabricated films were studied by X-ray diffraction, which revealed a dominant anatase phase in the structure, as was corroborated by Raman spectroscopy. The crystallite size of the materials was determined using the Scherrer method. Using optical measurements, we estimated the bandgap energy (Eg) of the photoanodes that varied in the samples at around 3 eV. The assembled solar cells demonstrated a significant efficiency of 4.87% in the TiO₂ Hombikat UV100/TiO2 P25 sample with the proportion of 50–50% (HP50) of blended photoanode. This sample device exhibited a fill factor of 50.41%, an open circuit voltage (Voc) of 0.65 V, and a current density of 14.75 mA/cm² for an active surface area of 0.19 cm². The HP50 sample constituted highly efficient DSSC-Ns and photoanodes with lower open-circuit voltage in the series, while HP40 developed a V_oc of 0.73 V, and HP30 developed a V_oc of 0.70 V. Full article

(This article belongs to the Special Issue New Technologies and Processing of Photoelectric Functional Materials and Devices)

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16 pages, 972 KiB

Open AccessFeature PaperReview

Particle Size as an Indicator of Wheat Flour Quality: A Review

by Dariusz Dziki, Anna Krajewska and Pavol Findura

Processes 2024, 12(11), 2480; https://doi.org/10.3390/pr12112480 - 8 Nov 2024

Abstract

Wheat flour is one of the most important food raw materials, with its quality determined by various indicators. One such indicator is particle size and granulometric distribution. In recent years, numerous studies have focused on the effect of flour and bran particle size [...] Read more.

Wheat flour is one of the most important food raw materials, with its quality determined by various indicators. One such indicator is particle size and granulometric distribution. In recent years, numerous studies have focused on the effect of flour and bran particle size on the properties of cereal products such as bread, pasta, noodles, and cookies. The aim of this review was to analyze the extent to which this parameter influences the properties of these cereal products. Additionally, the relationships between flour particle size and its chemical composition were presented. Key factors affecting the granulometric composition of flour, related to wheat grain properties and the grinding process, were also discussed. The study specifically focuses on research conducted in the last five years. Full article

(This article belongs to the Special Issue Feature Papers in the "Food Process Engineering" Section)

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13 pages, 2761 KiB

Open AccessArticle

CO₂-Enhanced Gas Recovery in Offshore Carbon-Rich Gas Reservoirs—Part 1: In Situ Gas Dispersion Behaviors

by Ping Jiang, Yuqiang Zha, Qing Ye, Runfu Xiong, Nan Zhao, Fengyang Mo, Lei Sun, Minxuan Li, Yuqi Zeng and Bin Liang

Processes 2024, 12(11), 2479; https://doi.org/10.3390/pr12112479 - 8 Nov 2024

Abstract

In the middle and late stages of offshore carbon-rich gas reservoir development, insufficient reservoir energy poses significant challenges and difficulty in improving gas recovery. Injecting CO₂ back into the reservoir is a promising development approach that can address both carbon emissions and [...] Read more.

In the middle and late stages of offshore carbon-rich gas reservoir development, insufficient reservoir energy poses significant challenges and difficulty in improving gas recovery. Injecting CO₂ back into the reservoir is a promising development approach that can address both carbon emissions and enhanced gas recovery (EGR). During the CO₂ injection process, the CO₂–CH₄ dispersion significantly impacts the recovery of CH₄. To understand the mass transfer and dispersion laws of CO₂ and high-carbon natural gas under current in situ reservoir conditions, this study conducted 1-m-long core experiments to investigate the effects of different gas compositions and permeabilities on gas recovery and diffusion laws in offshore reservoirs, taking into account the evolution of permeability in the porous medium. The experimental results indicate that the higher carbon concentration helps reduce mixing with formation gas, which consists of 70% methane, 25% nitrogen, and 5% carbon dioxide, resulting in a smaller diffusion coefficient. Under the conditions of an injection rate of 0.4 mL/min, a temperature of 81 °C, and a pressure of 7 MPa, the diffusion coefficient decreases by 27.5% as the carbon dioxide concentration increases from 70% to 90%, resulting in a 1.5% increase in recovery efficiency. As the permeability decreases, the viscous resistance of the fluid increases, leading to longer breakthrough times, and the reservoir fluid becomes more akin to piston displacement, reducing the degree of dispersion. The findings of this study provide guidance for optimizing gas injection strategies by reducing CO₂ dispersion and further enhancing natural gas recovery. Full article

(This article belongs to the Special Issue Carbon Capture, Utilization, and Storage (CCUS) in Unconventional Oil and Gas)

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18 pages, 430 KiB

Open AccessReview

A Review of Data-Driven Intelligent Monitoring for Geological Drilling Processes

by Sheng Du, Cheng Huang, Xian Ma and Haipeng Fan

Processes 2024, 12(11), 2478; https://doi.org/10.3390/pr12112478 - 8 Nov 2024

Abstract

The exploration and development of resources and energy are fundamental to human survival and development, and geological drilling is a key method for deep resource and energy exploration. Intelligent monitoring technology can achieve anomaly detection, fault diagnosis, and fault prediction in the drilling [...] Read more.

The exploration and development of resources and energy are fundamental to human survival and development, and geological drilling is a key method for deep resource and energy exploration. Intelligent monitoring technology can achieve anomaly detection, fault diagnosis, and fault prediction in the drilling process, which is crucial for ensuring production safety and improving drilling efficiency. The drilling process is characterized by complex geological conditions, variable working conditions, and low information value density, which pose a series of difficulties and challenges for intelligent monitoring. This paper reviews the research progress of the data-driven intelligent monitoring of geological drilling processes, focusing on the above difficulties and challenges. It mainly includes multivariate statistics, machine learning, and multi-model fusion. Multivariate statistical methods can effectively handle and analyze complex geological drilling data, while machine learning methods can efficiently extract key patterns and trends from a large amount of geological drilling data. Multi-model fusion methods, by combining the advantages of the first two methods, enhance the ability to handle complex multivariable and nonlinear problems. This review shows that existing research still faces problems such as limited data processing capabilities and insufficient model generalization capabilities. Improving the efficiency of data processing and the generalization capability of models may be the main research directions in the future. Full article

(This article belongs to the Special Issue Application of Artificial Intelligence in Industrial Process Modelling and Optimization)

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17 pages, 9123 KiB

Open AccessArticle

The Influence of Rock and Natural Weak Plane Properties on the Vertical Propagation of Hydraulic Fractures

by Xuefeng Yang, Cheng Chang, Qiuyang Cheng, Weiyang Xie, Haoran Hu, Yongming Li, Yitao Huang and Yu Peng

Processes 2024, 12(11), 2477; https://doi.org/10.3390/pr12112477 - 7 Nov 2024

Abstract

China has abundant shale gas resources with good exploration value and development potential, making it a recent hotspot for exploration and development. It is widely agreed that large-scale hydraulic fracturing is essential for reservoir enhancement in shale formations. However, the evolution of fractures [...] Read more.

China has abundant shale gas resources with good exploration value and development potential, making it a recent hotspot for exploration and development. It is widely agreed that large-scale hydraulic fracturing is essential for reservoir enhancement in shale formations. However, the evolution of fractures during hydraulic fracturing is highly complex, necessitating research on the influence of various factors on the vertical propagation of hydraulic fractures. Based on geological and engineering parameters from the Luzhou block in southern Sichuan, this study employed the finite element method (FEM) and the cohesive element method to establish a coupled fluid-solid model for the vertical propagation of hydraulic fractures. Numerical simulations were conducted to investigate the interaction between hydraulic fractures and natural weak planes, clarifying the mechanisms involved. This study elucidates how different rock and natural weak plane properties affect the vertical propagation of hydraulic fractures and draws diagrams illustrating these interactions. The research indicated three fracture distribution patterns after the intersection of hydraulic fractures with natural weak planes: passive fractures, ‘I’-shaped fractures, and crossing fractures. The main fractures in these patterns exhibit initial damage and damage evolution characterized by tensile failure. Specifically, in passive fractures, the initial damage and damage evolution of natural weak planes manifest as shear failure. In ‘I’-shaped fractures, the initial damage in natural weak planes is characterized by shear failure, with damage evolution showing tensile failure. Crossing fractures show minimal damage in the weak planes. Under conditions of high natural weak plane cohesive strength, high Young’s modulus, low interlayer rock cohesive strength, high vertical stress difference, low interlayer stress difference, and high intersection angles, crossing fractures tend to form. Conversely, conditions of low natural weak plane cohesive strength, low Young’s modulus, high interlayer rock cohesive strength, low vertical stress difference, high interlayer stress difference, and low intersection angles favor the formation of ‘I’-shaped fractures. Passive fractures form under conditions of low natural weak plane cohesive strength and high vertical stress difference. This study found that Poisson’s ratio has a minimal effect on the vertical expansion of hydraulic fractures under the studied conditions, with natural weak plane strength being the primary control factor for fracture patterns. These findings enhance the theoretical foundation for the vertical propagation of hydraulic fractures in deep shale formations, facilitating the development and implementation of strategies for enhancing production in shale reservoirs with natural weak planes and better optimizing production in different types of shale reservoirs. Full article

(This article belongs to the Special Issue Advances in Enhancing Unconventional Oil/Gas Recovery, 2nd Edition)

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