Processes

23 pages, 3658 KiB

Open AccessArticle

An Efficient Method for Identifying Inter-Well Connectivity Using AP Clustering and Graphical Lasso: Validation with Tracer Test Results

by Lingfeng Zhang, Xinwei Liao, Peng Dong, Shanze Hou, Boying Li and Zhiming Chen

Processes 2024, 12(10), 2143; https://doi.org/10.3390/pr12102143 - 1 Oct 2024

Abstract

Identifying inter-well connectivity is crucial for optimizing reservoir development and facilitating informed adjustments. While current engineering methods are effective, they are often prohibitively expensive due to the complex nature of reservoir conditions. In contrast, methods that utilize historical production data to identify inter-well [...] Read more.

Identifying inter-well connectivity is crucial for optimizing reservoir development and facilitating informed adjustments. While current engineering methods are effective, they are often prohibitively expensive due to the complex nature of reservoir conditions. In contrast, methods that utilize historical production data to identify inter-well connectivity offer faster and more cost-effective alternatives. However, when faced with incomplete dynamic data—such as long-term shut-ins and data gaps—these methods may yield substantial errors in correlation results. To address this issue, we have developed an unsupervised machine learning algorithm that integrates sparse inverse covariance estimation with affinity propagation clustering to map and analyze dynamic oil field data. This methodology enables the extraction of inter-well topological structures, facilitating the automatic clustering of producers and the quantitative identification of connectivity between injectors and producers. To mitigate errors associated with sparse production data, our approach employs sparse inverse covariance estimation for preprocessing the production performance data of the wells. This preprocessing step enhances the robustness and accuracy of subsequent clustering and connectivity analyses. The algorithm’s stability and reliability were rigorously evaluated using long-term tracer test results from a test block in an actual reservoir, covering a span of over a decade. The results of the algorithm were compared with those of the tracer test to evaluate its accuracy, precision rate, recall rate, and correlation. The clustering results indicate that wells with similar characteristics and production systems are automatically grouped into distinct clusters, reflecting the underlying geological understanding. The algorithm successfully divided the test block into four macro-regions, consistent with geological interpretations. Furthermore, the algorithm effectively identified the inter-well connectivity between injectors and producers, with connectivity magnitudes aligning closely with actual tracer test data. Overall, the algorithm achieved a precision rate of 79.17%, a recall rate of 90.48%, and an accuracy of 91.07%. This congruence validates the algorithm’s effectiveness in the quantitative analysis of inter-well connectivity and demonstrates significant potential for enhancing the accuracy and efficiency of inter-well connectivity identification. Full article

(This article belongs to the Section Energy Systems)

19 pages, 9912 KiB

Open AccessArticle

A Feasibility Study for the Hot-Air-Assisted Reflow Soldering Process Based on Computational Fluid Dynamics

by Natcha Kanjad, Chanapat Chanbandit and Jatuporn Thongsri

Processes 2024, 12(10), 2142; https://doi.org/10.3390/pr12102142 - 1 Oct 2024

Abstract

In hard disk drive (HDD) manufacturing, a reflow soldering process (RSP) employs heat generated at the welding tip (WT) to bond tiny electrical components for assembling an HDD. Generally, the heat was generated by an electric current applied to the WT. This article [...] Read more.

In hard disk drive (HDD) manufacturing, a reflow soldering process (RSP) employs heat generated at the welding tip (WT) to bond tiny electrical components for assembling an HDD. Generally, the heat was generated by an electric current applied to the WT. This article reports a feasibility study of using hot air based on computational fluid dynamics (CFD), a choice to assist heat generation. First, the WT and hot air tube (HAT) prototypes were designed and created. The HAT is a device that helps to supply hot air directly to generate heat at the WT. Then, the experiment was established to measure the temperature (T) supplied by the hot air. The measure results were employed to validate the CFD results. Next, the prototype HAT was used to investigate the T generated at the WT by CFD. The comparison revealed that the T measured by the experiment was in the 106.2 °C–133.5 °C range and that the CFD was in the 107.3 °C–136.6 °C range. The maximum error of the CFD results is 2.3% compared to the experimental results, confirming the credibility of the CFD results and methodology. The CFD results revealed that the operating conditions, such as WT, HAT designs, hot air inlet velocity, and inlet temperature, influence the T. Last, examples of suitable operating conditions for using hot air were presented, which confirmed that hot air is a proper choice for a low-temperature RPS. Full article

(This article belongs to the Special Issue Numerical Simulation and Optimization in Thermal Processes)

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13 pages, 1686 KiB

Open AccessArticle

Characterizing Wall Loss Effects of Intermediate-Volatility Hydrocarbons in a Smog Chamber with a Teflon Reactor

by Zhuoyue Ren, Wei Song, Xiaodie Pang, Yanli Zhang, Chenghao Liao, Yongbo Zhang and Xinming Wang

Processes 2024, 12(10), 2141; https://doi.org/10.3390/pr12102141 - 1 Oct 2024

Abstract

Intermediate-volatility organic compounds (IVOCs) serve as pivotal precursors to secondary organic aerosol (SOA). They are highly susceptible to substantial wall losses both in indoor environments and within smog chambers even with Teflon walls. Accurately characterizing the wall loss effects of IVOCs is thus [...] Read more.

Intermediate-volatility organic compounds (IVOCs) serve as pivotal precursors to secondary organic aerosol (SOA). They are highly susceptible to substantial wall losses both in indoor environments and within smog chambers even with Teflon walls. Accurately characterizing the wall loss effects of IVOCs is thus essential for simulation studies aiming to replicate their atmospheric behaviors in smog chambers to ensure precise modeling of their physical and chemical processes, including SOA formation, yet a comprehensive understanding of the wall loss behavior of IVOCs remains elusive. In this study, we conducted a thorough characterization of wall losses for typical intermediate-volatility hydrocarbon compounds, including eight normal alkanes (n-alkanes) and eight polycyclic aromatic hydrocarbons (PAHs), using the smog chamber with a 30 m³ Teflon reactor. Changes in the concentrations of gaseous IVOCs with the chamber were observed under dark conditions, and the experimental data were fitted to the reversible gas–wall mass transfer theory to determine the key parameters such as the wall accommodation coefficient (α_w) and the equivalent organic aerosol concentration (C_w) for different species. Our results reveal that C_w values for these hydrocarbon IVOCs range from 0.02 to 5.41 mg/m³, which increase with volatility for the PAHs but are relative stable for alkanes with an average of 3.82 ± 0.92 mg/m³. α_w span from 1.24 × 10⁻⁷ to 1.01 × 10⁻⁶, with the values for n-alkanes initially showing an increase followed by a decrease as carbon numbers rise and volatility decreases. The average α_w for n-alkanes and PAHs are 3.34 × 10⁻⁷ and 6.53 × 10⁻⁷, respectively. Our study shows that IVOCs exhibit different loss rates onto clean chamber walls under dry and dark conditions, with increasing rate as the volatility decreases. This study demonstrates how parameters can be acquired to address wall losses when conducting smog chamber simulation on atmospheric processes of IVOCs. Full article

(This article belongs to the Section Chemical Processes and Systems)

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13 pages, 3660 KiB

Open AccessArticle

A Novel Surrogate-Assisted Multi-Objective Well Control Parameter Optimization Method Based on Selective Ensembles

by Lian Wang, Rui Deng, Liang Zhang, Jianhua Qu, Hehua Wang, Liehui Zhang, Xing Zhao, Bing Xu, Xindong Lv and Caspar Daniel Adenutsi

Processes 2024, 12(10), 2140; https://doi.org/10.3390/pr12102140 - 1 Oct 2024

Abstract

Multi-objective optimization algorithms are crucial for addressing real-world problems, particularly with regard to optimizing well control parameters, which are often computationally expensive due to their reliance on numerical simulations. Surrogate-assisted models help to reduce this computational burden, but their effectiveness depends on the [...] Read more.

Multi-objective optimization algorithms are crucial for addressing real-world problems, particularly with regard to optimizing well control parameters, which are often computationally expensive due to their reliance on numerical simulations. Surrogate-assisted models help to reduce this computational burden, but their effectiveness depends on the quality of the surrogates, which can be affected by candidate dimension and noise. This study proposes a novel surrogate-assisted multi-objective optimization framework (MOO-SESA) that combines selective ensemble support-vector regression with NSGA-II. The framework’s uniqueness lies in its adaptive selection of a diverse subset of surrogates, established prior to iteration, to enhance accuracy, robustness, and computational efficiency. To our knowledge, this is the first instance in which selective ensemble techniques with multi-objective optimization have been applied to reservoir well control problems. Through employing an ensemble strategy for improving the quality of the surrogate model, MOO-SESA demonstrated superior well control scenarios and faster convergence compared to traditional surrogate-assisted models when applied to the SPE10 and Egg reservoir models. Full article

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

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19 pages, 7794 KiB

Open AccessArticle

Aerated Concrete, Based on the Ash of Thermal Power Plants, Nanostructured with Water-Soluble Fullerenols

by Olga V. Rudenko, Nikolay A. Charykov, Natalya A. Kulenova, Marzhan A. Sadenova, Darya K. Anop and Erzhan Kuldeyev

Processes 2024, 12(10), 2139; https://doi.org/10.3390/pr12102139 (registering DOI) - 1 Oct 2024

Abstract

This study is devoted to the synthesis of aerated concrete by a non-autoclave method using ash from thermal power plants and a nanopreparation. Fullerenol-m was used as a nanopreparation. The fullerenol-m content in the sealing water of aerated concrete changed in the range [...] Read more.

This study is devoted to the synthesis of aerated concrete by a non-autoclave method using ash from thermal power plants and a nanopreparation. Fullerenol-m was used as a nanopreparation. The fullerenol-m content in the sealing water of aerated concrete changed in the range of 0.00 ÷ 0.03 mas.%. The main performance characteristics of the nanostructured aerated concrete were studied, namely the compressive strength, impact toughness, thermal conductivity, density and moisture content. A significant improvement in the performance characteristics of the nanomodified aerated concrete compared to unmodified samples was demonstrated, which was most clearly manifested as an increase in impact toughness by several (three to five) times. The best performance characteristics of the modified aerated concrete were observed at a fullerenol-m concentration relative to the added cement within 0.022–0.028 wt.%. The authors attribute such a strong change and improvement in the physical, chemical and operational properties of aerated concrete when modified with fullerenol-m to the fact that fullerenol-m (a few thousandths of wt.%) has a very strong structuring effect on the sealing water and, as a consequence, on the resulting aerated concrete. Full article

(This article belongs to the Special Issue Advances in Nanomaterials for Cement-Based and Self-Healing Materials)

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10 pages, 260 KiB

Open AccessFeature PaperArticle

Experimental Application of Beneficial, Freeze-Dried Strain Enterococcus durans ED 26E/7 with Postbiotic Activity in Different Yogurts, Its Survival and Stability

by Andrea Lauková, Emília Dvorožňáková, Miroslava Petrová, Marcela Maloveská, Eva Bino, Natália Zábolyová, Anna Kandričáková and Monika Pogány Simonová

Processes 2024, 12(10), 2138; https://doi.org/10.3390/pr12102138 - 1 Oct 2024

Abstract

Yogurt is generally defined as a cultured milk product made using some species of lactic acid bacteria. Moreover, some additive bacteria are frequently involved in yogurts to provide health benefits. The objective of this study was testing the stability and survival of a [...] Read more.

Yogurt is generally defined as a cultured milk product made using some species of lactic acid bacteria. Moreover, some additive bacteria are frequently involved in yogurts to provide health benefits. The objective of this study was testing the stability and survival of a beneficial strain with postbiotic activity, Enterococcus durans ED 26E/7, in cow, goat, and ewe–goat milk yogurts. The validated methods were used in the study. Postbiotic, concentrated substance (CBs) from the strain ED 26E/7 inhibited growth of indicator bacteria by 60.5%. The strains E. hirae (96%) were susceptible to CBs (inhibitory activity from 200 to 25,600 AU/mL). The growth of staphylococci was inhibited by 79% with activity of 100 up to 25,600 AU/mL. Also, 40 out of 46 fecal E. coli were inhibited (activity 100 AU/mL). CBs was thermo-stable and remained active also after storage for 11 months at −20 °C and −80 °C. Exposing CBs to proteolytic enzymes did not lead to its complete deactivation indicating that it is probably not only a proteinaceous substance. The highest counts of the freeze-dried (encapsulated), safe ED 26E/7 strain and its stability were detected in ewe–goat milk yogurts. They reached up to 5.0 cfu/g. ED 26E/7 represents a further promising additive, although other testing will be performed. Full article

(This article belongs to the Section Food Process Engineering)

11 pages, 2053 KiB

Open AccessArticle

Tracking Differentiator-Based Identification Method for Temperature Predictive Control of Uncooled Heating Processes

by Shan Hua, Gang Chen, Yanni Dong, Changhao Fan and Zhuoyun Nie

Processes 2024, 12(10), 2137; https://doi.org/10.3390/pr12102137 - 1 Oct 2024

Abstract

The temperature control of uncooled heating processes presents challenges due to a substantial lag and the absence of active cooling mechanisms, which can lead to overshoot and oscillations. To address these issues, we propose an anti-disturbance identification method based on a tracking differentiator [...] Read more.

The temperature control of uncooled heating processes presents challenges due to a substantial lag and the absence of active cooling mechanisms, which can lead to overshoot and oscillations. To address these issues, we propose an anti-disturbance identification method based on a tracking differentiator (TD) and an input-constrained temperature predictive control (ICTPC) strategy. Our approach specifically considers the impact of unknown disturbances on model identification within a second-order heating process. By employing a TD to differentiate the input and output signals, we effectively minimize the identification error caused by low-frequency disturbances, yielding a robust anti-disturbance identification technique. Following this, we establish input constraints to limit the amplitude and variation of the control input, ensuring a more controlled and predictable system response. Using the identified model, an ICTPC algorithm is designed to achieve stable temperature control in uncooled heating processes. Experimental results from a typical uncooled heating system demonstrate that our method not only significantly reduces overshoot but also effectively mitigates temperature fluctuations, leading to enhanced control performance and system stability. This study provides a practical solution for temperature control in systems without cooling capabilities, offering substantial improvements in the efficiency and quality of industrial production processes. Full article

(This article belongs to the Special Issue Design and Control of Complex and Intelligent Systems)

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18 pages, 8155 KiB

Open AccessArticle

Optimizing Underground Natural Gas Storage Capacity through Numerical Modeling and Strategic Well Placement

by Cristian Nicolae Eparu, Alina Petronela Prundurel, Rami Doukeh, Doru Bogdan Stoica, Iuliana Veronica Ghețiu, Silviu Suditu, Ioana Gabriela Stan and Renata Rădulescu

Processes 2024, 12(10), 2136; https://doi.org/10.3390/pr12102136 - 1 Oct 2024

Abstract

This study focuses on optimizing the storage capacity of an underground natural gas storage facility through numerical modeling and simulation techniques. The reservoir, characterized by an elongated dome structure, was discretized into approximately 16,000 cells. Simulations were conducted using key parameters such as [...] Read more.

This study focuses on optimizing the storage capacity of an underground natural gas storage facility through numerical modeling and simulation techniques. The reservoir, characterized by an elongated dome structure, was discretized into approximately 16,000 cells. Simulations were conducted using key parameters such as permeability (10–70 mD) and porosity (12–26%) to assess the dynamics of gas injection and pressure distribution. The model incorporated core and petrophysical data to accurately represent the reservoir’s behavior. By integrating new wells in areas with storage deficits, the model demonstrated improvements in storage efficiency and pressure uniformity. The introduction of additional wells led to a significant increase in storage volume from 380 to 512 million Sm³ and optimized the injection process by reducing the storage period by 25%. The study concludes that reservoir performance can be enhanced with targeted well placement and customized flow rates, resulting in both increased storage capacity and economic benefits. Full article

(This article belongs to the Special Issue Process System Engineering of Gas Hydrate: Multiple Processes, Scales, Physics Fields and Senarios)

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11 pages, 6885 KiB

Open AccessArticle

Study on the Accumulation Model of the Cretaceous Reservoir in AHDEB Oilfield, Iraq

by Qiang Wang, Tao Wen, Bo Li, Jun Xin, Meng Tian and Baiyi Wu

Processes 2024, 12(10), 2135; https://doi.org/10.3390/pr12102135 - 1 Oct 2024

Viewed by 187

Abstract

The Ahdeb oil field is located in the southwestern part of the Zagros fold deformation zone. The study of the model of the formation of the oil reservoir in this field will be helpful to deepen the pattern of hydrocarbon distribution in this [...] Read more.

The Ahdeb oil field is located in the southwestern part of the Zagros fold deformation zone. The study of the model of the formation of the oil reservoir in this field will be helpful to deepen the pattern of hydrocarbon distribution in this zone. In this paper, we use the seismic data of the Ahdeb oil field to recover the tectonic evolution history of the field. Under neotectonic movement, the oil field formed in the early stage, migrated to the high point in the late stage, and finally entered the present formation. From here, for the oil-bearing inclusions within the reservoir, the photometric absorption values of the organic matter groups were measured by infrared spectroscopy. Their ratios were used to evaluate the maturity, thus discovering two phases of oil charging. Finally, using the hydrocarbon generation history and tectonic evolution history, combined with the oil and gas transportation periods in the reservoir, we deduce that the reservoir formation mode in the area is a two-phase gathering and final adjustment formation mode. This understanding of the hydrocarbon formation patterns will promote oil and gas exploration in this zone. Full article

(This article belongs to the Special Issue Theoretical Progress in the Exploration and Development of Deep Coal-Measure Gas)

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22 pages, 2057 KiB

Open AccessArticle

FDADNet: Detection of Surface Defects in Wood-Based Panels Based on Frequency Domain Transformation and Adaptive Dynamic Downsampling

by Hongli Li, Zhiqi Yi, Zhibin Wang, Ying Wang, Liang Ge, Wei Cao, Liye Mei, Wei Yang and Qin Sun

Processes 2024, 12(10), 2134; https://doi.org/10.3390/pr12102134 - 30 Sep 2024

Viewed by 266

Abstract

The detection of surface defects on wood-based panels plays a crucial role in product quality control. However, due to the complex background and low contrast of defects in wood-based panel images, features extracted by traditional deep learning methods based on spatial domain processing [...] Read more.

The detection of surface defects on wood-based panels plays a crucial role in product quality control. However, due to the complex background and low contrast of defects in wood-based panel images, features extracted by traditional deep learning methods based on spatial domain processing often contain noise and blurred boundaries, which severely affects detection performance. To address these issues, we have proposed a wood-based panel surface defect detection method based on frequency domain transformation and adaptive dynamic downsampling (FDADNet). Specifically, we designed a Multi-axis Frequency Domain Weighted Information Representation Module (MFDW), which effectively decoupled the indistinguishable low-contrast defects from the background in the transform domain. Gaussian filtering was then employed to eliminate noise and blur between the defects and the background. Additionally, to tackle the issue of scale differences in defects that led to difficulties in accurate capture, we designed an Adaptive Dynamic Convolution (ADConv) module for downsampling. This method flexibly compressed and enhanced features, effectively improving the differentiation of the features of objects of varying scales in the transform space, and ultimately achieved effective defect detection. To compensate for the lack of data, we constructed a dataset of wood-based panel surface defects, WBP-DET. The experimental results showed that the proposed FDADNet effectively improved the detection performance of wood-based panel surface defects in complex scenarios, achieving a solid balance between efficiency and accuracy. Full article

(This article belongs to the Special Issue Research on Intelligent Fault Diagnosis Based on Neural Network)

14 pages, 3446 KiB

Open AccessArticle

Intelligent Prediction of Rate of Penetration Using Mechanism-Data Fusion and Transfer Learning

by Zhe Huang, Lin Zhu, Chaochen Wang, Chengkai Zhang, Qihao Li, Yibo Jia and Linjie Wang

Processes 2024, 12(10), 2133; https://doi.org/10.3390/pr12102133 - 30 Sep 2024

Viewed by 237

Abstract

Rate of penetration (ROP) is crucial for evaluating drilling efficiency, with accurate prediction essential for enhancing performance and optimizing parameters. In practice, complex and variable downhole environments pose significant challenges for mechanistic ROP equations, resulting in prediction difficulties and low accuracy. Recently, data-driven [...] Read more.

Rate of penetration (ROP) is crucial for evaluating drilling efficiency, with accurate prediction essential for enhancing performance and optimizing parameters. In practice, complex and variable downhole environments pose significant challenges for mechanistic ROP equations, resulting in prediction difficulties and low accuracy. Recently, data-driven machine learning models have been widely applied to ROP prediction. However, these models often lack mechanistic constraints, limiting their performance to specific conditions and reducing their real-world applicability. Additionally, geological variability across wells further hinders the transferability of conventional intelligent models. Thus, combining mechanistic knowledge with intelligent models and enhancing model stability and transferability are key challenges in ROP prediction research. To address these challenges, this paper proposes a Mechanism-Data Fusion and Transfer Learning method to construct an intelligent prediction model for ROP, achieving accurate ROP predictions. A multilayer perceptron (MLP) was selected as the base model, and training was performed using data from neighboring wells and partial data from the target well. The Two-stage TrAdaBoost.R2 algorithm was employed to enhance model transferability. Additionally, drilling mechanistic knowledge was incorporated into the model’s loss function as a constraint to achieve a fusion of mechanistic knowledge and data-driven approaches. Using MAPE as the measure of accuracy, compared with conventional intelligent models, the proposed ROP prediction model improved prediction accuracy on the target well by 64.51%. The model transfer method proposed in this paper has a field test accuracy of 89.71% in an oilfield in China. These results demonstrate the effectiveness and feasibility of the proposed transfer learning method and mechanistic–data integration approach. Full article

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

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19 pages, 20016 KiB

Open AccessArticle

Effects of Aqueous Solubility and Geochemistry on CO₂ Storage in Offshore Basins

by Yanxin Lv, Xiaoyu Fang, Guifeng Wang, Shiguo Wu, Yi Xin, Haibo Li and Weiji Liu

Processes 2024, 12(10), 2132; https://doi.org/10.3390/pr12102132 - 30 Sep 2024

Viewed by 327

Abstract

The increasing global focus on carbon capture and storage (CCS) has highlighted the potential for offshore CO₂ sequestration, particularly following recent successes in onshore projects. This research investigates the qualitative analysis of carbon trapping efficiency in offshore basins, employing a GEM simulator [...] Read more.

The increasing global focus on carbon capture and storage (CCS) has highlighted the potential for offshore CO₂ sequestration, particularly following recent successes in onshore projects. This research investigates the qualitative analysis of carbon trapping efficiency in offshore basins, employing a GEM simulator to incorporate factors such as aqueous solubility and geochemistry. The findings reveal that anticlines represent ideal geological structures for carbon storage, effectively trapping a significant portion of injected CO₂. For effective mineralization, it is crucial to dissolve CO₂ into saline aquifers to generate H⁺, which facilitates the release of Ca²⁺ and Al³⁺ from anorthite. This process leads to the dissolution of anorthite and the precipitation of kaolinite, while calcite transitions from a dissolved state to a precipitated state over time. The analysis indicates that structural trapping provides the highest storage contribution during the injection phase, whereas residual gas trapping becomes dominant by the end of the simulation. Notably, it is observed that the storage contribution of structural trapping decreases from 28.39% to 19.05%, and the percentage increase in storage contributions of residual gas, solubility, ionic, and mineral trapping are 4.12%, 3.25%, 1.69%, and 0.28% for CO₂ plus water injection, thereby improving the long-term security of CO₂ storage in offshore basins. It is most beneficial to optimize the layout and design of the injection well to ensure a uniform distribution of carbon dioxide and to increase the injection rate. Full article

(This article belongs to the Section Energy Systems)

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12 pages, 1858 KiB

Open AccessArticle

Integrating Suspended Sludge and Fixed Film into a Biological Wastewater Treatment System to Enhance Nitrogen Removal

by Quang Chi Bui, Nguyen Nguyet Minh Phan, Trung Viet Nguyen, Chih-Chi Yang, Ku-Fan Chen and Yung-Pin Tsai

Processes 2024, 12(10), 2131; https://doi.org/10.3390/pr12102131 - 30 Sep 2024

Viewed by 304

Abstract

Integrated fixed-film activated sludge (IFAS) technology greatly enhances nitrogen removal effectiveness and treatment capacity in municipal wastewater treatment plants, addressing the issue of limited land availability. Hence, this method is appropriate for treating household wastewater from office buildings. The research was conducted at [...] Read more.

Integrated fixed-film activated sludge (IFAS) technology greatly enhances nitrogen removal effectiveness and treatment capacity in municipal wastewater treatment plants, addressing the issue of limited land availability. Hence, this method is appropriate for treating household wastewater from office buildings. The research was conducted at the wastewater treatment plant in an office building in Ho Chi Minh City, Vietnam. Experiments were conducted to ascertain the most favorable working conditions, including hydraulic retention time (HRT), alkalinity dosage, and dissolved oxygen (DO). According to the study, the IFAS system had the highest nitrogen removal effectiveness when operated at a hydraulic retention time (HRT) of 7 h, an alkalinity dose of 7.14 mgCaCO₃/mgN-NH₄⁺, and a dissolved oxygen (DO) value of 6 mg/L. The nitrification efficiency ranges from 89.2% to 98.8%. The N-NO₃⁻ concentration post-treatment is within the range of 27–45 mgN-NO₃⁻/L, which is lower than the allowable discharge limit of 60 mg/L as per Vietnam’s wastewater discharge requirements. The research findings have enhanced the efficiency of the office building management process, thereby promoting the sustainable growth of society. Full article

(This article belongs to the Section Environmental and Green Processes)

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16 pages, 13371 KiB

Open AccessArticle

Simulation Research and Practical Application of Cutting Teeth for Drill Bits in Life-Support Holes

by Zebin Zhu, Jian Feng, Yuguo Kang, Biao Zhang and Xue Ling

Processes 2024, 12(10), 2130; https://doi.org/10.3390/pr12102130 - 30 Sep 2024

Viewed by 262

Abstract

This study aims to achieve rapid drilling of life-support holes, regarding the optimization design of drill bits as the key, among which the simulation analysis of drill bit cutting teeth is an important technical means. Firstly, based on the rock mechanics test results [...] Read more.

This study aims to achieve rapid drilling of life-support holes, regarding the optimization design of drill bits as the key, among which the simulation analysis of drill bit cutting teeth is an important technical means. Firstly, based on the rock mechanics test results in the study area combined with the corresponding logging information, the analysis and evaluation of the geological conditions in the study area were completed, a complete rock mechanics characteristic profile was established, and the drillability of the rock was calculated to be relatively good. Then, a numerical simulation of parallel cutting of rock with conical teeth was established by experimentally testing rock mechanics parameters and using the discrete element method (PFC2D). The simulation study of the drill bit cutting teeth was completed by parameter calibration, analysis of rock cutting morphology, analysis of the number of rock cutting cracks, and analysis of the specific work of rock cutting and breaking. It was determined that the optimal rock-entering angle of the drill bit cutting teeth in the Shouyang mining area is 14°. Finally, verified by field practice, the optimized drill bit has stable performance, strong cutting ability, and good wear resistance; the maximum instantaneous mechanical drilling speed reaches 58.14 m/h, and it shows a slightly worn state after continuously drilling 582 m in the stratum, meeting the requirements of one-trip drilling and hole formation for life-support holes. This research provides a scientific basis and practical techniques for the construction of life-support holes in the Shouyang mining area and under similar geological conditions. It can provide more effective emergency plans and rescue strategies for possible mine disasters in the future, which is crucial for improving the technical system of emergency rescue for mine accidents and enhancing the emergency rescue capability of surface drilling. Full article

(This article belongs to the Special Issue Intelligent Safety Monitoring and Prevention Process in Coal Mines)

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13 pages, 1944 KiB

Open AccessArticle

A Convolutional Neural Network-Based Defect Recognition Method for Power Insulator

by Nan Li, Dejun Zeng, Yun Zhao, Jiahao Wang and Bo Wang

Processes 2024, 12(10), 2129; https://doi.org/10.3390/pr12102129 - 30 Sep 2024

Viewed by 229

Abstract

As the scale of the power grid rapidly expands, its operation becomes increasingly complex, with higher demands on personnel proficiency, grid stability, equipment safety, and operational efficiency. In this study, a novel power insulator defect detection method based on convolutional neural networks (CNNs) [...] Read more.

As the scale of the power grid rapidly expands, its operation becomes increasingly complex, with higher demands on personnel proficiency, grid stability, equipment safety, and operational efficiency. In this study, a novel power insulator defect detection method based on convolutional neural networks (CNNs) is proposed. This method innovatively combines the feature extraction advantages of deep learning to build an efficient binary classification model capable of accurately detecting defects in power insulators in complex backgrounds. To avoid the impact of a small dataset on model performance, transfer learning was employed during model training to enhance the model’s generalization ability. A combination of Grid Search and Random Search was used for hyperparameter tuning, and the Early Stopping strategy was introduced to effectively prevent the model from overfitting to the training set, ensuring generalization performance on the validation set. Experimental results show that the proposed method achieves an average accuracy of 98.6%, a recall of 96.8%, and an F1 score of 97.7% on the test set. Compared to traditional Faster RCNN and PCA-SVM methods, the proposed CNN model significantly improves detection accuracy and computational efficiency in complex backgrounds, exhibiting superior recognition precision and model generalization ability for efficiently and accurately identifying defective insulators. Full article

(This article belongs to the Special Issue Research on Intelligent Fault Diagnosis Based on Neural Network)

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19 pages, 3810 KiB

Open AccessArticle

Advanced Processes in Water Treatment: Synergistic Effects of Hydrodynamic Cavitation and Cold Plasma on Rhodamine B Dye Degradation

by Federico Verdini, Daniele Crudo, Valentina Bosco, Anna V. Kamler, Giancarlo Cravotto and Emanuela Calcio Gaudino

Processes 2024, 12(10), 2128; https://doi.org/10.3390/pr12102128 - 30 Sep 2024

Viewed by 296

Abstract

The increasing pollution of water bodies, due to the constant release of highly toxic and non-biodegradable organic pollutants, requires innovative solutions for environmental remediation and wastewater treatment. In this study, the effectiveness of different Advanced Oxidation Processes (AOPs) for the purification of water [...] Read more.

The increasing pollution of water bodies, due to the constant release of highly toxic and non-biodegradable organic pollutants, requires innovative solutions for environmental remediation and wastewater treatment. In this study, the effectiveness of different Advanced Oxidation Processes (AOPs) for the purification of water contaminated with Rhodamine B (RhB) dye at a concentration of 5 mg/L were investigated and compared. Using the classical ozonation strategy as a benchmark treatment, the research showed over 99% degradation of RhB within 4 min in a laboratory-scale batch setup with a capacity of 0.2 L. In contrast, a “chemical-free” process exploiting ultrasound (US) technology achieved a 72% degradation rate within 60 min. Further experiments were conducted using a pilot-scale rotor-stator hydrodynamic cavitation (HC) reactor on a 15 L solution leading to 33% of RhB removal in the presence of hydrogen peroxide (H₂O₂) at 75 mg/L. However, the use of an innovative cavitational reactor, which hybridizes HC with cold plasma, showed remarkable efficiency and achieved 97% degradation of RhB in just 5 min when treating a 5 L solution at an inlet pressure of 20 bar in a loop configuration. In addition, a degradation rate of 58% was observed in a flow-through configuration, emphasising the robustness and scalability of the HC/electrical discharge (ED) plasma technology. These results underline the potential of hybrid HC/ED plasma technology as an intensified and scalable process for the purification of water, as it offers a catalyst- and oxidant-free protocol. Full article

(This article belongs to the Special Issue Features, Reviews and Perspectives for the 10th Anniversary of Processes)

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16 pages, 2548 KiB

Open AccessArticle

Fault Diagnosis of Pumped Storage Units—A Novel Data-Model Hybrid-Driven Strategy

by Jie Bai, Chuanqiang Che, Xuan Liu, Lixin Wang, Zhiqiang He, Fucai Xie, Bingjie Dou, Haonan Guo, Ruida Ma and Hongbo Zou

Processes 2024, 12(10), 2127; https://doi.org/10.3390/pr12102127 - 30 Sep 2024

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Abstract

Pumped storage units serve as a crucial support for power systems to adapt to large-scale and high-proportion renewable energy sources by providing a stable and flexible energy supply. However, due to the coupling effects of electric power load demands and the complex multi-source [...] Read more.

Pumped storage units serve as a crucial support for power systems to adapt to large-scale and high-proportion renewable energy sources by providing a stable and flexible energy supply. However, due to the coupling effects of electric power load demands and the complex multi-source factors within the water–mechanical–electrical system, the interrelationship between unit parameters becomes more intricate, posing significant threats to the operational reliability and health status of the units. The complexity of fault diagnosis is further aggravated by the intricate and varied nature of fault characteristics, as well as the challenges in signal extraction under conditions of strong electromagnetic interference and high noise levels. To address these issues, this paper proposes a novel data-model hybrid-driven strategy that analyzes vibration signals to achieve rapid and accurate fault diagnosis of the units. Firstly, the spectral kurtosis theory is employed to enhance the traditional empirical mode decomposition, achieving optimal decomposition and noise reduction effects for vibration signals. Secondly, the intrinsic mode functions (IMFs) obtained from the decomposition are reconstructed, and the entropy values of effective IMFs are calculated as fault feature vectors. Subsequently, the CNN-LSTM model is utilized for fault diagnosis. The effectiveness and feasibility of the proposed method are verified through actual operational data from pumped storage units in a specific region. Through analysis, the fault diagnosis accuracy of the method proposed in this paper can be maintained above 95%, demonstrating robustness in complex engineering environments and effectively ensuring the safe and stable operation of pumped storage units. Full article

(This article belongs to the Section Process Control and Monitoring)

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17 pages, 2924 KiB

Open AccessArticle

A Fault Diagnosis Method for Pumped Storage Unit Stator Based on Improved STFT-SVDD Hybrid Algorithm

by Jie Bai, Xuan Liu, Bingjie Dou, Xiaohui Yang, Bo Chen, Yaowen Zhang, Jiayu Zhang, Zhenzhong Wang and Hongbo Zou

Processes 2024, 12(10), 2126; https://doi.org/10.3390/pr12102126 - 30 Sep 2024

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Abstract

Stator faults are one of the common issues in pumped storage generators, significantly impacting their performance and safety. To ensure the safe and stable operation of pumped storage generators, a stator fault diagnosis method based on an improved short-time Fourier transform (STFT)-support vector [...] Read more.

Stator faults are one of the common issues in pumped storage generators, significantly impacting their performance and safety. To ensure the safe and stable operation of pumped storage generators, a stator fault diagnosis method based on an improved short-time Fourier transform (STFT)-support vector data description (SVDD) hybrid algorithm is proposed. This method establishes a fault model for inter-turn short circuits in the stator windings of pumped storage generators and analyzes the electrical and magnetic states associated with such faults. Based on the three-phase current signals observed during an inter-turn short circuit fault in the stator windings, the three-phase currents are first converted into two-phase currents using the principle of equal magnetic potential. Then, the STFT is applied to transform the time-domain signals of the stator’s two-phase currents into frequency-domain signals, and the resulting fault current spectrum is input into the improved SVDD network for processing. This ultimately outputs the diagnosis result for inter-turn short circuit faults in the stator windings of the pumped storage generator. Experimental results demonstrate that this method can effectively distinguish between normal and faulty states in pumped storage generators, enabling the diagnosis of inter-turn short circuit faults in stator windings with low cross-entropy loss. Through analysis, under small data sample conditions, the accuracy of the proposed method in this paper can be improved by up to 7.2%. In the presence of strong noise interference, the fault diagnosis accuracy of the proposed method remains above 90%, and compared to conventional methods, the fault diagnosis accuracy can be improved by up to 6.9%. This demonstrates that the proposed method possesses excellent noise robustness and small sample learning ability, making it effective in complex, dynamic, and noisy environments. Full article

(This article belongs to the Section Process Control and Monitoring)

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12 pages, 3367 KiB

Open AccessArticle

Systematic Exploration of the Interactions between Pyrite and Coal from the View of Density Functional Theory

by Peng Xi, Fengling Sun, Xiaoyu Tang, Xiaoping Fan, An Lu, Kaifei Lu and Qiming Zhuo

Processes 2024, 12(10), 2125; https://doi.org/10.3390/pr12102125 - 29 Sep 2024

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Abstract

Coal is often adhered to by pyrite during slime flotation, causing an increase in the sulfur content of clean coal. In order to study the mechanism of pyrite adhesion to coal surfaces, different coal structural units were built and optimized, and the most [...] Read more.

Coal is often adhered to by pyrite during slime flotation, causing an increase in the sulfur content of clean coal. In order to study the mechanism of pyrite adhesion to coal surfaces, different coal structural units were built and optimized, and the most stable adsorption model of them on pyrite surfaces was determined. The mechanism of pyrite particles adhering to the surface of coal slurries was explored with the method of DFT. The results showed that the interaction mechanism between pyrite surface and Ph-OH and Ph-O-CH₃ was the result of a weak interaction between the H atom of Ph-OH and Ph-O-CH₃ and the S atom of the pyrite surface. The interaction mechanism between the pyrite surface and Ph-COOH and Ph-CO-CH₃ was both as a result of H-S interactions and weak Fe-O interactions. On the whole, there were weak interactions between pyrite particles and the coal slurry, and the pyrite particles can spontaneously adsorb on the surface of the coal slurry. Full article

(This article belongs to the Section Chemical Processes and Systems)

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17 pages, 6298 KiB

Open AccessArticle

Sealing Characteristics Analysis of New Subsea Wellhead Sealing Device

by Jing Li, Bo Ning, Dezhi Qiu, Fenlan Ou, Lantao Geng, Peng Xu and Beibei Kou

Processes 2024, 12(10), 2124; https://doi.org/10.3390/pr12102124 - 29 Sep 2024

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Abstract

Subsea wellhead systems are the crucial equipment for the development of oil and gas resources offshore, while the sealing device plays a vital role as the main component of the wellhead system. Once the seal fails, it is necessary to retrieve the original [...] Read more.

Subsea wellhead systems are the crucial equipment for the development of oil and gas resources offshore, while the sealing device plays a vital role as the main component of the wellhead system. Once the seal fails, it is necessary to retrieve the original wellhead system and either repair the sealing device or reinstall a new one. This will result in a delay in normal production and an increase in development costs. Therefore, a novel subsea wellhead sealing device is designed. A finite element analysis model is developed to study the underwater wellhead sealing mechanism regarding the equivalent stress and contact stress. The research results show that as the driving block gradually increases from 4 mm to 12 mm, the stress of the 12 convex parts on the sealing body also increases. The maximum equivalent stress reaches 3.5 times the yield limit, indicating that it has entered the yield stage and can achieve a more effective seal. The analysis of the contact stress of the sealing body reveals that the contact stress of the driving block increases, leading to plastic deformation of the sealing body while driving it to achieve a complete seal. In general, the finite element simulation results are consistent with the engineering practice. By analyzing the sealing characteristics, it can serve as the foundation for designing and providing theoretical support for the optimization of the metal-sealing structure. Full article

(This article belongs to the Topic Energy Extraction and Processing Science)

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13 pages, 19727 KiB

Open AccessArticle

Oolitic Sedimentary Characteristics of the Upper Paleozoic Bauxite Series in the Eastern Ordos Basin and Its Significance for Oil and Gas Reservoirs

by Fengyu Sun, Changling Qu, Gaoshe Cao, Liqin Xie, Xiaohu Shi, Shengtao Luo, Zhuang Liu, Ling Zhang, Xiaochen Ma, Xinhang Zhou, Sen Zhu and Zhenzhi Wang

Processes 2024, 12(10), 2123; https://doi.org/10.3390/pr12102123 - 29 Sep 2024

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Abstract

In recent years, great breakthroughs have been made in gas explorations of the Upper Paleozoic bauxite series in the Longdong area of the Ordos Basin, challenging the understanding that bauxite is not an effective reservoir. Moreover, studying the reservoir characteristics of bauxite is [...] Read more.

In recent years, great breakthroughs have been made in gas explorations of the Upper Paleozoic bauxite series in the Longdong area of the Ordos Basin, challenging the understanding that bauxite is not an effective reservoir. Moreover, studying the reservoir characteristics of bauxite is crucial for oil and gas exploration. Taking the bauxite series in the Longdong area as an example, this study systematically collects data from previous publications and analyzes the petrology, mineralogy, oolitic micro-morphology, chemical composition, and other sedimentary characteristics of the bauxite series in the study area using field outcrops, core observations, rock slices, cast slices, X-ray diffraction analysis, scanning electron microscopy and energy spectra, and so on. In this study, the oolitic microscopic characteristics of the bauxite reservoir and the significance of oil and gas reservoirs are described. The results show that the main minerals in the bauxite reservoir are boehmite and clay minerals composed of 73.5–96.5% boehmite, with an average of 90.82%. The rocks are mainly bauxitic mudstone and bauxite. A large number of oolites are observable in the bauxite series, and corrosion pores and intercrystalline pores about 8–20 μm in size have generally developed. These pores are important storage spaces in the reservoir. The brittleness index of the bauxite series was found to be as high as 99.3%, which is conducive to subsequent mining and fracturing. The main gas source rocks of oolitic bauxite rock and the Paleozoic gas series are the coal measure source rocks of the Upper Paleozoic. The oolitic bauxite reservoirs in the study area generally have obvious gas content, but the continuity of the planar distribution of the bauxite reservoirs is poor, providing a scientific basis for studying bauxite reservoirs and improving the exploratory effects of bauxite gas reservoirs. Full article

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

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17 pages, 5518 KiB

Open AccessArticle

Robustness and Scalability of Incomplete Virtual Pheromone Maps for Stigmergic Collective Exploration

by Kaloyan Dimitrov and Vladimir Hristov

Processes 2024, 12(10), 2122; https://doi.org/10.3390/pr12102122 - 29 Sep 2024

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Abstract

The Swarm Guiding and Communication System (SGCS) is a decision-making and information-sharing framework for robot swarms that only needs close-range peer-to-peer communication and no centralized control. Each robot makes decisions based on an incomplete virtual pheromone map that is updated on each interaction [...] Read more.

The Swarm Guiding and Communication System (SGCS) is a decision-making and information-sharing framework for robot swarms that only needs close-range peer-to-peer communication and no centralized control. Each robot makes decisions based on an incomplete virtual pheromone map that is updated on each interaction with another robot, imitating ant colonial behavior. Similar systems rely on continuous communication with no range limitations, environment modification, or centralized control. A computer simulation is developed to assess the effectiveness and robustness of the framework in covering an area. Consistency and the time needed for 99% coverage are compared with an unbiased random walk. The pheromone approach is shown to outperfom the unbiased one regardless of number of agents. Innate resilience to individual failures is also demonstrated. Full article

(This article belongs to the Special Issue Challenges and Advances of Process Control Systems)

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11 pages, 7824 KiB

Open AccessArticle

Extraction of Vanadium from High Phosphorus Vanadium Containing Waste Residue via Carbonation: Optimization Using Response Surface Methodology

by Zhigang Bai, Yimin Zhang, Nannan Xue, Qiushi Zheng and Zilin Dai

Processes 2024, 12(10), 2121; https://doi.org/10.3390/pr12102121 - 29 Sep 2024

Viewed by 228

Abstract

Vanadium (V) was successfully extracted from a high phosphorus vanadium residue (HPVR) through a carbonation process. Vanadium within HPVR substitutes for Fe in the mineral structure of Ca₉(Fe,V)(PO₄)₇ at elevated temperatures, Na₂CO₃ reacts with V [...] Read more.

Vanadium (V) was successfully extracted from a high phosphorus vanadium residue (HPVR) through a carbonation process. Vanadium within HPVR substitutes for Fe in the mineral structure of Ca₉(Fe,V)(PO₄)₇ at elevated temperatures, Na₂CO₃ reacts with V to form sodium metavanadate (NaVO₃), concurrently generating calcium carbonate (CaCO₃) through its interaction with Ca₉(Fe,V)(PO₄)₇. Subsequently, V is liberated and leached by water, dissolving in the aqueous phase as metavanadate ions (VO³⁻). Crucial factors influencing V leaching efficiency include roasting time, roasting temperature, and the amount of Na₂CO₃ utilized. Response Surface Methodology (RSM) was employed. The optimized parameters determined were as follows: a roasting temperature of 850 °C, a roasting duration of 120 min, a Na₂CO₃ dosage of 8.01%, a liquid-to-solid ratio (L/S) of 3, and a leaching time of 60 min. Under these conditions, a remarkable V leaching efficiency of 83.82% was achieved. This study underscores the viability of a simplified approach for treating solid waste containing metal slag, which not only mitigates environmental pollution but also yields valuable metals. Full article

(This article belongs to the Section Environmental and Green Processes)

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32 pages, 928 KiB

Open AccessReview

A Comprehensive Synthesis on Analytical Algorithms for Assessing Elastic Buckling Loads of Thin-Walled Isotropic and Laminated Cylindrical Shells

by Maria Tănase

Processes 2024, 12(10), 2120; https://doi.org/10.3390/pr12102120 - 29 Sep 2024

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Abstract

A comprehensive review is presented on the main analytical methods used in the specialized literature to evaluate the buckling loads of thin-walled cylindrical shells (TWCS) subjected to different mechanical loads or load combinations. The analytical formulations are first presented for unstiffened TWCS, followed [...] Read more.

A comprehensive review is presented on the main analytical methods used in the specialized literature to evaluate the buckling loads of thin-walled cylindrical shells (TWCS) subjected to different mechanical loads or load combinations. The analytical formulations are first presented for unstiffened TWCS, followed by stiffened TWCS in different configurations (stiffeners in the axial direction, circumferential direction or both axial and circumferential directions, placed on the external or internal surface of the shell). This research can serve as a helpful resource for researchers investigating this field, allowing the analytical methods to be used as a reference basis for numerical and experimental results regarding the behavior of structures in the category of TWCS. Full article

(This article belongs to the Special Issue Modeling and Simulation of Complex Networks for Automation in Systems Engineering)

6 pages, 5114 KiB

Open AccessCommunication

The Role of K₂CO₃ in the Synthesis of Dimethyl Carbonate from CO₂ and Methanol

by Yi Zhou, Mingzhe Chen, Congyi Wu, Xueling Dong and Dezhong Yang

Processes 2024, 12(10), 2119; https://doi.org/10.3390/pr12102119 - 29 Sep 2024

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Abstract

The synthesis of dimethyl carbonate (DMC) from methanol and CO₂ has also received widespread attention, and K₂CO₃ is usually used as a catalyst in the synthesis of DMC. In this work, the role of K₂CO₃ in [...] Read more.

The synthesis of dimethyl carbonate (DMC) from methanol and CO₂ has also received widespread attention, and K₂CO₃ is usually used as a catalyst in the synthesis of DMC. In this work, the role of K₂CO₃ in synthesizing dimethyl carbonate (DMC) from methanol and CO₂ was revisited. Interestingly, NMR results indicated that K₂CO₃ can react with methanol to form carbonate CH₃OCOO⁻, an essential intermediate in the synthesis of DMC, which can be transformed into DMC in the presence of CH₃I. In other words, K₂CO₃ can act as not only a catalyst but also a reactant to synthesize DMC from methanol and CO₂. Full article

(This article belongs to the Special Issue Research Progress in Carbon Dioxide Capture and Utilization Technology)

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16 pages, 9965 KiB

Open AccessArticle

Factors Influencing Radiation Sound Fields in Logging While Drilling Using an Acoustic Dipole Source

by Jingji Cao, Ruibao Qin, Xiongyan Li, Xinyu Ye, Chuang Hei, Zhongxu Yin and Peng Wang

Processes 2024, 12(10), 2118; https://doi.org/10.3390/pr12102118 - 29 Sep 2024

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Abstract

With the increasing number of complex well types in the development stage of oil and gas fields, it is becoming increasingly urgent to use remote detection logging while drilling (LWD) to explore the geological structures in a formation. In this paper, the feasibility [...] Read more.

With the increasing number of complex well types in the development stage of oil and gas fields, it is becoming increasingly urgent to use remote detection logging while drilling (LWD) to explore the geological structures in a formation. In this paper, the feasibility and reliability of the dipole remote detection of logging while drilling are demonstrated theoretically. For this purpose, we use an asymptotic solution of elastic wave far-field displacement to derive the calculation formula for the radiation pattern and energy flux of an LWD dipole source. The effects of influencing factors, including the source frequency, formation property, drill collar size, and mud parameter, on the radiation pattern and energy flux are analyzed. The results show that the horizontally polarized shear wave (SH-wave) has a greater advantage in imaging the reflector compared with the cases of the compressive wave (P-wave) and vertically polarized shear wave (SV-wave), which indicates the dominance of the SH-wave in dipole remote detection while drilling. The optimal source excitation frequency of 2.5 kHz and inner and outer radii of the drill collar of 0.02 and 0.1 m, respectively, should be considered in the design of an LWD dipole shear wave reflection tool. However, the heavy drilling mud is not conducive to remote detection during logging while drilling. In addition, the reflection of the SH-wave for the LWD condition is simulated. Under the conditions of optimal source frequency, drill collar size, and mud parameters, the reflection of the SH-wave signal is still detected under the fast formation. Full article

(This article belongs to the Special Issue Rock Physics, Well Logging, and Formation Evaluation in Energy Exploration Systems)

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33 pages, 9586 KiB

Open AccessArticle

Particle Dynamics Study on Influencing Factors of Ice Slurry Flow Characteristics in District Cooling Systems

by Di Yang and Wenpeng Hong

Processes 2024, 12(10), 2117; https://doi.org/10.3390/pr12102117 - 28 Sep 2024

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Abstract

In district cooling systems, substituting the conventional cooling medium with ice slurry represents an ideal approach to achieve economical operation. During pipeline transportation, ice slurry exhibits heterogeneous flow characteristics distinct from those of pure fluids. Consequently, investigating the flow field characteristics of non-homogeneous [...] Read more.

In district cooling systems, substituting the conventional cooling medium with ice slurry represents an ideal approach to achieve economical operation. During pipeline transportation, ice slurry exhibits heterogeneous flow characteristics distinct from those of pure fluids. Consequently, investigating the flow field characteristics of non-homogeneous ice slurry, quantitatively analyzing the rheological variations and flow resistance laws due to the uneven distribution of ice particles, and standardizing the comprehension and depiction of flow patterns within ice slurry pipes hold significant theoretical importance and practical value. This study analyzes the heterogeneous isothermal flow characteristics of ice slurry in a straight pipe by employing particle dynamics and the Euler–Euler dual-fluid model. Taking into account the impact of ice particles’ non-uniform distribution on the rheological properties of ice slurry, a particle concentration diffusion equation is incorporated to develop an isothermal flow resistance model for ice slurry. The flow behavior of ice slurry with initial average ice particle fractions (IPFs) ranging from 0% to 20% in DN20 horizontal straight and elbow pipes is examined. The findings reveal that the degree of heterogeneous flow in ice slurry is inversely proportional to the initial velocity and directly proportional to the initial concentration of ice particles. When the flow velocity is close to 0.5 m/s, the flow resistance of ice particles exhibits a linear positive correlation with changes in flow velocity, whereas the flow resistance of the fluid-carrying phase displays a linear negative correlation. As the flow rate increases to 1 m/s, the contribution of each phase to the total flow resistance becomes independent of the initial velocity parameter. Additionally, the drag fraction of the ice particle phase is positively associated with the initial concentration of ice particles. Furthermore, the phenomenon of “secondary flow” arises when ice slurry flows through an elbow, enhancing the mixing of ice particles with the carrier fluid. The extent of this mixing intensifies with a decrease in the turning radius and an increase in the initial velocity. Full article

(This article belongs to the Special Issue Model Predictive Control of Heating and Cooling Systems)

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17 pages, 11155 KiB

Open AccessArticle

Numerical Simulation and Response Surface Analysis of Esterification of Monobutyl Chlorophosphate with n-Butanol in a Microchannel Reactor

by Shang Gao, Jiahua Li, Xiang Qiu, Xiang Zheng, Miaomiao Jin, Yulu Liu and Haifang Mao

Processes 2024, 12(10), 2116; https://doi.org/10.3390/pr12102116 - 28 Sep 2024

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Abstract

Microreactors are essential for microchemical reactions owing to their high mass transfer efficiency, precise control of reaction time, easy amplification, and good safety performance. These characteristics provide several advantages, including shortened reaction times and enhanced chemical reaction conversion rates, rendering microreactors particularly significant [...] Read more.

Microreactors are essential for microchemical reactions owing to their high mass transfer efficiency, precise control of reaction time, easy amplification, and good safety performance. These characteristics provide several advantages, including shortened reaction times and enhanced chemical reaction conversion rates, rendering microreactors particularly significant in chemical production. In this study, a finite-rate model was developed for the esterification of monobutyl chlorophosphate (MCP) and n-butanol in a microchannel reactor. This study investigates the impact of the microchannel’s length-to-diameter ratio, the mass ratio of n-butanol to MCP at the inlet, and the inlet flow ratio on the entire reaction system through numerical simulations. The findings indicate that increasing the length-to-diameter ratio and reducing the inlet flow rate effectively prolongs the residence time of materials in the microreactor, thereby enhancing the conversion rate of the reactants. Optimal results are achieved with a moderate n-butanol/MCP mass ratio, which facilitates MCP transformation. Moreover, this study employs response surface analysis to investigate the influence of independent factors, such as the microchannel’s length-to-diameter ratio, component ratio, and inlet velocity ratio, on MCP conversion rates. A prediction formula with conversion rate as the dependent variable and microchannel length-to-diameter ratio, component ratio, and inlet velocity ratio as independent variables was established. Full article

(This article belongs to the Section Chemical Processes and Systems)

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25 pages, 2570 KiB

Open AccessReview

Application of Active Packaging Films for Extending the Shelf Life of Red Meats: A Review

by Cielo Estefanía Figueroa-Enríquez, Francisco Rodríguez-Félix, Saúl Ruiz-Cruz, Daniela Denisse Castro-Enriquez, Humberto Gonzalez-Rios, José Ángel Perez-Alvarez, José Agustín Tapia-Hernández, Tomás Jesús Madera-Santana, Eneida Azaret Montaño-Grijalva and Itzel Yanira López-Peña

Processes 2024, 12(10), 2115; https://doi.org/10.3390/pr12102115 - 28 Sep 2024

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Abstract

Meat is known for its high perishability and short shelf life if not properly packaged or stored. Packaging materials play a crucial role in preserving food quality, and there is a growing demand from consumers, industry professionals, and researchers for natural packaging materials [...] Read more.

Meat is known for its high perishability and short shelf life if not properly packaged or stored. Packaging materials play a crucial role in preserving food quality, and there is a growing demand from consumers, industry professionals, and researchers for natural packaging materials that incorporate health-beneficial extracts. Additionally, there is an increasing emphasis on avoiding non-biodegradable plastics in order to reduce environmental pollution. Currently used polymers in food packaging typically feature properties such as oxygen barriers, moisture resistance, and oxidation inhibition, helping to prevent undesirable aromas, flavors, and colors in food. Packaging not only serves as a container for transportation but also prevents physical damage, maintains quality, and ensures food safety. In the pursuit of more sustainable solutions, various compounds are being explored for food packaging, including those derived from proteins, lipids, waxes, and polysaccharides. These materials can be combined with bioactive compounds, such as natural plant extracts, which provide antioxidant, antimicrobial, anti-inflammatory, and anticancer benefits. Different techniques, such as electrohydrodynamic processes and casting methods, are employed in the preparation of these packaging materials. This review highlights the applications and properties of polymers used in meat packaging and promotes the use of biodegradable materials as a viable solution to reduce environmental pollution. Full article

(This article belongs to the Special Issue Feature Reviews in Food Processing Technologies: Present Innovations and Future Opportunities)

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13 pages, 526 KiB

Open AccessArticle

The Effects of Different Cooking Systems on Changes in the Bioactive Compounds, Polyphenol Profiles, Biogenic Elements, and Protein Contents of Cauliflower Florets

by Isam A. Mohamed Ahmed, Fahad Y. Al-Juhaimi, Mehmet Musa Özcan, Nurhan Uslu and Emad Karrar

Processes 2024, 12(10), 2114; https://doi.org/10.3390/pr12102114 - 28 Sep 2024

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Abstract

In the current study, we examined the effects of boiling cauliflower in a pressure cooker, conventional boiling, conventional heating, and microwave heating on the chemical components, total phenol, flavonoids, antioxidant capacity (DPPH test), phenolic compounds, and mineral contents of cauliflower florets to reveal [...] Read more.

In the current study, we examined the effects of boiling cauliflower in a pressure cooker, conventional boiling, conventional heating, and microwave heating on the chemical components, total phenol, flavonoids, antioxidant capacity (DPPH test), phenolic compounds, and mineral contents of cauliflower florets to reveal the differences between these cooking methods. Cauliflower is generally consumed either boiled or cooked in dry heat. In this study, different boiling and dry heat cooking methods were tried to reveal the changes in phytochemical composition and protein and mineral contents of cauliflower florets. Depending on the cooking methods of the cauliflower florets, the total phenolic and flavonoid contents of the cauliflower florets were determined to be between 273.72 (conventional heating) and 731.01 mg GAE/100 g (microwave heating) and 142.02 (conventional heating) and 797.10 mg/100 g (conventional boiling), respectively. The antioxidant capacity results of cauliflowers were found to be between 8.30 (conventional heating) and 33.69 mmol/kg (fresh). Statistically significant differences were detected in the moisture, total phenol, total flavonoid, and antioxidant activity values of cauliflower depending on the cooking techniques applied (p < 0.05). The gallic acid and 3,4-dihydroxybenzoic acid values of fresh and cooked cauliflowers were identified to be between 10.93 (microwave heating) and 194.79 mg/100 g (boiling in pressure cooker) and 17.58 (conventional heating) and 145.80 mg/100 g (boiling in pressure cooker), respectively. In general, the lowest amounts of phenolic compounds were defined in cauliflower samples boiled with a conventional heating system, followed by cauliflower samples cooked with the microwave heating method. Considering the component amounts as a result of cooking, the highest phenolic component amounts were specified in the cauliflower sample cooked by boiling in a pressure cooker. The protein quantities of fresh and cooked cauliflowers were determined to be between 16.11 (fresh) and 19.79% (microwave heating). The K and S contents of fresh cauliflowers and cauliflowers cooked with different blanching methods were specified to be between 19,647.62 (conventional boiling) and 35,130.01 mg/kg (conventional heating) and 3196.54 (boiling in pressure cooker) and 5105.65 mg/kg (microwave heating), respectively. The K, Mg, S, Fe, Cu, Mn, and Zn results of cauliflowers cooked in an oven and microwave were higher than those cooked using the control and boiling methods. Full article

(This article belongs to the Section Food Process Engineering)

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