Journal Description
Processes
Processes
is an international, peer-reviewed, open access journal on processes/systems in chemistry, biology, material, energy, environment, food, pharmaceutical, manufacturing, automation control, catalysis, separation, particle and allied engineering fields published monthly online by MDPI. The Systems and Control Division of the Canadian Society for Chemical Engineering (CSChE S&C Division) and the Brazilian Association of Chemical Engineering (ABEQ) are affiliated with Processes and their members receive discounts on the article processing charges. Please visit Society Collaborations for more details.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), Ei Compendex, Inspec, AGRIS, and other databases.
- Journal Rank: JCR - Q2 (Engineering, Chemical) / CiteScore - Q2 (Chemical Engineering (miscellaneous))
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 13.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.5 (2022);
5-Year Impact Factor:
3.4 (2022)
Latest Articles
Screening of Metal Reduction Potential for Thermochemical Hydrogen Storage
Processes 2024, 12(5), 1004; https://doi.org/10.3390/pr12051004 (registering DOI) - 15 May 2024
Abstract
The screening of all non-radioactive metals without lanthanides for thermochemical hydrogen storage was performed based on physical chemistry calculations. The thermodynamic data were collected from the NIST (National Institute of Standards and Technology) public data repository, which was followed by calculations regarding the
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The screening of all non-radioactive metals without lanthanides for thermochemical hydrogen storage was performed based on physical chemistry calculations. The thermodynamic data were collected from the NIST (National Institute of Standards and Technology) public data repository, which was followed by calculations regarding the change in enthalpy, entropy, Gibbs free energy and equilibrium reaction temperature. The results were critically evaluated based on thermodynamic parameters, viable metals were identified, and their hydrogen storage densities and energy–enthalpy ratios were evaluated. The elements viable for controlled thermochemical hydrogen storage via the reversible reduction and oxidation of metal oxides and metals are manganese (Mn), iron (Fe), molybdenum (Mo) and tungsten (W). Manganese has the largest theoretical potential for hydrogen storage with reversible reduction and oxidation of metal oxides and metals. The second candidate is iron, while the other two (Mo and W) have much lower potential. More research efforts should be dedicated to experimental testing of the identified metals (Mn, Fe, Mo and W) and their different oxides for thermochemical hydrogen storage capabilities both on laboratory and pilot scales. Ferromanganese alloy(s) might also prove itself as an efficient and affordable thermochemical hydrogen storage material. Our theoretical investigation expanded the knowledge on thermochemical hydrogen storage and is accompanied with a brief literature review revealing the lack of experimental studies, especially on oxidation of metals with water vapor occurring during the hydrogen release phase of the cycle. Consequently, accurate modelling of transport, kinetics and other phenomena during hydrogen storage and release is scarce.
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(This article belongs to the Section Materials Processes)
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Open AccessCorrection
Correction: AL-Aoh, H.A. Removal of the Pigment Congo Red from Synthetic Wastewater with a Novel and Inexpensive Adsorbent Generated from Powdered Foeniculum Vulgare Seeds. Processes 2023, 11, 446
by
Hatem A. AL-Aoh
Processes 2024, 12(5), 1003; https://doi.org/10.3390/pr12051003 (registering DOI) - 15 May 2024
Abstract
In the original publication [...]
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Open AccessArticle
A Study on the Mechanism of Fracture Initiation and Propagation under Multi-Perforation Conditions in Hydraulic Fracturing
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Dongwei Ding, Wei Xiong, Wei Guo, Haiqing Yu and Keyuan Wang
Processes 2024, 12(5), 1002; https://doi.org/10.3390/pr12051002 (registering DOI) - 15 May 2024
Abstract
To reveal the mechanism of hydraulic fracture initiation and propagation under the conditions of multiple perforations during horizontal well fracturing, we creatively conducted dual-hole fracturing experiments on small rock samples and established a two-dimensional model of a single cluster with multiple perforations in
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To reveal the mechanism of hydraulic fracture initiation and propagation under the conditions of multiple perforations during horizontal well fracturing, we creatively conducted dual-hole fracturing experiments on small rock samples and established a two-dimensional model of a single cluster with multiple perforations in a horizontal well based on the extended finite element method using the fluid–solid coupling equation, which was combined with the basic theory of damage mechanics. The biggest difference from previous research is that this model does not consider the hypothesis of stress shadows and only focuses on studying the initiation and propagation of multiple perforations in one cluster. We studied the effects of perforation parameters, stress state, and injection flow rate on the initiation and propagation of hydraulic fractures using this model. The experimental and simulation results indicate that under multi-perforation conditions, the number of fractures depends on the number of perforations. The simulation results show that when the spacing between perforations increases or the number of perforations reduces, the initiation time of perforation is advanced and the interference between fractures weakens, which is conducive to the initiation and propagation of hydraulic fractures. As the stress difference increases, the initiation time of perforation becomes earlier and the deflection angle of the outermost fractures becomes smaller, which is conducive to the parallel expansion of the fractures. Moreover, although this has little impact on the morphology of fractures with the rise in flow rate in simulation, it is beneficial for improving the initiation and propagation speed of fractures. The length of fractures also increases significantly at the same time point. In addition, both the experiments and simulations revealed that an increase in the flow rate could accelerate the initiation time of fractures. The proposed model can guide fracturing construction to optimize the design of perforation spacing during horizontal well fracturing, which can contribute to reducing development costs and improving the final production.
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(This article belongs to the Special Issue Advances in Gas Adsorption and Porosity for Enhanced Recovery of Shale Gas)
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Comparative Review on the Production and Purification of Bioethanol from Biomass: A Focus on Corn
by
Jean Claude Assaf, Zeinab Mortada, Sid-Ahmed Rezzoug, Zoulikha Maache-Rezzoug, Espérance Debs and Nicolas Louka
Processes 2024, 12(5), 1001; https://doi.org/10.3390/pr12051001 (registering DOI) - 15 May 2024
Abstract
In the contemporary era, conventional energy sources like oil, coal, and natural gas overwhelmingly contribute 89.6% to global CO2 emissions, intensifying environmental challenges. Recognizing the urgency of addressing climate concerns, a pivotal shift towards renewable energy, encompassing solar, wind, and biofuels, is
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In the contemporary era, conventional energy sources like oil, coal, and natural gas overwhelmingly contribute 89.6% to global CO2 emissions, intensifying environmental challenges. Recognizing the urgency of addressing climate concerns, a pivotal shift towards renewable energy, encompassing solar, wind, and biofuels, is crucial for bolstering environmental sustainability. Bioethanol, a globally predominant biofuel, offers a versatile solution, replacing gasoline or integrating into gasoline–ethanol blends while serving as a fundamental building block for various valuable compounds. This review investigates the dynamic landscape of biomass generations, drawing insightful comparisons between the first, second, third, and fourth generations. Amid the drive for sustainability, the deliberate focus on the initial generation of biomass, particularly corn, in bioethanol production is grounded in the current dependence on edible crops. The established utilization of first-generation biomass, exemplified by corn, underscores the necessity for a comprehensive examination of its advantages and challenges, allowing for a nuanced exploration of existing infrastructure and practices. To produce bioethanol from corn feedstock, various milling methods can be employed. Thus, this paper delves into a comparative assessment of dry-milling and wet-milling processes scrutinizing their efficiency, environmental impact, and economic feasibility.
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(This article belongs to the Section Environmental and Green Processes)
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Open AccessArticle
Simulation of Key Influencing Factors of Hydraulic Fracturing Fracture Propagation in a Shale Reservoir Based on the Displacement Discontinuity Method (DDM)
by
Pengcheng Ma and Shanfa Tang
Processes 2024, 12(5), 1000; https://doi.org/10.3390/pr12051000 (registering DOI) - 15 May 2024
Abstract
In the process of the large-scale hydraulic fracturing of a shale gas field in the Weiyuan area of Sichuan province, the quantitative description and evaluation of hydraulic fracture expansion morphology and the three-dimensional distribution law are the key points of evaluation of block
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In the process of the large-scale hydraulic fracturing of a shale gas field in the Weiyuan area of Sichuan province, the quantitative description and evaluation of hydraulic fracture expansion morphology and the three-dimensional distribution law are the key points of evaluation of block fracturing transformation effect. Many scholars have used the finite element method, discrete element method, grid-free method and other numerical simulation methods to quantitatively characterize hydraulic fractures, but there are often the problems that the indoor physical simulation results are much different from the actual results and the accuracy of most quantitative studies is poor. Considering rock mechanics parameters and based on the displacement discontinuity method (DDM), a single-stage multi-cluster fracture propagation model of horizontal well was established. The effects of Young’s modulus, Poisson’s ratio, the in situ stress difference, the approximation angle, the perforation cluster number and the perforation spacing on the formation of complex fracture networks and on the geometrical parameters of hydraulic fractures were simulated. The research results can provide theoretical reference and practical guidance for the optimization of large-scale fracturing parameters and the quantitative post-fracturing evaluation of horizontal wells in unconventional reservoirs such as shale gas reservoirs.
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(This article belongs to the Special Issue Recent Advances in Hydrocarbon Production Processes from Geoenergy)
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Open AccessArticle
Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing
by
Chandra Mouli R. Madhuranthakam, Farzad Hourfar and Ali Elkamel
Processes 2024, 12(5), 999; https://doi.org/10.3390/pr12050999 (registering DOI) - 15 May 2024
Abstract
The transition from batch to continuous production in the catalytic hydrogenation of nitrile butadiene rubber (NBR) into hydrogenated NBR (HNBR) marks a significant advance for applications under demanding conditions. This study introduces a continuous process utilizing a static mixer (SM) reactor, which notably
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The transition from batch to continuous production in the catalytic hydrogenation of nitrile butadiene rubber (NBR) into hydrogenated NBR (HNBR) marks a significant advance for applications under demanding conditions. This study introduces a continuous process utilizing a static mixer (SM) reactor, which notably achieves a hydrogenation conversion rate exceeding 97%. We thoroughly review a mechanistic model of the SM reactor to elucidate the internal dynamics governing the hydrogenation process and address the inherent uncertainties in key parameters such as the Peclet number (Pe), dimensionless time (θτ), reaction coefficient (R), and flow rate coefficient (q). A comprehensive dataset generated from varied parameter values serves as the basis for training an artificial neural network (ANN), which is then compared against traditional models including linear regression, decision tree, and random forest in terms of efficacy. Our results clearly demonstrate the ANN’s superiority in predicting the degree of hydrogenation, achieving the lowest root mean squared error (RMSE) of 3.69 compared to 21.90 for linear regression, 4.94 for decision tree, and 7.51 for random forest. The ANN’s robust capability for modeling complex nonlinear relationships and dynamics significantly enhances decision-making, planning, and optimization of the reactor, reducing computational demands and operational costs. In other words, this approach allows users to rely on a single ML-based model instead of multiple mechanistic models for reflecting the effects of possible uncertainties. Additionally, a feature importance study validates the critical impact of time and element number on the hydrogenation process, further supporting the ANN’s predictive accuracy. These findings underscore the potential of ML-based models in streamlining and enhancing the efficiency of chemical production processes.
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(This article belongs to the Section Materials Processes)
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A Li-Ion Battery State of Charge Estimation Strategy Based on the Suboptimal Multiple Fading Factor Extended Kalman Filter Algorithm
by
Weibin Wu, Jinbin Zeng, Qifei Jian, Luxin Tang, Junwei Hou, Chongyang Han, Qian Song and Yuanqiang Luo
Processes 2024, 12(5), 998; https://doi.org/10.3390/pr12050998 (registering DOI) - 14 May 2024
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The state of charge (SOC) is an important indicator for evaluating a battery management system (BMS), which is crucial for the reliability, performance, and life management of a battery. In this paper, the characteristics of a Li-ion battery are deeply studied to explore
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The state of charge (SOC) is an important indicator for evaluating a battery management system (BMS), which is crucial for the reliability, performance, and life management of a battery. In this paper, the characteristics of a Li-ion battery are deeply studied to explore the charge/discharge curve under different environments. Meanwhile, a second-order RC equivalent circuit model is constructed. The function identification of the EMF and SOC is performed based on the least squares method. The model estimation error is verified by simulation to be less than 0.05 V. Based on the Suboptimal Multiple Fading Factor Extended Kalman Filter (SMFEKF) algorithm, the SOC under constant current and UDDS conditions are estimated. Matlab/simulink simulations illustrate that the estimated accuracy of the proposed algorithm is improved by 79.36% compared with the EKF algorithm. Finally, the validity of the algorithm is verified jointly with the BMS. The results show that the estimation error is within 4% in both constant current condition as well as UDDS conditions, and it can still be predicted quickly and accurately under the uncertainty in the initial value of the SOC.
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Open AccessFeature PaperArticle
Co-Product of Pracaxi Seeds: Quantification of Epicatechin by HPLC-DAD and Microencapsulation of the Extract by Spray Drying
by
Raimundo Lopes da Silva, Lindalva Maria de Meneses Costa Ferreira, José Otávio Carréra Silva-Júnior, Attilio Converti and Roseane Maria Ribeiro-Costa
Processes 2024, 12(5), 997; https://doi.org/10.3390/pr12050997 (registering DOI) - 14 May 2024
Abstract
In the industrial processing of fruits, co-products are generated, which are often not used. The pracaxi co-product, obtained by cold pressing its seeds, contains phenolic compounds with antioxidant activity, which in this work were extracted and microencapsulated by spray drying. The pracaxi extract
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In the industrial processing of fruits, co-products are generated, which are often not used. The pracaxi co-product, obtained by cold pressing its seeds, contains phenolic compounds with antioxidant activity, which in this work were extracted and microencapsulated by spray drying. The pracaxi extract was characterized by Fourier-transform infrared spectroscopy (FTIR) and high-performance liquid chromatography (HPLC-DAD), and its antioxidant activity was quantified by the ABTS and DPPH assays. Total polyphenol and flavonoid contents in the extract and microparticles were determined by UV-Vis spectrophotometry. Microparticles were then characterized regarding their moisture content, morphology (by scanning electron microscopy), size, polydispersity index and zeta potential. The FTIR spectra revealed functional groups that may be related to phenolic compounds. The extract showed good antioxidant activity according to both selected assays, while the HPLC-DAD analysis evidenced epicatechin as the main compound, whose content was quantified and validated according to the guidelines of recognized national and international agencies. The total polyphenol contents were 20.61 ± 0.20 mg gallic acid equivalent (GAE)/g in the extract and 18.48 ± 0.10 mg GAE/g in the microparticles, while the total flavonoid contents were 28.29 ± 0.70 mg quercetin equivalent (QE)/g and 13.73 ± 0.10 mg QE/g, respectively. Microparticles had a low moisture content, spherical shape, size less than 1 μm and negative zeta potential. Furthermore, they were able to satisfactorily retain phenolic compounds, although in a smaller amount compared to the extract due to small losses resulting from degradation during the drying process. These results, taken as a whole, demonstrate that the pracaxi co-product can be a promising candidate in obtaining products of interest for the cosmetic and food sectors by aiming to exploit its antioxidant activity.
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(This article belongs to the Special Issue Solid and Hazardous Waste Disposal and Resource Utilization)
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Assessment of Heavy Metal Contamination and Ecological Risk in Soil within the Zheng–Bian–Luo Urban Agglomeration
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Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong, Fanbo Li and Sujun Xie
Processes 2024, 12(5), 996; https://doi.org/10.3390/pr12050996 (registering DOI) - 14 May 2024
Abstract
As urbanization accelerates, the contamination of urban soil and the consequent health implications stemming from urban expansion are increasingly salient. In recent years, a plethora of cities and regions nationwide have embarked on rigorous soil geological surveys with a focus on environmental quality,
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As urbanization accelerates, the contamination of urban soil and the consequent health implications stemming from urban expansion are increasingly salient. In recent years, a plethora of cities and regions nationwide have embarked on rigorous soil geological surveys with a focus on environmental quality, yielding invaluable foundational data. This research aims to develop scientifically robust and rational land-use planning strategies while assessing the levels of heavy metal pollution and associated risks. The urban agglomeration encompassing Zhengzhou, Luoyang, and Kaifeng (referred to as Zheng–Bian–Luo Urban Agglomeration) in Henan Province was designated as the study area. Leveraging the Nemerow comprehensive index method alongside the Hakanson potential ecological risk assessment method, this study delved into the pollution levels and potential ecological ramifications of nine heavy metals, namely Cr, Mn, Ni, Cu, Zn, As, Cd, Pb, and Co. Research indicates that the hierarchy of individual potential ecological risks ranges from most to least significant as follows: Cd > Pb > Cr > Ni > Cu > Zn > As > Mn > Co. The concentrations of Cd in both Zhengzhou and Kaifeng surpassed the established background levels. Furthermore, the mean single-factor pollution index values for the heavy metals Cd and Zn exceeded 1, signifying a state of minor pollution. The Nemerow comprehensive index P of Cd and Zn is between 1 < Pcomp ≤ 2, which is considered mild pollution. The comprehensive P values of the other seven metal elements are all less than 0.7, reaching a clean (alert) level. Predominantly, the primary potential risk factor in the superficial soil of the Zheng–Bian–Luo urban agglomeration is Cd, while the ecological risk implications associated with other heavy metal elements are comparatively minimal. The soil environmental quality within the designated study area remains secure, although certain localized areas pose potential risks of heavy metal pollution. A comprehensive assessment of the current state of soil heavy metal pollution is essential to establish a theoretical foundation and provide technical support for soil environmental protection, pollution mitigation, and sustainable utilization.
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(This article belongs to the Special Issue Solid and Hazardous Waste Disposal and Resource Utilization)
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Constructing a Skeletal Iso-Propanol–Butanol–Ethanol (IBE)–Diesel Mechanism Using the Decoupling Method
by
Yi Ma, Shaomin Zhao, Junhong Zhao, Jun Fu and Wenhua Yuan
Processes 2024, 12(5), 995; https://doi.org/10.3390/pr12050995 (registering DOI) - 14 May 2024
Abstract
In recent years, biofuels have gained considerable prominence in response to growing concerns about resource scarcity and environmental pollution. Previous investigations have revealed that the appropriate blending of iso-propanol–butanol–ethanol (IBE) into diesel significantly improves both the c combustion efficiency and emission performance of
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In recent years, biofuels have gained considerable prominence in response to growing concerns about resource scarcity and environmental pollution. Previous investigations have revealed that the appropriate blending of iso-propanol–butanol–ethanol (IBE) into diesel significantly improves both the c combustion efficiency and emission performance of internal combustion engines (ICEs). However, the combustion mechanism of IBE–diesel for the numerical studies of engines has not reached maturity. In this study, a skeletal IBE–diesel multi-component mechanism, comprising 157 species and 603 reactions, was constructed using the decoupling method. It was formulated by amalgamating the reduced fuel-related sub-mechanisms derived from diesel surrogates (n-dodecane, iso-cetane, iso-octane, toluene, and decalin) and n-butanol, along with the detailed core sub-mechanisms of C1, C2, C3, CO, and H2. The constructed mechanism is capable of better matching the physical and chemical properties of actual diesel fuel. Extensive validation, including ignition delay, laminar flame speed, a premixed flame species profile, and engine experimental data, confirms the reliability of the mechanism in engine numerical studies. Subsequent investigations reveal that as the IBE blend ratio and EGR rate increase, the ignition delay exhibits an increase, while the combustion duration experiences a decrease. Blending IBE into diesel, along with a specific EGR rate, proves effective in simultaneously reducing NOx and soot emissions.
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(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System, 2nd Edition)
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Plasma Processing of Rubber Powder from End-of-Life Tires: Numerical Analysis and Experiment
by
Vladimir Messerle and Alexandr Ustimenko
Processes 2024, 12(5), 994; https://doi.org/10.3390/pr12050994 (registering DOI) - 13 May 2024
Abstract
Tire recycling is becoming an increasingly important problem due to the growing number of end-of-life tires (ELTs). World-wide, ELTs account for more than 80 million tons. ELTs contribute to environmental pollution in the long term. They are flammable, toxic and non-biodegradable. At the
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Tire recycling is becoming an increasingly important problem due to the growing number of end-of-life tires (ELTs). World-wide, ELTs account for more than 80 million tons. ELTs contribute to environmental pollution in the long term. They are flammable, toxic and non-biodegradable. At the same time, ELTs contain rubber, metal and textile cord, which are valuable raw materials. ELTs are buried in landfills, burned, crushed and restored. Most of these methods have a negative impact on the environment. From an environmental point of view, the most preferred ways to recycle tires are retreading and shredding. Rubber powder (RP) or crumb is mainly used for rubber pavers production, waterproofing, curbs, road slabs and various surfaces. An alternative method for RP processing, eliminating the disadvantages of the above approaches, is plasma gasification and pyrolysis. The paper presents a thermodynamic and kinetic analysis and an experiment on plasma processing of RP from worn tires to produce flammable gas. At a mass-average temperature of 1750 K, the yield of synthesis gas from plasma-air gasification of RP was 44.6% (hydrogen—19.1, carbon monoxide—25.5), and 95.6% of carbon was gasified. The experimental and calculated results satisfactorily agreed. It was found that plasma products from RP did not contain harmful impurities, either in calculations or experiments. Plasma gasification allows for recycling ELTs in an environmentally friendly way while also generating flammable gases that are valuable commodities. In this research, plasma technology was demonstrated to be effective for gasifying RP to produce flammable gas.
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(This article belongs to the Section Chemical Processes and Systems)
Open AccessArticle
Estimating the Lifetime of Rotary Dryer Flights Based on Experimental Data
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Marius Gabriel Petrescu, Andrei Burlacu, Gheorghe Dan Isbășoiu, Teodor Dumitru and Maria Tănase
Processes 2024, 12(5), 993; https://doi.org/10.3390/pr12050993 (registering DOI) - 13 May 2024
Abstract
The studies carried out address an important problem for the concrete and asphalt industry, referring to the wear phenomena that affect the elements (flights) of rotary dryers used to dry mineral aggregates. In this article, the authors propose a lifetime estimation method for
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The studies carried out address an important problem for the concrete and asphalt industry, referring to the wear phenomena that affect the elements (flights) of rotary dryers used to dry mineral aggregates. In this article, the authors propose a lifetime estimation method for rotary dryer flights. In order to benefit from greater credibility, the proposed method was applied based on the experimental results obtained, by the authors, in the laboratory, on a stand that reproduces a portion of the real equipment. Starting from these results, the authors identified the mathematical functions used to model the failure rates (wear) of the flights by referring to characteristic quantities for wear evaluation: mass loss of material; reduction in the thickness of the part; surface affected by wear. The experimental data—the input data for the proposed algorithm—correspond to six steels used in industrial applications. The wear phenomenon was modeled considering both the situation of uniform wear and the situation of differentiated wear on the flight surface. Therefore, the steel type with the highest service life values could be identified, namely, steel grades E and G. The method proposed in this paper can be extended to any category of material or part provided that the failure rate function is identified beforehand, possibly based on a laboratory experiment.
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(This article belongs to the Section Process Control and Monitoring)
Open AccessFeature PaperArticle
NADES-Based Extracts of Selected Medicinal Herbs as Promising Formulations for Cosmetic Usage
by
Djurdja Ivkovic, Ilija Cvijetic, Aleksandra Radoicic, Jelena Stojkovic-Filipovic, Jelena Trifkovic, Maja Krstic Ristivojevic and Petar Ristivojevic
Processes 2024, 12(5), 992; https://doi.org/10.3390/pr12050992 (registering DOI) - 13 May 2024
Abstract
As a functional extraction medium, natural deep eutectic solvents (NADESs) can dissolve various plant metabolites. Those solvents provide untapped potential for creating novel green extracts with distinctive phytochemical signatures and unique biological activities. This is particularly relevant given the rising need for eco-friendly
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As a functional extraction medium, natural deep eutectic solvents (NADESs) can dissolve various plant metabolites. Those solvents provide untapped potential for creating novel green extracts with distinctive phytochemical signatures and unique biological activities. This is particularly relevant given the rising need for eco-friendly and sustainable skin care products. The main aim of this work was to optimize the most efficient natural deep eutectic solvents (NADESs) for extracting bioactives from 18 medicinal herbs applicable to the cosmetic industry. Selection of the most potent herbs involved assessing their conventional extracts for tyrosinase inhibition, antioxidant activity, and keratinocyte cytotoxicity. Moreover, we analyzed the phenolic profile using ultra-high-pressure liquid chromatography/mass spectrometry (UHPLC/MS) and spectrophotometric assays such as total phenolic (TPC) and flavonoid content (TFC). Using the COSMO-RS method, we modeled the solubility of 12 phenolics in 64 virtual NADESs and selected the 7 most promising ones for further experimental validation. NADESs, including betaine-urea, betaine-proline, and betaine-lysine, were computationally chosen and demonstrated the highest levels of TPC and antioxidative capacity, as confirmed by in vitro assays. The proposed combination of NADES herbal extracts represents a promising natural constituent for the cosmetic industry.
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(This article belongs to the Special Issue Recent Advances in Processing Technologies for Substance Extraction, Separation, and Enrichment)
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Machine Learning Algorithms That Emulate Controllers Based on Particle Swarm Optimization—An Application to a Photobioreactor for Algal Growth
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Viorel Mînzu, Iulian Arama and Eugen Rusu
Processes 2024, 12(5), 991; https://doi.org/10.3390/pr12050991 (registering DOI) - 13 May 2024
Abstract
Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations of the PM, there is a big computational effort that
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Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations of the PM, there is a big computational effort that leads to a large controller execution time. The main motivation of this work is to decrease the computational effort and, consequently, the controller execution time. This paper proposes to replace the PSO predictor with a machine learning model that has “learned” the quasi-optimal behavior of the couple (PSO and PM); the training data are obtained through closed-loop simulations over the control horizon. The new controller should preserve the process’s quasi-optimal control. In identical conditions, the process evolutions must also be quasi-optimal. The multiple linear regression and the regression neural networks were considered the predicting models. This paper first proposes algorithms for collecting and aggregating data sets for the learning process. Algorithms for constructing the machine learning models and implementing the controllers and closed-loop simulations are also proposed. The simulations prove that the two machine learning predictors have learned the PSO predictor’s behavior, such that the process evolves almost identically. The resulting controllers’ execution time have decreased hundreds of times while keeping their optimality; the performance index has even slightly increased.
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(This article belongs to the Special Issue Industrial Process Operation State Sensing and Performance Optimization)
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Open AccessArticle
Enhancing Low-Fat Probiotic Yogurt: The Role of Xanthan Gum in Functionality and Microbiological Quality
by
Khalid A. Alsaleem and Mahmoud E. A. Hamouda
Processes 2024, 12(5), 990; https://doi.org/10.3390/pr12050990 (registering DOI) - 13 May 2024
Abstract
The objective of this study was to determine the effect of XG addition on low-fat yogurt (LFY) properties. Pasteurized skimmed buffalo milk (SBM) was heated to 95 ± 2 °C for 16 s, cooled to 40 ± 1 °C, and then divided into
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The objective of this study was to determine the effect of XG addition on low-fat yogurt (LFY) properties. Pasteurized skimmed buffalo milk (SBM) was heated to 95 ± 2 °C for 16 s, cooled to 40 ± 1 °C, and then divided into six treatment lots. The treatments included the following: T1 (control), T2 (0.2% XG), T3 (0.4% XG), T4 (0.6% XG), T5 (0.8% XG), and T6 (1% XG). A proportion of 2% of a mixed starter culture from Streptococcus thermophilus (ST), Lactobacillus bulgaricus (LB), and Bifidobacterium bifidum (BB) in the ratio 1:1:1 was added. Yogurt was manufactured following the standard manufacturing protocol. Chemical composition and texture were determined at fresh time, while water-holding capacity (WHC), viscosity, and syneresis % were determined at 0, 7, 14, and 21 days of storage. Total bacterial counts (TBC), lactobacilli, streptococci, and bifidobacteria counts were determined at 0, 7, 14, and 21 days of storage. Sensory analysis was performed immediately upon the cooling stage (time zero) and then after 14 and 21 days of storage. The experiment was performed in trice. The results obtained showed that the addition of XG in LFY significantly (p < 0.05) decreases the pH, total protein (TP), and ash, and significantly (p < 0.05) increased the total solids (TS). Additionally, the addition of XG led to a significant (p < 0.05) increase in hardness, WHC, and viscosity; however, syneresis significantly (p < 0.05) decreased. The addition of higher amounts of XG led to a significant (p < 0.05) decrease in the TBC and led to a significant (p < 0.05) increase in counts of ST, LB, and BB during the first two weeks of the storage period. Sensory evaluation revealed that increasing the XG concentration up to 0.8% increased the product’s acceptability among panelists; however, further increasing the concentration to 1% had a detrimental impact on its acceptability. To conclude, this study showed that XG can be used as a stabilizer in the manufacturing of LFY as well as a prebiotic for starter culture and improve the quality of LFY.
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(This article belongs to the Special Issue Microbial Cultures in Food Production)
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Physico-Chemical Aspects of Metal–Fulvic Complexation
by
Martina Klučáková, Jitka Krouská and Michal Kalina
Processes 2024, 12(5), 989; https://doi.org/10.3390/pr12050989 (registering DOI) - 13 May 2024
Abstract
The interactions of metal ions with fulvic acids were investigated from the point of view of the thermodynamic aspects of complexation as well as the size and charge of the formed complexes. Thermodynamic aspects were studied by means of isothermal titration calorimetry. Particle
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The interactions of metal ions with fulvic acids were investigated from the point of view of the thermodynamic aspects of complexation as well as the size and charge of the formed complexes. Thermodynamic aspects were studied by means of isothermal titration calorimetry. Particle size distribution was determined by the method of dynamic light scattering and charge by the measurement of zeta potential. Complexation resulted in changes in particle size and charge. The particle size distribution was trimodal for fulvic acids and bimodal for fulvic complexes with calcium and magnesium, while copper–fulvic complexes had only one size fraction. The compensation of the negative charge of carboxylic and phenolic functional groups by positively charged metal ions resulted in an increase in zeta potential which became closer to zero in the case of copper–fulvic complexes. However, all metal–humic complexes behaved as colloidally unstable, which resulted in visually observable sedimentation. Calorimetric measurements provided positive values for changes in enthalpy, which indicated endothermic processes. In contrast, quantum chemical calculations as well as experiments with model compounds provided negative values indicating exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive.
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(This article belongs to the Section Particle Processes)
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Open AccessArticle
Optimization of the Assessment Method for Photovoltaic Module Enhancers: A Cost-Efficient Economic Approach Developed through Modified Area and Cost Factor
by
Sakhr M. Sultan, Tso Chih Ping, Khan Sobayel, Mohammad Z. Abdullah and Kamaruzzaman Sopian
Processes 2024, 12(5), 988; https://doi.org/10.3390/pr12050988 (registering DOI) - 13 May 2024
Abstract
The advancement of photovoltaic module (PV) enhancer technology shows significant promise due to its rapid growth. Nevertheless, there remains a requirement for ongoing research to refine the evaluation techniques for this technology. In a prior investigation, the concept of the area and cost-effectiveness
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The advancement of photovoltaic module (PV) enhancer technology shows significant promise due to its rapid growth. Nevertheless, there remains a requirement for ongoing research to refine the evaluation techniques for this technology. In a prior investigation, the concept of the area and cost-effectiveness factor, denoted as , was introduced to analyze the economic impact of enhancing the PV through techniques such as reflectors or coolers. This metric relates the surface area and manufacturing expenses of a PV enhancer to its capacity for improving the PV output power, aiding in the comparison of different enhancer types. However, this assessment approach is costly, requiring a set of PVs without enhancers to be compared with an equal number of modules fitted with enhancers. This paper introduces a modified version of this metric, termed the modified area and cost-effectiveness factor ( ), along with its minimum value ( ), with the aim of reducing the assessment expenses associated with PV enhancers. This modification hinges on knowing the output power from a single solar cell without an enhancer, as well as from a PV with an enhancer containing a known number of solar cells. Additionally, it relies on data regarding the manufacturing cost of the PV enhancer, the cost of one watt of PV power, and the combined surface area of the PV and its enhancer. The equations for computing the total number of solar cells and the associated costs in addition to the expenses cost are also proposed for and . The results of the present study using show that there is a proportional relationship between the percentage of solar cell saving and the number of solar cells. As the solar cells increase, the percentage of solar sell saving increases. The findings reveal that utilizing leads to a 48.33% increase in the proportion of solar cells saved compared to the existing method. It can be concluded that the proposed method is cost-efficient and holds promise for adoption by PV enhancer designers and manufacturers.
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(This article belongs to the Special Issue Computational Energy Optimization Processes during Nanofluid Flows with Emphasis on Applications)
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Sustainability Assessment of 2G Bioethanol Production from Residual Lignocellulosic Biomass
by
Bárbara Correia, Henrique A. Matos, Tiago F. Lopes, Susana Marques and Francisco Gírio
Processes 2024, 12(5), 987; https://doi.org/10.3390/pr12050987 (registering DOI) - 13 May 2024
Abstract
The development of sustainable biofuels can help to reduce the reliance on fossil fuels and mitigate the impact of climate change. This study analyzes bioethanol production from agro-forestry residual biomass, namely eucalyptus residues and corn stover. The study includes process simulation using Aspen
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The development of sustainable biofuels can help to reduce the reliance on fossil fuels and mitigate the impact of climate change. This study analyzes bioethanol production from agro-forestry residual biomass, namely eucalyptus residues and corn stover. The study includes process simulation using Aspen Plus software, followed by economic analysis and life cycle assessment (LCA) with the help of SimaPro software and by applying the environmental footprint (EF) 3.0 method. The economic analysis on the biorefinery’s economic viability, equipment, and production costs reveals a positive decision for bioethanol production from eucalyptus residues due to logistical and transportation costs. The minimum ethanol selling price (MESP) obtained was 2.19 €/L and 2.45 €/L for eucalyptus residues and corn stover, respectively. From the LCA with a functional unit of 1 MJ of ethanol, bioethanol production from eucalyptus residues results in a single score impact of 37.86 µPt, whereas for corn stover, it is 33.47 µPt. In the climate change impact category, the eucalyptus residues scenario has an impact of 0.264 kg CO2 eq/MJ ethanol while corn stover leads to 0.254 kg CO2 eq/MJ ethanol. In-situ enzyme production, heat integration, and the use of renewable energy sources were also analyzed. Combining in situ enzyme production with renewable energy sources lowers CO2 equivalent emissions by 89% for both feedstocks, in comparison to the base-case scenario.
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(This article belongs to the Special Issue Biorefinery and Thermochemical Conversion as Solutions for the Industrial Use of Agro-Industrial Residues)
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A Robust Process Identification Method under Deterministic Disturbance
by
Youngjin Yook, Syng Chul Chu, Chang Gyu Im, Su Whan Sung and Kyung Hwan Ryu
Processes 2024, 12(5), 986; https://doi.org/10.3390/pr12050986 (registering DOI) - 12 May 2024
Abstract
This study introduces a novel process identification method aimed at overcoming the challenge of accurately estimating process models when faced with deterministic disturbances, a common limitation in conventional identification methods. The proposed method tackles the difficult modeling problems due to deterministic disturbances by
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This study introduces a novel process identification method aimed at overcoming the challenge of accurately estimating process models when faced with deterministic disturbances, a common limitation in conventional identification methods. The proposed method tackles the difficult modeling problems due to deterministic disturbances by representing the disturbances as a linear combination of Laguerre polynomials and applies an integral transform with frequency weighting to estimate the process model in a numerically robust and stable manner. By utilizing a least squares approach for parameter estimation, it sidesteps the complexities inherent in iterative optimization processes, thereby ensuring heightened accuracy and robustness from a numerical analysis perspective. Comprehensive simulation results across various process types demonstrate the superior capability of the proposed method in accurately estimating the model parameters, even in the presence of significant deterministic disturbances. Moreover, it shows promising results in providing a reasonably accurate disturbance model despite structural disparities between the actual disturbance and the model. By improving the precision of process models under deterministic disturbances, the proposed method paves the way for developing refined and reliable control strategies, aligning with the evolving demands of modern industries and laying solid groundwork for future research aimed at broadening application across diverse industrial practices.
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(This article belongs to the Section Process Control and Monitoring)
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Fault Diagnosis of Wind Turbine Gearbox Using Vibration Scatter Plot and Visual Geometric Group Network
by
Meng-Hui Wang, Chun-Chun Hung, Shiue-Der Lu, Fu-Hao Chen, Yu-Xian Su and Cheng-Chien Kuo
Processes 2024, 12(5), 985; https://doi.org/10.3390/pr12050985 (registering DOI) - 12 May 2024
Abstract
This study aims to develop a fault detection system designed specifically for wind turbine gearboxes. It proposes a hybrid fault diagnosis algorithm that combines scatter plot analysis with the visual geometric group (VGG) technique to identify various fault types, including gear rust, chipping,
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This study aims to develop a fault detection system designed specifically for wind turbine gearboxes. It proposes a hybrid fault diagnosis algorithm that combines scatter plot analysis with the visual geometric group (VGG) technique to identify various fault types, including gear rust, chipping, wear, and aging. To capture vibration signals, a three-axis vibration sensor was integrated with a NI-9234 DAQ card. Digital signal processing techniques were employed to actively filter out noise from the captured signals. Gaussian white noise was incorporated into the training data to enhance the noise resistance of the network model, which was then utilized for scatter plot generation. The VGG technique was subsequently applied to identify faults. The testing data were collected at two different speeds, with 1500 samples taken at each speed, totaling 3000 samples. For both training and testing, 400 samples of each fault type were employed for training, while 200 samples were allocated for testing. The test results demonstrated an overall identification accuracy of 97.7% for both the no-fault gearbox and the four-fault states, underscoring the effectiveness of the proposed methodology.
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(This article belongs to the Section Automation Control Systems)
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