Processes

34 pages, 10872 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Modeling of Multiphase Flow, Superheat Dissipation, Particle Transport, and Capture in a Vertical and Bending Continuous Caster

by Mingyi Liang, Seong-Mook Cho, Xiaoming Ruan and Brian G. Thomas

Processes 2022, 10(7), 1429; https://doi.org/10.3390/pr10071429 - 21 Jul 2022

Cited by 4 | Viewed by 1907

Abstract

A new model of particle entrapment during continuous casting of steel is presented, which includes the effects of multiphase flow from argon gas injection and thermal buoyancy from superheat in the strand. The model simulates three different capture mechanisms, including capture by solidified [...] Read more.

A new model of particle entrapment during continuous casting of steel is presented, which includes the effects of multiphase flow from argon gas injection and thermal buoyancy from superheat in the strand. The model simulates three different capture mechanisms, including capture by solidified hooks at the meniscus, entrapment between dendrites, and engulfment by the surrounding of large particles. The fluid flow and bubble capture results are validated with plant measurements, including nail board dipping tests and ultrasonic tests, respectively, and good agreement is seen. Results suggest that the superheat has a negligible effect on the flow in the mold region. However, higher (30 K) superheat causes a more complex flow in the lower strand by creating multiple recirculation zones due to the thermal buoyancy effects. This causes less penetration deep into the strand, which leads to fewer and shallower particle captures. Lower (10 K) superheat may enable significant top surface freezing, leading to very large internal defect clusters. Lower superheat also leads to deeper meniscus hooks, which sometimes (0.003%) capture large (1 mm) bubbles. Capture bands occur near the transition line from vertical to curved, due to the downward fluid velocity balancing the particle terminal velocity, enabling capture in the relative stagnation region beneath the longitudinal recirculation zone. These findings agree with plant observations. Full article

(This article belongs to the Special Issue High-Efficiency and High-Quality Continuous Casting Processes)

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9 pages, 1646 KiB

Open AccessArticle

Purification and Characterization of a Novel Factor of Crotoxin Inter-CRO (V-1), a New Phospholipase A₂ Isoform from Crotalus durissus collilineatus Snake Venom Using an In Vitro Neuromuscular Preparation

by Corina Vera-Gonzales, Carlos Alberto Arenas-Chávez, Luis A. Ponce-Soto, Aldo Alvarez-Risco, Shyla Del-Aguila-Arcentales, Neal M. Davies and Jaime A. Yáñez

Processes 2022, 10(7), 1428; https://doi.org/10.3390/pr10071428 - 21 Jul 2022

Cited by 1 | Viewed by 1517

Abstract

The fractionation of Crotalus durissus collilineatus whole venom through an HPLC chromatographic method enabled the purification of a new V-1 neurotoxin. Inter-CRO (V-1) presents similarity in its primary structure to crotoxin B (CB), suggesting another isoform of this toxin. The aim of this [...] Read more.

The fractionation of Crotalus durissus collilineatus whole venom through an HPLC chromatographic method enabled the purification of a new V-1 neurotoxin. Inter-CRO (V-1) presents similarity in its primary structure to crotoxin B (CB), suggesting another isoform of this toxin. The aim of this study was to compare V-1 to the crotoxin complex (CA/CB) and CB to elucidate aspects related to its functionality. The homogeneity of the purified protein was confirmed with a molecular mass of 1425.45 Da, further verified by mass spectrometry. The sequence of the protein showed high similarity to other viperid snake venom PLA₂ proteins. The results of this study report that V-1 is an uncharacterized novel toxin with different biological activities from CB. V-1 maintained catalytic activity but presented neurotoxic activity as observed by the 2.5-fold increase in twitch tension record compared to control values on isolated muscle cells. Full article

(This article belongs to the Section Pharmaceutical Processes)

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15 pages, 2982 KiB

Open AccessArticle

An Intelligent Gender Classification System in the Era of Pandemic Chaos with Veiled Faces

by Jawad Rasheed, Sadaf Waziry, Shtwai Alsubai and Adnan M. Abu-Mahfouz

Processes 2022, 10(7), 1427; https://doi.org/10.3390/pr10071427 - 21 Jul 2022

Cited by 11 | Viewed by 2369

Abstract

In the world of chaos, the pandemic has driven individuals around the globe to wear face masks for preventing the virus’s transmission, however, this has made it difficult to determine the gender of the person wearing a mask. Gender information is part of [...] Read more.

In the world of chaos, the pandemic has driven individuals around the globe to wear face masks for preventing the virus’s transmission, however, this has made it difficult to determine the gender of the person wearing a mask. Gender information is part of soft biometrics, which provides extra information about a person’s identification, thus, identifying a gender based on a veiled face is among the urgent challenges that must be advocated for in the next decade. Therefore, this study exploited various pre-trained deep learning networks (DenseNet121, DenseNet169, ResNet50, ResNet101, Xception, InceptionV3, MobileNetV2, EfficientNetB0, and VGG16) to analyze the effect of the mask while identifying the gender using facial images of human beings. The study comprises two strategies. First, the experimental part involves the training of models using facial images with and without masks, while the second strategy considers images with masks only, to train the pre-trained models. Experimental results reveal that DenseNet121 and Xception networks performed well for both strategies. Besides this, the Inception network outperformed all others by attaining 98.75% accuracy for the first strategy, whereas EfficientNetB0 performed well for the second strategy by securing 97.27%. Moreover, results suggest that facemasks evidently impact the performance of state-of-the-art pre-trained networks for gender classification. Full article

(This article belongs to the Special Issue Recent Advances in Machine Learning and Applications)

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20 pages, 7804 KiB

Open AccessArticle

A Bearing Fault Diagnosis Method Based on Spectrum Map Information Fusion and Convolutional Neural Network

by Baiyang Wang, Guifang Feng, Dongyue Huo and Yuyun Kang

Processes 2022, 10(7), 1426; https://doi.org/10.3390/pr10071426 - 21 Jul 2022

Cited by 10 | Viewed by 1875

Abstract

With the development of information technology, it has become increasingly important to use intelligent algorithms to diagnose mechanical equipment faults based on vibration signals of rolling bearings. However, with the application of high-performance sensors in the Internet of Things, the complexity of real-time [...] Read more.

With the development of information technology, it has become increasingly important to use intelligent algorithms to diagnose mechanical equipment faults based on vibration signals of rolling bearings. However, with the application of high-performance sensors in the Internet of Things, the complexity of real-time classification of multichannel, multidimensional sensor signals is increasing. In view of the need for intelligent methods for fault diagnosis methods of mechanical equipment, the generalization ability of fault diagnosis models also needs to be further strengthened. In this context, in order to make fault diagnosis intelligent and efficient, a bearing fault diagnosis method based on spectrum map information fusion and convolutional neural network (CNN) is proposed. First, short-time Fourier transform (STFT) is used to analyze the multichannel vibration signal of the rolling bearing and obtain the frequency domain information of the signal over a period of time. Second, the information fusion is converted into two-dimensional (2D) images, which are input into CNN for training, and the bearing fault identification model is obtained. Next, the frequency domain information of each signal is converted into a 2D spectrum map, which is used as a CNN training dataset to train a bearing fault identification model. Finally, the diagnostic model is validated using the existing datasets. The results show that the accuracy of fault diagnosis using the proposed bearing is greater than 99.4% and can even reach 100%. The proposed method considerably reduces the workload of the diagnosis process, with strong robustness and generalization ability. Full article

(This article belongs to the Special Issue Predictive Maintenance for Manufacturing System)

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3 pages, 189 KiB

Open AccessEditorial

Introduction to the Special Issue “Extraction and Fractionation Processes of Functional Components in Food Engineering”

by Blanca Hernández-Ledesma, Roberta Claro da Silva and Juliana Maria Leite Nobrega De Moura Bell

Processes 2022, 10(7), 1425; https://doi.org/10.3390/pr10071425 - 21 Jul 2022

Viewed by 1077

Abstract

Diet plays an unquestionable role in the growth, development, and maintenance of all body functions [...] Full article

(This article belongs to the Special Issue Extraction and Fractionation Processes of Functional Components in Food Engineering)

24 pages, 13622 KiB

Open AccessArticle

Mechanical and Microstructural Properties of Composite Mortars with Lime, Silica Fume and Rice Husk Ash

by Ramalingam Malathy, Ragav Shanmugam, Ill-Min Chung, Seung-Hyun Kim and Mayakrishnan Prabakaran

Processes 2022, 10(7), 1424; https://doi.org/10.3390/pr10071424 - 21 Jul 2022

Cited by 15 | Viewed by 2382

Abstract

A mixture of hydraulic lime and pozzolanic material can be used as a binder in making concrete and mortar for energy-efficient construction purposes. Generally, lime possesses lower strength and higher setting time. By introducing pozzolans in the lime mortar, their cementitious properties could [...] Read more.

A mixture of hydraulic lime and pozzolanic material can be used as a binder in making concrete and mortar for energy-efficient construction purposes. Generally, lime possesses lower strength and higher setting time. By introducing pozzolans in the lime mortar, their cementitious properties could be increased and could compete with the cement mortars. The use of pozzolan-lime binder in mortar reduces the utilisation of cement, and hence reduces the environmental problem originating from cement production. This study mainly deals with the mechanical and microstructural properties of lime and lime composite mortars made up of hydraulic lime, silica fume and rice husk ash. Three composite mortars were made with the following combination such as hydraulic lime-silica fume (LSF), hydraulic lime-rice husk ash (LRA) and hydraulic lime-silica fume-rice husk ash (LSR). Further, their properties were compared with the pure lime mortar. Preliminary investigations were made on the lime reactivity and pozzolanic reactivity tests. It was understood that silica fumes have a (15%) better reactivity than rice husk ash. The introduction of pozzolans in the lime mortar promotes fresh, hardened and microstructural properties. The 28 days’ compressive strength of lime composite mortars achieved more than 16 Mpa, while the lime mortar attained 4 Mpa. The combined effect of pozzolanic reaction, hydration and carbonation in the lime composite mortars achieved four times the strength of lime mortar at 28 days. A high peak of calcium carbonate was detected in lime mortar as a result of carbonation. The well-developed microstructure of calcium silicate hydrate and calcium hydroxide exhibits the formation of hydration products in the lime composite mortars as observed from a scanning electron microscope (SEM), energy-dispersive X-ray (EDX) and X-ray diffraction (XRD). Similar graphs of Fourier transform infrared spectroscopy (FT-IR) showed the presence of equivalent functional elements in all lime composite mortars. Full article

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18 pages, 2705 KiB

Open AccessArticle

Influence of Varying Compression Ratio of a Compression Ignition Engine Fueled with B20 Blends of Sea Mango Biodiesel

by R Rohith Renish, Amala Justus Selvam, Robert Čep and Muniyandy Elangovan

Processes 2022, 10(7), 1423; https://doi.org/10.3390/pr10071423 - 21 Jul 2022

Cited by 3 | Viewed by 1920

Abstract

The ever-worsening environmental situation brought on by the huge use of fossil fuels has ramped up biodiesel production. Several studies have shown that a 20% biodiesel-diesel blend (B20) could be the best for utility in a compression ignition (CI) engine. The present study [...] Read more.

The ever-worsening environmental situation brought on by the huge use of fossil fuels has ramped up biodiesel production. Several studies have shown that a 20% biodiesel-diesel blend (B20) could be the best for utility in a compression ignition (CI) engine. The present study focuses on the characteristics of a variable compression ratio (VCR) engine running with a B20 blend of sea mango biodiesel at compression ratios of 16:1, 17:1 and 18:1. VCR is a technology which permits the engine to modify its compression ratio to improve the fuel economy under varying loads. The experimental results reveal an improvement of 5.27% and 6.25% in the BTE as well as SFC with B20 mix, respectively, at compression ratio (CR) 18:1 against diesel at standard CR, which is 17:1. At CR 18:1, the CO, HC and smoke emissions of B20 fuel at full load were 26.78%, 37.76% and 23.44%, correspondingly lower than those of diesel at standard CR. However, the blend was found to have higher NO_x emissions at all the CRs. The least NO_x emissions of the blend were noted to be at CR 16:1, although it was 0.77% higher than diesel at standard CR. The combustion characteristics also improved at higher CRs. The findings of this study indicate that the B20 blend of sea mango biodiesel could be utilized at CR 18:1 to replace diesel without any engine modifications. Full article

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16 pages, 3826 KiB

Open AccessEditor’s ChoiceArticle

Inline Weld Depth Evaluation and Control Based on OCT Keyhole Depth Measurement and Fuzzy Control

by Maximilian Schmoeller, Tony Weiss, Korbinian Goetz, Christian Stadter, Christian Bernauer and Michael F. Zaeh

Processes 2022, 10(7), 1422; https://doi.org/10.3390/pr10071422 - 21 Jul 2022

Cited by 5 | Viewed by 1847

Abstract

In an industrial joining process, exemplified by deep penetration laser beam welding, ensuring a high quality of welds requires a great effort. The quality cannot be fully established by testing, but can only be produced. The fundamental requirements for a high weld seam [...] Read more.

In an industrial joining process, exemplified by deep penetration laser beam welding, ensuring a high quality of welds requires a great effort. The quality cannot be fully established by testing, but can only be produced. The fundamental requirements for a high weld seam quality in laser beam welding are therefore already laid in the process, which makes the use of control systems essential in fully automated production. With the aid of process monitoring systems that can supply data inline to a production process, the foundation is laid for the efficient and cycle-time-neutral control of welding processes. In particular, if novel, direct measurement methods, such as Optical Coherence Tomography, are used for the acquisition of direct geometric quantities, e.g., the weld penetration depth, a significant control potential can be exploited. In this work, an inline weld depth control system based on an OCT keyhole depth measurement is presented. The system is capable of automatically executing an inline control of the deep penetration welding process based only on a specified target weld depth. The performance of the control system was demonstrated on various aluminum alloys and for different penetration depths. In addition, the ability of the control to respond to unforeseen external disturbances was tested. Within the scope of this work, it was thus possible to provide an outlook on future developments in the field of laser welding technology, which could develop in the direction of an intuitive manufacturing process. This objective should be accomplished through the use of intelligent algorithms and innovative measurement technology—following the example of laser beam cutting, where the processing systems themselves have been provided with the ability to select suitable process parameters for several years now. Full article

(This article belongs to the Special Issue Manufacturing Industry 4.0: Trends and Perspectives)

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20 pages, 4351 KiB

Open AccessArticle

Determination of Gas Extraction Borehole Parameters in Fractured Zone on ‘Borehole in Place of Roadway’ Based on RSM-GRA-GA

by Zhenghan Qin, Haisheng Shen, Yong Yuan, Zhixiong Gong, Zhongshun Chen and Yongqi Xia

Processes 2022, 10(7), 1421; https://doi.org/10.3390/pr10071421 - 21 Jul 2022

Cited by 2 | Viewed by 1244

Abstract

Large-diameter gas extraction borehole is considered an effective method by which to realize coal mine methane exploitation and outburst prevention. Efficient gas extraction can be achieved by selecting the right borehole parameters. In this paper, by comparing several conventional objective weighting methods, the [...] Read more.

Large-diameter gas extraction borehole is considered an effective method by which to realize coal mine methane exploitation and outburst prevention. Efficient gas extraction can be achieved by selecting the right borehole parameters. In this paper, by comparing several conventional objective weighting methods, the PCA was used to assign the weights to the research indices, the optimization objective was reduced from multi-dimensional to one-dimensional with the help of the gray correlation analysis. The study of gas extraction effect under different borehole parameters based on the response surface model. Numerical simulations were used to analyze the mixed volume of gas extraction, the pure volume of extraction and the concentration in the upper corner after extraction under different schemes. Finally, a genetic algorithm degree model was used to solve the solution and determine the optimal arrangement of borehole parameters. The study shows that (1) the weight shares of borehole stratum, borehole diameter and borehole spacing were 0.385, 0.285 and 0.33, respectively, in the reduced dimensional analysis of the PCA. (2) Using the results of improved gray correlation analysis as a comprehensive evaluation value to measure the effect of gas extraction, the optimal range of the model was 28–30 m borehole level, 190–210 mm borehole diameter and 5.5–6.5 m borehole spacing. (3) Using the genetic algorithm to solve the model, we obtained the borehole layer 28.79 m, borehole diameter 199.89 mm, borehole spacing 5.76 m. The borehole gas extraction effect was good under this parameter. The extraction mixed volume was 129.8 m³/min, the extraction pure volume was 9.16 m³/min, the upper corner concentration was 0.52%, and the prediction accuracy of the model was 97.8%. Full article

(This article belongs to the Special Issue Fracking and Permeability Enhancement in Fractured Rock Masses for Underground Mining)

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15 pages, 2179 KiB

Open AccessArticle

Virtual Screening of Drug Proteins Based on the Prediction Classification Model of Imbalanced Data Mining

by Lili Yin, Xiaokang Du, Chao Ma and Hengwen Gu

Processes 2022, 10(7), 1420; https://doi.org/10.3390/pr10071420 - 21 Jul 2022

Cited by 2 | Viewed by 1354

Abstract

We propose a virtual screening method based on imbalanced data mining in this paper, which combines virtual screening techniques with imbalanced data classification methods to improve the traditional virtual screening process. First, in the actual virtual screening process, we apply k-means and smote [...] Read more.

We propose a virtual screening method based on imbalanced data mining in this paper, which combines virtual screening techniques with imbalanced data classification methods to improve the traditional virtual screening process. First, in the actual virtual screening process, we apply k-means and smote heuristic oversampling method to deal with imbalanced data. Meanwhile, to enhance the accuracy of the virtual screening process, a particle swarm optimization algorithm is introduced to optimize the parameters of the support vector machine classifier, and the concept of ensemble learning is brought in. The classification technique based on particle swarm optimization, support vector machine and adaptive boosting is used to screen the molecular docking conformation to improve the accuracy of the prediction. Finally, in the experimental construction and analysis section, the proposed method was validated using relevant data from the protein data bank database and PubChem database. The experimental results indicated that the proposed method can effectively improve the accuracy of virus screening and has practical guidance for new drug development. This research regards virtual screening as a problem of imbalanced data classification, which has obvious guiding significance and also provides a certain reference for the problems faced by virtual screening technology. Full article

(This article belongs to the Special Issue Systematic Design, Testing and Development of In Vitro Diagnostic Instruments)

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18 pages, 1399 KiB

Open AccessArticle

Factor Model for Online Education during the COVID-19 Pandemic Using the IoT

by Faheem Khan, Ilhan Tarimer and Whangbo Taekeun

Processes 2022, 10(7), 1419; https://doi.org/10.3390/pr10071419 - 21 Jul 2022

Cited by 7 | Viewed by 2019

Abstract

Coronavirus disease (COVID-19) has spread quickly around the globe. COVID-19 has affected the education sector due to partial or complete lockdowns that were implemented throughout the world between 2019 and 2022. This pandemic severely affected the education sectors in developing countries such as [...] Read more.

Coronavirus disease (COVID-19) has spread quickly around the globe. COVID-19 has affected the education sector due to partial or complete lockdowns that were implemented throughout the world between 2019 and 2022. This pandemic severely affected the education sectors in developing countries such as Pakistan. All the educational institutions in Pakistan turned to online education. However, the education sector lacked the teaching experts, digital experts, the Internet of Things (IoT), and resources needed for online education. The shift from traditional to online education has created many challenges for developing countries during a pandemic such as COVID-19, for example, access to the IoT. This paper aims to introduce the factor model (F model), which will provide guidelines for the government and universities for minimizing the deficiencies related to online education. The F-model will identify all the factors that affect the performance and guide the user about their importance. This will allow the user to resolve that issue and improve the performance of their department or institution. Thus, the F model will benefit the education sector by mitigating the challenges related to online education. The F model is not only confined to online education but can be operated in the fields of science and industry for data extraction and the calculation of results. First, the data is collected physically and online through a student survey related to the challenges of online education during a pandemic. The data extraction and the calculation of the results are carried out using the F model. The results of the survey are alarming and the government has a lot of work to do to improve online education using the IoT. According to the F model, the government should take serious action to improve the performance of students, teachers, and all education sectors not only during the COVID-19 pandemic but also for possible future pandemics. Full article

(This article belongs to the Special Issue Advances in Lightweight AI for Internet of Things Devices for Smart Cities)

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13 pages, 3885 KiB

Open AccessEditor’s ChoiceArticle

Use of 2-Ethylhexyl Nitrate for the Slow Pyrolysis of Plastic Waste

by Jochen Uebe, Audrone Zukauskaite, Zilvinas Kryzevicius and Gintare Vanagiene

Processes 2022, 10(7), 1418; https://doi.org/10.3390/pr10071418 - 20 Jul 2022

Cited by 1 | Viewed by 1410

Abstract

Plastics are widely used and are part of modern life. Recycling of plastic waste can be achieved by pyrolysis. Conventional pyrolysis of plastic waste takes place at temperatures higher than 450 °C, because the oil yield is higher. In this study, we examined [...] Read more.

Plastics are widely used and are part of modern life. Recycling of plastic waste can be achieved by pyrolysis. Conventional pyrolysis of plastic waste takes place at temperatures higher than 450 °C, because the oil yield is higher. In this study, we examined if an initiator for radical reactions can achieve the conventional pyrolysis of HDPE and PP even at low temperatures. To support the onset of decomposition of HDPE and PP at low temperatures, 2-ethylhexyl nitrate (2-EHN) was added. 2-EHN forms radicals already at about 150 °C and can thus initiate the pyrolysis process at lower temperatures. Pyrolysis oil yields increased, especially for HDPE pyrolysis, at the expense of the gaseous (minus 50%) and especially the solid fraction (minus 80%). For PP and HDPE pyrolysis oil, the proportion of carbon compounds shifted toward shorter-chain, less cyclic compounds, and there was an improvement in the physicochemical property profile: the heating values of both oils were slightly higher and the pour point significantly lower, in line with the shift toward shorter-chain compounds. The diesel content and, to a lesser extent, the gasoline content increased at the expense of waxes and other high-boiling compounds. Full article

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21 pages, 3421 KiB

Open AccessArticle

Regenerable Kiwi Peels as an Adsorbent to Remove and Reuse the Emerging Pollutant Propranolol from Water

by Jennifer Gubitosa, Vito Rizzi, Paola Fini, Sergio Nuzzo and Pinalysa Cosma

Processes 2022, 10(7), 1417; https://doi.org/10.3390/pr10071417 - 20 Jul 2022

Cited by 5 | Viewed by 1667

Abstract

This work aims to characterize the adsorption process of propranolol HCl, an emerging pollutant and a widely used β-blocker, onto kiwi peels, an agricultural waste. The use of UV-vis spectroscopy was considered to obtain information about the pollutant removal working in the in-batch [...] Read more.

This work aims to characterize the adsorption process of propranolol HCl, an emerging pollutant and a widely used β-blocker, onto kiwi peels, an agricultural waste. The use of UV-vis spectroscopy was considered to obtain information about the pollutant removal working in the in-batch mode. In a relatively short time, the adsorption process could remove the pollutant from water. A kiwi peel maximum adsorption capacity of 2 mg/g was obtained. With the perspective of scaling up the process, preliminary in-flux measurements were also performed. The investigation of the whole in-batch adsorption process was conducted by studying the effect of ionic strength (adopting salt concentrations from 0 to 0.4 M), pH values (from 2 to 12), adsorbent/pollutant amounts (from 25 to 100 mg and from 7.5 to 15 mg/L, respectively), and temperature values (from 289 to 305 K). The thermodynamics, the adsorption isotherms, and the kinetics of the adsorption process were also carefully investigated. The Langmuir model fitted the experimental data well, with an R² of 0.9912, restituting K_L: 1 L/mg and Q₀: 1.8 mg/g. The temperature increase enhanced the pollutant removal due to the endothermic adsorption characteristics. Accordingly, a ΔH°_298K of +70 KJ/mol was obtained. The pseudo-first-order kinetic model described the process. Due to the results observed during the study of the effects of pH and ionic strength, the prominent presence of electrostatic interactions, working in synergy with hydrophobic forces and H-bonds between the pollutant and kiwi peel surfaces, was successfully demonstrated. In particular, FTIR-ATR measurements confirmed the latter findings. Finally, desorption experiments for recycling 100% of propranolol for each cycle were performed using 0.1 M MgCl₂. Ten cycles of adsorption/desorption were obtained and indicated that the percentage of propranolol removal was not affected during each run, increasing the maximum adsorption from 2 to 20 mg/g. Full article

(This article belongs to the Special Issue Eco-Friendly Materials in Emergent Contaminants Removal Processes)

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14 pages, 11550 KiB

Open AccessArticle

Experimental Study on a New Combined Gas–Liquid Separator

by Lei Ji, Qin Zhao, Huiming Deng, Lanyue Zhang and Wanquan Deng

Processes 2022, 10(7), 1416; https://doi.org/10.3390/pr10071416 - 20 Jul 2022

Cited by 2 | Viewed by 1880

Abstract

Gas–liquid separation at natural gas wellheads has always been a key technical problem in the fields of natural gas transportation and storage. Developing a gas–liquid separation device that is both universal and highly efficient is the current challenge. A new type of combined [...] Read more.

Gas–liquid separation at natural gas wellheads has always been a key technical problem in the fields of natural gas transportation and storage. Developing a gas–liquid separation device that is both universal and highly efficient is the current challenge. A new type of combined gas–liquid separation device was designed in this study, and the efficiency of the separator was studied using a laser Doppler anemometer and phase Doppler particle analyzer at a flow rate of 10–60 Nm³/h. The results showed that the separation efficiency of the combined separator was above 95% at each experimental flow rate, verifying the strong applicability of the combined separator. Moreover, the separation efficiency was as high as 99% at the flow rates of 10 and 60 Nm³/h, thereby realizing efficient separation. This study is significant to the development of gas–liquid separation devices. Full article

(This article belongs to the Special Issue Advanced in Dewatering and Drying Processes)

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17 pages, 4852 KiB

Open AccessArticle

Influence of Heterogeneous Caprock on the Safety of Carbon Sequestration and Carbon Displacement

by Xiaochen Wang, Xinwei Liao, Peng Dong, Kang Tang, Xudong Zhao and Chen Guo

Processes 2022, 10(7), 1415; https://doi.org/10.3390/pr10071415 - 20 Jul 2022

Cited by 2 | Viewed by 1337

Abstract

Carbon Capture, Utilization and Storage (CCUS) is a method of burying the captured CO₂ into the reservoir and displacement of crude oil from reservoirs, which considers both economy and environmental protection. At present, it is considered as an important means to deal [...] Read more.

Carbon Capture, Utilization and Storage (CCUS) is a method of burying the captured CO₂ into the reservoir and displacement of crude oil from reservoirs, which considers both economy and environmental protection. At present, it is considered as an important means to deal with global climate change. To ensure the safety of the CCUS scheme, it is very important to study the invasion and migration of CO₂ in different types of caprocks. In this paper, we first choose the injection-production method of fixed gas injection rate at the top of the reservoir and constant pressure oil production at the bottom. Secondly, the distribution of porosity and permeability in the caprock is designed, and four types of caprock models are established: homogeneous caprock, layered homogeneous caprock, heterogeneous caprock, and layered heterogeneous caprock. Finally, the intrusion amount and migration characteristics of CO₂ in caprock of four schemes in injection-production stage and burial stage are studied, and comprehensive analysis and evaluation are made in combination with the pressure distribution of caprock. In addition, the oil recovery ratio, geological CO₂ storage, and amount of CO₂ intrusion in caprock under different injection-production parameters in this model are also analyzed. This study provides a scientific basis for the safe operation of CCUS and geological storage of CO₂. Full article

(This article belongs to the Special Issue Recent Progress in CO₂ Capture, Utilization, and Storage (CCUS) Technologies for CO₂ Emissions Control)

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17 pages, 6631 KiB

Open AccessArticle

Study on Speed Planning of Signalized Intersections with Autonomous Vehicles Considering Regenerative Braking

by Ning Li, Jiarao Yang, Junping Jiang, Feng Hong, Yang Liu and Xiaobin Ning

Processes 2022, 10(7), 1414; https://doi.org/10.3390/pr10071414 - 20 Jul 2022

Cited by 5 | Viewed by 1335

Abstract

In order to reduce the energy consumption caused by the frequent braking of vehicles at signalized intersections, an optimized speed trajectory control method is proposed, based on braking energy recovery efficiency (BERE) in connection with an automated system for vehicle real-time interaction with [...] Read more.

In order to reduce the energy consumption caused by the frequent braking of vehicles at signalized intersections, an optimized speed trajectory control method is proposed, based on braking energy recovery efficiency (BERE) in connection with an automated system for vehicle real-time interaction with roadside facilities and regional central control. Our objectives were as follows; firstly, to establish the simulation model of the hybrid energy regenerative braking system (HERBS) and to verify it by bench test. Secondly, to build up the genetic algorithm (GA) optimization model for the deceleration stopping of the HERBS. Then, to obtain signal light status and timing information to be the constraints; the BERE is to be the optimized objective, resulting in optimization for the speed trajectory under the deceleration stopping condition of a single signalized intersection. Finally, vehicle simulations in ADVISOR software are utilized to validate the optimization results. The results show that the BERE during deceleration stopping at a single signalized intersection after the speed trajectory optimization is 36.21% higher than that of inexperienced drivers, and 7.82% higher than that of experienced drivers. Full article

(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System)

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19 pages, 3398 KiB

Open AccessEditor’s ChoiceArticle

A Novel Exponential-Weighted Method of the Antlion Optimization Algorithm for Improving the Convergence Rate

by Szu-Chou Chen, Wen-Chen Huang, Ming-Hsien Hsueh, Chieh-Yu Pan and Chih-Hao Chang

Processes 2022, 10(7), 1413; https://doi.org/10.3390/pr10071413 - 20 Jul 2022

Cited by 1 | Viewed by 1332

Abstract

The antlion optimization algorithm (ALO) is one of the most effective algorithms to solve combinatorial optimization problems, but it has some disadvantages, such as a long runtime. As a result, this problem impedes decision makers. In addition, due to the nature of the [...] Read more.

The antlion optimization algorithm (ALO) is one of the most effective algorithms to solve combinatorial optimization problems, but it has some disadvantages, such as a long runtime. As a result, this problem impedes decision makers. In addition, due to the nature of the problem, the speed of convergence is a critical factor. As the size of the problem dimension grows, the convergence speed of the optimizer becomes increasingly significant. Many modified versions of the ALO have been developed in the past. Nevertheless, there are only a few research articles that discuss better boundary strategies that can increase the diversity of ants walking around an antlion to accelerate convergence. A novel exponential-weighted antlion optimization algorithm (EALO) is proposed in this paper to address slow convergence rates. The algorithm uses exponential functions and a random number in the interval 0, 1 to increase the diversity of the ant’s random walks. It has been demonstrated that by optimizing twelve classical objective functions of benchmark functions, the novel method has a higher convergence rate than the ALO. This is because it has the most powerful search capability and speed. In addition, the proposed method has also been compared to other existing methods, and it has obtained superior experimental results relative to compared methods. Therefore, the proposed EALO method deserves consideration as a possible optimization tool for solving combinatorial optimization problems, due to its highly competitive results. Full article

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25 pages, 10747 KiB

Open AccessArticle

Performance Comparison and Optimization of 16V265H Diesel Engine Fueled with Biodiesel Based on Miller Cycle

by Feng Jiang, Junming Zhou, Jie Hu, Xueyou Tan, Qinglie Mo and Wentong Cao

Processes 2022, 10(7), 1412; https://doi.org/10.3390/pr10071412 - 20 Jul 2022

Cited by 2 | Viewed by 1527

Abstract

This paper introduces the theoretical basis and optimization method of diesel engine working process theory. By comparing two Miller cycle schemes of B20 biodiesel under different load conditions of 1000 rpm (100%, 75%, and 50%), the best Miller cycle scheme and the best [...] Read more.

This paper introduces the theoretical basis and optimization method of diesel engine working process theory. By comparing two Miller cycle schemes of B20 biodiesel under different load conditions of 1000 rpm (100%, 75%, and 50%), the best Miller cycle scheme and the best Miller degree were found. Then, based on the Miller cycle scheme, its performance was optimized and analyzed, and the best intake timing scheme of the B20 biodiesel engine under different working conditions was obtained. The results show that the performance of B20 biodiesel in variable valve overlap angle Miller cycle is better than that in variable cam profile Miller cycle, and the effect is the best when the Miller degree is 30 °CA. When B20 biodiesel is used under 100% and 50% load conditions, the maximum power under the two loads is in the area near intake valve timing 179 °CAA and exhaust valve timing 174 °CAA, and intake valve timing 224.5 °CAA and exhaust valve timing 119 °CAA, respectively. Fuel consumption, soot emissions, and NOx emissions also have the corresponding best performance intake valve and exhaust valve positions. Full article

(This article belongs to the Special Issue Clean Combustion and Emission in Vehicle Power System)

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18 pages, 10537 KiB

Open AccessArticle

Photovoltaic Fuzzy Logical Control MPPT Based on Adaptive Genetic Simulated Annealing Algorithm-Optimized BP Neural Network

by Yan Zhang, Ya-Jun Wang, Yong Zhang and Tong Yu

Processes 2022, 10(7), 1411; https://doi.org/10.3390/pr10071411 - 20 Jul 2022

Cited by 7 | Viewed by 1818

Abstract

The P–U characteristic curve of the photovoltaic (PV) cell is a single peak curve with only one maximum power point (MPP). However, the fluctuation of the irradiance level and ambient temperature will cause the drift of MPP. In the maximum power point tracking [...] Read more.

The P–U characteristic curve of the photovoltaic (PV) cell is a single peak curve with only one maximum power point (MPP). However, the fluctuation of the irradiance level and ambient temperature will cause the drift of MPP. In the maximum power point tracking (MPPT) algorithm of PV systems, BP neural network (BPNN) has an unstable learning rate and poor performance, while the genetic algorithm (GA) tends to fall into local optimum. Therefore, a novel PV fuzzy MPPT algorithm based on an adaptive genetic simulated annealing-optimized BP neural network (AGSA-BPNN-FLC) is proposed in this paper. First, the adaptive GA is adopted to generate the corresponding population and increase the population diversity. Second, the simulated annealing (SA) algorithm is applied to the parent and offspring with a higher fitness value to improve the convergence rate of GA, and the optimal weight threshold of BPNN are updated by GA and SA algorithm. Third, the optimized BPNN is employed to predict the MPP voltage of PV cells. Finally, the fuzzy logical control (FLC) is used to eliminate local power oscillation and improve the robustness of the PV system. The proposed algorithm is applied and compared with GA-BPNN, simulated annealing-genetic (SA-GA), particle swarm optimization (PSO), grey wolf optimization (GWO) and FLC algorithm under the condition that both the irradiance and temperature change. Simulation results indicate that the proposed MPPT algorithm is superior to the above-mentioned algorithms with efficiency, steady-state oscillation rate, tracking time and stability accuracy, and they have a good universality and robustness. Full article

(This article belongs to the Topic Sustainable Energy Technology)

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3 pages, 172 KiB

Open AccessEditorial

Special Issue: “Emerging Technologies in Heating, Ventilation, Air Conditioning and Refrigeration (HVAC&R) Systems”

by Kai-Shing Yang, Jin-Cherng Shyu and Ming-Tsang Lee

Processes 2022, 10(7), 1410; https://doi.org/10.3390/pr10071410 - 20 Jul 2022

Cited by 1 | Viewed by 1183

Abstract

Heating, ventilation, air conditioning and refrigeration (HVAC&R) systems provide physical environment comfort for the occupants at a possible expense of large amount of energy consumption [...] Full article

(This article belongs to the Special Issue Emerging Technologies in Heating, Ventilation, Air Conditioning and Refrigeration (HVAC&R) Systems)

17 pages, 14186 KiB

Open AccessFeature PaperArticle

Comparison Process of Blood Heavy Metals Absorption Linked to Measured Air Quality Data in Areas with High and Low Environmental Impact

by Nicoletta Lotrecchiano, Luigi Montano, Ian Marc Bonapace, Tenore Giancarlo, Paolo Trucillo and Daniele Sofia

Processes 2022, 10(7), 1409; https://doi.org/10.3390/pr10071409 - 19 Jul 2022

Cited by 9 | Viewed by 1975

Abstract

Air pollution is a problem shared by the entire world population, and researchers have highlighted its adverse effects on human health in recent years. The object of this paper was the relationship between the pollutants’ concentrations measured in the air and the quantity [...] Read more.

Air pollution is a problem shared by the entire world population, and researchers have highlighted its adverse effects on human health in recent years. The object of this paper was the relationship between the pollutants’ concentrations measured in the air and the quantity of pollutant itself inhaled by the human body. The area chosen for the study has a high environmental impact given the significant presence on the territory of polluting activities. The Acerra area (HI) has a waste-to-energy plant and numerous industries to which polluting emissions are attributed. This area has always been the subject of study as the numbers of cancer patients are high. A survey on male patients to evaluate the heavy metals concentrations in the blood was conducted in the two areas and then linked to its values aero-dispersed. Using the air quality data measured by the monitoring networks in two zones, one with high environmental impact (HI) and one with low environmental impact (LI), the chronicle daily intake (CDI) of pollutants inhaled by a single person was calculated. The pollutants considered in this study are PM10 and four heavy metals (As, Cd, Ni, Pb) constituting the typical particulates of the areas concerned. The CDI values calculated for the two zones are significantly higher in the HI zone following the seasonal pollution trend. Full article

(This article belongs to the Special Issue Air Quality Monitoring for Smart Cities and Industrial Applications)

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42 pages, 3029 KiB

Open AccessFeature PaperReview

Recent Criterion on Stability Enhancement of Perovskite Solar Cells

by Md Saif Hasan, Jahangir Alom, Md Asaduzzaman, Mohammad Boshir Ahmed, Md Delowar Hossain, ASM Saem, Jahangir Masud, Jivan Thakare and Md Ashraf Hossain

Processes 2022, 10(7), 1408; https://doi.org/10.3390/pr10071408 - 19 Jul 2022

Cited by 9 | Viewed by 5185

Abstract

Perovskite solar cells (PSCs) have captured the attention of the global energy research community in recent years by showing an exponential augmentation in their performance and stability. The supremacy of the light-harvesting efficiency and wider band gap of perovskite sensitizers have led to [...] Read more.

Perovskite solar cells (PSCs) have captured the attention of the global energy research community in recent years by showing an exponential augmentation in their performance and stability. The supremacy of the light-harvesting efficiency and wider band gap of perovskite sensitizers have led to these devices being compared with the most outstanding rival silicon-based solar cells. Nevertheless, there are some issues such as their poor lifetime stability, considerable J–V hysteresis, and the toxicity of the conventional constituent materials which restrict their prevalence in the marketplace. The poor stability of PSCs with regard to humidity, UV radiation, oxygen and heat especially limits their industrial application. This review focuses on the in-depth studies of different direct and indirect parameters of PSC device instability. The mechanism for device degradation for several parameters and the complementary materials showing promising results are systematically analyzed. The main objective of this work is to review the effectual strategies of enhancing the stability of PSCs. Several important factors such as material engineering, novel device structure design, hole-transporting materials (HTMs), electron-transporting materials (ETMs), electrode materials preparation, and encapsulation methods that need to be taken care of in order to improve the stability of PSCs are discussed extensively. Conclusively, this review discusses some opportunities for the commercialization of PSCs with high efficiency and stability. Full article

(This article belongs to the Special Issue Technological Advancements in Nanomaterials Synthesis and Application)

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15 pages, 12112 KiB

Open AccessArticle

Continuous Nonsingular Fast Terminal Sliding Mode Control for Speed Tracking of PMSM Based on Finite Time Disturbance Observer

by Yaobin Yue, Yanfeng Geng and Weiliang Wang

Processes 2022, 10(7), 1407; https://doi.org/10.3390/pr10071407 - 19 Jul 2022

Cited by 5 | Viewed by 1537

Abstract

A continuous nonsingular fast terminal sliding mode (CNFTSM) control strategy with an automated double power reaching law is proposed to improve the performance of speed dynamic response and accuracy tracking for the permanent magnet synchronous motor (PMSM) servo system. In pursuit of robustness [...] Read more.

A continuous nonsingular fast terminal sliding mode (CNFTSM) control strategy with an automated double power reaching law is proposed to improve the performance of speed dynamic response and accuracy tracking for the permanent magnet synchronous motor (PMSM) servo system. In pursuit of robustness against system uncertainties, a finite-time convergent extended state observer (ESO) is designed to estimate external disturbances, parameter variation, and unmodeled dynamics as a feedforward compensation to the output feedback control system. The developed controller, based on Lyapunov stability theory analysis, can guarantee finite time stability from any initial state in the presence of internal and external disturbances. The modified sliding mode reaching law can achieve enough convergence rate compared with the exponential reaching law, and the inherent chattering of sliding mode is reduced when system states approach the equilibrium point. Theoretical analysis and simulation results demonstrate that the proposed composite controller can achieve higher performance than the conventional sliding mode method. Full article

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15 pages, 1625 KiB

Open AccessArticle

Intelligent Model for Power Cells State of Charge Forecasting in EV

by Víctor López, Esteban Jove, Francisco Zayas Gato, Francisco Pinto-Santos, Andrés José Piñón-Pazos, Jose-Luis Casteleiro-Roca, Hector Quintian and Jose Luis Calvo-Rolle

Processes 2022, 10(7), 1406; https://doi.org/10.3390/pr10071406 - 19 Jul 2022

Cited by 5 | Viewed by 1865

Abstract

In electric vehicles and mobile electronic devices, batteries are one of the most critical components. They work by using electrochemical reactions that have been thoroughly investigated to identify their behavior and characteristics at each operating point. One of the fascinating aspects of batteries [...] Read more.

In electric vehicles and mobile electronic devices, batteries are one of the most critical components. They work by using electrochemical reactions that have been thoroughly investigated to identify their behavior and characteristics at each operating point. One of the fascinating aspects of batteries is their complicated behavior. The type of power cell reviewed in this study is a Lithium Iron Phosphate LiFePO

_{4}

(LFP). The goal of this study is to develop an intelligent model that can forecast the power cell State of Charge (SOC). The dataset used to create the model comprises all the operating points measured from an actual system during a capacity confirmation test. Regression approaches based on Deep Learning (DL), such as Long Short-Term Memory networks (LSTM), were evaluated under different model configurations and forecasting horizons. Full article

(This article belongs to the Special Issue Challenges in Machine Learning, Artificial Intelligence, Wireless Sensor Networks and Smart Cities)

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12 pages, 3252 KiB

Open AccessArticle

Research on the Formulation System of Weak Gel and the Influencing Factors of Gel Formation after Polymer Flooding in Y1 Block

by Guangsheng Cao, Jiajun Wu, Yujie Bai, Ning Zhang, Peidong Xing, Qian Xu, Dandan Li, Xin Cong and Jiankang Liu

Processes 2022, 10(7), 1405; https://doi.org/10.3390/pr10071405 - 19 Jul 2022

Cited by 2 | Viewed by 1295

Abstract

After long-term polymer flooding, water channeling, and ineffective water circulation occur in oil wells, which seriously affect polymer flooding efficiency and oilfield recovery. The weak gel system has the property of delaying cross-linking. After the weak gel system enters the deep formation, the [...] Read more.

After long-term polymer flooding, water channeling, and ineffective water circulation occur in oil wells, which seriously affect polymer flooding efficiency and oilfield recovery. The weak gel system has the property of delaying cross-linking. After the weak gel system enters the deep formation, the cross-linking reaction is carried out, which can achieve the purpose of deep regulation and flooding. In this paper, according to the formation characteristics of high temperature, high permeability, and large pores in Y1 block (a block in the Daqing Yushulin Oilfield), the formulation of weak gel system was developed. The optimal formulation was determined by parameters such as gel-forming properties, stability, viscoelasticity, and rheology. Finally, the best formulation for the Y1 block is that containing 0.22% of polyacrylamide (HPAM) and 0.15% of chromium (III) acetate system. The gel-forming time of the formulation is 8 h, and the viscosity can be maintained at 15,000–24,000 mPa·s. Next, this paper studied the factors that affect the gelation of formulations, mainly including dissolved oxygen content, bacterial content, insoluble suspended solids content, and metal ions in the formulation water. The results show that the critical point of the worst effect is the oxygen content close to 1.5 mg/L, and the optimal critical point of oxygen content of the gel system is 7 mg/L. The bacteria in the prepared water degrade the weak gel solution. The more bacteria, the more serious the degradation of the weak gel. A small amount of insoluble suspended solids will greatly increase the viscosity of the weak gel solution, but will accelerate the gel-breaking time. When the content of insoluble suspended solids is high, more than 1000 mg/L, a precipitate will be formed at the bottom of the solution, and the difference in the content of insoluble suspended solids in this interval has little effect on weak gels. The metal ion that mainly affects the gelation effect is Fe²⁺. With the increase of Fe²⁺ mass concentration, the viscosity of weak gel decreases sharply. Full article

(This article belongs to the Topic Enhanced Oil Recovery Technologies, 2nd Volume)

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11 pages, 2186 KiB

Open AccessArticle

Quantitative Assessment of the Efficacy of the Nd:YAG Laser Therapy of Psoriasis

by Wiktoria Odrzywołek, Anna Deda, Julita Zdrada, Dominika Wcisło-Dziadecka, Barbara Błońska-Fajfrowska and Sławomir Wilczyński

Processes 2022, 10(7), 1404; https://doi.org/10.3390/pr10071404 - 19 Jul 2022

Viewed by 2839

Abstract

Psoriasis is a chronic inflammatory disease. Within psoriatic lesions, microvascular dysfunction and numerous, tortuous blood vessels occurs. The Nd:YAG laser causes the selective destruction of dilated capillaries, which contributes to the inhibition of leukocyte transport within psoriatic lesions and may be an effective [...] Read more.

Psoriasis is a chronic inflammatory disease. Within psoriatic lesions, microvascular dysfunction and numerous, tortuous blood vessels occurs. The Nd:YAG laser causes the selective destruction of dilated capillaries, which contributes to the inhibition of leukocyte transport within psoriatic lesions and may be an effective method of psoriasis therapy. This preliminary study was designed to assess the effectiveness of the Nd:YAG laser in reducing psoriatic lesions. Twenty volunteers suffering from psoriasis met the inclusion criteria and were qualified for the study. The non-lesional skin areas and areas with psoriatic lesions were imaged using a DUB SkinScanner high-frequency ultrasound, and skin parameters, including the stratum corneum hydration, melanin and hemoglobin level, were evaluated. The thickness of the epidermis and the SLEB layer, as well as the density of the dermis, were assessed before and after the therapy. The Nd:YAG laser, with a wavelength of 1064 nm and a 650-microsecond pulse duration, was used to treat psoriasis. The density of psoriatic skin after treatment increased by 7.26 u.m. and epidermis thickness decreased by 0.068 u.m. The stratum corneum hydration increased by 9.5 u.m., hemoglobin value decreased by 35 u.m. and melanin decreased by 12 u.m. The thickness of the SLEB layer was also reduced from 0.340 mm before the therapy to 0.195 mm after the therapy. The increase in skin density and the decrease in epidermal thickness after the therapy may prove the effectiveness of the Nd:YAG laser in reducing psoriatic lesions. The thickness of the SLEB layer and hemoglobin decrease indicate a reduction in inflammation. Laser therapy improves the epidermal hydration of psoriatic skin. Full article

(This article belongs to the Special Issue 10th Anniversary of Processes: Women's Special Issue Series)

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10 pages, 2713 KiB

Open AccessArticle

Bergenin from Bergenia Species Produces a Protective Response against Myocardial Infarction in Rats

by Taseer Ahmad, Imran Ul Haq, Taous Khan, Mater H. Mahnashi, Mohammed Y. Alasmary, Sultan A. Almedhesh, Hamdan Al Shehri, Mohammed A. Alshahrani and Abdul Jabbar Shah

Processes 2022, 10(7), 1403; https://doi.org/10.3390/pr10071403 - 19 Jul 2022

Cited by 3 | Viewed by 1787

Abstract

Bergenin is a phenolic glycoside that has been reported to occur naturally in several plant species, reported as a cardioprotective. However, bergenin, one of the important phytochemicals in these plants, is still not reported as a cardioprotective. The present study was designed to [...] Read more.

Bergenin is a phenolic glycoside that has been reported to occur naturally in several plant species, reported as a cardioprotective. However, bergenin, one of the important phytochemicals in these plants, is still not reported as a cardioprotective. The present study was designed to investigate the cardioprotective effects of bergenin on isoproterenol-induced myocardial infarction in rats. Bergenin and atenolol were administered through intraperitoneal (i.p.) injection to Sprague Dawley (SD) rats in separate experiments for five (5) days. At the end of this period, rats were administered isoproterenol (80 mg/kg s.c.) to induce myocardial injury. After induction, rats were anaesthetized to record lead II ECG, then sacrificed, blood was collected to analyze cardiac marker enzymes, and a histopathological study of the heart tissues was also performed. Pretreatment with bergenin showed a significant decrease in ST-segment elevation, deep Q-wave, infarct size, and also normalized cardiac marker enzymes (cTnI, CPK, CK-MB, LDH, ALT, and AST), particularly at 3 mg/kg, as compared to isoproterenol treated group. Our findings revealed, for the first time, the use of glycoside bergenin as a potential cardioprotective agent against the isoproterenol-induced MI in rats. Full article

(This article belongs to the Special Issue Bioactive Compounds from Natural Plants)

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11 pages, 5559 KiB

Open AccessArticle

Drying Characteristics of a Combined Drying System of Low-Pressure Superheated Steam and Heat Pump

by Yuan Yao, Zhenneng Lu, Yulie Gong, Song Guo, Chupeng Xiao and Wenbo Hu

Processes 2022, 10(7), 1402; https://doi.org/10.3390/pr10071402 - 19 Jul 2022

Viewed by 1712

Abstract

The present study aimed at investigating the use of a drying system combining the concept of low-pressure superheated steam drying and heat pump drying for fish. The effects of various drying medium pressures on the temperature field, airflow field, drying time, equipment performance [...] Read more.

The present study aimed at investigating the use of a drying system combining the concept of low-pressure superheated steam drying and heat pump drying for fish. The effects of various drying medium pressures on the temperature field, airflow field, drying time, equipment performance as well as the power consumption of the drying process were investigated and discussed. Four comparative tests with different initial pressures were carried out according to a specified drying process by the combined drying system. The results showed that when the vacuum was high, the temperature field and airflow field in the drying chamber were more uniform. Due to the poor heat transfer performance of the drying medium at high vacuum, the drying time increased with a decrease in initial pressure. It was also found that with the decrease in drying medium pressure, the power consumption of the heat pump and the axial fans was reduced, while the power consumption of the electric heater went up. Overall, the total power consumption is directly proportional to the drying medium pressure. Full article

(This article belongs to the Special Issue Drying Kinetics and Quality Control in Food Processing)

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17 pages, 3509 KiB

Open AccessArticle

Multi-Objective Optimal Scheduling for Multi-Renewable Energy Power System Considering Flexibility Constraints

by Lei Yang, Wei Huang, Cheng Guo, Dan Zhang, Chuan Xiang, Longjie Yang and Qianggang Wang

Processes 2022, 10(7), 1401; https://doi.org/10.3390/pr10071401 - 18 Jul 2022

Cited by 5 | Viewed by 1252

Abstract

As renewable energy penetration increases, the lack of flexibility in a multi-renewable power system can seriously affect its own economics and reliability. To address this issue, three objectives are considered in this study: power fluctuations on tie-line, operating cost, and curtailment rate of [...] Read more.

As renewable energy penetration increases, the lack of flexibility in a multi-renewable power system can seriously affect its own economics and reliability. To address this issue, three objectives are considered in this study: power fluctuations on tie-line, operating cost, and curtailment rate of renewable energy. Presented also is an optimal day-ahead scheduling model based on the MREPS for distributed generations with flexibility constraints. The multi-objective particle swarm optimization (MOPSO) algorithm can be applied to obtain a set of Pareto non-dominated solutions for the day-ahead scheduling strategy with the proposed model. By using fuzzy comprehensive evaluation, the optimal compromise solution is determined in the set. The presented method sacrifices a small amount of economy and power fluctuation, but it can reduce the deviation between forecast and realized power fluctuations on the tie-line, while improving the utilization of renewable energy. Full article

(This article belongs to the Special Issue Modeling, Analysis and Control Processes of New Energy Power Systems)

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24 pages, 11640 KiB

Open AccessArticle

Correlations Based on Numerical Validation of Oscillating Flow Regenerator

by Kuruchanvalasu Jambulingam Bharanitharan, Sundararaj Senthilkumar, Kuan-Lin Chen, Kuan-Yu Luo and Shung-Wen Kang

Processes 2022, 10(7), 1400; https://doi.org/10.3390/pr10071400 - 18 Jul 2022

Cited by 2 | Viewed by 1661

Abstract

Stirling regenerator is one of the emerging heat exchanger systems in the area of cryogenic cooling. Many kinds of research have been conducted to study the efficiency of Stirling regenerators. Therefore, the principles and related knowledge of Stirling refrigerators must be thoroughly understood [...] Read more.

Stirling regenerator is one of the emerging heat exchanger systems in the area of cryogenic cooling. Many kinds of research have been conducted to study the efficiency of Stirling regenerators. Therefore, the principles and related knowledge of Stirling refrigerators must be thoroughly understood to design a regenerator with excellent performance for low-temperature and cryogenic engineering applications. In this study, an experimental setup is developed to estimate the pressure drop of the oscillating flow through two different wire-mesh regenerators, namely, 200 mesh and 300 mesh, for various operating frequencies ranging from 3 (200 RPM) to 10 Hz (600 RPM). Transient, axisymmetric, incompressible, and laminar flow governing equations are solved numerically, and source terms are added in the governing equations with the help of the porous media model and the Ergun semiempirical correlation, assuming that the wire meshes are cylindrical particles arranged uniformly. Simulation results show that the numerical predictions of temporal pressure variation are in reasonably good agreement with those of experimental findings. It is also found that the Ergun correlation works more accurately for higher flow rate conditions. Full article

(This article belongs to the Special Issue Emerging Technologies in Heating, Ventilation, Air Conditioning and Refrigeration (HVAC&R) Systems (Second Volume))

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