Next Issue
Volume 7, April
Previous Issue
Volume 7, February
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.5
Journals
Processes
Volume 7
Issue 3
share announcement

Processes, Volume 7, Issue 3 (March 2019) – 59 articles

Cover Story (view full-size image): Podocyte cells wrap around blood vessels in the kidney and play a key role in the progression of diabetic kidney disease (DKD). Podocytes prompt a glucose-stimulated local renin-angiotensin system (RAS) that produces angiotensin II (ANG II). ACE inhibition is a pharmaceutical approach to suppress ANG II and slow DKD progression. A PK/PD model for ACE inhibition in a local RAS network in a podocyte has been developed and compared with a systemic RAS model. The model is parameterized for normal and impaired renal function and can consider subject-specific glucose dynamics as input, enabling the study of various pathophysiological conditions. View this paper.
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
14 pages, 2531 KiB  
Article
Mold Level Predict of Continuous Casting Using Hybrid EMD-SVR-GA Algorithm
by Zhufeng Lei and Wenbin Su
Processes 2019, 7(3), 177; https://doi.org/10.3390/pr7030177 - 26 Mar 2019
Cited by 11 | Viewed by 4349
Abstract
The prediction of mold level is a basic and key problem of continuous casting production control. Many current techniques fail to predict the mold level because of mold level is non-linear, non-stationary and does not have a normal distribution. A hybrid model, based [...] Read more.
The prediction of mold level is a basic and key problem of continuous casting production control. Many current techniques fail to predict the mold level because of mold level is non-linear, non-stationary and does not have a normal distribution. A hybrid model, based on empirical mode decomposition (EMD) and support vector regression (SVR), is proposed to solve the mold level in this paper. Firstly, the EMD algorithm, with adaptive decomposition, is used to decompose the original mold level signal to many intrinsic mode functions (IMFs). Then, the SVR model optimized by genetic algorithm (GA) is used to predict the IMFs and residual sequences. Finally, the equalization of the predict results is reconstructed to obtain the predict result. Several hybrid predicting methods such as EMD and autoregressive moving average model (ARMA), EMD and SVR, wavelet transform (WT) and ARMA, WT and SVR are discussed and compared in this paper. These methods are applied to mold level prediction, the experimental results show that the proposed hybrid method based on EMD and SVR is a powerful tool for solving complex time series prediction. In view of the excellent generalization ability of the EMD, it is believed that the hybrid algorithm of EMD and SVR is the best model for mold level predict among the six methods, providing a new idea for guiding continuous casting process improvement. Full article
(This article belongs to the Special Issue Advances in Theoretical and Computational Energy Optimization Processes)
►▼ Show Figures

Figure 1

37 pages, 789 KiB  
Article
Designing Supply Networks in Automobile and Electronics Manufacturing Industries: A Multiplex Analysis
by Myung Kyo Kim and Ram Narasimhan
Processes 2019, 7(3), 176; https://doi.org/10.3390/pr7030176 - 26 Mar 2019
Cited by 8 | Viewed by 3746
Abstract
This study investigates the process of how the original equipment manufacturers (OEMs) in automobile and consumer electronics industries design their supply networks. In contrast to the sociological viewpoint, which regards the emergence of networks as a social and psychological phenomenon occurring among non-predetermined [...] Read more.
This study investigates the process of how the original equipment manufacturers (OEMs) in automobile and consumer electronics industries design their supply networks. In contrast to the sociological viewpoint, which regards the emergence of networks as a social and psychological phenomenon occurring among non-predetermined individuals, this paper attempts to provide a strategic supply network perspective that views the supply network as a strategic choice made by an OEM. Anchored in the multiplex investigation of supply network architectures, this study looks into the following specific questions: (1) Are an OEM’s strategic intent choices associated with supply network architecture and (2) If so, what differential effects do those strategic intents have on the architectural properties of the supply network? Further field investigations were conducted to provide deeper insights into the quantitative and qualitative findings from statistical analyses. Full article
(This article belongs to the Special Issue Performance Measurement and Optimization for Sustainable Production Processes Improvement)
►▼ Show Figures

Figure 1

17 pages, 4413 KiB  
Article
A Novel Multiphase Methodology Simulating Three Phase Flows in a Steel Ladle
by Marco A. Ramírez-Argáez, Abhishek Dutta, A. Amaro-Villeda, C. González-Rivera and A. N. Conejo
Processes 2019, 7(3), 175; https://doi.org/10.3390/pr7030175 - 26 Mar 2019
Cited by 7 | Viewed by 3421
Abstract
Mixing phenomena in metallurgical steel ladles by bottom gas injection involves three phases namely, liquid molten steel, liquid slag and gaseous argon. In order to numerically solve this three-phase fluid flow system, a new approach is proposed which considers the physical nature of [...] Read more.
Mixing phenomena in metallurgical steel ladles by bottom gas injection involves three phases namely, liquid molten steel, liquid slag and gaseous argon. In order to numerically solve this three-phase fluid flow system, a new approach is proposed which considers the physical nature of the gas being a dispersed phase in the liquid, while the two liquids namely, molten steel and slag are continuous phases initially separated by a sharp interface. The model was developed with the combination of two algorithms namely, IPSA (inter phase slip algorithm) where the gas bubbles are given a Eulerian approach since are considered as an interpenetrating phase in the two liquids and VOF (volume of fluid) in which the liquid is divided into two separate liquids but depending on the physical properties of each liquid they are assigned a mass fraction of each liquid. This implies that both the liquid phases (steel and slag) and the gas phase (argon) were solved for the mass balance. The Navier–Stokes conservation equations and the gas-phase turbulence in the liquid phases were solved in combination with the standard k-ε turbulence model. The mathematical model was successfully validated against flow patterns obtained experimentally using particle image velocimetry (PIV) and by the calculation of the area of the slag eye formed in a 1/17th water–oil physical model. The model was applied to an industrial ladle to describe in detail the turbulent flow structure of the multiphase system. Full article
(This article belongs to the Special Issue Multiphase Reaction Engineering, Reactors and Processes )
►▼ Show Figures

Graphical abstract

15 pages, 2804 KiB  
Article
Strategic Framework for Parameterization of Cell Culture Models
by Pavlos Kotidis and Cleo Kontoravdi
Processes 2019, 7(3), 174; https://doi.org/10.3390/pr7030174 - 26 Mar 2019
Cited by 2 | Viewed by 3359
Abstract
Global Sensitivity Analysis (GSA) is a technique that numerically evaluates the significance of model parameters with the aim of reducing the number of parameters that need to be estimated accurately from experimental data. In the work presented herein, we explore different methods and [...] Read more.
Global Sensitivity Analysis (GSA) is a technique that numerically evaluates the significance of model parameters with the aim of reducing the number of parameters that need to be estimated accurately from experimental data. In the work presented herein, we explore different methods and criteria in the sensitivity analysis of a recently developed mathematical model to describe Chinese hamster ovary (CHO) cell metabolism in order to establish a strategic, transferable framework for parameterizing mechanistic cell culture models. For that reason, several types of GSA employing different sampling methods (Sobol’, Pseudo-random and Scrambled-Sobol’), parameter deviations (10%, 30% and 50%) and sensitivity index significance thresholds (0.05, 0.1 and 0.2) were examined. The results were evaluated according to the goodness of fit between the simulation results and experimental data from fed-batch CHO cell cultures. Then, the predictive capability of the model was tested against four different feeding experiments. Parameter value deviation levels proved not to have a significant effect on the results of the sensitivity analysis, while the Sobol’ and Scrambled-Sobol’ sampling methods and a 0.1 significance threshold were found to be the optimum settings. The resulting framework was finally used to calibrate the model for another CHO cell line, resulting in a good overall fit. The results of this work set the basis for the use of a single mechanistic metabolic model that can be easily adapted through the proposed sensitivity analysis method to the behavior of different cell lines and therefore minimize the experimental cost of model development. Full article
(This article belongs to the Special Issue In silico metabolic modeling and engineering)
►▼ Show Figures

Figure 1

13 pages, 2202 KiB  
Article
Enhancement Effect of Ordered Hierarchical Pore Configuration on SO2 Adsorption and Desorption Process
by Yuwen Zhu, Yanfang Miao and Haoyu Li
Processes 2019, 7(3), 173; https://doi.org/10.3390/pr7030173 - 25 Mar 2019
Cited by 16 | Viewed by 3376
Abstract
Carbonaceous adsorbents with both high sulfur capacity and easy regeneration are required for flue gas desulfurization. A hierarchical structure is desirable for SO2 removal, since the micropores are beneficial for SO2 adsorption, while the mesopore networks facilitate gas diffusion and end-product [...] Read more.
Carbonaceous adsorbents with both high sulfur capacity and easy regeneration are required for flue gas desulfurization. A hierarchical structure is desirable for SO2 removal, since the micropores are beneficial for SO2 adsorption, while the mesopore networks facilitate gas diffusion and end-product H2SO4 storage. Herein, an ordered hierarchical porous carbon was synthesized via a soft-template method and subsequent activation, used in SO2 removal, and compared with coal-based activated carbon, which also had a hierarchical pore configuration. The more detailed, abundant micropores created in CO2 activation, especially the ultramicropores (d < 0.7 nm), are essential in enhancing the SO2 adsorption and the reserves rather than the pore patterns. While O2 and H2O participate in the reaction, the hierarchical porous carbon with ordered mesopores greatly improves SO2 removal dynamics and sulfur capacity, as this interconnecting pore pattern facilitates H2SO4 transport from micropores to mesopores, releasing the SO2 adsorption space. Additionally, the water-washing regeneration performances of the two types of adsorbents were comparatively determined and provide a new insight into the mass-transfer resistance in the pore structure. The ordered hierarchical carbon promoted H2SO4 desorption efficiency and cycled SO2 adsorption–desorption performance, further indicating that interconnecting micro- and mesopores facilitated the diffusion of adsorbates. Full article
(This article belongs to the Special Issue Energy, Economic and Environment for Industrial Production Processes)
►▼ Show Figures

Figure 1

18 pages, 4822 KiB  
Article
Effective Dynamic Control Strategy of a Key Supplier with Multiple Downstream Manufacturers Using Industrial Internet of Things and Cloud System
by Hyunsoo Lee
Processes 2019, 7(3), 172; https://doi.org/10.3390/pr7030172 - 24 Mar 2019
Cited by 8 | Viewed by 3952
Abstract
Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the embedded intelligence analytics. This research applied this trend [...] Read more.
Intelligent data analytics-based cloud computing is a leading trend for managing a large-scale network in contemporary manufacturing environments. The data and information are shared using the cloud environments and valuable knowledge is driven using the embedded intelligence analytics. This research applied this trend to the control of a key supplier’s real-time production planning for solving joint production goals with downstream producers. As a key supplier has several downstream producers in general, several uncertainties are embedded on the supply chain network such as the quality issue in the supplier and the occurrence of unexpected orders from the downstream industries. While the control of a supply plan is difficult considering these dynamics in traditional frameworks, the proposed framework detects the dynamic changes accurately using the constructed cloud system. Moreover, the real-time control considering uncertain scenarios as well as the extracted knowledge is achieved using the provided Industrial Internet of Things (IIoT) and simulation-based control model using stochastic network. To show the effective of the suggested framework, real manufacturing cases and their numerical analyses are provided. Full article
(This article belongs to the Special Issue Process Industry 4.0: Application Research to Small and Medium-Sized Enterprises (SMEs))
►▼ Show Figures

Figure 1

17 pages, 2775 KiB  
Article
Novel Deep Eutectic Solvent Based on Levulinic Acid and 1,4-Butanediol as an Extraction Media for Bioactive Alkaloid Rutaecarpine
by Yue-Yue Si, Shi-Wei Sun, Kun Liu, Yang Liu, Hai-Lin Shi, Ke Zhao, Jin Wang and Wei Wang
Processes 2019, 7(3), 171; https://doi.org/10.3390/pr7030171 - 24 Mar 2019
Cited by 17 | Viewed by 4672
Abstract
Deep eutectic solvents (DESs) are increasingly receiving interest as a new type of green and sustainable alternative to hazardous organic solvents. In this work, a novel DES based on levulinic acid (La) and 1,4-butanediol (Buta) as an extraction media was developed for extracting [...] Read more.
Deep eutectic solvents (DESs) are increasingly receiving interest as a new type of green and sustainable alternative to hazardous organic solvents. In this work, a novel DES based on levulinic acid (La) and 1,4-butanediol (Buta) as an extraction media was developed for extracting the bioactive alkaloid rutaecarpine from the unripe fruits of Tetradium ruticarpum. 24 different DESs consisting of choline chloride, betaine, sugar alcohols, organic acids, amides, and sugars were prepared and tailored to test their extraction efficiency. After initial screening, a hydrophilic DES composed of La and Buta with 1:0.5 molar ratio containing 25% water was tailored for the highest extraction efficiency, followed by the optimizations of molar ratio and water content. The interaction between the molecules of La-Buta DES was investigated by nuclear magnetic resonance spectroscopy in order to confirm its deep eutectic supermolecular structure feature. The extraction conditions were optimized by single-factor experiments, including extraction temperature, extraction time, and solid-liquid ratio. The developed La-Buta DES extraction procedure was successfully applied for the analysis of rutaecarpine in Chinese patent medicines containing the unripe fruits of T. ruticarpum. The excellent property of La-Buta DES indicated its potential as a promising green solvent instead of conventional organic solvent for the extraction of rutaecarpine from the unripe fruits of T. ruticarpum, and that it can used as a sustainable and safe extraction media for other applications. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
►▼ Show Figures

Figure 1

23 pages, 29225 KiB  
Article
A Systematic Grey-Box Modeling Methodology via Data Reconciliation and SOS Constrained Regression
by José Luis Pitarch, Antonio Sala and César de Prada
Processes 2019, 7(3), 170; https://doi.org/10.3390/pr7030170 - 23 Mar 2019
Cited by 20 | Viewed by 4468
Abstract
Developing the so-called grey box or hybrid models of limited complexity for process systems is the cornerstone in advanced control and real-time optimization routines. These models must be based on fundamental principles and customized with sub-models obtained from process experimental data. This allows [...] Read more.
Developing the so-called grey box or hybrid models of limited complexity for process systems is the cornerstone in advanced control and real-time optimization routines. These models must be based on fundamental principles and customized with sub-models obtained from process experimental data. This allows the engineer to transfer the available process knowledge into a model. However, there is still a lack of a flexible but systematic methodology for grey-box modeling which ensures certain coherence of the experimental sub-models with the process physics. This paper proposes such a methodology based in data reconciliation (DR) and polynomial constrained regression. A nonlinear optimization of limited complexity is to be solved in the DR stage, whereas the proposed constrained regression is based in sum-of-squares (SOS) convex programming. It is shown how several desirable features on the polynomial regressors can be naturally enforced in this optimization framework. The goodnesses of the proposed methodology are illustrated through: (1) an academic example and (2) an industrial evaporation plant with real experimental data. Full article
(This article belongs to the Special Issue Process Modelling and Simulation)
►▼ Show Figures

Figure 1

14 pages, 1477 KiB  
Article
A Novel Robust Method for Solving CMB Receptor Model Based on Enhanced Sampling Monte Carlo Simulation
by Wen Hou, Yunlei Yang, Zheng Wang, Muzhou Hou, Qianhong Wu and Xiaoliang Xie
Processes 2019, 7(3), 169; https://doi.org/10.3390/pr7030169 - 23 Mar 2019
Cited by 3 | Viewed by 3411
Abstract
The traditional effective variance weighted least squares algorithms for solving CMB (Chemical Mass Balance) models have the following drawbacks: When there is collinearity among the sources or the number of species is less than the number of sources, then some negative value of [...] Read more.
The traditional effective variance weighted least squares algorithms for solving CMB (Chemical Mass Balance) models have the following drawbacks: When there is collinearity among the sources or the number of species is less than the number of sources, then some negative value of contribution will appear in the results of the source apportionment or the algorithm does not converge to calculation. In this paper, a novel robust algorithm based on enhanced sampling Monte Carlo simulation and effective variance weighted least squares (ESMC-CMB) is proposed, which overcomes the above weaknesses. In the following practical instances for source apportionment, when nine species and nine sources, with no collinearity among them, are selected, EPA-CMB8.2 (U.S. Environmental Protection Agency-CMB8.2), NKCMB1.0 (NanKai University, China-CMB1.0) and ESMC-CMB can obtain similar results. When the source raise dust is added to the source profiles, or nine sources and eight species are selected, EPA-CMB8.2 and NKCMB1.0 cannot solve the model, but the proposed ESMC-CMB algorithm can achieve satisfactory results that fully verify the robustness and effectiveness of ESMC-CMB. Full article
(This article belongs to the Special Issue Advances in Theoretical and Computational Energy Optimization Processes)
►▼ Show Figures

Figure 1

22 pages, 6750 KiB  
Article
Numerical Investigation of SCR Mixer Design Optimization for Improved Performance
by Ghazanfar Mehdi, Song Zhou, Yuanqing Zhu, Ahmer Hussain Shah and Kishore Chand
Processes 2019, 7(3), 168; https://doi.org/10.3390/pr7030168 - 22 Mar 2019
Cited by 25 | Viewed by 5316
Abstract
The continuous increase in the number of stringent exhaust emission legislations of marine Diesel engines had led to a decrease in NOx emissions at the required level. Selective catalyst reduction (SCR) is the most prominent and mature technology used to reduce NO [...] Read more.
The continuous increase in the number of stringent exhaust emission legislations of marine Diesel engines had led to a decrease in NOx emissions at the required level. Selective catalyst reduction (SCR) is the most prominent and mature technology used to reduce NOx emissions. However, to obtain maximum NOx removal with minimum ammonia slip remains a challenge. Therefore, new mixers are designed in order to obtain the maximum SCR efficiency. This paper reports performance parameters such as uniformity of velocity, ammonia uniformity distribution, and temperature distribution. Also, a numerical model is developed to investigate the interaction of urea droplet with exhaust gas and its effects by using line (LM) and swirl (SM) type mixers alone and in combination (LSM). The urea droplet residence time and its interaction in straight pipe are also investigated. Model calculations proved the improvement in velocity uniformity, distribution of ammonia uniformity, and temperature distribution for LSM. Prominent enhancement in the evaporation rate was also achieved by using LSM, which may be due to the breaking of urea droplets into droplets of smaller diameter. Therefore, the SCR system accomplished higher urea conversion efficiency by using LSM. Lastly, the ISO 8178 standard engine test cycle E3 was used to verify the simulation results. It has been observed that the average weighted value of NOx emission obtained at SCR outlet using LSM was 2.44 g/kWh, which strongly meets International Maritime Organization (IMO) Tier III NOx (3.4 g/kWh) emission regulations. Full article
(This article belongs to the Special Issue Advances in Theoretical and Computational Energy Optimization Processes)
►▼ Show Figures

Figure 1

16 pages, 5564 KiB  
Article
Effect of Nitric Acid Modification on Characteristics and Adsorption Properties of Lignite
by Bo Huang, Guowei Liu, Penghui Wang, Xiang Zhao and Hongxiang Xu
Processes 2019, 7(3), 167; https://doi.org/10.3390/pr7030167 - 22 Mar 2019
Cited by 54 | Viewed by 5083
Abstract
The objective of this research was to explore the changes of the pore structure and surface properties of nitric-modified lignite and base the adsorption performance on physical and chemical adsorbent characteristics. To systematically evaluate pore structure and surface chemistry effects, several lignite samples [...] Read more.
The objective of this research was to explore the changes of the pore structure and surface properties of nitric-modified lignite and base the adsorption performance on physical and chemical adsorbent characteristics. To systematically evaluate pore structure and surface chemistry effects, several lignite samples were treated with different concentrations of nitric acid in order to get different pore structure and surface chemistry adsorbent levels. A common heavy metal ion contaminant in water, Pb2+, served as an adsorbate probe to demonstrate the change of modified lignite adsorption properties. The pore structure and surface properties of lignite samples before and after modification were characterized by static nitrogen adsorption, X-ray diffraction, Scanning electron microscope, Fourier transform infrared spectroscopy, zeta potential, and X-ray photoelectron spectroscopy. The experimental results showed that nitric acid modification can increase the ability of lignite to adsorb Pb2+. The adsorption amount of Pb2+ increased from 14.45 mg·g−1 to 30.68 mg·g−1. Nitric acid reacted with inorganic mineral impurities such as iron dolomite in lignite and organic components in coal, which caused an increase in pore size and a decrease in specific surface areas. A hydrophilic adsorbent surface more effectively removed Pb2+ from aqueous solution. Nitric acid treatment increased the content of polar oxygen-containing functional groups such as hydroxyl, carbonyl, and carboxyl groups on the surface of lignite. Treatment introduced nitro groups, which enhanced the negative electrical properties, the polarity of the lignite surface, and its metal ion adsorption performance, a result that can be explained by enhanced water adsorption on hydrophilic surfaces. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
►▼ Show Figures

Figure 1

17 pages, 4248 KiB  
Article
Accelerating Biologics Manufacturing by Upstream Process Modelling
by Martin Kornecki and Jochen Strube
Processes 2019, 7(3), 166; https://doi.org/10.3390/pr7030166 - 21 Mar 2019
Cited by 34 | Viewed by 7564
Abstract
Intensified and accelerated development processes are being demanded by the market, as innovative biopharmaceuticals such as virus-like particles, exosomes, cell and gene therapy, as well as recombinant proteins and peptides will possess no available platform approach. Therefore, methods that are able to accelerate [...] Read more.
Intensified and accelerated development processes are being demanded by the market, as innovative biopharmaceuticals such as virus-like particles, exosomes, cell and gene therapy, as well as recombinant proteins and peptides will possess no available platform approach. Therefore, methods that are able to accelerate this development are preferred. Especially, physicochemical rigorous process models, based on all relevant effects of fluid dynamics, phase equilibrium, and mass transfer, can be predictive, if the model is verified and distinctly quantitatively validated. In this approach, a macroscopic kinetic model based on Monod kinetics for mammalian cell cultivation is developed and verified according to a general valid model validation workflow. The macroscopic model is verified and validated on the basis of four decision criteria (plausibility, sensitivity, accuracy and precision as well as equality). The process model workflow is subjected to a case study, comprising a Chinese hamster ovary fed-batch cultivation for the production of a monoclonal antibody. By performing the workflow, it was found that, based on design of experiments and Monte Carlo simulation, the maximum growth rate µmax exhibited the greatest influence on model variables such as viable cell concentration XV and product concentration. In addition, partial least squares regressions statistically evaluate the correlations between a higher µmax and a higher cell and product concentration, as well as a higher substrate consumption. Full article
(This article belongs to the Section Biological Processes and Systems)
►▼ Show Figures

Figure 1

17 pages, 4857 KiB  
Article
Development of Environmental Friendly Dust Suppressant Based on the Modification of Soybean Protein Isolate
by Hu Jin, Wen Nie, Yansong Zhang, Hongkun Wang, Haihan Zhang, Qiu Bao and Jiayi Yan
Processes 2019, 7(3), 165; https://doi.org/10.3390/pr7030165 - 20 Mar 2019
Cited by 60 | Viewed by 6317
Abstract
Aiming to further improve the dust suppression performance of the dust suppressant, the present study independently develops a new type of biodegradable environmentally-friendly dust suppressant. Specifically, the naturally occurring biodegradable soybean protein isolate (SPI) is selected as the main material, which is subject [...] Read more.
Aiming to further improve the dust suppression performance of the dust suppressant, the present study independently develops a new type of biodegradable environmentally-friendly dust suppressant. Specifically, the naturally occurring biodegradable soybean protein isolate (SPI) is selected as the main material, which is subject to an anionic surfactant, i.e., sodium dodecyl sulfonate (SDS) for modification with the presence of additives including carboxymethylcellulose sodium and methanesiliconic acid sodium. As a result, the SDS-SPI cementing dust suppressant is produced. The present study experimentally tests solutions with eight different dust suppressant concentrations under the same experimental condition, so as to evaluate their dust suppression performances. Key metrics considered include water retention capability, cementing power and dust suppression efficiency. The optimal concentration of dust suppressant solution is determined by collectively comparing these metrics. The experiments indicate that the optimal dust suppressant concentration is 3%, at which level the newly developed environmentally-friendly dust suppressant solution exhibits a decent dust suppression characteristic, with the water retention power reaching its peak level, and the corresponding viscosity being 12.96 mPa·s. This performance can generally meet the requirements imposed by coal mines. The peak efficiency of dust suppression can reach 92.13%. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were used to analyze the dust suppression mechanism of the developed dust suppressant. It was observed that a dense hardened shell formed on the surface of the pulverized coal particles sprayed with the dust suppressant. There is strong cementation between coal dust particles, and the cementation effect is better. This can effectively inhibit the re-entrainment of coal dust and reduce environmental pollution. Full article
(This article belongs to the Special Issue Renewable Polymers: Processing and Chemical Modifications)
►▼ Show Figures

Figure 1

15 pages, 1194 KiB  
Article
Evaluation of the Difficulties in the Internet of Things (IoT) with Multi-Criteria Decision-Making
by Buse Uslu, Tamer Eren, Şeyda Gür and Evrencan Özcan
Processes 2019, 7(3), 164; https://doi.org/10.3390/pr7030164 - 20 Mar 2019
Cited by 32 | Viewed by 5586
Abstract
The rapid development of technology has increased the desire of all to be on the Internet. The discovery that objects born of the Internet communicate with each other without external factors revealed, with the fourth industrial revolution, the concept of the Internet of [...] Read more.
The rapid development of technology has increased the desire of all to be on the Internet. The discovery that objects born of the Internet communicate with each other without external factors revealed, with the fourth industrial revolution, the concept of the Internet of Things (IoT). The communication of objects with each other means minimum labor and minimum cost for enterprises. Enterprises that want to transition to the Internet of Things face many difficulties. Identifying and correcting these difficulties can lead to both lost time and high cost. In this study, we investigated the difficulties encountered in the Internet of Things. As a result of the study, the degree of importance of the factors causing these difficulties was determined by multi-criteria decision-making methods and was presented to the enterprises. The main criteria, and the sub-criteria related to these main criteria, were determined. The main purpose of the enterprises transitioning to Industry 4.0 is the communication of things with each other. In this study, we aimed to determine which criteria caused difficulties in the transition to Industry 4.0. Then, the degree of importance of the criteria was determined using the analytic hierarchy process (AHP) and analytic network process (ANP) methods, in the multi-criteria decision-making. Through the study, we determined which criteria should be taken into consideration by the enterprises that want to transition to the Internet of Things. In this way, enterprises will be able to accelerate that transition by minimizing time and monetary loss. Full article
(This article belongs to the Special Issue Process Industry 4.0: Application Research to Small and Medium-Sized Enterprises (SMEs))
►▼ Show Figures

Figure 1

17 pages, 514 KiB  
Article
Application of Parameter Optimization to Search for Oscillatory Mass-Action Networks Using Python
by Veronica L. Porubsky and Herbert M. Sauro
Processes 2019, 7(3), 163; https://doi.org/10.3390/pr7030163 - 18 Mar 2019
Cited by 4 | Viewed by 3855
Abstract
Biological systems can be described mathematically to model the dynamics of metabolic, protein, or gene-regulatory networks, but locating parameter regimes that induce a particular dynamic behavior can be challenging due to the vast parameter landscape, particularly in large models. In the current work, [...] Read more.
Biological systems can be described mathematically to model the dynamics of metabolic, protein, or gene-regulatory networks, but locating parameter regimes that induce a particular dynamic behavior can be challenging due to the vast parameter landscape, particularly in large models. In the current work, a Pythonic implementation of existing bifurcation objective functions, which reward systems that achieve a desired bifurcation behavior, is implemented to search for parameter regimes that permit oscillations or bistability. A differential evolution algorithm progressively approximates the specified bifurcation type while performing a global search of parameter space for a candidate with the best fitness. The user-friendly format facilitates integration with systems biology tools, as Python is a ubiquitous programming language. The bifurcation–evolution software is validated on published models from the BioModels Database and used to search populations of randomly-generated mass-action networks for oscillatory dynamics. Results of this search demonstrate the importance of reaction enrichment to provide flexibility and enable complex dynamic behaviors, and illustrate the role of negative feedback and time delays in generating oscillatory dynamics. Full article
(This article belongs to the Special Issue Methods in Computational Biology)
►▼ Show Figures

Graphical abstract

24 pages, 37150 KiB  
Article
DEM Investigation of the Influence of Minerals on Crack Patterns and Mechanical Properties of Red Mudstone
by Shuai Zhang, Dongsheng Zhang, Qiang Zhao, Mingbo Chi, Wei Zhang and Wei Yu
Processes 2019, 7(3), 162; https://doi.org/10.3390/pr7030162 - 15 Mar 2019
Cited by 8 | Viewed by 3118
Abstract
Rocks are natural heterogeneous materials. It is common for a rock to have several kinds of minerals, which will have a significant effect on its mechanical behavior. The purpose of the numerical simulation study in this paper is to explore the effects of [...] Read more.
Rocks are natural heterogeneous materials. It is common for a rock to have several kinds of minerals, which will have a significant effect on its mechanical behavior. The purpose of the numerical simulation study in this paper is to explore the effects of minerals on the crack patterns and mechanical properties of rocks. First, the corresponding calculation model is established by using the discrete element method (DEM), whereby the mechanical parameters of the blocks and joints in the Tyson polygon procedure are fitted with the rock properties obtained in the laboratory. Then, various combination models of different mineral sizes and ratios are established to study the effects of mineral size, position, and ratio on the fracture distribution and mechanical properties of rock samples. The results indicate that with increased circle size of the center mineral and the mineral ratio, the elastic modulus and uniaxial compression strength (UCS) of the model gradually increase. The drop degree of post-peak stress decreases, and the integrity and bearing capacity increase. It is found that there is a quartic polynomial relationship between elastic modulus and mineral circle radius, with R2 ≥ 0.94. The minerals located in the crack propagation path will effectively block the crack and change the propagation direction. When the mineral position is close to the model boundaries, especially the lateral boundaries, it has a significant influence on the crack initiation position, causing crack initiation to occur at the upper boundary of the mineral circle and propagate to the middle of the model. With increased mineral percentage and small-size mineral circle proportion, the depth of extension of the crack from boundary to center is reduced, the crack has wide development in the boundary area, the number of central cracks in the rock specimen decreases, and the degree of fragmentation decreases. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
►▼ Show Figures

Figure 1

24 pages, 6877 KiB  
Article
Evaluating the Factors that are Affecting the Implementation of Industry 4.0 Technologies in Manufacturing MSMEs, the Case of Peru
by Chung-Jen Huang, Elisa Denisse Talla Chicoma and Yi-Hsien Huang
Processes 2019, 7(3), 161; https://doi.org/10.3390/pr7030161 - 15 Mar 2019
Cited by 20 | Viewed by 9067
Abstract
The micro, small, and medium enterprises (MSMEs) sector plays a very crucial role in the economic and social development of Peru. Unfortunately, the tough access to the use of technologies is one of the weaknesses of this type of enterprises, which implies a [...] Read more.
The micro, small, and medium enterprises (MSMEs) sector plays a very crucial role in the economic and social development of Peru. Unfortunately, the tough access to the use of technologies is one of the weaknesses of this type of enterprises, which implies a low technological intensity production, according to the new technological trends. This study analyzes the factors that are affecting the implementation of Industry 4.0 technologies in Peruvian micro, small, and medium enterprises. According to the findings from the semi-structured interviews, it has identified four factors that respond to the main question of this research—lack of advanced technology, lack of financial investment, poor management vision, and lack of skilled workers. Data from 49 enterprises from the manufacturing sector were used for the assessment. The surveys conducted on business managers were evaluated using a multi-criterion decision-making method by the analytic hierarchy process. The findings of the study generate some recommendations that could be beneficial for the sectors involved with micro, small, and medium enterprises in Peru. Full article
(This article belongs to the Special Issue Process Industry 4.0: Application Research to Small and Medium-Sized Enterprises (SMEs))
►▼ Show Figures

Figure 1

15 pages, 2083 KiB  
Article
Study of Various Aqueous and Non-Aqueous Amine Blends for Hydrogen Sulfide Removal from Natural Gas
by Usman Shoukat, Diego D. D. Pinto and Hanna K. Knuutila
Processes 2019, 7(3), 160; https://doi.org/10.3390/pr7030160 - 15 Mar 2019
Cited by 40 | Viewed by 6024
Abstract
Various novel amine solutions both in aqueous and non-aqueous [monoethylene glycol (MEG)/triethylene glycol(TEG)] forms have been studied for hydrogen sulfide (H2S) absorption. The study was conducted in a custom build experimental setup at temperatures relevant to subsea operation conditions and atmospheric [...] Read more.
Various novel amine solutions both in aqueous and non-aqueous [monoethylene glycol (MEG)/triethylene glycol(TEG)] forms have been studied for hydrogen sulfide (H2S) absorption. The study was conducted in a custom build experimental setup at temperatures relevant to subsea operation conditions and atmospheric pressure. Liquid phase absorbed H2S, and amine concentrations were measured analytically to calculate H2S loading (mole of H2S/mole of amine). Maximum achieved H2S loadings as the function of pKa, gas partial pressure, temperature and amine concentration are presented. Effects of solvent type on absorbed H2S have also been discussed. Several new solvents showed higher H2S loading as compared to aqueous N-Methyldiethanolamine (MDEA) solution which is the current industrial benchmark compound for selective H2S removal in natural gas sweetening process. Full article
(This article belongs to the Special Issue Gas Capture Processes)
►▼ Show Figures

Graphical abstract

12 pages, 6508 KiB  
Article
Application of VES Acid System on Carbonate Rocks with Uninvaded Matrix for Acid Etching and Fracture Propagation
by Yahong Wu, Weiwei Luo, Xunan Jia, Haoqing Fang, Honggang Wang and Shuai Yu
Processes 2019, 7(3), 159; https://doi.org/10.3390/pr7030159 - 15 Mar 2019
Cited by 1 | Viewed by 3590
Abstract
We investigated the performance of viscoelastic surfactant (VES) solution when applied in treatment on the uninvaded matrix using core flooding tests to analyze the impact of VES/CaCl2 concentration on fluid viscosity. In this paper, core samples from Tahe carbonate reservoir, with an [...] Read more.
We investigated the performance of viscoelastic surfactant (VES) solution when applied in treatment on the uninvaded matrix using core flooding tests to analyze the impact of VES/CaCl2 concentration on fluid viscosity. In this paper, core samples from Tahe carbonate reservoir, with an average permeability less than 0.02 × 10−3 μm−2 and a small average porosity in the range of approximately 0.04–5.24% are used in the experiments. Computed tomography (CT) scanning is used to provide a detailed description of inner structure variation of cores after the acid system treatment. The results confirmed that a large pressure difference contributed to fracture propagation and the relative permeability of water increased significantly after the treatment. It was also found that higher concentrations of VES and/or Ca2+ induced higher viscosity and a stronger fracturing effect, while a lower concentration improved the reaction rates and etching effect, generating small worm holes inside the core. Foam in-situ produced during the etching process is the major contributor to the fluid viscosity enhancement. The permeability of fracture formed on the surface of the core is more sensitive to the confining pressure. These findings can help better understand the rheological properties of the acid system and etching and fracturing mechanisms during acid treatment, and which provides instructions for field implementation. Full article
(This article belongs to the Special Issue Advances in Experimental and Theoretical Studies of Fluid Flow and Solute Transport in Porous Media)
►▼ Show Figures

Figure 1

18 pages, 2210 KiB  
Article
Implementation of Maximum Power Point Tracking Based on Variable Speed Forecasting for Wind Energy Systems
by Yujia Zhang, Lei Zhang and Yongwen Liu
Processes 2019, 7(3), 158; https://doi.org/10.3390/pr7030158 - 15 Mar 2019
Cited by 35 | Viewed by 4196
Abstract
In order to precisely control the wind power generation systems under nonlinear variable wind velocity, this paper proposes a novel maximum power tracking (MPPT) strategy for wind turbine systems based on a hybrid wind velocity forecasting algorithm. The proposed algorithm adapts the bat [...] Read more.
In order to precisely control the wind power generation systems under nonlinear variable wind velocity, this paper proposes a novel maximum power tracking (MPPT) strategy for wind turbine systems based on a hybrid wind velocity forecasting algorithm. The proposed algorithm adapts the bat algorithm and improved extreme learning machine (BA-ELM) for forecasting wind speed to alleviate the slow response of anemometers and sensors, considering that the change of wind speed requires a very short response time. In the controlling strategy, to optimize the output power, a state feedback control technique is proposed to achieve the rotor flux and rotor speed tracking purpose based on MPPT algorithm. This method could decouple the current and voltage of induction generator to track the reference of stator current and flux linkage. By adjusting the wind turbine mechanical speed, the wind energy system could operate at the optimal rotational speed and achieve the maximal power. Simulation results verified the effectiveness of the proposed technique. Full article
(This article belongs to the Special Issue Advances in Theoretical and Computational Energy Optimization Processes)
►▼ Show Figures

Figure 1

18 pages, 2104 KiB  
Article
Viscoelastic Properties of Crosslinked Chitosan Films
by Joseph Khouri, Alexander Penlidis and Christine Moresoli
Processes 2019, 7(3), 157; https://doi.org/10.3390/pr7030157 - 14 Mar 2019
Cited by 41 | Viewed by 6334
Abstract
Chitosan films containing citric acid were prepared using a multi-step process called heterogeneous crosslinking. These films were neutralized first, followed by citric acid addition, and then heat treated at 150 °C/0.5 h in order to potentially induce covalent crosslinking. The viscoelastic storage modulus, [...] Read more.
Chitosan films containing citric acid were prepared using a multi-step process called heterogeneous crosslinking. These films were neutralized first, followed by citric acid addition, and then heat treated at 150 °C/0.5 h in order to potentially induce covalent crosslinking. The viscoelastic storage modulus, E′, and tanδ were studied using dynamic mechanical analysis, and compared with neat and neutralized films to elucidate possible crosslinking with citric acid. Films were also prepared with various concentrations of a model crosslinker, glutaraldehyde, both homogeneously and heterogeneously. Based on comparisons of neutralized films with films containing citric acid, and between citric acid films either heat treated or not heat treated, it appeared that the interaction between chitosan and citric acid remained ionic without covalent bond formation. No strong evidence of a glass transition from the tanδ plots was observable, with the possible exception of heterogeneously crosslinked glutaraldehyde films at temperatures above 200 °C. Full article
(This article belongs to the Special Issue Renewable Polymers: Processing and Chemical Modifications)
►▼ Show Figures

Graphical abstract

14 pages, 296 KiB  
Review
Some Advances in Supercritical Fluid Extraction for Fuels, Bio-Materials and Purification
by Yizhak Marcus
Processes 2019, 7(3), 156; https://doi.org/10.3390/pr7030156 - 13 Mar 2019
Cited by 13 | Viewed by 5495
Abstract
Supercritical fluids are used for the extraction of desired ingredients from natural materials, but also for the removal of undesired and harmful ingredients. In this paper, the pertinent physical and chemical properties of supercritical water, methanol, ethanol, carbon dioxide, and their mixtures are [...] Read more.
Supercritical fluids are used for the extraction of desired ingredients from natural materials, but also for the removal of undesired and harmful ingredients. In this paper, the pertinent physical and chemical properties of supercritical water, methanol, ethanol, carbon dioxide, and their mixtures are provided. The methodologies used with supercritical fluid extraction are briefly dealt with. Advances in the application of supercritical extraction to fuels, the gaining of antioxidants and other useful items from biomass, the removal of undesired ingredients or contaminants, and the preparation of nanosized particles of drugs are described. Full article
(This article belongs to the Special Issue Advances in Supercritical Fluid Extraction)
23 pages, 8001 KiB  
Article
Experimental Development of Coal-Like Material with Solid-Gas Coupling for Quantitative Simulation Tests of Coal and Gas Outburst Occurred in Soft Coal Seams
by Xingkai Wang, Wenbing Xie, Zhili Su and Qingteng Tang
Processes 2019, 7(3), 155; https://doi.org/10.3390/pr7030155 - 13 Mar 2019
Cited by 8 | Viewed by 2944
Abstract
Solid-gas coupling coal-like materials are essential for simulating coal and gas outbursts and the long-term safety study of CO2 sequestration in coal. However, reported materials still differ substantially from natural coal in mechanical, deformation and gaseous properties; the latter two aspects are [...] Read more.
Solid-gas coupling coal-like materials are essential for simulating coal and gas outbursts and the long-term safety study of CO2 sequestration in coal. However, reported materials still differ substantially from natural coal in mechanical, deformation and gaseous properties; the latter two aspects are common not considered. There is a lack of a definite and quantitative preparation method of coal-like materials with high similarity for future reference. Here, 25 groups of raw material ratios were designed in the orthogonal experiment using uniaxial compression, shearing and adsorption/desorption tests. Experiment results indicated that the coal-like materials were highly similar to soft coals in properties mentioned above. And range analysis revealed the key influencing factors of each mechanical index. The gypsum/petrolatum ratio controls the density, compressive strength, elastic modulus, cohesion and deformation characteristic. The coarse/fine coal powder (1–2 and 0–0.5 mm) controls the internal friction angle and is the secondary controlling factor for compressive strength and elastic modulus. The effect of coal particle size on the sample strength was studied using scanning electron microscope (SEM). When the gypsum/petrolatum ratio increased, the deformation characteristics changed from ductile to brittle. The different failure modes in the samples were revealed. The coal powder content is a key in the gas adsorption/desorption properties and an empirical formula for estimating the adsorption capacity was established. Based on the range analysis of experimental results, a multiple linear regression model of the mechanical parameters and their key influencing factors was obtained. Finally, a composition closely resembling the natural coal was determined, which differs by only 0.47–7.41% in all parameters except porosity (11.76%). Possible improvements and extension to similar materials are discussed. The findings of this study can help for better understanding of coal and gas outburst mechanism and stability of CO2 sequestration in soft coal seams. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
►▼ Show Figures

Graphical abstract

18 pages, 2982 KiB  
Article
Ascertainment of Surfactin Concentration in Bubbles and Foam Column Operated in Semi-Batch
by Rafael Firmani Perna, Maria Carolina Pereira Gonçalves and Cesar Costapinto Santana
Processes 2019, 7(3), 154; https://doi.org/10.3390/pr7030154 - 13 Mar 2019
Cited by 5 | Viewed by 3448
Abstract
This paper describes a mathematical model for the convection, diffusion, and balance phenomena for predicting the depletion curves, i.e., variations in the timed surface-active molecule concentration for fractionation processes in bubbles and foam column, operated in semi-batch. The model was applied for the [...] Read more.
This paper describes a mathematical model for the convection, diffusion, and balance phenomena for predicting the depletion curves, i.e., variations in the timed surface-active molecule concentration for fractionation processes in bubbles and foam column, operated in semi-batch. The model was applied for the purification of the surfactin solution and the results were compared with experimental data. Gibbs adsorption curves were obtained for the biosurfactant at different temperatures, and then adjusted with estimated parameters, according to the Langmuir adsorption model. The gas bubble sizes were optically determined. The isotherm adsorption parameters and bubble average diameter are crucial for the attainment of the depletion curves, generated by the model described. The results demonstrate that the process is most effective when operating a column with reduced gas flow and low initial concentration. A top product with two or thirty times greater concentration than the initial one was achieved and the highest biosurfactant concentrations were attained for higher operating temperatures. It was also observed that bubble diameter increased with a higher gas flow. The adjustment obtained for the adsorption curves of Gibbs was satisfactory. Therefore, there was evidence that surfactin molecules adsorb in monolayers in the liquid–gas interface. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control of Chemical Processes)
►▼ Show Figures

Figure 1

20 pages, 1468 KiB  
Article
Drivers and Barriers in Using Industry 4.0: A Perspective of SMEs in Romania
by Mirela Cătălina Türkeș, Ionica Oncioiu, Hassan Danial Aslam, Andreea Marin-Pantelescu, Dan Ioan Topor and Sorinel Căpușneanu
Processes 2019, 7(3), 153; https://doi.org/10.3390/pr7030153 - 12 Mar 2019
Cited by 144 | Viewed by 11528
Abstract
Considering the worldwide evolutionary stage of Industry 4.0, this study wants to fill in a lack of information and decision-making, trying to answer a question about the level of preparation of Romanian Small and Medium-sized Enterprises (SMEs) regarding the implementation of the new [...] Read more.
Considering the worldwide evolutionary stage of Industry 4.0, this study wants to fill in a lack of information and decision-making, trying to answer a question about the level of preparation of Romanian Small and Medium-sized Enterprises (SMEs) regarding the implementation of the new technology. The main purpose of this article is to identify the opinions and perceptions of SME managers in Romania on the drivers and barriers of implementing Industry 4.0 technology for business development. The research method used in the study was analyzed by sampling using the questionnaire as a data collection tool. It includes closed questions, measured with a nominal and orderly scale. 176 managers provided complete and useful answers to this research. The collected data were analyzed with the Statistical Package for the Social Sciences (SPSS) package using frequency tables, contingency tables, and main component analysis. Major contributions from research have highlighted the fact that Romania is in a full transition process from industry 2.0 to industry 4.0. There was also a high level of knowledge of the new Industry 4.0 technology, and a desire to implement it in the Romanian SMEs, as well as the low level of resources needed to implement it. Full article
(This article belongs to the Special Issue Process Industry 4.0: Application Research to Small and Medium-Sized Enterprises (SMEs))
►▼ Show Figures

Figure 1

21 pages, 5666 KiB  
Article
An Intelligent Fault Diagnosis Method Using GRU Neural Network towards Sequential Data in Dynamic Processes
by Jing Yuan and Ying Tian
Processes 2019, 7(3), 152; https://doi.org/10.3390/pr7030152 - 12 Mar 2019
Cited by 34 | Viewed by 5304
Abstract
Intelligent fault diagnosis is a promising tool to deal with industrial big data due to its ability in rapidly and efficiently processing collected signals and providing accurate diagnosis results. In traditional static intelligent diagnosis methods, however, the correlation between sequential data is neglected, [...] Read more.
Intelligent fault diagnosis is a promising tool to deal with industrial big data due to its ability in rapidly and efficiently processing collected signals and providing accurate diagnosis results. In traditional static intelligent diagnosis methods, however, the correlation between sequential data is neglected, and the features of raw data cannot be effectively extracted. Therefore, this paper proposes a three-stage fault diagnosis method based on a gate recurrent unit (GRU) network. The raw data is divided into several sequence units by first using a moving horizon as the input of GRU. In this way, we can intercept the sequence to get information as needed. Then, the GRU deep network is established through batch normalization (BN) algorithm to extract the dynamic feature from the sequence units effectively. Finally, the softmax regression is employed to classify faults based on dynamic features. Thus, the diagnosis result is obtained with a probabilistic explanation. Two chemical processes validate the proposed method: Tennessee Eastman (TE) benchmark process as well as para-xylene (PX) oxidation process. In the case of TE, the diagnosis results demonstrate the proposed method is superior to conventional methods. Furthermore, in the case of PX oxidation, the result shows that the proposed method also has an exceptional effect with a little historical data. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control of Chemical Processes)
►▼ Show Figures

Figure 1

11 pages, 3784 KiB  
Discussion
Data-Mining for Processes in Chemistry, Materials, and Engineering
by Hao Li, Zhien Zhang and Zhe-Ze Zhao
Processes 2019, 7(3), 151; https://doi.org/10.3390/pr7030151 - 11 Mar 2019
Cited by 39 | Viewed by 6292
Abstract
With the rapid development of machine learning techniques, data-mining for processes in chemistry, materials, and engineering has been widely reported in recent years. In this discussion, we summarize some typical applications for process optimization, design, and evaluation of chemistry, materials, and engineering. Although [...] Read more.
With the rapid development of machine learning techniques, data-mining for processes in chemistry, materials, and engineering has been widely reported in recent years. In this discussion, we summarize some typical applications for process optimization, design, and evaluation of chemistry, materials, and engineering. Although the research and application targets are various, many important common points still exist in their data-mining. We then propose a generalized strategy based on the philosophy of data-mining, which should be applicable for the design and optimization targets for processes in various fields with both scientific and industrial purposes. Full article
(This article belongs to the Special Issue Process Modelling and Simulation)
►▼ Show Figures

Figure 1

13 pages, 2218 KiB  
Article
Synthesis of Porous Fe/C Bio-Char Adsorbent for Rhodamine B from Waste Wood: Characterization, Kinetics and Thermodynamics
by Yao Zhang, Zhichao Lou, Chaochao Wang, Weikai Wang and Jiabin Cai
Processes 2019, 7(3), 150; https://doi.org/10.3390/pr7030150 - 09 Mar 2019
Cited by 8 | Viewed by 3596
Abstract
In the past decades, dyes waste waters produced from industries have become a major source of environmental pollution causing the destruction of aquatic communities in the ecosystem and greatly threatened human health. Herein, a novel magnetic adsorbent was synthesized by carbonizing iron (III) [...] Read more.
In the past decades, dyes waste waters produced from industries have become a major source of environmental pollution causing the destruction of aquatic communities in the ecosystem and greatly threatened human health. Herein, a novel magnetic adsorbent was synthesized by carbonizing iron (III) 2,4-pentanedionate (Fe(acac)3) pre-enriched forestry waste wood at a pyrolysis temperature of 1000 °C. The characterization of the adsorbent conducted via SEM, EDS, VSM, XRD, XPS, and FT-IR spectroscopy. The adsorption trend followed the pseudo-second order kinetics model. The corresponding adsorption performance was efficient with an equilibrium time of only 1 min. Affect factors on the adsorption performance, such as adsorbent dosage, contact time and temperature, were investigated. The magnetic bio-char showed a high adsorption capacity and an efficient adsorption toward RhB, implying great potential application in the treatment of colored wastewaters. Full article
(This article belongs to the Special Issue Wastewater Treatment Processes)
►▼ Show Figures

Figure 1

26 pages, 7441 KiB  
Article
Experimental Investigation of Pore Structure and Movable Fluid Traits in Tight Sandstone
by Dengke Liu, Wei Sun and Dazhong Ren
Processes 2019, 7(3), 149; https://doi.org/10.3390/pr7030149 - 08 Mar 2019
Cited by 20 | Viewed by 3690
Abstract
Whether the variation of pore structures and movable fluid characteristics enhance, deteriorate, or have no influence on reservoir quality has long been disputed, despite their considerable implications for hydrocarbon development in tight sandstone reservoirs. To elucidate these relationships, this study systematically analyzes pore [...] Read more.
Whether the variation of pore structures and movable fluid characteristics enhance, deteriorate, or have no influence on reservoir quality has long been disputed, despite their considerable implications for hydrocarbon development in tight sandstone reservoirs. To elucidate these relationships, this study systematically analyzes pore structures qualitatively and quantitatively by various kinds of direct observations, indirect methods, and imaging simulations. We found that the uncertainty of porosity measurements, caused by the complex pore-throat structure, needs to be eliminated to accurately characterize reservoir quality. Bulk water was more easily removed, while surface water tended to be retained in the pores, and the heterogeneity of pore structures was caused by the abundance of tiny pores. The rates of water saturation reduction in macropores are faster than those for tiny pores, and sandstones with poor reservoir quality show no marked descending of lower limits of movable pore radius, indicating that the movable fluid would advance exempted from the larger pores. This study suggests that the deterioration of reservoir quality is strongly affected by the reduction of larger pores and the aqueous phases tended to remain in the tiny pores in the forms of surface water. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
►▼ Show Figures

Figure 1

20 pages, 1993 KiB  
Article
Multiphase Open Phase Processes Differential Equations
by Nikolay A. Charykov, Marina V. Charykova, Konstantin N. Semenov, Victor A. Keskinov, Alexey V. Kurilenko, Zhassulan K. Shaimardanov and Botagoz K. Shaimardanova
Processes 2019, 7(3), 148; https://doi.org/10.3390/pr7030148 - 08 Mar 2019
Cited by 7 | Viewed by 3379
Abstract
The thermodynamic approach for the description of multiphase open phase processes is developed based on van der Waals equation in the metrics of Gibbs and incomplete Gibbs potentials. Examples of thermodynamic modeling of the multiphase and multicomponent A3B5 systems (In-Ga-As-Sb [...] Read more.
The thermodynamic approach for the description of multiphase open phase processes is developed based on van der Waals equation in the metrics of Gibbs and incomplete Gibbs potentials. Examples of thermodynamic modeling of the multiphase and multicomponent A3B5 systems (In-Ga-As-Sb and In-P-As-Sb) and Na+, K+, Mg2+, Ca2+//Cl−, SO42−-H2O water–salt system are presented. Topological isomorphism of different type phase diagrams is demonstrated. Full article
(This article belongs to the Special Issue Multiphase Reaction Engineering, Reactors and Processes )
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-59
Previous Issue
Next Issue
Back to TopTop