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Processes, Volume 6, Issue 12 (December 2018) – 36 articles

Cover Story (view full-size image): Pore channels in silica-based membranes with pore sizes in the range of several angstroms, can act as a molecular sieve to separate gas mixtures of different molecular diameters. For instance, helium and hydrogen with molecular diameters smaller than their pore size could permeate across the silica-based membrane, while gases with larger molecular diameters, such as argon or carbon dioxide, fail to permeate through the membrane. Therefore, pore size is of great importance for silica-based membranes. In this paper, we have developed a method which employs the experimental activation energy of gas permeation to estimate pore size distribution. View this paper.
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24 pages, 6440 KiB  
Article
A General Model for Estimating Emissions from Integrated Power Generation and Energy Storage. Case Study: Integration of Solar Photovoltaic Power and Wind Power with Batteries
by Ian Miller, Emre Gençer and Francis M. O’Sullivan
Processes 2018, 6(12), 267; https://doi.org/10.3390/pr6120267 - 18 Dec 2018
Cited by 28 | Viewed by 6516
Abstract
The penetration of renewable power generation is increasing at an unprecedented pace. While the operating greenhouse gas (GHG) emissions of photovoltaic (PV) and wind power are negligible, their upstream emissions are not. The great challenge with the deployment of renewable power generators is [...] Read more.
The penetration of renewable power generation is increasing at an unprecedented pace. While the operating greenhouse gas (GHG) emissions of photovoltaic (PV) and wind power are negligible, their upstream emissions are not. The great challenge with the deployment of renewable power generators is their intermittent and variable nature. Current electric power systems balance these fluctuations primarily using natural gas fired power plants. Alternatively, these dynamics could be handled by the integration of energy storage technologies to store energy during renewable energy availability and discharge when needed. In this paper, we present a model for estimating emissions from integrated power generation and energy storage. The model applies to emissions of all pollutants, including greenhouse gases (GHGs), and to all storage technologies, including pumped hydroelectric and electrochemical storage. As a case study, the model is used to estimate the GHG emissions of electricity from systems that couple photovoltaic and wind generation with lithium-ion batteries (LBs) and vanadium redox flow batteries (VFBs). To facilitate the case study, we conducted a life cycle assessment (LCA) of photovoltaic (PV) power, as well as a synthesis of existing wind power LCAs. The PV LCA is also used to estimate the emissions impact of a common PV practice that has not been comprehensively analyzed by LCA—solar tracking. The case study of renewables and battery storage indicates that PV and wind power remain much less carbon intensive than fossil-based generation, even when coupled with large amounts of LBs or VFBs. Even the most carbon intensive renewable power analyzed still emits only ~25% of the GHGs of the least carbon intensive mainstream fossil power. Lastly, we find that the pathway to minimize the GHG emissions of power from a coupled system depends upon the generator. Given low-emission generation (<50 gCO2e/kWh), the minimizing pathway is the storage technology with lowest production emissions (VFBs over LBs for our case study). Given high-emission generation (>200 gCO2e/kWh), the minimizing pathway is the storage technology with highest round-trip efficiency (LBs over VFBs). Full article
(This article belongs to the Special Issue Modeling and Simulation of Energy Systems)
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13 pages, 1763 KiB  
Article
A Green Process for the Extraction and Purification of Hesperidin from Mexican Lime Peel (Citrus aurantifolia Swingle) that is Extendible to the Citrus Genus
by J. Daniel Padilla de la Rosa, Priscilla Ruiz-Palomino, Enrique Arriola-Guevara, Jorge García-Fajardo, Georgina Sandoval and Guadalupe M. Guatemala-Morales
Processes 2018, 6(12), 266; https://doi.org/10.3390/pr6120266 - 15 Dec 2018
Cited by 30 | Viewed by 8102
Abstract
The processing of Mexican limes generates great amounts of peel as a by-product. Lime peel is mainly rich in the flavonoid hesperidin, whose bioactivity is oriented mainly to cardiovascular diseases and cancer. The purpose of this work was to develop a green process [...] Read more.
The processing of Mexican limes generates great amounts of peel as a by-product. Lime peel is mainly rich in the flavonoid hesperidin, whose bioactivity is oriented mainly to cardiovascular diseases and cancer. The purpose of this work was to develop a green process for the extraction and purification of hesperidin from Mexican lime peel. The extraction of hesperidin was investigated on a laboratory scale by varying the solvent composition and the solid-to-solvent ratio, and then scaling this process (volume: 20 L). Next, a purification process using adsorption resins was assessed: first through static tests to determine the adsorption efficiency with two resins (FPX66, EXA118), and then on a packed column with 80 mL of resin at 25 °C. Lab-scale extraction showed that the best conditions were a solid-to-solvent ratio of 0.33 g/mL and 60% ethanol. After using these conditions at pilot scale and concentrating the solution, the hesperidin content of the extract was 0.303 mg/mL. Through static tests, higher adsorption efficiencies were achieved with the EXA-118 resin and diluted extract (4:6 ratio with 10% dimethylsulfoxide, (DMSO)). Finally, the purification process on a packed column from the diluted extract (hesperidin concentration of 0.109 mg/mL) had a mean recovery efficiency of almost 90%. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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14 pages, 2497 KiB  
Article
Effect of Control Horizon in Model Predictive Control for Steam/Water Loop in Large-Scale Ships
by Shiquan Zhao, Anca Maxim, Sheng Liu, Robin De Keyser and Clara Ionescu
Processes 2018, 6(12), 265; https://doi.org/10.3390/pr6120265 - 14 Dec 2018
Cited by 18 | Viewed by 4979
Abstract
This paper presents an extensive analysis of the properties of different control horizon sets in an Extended Prediction Self-Adaptive Control (EPSAC) model predictive control framework. Analysis is performed on the linear multivariable model of the steam/water loop in large-scale watercraft/ships. The results indicate [...] Read more.
This paper presents an extensive analysis of the properties of different control horizon sets in an Extended Prediction Self-Adaptive Control (EPSAC) model predictive control framework. Analysis is performed on the linear multivariable model of the steam/water loop in large-scale watercraft/ships. The results indicate that larger control horizon values lead to better loop performance, at the cost of computational complexity. Hence, it is necessary to find a good trade-off between the performance of the system and allocated or available computational complexity. In this original work, this problem is explicitly treated as an optimization task, leading to the optimal control horizon sets for the steam/water loop example. Based on simulation results, it is concluded that specific tuning of control horizons outperforms the case when only a single valued control horizon is used for all the loops. Full article
(This article belongs to the Special Issue Optimization for Control, Observation and Safety)
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16 pages, 726 KiB  
Article
Analysis of the Difficulties of SMEs in Industry 4.0 Applications by Analytical Hierarchy Process and Analytical Network Process
by Ali Sevinç, Şeyda Gür and Tamer Eren
Processes 2018, 6(12), 264; https://doi.org/10.3390/pr6120264 - 12 Dec 2018
Cited by 78 | Viewed by 8402
Abstract
The concept of Industry 4.0 is seen as a recent paradigm in the manufacturing sector. The use of new production and management technologies required by the concept of Industry 4.0 is very important for small enterprises in order to keep up with the [...] Read more.
The concept of Industry 4.0 is seen as a recent paradigm in the manufacturing sector. The use of new production and management technologies required by the concept of Industry 4.0 is very important for small enterprises in order to keep up with the competition. However, most enterprises look at these requirements in a negative way. This study analyzes the propulsion forces of Industry 4.0 adopted in small and medium enterprises. By analyzing the difficulties in the transition process of small and medium-sized enterprises (SMEs) to Industry 4.0, the company contributes to the determination of strategic steps taking these results into consideration. This will facilitate the transition of enterprises to Industry 4.0 and progress can be made towards efficient use of resources. A hierarchical structure was established under the four main criteria of innovation, organization, environmental, and financial aspects, and the relative weight of these criteria and sub-criteria were calculated. The surveys conducted on business managers were evaluated using multi-criteria decision-making methods by the analytic hierarchy process method and the analytic network process. At the same time, the interaction between these criteria was taken into consideration and the criteria were re-evaluated by the analytical network process method. The results of the two methods seem to support each other. Full article
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13 pages, 1634 KiB  
Article
Low-Temperature Steam Reforming of Natural Gas after LPG-Enrichment with MFI Membranes
by Dominik Seeburg, Dongjing Liu, Radostina Dragomirova, Hanan Atia, Marga-Martina Pohl, Hadis Amani, Gabriele Georgi, Stefanie Kreft and Sebastian Wohlrab
Processes 2018, 6(12), 263; https://doi.org/10.3390/pr6120263 - 12 Dec 2018
Cited by 6 | Viewed by 5589
Abstract
Low-temperature hydrogen production from natural gas via steam reforming requires novel processing concepts as well as stable catalysts. A process using zeolite membranes of the type MFI (Mobile FIve) was used to enrich natural gas with liquefied petroleum gas (LPG) alkanes (in particular, [...] Read more.
Low-temperature hydrogen production from natural gas via steam reforming requires novel processing concepts as well as stable catalysts. A process using zeolite membranes of the type MFI (Mobile FIve) was used to enrich natural gas with liquefied petroleum gas (LPG) alkanes (in particular, propane and n-butane), in order to improve the hydrogen production from this mixture at a reduced temperature. For this purpose, a catalyst precursor based on Rh single-sites (1 mol% Rh) on alumina was transformed in situ to a Rh1/Al2O3 catalyst possessing better performance capabilities compared with commercial catalysts. A wet raw natural gas (57.6 vol% CH4) was fully reformed at 650 °C, with 1 bar absolute pressure over the Rh1/Al2O3 at a steam to carbon ratio S/C = 4, yielding 74.7% H2. However, at 350 °C only 21 vol% H2 was obtained under these conditions. The second mixture, enriched with LPG, was obtained from the raw gas after the membrane process and contained only 25.2 vol% CH4. From this second mixture, 47 vol% H2 was generated at 350 °C after steam reforming over the Rh1/Al2O3 catalyst at S/C = 4. At S/C = 1 conversion was suppressed for both gas mixtures. Single alkane reforming of C2–C4 showed different sensitivity for side reactions, e.g., methanation between 350 and 650 °C. These results contribute to ongoing research in the field of low-temperature hydrogen release from natural gas alkanes for fuel cell applications as well as for pre-reforming processes. Full article
(This article belongs to the Special Issue Novel Membrane Technologies for Traditional Industrial Processes)
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15 pages, 2825 KiB  
Article
Polyphenols from Red Vine Leaves Using Alternative Processing Techniques
by Simone Bachtler and Hans-Jörg Bart
Processes 2018, 6(12), 262; https://doi.org/10.3390/pr6120262 - 12 Dec 2018
Cited by 8 | Viewed by 3438
Abstract
The extraction kinetics of polyphenols, which are leached from red vine leaves, are studied and evaluated using a laboratory robot and nonconventional processing techniques such as ultrasonic (US)-, microwave (MW)-, and pulsed electric field (PEF)-assisted extraction processes. The robotic high-throughput screening reveals optimal [...] Read more.
The extraction kinetics of polyphenols, which are leached from red vine leaves, are studied and evaluated using a laboratory robot and nonconventional processing techniques such as ultrasonic (US)-, microwave (MW)-, and pulsed electric field (PEF)-assisted extraction processes. The robotic high-throughput screening reveals optimal extraction conditions at a pH value of 2.5, a temperature of 56 °C, and a solvent mixture of methanol:water:HCl of 50:49:1 v/v/v. Nonconventional processing techniques, such as MW- and US-assisted extraction, have the fastest kinetics and produce the highest polyphenol yield. The non-conventional techniques yield is 2.29 g/L (MW) resp. 2.47 g/L (US) for particles that range in size from 450 to 2000 µm and 2.20 g/L (MW) resp. 2.05 g/L (US) for particles that range from 2000 to 4000 µm. PEF has the lowest yield of polyphenols with 0.94 g/L (450–2000 µm), resp. 0.64 g/L (2000–4000 µm) in comparison to 1.82 g/L (2000 to 4000 µm) in a standard stirred vessel (50 °C). When undried red vine leaves (2000 to 4000 µm) are used the total phenol content is 1.44 g/L with PEF. Full article
(This article belongs to the Special Issue Microwave Applications in Chemical Engineering)
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22 pages, 7241 KiB  
Article
Numerical Simulations of Dynamic Pipeline-Vessel Response on a Deepwater S-Laying Vessel
by Yingfei Zan, Lihao Yuan, Kuo Huang, Song Ding and Zhaohui Wu
Processes 2018, 6(12), 261; https://doi.org/10.3390/pr6120261 - 11 Dec 2018
Cited by 16 | Viewed by 4960
Abstract
The dynamic action induced on offshore pipelines by deepwater S-laying is significant, and directly determines how the pipeline structures are designed and installed. Existing research has not fully investigated the benefits of coupling models of pipeline and pipelaying vessel motions. Therefore, this paper [...] Read more.
The dynamic action induced on offshore pipelines by deepwater S-laying is significant, and directly determines how the pipeline structures are designed and installed. Existing research has not fully investigated the benefits of coupling models of pipeline and pipelaying vessel motions. Therefore, this paper presents a coupled time-domain numerical model for examining the effect of coupled dynamic reactions. The coupled model takes into account the motion of the pipelaying vessel, surface waves, ocean currents, wind forces, pipeline dynamics, and contact between the rollers and the pipeline. A proportional, integral, derivative (PID) controller was used for simulating the control of the pipelaying vessel. The hydrodynamic forces that the pipeline experiences were modeled using the Morison equation. The model was solved using Newmark’s method and verified using OrcaFlex software. The model was then used to analyze practical operations: the laying of a 22″ gas export pipeline on the seabed by the pipelaying vessel HYSY201 in the Pingbei-Huangyan gas fields in the East China Sea. The effects of coupled factors on pipelaying vessel motions and pipeline dynamics were approximated. These effects included configurations, axial tensions, and bending moments. The results show a significant connection between the dynamic responses of the pipelines and pipelaying vessel motions. Full article
(This article belongs to the Section Process Control and Monitoring)
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19 pages, 284 KiB  
Article
Business Model Innovation of Industry 4.0 Solution Providers Towards Customer Process Innovation
by Julian Marius Müller and Simon Däschle
Processes 2018, 6(12), 260; https://doi.org/10.3390/pr6120260 - 10 Dec 2018
Cited by 49 | Viewed by 8476
Abstract
The article investigates the role of business model innovation by Industry 4.0 solution providers and their impact on process innovation of their customers. Industry 4.0 solution providers are hereby seen as the enablers and providers of Industry 4.0 technologies, which provide access to [...] Read more.
The article investigates the role of business model innovation by Industry 4.0 solution providers and their impact on process innovation of their customers. Industry 4.0 solution providers are hereby seen as the enablers and providers of Industry 4.0 technologies, which provide access to several potentials of Industry 4.0 technologies to their customers. In particular, the role of small and medium-sized enterprises (SMEs) that provide solutions that are based on Industry 4.0 technologies for their customers are investigated, which in turn can improve and innovate their own processes. Frist, the article presents an overview of the current state of research and a brief theoretical background. Second, the article bases its findings on an empirical study of 111 Industry 4.0 providers from Germany that are SMEs. Analyzing the results of questionnaires, correlations between Industry 4.0 solutions and two perspectives are examined: benefits for the solution providers and benefits for process improvements and innovations of the customers. Subsequently, the article discusses these findings, closing the article with both managerial and research implications. Full article
15 pages, 858 KiB  
Article
Receding Horizon Optimization of Wind Farm Active Power Distribution with Power Tracking Error and Transmission Loss
by Jingchun Chu, Ling Yuan, Zhongwei Lin, Wei Xu and Zhenyu Chen
Processes 2018, 6(12), 259; https://doi.org/10.3390/pr6120259 - 10 Dec 2018
Cited by 3 | Viewed by 3244
Abstract
In this paper, a receding-horizon optimization strategy is introduced to optimize the wind farm active power distribution with power tracking error and transmission loss. Based on the wind farm transmission connections, a wind farm can be divided into clusters, in which the wind [...] Read more.
In this paper, a receding-horizon optimization strategy is introduced to optimize the wind farm active power distribution with power tracking error and transmission loss. Based on the wind farm transmission connections, a wind farm can be divided into clusters, in which the wind turbine generator systems connected to one booster station can be taken as one cluster, and different clusters connected from booster stations to the farm-level main transformer output the electric power to the grid. Thus, in the proposed strategy, the power tracking characteristic of the wind turbine generator system is modeled as a first-order system to quantify the power tracking error during the power tracking dynamic process, where the power transmission losses from wind turbine generator systems to booster stations are also modeled and considered in the optimization. The proposed strategy is applied to distribute the active power set-point within a cluster while the clusters’ set-point still follows the conventional strategy of the wind farm. Simulation results show significant improvement for both optimization targets of the proposed strategy. Full article
(This article belongs to the Special Issue Energy, Economic and Environment for Industrial Production Processes)
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11 pages, 1513 KiB  
Article
Multiresponse Optimization of Ultrasonic-Assisted Extraction for Aurantii Fructus to Obtain High Yield of Antioxidant Flavonoids Using a Response Surface Methodology
by Yingjie He, Yun Chen, Yiting Shi, Kanghong Zhao, Haiyan Tan, Jianguo Zeng, Qi Tang and Hongqi Xie
Processes 2018, 6(12), 258; https://doi.org/10.3390/pr6120258 - 10 Dec 2018
Cited by 8 | Viewed by 2928
Abstract
Aurantii fructus (zhiqiao, ZQ) is a traditional Chinese medicine (TCM) and raw material of TCM healthcare food (TCM-HF), mainly focused on the regulation of gastrointestinal disorders and the abundant application of antioxidants. Pharmacological investigations of ZQ flavonoids have identified them as the main [...] Read more.
Aurantii fructus (zhiqiao, ZQ) is a traditional Chinese medicine (TCM) and raw material of TCM healthcare food (TCM-HF), mainly focused on the regulation of gastrointestinal disorders and the abundant application of antioxidants. Pharmacological investigations of ZQ flavonoids have identified them as the main bioactive components in recent years, but little has been reported on the extraction processes of antioxidant flavonoids (AFs). The aim of this study was to establish an efficient ultrasonic-assisted extraction (UAE) method for the extraction of AFs from ZQ using a response surface methodology (RSM), analyze the composition of AFs, and develop a qualitative evaluation method for ZQ. Flavonoid yield and antioxidant ability were selected as the responses to optimize the extraction of AFs, and the multiple effects of independent variables were investigated. The optimized conditions for the extraction of AFs based on the Box-Behnken design (BBD) were as follows: ethanol concentration, 58%; extraction temperature, 70 °C; and extraction time, 17 min. The flavonoid yield and antioxidant activity reached 241.70 mg/g and 59.42%, respectively, which matched the predicted values. Furthermore, optimized UAE processes were first established for the efficient and fast extraction of AFs. Flavanones and polymethoxyflavonoids (PMFs) were identified as potential AFs using time-of-flight mass spectrometry. Meanwhile, the quality of ZQ was evaluated using the criteria importance through intercriteria correlation (CRITIC) method for the first time, and Yuanjiang ZQ was considered as an excellent raw material of TCM-HF. Full article
(This article belongs to the Special Issue Microwave Applications in Chemical Engineering)
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12 pages, 1713 KiB  
Article
Experimental Study on Compression Deformation and Permeability Characteristics of Grading Broken Gangue under Stress
by Yu Zhang, Wei Zhou, Ming Li and Zhanqing Chen
Processes 2018, 6(12), 257; https://doi.org/10.3390/pr6120257 - 9 Dec 2018
Cited by 8 | Viewed by 3331
Abstract
As the important raw material for backfill mining, broken gangue’s deformation and permeability characteristics directly affect the deformation of the overlying strata above the filling space. In this paper, through lateral compression and pressed seepage tests, the deformation and permeability characteristics of broken [...] Read more.
As the important raw material for backfill mining, broken gangue’s deformation and permeability characteristics directly affect the deformation of the overlying strata above the filling space. In this paper, through lateral compression and pressed seepage tests, the deformation and permeability characteristics of broken gangue as a function of the stress level and grading features were studied. This research indicates that the stress of broken gangue increases exponentially with an increase in strain, and the compression modulus and compression rate present a positive correlation. The samples with discontinuous grading are more difficult to compress than the continuous grading samples, and the discontinuous grading samples are tighter in accordance with the increase in compression rate. At the same time, the change range of the seepage velocity and permeability of the broken gangue decreases. Positive correction between the grading index of the broken gangue and the effect of reducing the permeability of samples is more obvious under axial compression, and less axial stress is needed to achieve the same permeability level for discontinuous grading. This paper can provide an important test basis for the design of grading parameters and the prediction of filling effects of broken gangue on backfill mining. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
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9 pages, 684 KiB  
Project Report
Full-Scale Processing by Anaerobic Baffle Reactor, Sequencing Batch Reactor, and Sand Filter for Treating High-Salinity Wastewater from Offshore Oil Rigs
by Wenjie Zhang, Yuan Wei and Yue Jin
Processes 2018, 6(12), 256; https://doi.org/10.3390/pr6120256 - 9 Dec 2018
Cited by 11 | Viewed by 4978
Abstract
High-salinity wastewater discharged from offshore oil rigs (WORS) is harmful to marine environments. Therefore, WORS should be properly treated before discharge. In this study, a full-scale anaerobic baffle reactor (ABR) + sequencing batch reactor (SBR) + sand filter (SF) process was used for [...] Read more.
High-salinity wastewater discharged from offshore oil rigs (WORS) is harmful to marine environments. Therefore, WORS should be properly treated before discharge. In this study, a full-scale anaerobic baffle reactor (ABR) + sequencing batch reactor (SBR) + sand filter (SF) process was used for the first time to treat WORS at an inshore treatment terminal. After seeding with residual sludge from a municipal wastewater treatment facility, the start-up of the ABR and SBR was accomplished in one month. During a steady running period, the ABR + SBR process showed stable performance in treating WORS. The results of microbial diversity indicated that Rhizobiales, Thermotogales, and Actinomycetales were the most abundant genera in the ABR sample, while Acidobacteria DRC31, Lactobacillales, and Bacillales prevailed in the SBR sample. The results showed that ABR + SBR is a reliable process for WORS treatment, with the treated WORS meeting the National Sewage Comprehensive Emission Standards (GB8978-1996). Full article
(This article belongs to the Special Issue Wastewater Treatment Processes)
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15 pages, 1329 KiB  
Article
An Analysis of Uncertainty Propagation Methods Applied to Breakage Population Balance
by Satyajeet Bhonsale, Dries Telen, Bard Stokbroekx and Jan Van Impe
Processes 2018, 6(12), 255; https://doi.org/10.3390/pr6120255 - 8 Dec 2018
Cited by 10 | Viewed by 3774
Abstract
In data-driven empirical or hybrid modeling, the experimental data influences the model parameters and thus also the model predictions. The experimental data has some variability due to measurement noise and due to the intrinsic stochastic nature of certain pharmaceutical processes such as aggregation [...] Read more.
In data-driven empirical or hybrid modeling, the experimental data influences the model parameters and thus also the model predictions. The experimental data has some variability due to measurement noise and due to the intrinsic stochastic nature of certain pharmaceutical processes such as aggregation or breakage. To use predictive models, it is imperative that the accuracy of the predictions is known. To this extent, various uncertainty propagation techniques applied to a predictive breakage population balance model are studied. Three uncertainty propagation techniques are studied: linearization, sigma point, and polynomial chaos. These are compared to the uncertainty obtained from Monte Carlo simulations. Linearization performs the worst in the given scenario, while sigma point and polynomial chaos methods have similar performance in terms of accuracy. Full article
(This article belongs to the Special Issue Recent Advances in Population Balance Modeling)
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19 pages, 11986 KiB  
Article
Information Extraction from Retinal Images with Agent-Based Technology
by Pablo Chamoso, Sara Rodríguez, Luis García-Ortiz and Juan Manuel Corchado
Processes 2018, 6(12), 254; https://doi.org/10.3390/pr6120254 - 6 Dec 2018
Cited by 2 | Viewed by 3470
Abstract
The study of retinal vessels can provide information on a wide range of illnesses in the human body. Numerous works have already focused on this new field of research and several medical software programs have been proposed to facilitate the close examination of [...] Read more.
The study of retinal vessels can provide information on a wide range of illnesses in the human body. Numerous works have already focused on this new field of research and several medical software programs have been proposed to facilitate the close examination of retinal vessels. Some allow for the automatic extraction of information and can be combined with other clinical tools for effective diagnosis and further medical studies. This article proposes an Agent-based Virtual Organizations (VO) System which applies a novel methodology for taking measurements from fundus images and extracting information on the retinal vessel caliber. A case study was conducted to evaluate the performance of the developed system, and the fundus images of different patients were used to extract information. Its performance was compared with that of similar tools. Full article
(This article belongs to the Special Issue Systems Biomedicine )
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17 pages, 7438 KiB  
Article
Dual Population Balance Monte Carlo Simulation of Particle Synthesis by Flame Spray Pyrolysis
by Ivan Skenderović, Gregor Kotalczyk and Frank Einar Kruis
Processes 2018, 6(12), 253; https://doi.org/10.3390/pr6120253 - 6 Dec 2018
Cited by 14 | Viewed by 4523
Abstract
The Dual Population Balance Monte Carlo Method (DPBMC) takes into account the full size spectrum of the droplet and particle phase. Droplet and particle size distributions are rendered by weighted simulation particles. This allows for an accurate description of particle nucleation and coagulation [...] Read more.
The Dual Population Balance Monte Carlo Method (DPBMC) takes into account the full size spectrum of the droplet and particle phase. Droplet and particle size distributions are rendered by weighted simulation particles. This allows for an accurate description of particle nucleation and coagulation and droplet combustion, simultaneously. Internal droplet properties such as temperature and concentrations fields are used to define criteria for the onset of droplet breakage in the framework of weighted Monte Carlo droplets. We discuss the importance of droplet polydispersity on particle formation in metal oxide particle synthesis, which is shown to strongly affect particle formation and growth. The method is applied to particle synthesis from metal nitrate precursor solutions with flame spray pyrolysis (FSP) and compared to experiments from literature. Full article
(This article belongs to the Special Issue Recent Advances in Population Balance Modeling)
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12 pages, 862 KiB  
Article
A Multi-Criteria Decision-Making (MCDM) Approach Using Hybrid SCOR Metrics, AHP, and TOPSIS for Supplier Evaluation and Selection in the Gas and Oil Industry
by Chia-Nan Wang, Ying-Fang Huang, I-Fang Cheng and Van Thanh Nguyen
Processes 2018, 6(12), 252; https://doi.org/10.3390/pr6120252 - 6 Dec 2018
Cited by 46 | Viewed by 7149
Abstract
Suppliers are extremely important in business operations. The supplier ensures the supply of materials, raw materials, commodities, etc. in sufficient quantity, quality, stability, and accuracy to meet the requirements of production and business with low costs and on-time deliveries. Therefore, selecting and managing [...] Read more.
Suppliers are extremely important in business operations. The supplier ensures the supply of materials, raw materials, commodities, etc. in sufficient quantity, quality, stability, and accuracy to meet the requirements of production and business with low costs and on-time deliveries. Therefore, selecting and managing good suppliers is a prerequisite for organizing the production of quality products as desired, according to the schedule, and with reasonable prices and competitiveness in the market. It is also important to gain the support of suppliers in order to continue to improve and achieve more as a business. The evaluation and selection of a supplier is a Multi-Criteria Decision-Making (MCDM) issue, in which the decision-maker is faced with both qualitative and quantitative factors. In this research, the authors propose an MCDM model using a hybrid of Supply Chain Operations Reference metrics (SCOR metrics), the Analytic Hierarchy Process (AHP) model, and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach for supplier evaluation and selection in the gas and oil industry. Using literature reviews on SCOR metrics, all criteria that impact supplier selection are defined in the first stage, the AHP model is applied to determine the weight of each factor in the second stage, and the optimal supplier is presented in final stage using the TOPSIS model. As a result, Decision-Making Unit 5 (DMU-05) is found to be the best supplier for the gas and oil industry in this research. The contribution of this work is to propose a new hybrid MCDM model for supplier selection in the gas and oil industry. This research also introduces a useful tool for supplier selection in other industries. Full article
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16 pages, 2710 KiB  
Article
Theoretical Methodology of a High-Flux Coal-Direct Chemical Looping Combustion System
by Xiaojia Wang, Xianli Liu, Zhaoyang Jin, Jiewen Zhu and Baosheng Jin
Processes 2018, 6(12), 251; https://doi.org/10.3390/pr6120251 - 4 Dec 2018
Cited by 2 | Viewed by 3151
Abstract
This study, as an extension of our previous experimental tests, presented a mechanism analysis of air reactor (AR) coupling in a high-flux coal-direct chemical looping combustion (CDCLC) system and provided a theoretical methodology to the system optimal design with favorable operation stability and [...] Read more.
This study, as an extension of our previous experimental tests, presented a mechanism analysis of air reactor (AR) coupling in a high-flux coal-direct chemical looping combustion (CDCLC) system and provided a theoretical methodology to the system optimal design with favorable operation stability and low gas leakages. Firstly, it exhibited the dipleg flow diagrams of the CDCLC system and concluded the feasible gas–solid flow states for solid circulation and gas leakage control. On this basis, the semi-theoretical formulas of gas leakages were proposed to predict the optimal regions of the pressure gradients of the AR. Meanwhile, an empirical formula of critical sealing was also developed to identify the advent of circulation collapse so as to ensure the operation stability of the whole system. Furthermore, the theoretical methodology was applied in the condition design of the cold system. The favorable gas–solid flow behaviors together with the good control of gas leakages demonstrated the feasibility of the theoretical methodology. Finally, the theoretical methodology was adopted to carry out a capability assessment of the high-flux CDCLC system under a hot state in terms of the restraint of gas leakages and the stability of solid circulation. Full article
(This article belongs to the Special Issue Gas Capture Processes)
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18 pages, 5383 KiB  
Article
Two-Step Many-Objective Optimal Power Flow Based on Knee Point-Driven Evolutionary Algorithm
by Yahui Li and Yang Li
Processes 2018, 6(12), 250; https://doi.org/10.3390/pr6120250 - 4 Dec 2018
Cited by 10 | Viewed by 3771
Abstract
To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algorithm (KnEA) is introduced to address the [...] Read more.
To coordinate the economy, security and environment protection in the power system operation, a two-step many-objective optimal power flow (MaOPF) solution method is proposed. In step 1, it is the first time that knee point-driven evolutionary algorithm (KnEA) is introduced to address the MaOPF problem, and thereby the Pareto-optimal solutions can be obtained. In step 2, an integrated decision analysis technique is utilized to provide decision makers with decision supports by combining fuzzy c-means (FCM) clustering and grey relational projection (GRP) method together. In this way, the best compromise solutions (BCSs) that represent decision makers’ different, even conflicting, preferences can be automatically determined from the set of Pareto-optimal solutions. The primary contribution of the proposal is the innovative application of many-objective optimization together with decision analysis for addressing MaOPF problems. Through examining the two-step method via the IEEE 118-bus system and the real-world Hebei provincial power system, it is verified that our approach is suitable for addressing the MaOPF problem of power systems. Full article
(This article belongs to the Special Issue Energy, Economic and Environment for Industrial Production Processes)
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30 pages, 8750 KiB  
Article
Offshore Power Plants Integrating a Wind Farm: Design Optimisation and Techno-Economic Assessment Based on Surrogate Modelling
by Luca Riboldi and Lars O. Nord
Processes 2018, 6(12), 249; https://doi.org/10.3390/pr6120249 - 4 Dec 2018
Cited by 20 | Viewed by 5250
Abstract
The attempt to reduce the environmental impact of the petroleum sector has been the driver for researching energy efficient solutions to supply energy offshore. An attractive option is to develop innovative energy systems including renewable and conventional sources. The paper investigates the possibility [...] Read more.
The attempt to reduce the environmental impact of the petroleum sector has been the driver for researching energy efficient solutions to supply energy offshore. An attractive option is to develop innovative energy systems including renewable and conventional sources. The paper investigates the possibility to integrate a wind farm into an offshore combined cycle power plant. The design of such an energy system is a complex task as many, possibly conflicting, requirements have to be satisfied. The large variability of operating conditions due to the intermittent nature of wind and to the different stages of exploitation of an oil field makes it challenging to identify the optimal parameters of the combined cycle and the optimal size of the wind farm. To deal with the issue, an optimisation procedure was developed that was able to consider the performance of the system at a number of relevant off-design conditions in the definition of the optimal design. A surrogate modelling technique was applied in order to reduce the computational effort that would otherwise make the optimisation process unfeasible. The developed method was applied to a case study and the resulting optimal designs were assessed and compared to other concepts, with or without wind power integration. The proposed offshore power plant returned the best environmental performance, as it was able to significantly cut the total carbon dioxide (CO2) emissions in comparison to all the other concepts evaluated. The economic analysis showed the difficulty to repay the additional investment for a wind farm and the necessity of favourable conditions, in terms of gas and carbon dioxide (CO2) prices. Full article
(This article belongs to the Special Issue Modeling and Simulation of Energy Systems)
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25 pages, 4998 KiB  
Review
Recent Progress of Plasma-Assisted Nitrogen Fixation Research: A Review
by Sirui Li, Jose A. Medrano, Volker Hessel and Fausto Gallucci
Processes 2018, 6(12), 248; https://doi.org/10.3390/pr6120248 - 3 Dec 2018
Cited by 95 | Viewed by 14161
Abstract
Nitrogen is an essential element to plants, animals, human beings and all the other living things on earth. Nitrogen fixation, which converts inert atmospheric nitrogen into ammonia or other valuable substances, is a very important part of the nitrogen cycle. The Haber-Bosch process [...] Read more.
Nitrogen is an essential element to plants, animals, human beings and all the other living things on earth. Nitrogen fixation, which converts inert atmospheric nitrogen into ammonia or other valuable substances, is a very important part of the nitrogen cycle. The Haber-Bosch process plays the dominant role in the chemical nitrogen fixation as it produces a large amount of ammonia to meet the demand from the agriculture and chemical industries. However, due to the high energy consumption and related environmental concerns, increasing attention is being given to alternative (greener) nitrogen fixation processes. Among different approaches, plasma-assisted nitrogen fixation is one of the most promising methods since it has many advantages over others. These include operating at mild operation conditions, a green environmental profile and suitability for decentralized production. This review covers the research progress in the field of plasma-assisted nitrogen fixation achieved in the past five years. Both the production of NOx and the synthesis of ammonia are included, and discussion on plasma reactors, operation parameters and plasma-catalysts are given. In addition, outlooks and suggestions for future research are also given. Full article
(This article belongs to the Special Issue Plasma-Based Processes for Improved Energy Efficiency)
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17 pages, 3595 KiB  
Article
Modeling and Simulation Studies of a Novel Coupled Plug Flow Crystallizer for the Continuous Separation of Conglomerate-Forming Enantiomers
by Aniruddha Majumder
Processes 2018, 6(12), 247; https://doi.org/10.3390/pr6120247 - 1 Dec 2018
Cited by 12 | Viewed by 4220
Abstract
Separation of enantiomers is a major concern in pharmaceutical industries due to the different therapeutic activities exhibited by the enantiomers. Preferential crystallization is an attractive means to separate the conglomerate-forming enantiomers. In this work, a simulation study is presented for a proposed novel [...] Read more.
Separation of enantiomers is a major concern in pharmaceutical industries due to the different therapeutic activities exhibited by the enantiomers. Preferential crystallization is an attractive means to separate the conglomerate-forming enantiomers. In this work, a simulation study is presented for a proposed novel preferential crystallization configuration that involves coupled plug flow crystallizers (PFCs). The PFCs are coupled through liquid phase exchange which helps the enrichment of the preferred enantiomer in the liquid phase. A set of coupled population balance equations (PBEs) are used to describe the evolution of the crystal size distribution (CSD) in the PFCs. The PBEs and the relevant mass balance equations are solved using the high-resolution finite-volume method. The simulation results predict that the proposed configuration has higher productivity compared to the currently used crystallization configurations while maintaining the same level of purity. Moreover, the effect of process variables, such as the extent of liquid phase exchange and the location of the PFC where liquid phase exchange occurs, are studied. The insights obtained from this simulation study will be useful in design, development, and optimization of such novel crystallization platforms. Full article
(This article belongs to the Special Issue Recent Advances in Population Balance Modeling)
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14 pages, 1662 KiB  
Article
Parameter Identification For Continuous Fluidized Bed Spray Agglomeration
by Ievgen Golovin, Gerd Strenzke, Robert Dürr, Stefan Palis, Andreas Bück, Evangelos Tsotsas and Achim Kienle
Processes 2018, 6(12), 246; https://doi.org/10.3390/pr6120246 - 30 Nov 2018
Cited by 14 | Viewed by 4463
Abstract
Agglomeration represents an important particle formation process used in many industries. One particularly attractive process setup is continuous fluidized bed spray agglomeration, which features good mixing as well as high heat and mass transfer on the one hand and constant product throughput with [...] Read more.
Agglomeration represents an important particle formation process used in many industries. One particularly attractive process setup is continuous fluidized bed spray agglomeration, which features good mixing as well as high heat and mass transfer on the one hand and constant product throughput with constant quality as well as high flow rates compared to batch mode on the other hand. Particle properties such as agglomerate size or porosity significantly affect overall product properties such as re-hydration behavior and dissolubility. These can be influenced by different operating parameters. In this manuscript, a population balance model for a continuous fluidized bed spray agglomeration is presented and adapted to experimental data. Focus is on the description of the dynamic behavior in continuous operation mode in a certain neighborhood around steady-state. Different kernel candidates are evaluated and it is shown that none of the kernels are able to match the first six minutes with time independent parameters. Afterwards, a good fit can be obtained, where the Brownian and the volume independent kernel models match best with the experimental data. Model fit is improved for identification on a shifted time domain neglecting the initial start-up phase. Here, model identifiability is shown and parameter confidence intervals are computed via parametric bootstrap. Full article
(This article belongs to the Special Issue Recent Advances in Population Balance Modeling)
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16 pages, 2900 KiB  
Article
Wheat Germ Drying with Different Time-Temperature Combinations in a Fluidized Bed Dryer
by Der-Sheng Chan and Meng-I Kuo
Processes 2018, 6(12), 245; https://doi.org/10.3390/pr6120245 - 28 Nov 2018
Cited by 7 | Viewed by 5296
Abstract
The development of an effective drying performance of the fluidized bed dryer (FBD) is crucial to reduce drying costs. The objective of this study was to investigate the drying performance of wheat germ (WG) with different time-temperature combinations in the FBD. The WG [...] Read more.
The development of an effective drying performance of the fluidized bed dryer (FBD) is crucial to reduce drying costs. The objective of this study was to investigate the drying performance of wheat germ (WG) with different time-temperature combinations in the FBD. The WG was dried at different set temperatures of 80, 100 and 120 °C. The moisture content (MC) and water activity (WA) of WG were measured. A mathematical model was proposed to develop an optimal drying condition. The changes in the MC of WG during drying in the FBD could be divided into the decreased period, the dynamic equilibrium period and the increased period. The product temperature of 45 °C and WA of 0.3 of WG drying could be attained by different time-temperature combinations. The mathematical model, which was developed in conjunction with different time-temperature combinations, could predict the dehydration time and the condensation time of WG for optimization the drying conditions. The WG dehydration at the heating stage and the WG condensation at the cooling stage could also be evaluated by the dehydration flux and the condensation flux, respectively. The optimal drying performance of WG exists in a compromise between promoting dehydration and reducing condensation. Information obtained from the analysis of dehydration flux and condensation flux with experimental data and simulation gave the guidelines for performing an effective drying of WG in the FBD. Full article
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21 pages, 16770 KiB  
Article
An Efficient Solitary Senior Citizens Care Algorithm and Application: Considering Emotional Care for Big Data Collection
by Jun-Ho Huh
Processes 2018, 6(12), 244; https://doi.org/10.3390/pr6120244 - 27 Nov 2018
Cited by 9 | Viewed by 4861
Abstract
The issue of solitary senior citizens dying alone has become serious in advanced countries where the average lifespan of their citizens is continuously extending due to improved health care and diet. Such unattended deaths are considered to be one of the major issues [...] Read more.
The issue of solitary senior citizens dying alone has become serious in advanced countries where the average lifespan of their citizens is continuously extending due to improved health care and diet. Such unattended deaths are considered to be one of the major issues pertaining to the ever-growing number of senior citizens so that many research studies have been conducted to find a solution to mitigate the situation. The framework proposed in this study allows monitoring of electric power consumption patterns of solitary senior citizens. At the same time, a test bed was constructed to estimate the performance of the framework. The results from the test bed experiment revealed that the framework was effective, flexible, and expandable for actual implementation. This framework is the product of these research studies describing individual designs and the method of implementing them for actual application. This research has confirmed that the framework for an extendable solitary senior citizens care system can be designed and implemented at low cost and the operations between system components worked smoothly while interacting flexibly. In particular, the rate of these old people dying alone in poor areas was above normal so that the proposed system would be quite meaningful to society as it helps in monitoring their safety by locating the whereabouts of those people with dementia or checking their daily routines, for example. Full article
(This article belongs to the Special Issue Big Data in Biology, Life Sciences and Healthcare)
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15 pages, 3052 KiB  
Article
A Data-Driven Reaction Network for the Fluid Catalytic Cracking of Waste Feeds
by José Ignacio Alvira, Idoia Hita, Elena Rodríguez, José M. Arandes and Pedro Castaño
Processes 2018, 6(12), 243; https://doi.org/10.3390/pr6120243 - 27 Nov 2018
Cited by 14 | Viewed by 5174
Abstract
Establishing a reaction network is of uttermost importance in complex catalytic processes such as fluid catalytic cracking (FCC). This step is the seed for a faithful reactor modeling and the subsequent catalyst re-design, process optimization or prediction. In this work, a dataset of [...] Read more.
Establishing a reaction network is of uttermost importance in complex catalytic processes such as fluid catalytic cracking (FCC). This step is the seed for a faithful reactor modeling and the subsequent catalyst re-design, process optimization or prediction. In this work, a dataset of 104 uncorrelated experiments, with 64 variables, was obtained in an FCC simulator using six types of feedstock (vacuum gasoil, polyethylene pyrolysis waxes, scrap tire pyrolysis oil, dissolved polyethylene and blends of the previous), 36 possible sets of conditions (varying contact time, temperature and catalyst/oil ratio) and three industrial catalysts. Principal component analysis (PCA) was applied over the dataset, showing that the main components are associated with feed composition (27.41% variance), operational conditions (19.09%) and catalyst properties (12.72%). The variables of each component were correlated with the indexes and yields of the products: conversion, octane number, aromatics, olefins (propylene) or coke, among others. Then, a data-driven reaction network was proposed for the cracking of waste feeds based on the previously obtained correlations. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control of Chemical Processes)
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3 pages, 140 KiB  
Editorial
Special Issue on “Biological Networks”
by Rudiyanto Gunawan and Neda Bagheri
Processes 2018, 6(12), 242; https://doi.org/10.3390/pr6120242 - 27 Nov 2018
Viewed by 2602
Abstract
Networks of coordinated interactions among biological entities govern a myriad of biological functions that span a wide range of both length and time scales—from ecosystems to individual cells, and from years (e.g., the life cycle of periodical cicadas) to milliseconds (e.g., allosteric enzyme
[...] Read more.
Networks of coordinated interactions among biological entities govern a myriad of biological functions that span a wide range of both length and time scales—from ecosystems to individual cells, and from years (e.g., the life cycle of periodical cicadas) to milliseconds (e.g., allosteric enzyme
regulation[...] Full article
(This article belongs to the Special Issue Biological Networks)
11 pages, 3774 KiB  
Article
Intensification of Reactive Distillation for TAME Synthesis Based on the Analysis of Multiple Steady-State Conditions
by Takehiro Yamaki, Keigo Matsuda, Duangkamol Na-Ranong and Hideyuki Matsumoto
Processes 2018, 6(12), 241; https://doi.org/10.3390/pr6120241 - 26 Nov 2018
Cited by 4 | Viewed by 5338
Abstract
Our previous study reported that operation in multiple steady states contributes to an improvement in reaction conversion, making it possible to reduce the energy consumption of the reactive distillation process for tert-amyl methyl ether (TAME) synthesis. This study clarified the factors responsible [...] Read more.
Our previous study reported that operation in multiple steady states contributes to an improvement in reaction conversion, making it possible to reduce the energy consumption of the reactive distillation process for tert-amyl methyl ether (TAME) synthesis. This study clarified the factors responsible for an improvement in the reaction conversion for operation in the multiple steady states of the reactive distillation column used in TAME synthesis. The column profiles for those conditions, in which multiple steady states existed and those in which they did not exist, were compared. The vapor and liquid flow rates with the multiple steady states were larger than those when the multiple steady states did not exist. The effect of the duty of the intermediate condenser, which was introduced at the top of the reactive section, on the liquid flow rate for a reflux ratio of 1 was examined. The amount of TAME production increased from 55.2 to 72.1 kmol/h when the intermediate condenser was operated at 0 to −5 MW. Furthermore, the effect of the intermediate reboiler duty on the reaction performance was evaluated. The results revealed that the liquid and vapor flow rates influenced the reaction and separation performances, respectively. Full article
(This article belongs to the Special Issue Process Design, Integration, and Intensification)
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18 pages, 9410 KiB  
Article
Experimental Studies on Corrosion Behavior of Ceramic Surface Coating using Different Deposition Techniques on 6082-T6 Aluminum Alloy
by Ali Algahtani, Essam R.I. Mahmoud, Sohaib Z. Khan and Vineet Tirth
Processes 2018, 6(12), 240; https://doi.org/10.3390/pr6120240 - 26 Nov 2018
Cited by 14 | Viewed by 4986
Abstract
Aluminum alloys cannot be used in aggressive corrosion environments application. In this paper, three different surface coating technologies were used to coat the 6082-T6 aluminum alloy to increase the corrosion resistance, namely Plasma Electrolytic Oxidation (PEO), Plasma Spray Ceramic (PSC) and Hard Anodizing [...] Read more.
Aluminum alloys cannot be used in aggressive corrosion environments application. In this paper, three different surface coating technologies were used to coat the 6082-T6 aluminum alloy to increase the corrosion resistance, namely Plasma Electrolytic Oxidation (PEO), Plasma Spray Ceramic (PSC) and Hard Anodizing (HA). The cross-sectional microstructure analysis revealed that HA coating was less uniform compared to other coatings. PEO coating was well adhered to the substrate despite the thinnest layer among all three coatings, while the PSC coating has an additional loose layer between the coat and the substrate. X-ray diffraction (XRD) analysis revealed crystalline alumina phases in PEO and PSC coatings while no phase was detected in HA other than an aluminum element. A series of electrochemistry experiments were used to evaluate the corrosion performances of these three types of coatings. Generally, all three-coated aluminum showed better corrosion performances. PEO coating has no charge transfer under all Inductive Coupled Plasma (ICP) tests, while small amounts of Al3+ were released for both HA and PSC coatings at 80 °C. The PEO coating showed the lowest corrosion current density followed by HA and then PSC coatings. The impedance resistance decreased as the immersion time increased, which indicated that this is due to the degradation and deterioration of the protective coatings. The results indicate that the PEO coating can offer the most effective protection to the aluminum substrate as it has the highest enhancement factor under electrochemistry tests compared to the other two coatings. Full article
(This article belongs to the Special Issue Thin Film Processes)
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16 pages, 3360 KiB  
Article
Estimation of Pore Size Distribution of Amorphous Silica-Based Membrane by the Activation Energies of Gas Permeation
by Guozhao Ji, Xuechao Gao, Simon Smart, Suresh K. Bhatia, Geoff Wang, Kamel Hooman and João C. Diniz da Costa
Processes 2018, 6(12), 239; https://doi.org/10.3390/pr6120239 - 23 Nov 2018
Cited by 8 | Viewed by 4268
Abstract
Cobalt oxide silica membranes were prepared and tested to separate small molecular gases, such as He (dk = 2.6 Å) and H2 (dk = 2.89 Å), from other gases with larger kinetic diameters, such as CO2 ( [...] Read more.
Cobalt oxide silica membranes were prepared and tested to separate small molecular gases, such as He (dk = 2.6 Å) and H2 (dk = 2.89 Å), from other gases with larger kinetic diameters, such as CO2 (dk = 3.47 Å) and Ar (dk = 3.41 Å). In view of the amorphous nature of silica membranes, pore sizes are generally distributed in the ultra-microporous range. However, it is difficult to determine the pore size of silica derived membranes by conventional characterization methods, such as N2 physisorption-desorption or high-resolution electron microscopy. Therefore, this work endeavors to determine the pore size of the membranes based on transport phenomena and computer modelling. This was carried out by using the oscillator model and correlating with experimental results, such as gas permeance (i.e., normalized pressure flux), apparent activation energy for gas permeation. Based on the oscillator model, He and H2 can diffuse through constrictions narrower than their gas kinetic diameters at high temperatures, and this was possibly due to the high kinetic energy promoted by the increase in external temperature. It was interesting to observe changes in transport phenomena for the cobalt oxide doped membranes exposed to H2 at high temperatures up to 500 °C. This was attributed to the reduction of cobalt oxide, and this redox effect gave different apparent activation energy. The reduced membrane showed lower apparent activation energy and higher gas permeance than the oxidized membrane, due to the enlargement of pores. These results together with effective medium theory (EMT) suggest that the pore size distribution is changed and the peak of the distribution is slightly shifted to a larger value. Hence, this work showed for the first time that the oscillator model with EMT is a potential tool to determine the pore size of silica derived membranes from experimental gas permeation data. Full article
(This article belongs to the Special Issue Transport of Fluids in Nanoporous Materials)
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45 pages, 2532 KiB  
Review
Modeling and Simulation of Energy Systems: A Review
by Avinash Shankar Rammohan Subramanian, Truls Gundersen and Thomas Alan Adams II
Processes 2018, 6(12), 238; https://doi.org/10.3390/pr6120238 - 23 Nov 2018
Cited by 103 | Viewed by 22816
Abstract
Energy is a key driver of the modern economy, therefore modeling and simulation of energy systems has received significant research attention. We review the major developments in this area and propose two ways to categorize the diverse contributions. The first categorization is according [...] Read more.
Energy is a key driver of the modern economy, therefore modeling and simulation of energy systems has received significant research attention. We review the major developments in this area and propose two ways to categorize the diverse contributions. The first categorization is according to the modeling approach, namely into computational, mathematical, and physical models. With this categorization, we highlight certain novel hybrid approaches that combine aspects of the different groups proposed. The second categorization is according to field namely Process Systems Engineering (PSE) and Energy Economics (EE). We use the following criteria to illustrate the differences: the nature of variables, theoretical underpinnings, level of technological aggregation, spatial and temporal scales, and model purposes. Traditionally, the Process Systems Engineering approach models the technological characteristics of the energy system endogenously. However, the energy system is situated in a broader economic context that includes several stakeholders both within the energy sector and in other economic sectors. Complex relationships and feedback effects exist between these stakeholders, which may have a significant impact on strategic, tactical, and operational decision-making. Leveraging the expertise built in the Energy Economics field on modeling these complexities may be valuable to process systems engineers. With this categorization, we present the interactions between the two fields, and make the case for combining the two approaches. We point out three application areas: (1) optimal design and operation of flexible processes using demand and price forecasts, (2) sustainability analysis and process design using hybrid methods, and (3) accounting for the feedback effects of breakthrough technologies. These three examples highlight the value of combining Process Systems Engineering and Energy Economics models to get a holistic picture of the energy system in a wider economic and policy context. Full article
(This article belongs to the Special Issue Modeling and Simulation of Energy Systems)
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