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Processes, Volume 7, Issue 2 (February 2019)

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Open AccessFeature PaperArticle Long-Term Stability of Thin-Film Pd-Based Supported Membranes
Processes 2019, 7(2), 106; https://doi.org/10.3390/pr7020106 (registering DOI)
Received: 16 January 2019 / Revised: 1 February 2019 / Accepted: 13 February 2019 / Published: 16 February 2019
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Abstract
Membrane reactors have demonstrated a large potential for the production of hydrogen via reforming of different feedstocks in comparison with other reactor types. However, the long-term performance and stability of the applied membranes are extremely important for the possible industrial exploitation of these [...] Read more.
Membrane reactors have demonstrated a large potential for the production of hydrogen via reforming of different feedstocks in comparison with other reactor types. However, the long-term performance and stability of the applied membranes are extremely important for the possible industrial exploitation of these reactors. This study investigates the long-term stability of thin-film Pd-Ag membranes supported on porous Al2O3 supports. The stability of five similarly prepared membranes have been investigated for 2650 h, up to 600 °C and in fluidized bed conditions. Results show the importance and the contribution of the sealing of the membranes at temperatures up to 500 °C. At higher temperatures the membranes surface deformation results in pinhole formation and a consequent decrease in selectivity. Stable operation of the membranes in a fluidized bed is observed up to 450 °C, however, at higher temperatures the scouring action of the particles under fluidization causes significant deformation of the palladium surface resulting in a decreased selectivity. Full article
(This article belongs to the Special Issue Catalysis in Membrane Reactors)
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Open AccessReview Biomaterial Implants in Abdominal Wall Hernia Repair: A Review on the Importance of the Peritoneal Interface
Processes 2019, 7(2), 105; https://doi.org/10.3390/pr7020105 (registering DOI)
Received: 1 January 2019 / Revised: 8 February 2019 / Accepted: 10 February 2019 / Published: 16 February 2019
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Abstract
Biomaterials have long been used to repair defects in the clinical setting, which has led to the development of a wide variety of new materials tailored to specific therapeutic purposes. The efficiency in the repair of the defect and the safety of the [...] Read more.
Biomaterials have long been used to repair defects in the clinical setting, which has led to the development of a wide variety of new materials tailored to specific therapeutic purposes. The efficiency in the repair of the defect and the safety of the different materials employed are determined not only by the nature and structure of their components, but also by the anatomical site where they will be located. Biomaterial implantation into the abdominal cavity in the form of a surgical mesh, such as in the case of abdominal hernia repair, involves the contact between the foreign material and the peritoneum. This review summarizes the different biomaterials currently available in hernia mesh repair and provides insights into a series of peculiarities that must be addressed when designing the optimal mesh to be used in this interface. Full article
(This article belongs to the Special Issue Biomaterials and Tissue Engineering)
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Open AccessArticle The Application of a Three-Dimensional Deterministic Model in the Study of Debris Flow Prediction Based on the Rainfall-Unstable Soil Coupling Mechanism
Processes 2019, 7(2), 99; https://doi.org/10.3390/pr7020099 (registering DOI)
Received: 15 December 2018 / Revised: 7 February 2019 / Accepted: 7 February 2019 / Published: 15 February 2019
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Abstract
As debris flow is one of the most destructive natural disasters in many parts of the world, the assessment and management of future debris flows with proper forecasting methods are crucial for the safety of life and property. So increasing attention has been [...] Read more.
As debris flow is one of the most destructive natural disasters in many parts of the world, the assessment and management of future debris flows with proper forecasting methods are crucial for the safety of life and property. So increasing attention has been paid to the forecasting methods on debris flows. A debris flow forecasting method based on the rainfall-unstable soil coupling mechanism (R-USCM) is presented in the current study. This method is based on the debris flow formation mechanism. The density of sediment is introduced as an evaluation index to determine the susceptibility of debris flow occurrence. The forecasting method includes two phases: (1) rainfall and soil coupling and (2) runoff and unstable soil coupling. Scoops3D, a three-dimensional (3D) model for analyzing slope stability, was introduced into the debris flow forecasting method. In order to test the forecasting accuracy of this method, Jiaohe County was selected as a research area, and the serious debris flow disasters attributed to strong rainfall on 20 July 2017 were taken as the research case. By comparing the forecasting results with the debris flow distribution map for Jiaohe County, the method based on the R-USCM is feasible for forecasting debris flows at the regional scale. The application of the Scoops3D model can more reasonably analyze the slope stability than the traditional two dimensional (2D) method and improve the forecasting ability of debris flows. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
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Open AccessArticle Improvement of Temperature Control Performance of Thermoelectric Dehumidifier Used Industry 4.0 by the SF-PI Controller
Processes 2019, 7(2), 98; https://doi.org/10.3390/pr7020098 (registering DOI)
Received: 22 January 2019 / Revised: 8 February 2019 / Accepted: 11 February 2019 / Published: 15 February 2019
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Abstract
This paper proposes the series connected fuzzy-proportional integral (SF-PI) controller, which is composed of the fuzzy control and the PI controller to improve temperature control performance of dehumidifier using a thermoelectric element. The control of conventional PI controller usually uses fixed gain. For [...] Read more.
This paper proposes the series connected fuzzy-proportional integral (SF-PI) controller, which is composed of the fuzzy control and the PI controller to improve temperature control performance of dehumidifier using a thermoelectric element. The control of conventional PI controller usually uses fixed gain. For that reason, it is limited in achieving satisfactory control performance in both transient-state and steady-state. The fuzzy control within SF-PI controller adjusts the input value of PI controller according to operating condition. The PI controller within the SF-PI controller controls the temperature of the thermoelectric element using that value. The SF-PI controller can achieve more accurate temperature control than a conventional PI controller for that reason. The SF-PI controller has been tested for various indoor environmental conditions such as temperature and relative humidity conditions. The average temperature error of the SF-PI controller between the reference temperature and the thermoelectric element temperature is 22% of traditional PI’s value and consumption power is reduced by about 10%. Therefore, the SF-PI controller proposed in this paper can improved the performance of temperature control of dehumidifier using thermoelectric element. The power consumed by buildings accounts for a significant portion of the total power consumption, of which the air conditioner represents the largest energy consumer. In this paper, it is possible to reduce the energy consumption by improving the performance of the dehumidifier, one of the air conditioners, and it can be applied to various control fields in the future. Full article
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Open AccessFeature PaperArticle Metabolic Modeling of Clostridium difficile Associated Dysbiosis of the Gut Microbiota
Processes 2019, 7(2), 97; https://doi.org/10.3390/pr7020097 (registering DOI)
Received: 16 December 2018 / Revised: 30 January 2019 / Accepted: 6 February 2019 / Published: 15 February 2019
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Abstract
Recent in vitro experiments have demonstrated the ability of the pathogen Clostridium difficile and commensal gut bacteria to form biofilms on surfaces, and biofilm development in vivo is likely. Various studies have reported that 3%–15% of healthy adults are asymptomatically colonized with C. [...] Read more.
Recent in vitro experiments have demonstrated the ability of the pathogen Clostridium difficile and commensal gut bacteria to form biofilms on surfaces, and biofilm development in vivo is likely. Various studies have reported that 3%–15% of healthy adults are asymptomatically colonized with C. difficile, with commensal species providing resistance against C. difficile pathogenic colonization. C. difficile infection (CDI) is observed at a higher rate in immunocompromised patients previously treated with broad spectrum antibiotics that disrupt the commensal microbiota and reduce competition for available nutrients, resulting in imbalance among commensal species and dysbiosis conducive to C. difficile propagation. To investigate the metabolic interactions of C. difficile with commensal species from the three dominant phyla in the human gut, we developed a multispecies biofilm model by combining genome-scale metabolic reconstructions of C. difficile, Bacteroides thetaiotaomicron from the phylum Bacteroidetes, Faecalibacterium prausnitzii from the phylum Firmicutes, and Escherichia coli from the phylum Proteobacteria. The biofilm model was used to identify gut nutrient conditions that resulted in C. difficile-associated dysbiosis characterized by large increases in C. difficile and E. coli abundances and large decreases in F. prausnitzii abundance. We tuned the model to produce species abundances and short-chain fatty acid levels consistent with available data for healthy individuals. The model predicted that experimentally-observed host-microbiota perturbations resulting in decreased carbohydrate/increased amino acid levels and/or increased primary bile acid levels would induce large increases in C. difficile abundance and decreases in F. prausnitzii abundance. By adding the experimentally-observed perturbation of increased host nitrate secretion, the model also was able to predict increased E. coli abundance associated with C. difficile dysbiosis. In addition to rationalizing known connections between nutrient levels and disease progression, the model generated hypotheses for future testing and has the capability to support the development of new treatment strategies for C. difficile gut infections. Full article
(This article belongs to the Special Issue Methods in Computational Biology)
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Open AccessArticle Profile Monitoring for Autocorrelated Reflow Processes with Small Samples
Processes 2019, 7(2), 104; https://doi.org/10.3390/pr7020104 (registering DOI)
Received: 12 January 2019 / Revised: 2 February 2019 / Accepted: 12 February 2019 / Published: 15 February 2019
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Abstract
The methodology of profile monitoring combines both the model fitting and statistical process control (SPC) techniques. Over the past ten years, a variety of profile monitoring methods have been proposed and extensively investigated in terms of different process profiles. However, monitoring tasks still [...] Read more.
The methodology of profile monitoring combines both the model fitting and statistical process control (SPC) techniques. Over the past ten years, a variety of profile monitoring methods have been proposed and extensively investigated in terms of different process profiles. However, monitoring tasks still exhibit a primary problem in that the errors surrounding the functional relationship are frequently assumed to be independent within every single profile. However, the assumption of independence is an unrealistic assumption in many practical instances. In particular, within-profile autocorrelation often occurs in the profile data. To mitigate the within-profile autocorrelation, a monitoring method incorporating an autoregressive (AR)(1) model to cope with autocorrelation is proposed. In this paper, the reflow process with small samples in surface mount technology (SMT) is investigated. In Phase I, three different process models are compared in combination with the first-order autoregressive model, while an appropriate profile model is sought. The Hotelling T2 and exponentially weighted moving average (EWMA) control charts are used together to monitor the parameter estimates (i.e., profile shape) and residuals (i.e., profile variability), respectively. Full article
(This article belongs to the Special Issue Optimization for Control, Observation and Safety)
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Open AccessFeature PaperArticle Scheduling of Energy-Integrated Batch Process Systems Using a Pattern-Based Framework
Processes 2019, 7(2), 103; https://doi.org/10.3390/pr7020103 (registering DOI)
Received: 18 January 2019 / Revised: 6 February 2019 / Accepted: 8 February 2019 / Published: 15 February 2019
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Abstract
In this paper, a novel pattern-based method is developed for the generation of optimal schedules for energy-integrated batch process systems. The proposed methodology is based on the analysis of available schedules for the identification of repetitive patterns. It is shown that optimal schedules [...] Read more.
In this paper, a novel pattern-based method is developed for the generation of optimal schedules for energy-integrated batch process systems. The proposed methodology is based on the analysis of available schedules for the identification of repetitive patterns. It is shown that optimal schedules of energy-integrated batch processes are composed of several repeating sections (or building blocks), and their sizes and relative positions are dependent on the scheduling horizon and constraints. Based on such a decomposition, the proposed pattern-based algorithm generates an optimal schedule by computing the number and sequence of these blocks. The framework is then integrated with rigorous optimization-based approach wherein it is shown that the learning from the pattern-based solution significantly improves the performance of rigorous optimization. The main advantage of the pattern-based method is the significant reduction in computational time required to solve large scheduling problems, thus enabling the possibility of on-line rescheduling. Three literature examples were considered to demonstrate the presence of repeating patterns in optimal schedules of energy-integrated batch systems. The effectiveness of the proposed methodology was illustrated using an integrated reactor-separator system. Full article
(This article belongs to the Special Issue Design and Control of Sustainable Systems)
Open AccessArticle Dynamics of Water Quality: Impact Assessment Process for Water Resource Management
Processes 2019, 7(2), 102; https://doi.org/10.3390/pr7020102 (registering DOI)
Received: 31 December 2018 / Revised: 24 January 2019 / Accepted: 27 January 2019 / Published: 15 February 2019
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Abstract
Surface water is an important source of water supply for irrigation purpose and in urban areas, sewage water is being disposed of in nearby canals without treatment. A study was conducted to investigate the dynamics of water quality of irrigation canal as a [...] Read more.
Surface water is an important source of water supply for irrigation purpose and in urban areas, sewage water is being disposed of in nearby canals without treatment. A study was conducted to investigate the dynamics of water quality of irrigation canal as a result of this practice. The study ascertained the impact of different salinity parameters, indices and approaches to examine the hazardous effects on quality of canal water. The study analyses the samples collected for various parameters like pH, TDS, EC, Na, Cl, Ca, Mg, K, CO3, HCO3 etc. It helped to decide the restriction on use of water based on FAO-UN guidelines. Investigations were focused on assessment of contaminants affecting the quality of water and having hazardous effects on different stages of irrigation water usage. Wilcox diagram and Doneen’s approach-based analysis helped to identify the class and quality of water. This study shall help to analyze the quality of water and provide support to the decision makers for better water resource management and policy development for irrigation purpose i.e. treatment and distribution of water resource. Full article
(This article belongs to the Special Issue Water Quality Modelling)
Open AccessArticle Discrete Element Method Model Optimization of Cylindrical Pellet Size
Processes 2019, 7(2), 101; https://doi.org/10.3390/pr7020101 (registering DOI)
Received: 11 January 2019 / Revised: 6 February 2019 / Accepted: 13 February 2019 / Published: 15 February 2019
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Abstract
The DEM (Discrete Element Method) is one option for studying the kinematic behaviour of cylindrical pellets. The DEM experiments attempted to optimize the numerical model parameters that affected time and velocity as a cylindrical vessel emptied. This vessel was filled with cylindrical pellets. [...] Read more.
The DEM (Discrete Element Method) is one option for studying the kinematic behaviour of cylindrical pellets. The DEM experiments attempted to optimize the numerical model parameters that affected time and velocity as a cylindrical vessel emptied. This vessel was filled with cylindrical pellets. Optimization was accomplished by changing the coefficient of friction between particles and selecting the length accuracy grade of the sample cylindrical pellets. The initial state was a series of ten vessel-discharge experiments evaluated using PIV (Particle Image Velocimetry). The cylindrical pellet test samples were described according to their length in three accuracy grades. These cylindrical pellet length accuracy grades were subsequently used in the DEM simulations. The article discusses a comparison of the influence of the length accuracy grade of cylindrical pellets on optimal calibration of time and velocity when the cylindrical vessel is emptied. The accuracy grade of cylindrical pellet length in the DEM sample plays a significant role in relation to the complexity of a created simulation. Full article
Open AccessFeature PaperArticle Hybrid Approach for Optimisation and Analysis of Palm Oil Mill
Processes 2019, 7(2), 100; https://doi.org/10.3390/pr7020100 (registering DOI)
Received: 11 January 2019 / Revised: 9 February 2019 / Accepted: 11 February 2019 / Published: 15 February 2019
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Abstract
A palm oil mill produces crude palm oil, crude palm kernel oil and other biomass from fresh fruit bunches. Although the milling process is well established in the industry, insufficient research and development reported in optimising and analysing the operations of a palm [...] Read more.
A palm oil mill produces crude palm oil, crude palm kernel oil and other biomass from fresh fruit bunches. Although the milling process is well established in the industry, insufficient research and development reported in optimising and analysing the operations of a palm oil mill. The performance of a palm oil mill (e.g., costs, utilisation and flexibility) is affected by factors such as operating time, capacity and fruit availability. This paper presents a hybrid combined mathematical programming and graphical approach to solve and analyse a palm oil mill case study in Malaysia. The hybrid approach consists of two main steps: (1) optimising a palm oil milling process to achieve maximum economic performance via input-output optimisation model (IOM); and (2) performing a feasible operating range analysis (FORA) to study the utilisation and flexibility of the developed design. Based on the optimised results, the total equipment units needed is reduced from 39 to 26 unit, bringing down the total capital investment by US$6.86 million (from 18.42 to 11.56 million US$) with 23% increment in economic performance (US$0.82 million/y) achieved. An analysis is presented to show the changes in utilisation and flexibility of the mill against capital investment. During the peak crop season, the utilisation index increases from 0.6 to 0.95 while the flexibility index decreases from 0.4 to 0.05. Full article
(This article belongs to the Special Issue Process Design, Integration, and Intensification)
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Open AccessFeature PaperArticle An Optimization-Based Framework to Define the Probabilistic Design Space of Pharmaceutical Processes with Model Uncertainty
Processes 2019, 7(2), 96; https://doi.org/10.3390/pr7020096
Received: 29 December 2018 / Revised: 30 January 2019 / Accepted: 1 February 2019 / Published: 14 February 2019
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Abstract
To increase manufacturing flexibility and system understanding in pharmaceutical development, the FDA launched the quality by design (QbD) initiative. Within QbD, the design space is the multidimensional region (of the input variables and process parameters) where product quality is assured. Given the high [...] Read more.
To increase manufacturing flexibility and system understanding in pharmaceutical development, the FDA launched the quality by design (QbD) initiative. Within QbD, the design space is the multidimensional region (of the input variables and process parameters) where product quality is assured. Given the high cost of extensive experimentation, there is a need for computational methods to estimate the probabilistic design space that considers interactions between critical process parameters and critical quality attributes, as well as model uncertainty. In this paper we propose two algorithms that extend the flexibility test and flexibility index formulations to replace simulation-based analysis and identify the probabilistic design space more efficiently. The effectiveness and computational efficiency of these approaches is shown on a small example and an industrial case study. Full article
(This article belongs to the Special Issue Model-Based Tools for Pharmaceutical Manufacturing Processes)
Open AccessArticle Degradation of Aqueous Polycyclic Musk Tonalide by Ultraviolet-Activated Free Chlorine
Processes 2019, 7(2), 95; https://doi.org/10.3390/pr7020095
Received: 6 December 2018 / Revised: 31 January 2019 / Accepted: 7 February 2019 / Published: 14 February 2019
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Abstract
Chlorine-incorporating ultraviolet (UV) provides a multiple barrier for drinking water disinfection. Meanwhile, post-UV employment can promote the degradation of micropollutants by radical production from chlorine residual photolysis. This work studied the degradation of one such chemical, tonalide (AHTN), by low-pressure UV-activated free chlorine [...] Read more.
Chlorine-incorporating ultraviolet (UV) provides a multiple barrier for drinking water disinfection. Meanwhile, post-UV employment can promote the degradation of micropollutants by radical production from chlorine residual photolysis. This work studied the degradation of one such chemical, tonalide (AHTN), by low-pressure UV-activated free chlorine (FC) under typical UV disinfection dosage of <200 mJ·cm−2 and water matrix of filtered tank effluent. AHTN was rapidly degraded by UV/FC in accordance with pseudo-first-order kinetics. The reaction rate constants of AHTN with reactive chlorine species and hydroxyl radical (HO•) were estimated. Mechanistic exploration evidenced that under UV/FC, AHTN degradation was attributable to direct photolysis, ClO•, and HO•. The carbonyl side chain of AHTN served as an important attack site for radicals. Water matrices, such as natural organic matter (NOM), HCO3, Cu2+, PO43−, and Fe2+, showed noticeable influence on the UV/FC process with an order of NOM > HCO3 >Cu2+ > PO43− > Fe2+. Reaction product analysis showed ignorable formation of chlorinated intermediates and disinfection byproducts. Full article
(This article belongs to the Special Issue Application of Advanced Oxidation Processes)
Open AccessFeature PaperReview Accelerating Biologics Manufacturing by Modeling or: Is Approval under the QbD and PAT Approaches Demanded by Authorities Acceptable Without a Digital-Twin?
Processes 2019, 7(2), 94; https://doi.org/10.3390/pr7020094
Received: 16 November 2018 / Revised: 16 January 2019 / Accepted: 31 January 2019 / Published: 13 February 2019
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Abstract
Innovative biologics, including cell therapeutics, virus-like particles, exosomes,
recombinant proteins, and peptides, seem likely to substitute monoclonal antibodies as the main
therapeutic entities in manufacturing over the next decades. This molecular variety causes a
growing need for a general change of methods as [...] Read more.
Innovative biologics, including cell therapeutics, virus-like particles, exosomes,
recombinant proteins, and peptides, seem likely to substitute monoclonal antibodies as the main
therapeutic entities in manufacturing over the next decades. This molecular variety causes a
growing need for a general change of methods as well as mindset in the process development stage,
as there are no platform processes available such as those for monoclonal antibodies. Moreover,
market competitiveness demands hyper-intensified processes, including accelerated decisions
toward batch or continuous operation of dedicated modular plant concepts. This indicates gaps in
process comprehension, when operation windows need to be run at the edges of optimization. In
this editorial, the authors review and assess potential methods and begin discussing possible
solutions throughout the workflow, from process development through piloting to manufacturing
operation from their point of view and experience. Especially, the state-of-the-art for modeling in
red biotechnology is assessed, clarifying differences and applications of statistical, rigorous
physical-chemical based models as well as cost modeling. “Digital-twins” are described and efforts
vs. benefits for new applications exemplified, including the regulation-demanded QbD (quality by
design) and PAT (process analytical technology) approaches towards digitalization or industry 4.0
based on advanced process control strategies. Finally, an analysis of the obstacles and possible
solutions for any successful and efficient industrialization of innovative methods from process
development, through piloting to manufacturing, results in some recommendations. A central
question therefore requires attention: Considering that QbD and PAT have been required by
authorities since 2004, can any biologic manufacturing process be approved by the regulatory
agencies without being modeled by a “digital-twin” as part of the filing documentation? Full article
(This article belongs to the Special Issue Processes Accelerating Biologics Manufacturing by Modelling)
Open AccessArticle Cogeneration Process Technical Viability for an Apartment Building: Case Study in Mexico
Processes 2019, 7(2), 93; https://doi.org/10.3390/pr7020093
Received: 29 December 2018 / Revised: 5 February 2019 / Accepted: 7 February 2019 / Published: 13 February 2019
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Abstract
The objective of this paper is to evaluate and to simulate the cogeneration process applied to an apartment building in the Polanco area (Mexico). Considering the building’s electric, thermal demand and consumption data, the cogeneration process model was simulated using Thermoflow© software [...] Read more.
The objective of this paper is to evaluate and to simulate the cogeneration process applied to an apartment building in the Polanco area (Mexico). Considering the building’s electric, thermal demand and consumption data, the cogeneration process model was simulated using Thermoflow© software (Thermoflow Inc., Jacksonville, FL, USA), in order to cover 1.1 MW of electric demand and to supply the thermal needs of hot water, heating, air conditioning and heating pool. As a result of analyzing various schemes of cogeneration, the most efficient scheme consists of the use of a gas turbine (Siemens model SGT-100-1S), achieving a cycle with efficiency of 84.4% and a heat rate of 14,901 kJ/kWh. The economic results of this evaluation show that it is possible to implement the cogeneration in the building with a natural gas price below US$0.014/kWh. The use of financing schemes makes the economic results more attractive. Furthermore, the percentage of the turbine load effect on the turbine load net power, cogeneration efficiency, chimney flue gas temperature, CO2 emission, net heat ratio, turbine fuel flow and after burner fuel flow was also studied. Full article
Open AccessFeature PaperArticle Distilling Robust Design Principles of Biocircuits Using Mixed Integer Dynamic Optimization
Processes 2019, 7(2), 92; https://doi.org/10.3390/pr7020092
Received: 3 December 2018 / Revised: 24 January 2019 / Accepted: 31 January 2019 / Published: 13 February 2019
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Abstract
A major challenge in model-based design of synthetic biochemical circuits is how to address uncertainty in the parameters. A circuit whose behavior is robust to variations in the parameters will have more chances to behave as predicted when implemented in practice, and also [...] Read more.
A major challenge in model-based design of synthetic biochemical circuits is how to address uncertainty in the parameters. A circuit whose behavior is robust to variations in the parameters will have more chances to behave as predicted when implemented in practice, and also to function reliably in presence of fluctuations and noise. Here, we extend our recent work on automated-design based on mixed-integer multi-criteria dynamic optimization to take into account parametric uncertainty. We exploit the intensive sampling of the design space performed by a global optimization algorithm to obtain the robustness of the topologies without significant additional computational effort. Our procedure provides automatically topologies that best trade-off performance and robustness against parameter fluctuations. We illustrate our approach considering the automated design of gene circuits achieving adaptation. Full article
(This article belongs to the Special Issue Computational Synthetic Biology)
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Open AccessArticle Purification of Flavonoids from Mulberry Leaves via High-Speed Counter-Current Chromatography
Processes 2019, 7(2), 91; https://doi.org/10.3390/pr7020091
Received: 22 January 2019 / Revised: 2 February 2019 / Accepted: 3 February 2019 / Published: 13 February 2019
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Abstract
In order to obtain high-purity flavonoid products, the extracts from mulberry leaves were separated and purified via high-speed counter-current chromatography (HSCCC). Moreover, the product was detected via high-performance liquid chromatography (HPLC). The characteristic absorption wavelength of the rutin standard for HSCCC detection and [...] Read more.
In order to obtain high-purity flavonoid products, the extracts from mulberry leaves were separated and purified via high-speed counter-current chromatography (HSCCC). Moreover, the product was detected via high-performance liquid chromatography (HPLC). The characteristic absorption wavelength of the rutin standard for HSCCC detection and HPLC analysis at 257 nm was tested by ultraviolet scanning analysis. The effect of solvent systems and mobile phase flow rate on the separation efficiency were then researched. Finally, the solvent system of V(ethyl acetate):V(n-butanol):V(water) = 4:1:5 was selected as the operating system for HSCCC. This work theoretically analyzed the impact of the molecular structure and polarity of flavonoids on the choice of solvent systems. The results showed that the mobile phase flow rate had a great influence on the separation efficiency. Furthermore, the separation efficiency increased as the mobile phase flow rate decreased. When the mobile phase flow rate was 5 mL/min, the peak time for flavonoids was 140 min, the retention of the stationary phase was 56.4%, and the purity of the product reached 93.8%. The results of this study greatly improved the purity of flavonoids in mulberry leaf and provided a strong support for the separation and purification of mulberry leaf extract. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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Open AccessArticle Evaluation of Conditions Affecting Properties of Gac (Momordica Cocochinensis Spreng) Oil-Loaded Solid Lipid Nanoparticles (SLNs) Synthesized Using High-Speed Homogenization Process
Processes 2019, 7(2), 90; https://doi.org/10.3390/pr7020090
Received: 4 January 2019 / Revised: 2 February 2019 / Accepted: 3 February 2019 / Published: 12 February 2019
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Abstract
In this study, we attempted the preparation of gac oil-loaded solid lipid nanoparticles (SLNs) by the high-speed homogenization method using Naterol SE solid lipid, a cosmetic self-emulsifying base, and surfactant and investigated the effects of different conditions on the characteristics of the resulting [...] Read more.
In this study, we attempted the preparation of gac oil-loaded solid lipid nanoparticles (SLNs) by the high-speed homogenization method using Naterol SE solid lipid, a cosmetic self-emulsifying base, and surfactant and investigated the effects of different conditions on the characteristics of the resulting nanoparticles. The suspensions containing 5% active agents (gac-oil, w/w) were dispersed in a surfactant concentration of 5% (w/w) (Span 80:Tween 80 ratio of 28:72 w/w) and 2.5% (w/w) of solid lipid (Naterol SE) concentration. Suitable conditions for hot homogenization were 13,000 rpm, 60 min and 60 °C for speed, time and temperature, respectively. The suitable conditions for the subsequent cold homogenization were 25 min of homogenization time and 5 °C of temperature. The results showed that the mean size of SLNs-gac oil was 107 nm (measured by laser diffraction spectrometry, LDS), and dried size of SLNs-gac oil ranged from 50 to 80 nm (measured by transmission electron microscope, TEM). In addition, the study investigated the impact of gac oil content on the particle size of SLNs-gac oil and its stability under different storage conditions of UV radiation and storage temperature. At high storage temperatures, the color changes (ΔE) of the samples were more profound in comparison to that at the low storage temperature. The ΔE value of the blank sample (SLN-FREE gac-oil) was higher than that of the Gac oil-loaded SLNs samples (SLN-gac oil). Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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Open AccessArticle Sensor Fault-Tolerant Control Design for Mini Motion Package Electro-Hydraulic Actuator
Processes 2019, 7(2), 89; https://doi.org/10.3390/pr7020089
Received: 10 January 2019 / Revised: 8 February 2019 / Accepted: 9 February 2019 / Published: 12 February 2019
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Abstract
With the rapid development of computer science and information and communication technology (ICT), increasingly intelligent, and complex systems have been applied to industries as well as human life. Fault-tolerant control (FTC) has, therefore, become one of the most important topics attracting attention from [...] Read more.
With the rapid development of computer science and information and communication technology (ICT), increasingly intelligent, and complex systems have been applied to industries as well as human life. Fault-tolerant control (FTC) has, therefore, become one of the most important topics attracting attention from both engineers and researchers to maintain system performances when faults occur. The ultimate goal of this study was to develop a sensor fault-tolerant control (SFTC) to enhance the robust position tracking control of a class of electro-hydraulic actuators called mini motion packages (MMPs), which are widely used for applications requiring large force-displacement ratios. First, a mathematical model of the MMP system is presented, which is then applied in the position control process of the MMP system. Here, a well-known proportional, integrated and derivative (PID) control algorithm is employed to ensure the positional response to the reference position. Second, an unknown input observer (UIO) is designed to estimate the state vector and sensor faults using a linear matrix inequality (LMI) optimization algorithm. Then an SFTC is used to deal with sensor faults of the MMP system. The SFTC is formed of the fault detection and the fault compensation with the goal of determining the location, time of occurrence, and magnitude of the faults in the fault signal compensation process. Finally, numerical simulations were run to demonstrate the superior performance of the proposed approach compared to traditional tracking control. Full article
(This article belongs to the Section Other Topics)
Open AccessFeature PaperArticle Phytochemical Content of Melissa officinalis L. Herbal Preparations Appropriate for Consumption
Processes 2019, 7(2), 88; https://doi.org/10.3390/pr7020088
Received: 18 January 2019 / Revised: 1 February 2019 / Accepted: 5 February 2019 / Published: 12 February 2019
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Abstract
Melissa Officinalis L. (MOL) domestic preparations appropriate for consumption were studied by monitoring content in Na, K, Ca, Li, phenolic bioactives (total phenols, hydroxycinnamic acid derivatives and flavonols), and antioxidant activity (1,1-diphenyl-2-picrylhydrazyl radical inhibition (DPPH) and ferric reducing ability (FRAP)). The effects of [...] Read more.
Melissa Officinalis L. (MOL) domestic preparations appropriate for consumption were studied by monitoring content in Na, K, Ca, Li, phenolic bioactives (total phenols, hydroxycinnamic acid derivatives and flavonols), and antioxidant activity (1,1-diphenyl-2-picrylhydrazyl radical inhibition (DPPH) and ferric reducing ability (FRAP)). The effects of practice applied, material to solvent ratio, time of preparation, and solvent were studied. MOL decoctions and infusions, commonly prepared at home, were better or of equal nutritional value to preparations upon ultrasounds or maceration concerning the studied parameters. Aqueous MOL preparations were richer in total phenols (704–1949 mg per 250 mL) and the examined macroelements (1.1–2.9, 30.5–288.4 and 50.1–176.1 mg Na, K and Ca per 250 mL, respectively) and showed better antioxidant activity compared to ethanol counterparts. The 25% w/v hydroethanolic MOL preparations, suitable for consumption, presented a significant content in phenolic antioxidants and in the examined minerals, too. MOL infusions were significantly richer in total phenols with respective chamomile and olive leaf ones, comparatively examined. Overall acceptance scores of aqueous MOL preparations indicated that bitterness has to be masked for efficient reception by the consumers. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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Open AccessArticle Using the Optimization Algorithm to Evaluate the Energetic Industry: A Case Study in Thailand
Processes 2019, 7(2), 87; https://doi.org/10.3390/pr7020087
Received: 17 December 2018 / Revised: 3 February 2019 / Accepted: 5 February 2019 / Published: 9 February 2019
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Abstract
Thailand’s economy is developing rapidly, with energy being a significant factor in this development. This study uses a variety of models to assess the performance of Thailand’s energy industry in two different phases, the first being from 2013 to 2017 and the second [...] Read more.
Thailand’s economy is developing rapidly, with energy being a significant factor in this development. This study uses a variety of models to assess the performance of Thailand’s energy industry in two different phases, the first being from 2013 to 2017 and the second from 2018 to 2020. The Malmquist model-one of data envelopment required input and output data that showed Thailand’s productivity index and the rate-of-change ratio, which is used to assess technical changes, change efficiency, and productivity changes of the 12 listed companies in energetic generation and distribution in Thailand. To calculate future indicators, the forecast data are generated by applying the Grey model (1,1) GM(1,1). Accuracy prediction is determined by the mean absolute percentage error (MAPE). The results show that the magnitude of the change in efficiency during the first period is stable, and some major changes in the technical level of some companies may be observed. In the future, the performance of most companies has increased steadily, but performance has been outstanding. This research provides insights into Thailand’s energy over the past few years, and predictions of future performance may be used as a reference for more purposes. Full article
(This article belongs to the Special Issue Energy, Economic and Environment for Industrial Production Processes)
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Open AccessArticle Life Cycle Assessment and Economic Analysis of an Innovative Biogas Membrane Reformer for Hydrogen Production
Processes 2019, 7(2), 86; https://doi.org/10.3390/pr7020086
Received: 21 December 2018 / Revised: 28 January 2019 / Accepted: 4 February 2019 / Published: 8 February 2019
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Abstract
This work investigates the environmental and economic performances of a membrane reactor for hydrogen production from raw biogas. Potential benefits of the innovative technology are compared against reference hydrogen production processes based on steam (or autothermal) reforming, water gas shift reactors and a [...] Read more.
This work investigates the environmental and economic performances of a membrane reactor for hydrogen production from raw biogas. Potential benefits of the innovative technology are compared against reference hydrogen production processes based on steam (or autothermal) reforming, water gas shift reactors and a pressure swing adsorption unit. Both biogas produced by landfill and anaerobic digestion are considered to evaluate the impact of biogas composition. Starting from the thermodynamic results, the environmental analysis is carried out using environmental Life cycle assessment (LCA). Results show that the adoption of the membrane reactor increases the system efficiency by more than 20 percentage points with respect to the reference cases. LCA analysis shows that the innovative BIONICO system performs better than reference systems when biogas becomes a limiting factor for hydrogen production to satisfy market demand, as a higher biogas conversion efficiency can potentially substitute more hydrogen produced by fossil fuels (natural gas). However, when biogas is not a limiting factor for hydrogen production, the innovative system can perform either similar or worse than reference systems, as in this case impacts are largely dominated by grid electric energy demand and component use rather than conversion efficiency. Focusing on the economic results, hydrogen production cost shows lower value with respect to the reference cases (4 €/kgH2 vs 4.2 €/kgH2) at the same hydrogen delivery pressure of 20 bar. Between landfill and anaerobic digestion cases, the latter has the lower costs as a consequence of the higher methane content. Full article
(This article belongs to the Special Issue Green Sustainable Chemical Processes)
Open AccessArticle Modeling, Management, and Control of an Autonomous Wind/Fuel Cell Micro-Grid System
Processes 2019, 7(2), 85; https://doi.org/10.3390/pr7020085
Received: 3 January 2019 / Revised: 25 January 2019 / Accepted: 4 February 2019 / Published: 8 February 2019
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Abstract
This paper proposes a microelectric power grid that includes wind and fuel cell power generation units, as well as a water electrolyzer for producing hydrogen gas. The grid is loaded by an induction motor (IM) as a dynamic load and constant impedance load. [...] Read more.
This paper proposes a microelectric power grid that includes wind and fuel cell power generation units, as well as a water electrolyzer for producing hydrogen gas. The grid is loaded by an induction motor (IM) as a dynamic load and constant impedance load. An optimal control algorithm using the Mine Blast Algorithm (MBA) is designed to improve the performance of the proposed renewable energy system. Normally, wind power is adapted to feed the loads at normal circumstances. Nevertheless, the fuel cell compensates extra load power demand. An optimal controller is applied to regulate the load voltage and frequency of the main power inverter. Also, optimal vector control is applied to the IM speed control. The response of the microgrid with the proposed optimal control is obtained under step variation in wind speed, load impedance, IM rotor speed, and motor mechanical load torque. The simulation results indicate that the proposed renewable generation system supplies the system loads perfectly and keeps up the desired load demand. Furthermore, the IM speed performance is acceptable under turbulent wind speed. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
Open AccessArticle Model for the Patterns of Salt-Spray-Induced Chloride Corrosion in Concretes under Coupling Action of Cyclic Loading and Salt Spray Corrosion
Processes 2019, 7(2), 84; https://doi.org/10.3390/pr7020084
Received: 15 December 2018 / Revised: 1 February 2019 / Accepted: 2 February 2019 / Published: 7 February 2019
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Abstract
In this study, the patterns of chloride ion erosion of unsaturated concrete subjected to the coupling action of cyclic loading and salt spray corrosion were experimentally studied, and Fick’s Second Law was used to fit the variation patterns of chloride concentration to obtain [...] Read more.
In this study, the patterns of chloride ion erosion of unsaturated concrete subjected to the coupling action of cyclic loading and salt spray corrosion were experimentally studied, and Fick’s Second Law was used to fit the variation patterns of chloride concentration to obtain the chloride diffusion coefficient. Accordingly, we have established a mathematical model that describes chloride transport in unsaturated concrete and accounts for the effects of gas flow, water migration, convection diffusion, and capillary action. This model is composed of three equations—the gas flow equation, the solution flow equation, and the solute convection–diffusion equation. The COMSOL numerical analysis software was subsequently used to obtain solutions for this model, based on parameters such as porosity and the chloride diffusion coefficient. Subsequently, the saturation, relative permeability, and the chloride ion concentration during the first corrosion cycle were analyzed. The numerical results were consistent with the experimental values and were therefore superior to the values obtained using Fick’s Second Law. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
Open AccessArticle Environmental Sustainability Assessment of Typical Cathode Materials of Lithium-Ion Battery Based on Three LCA Approaches
Processes 2019, 7(2), 83; https://doi.org/10.3390/pr7020083
Received: 2 January 2019 / Revised: 22 January 2019 / Accepted: 24 January 2019 / Published: 7 February 2019
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Abstract
With the rapid increase in production of lithium-ion batteries (LIBs) and environmental issues arising around the world, cathode materials, as the key component of all LIBs, especially need to be environmentally sustainable. However, a variety of life cycle assessment (LCA) methods increase the [...] Read more.
With the rapid increase in production of lithium-ion batteries (LIBs) and environmental issues arising around the world, cathode materials, as the key component of all LIBs, especially need to be environmentally sustainable. However, a variety of life cycle assessment (LCA) methods increase the difficulty of environmental sustainability assessment. Three authoritative LCAs, IMPACT 2002+, Eco-indicator 99(EI-99), and ReCiPe, are used to assess three traditional marketization cathode materials, compared with a new cathode model, FeF3(H2O)3/C. They all show that four cathode models are ranked by a descending sequence of environmental sustainable potential: FeF3(H2O)3/C, LiFe0.98Mn0.02PO4/C, LiFePO4/C, and LiCoO2/C in total values. Human health is a common issue regarding these four cathode materials. Lithium is the main contributor to the environmental impact of the latter three cathode materials. At the midpoint level in different LCAs, the toxicity and land issues for LiCoO2/C, the non-renewable resource consumption for LiFePO4/C, the metal resource consumption for LiFe0.98Mn0.02PO4/C, and the mineral refinement for FeF3(H2O)3/C show relatively low environmental sustainability. Three LCAs have little influence on total endpoint and element contribution values. However, at the midpoint level, the indicator with the lowest environmental sustainability for the same cathode materials is different in different methodologies. Full article
(This article belongs to the Special Issue Modelling and Process Control of Fuel Cell Systems)
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Open AccessArticle Agent-Based Simulation of Value Flow in an Industrial Production Process
Processes 2019, 7(2), 82; https://doi.org/10.3390/pr7020082
Received: 15 December 2018 / Revised: 2 February 2019 / Accepted: 3 February 2019 / Published: 7 February 2019
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Abstract
The current competitive environment demands companies to be more and more efficient. In order to increase manufacturing efficiency, two apparently independent approaches have emerged: lean strategies, focusing on identifying and minimizing non-added value activities, identifying wastes in the system and their elimination, and [...] Read more.
The current competitive environment demands companies to be more and more efficient. In order to increase manufacturing efficiency, two apparently independent approaches have emerged: lean strategies, focusing on identifying and minimizing non-added value activities, identifying wastes in the system and their elimination, and information tools for planning and controlling activities. In this paper, a manufacturing system was considered for which it was necessary to increase the production capacity in order to respond to the customer’s increased demand. A practical case study in the automotive industry for a medium-sized enterprise was considered. In order to investigate the production process parameters and to implement lean principles, Value Stream Mapping (current analysis and optimized solution) and Anylogic agent-based simulations were carried out. Based on this, the lean performances, specific for the target VSM, were evaluated in terms of key performance indicators. The benefits of integrating agent-based simulation in the design and analysis of the value flow in the production chain are the capitalization of the information offered by Value Stream Mapping and the possibility to choose the best one from the possible scenarios. It generates important time and cost reductions without further resource waste. Full article
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Open AccessFeature PaperArticle Reaction Kinetics of Carbon Dioxide in Aqueous Blends of N-Methyldiethanolamine and L-Arginine Using the Stopped-Flow Technique
Processes 2019, 7(2), 81; https://doi.org/10.3390/pr7020081
Received: 7 January 2019 / Revised: 28 January 2019 / Accepted: 29 January 2019 / Published: 6 February 2019
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Abstract
: Reduction of carbon dioxide emission from natural and industrial flue gases is paramount to help mitigate its effect on global warming. Efforts are continuously deployed worldwide to develop efficient technologies for CO2 capture. The use of environment friendly amino acids as [...] Read more.
: Reduction of carbon dioxide emission from natural and industrial flue gases is paramount to help mitigate its effect on global warming. Efforts are continuously deployed worldwide to develop efficient technologies for CO2 capture. The use of environment friendly amino acids as rate promoters in the present amine systems has attracted the attention of many researchers recently. In this work, the reaction kinetics of carbon dioxide with blends of N-methyldiethanolamine and L-Arginine was investigated using stopped flow technique. The experiments were performed over a temperature range of 293 to 313 K and solution concentration up to one molar of different amino acid/amine ratios. The overall reaction rate constant (kov) was found to increase with increasing temperature and amine concentration as well as with increased proportion of L-Arginine concentration in the mixture. The experimental data were fitted to the zwitterion and termolecular mechanisms using a nonlinear regression technique with an average absolute deviation (AAD) of 7.6% and 8.0%, respectively. A comparative study of the promoting effect of L-Arginine with that of the effect of Glycine and DEA in MDEA blends showed that MDEA-Arginine blend exhibits faster reaction rate with CO2 with respect to MDEA-DEA blend, while the case was converse when compared to the MDEA-Glycine blend. Full article
(This article belongs to the Special Issue Gas Capture Processes)
Open AccessArticle Optimal Operating Schedule for Energy Storage System: Focusing on Efficient Energy Management for Microgrid
Processes 2019, 7(2), 80; https://doi.org/10.3390/pr7020080
Received: 24 September 2018 / Revised: 26 December 2018 / Accepted: 28 December 2018 / Published: 6 February 2019
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Abstract
A microgrid is a group of many small-scale distributed energy resources, such as solar/wind energy sources, diesel generators, energy storage units, and electric loads. As a small-scale power grid, it can be operated independently or within an existing power grid(s). The microgrid energy [...] Read more.
A microgrid is a group of many small-scale distributed energy resources, such as solar/wind energy sources, diesel generators, energy storage units, and electric loads. As a small-scale power grid, it can be operated independently or within an existing power grid(s). The microgrid energy management system is a system that controls these components to achieve optimized operation in terms of price by reducing costs and maximizing efficiency in energy consumption. A post-Industry-4.0 consumer requires an optimal design and control of energy storage based on a demand forecast, using big data to stably supply clean, new, and renewable energy when necessary while maintaining a consistent level of quality. Thus, this study focused on software technology through which an optimized operation schedule for energy storage in a microgrid is derived. This energy storage operation schedule minimizes the costs involved in electricity use. For this, an optimization technique is used that sets an objective function representing the information and costs pertaining to electricity use, while minimizing its value by using Mixed Integer Linear Programming or a Genetic Algorithm. The main feature of the software is that an optimal operation schedule derivation function has been implemented with MATLAB for the following circumstances: when the basic operation rules are applied, when operating with another grid, when the external operating conditions are applied, and when the internal operating conditions are applied. Full article
Open AccessBrief Report Relationship Between MiRKAT and Coefficient of Determination in Similarity Matrix Regression
Processes 2019, 7(2), 79; https://doi.org/10.3390/pr7020079
Received: 30 December 2018 / Revised: 30 January 2019 / Accepted: 3 February 2019 / Published: 6 February 2019
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Abstract
The Microbiome Regression-based Kernel Association Test (MiRKAT) is widely used in testing for the association between microbiome compositions and an outcome of interest. The MiRKAT statistic is derived as a variance-component score test in a kernel machine regression-based generalized linear mixed model. In [...] Read more.
The Microbiome Regression-based Kernel Association Test (MiRKAT) is widely used in testing for the association between microbiome compositions and an outcome of interest. The MiRKAT statistic is derived as a variance-component score test in a kernel machine regression-based generalized linear mixed model. In this brief report, we show that the MiRKAT statistic is proportional to the R 2 (coefficient of determination) statistic in a similarity matrix regression, which characterizes the fraction of variability in outcome similarity, explained by microbiome similarity (up to a constant). Full article
(This article belongs to the Special Issue Microbial Communities in Health and Disease)
Open AccessArticle New Approaches in Modeling and Simulation of CO2 Absorption Reactor by Activated Potassium Carbonate Solution
Processes 2019, 7(2), 78; https://doi.org/10.3390/pr7020078
Received: 29 December 2018 / Revised: 18 January 2019 / Accepted: 28 January 2019 / Published: 4 February 2019
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Abstract
The increase of CO2 concentration in the atmosphere is in strong relation with the human-induced warming up due to industrial processes, transportation, etc. In order to reduce the CO2 content, end of pipe post-combustion methods can be used in addition to [...] Read more.
The increase of CO2 concentration in the atmosphere is in strong relation with the human-induced warming up due to industrial processes, transportation, etc. In order to reduce the CO2 content, end of pipe post-combustion methods can be used in addition to other methods and techniques. The CO2 capture by absorption in potassium carbonate–bicarbonate activated solutions remains a viable method. In this study, a mathematical model for a packed bed reactor has been developed and tested. The mathematical model is tested for an industrial reactor based on CO2 absorption in Carsol solutions. The proposed model was validated by resolving for CO2 and water content, carbonate–bicarbonate, concentrations etc. For each operational parameter the error was calculated. The error for CO2 concentration is up to 4%. The height of the packed reactor is calculated as function of CO2 concentration in the final gas phase. The validated model can also be used for absorbing other CO2 streams taking into account the fact that its efficiency was proved in industrial scale. Future reactors used for CO2 absorption should consist of two parts in order to use partially regenerated solutions in the first part, with significant energy savings in the operational costs. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control of Chemical Processes)
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Open AccessArticle Energy-Efficient Train Driving Strategy with Considering the Steep Downhill Segment
Processes 2019, 7(2), 77; https://doi.org/10.3390/pr7020077
Received: 13 January 2019 / Revised: 27 January 2019 / Accepted: 31 January 2019 / Published: 3 February 2019
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Abstract
Implementation of energy-efficient train driving strategy is an effective method to save train traction energy consumption, which has attracted much attention from both researchers and practitioners in recent years. Reducing the unnecessary braking during the journey and increasing the coasting distance are efficient [...] Read more.
Implementation of energy-efficient train driving strategy is an effective method to save train traction energy consumption, which has attracted much attention from both researchers and practitioners in recent years. Reducing the unnecessary braking during the journey and increasing the coasting distance are efficient to save energy in urban rail transit systems. In the steep downhill segment, the train speed will continue to increase without applying traction due to the ramp force. A high initial speed before stepping into the steep downhill segment will bring partial braking to prevent trains from overspeeding. Optimization of the driving strategy of urban rail trains can avoid the partial braking such that the potential energy is efficiently used and the traction energy is reduced. This paper presents an energy-efficient driving strategy optimization model for the segment with the steep downhill slopes. A numerical method is proposed to calculate the corresponding energy-efficient driving strategy of trains. Specifically, the steep downhill segment in the line is identified firstly for a given line and the solution space with different scenarios is analyzed. With the given cruising speed, a primary driving strategy is obtained, based on which the local driving strategy in the steep slope segment is optimized by replacing the cruising regime with coasting regime. Then, the adaptive gradient descent method is adopted to solve the optimal cruising speed corresponding to the minimum traction energy consumption of the train. Some case studies were conducted and the effectiveness of the algorithm was verified by comparing the energy-saving performance with the classical energy-efficient driving strategy of “Maximum traction–Cruising–Coasting–Maximum braking”. Full article
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