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Processes, Volume 7, Issue 1 (January 2019)

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Cover Story (view full-size image) This study presents CFD thermal design and experimental test results for a multi-tubular solar [...] Read more.
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Open AccessArticle Pilot Plant Data Assessment in Anaerobic Digestion of Organic Fraction of Municipal Waste Solids
Processes 2019, 7(1), 54; https://doi.org/10.3390/pr7010054
Received: 27 December 2018 / Revised: 16 January 2019 / Accepted: 16 January 2019 / Published: 21 January 2019
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Abstract
In this paper, a preliminary study of anaerobic digestion of organic fraction of municipal solid wastes (OFMSW) in presented with the aim to compare the performances of both wet- and dry-type reactors. The treatment of OFMSW via anaerobic digestion (AD) producing biogas is [...] Read more.
In this paper, a preliminary study of anaerobic digestion of organic fraction of municipal solid wastes (OFMSW) in presented with the aim to compare the performances of both wet- and dry-type reactors. The treatment of OFMSW via anaerobic digestion (AD) producing biogas is a process that is receiving a growing interest because two different needs can be coupled: the request of sustainable municipal waste treatments and increasing demand renewable energy. This paper aims to offer experimental results comparing batch test and continuous experimental reactors under different conditions of humidity and solid content. Results show that both the investigated configurations may be used for converting OFMSW into a high quality biogas and that the increase of dry matter in the continuous process still allows to achieve significant biogas production rates. A slight reduction of the methane content was observed (less than 5% relative) that can be also related to the change in the level of volatile fatty acids. These results are very promising in supporting the possibility of operating an industrial scale plant with a dry-process without affecting the system performance. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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Open AccessArticle Analysis of Influencing Factors of Occupational Safety and Health in Coal Chemical Enterprises Based on the Analytic Network Process and System Dynamics
Processes 2019, 7(1), 53; https://doi.org/10.3390/pr7010053
Received: 19 December 2018 / Revised: 16 January 2019 / Accepted: 17 January 2019 / Published: 21 January 2019
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Abstract
In the production process of coal chemical enterprises, there are factors such as dust, poisons, as well as toxic and harmful gases, which seriously restrict the safety and health of employees. It is urgent to strengthen research on occupational safety and health (OSH) [...] Read more.
In the production process of coal chemical enterprises, there are factors such as dust, poisons, as well as toxic and harmful gases, which seriously restrict the safety and health of employees. It is urgent to strengthen research on occupational safety and health (OSH) of coal chemical enterprises. Research on the influencing factors is very important to improve the level of OSH in coal chemical enterprises. Therefore, this paper analyzed the factors affecting OSH of coal chemical enterprises from four aspects: “human–machine–environment–management”. Then, an influencing factor indicator system was constructed. The weights of the indicator were analyzed using the Analytic Network Process (ANP). On this basis, the primary and secondary indicators of the influencing factors were ranked. Subsequently, the weights of ANP were taken as the influence coefficient between variables, and the System Dynamics (SD) model of OSH control measures was established and analyzed. According to the weights of ANP and the results of SD simulation, management and control measures were proposed to provide theoretical support and method guidance for improving the level of OSH in coal chemical enterprises. Finally, the research results were experimentally applied to coal chemical enterprises. The research results of the paper will improve the level of OSH in coal chemical enterprises of both theoretical and practical applications. Full article
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Open AccessFeature PaperArticle Component Characterization in a Growth-Dependent Physiological Context: Optimal Experimental Design
Processes 2019, 7(1), 52; https://doi.org/10.3390/pr7010052
Received: 28 November 2018 / Revised: 10 January 2019 / Accepted: 15 January 2019 / Published: 21 January 2019
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Abstract
Synthetic biology design challenges have driven the use of mathematical models to characterize genetic components and to explore complex design spaces. Traditional approaches to characterization have largely ignored the effect of strain and growth conditions on the dynamics of synthetic genetic circuits, and [...] Read more.
Synthetic biology design challenges have driven the use of mathematical models to characterize genetic components and to explore complex design spaces. Traditional approaches to characterization have largely ignored the effect of strain and growth conditions on the dynamics of synthetic genetic circuits, and have thus confounded intrinsic features of the circuit components with cell-level context effects. We present a model that distinguishes an activated gene’s intrinsic kinetics from its physiological context. We then demonstrate an optimal experimental design approach to identify dynamic induction experiments for efficient estimation of the component’s intrinsic parameters. Maximally informative experiments are chosen by formulating the design as an optimal control problem; direct multiple-shooting is used to identify the optimum. Our numerical results suggest that the intrinsic parameters of a genetic component can be more accurately estimated using optimal experimental designs, and that the choice of growth rates, sampling schedule, and input profile each play an important role. The proposed approach to coupled component–host modelling can support gene circuit design across a range of physiological conditions. Full article
(This article belongs to the Special Issue Computational Synthetic Biology)
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Open AccessReview Approaches to Suppress CO2-Induced Plasticization of Polyimide Membranes in Gas Separation Applications
Processes 2019, 7(1), 51; https://doi.org/10.3390/pr7010051
Received: 9 November 2018 / Revised: 2 January 2019 / Accepted: 15 January 2019 / Published: 21 January 2019
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Abstract
Polyimides with excellent physicochemical properties have aroused a great deal of interest as gas separation membranes; however, the severe performance decay due to CO2-induced plasticization remains a challenge. Fortunately, in recent years, advanced plasticization-resistant membranes of great commercial and environmental relevance [...] Read more.
Polyimides with excellent physicochemical properties have aroused a great deal of interest as gas separation membranes; however, the severe performance decay due to CO2-induced plasticization remains a challenge. Fortunately, in recent years, advanced plasticization-resistant membranes of great commercial and environmental relevance have been developed. In this review, we investigate the mechanism of plasticization due to CO2 permeation, introduce effective methods to suppress CO2-induced plasticization, propose evaluation criteria to assess the reduced plasticization performance, and clarify typical methods used for designing anti-plasticization membranes. Full article
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Open AccessArticle Model-Based Cost Optimization of Double-Effect Water-Lithium Bromide Absorption Refrigeration Systems
Processes 2019, 7(1), 50; https://doi.org/10.3390/pr7010050
Received: 16 October 2018 / Revised: 11 January 2019 / Accepted: 17 January 2019 / Published: 19 January 2019
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Abstract
This work presents optimization results obtained for a double-effect H2O-LiBr absorption refrigeration system considering the total cost as minimization criterion, for a wide range of cooling capacity values. As a model result, the sizes of the process units and the corresponding [...] Read more.
This work presents optimization results obtained for a double-effect H2O-LiBr absorption refrigeration system considering the total cost as minimization criterion, for a wide range of cooling capacity values. As a model result, the sizes of the process units and the corresponding operating conditions are obtained simultaneously. In this paper, the effectiveness factor of each proposed heat exchanger is considered as a model optimization variable which allows (if beneficial, according to the objective function to be minimized) its deletion from the optimal solution, therefore, helping us to determine the optimal configuration. Several optimization cases considering different target levels of cooling capacity are solved. Among the major results, it was observed that the total cost is considerably reduced when the solution heat exchanger operating at low temperature is deleted compared to the configuration that includes it. Also, it was found that the effect of removing this heat exchanger is comparatively more significant with increasing cooling capacity levels. A reduction of 9.8% in the total cost was obtained for a cooling capacity of 16 kW (11,537.2 $·year−1 vs. 12,794.5 $·year−1), while a reduction of 12% was obtained for a cooling capacity of 100 kW (31,338.1 $·year−1 vs. 35,613.9 $·year−1). The optimization mathematical model presented in this work assists in selecting the optimal process configuration, as well as determining the optimal process unit sizes and operating conditions of refrigeration systems. Full article
(This article belongs to the Special Issue Modeling and Simulation of Energy Systems)
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Open AccessArticle Processes of Cracking and Crushing in Hybrid Fibre Reinforced High-Performance Concrete Slabs
Processes 2019, 7(1), 49; https://doi.org/10.3390/pr7010049
Received: 23 November 2018 / Revised: 8 January 2019 / Accepted: 14 January 2019 / Published: 18 January 2019
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Abstract
This paper presents the experimental results obtained with the non-contact three-dimensional deformation measuring system–ARAMIS and finite element analysis performed using ANSYS of three slabs made of high-performance concrete (HPC) and hybrid (steel/ST and polypropylene/PP) fibre reinforced high-performance concrete (FRHPC). The research was performed [...] Read more.
This paper presents the experimental results obtained with the non-contact three-dimensional deformation measuring system–ARAMIS and finite element analysis performed using ANSYS of three slabs made of high-performance concrete (HPC) and hybrid (steel/ST and polypropylene/PP) fibre reinforced high-performance concrete (FRHPC). The research was performed on reinforced concrete (RC) slabs with a web mesh of ϕ8 mm bars. All the slabs had an identical amount of steel bars and differed by the fibre volume content. The main objective of the research was to determine the impact of adding polypropylene and steel fibres on the carrying capacity and ductility of HPC slabs. Analysis of the results was conducted based on load–deflection curves, crack distribution, vertical displacements and strains. The research findings indicate that fibres may improve peak strength. The presence of PP and ST hybrid fibres in HPC restricted the propagation of cracks. The energy absorption capacity as well as the ductility index of HPC can be raised by adding hybrid fibres. A comparison of the experimental test results with the nonlinear finite element analysis is made. The numerical results concurred well with the experimental data. The research results indicate that non-contact measurement of deformation is an effective tool for monitoring crushing in FRHPC slabs. Full article
(This article belongs to the Section Materials Processes)
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Open AccessArticle Employment of Emergency Advanced Nurses of Turkey: A Discrete-Event Simulation Application
Processes 2019, 7(1), 48; https://doi.org/10.3390/pr7010048
Received: 17 December 2018 / Revised: 29 December 2018 / Accepted: 16 January 2019 / Published: 18 January 2019
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Abstract
In the present study, problems in emergency services (ESs) were dealt with by analyzing the working system of ESs in Turkey. The purpose of this study was to reduce the waiting times spent in hospitals by employing advanced nurses (ANs) to treat patients [...] Read more.
In the present study, problems in emergency services (ESs) were dealt with by analyzing the working system of ESs in Turkey. The purpose of this study was to reduce the waiting times spent in hospitals by employing advanced nurses (ANs) to treat patients who are not urgent, or who may be treated as outpatients in ESs. By applying discrete-event simulation on a 1/24 (daily) and 7/24 (weekly) basis, and by employing ANs, it was determined that the number of patients that were treated increased by 26.71% on a 1/24 basis, and by 15.13% on a 7/24 basis. The waiting time that was spent from the admission to the ES until the treatment time decreased by 38.67% on a 1/24 basis and 53.66% on a 24/7 basis. Similarly, the length of stay was reduced from 82.46 min to 53.97 min in the ES. Among the findings, it was observed that the efficiency rate of the resources was balanced by the employment of ANs, although it was not possible to obtain sufficient efficiency from the resources used in the ESs prior to the present study. Full article
(This article belongs to the Special Issue Big Data in Biology, Life Sciences and Healthcare)
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Open AccessArticle Study on the Preparation and Hydration Properties of a New Cementitious Material for Tailings Discharge
Processes 2019, 7(1), 47; https://doi.org/10.3390/pr7010047
Received: 27 November 2018 / Revised: 6 January 2019 / Accepted: 14 January 2019 / Published: 17 January 2019
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Abstract
Blast furnace slag (BFS) is often used as a cement-based raw material for underground filling and surface cemented paste discharge of tailings during mining processes. This paper studied a new cement-based material (NCM) with BFS to replace ordinary Portland cement (OPC). A uniaxial [...] Read more.
Blast furnace slag (BFS) is often used as a cement-based raw material for underground filling and surface cemented paste discharge of tailings during mining processes. This paper studied a new cement-based material (NCM) with BFS to replace ordinary Portland cement (OPC). A uniaxial compressive strength (UCS) experiment was used to test the mechanical strength of samples; X-ray diffraction and thermal gravity experiments were used to test the crystalline phases and amount of hydration products by samples; a scanning electron microscope experiment was used to observe the influence of the hydration products morphology by samples; mercury intrusion porosimetry experiment was used to analyze the pore size distribution of samples. The samples with NCM had an optimum UCS; the crystalline phases of the hydration products were similar in OPC and NCM. However, the amount of product formed in OPC was less than that in NCM at the same curing time; more ettringite and calcium silicate hydrate were produced in samples with NCM, which filled the pores and enhanced the UCS of the samples. The final mercury intrusion volume of the samples with NCM were lower than the samples with OPC at the same curing time, which showed that samples with NCM had lower porosities. For the samples with NCM and OPC cured from 7 days to 28 days, the mercury intrusion volume was reduced by 18% and 13%, and the most common pore size of the samples reduced by 53% and 29%, respectively. This showed after 21 days curing time, the pores of all the samples getting smaller; however, the samples with NCM were more compact. The main ingredients of the NCM were clinker, lime, gypsum and BFS, and its ratio was 14:6:10:70. The content of additives to NCM was 0.4%, and the ratio of sodium sulfate: alum: sodium fluorosilicate was 2:1:1. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
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Open AccessArticle Simulating the Filtration Effects of Cement-Grout in Fractured Porous Media with the 3D Unified Pipe-Network Method
Processes 2019, 7(1), 46; https://doi.org/10.3390/pr7010046
Received: 8 December 2018 / Revised: 9 January 2019 / Accepted: 14 January 2019 / Published: 16 January 2019
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Abstract
In grouting process, filtration is the retention and adsorption of cement-grout particles in a porous/fractured medium. Filtration partly/even completely blocks the transportation channels in the medium, greatly decreasing its permeability. Taking into account filtration effects is essential for accurately estimating the grout penetration [...] Read more.
In grouting process, filtration is the retention and adsorption of cement-grout particles in a porous/fractured medium. Filtration partly/even completely blocks the transportation channels in the medium, greatly decreasing its permeability. Taking into account filtration effects is essential for accurately estimating the grout penetration region. In this paper, the 3D unified pipe-network method (UPM) is adopted for simulating 3D grout penetration process in a fractured porous medium, considering filtration effects. The grout is assumed to exhibit two-phase flow, and the filtration effects depend on not only the concentration and rheology of the grout but also the porosity and permeability of the fractured porous medium. By comparing the model with the experimental results, we firstly verify the proposed numerical model. Then sensitivity analysis is conducted, showing the influences of grout injection pressures, the water–cement ratios of grout (W/C) and the grout injection rates on filtration effect. Finally, the grout filtration process in a complex 3D fractured network is simulated, indicating that the size of the grout penetration region is limited due to filtration. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
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Open AccessArticle Characterization, Expression Profiling, and Functional Analyses of a 4CL-Like Gene of Populus trichocarpa
Processes 2019, 7(1), 45; https://doi.org/10.3390/pr7010045
Received: 2 December 2018 / Revised: 11 January 2019 / Accepted: 11 January 2019 / Published: 16 January 2019
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Abstract
Adenosine 5′-monophosphate (AMP) (adenylate)-forming acetyl-CoA synthetase (ACS) catalyzes the formation of acetyl-coenzyme A (CoA), and the ACS family is closely related to the 4-coumarate CoA ligase (4CL) family. In this study, a 4CL-like gene was cloned from Populus trichocarpa and named Pt4CL-like. Characterization [...] Read more.
Adenosine 5′-monophosphate (AMP) (adenylate)-forming acetyl-CoA synthetase (ACS) catalyzes the formation of acetyl-coenzyme A (CoA), and the ACS family is closely related to the 4-coumarate CoA ligase (4CL) family. In this study, a 4CL-like gene was cloned from Populus trichocarpa and named Pt4CL-like. Characterization of Pt4CL-like, using bioinformatics, showed that it contained box I and box II domains at the end of the C-terminal sequence, and there is a characteristic sequence of ACS, namely, peroxisome-targeting sequence (PTS). Real-time PCR results showed that the 4CL-like gene was expressed in all tissues tested, and was highly expressed in the stems. A denaturation and renaturation process was conducted, and the recombinant Pt4CL-like protein was purified through HisTrapTM high performance affinity chromatography. It showed Pt4CL-like protein did not catalyze substrates of 4CL, but could significantly catalyzed sodium acetate. These results indicate that Pt4CL-like protein belongs to the ACS family, providing a theoretical basis for further analysis and comparison of the functions of adenylate-forming enzymes and 4CL family. Full article
(This article belongs to the Section Biological Systems)
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Open AccessArticle Adsorption of Organic Constituents from Reverse Osmosis Concentrate in Coal Chemical Industry by Coking Coal
Processes 2019, 7(1), 44; https://doi.org/10.3390/pr7010044
Received: 20 November 2018 / Revised: 8 January 2019 / Accepted: 9 January 2019 / Published: 16 January 2019
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Abstract
To solve the unwieldy problem of coal chemical wastewater reverse osmosis concentrate (ROC), a novel treatment method in which coking coal was used to adsorb the organic from ROC and the adsorption mechanism involved was investigated. The results showed that the organic components [...] Read more.
To solve the unwieldy problem of coal chemical wastewater reverse osmosis concentrate (ROC), a novel treatment method in which coking coal was used to adsorb the organic from ROC and the adsorption mechanism involved was investigated. The results showed that the organic components in the ROC of coal chemical industry can be effectively absorbed by the coking coal and the total organic carbon, UV254 and chromaticity of treated ROC reduced by 70.18%, 70.15% and 59.55%, respectively, at the coking coal dosage of 80 g/L. The isothermal adsorption data were fitted to the Langmuir model well. The kinetics were expressed well by the quasi-second-order kinetic model. The intragranular diffusion model and the BET (Acronym for three scientists: Brunauer–Emmett–Teller) test showed that the adsorption occurred mainly on the surface of the coking coal and its macropores and mesopores. When the pollutants further diffused to the mesopores and micropores, the adsorption rate decreased. The result of X-ray photoelectron spectroscopy and fourier transform infrared spectroscopy spectra showed that the coking coal mainly adsorbed the nitrogen and oxygen species and the halogenated hydrocarbon organic compounds in the ROC. The chlorinated hydrocarbons and heterocyclic organics in ROC are adsorbed on the surface of coking coal. Full article
(This article belongs to the Special Issue Wastewater Treatment Processes)
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Open AccessCase Report Application of Supergravity Technology in a TEG Dehydration Process for Offshore Platforms
Processes 2019, 7(1), 43; https://doi.org/10.3390/pr7010043
Received: 2 December 2018 / Revised: 1 January 2019 / Accepted: 10 January 2019 / Published: 15 January 2019
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Abstract
In the dehydration process of offshore natural gas production, due to the site limitation of the platform, if the conventional triethylene glycol (TEG) dehydration process is employed, the size of the absorption tower is usually small. However, in the case of fluctuations in [...] Read more.
In the dehydration process of offshore natural gas production, due to the site limitation of the platform, if the conventional triethylene glycol (TEG) dehydration process is employed, the size of the absorption tower is usually small. However, in the case of fluctuations in raw material gas and large gas production, it is easy to cause a large loss of TEG and a flooding event, resulting in the water dew point of natural gas not meeting the requirements. Therefore, combined with the dehydration process of TEG and supergravity technology, a new dehydration process of natural gas suitable for offshore platforms is proposed in this paper. The principle and process of the TEG dehydration process based on supergravity technology are discussed by establishing a mass transfer model. The laboratory experiment of the new process is carried out, and the effects of TEG flow rate, super-gravity packed bed rotation speed, and gas flow rate on the air dew point are obtained. By studying the dewatering balance of the rotating packed bed in the improved process, it is proved that the dewatering performance of the high gravity machine (Higee) is much better than that of the ordinary tower dewatering equipment. Through field experiments, the dewatering effect of continuous operation and sudden changes in working conditions is obtained, indicating that the Higee can completely replace the traditional tower equipment for natural gas dehydration. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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Open AccessArticle Optimization of the Melting Performance of a Thermal Energy Storage Unit with Fractal Net Fins
Processes 2019, 7(1), 42; https://doi.org/10.3390/pr7010042
Received: 22 November 2018 / Revised: 26 December 2018 / Accepted: 29 December 2018 / Published: 15 January 2019
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Abstract
In this study, fractal net fins were introduced to improve the melting performance of a thermal energy storage unit. A transient model for melting heat transfer for phase change material (PCM) was presented and numerically analyzed, to study the melting performance in a [...] Read more.
In this study, fractal net fins were introduced to improve the melting performance of a thermal energy storage unit. A transient model for melting heat transfer for phase change material (PCM) was presented and numerically analyzed, to study the melting performance in a thermal energy storage unit using fractal net fins. The melting phase change process was modelled using the apparent heat capacity method. The evolutions of temperature and the liquid fraction in the thermal energy storage unit were investigated and discussed. The effects of the length and width ratios of the fractal net on melting performance were analyzed to obtain the optimal fin configuration. The results indicated that the fractal net fins significantly enhanced the melting heat transfer performance of the PCM in a thermal energy storage unit. The fractal net fins configuration was optimal when the length and width ratios of the fractal net were 0.5. The temperature response at the corner points of the fractal net fins was faster than that in the central points. Full article
(This article belongs to the Section Other Topics)
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Open AccessArticle Efficient Removal of Hexavalent Chromium from Wastewater with Electro-Reduction
Processes 2019, 7(1), 41; https://doi.org/10.3390/pr7010041
Received: 19 December 2018 / Revised: 8 January 2019 / Accepted: 9 January 2019 / Published: 15 January 2019
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Abstract
Removal of hexavalent chromium had attracted much attention as it is a hazardous contaminant. An electrocoagulation-like technology electro-reduction was applied. The chromium (VI) in the wastewater was reduced to chromium (III) by the electron supplied by electricity power and Fe2+, formed [...] Read more.
Removal of hexavalent chromium had attracted much attention as it is a hazardous contaminant. An electrocoagulation-like technology electro-reduction was applied. The chromium (VI) in the wastewater was reduced to chromium (III) by the electron supplied by electricity power and Fe2+, formed from corrosion of steel electrodes in acidic conditions. The mechanism and parameters affecting the reaction were investigated. The results optimized by response surface methodology indicated that the influence of single factor on the reduction efficiency followed the order: A: dosage of H2SO4 > C: reaction time > D: reaction temperature > B: current intensity. The reduction efficiency was hardly affected by current intensity, while it was increased with the increasing of reaction time and acid concentration. The reducing agent, Fe2+ an and extra free electron, acted as a reducing agent and could easily reduce hexavalent chromium to trivalent chromium at high temperatures in an acidic medium. Full article
(This article belongs to the Special Issue Wastewater Treatment Processes)
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Open AccessFeature PaperArticle Effective Dye Degradation by Graphene Oxide Supported Manganese Oxide
Processes 2019, 7(1), 40; https://doi.org/10.3390/pr7010040
Received: 1 December 2018 / Revised: 28 December 2018 / Accepted: 11 January 2019 / Published: 14 January 2019
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Graphene oxide (GO) was used as a support for manganese oxide (MnO2) for the preparation of a nanocomposite catalyst for the degradation of an azo dye, Reactive Black 5 (RB5). The nanocomposite was characterized for the structure by XRD, for the [...] Read more.
Graphene oxide (GO) was used as a support for manganese oxide (MnO2) for the preparation of a nanocomposite catalyst for the degradation of an azo dye, Reactive Black 5 (RB5). The nanocomposite was characterized for the structure by XRD, for the morphology with SEM, and for the surface chemistry with FTIR and potentiometric titration measurements. The GO-MnO2 nanocomposite presented a high catalytic activity for the degradation/oxidation of RB5 at ambient conditions, which was higher than that of the pure MnO2 and could be attributed to the beneficial contribution of the manganese oxide and the graphene oxide. Full article
(This article belongs to the Special Issue Wastewater Treatment Processes)
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Open AccessArticle Catastrophic Health Expenditures and Its Inequality in Households with Cancer Patients: A Panel Study
Processes 2019, 7(1), 39; https://doi.org/10.3390/pr7010039
Received: 28 November 2018 / Revised: 28 December 2018 / Accepted: 10 January 2019 / Published: 14 January 2019
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Abstract
This study aims to examine the determinants of catastrophic health expenditure in households with cancer patients by conducting a panel analysis of three-year data. Data are adopted from surveys administered by Korea Health Panel for 2012–2014. We conducted correspondence and conditional transition probability [...] Read more.
This study aims to examine the determinants of catastrophic health expenditure in households with cancer patients by conducting a panel analysis of three-year data. Data are adopted from surveys administered by Korea Health Panel for 2012–2014. We conducted correspondence and conditional transition probability analyses to examine households that incurred catastrophic health expenditure, followed by a panel logit analysis. The analyses reveal three notable results. First, the occurrence of catastrophic health expenditure differs by age group, that is, the probability of incurring catastrophic health expenditure increases with age. Second, this probability is higher in households with National Health Insurance than those receiving medical care benefits. Finally, households without private health insurance report a higher occurrence rate. The findings suggest that elderly people with cancer have greater medical coverage and healthcare needs. Private health insurance contributes toward protecting households from catastrophic health expenditure. Therefore, future research is needed on catastrophic health expenditure with focus on varying age groups, healthcare coverage type, and private health insurance. Full article
(This article belongs to the Special Issue Big Data in Biology, Life Sciences and Healthcare)
Open AccessArticle Model-Based Stochastic Fault Detection and Diagnosis of Lithium-Ion Batteries
Processes 2019, 7(1), 38; https://doi.org/10.3390/pr7010038
Received: 6 December 2018 / Revised: 1 January 2019 / Accepted: 9 January 2019 / Published: 13 January 2019
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Abstract
The Lithium-ion battery (Li-ion) has become the dominant energy storage solution in many applications, such as hybrid electric and electric vehicles, due to its higher energy density and longer life cycle. For these applications, the battery should perform reliably and pose no safety [...] Read more.
The Lithium-ion battery (Li-ion) has become the dominant energy storage solution in many applications, such as hybrid electric and electric vehicles, due to its higher energy density and longer life cycle. For these applications, the battery should perform reliably and pose no safety threats. However, the performance of Li-ion batteries can be affected by abnormal thermal behaviors, defined as faults. It is essential to develop a reliable thermal management system to accurately predict and monitor thermal behavior of a Li-ion battery. Using the first-principle models of batteries, this work presents a stochastic fault detection and diagnosis (FDD) algorithm to identify two particular faults in Li-ion battery cells, using easily measured quantities such as temperatures. In addition, models used for FDD are typically derived from the underlying physical phenomena. To make a model tractable and useful, it is common to make simplifications during the development of the model, which may consequently introduce a mismatch between models and battery cells. Further, FDD algorithms can be affected by uncertainty, which may originate from either intrinsic time varying phenomena or model calibration with noisy data. A two-step FDD algorithm is developed in this work to correct a model of Li-ion battery cells and to identify faulty operations in a normal operating condition. An iterative optimization problem is proposed to correct the model by incorporating the errors between the measured quantities and model predictions, which is followed by an optimization-based FDD to provide a probabilistic description of the occurrence of possible faults, while taking the uncertainty into account. The two-step stochastic FDD algorithm is shown to be efficient in terms of the fault detection rate for both individual and simultaneous faults in Li-ion batteries, as compared to Monte Carlo (MC) simulations. Full article
(This article belongs to the Special Issue Optimization for Control, Observation and Safety)
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Open AccessFeature PaperArticle Multiscale Agent-Based and Hybrid Modeling of the Tumor Immune Microenvironment
Processes 2019, 7(1), 37; https://doi.org/10.3390/pr7010037
Received: 11 December 2018 / Revised: 9 January 2019 / Accepted: 10 January 2019 / Published: 13 January 2019
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Abstract
Multiscale systems biology and systems pharmacology are powerful methodologies that are playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena and in clinical applications. In this review, we summarize the state of the art in the applications of agent-based models [...] Read more.
Multiscale systems biology and systems pharmacology are powerful methodologies that are playing increasingly important roles in understanding the fundamental mechanisms of biological phenomena and in clinical applications. In this review, we summarize the state of the art in the applications of agent-based models (ABM) and hybrid modeling to the tumor immune microenvironment and cancer immune response, including immunotherapy. Heterogeneity is a hallmark of cancer; tumor heterogeneity at the molecular, cellular, and tissue scales is a major determinant of metastasis, drug resistance, and low response rate to molecular targeted therapies and immunotherapies. Agent-based modeling is an effective methodology to obtain and understand quantitative characteristics of these processes and to propose clinical solutions aimed at overcoming the current obstacles in cancer treatment. We review models focusing on intra-tumor heterogeneity, particularly on interactions between cancer cells and stromal cells, including immune cells, the role of tumor-associated vasculature in the immune response, immune-related tumor mechanobiology, and cancer immunotherapy. We discuss the role of digital pathology in parameterizing and validating spatial computational models and potential applications to therapeutics. Full article
(This article belongs to the Special Issue Methods in Computational Biology)
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Open AccessFeature PaperReview Revolution 4.0: Industry vs. Agriculture in a Future Development for SMEs
Processes 2019, 7(1), 36; https://doi.org/10.3390/pr7010036
Received: 21 November 2018 / Revised: 4 January 2019 / Accepted: 8 January 2019 / Published: 11 January 2019
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Abstract
The present review retraces the steps of the industrial and agriculture revolution that have taken place up to the present day, giving ideas and considerations for the future. This paper analyses the specific challenges facing agriculture along the farming supply chain to permit [...] Read more.
The present review retraces the steps of the industrial and agriculture revolution that have taken place up to the present day, giving ideas and considerations for the future. This paper analyses the specific challenges facing agriculture along the farming supply chain to permit the operative implementation of Industry 4.0 guidelines. The subsequent scientific value is an investigation of how Industry 4.0 approaches can be improved and be pertinent to the agricultural sector. However, industry is progressing at a much faster rate than agriculture. In fact, already today experts talk about Industry 5.0. On the other hand, the 4.0 revolution in agriculture is still limited to a few innovative firms. For this reason, this work deals with how technological development affects different sectors (industry and agriculture) in different ways. In this innovative background, despite the advantages of industry or agriculture 4.0 for large enterprises, small- and medium-sized enterprises (SMEs) often face complications in such innovative processes due to the continuous development in innovations and technologies. Policy makers should propose strategies, calls for proposals with aim of supporting SMEs to invest on these technologies and making them more competitive in the marketplace. Full article
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Open AccessArticle The Effect of the Presence of Very Cohesive Geldart C Ultra-Fine Particles on the Fluidization of Geldart A Fine Particle Beds
Processes 2019, 7(1), 35; https://doi.org/10.3390/pr7010035
Received: 27 November 2018 / Revised: 31 December 2018 / Accepted: 5 January 2019 / Published: 11 January 2019
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Abstract
The effect of the presence of ultra-fines (d < 10 μm) on the fluidization of a bed containing fine particles (d < 100 μm), is the subject of this paper. Practically, it can happen due to breakage or surface abrasion of [...] Read more.
The effect of the presence of ultra-fines (d < 10 μm) on the fluidization of a bed containing fine particles (d < 100 μm), is the subject of this paper. Practically, it can happen due to breakage or surface abrasion of the fine particles in some processes which totally changes the size distribution and also fluidization behaviour. The materials used in this study are both ground calcium carbonate (GCC); fine is CALCIT MVT 100 (Geldart’s group A) and ultra-fine is CALCIT MX 10 (group C). The experimental results for different binary mixtures of these materials (ultra-fines have 30%, 50%, or 68% of the total mixture weight) show that the physical properties of the mixtures are close to those of pure ultra-fine powders. Using mean values of the bed pressure drop calculated from several independent repetitions, the fluidization behaviour of different mixtures are compared and discussed. The fluidization behaviour of the mixtures is non-reproducible and includes cracking, channelling and agglomeration (like for pure ultra-fine powders). Increasing the portion of ultra-fine materials in the mixture causes a delay in starting partial fluidization, an increase in the bed pressure drop as well as a delay in reaching the peak point. Full article
(This article belongs to the Special Issue Multiphase Reaction Engineering, Reactors and Processes)
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Open AccessArticle Textile Wastewater Treatment for Water Reuse: A Case Study
Processes 2019, 7(1), 34; https://doi.org/10.3390/pr7010034
Received: 11 December 2018 / Revised: 30 December 2018 / Accepted: 3 January 2019 / Published: 11 January 2019
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Abstract
The reduced natural waters and the large amount of wastewater produced by textile industry necessitate an effective water reuse treatment. In this study, a combined two-stage water reuse treatment was established to enhance the quality and recovery rate of reused water. The primary [...] Read more.
The reduced natural waters and the large amount of wastewater produced by textile industry necessitate an effective water reuse treatment. In this study, a combined two-stage water reuse treatment was established to enhance the quality and recovery rate of reused water. The primary treatment incorporated a flocculation and sedimentation system, two sand filtration units, an ozonation unit, an ultrafiltration (UF) system, and a reverse osmosis (RO) system. The second treatment included an ozonation unit, a sand filtration unit, and UF and RO systems. The color removal rate increased with the increasing ozone dosage, and the relational expression between the ozone dosage and color removal rate was fitted. Ozonation greatly reduced the color by 92.59 and 97.27 times during the primary and second ozonation stages, respectively. RO had the highest removal rate. The combined processes showed good performance in water reuse treatment. The treated, reused water satisfied the reuse standard and surpassed the drinking water standard rates for chemical oxygen consumption (CODcr), color, NH3-N, hardness, Cl, SO42−, turbidity, Fe3+, and Cu2+. The operating cost of reuse water treatment was approximately 0.44 USD·m−3. Full article
(This article belongs to the Special Issue Wastewater Treatment Processes)
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Open AccessArticle Mixing Efficiency Analysis on Droplet Formation Process in Microchannels by Numerical Methods
Processes 2019, 7(1), 33; https://doi.org/10.3390/pr7010033
Received: 20 December 2018 / Revised: 7 January 2019 / Accepted: 8 January 2019 / Published: 11 January 2019
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Abstract
Liquid–liquid two-phase flow in microchannels has attracted much attention, due to the superiority of mass transfer enhancement. One of the biggest unresolved challenges is the low mixing efficiency at the microscale. Suitable mixing efficiency is important to promote the mass transfer of two-phase [...] Read more.
Liquid–liquid two-phase flow in microchannels has attracted much attention, due to the superiority of mass transfer enhancement. One of the biggest unresolved challenges is the low mixing efficiency at the microscale. Suitable mixing efficiency is important to promote the mass transfer of two-phase flow in microchannels. In this paper, the mixing efficiency in three junction configurations, including a cross-shaped junction, a cross-shaped T-junction, and a T-junction, is investigated by the volume of fluid (VOF) method coupled with user-defined scalar (UDS) model. All three junction configurations are designed with the same hydraulic diameter of 100 μm. Mixing components are distributed in the front and back parts of the droplet. The mixing efficiency in the droplet forming stage and the droplet moving stage are compared quantitatively. Results show that different junction configurations create very different mixing efficiencies, and the cross-shaped T-junction performs best, with relatively lower disperse phase fractions. However, with an increase of the disperse phase fraction, the cross-shaped junction is superior. Full article
(This article belongs to the Section Other Topics)
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Open AccessEditorial Acknowledgement to Reviewers of Processes in 2018
Processes 2019, 7(1), 32; https://doi.org/10.3390/pr7010032
Published: 11 January 2019
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Abstract
Rigorous peer-review is the corner-stone of high-quality academic publishing [...] Full article
Open AccessFeature PaperArticle Multi-Tubular Reactor for Hydrogen Production: CFD Thermal Design and Experimental Testing
Processes 2019, 7(1), 31; https://doi.org/10.3390/pr7010031
Received: 3 December 2018 / Revised: 21 December 2018 / Accepted: 27 December 2018 / Published: 11 January 2019
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Abstract
This study presents the Computational Fluid Dynamics (CFD) thermal design and experimental tests results for a multi-tubular solar reactor for hydrogen production based on the ferrite thermochemical cycle in a pilot plant in the Plataforma Solar de Almería (PSA). The methodology followed for [...] Read more.
This study presents the Computational Fluid Dynamics (CFD) thermal design and experimental tests results for a multi-tubular solar reactor for hydrogen production based on the ferrite thermochemical cycle in a pilot plant in the Plataforma Solar de Almería (PSA). The methodology followed for the solar reactor design is described, as well as the experimental tests carried out during the testing campaign and characterization of the reactor. The CFD model developed for the thermal design of the solar reactor has been validated against the experimental measurements, with a temperature error ranging from 1% to around 10% depending on the location within the reactor. The thermal balance in the reactor (cavity and tubes) has been also solved by the CFD model, showing a 7.9% thermal efficiency of the reactor. CFD results also show the percentage of reacting media inside the tubes which achieve the required temperature for the endothermic reaction process, with 90% of the ferrite pellets inside the tubes above the required temperature of 900 °C. The multi-tubular solar reactor designed with aid of CFD modelling and simulations has been built and operated successfully. Full article
(This article belongs to the Special Issue Hydrogen Production Technologies)
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Open AccessArticle Ultrasonic-Assisted Extraction and Swarm Intelligence for Calculating Optimum Values of Obtaining Boric Acid from Tincal Mineral
Processes 2019, 7(1), 30; https://doi.org/10.3390/pr7010030
Received: 26 November 2018 / Revised: 18 December 2018 / Accepted: 27 December 2018 / Published: 10 January 2019
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Abstract
The objective of this study is to focus on boric acid extraction from the mineral tincal, in order to determine the optimum conditions thanks to the ultrasonic-assisted extraction (UAE) technique (with the response surface methodology (RSM) for the first time), and artificial intelligence [...] Read more.
The objective of this study is to focus on boric acid extraction from the mineral tincal, in order to determine the optimum conditions thanks to the ultrasonic-assisted extraction (UAE) technique (with the response surface methodology (RSM) for the first time), and artificial intelligence based swarm intelligence. Characterization of the tincal were done by using thermo-gravimetric assay (TG-DTA), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analyses. In detail, a central composite design (CCD) was used for determining the effects of different solvent/solid ratios, pH, extraction time, and extraction temperature on the yield, which was determined by the conductometric method. The optimum values regarding the best extraction process was calculated by using five different swarm intelligence techniques: Particle swarm optimization (PSO), cuckoo search (CS), genetic algorithms (GA), Differential evolution (DE), and the vortex optimization algorithm (VOA). In the study content, technical details regarding to background and applied experimental processes are given and the findings pointing an approximate 85–92% boron extraction from tincal ore are discussed generally. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
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Open AccessArticle Ambient Pressure-Dried Graphene–Composite Carbon Aerogel for Capacitive Deionization
Processes 2019, 7(1), 29; https://doi.org/10.3390/pr7010029
Received: 27 November 2018 / Revised: 20 December 2018 / Accepted: 3 January 2019 / Published: 8 January 2019
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Abstract
Capacitive deionization (CDI) technology possessing excellent desalination performance and energy efficiency is currently being widely studied in seawater desalination. In this work, the graphene–composite carbon aerogels (GCCAs) easily prepared by an ambient pressure drying method served as electrodes to remove salt ions in [...] Read more.
Capacitive deionization (CDI) technology possessing excellent desalination performance and energy efficiency is currently being widely studied in seawater desalination. In this work, the graphene–composite carbon aerogels (GCCAs) easily prepared by an ambient pressure drying method served as electrodes to remove salt ions in aqueous solution by CDI. The microstructure of the obtained GCCAs was found to depend on the component content in the precursor solution, and could be controlled through varying the mass ratio of resorcinol and formaldehyde to graphene oxide (RF/GO). The surface characteristics and microstructure of GCCAs were characterized by Raman spectroscopy, X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). In addition, the electrochemical tests and CDI experiments of GCCA electrodes were conducted in NaCl solution. Thanks to the reasonable pore structure and highly conductive network, GCCA-150 achieved the best salt adsorption capacity of 26.9 mg/g and 18.9 mg/g in NaCl solutions with concentrations of 500 mg/L and 250 mg/L, respectively. Full article
(This article belongs to the Special Issue Renewable Energy in Water Desalination: Model Based Approach)
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Open AccessArticle Numerical Investigation of Hydraulic Fracture Propagation Based on Cohesive Zone Model in Naturally Fractured Formations
Processes 2019, 7(1), 28; https://doi.org/10.3390/pr7010028
Received: 11 December 2018 / Revised: 2 January 2019 / Accepted: 2 January 2019 / Published: 8 January 2019
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Abstract
Complex propagation patterns of hydraulic fractures often play important roles in naturally fractured formations due to complex mechanisms. Therefore, understanding propagation patterns and the geometry of fractures is essential for hydraulic fracturing design. In this work, a seepage–stress–damage coupled model based on the [...] Read more.
Complex propagation patterns of hydraulic fractures often play important roles in naturally fractured formations due to complex mechanisms. Therefore, understanding propagation patterns and the geometry of fractures is essential for hydraulic fracturing design. In this work, a seepage–stress–damage coupled model based on the finite pore pressure cohesive zone (PPCZ) method was developed to investigate hydraulic fracture propagation behavior in a naturally fractured reservoir. Compared with the traditional finite element method, the coupled model with global insertion cohesive elements realizes arbitrary propagation of fluid-driven fractures. Numerical simulations of multiple-cluster hydraulic fracturing were carried out to investigate the sensitivities of a multitude of parameters. The results reveal that stress interference from multiple-clusters is responsible for serious suppression and diversion of the fracture network. A lower stress difference benefits the fracture network and helps open natural fractures. By comparing the mechanism of fluid injection, the maximal fracture network can be achieved with various injection rates and viscosities at different fracturing stages. Cluster parameters, including the number of clusters and their spacing, were optimal, satisfying the requirement of creating a large fracture network. These results offer new insights into the propagation pattern of fluid driven fractures and should act as a guide for multiple-cluster hydraulic fracturing, which can help increase the hydraulic fracture volume in naturally fractured reservoirs. Full article
(This article belongs to the Special Issue Fluid Flow in Fractured Porous Media)
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Open AccessArticle Robust Scheduling Optimization Model for Multi-Energy Interdependent System Based on Energy Storage Technology and Ground-Source Heat Pump
Processes 2019, 7(1), 27; https://doi.org/10.3390/pr7010027
Received: 6 November 2018 / Revised: 28 December 2018 / Accepted: 30 December 2018 / Published: 8 January 2019
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Abstract
The energy consumed by buildings makes up a significant part of total social energy consumption. The energy use rate of the traditional cooling and heating unit is low. A distributed cooling, heating, and power (CHP) system can achieve cascade use of energy and [...] Read more.
The energy consumed by buildings makes up a significant part of total social energy consumption. The energy use rate of the traditional cooling and heating unit is low. A distributed cooling, heating, and power (CHP) system can achieve cascade use of energy and reduce the long-distance transportation of energy. Along with the wide use of ground-source heat pumps and energy storage technology, the combined cooling, heating, and power (CCHP) system coupled with a ground-source heat pump and energy storage technology is increasingly being used. Firstly, we proposed the construction of a CCHP system driven by distributed energy resources (DERs) including three subsystems of an electricity subsystem, a CCHP subsystem and an auxiliary heating subsystem as the object of study in this paper. Besides, with the goals of reducing carbon emissions, increasing energy efficiency, and minimizing system cost, a constraint mechanism based on the DOM-PSO (dynamic object method/particle swarm optimization) algorithm was applied. Finally, taking Tianjin Eco-City as an example, we used the PSO algorithm to analyze the operating characteristics of the cold and power cogeneration system under the uncertainty of the wind power output. The simulation results show that the joint optimization mode operation strategy can balance the results of different optimization modes by increasing the robust coefficient of wind power. Of all scenarios examined, the CCHP system coupled with the ground-source heat pump and energy storage technology performed best. Full article
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Open AccessArticle Modeling/Simulation of the Dividing Wall Column by Using the Rigorous Model
Processes 2019, 7(1), 26; https://doi.org/10.3390/pr7010026
Received: 7 December 2018 / Revised: 18 December 2018 / Accepted: 29 December 2018 / Published: 8 January 2019
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Abstract
Dividing wall column (DWC) is an atypical distillation column with an internal, vertical WE partition wall that effectively accommodates two conventional distillation columns into one to improve the thermodynamic efficiency. In previous studies, different equivalent models by combining conventional columns are adopted to [...] Read more.
Dividing wall column (DWC) is an atypical distillation column with an internal, vertical WE partition wall that effectively accommodates two conventional distillation columns into one to improve the thermodynamic efficiency. In previous studies, different equivalent models by combining conventional columns are adopted to approximate the DWC modeling, which may not well describe the integration of the DWC; moreover, the computational cost increases when multiple columns are implemented to represent one DWC. In this paper, a rigorous mathematical model is proposed based on the mass balance, the energy and phase equilibrium of the DWC, where decision variables and state variables are equally treated. The model was developed in the general process modeling system (gPROMS). Based on the rigorous model, the influences of liquid split ratio and vapor split ratio are discussed, and it is shown that the heat duty is sensitive to changes on the liquid and vapor split ratio. Inappropriate liquid and vapor split ratio will increase the mixing effects at both ends of the dividing wall, and adversely affect the thermodynamic efficiency. Hence, the degree of mixing is defined to characterize the column efficiency. Furthermore, the middle component split ratio at the top of the pre-fractionator has an optimal point for better energy saving with certain liquid and vapor split ratios, and can be used as an indicator for the energy performance. Finally, the model was tested and validated against literature data by using the ternary benzene–toluene–xylene mixture system as a case study. Full article
(This article belongs to the Special Issue Modeling, Simulation and Control of Chemical Processes)
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Open AccessArticle Integration Multi-Model to Evaluate the Impact of Surface Water Quality on City Sustainability: A Case from Maanshan City in China
Processes 2019, 7(1), 25; https://doi.org/10.3390/pr7010025
Received: 23 November 2018 / Revised: 27 December 2018 / Accepted: 2 January 2019 / Published: 8 January 2019
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Abstract
Water pollution is a worldwide problem that needs to be solved urgently and has a significant impact on the efficiency of sustainable cities. The evaluation of water pollution is a Multiple Criteria Decision-Making (MCDM) problem and using a MCDM model can help control [...] Read more.
Water pollution is a worldwide problem that needs to be solved urgently and has a significant impact on the efficiency of sustainable cities. The evaluation of water pollution is a Multiple Criteria Decision-Making (MCDM) problem and using a MCDM model can help control water pollution and protect human health. However, different evaluation methods may obtain different results. How to effectively coordinate them to obtain a consensus result is the main aim of this work. The purpose of this article is to develop an ensemble learning evaluation method based on the concept of water quality to help policy-makers better evaluate surface water quality. A valid application is conducted to illustrate the use of the model for the surface water quality evaluation problem, thus demonstrating the effectiveness and feasibility of the proposed model. Full article
(This article belongs to the Special Issue Design and Control of Sustainable Systems)
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