Next Issue
Volume 7, December
Previous Issue
Volume 7, October

Table of Contents

Processes, Volume 7, Issue 11 (November 2019)

  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Readerexternal link to open them.
Cover Story (view full-size image) Environmental care is a must for society and governments, and aspects such as sustainability and [...] Read more.
Order results
Result details
Select all
Export citation of selected articles as:
Open AccessArticle
Design, Simulation, and Experiment of an LTCC-Based Xenon Micro Flow Control Device for an Electric Propulsion System
Processes 2019, 7(11), 862; https://doi.org/10.3390/pr7110862 - 19 Nov 2019
Abstract
A xenon micro flow control device (XMFCD) is the key component of a xenon feeding system, which controls the required micro flow xenon (µg/s–mg/s) to electric thrusters. Traditional XMFCDs usually have large volume and weight in order to achieve ultra-high fluid resistance and [...] Read more.
A xenon micro flow control device (XMFCD) is the key component of a xenon feeding system, which controls the required micro flow xenon (µg/s–mg/s) to electric thrusters. Traditional XMFCDs usually have large volume and weight in order to achieve ultra-high fluid resistance and have a long producing cycle and high processing cost. This paper proposes a miniaturized, easy-processing, and inexpensive XMFCD, which is fabricated by low-temperature co-fired ceramic (LTCC) technology. The design of the proposed XMFCD based on complex three-dimensional (3D) microfluidic channels is described, and its fabrication process based on LTCC is illustrated. The microfluidic channels of the fabricated single (9 mm diameter and 1.4 mm thickness) and dual (9 mm diameter and 2.4 mm thickness) XMFCDs were both checked by X-ray, which proved the LTCC method’s feasibility. A mathematical model of flow characteristics is established with the help of finite element analysis, and the model is validated by the experimental results of the single and dual XMFCDs. Based on the mathematical model, the influence of the structure parameters (diameter of orifice and width of the groove) on flow characteristics is investigated, which can guide the optimized design of the proposed XMFCD. Full article
(This article belongs to the Special Issue Smart Flow Control Processes in Micro Scale)
Show Figures

Figure 1

Open AccessArticle
Assessment of the Toxicity of Natural Oils from Mentha piperita, Pinus roxburghii, and Rosa spp. Against Three Stored Product Insects
Processes 2019, 7(11), 861; https://doi.org/10.3390/pr7110861 - 18 Nov 2019
Abstract
Three natural oils extracted from Mentha piperita, Pinus roxburghii, and Rosa spp. were assessed in order to determine their insecticidal activity against the adults of three stored product insects: the rice weevil (Sitophilus oryzae L.), the lesser grain borer ( [...] Read more.
Three natural oils extracted from Mentha piperita, Pinus roxburghii, and Rosa spp. were assessed in order to determine their insecticidal activity against the adults of three stored product insects: the rice weevil (Sitophilus oryzae L.), the lesser grain borer (Rhyzopertha dominica, Fabricius), and the red flour beetle (Tribolium castaneum, Herbst.). By Gas chromatography–mass spectrometry (GC/MS) analysis, the main compounds in the n-hexane oil from Rosa spp. were determined to be methyl eugenol (52.17%), phenylethyl alcohol (29.92%), diphenyl ether (7.75%), and geraniol (5.72%); in the essential oil from M. piperita, they were menthone (20.18%), 1,8-cineole (15.48%), menthyl acetate (13.13%), caryophyllene (4.82%), β-pinene (4.37%), and D-limonene (2.81%); and from the foliage of P. roxburghii, they were longifolene (19.52%), caryophyllene (9.45%), Δ-3-carene (7.01%), α-terpineol (6.75%), and γ-elemene (3.88%). S. oryzae and R. dominica were reared using sterilized wheat grains, and T. castaneum was reared on wheat flour mixed with yeast (10:1, w/w), all under laboratory conditions (27 ± 1 °C and 65% ± 5% Relative humidity (R.H). Two toxicity bioassays were used, as well as contact using thin film residues and fumigation bioassays. The results indicated that M. piperita caused a high toxicity for S. oryzae compared to other insects. High significant variations were observed between the tested M. piperita doses against the stored insects, and this natural material could be used to control insects that infect the grains. Also, the data indicated that the Rosa spp. oil had a low-toxicity effect against these insects compared to other oils. We recommend using natural oils against the stored weevils and petals, rather than the chemical agent, so as to serve human health. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
Open AccessArticle
Green Synthesized Silver Nanoparticles of Myrtus communis L (AgMC) Extract Inhibits Cancer Hallmarks via Targeting Aldose Reductase (AR) and Associated Signaling Network
Processes 2019, 7(11), 860; https://doi.org/10.3390/pr7110860 - 18 Nov 2019
Abstract
In this current study, we demonstrated the green synthesis and characterization of silver nanoparticles using Myrtus communis L. plant extract (Ag-MC) and its evaluation of anticancer and antimicrobial activities. The green synthesis of (Ag-MC), was assessed by numerous characterization techniques such as ultraviolet-visible [...] Read more.
In this current study, we demonstrated the green synthesis and characterization of silver nanoparticles using Myrtus communis L. plant extract (Ag-MC) and its evaluation of anticancer and antimicrobial activities. The green synthesis of (Ag-MC), was assessed by numerous characterization techniques such as ultraviolet-visible spectroscopy (UV-VIS), Fourier-transform infrared spectroscopy (FT-IR), X-ray powder diffraction (XRD) transmission electron microscopy (TEM) and energy dispersive x-ray spectroscopy (EDX). The anti-cancer activity of the green synthesized silver nanoparticles was evaluated by the median inhibitory dose (IC50) on human liver carcinoma cell lines (HepG2). These results suggested that SN-NPs can be used as effective anticancer cell lines, as well as antibacterial and antiseptic agents in the medical field. This study showed that overexpression of aldose reductase (AR) in the human liver carcinoma cell line, HepG2, was down regulated by administration of SN-MC. The down regulation of AR was associated with abrogation of Pl3k/Akt, ERK and NF-kB pathways and the inhibition of cancer hallmarks, however, the target molecule for Ag-MC was not practically established. Thus it is still unknown if the consequences were due to AR inhibition or direct Ag-MC interaction with AR. Full article
(This article belongs to the Special Issue Production and Biomedical Applications of Bioactive Compounds)
Show Figures

Figure 1

Open AccessArticle
Interaction of Wu’s Slip Features in Bioconvection of Eyring Powell Nanoparticles with Activation Energy
Processes 2019, 7(11), 859; https://doi.org/10.3390/pr7110859 - 18 Nov 2019
Abstract
The current continuation aim is to explore the rheological consequences of Eyring Powell nanofluid over a moving surface in the presence of activation energy and thermal radiation. The bioconvection of magnetized nanoparticles is executed with the evaluation of motile microorganism. The most interesting [...] Read more.
The current continuation aim is to explore the rheological consequences of Eyring Powell nanofluid over a moving surface in the presence of activation energy and thermal radiation. The bioconvection of magnetized nanoparticles is executed with the evaluation of motile microorganism. The most interesting Wu’s slip effects are also assumed near the surface. The evaluation of nanoparticles for current flow problems has been examined by using Buongiorno’s model. The governing equations for the assumed flow problem are constituted under the boundary layer assumptions. After converting these equations in dimensionless form, the famous shooting technique is executed. A detailed physical significance is searched out in the presence of slip features. The variation of physical quantities, namely velocity, nanoparticles temperature, nano particles concentration, motile microorganism density, skin friction coefficient, local Nusselt number and motile organism density number are observed with detailed physical aspects for various flow controlling parameters. Full article
(This article belongs to the Special Issue Fluid Flow and Heat Transfer of Nanofluids)
Show Figures

Figure 1

Open AccessArticle
Insights into the Fouling Propensities of Natural Derived Alginate Blocks during the Microfiltration Process
Processes 2019, 7(11), 858; https://doi.org/10.3390/pr7110858 - 17 Nov 2019
Abstract
Membrane technology has been one of the most promising techniques to solve the water problem in future. Unfortunately, it suffers from the fouling problem which is ubiquitous in membrane systems. The origin of the bewilderments of the fouling problem lies in the lack [...] Read more.
Membrane technology has been one of the most promising techniques to solve the water problem in future. Unfortunately, it suffers from the fouling problem which is ubiquitous in membrane systems. The origin of the bewilderments of the fouling problem lies in the lack of deep understanding. Recent studies have pointed out that the molecular structure of foulant affects its fouling propensity which has been ignored in the past. In this study, the filtration behaviors of alginate blocks derived from the same source were comprehensively explored. Alginate blocks share the same chemical composition but differ from each other in molecular structure. The alginate was first extracted from natural seaweed using calcium precipitation and ion-exchange methods. Extracted alginate was further fractionized into MG-, MM- and GG-blocks and the characteristics of the three blocks were examined by Fourier transform infrared spectroscopy (FTIR) and field emission scanning electron microscopy (FESEM) observations, and transparent exopolymer particles’ (TEPs) measurements. Results showed that MG-, MM- and GG-blocks had the same functional groups, but they showed different intermolecular interactions. TEP formation from MG-, MM- and GG-blocks revealed that the molecule crosslinking of them decreased in the order of MM-blocks > GG-blocks > MG-blocks. It was further found from microfiltration tests that these alginate blocks had completely different fouling propensities which can be explained by the TEP formation. TEPs would accumulate on membrane surfaces and worked as a pre-filter to avoid serious pore blocking of membrane. That all suggested that the membrane fouling was closely related to the molecular structure of foulant. It is expected that this study can provide useful insights into the fouling propensities of different types of polysaccharides during filtration processes. Full article
(This article belongs to the Special Issue Gas, Water and Solid Waste Treatment Technology)
Show Figures

Graphical abstract

Open AccessArticle
Non-Structural Damage Verification of the High Pressure Pump Assembly Ball Valve in the Gasoline Direct Injection Vehicle System
Processes 2019, 7(11), 857; https://doi.org/10.3390/pr7110857 - 16 Nov 2019
Abstract
The injection pressure of the gasoline direct injection vehicle is currently developing from the low pressure to the high pressure, and the increase of the injection pressure has brought various damage problems to the high pressure pump structure. These problems should be solved [...] Read more.
The injection pressure of the gasoline direct injection vehicle is currently developing from the low pressure to the high pressure, and the increase of the injection pressure has brought various damage problems to the high pressure pump structure. These problems should be solved urgently. In this paper, the damage problem of the high pressure pump unloading valve ball in a gasoline direct injection vehicle under high pressure conditions is studied. The theoretical calculation of the force of the pressure relief valve is carried out. Firstly, the equivalent friction coefficient is obtained by decoupling analysis of the statically indeterminate model. Based on this, a finite element model is established. The equivalent stress is obtained by numerical simulation. The equivalent stress is compared with the yield strength of the valve ball material to determine that the valve ball damage is a non-static damage. At the same time, the s-N curve of the probability of destruction of one-millionth of the material of the valve ball is given. Then, the fatigue numerical simulation is performed. A safety factor of 3.66 is obtained. In summary, the high pressure relief valve ball in the direct injection high pressure pump should not be a traditional structural damage under high pressure conditions. In the theoretical calculation, the tangential displacement and radial displacement of the ball are all on the micrometer level. It can be presumed that the surface damage of the valve ball is microscopic damage, such as fretting wear. Full article
(This article belongs to the Special Issue Smart Flow Control Processes in Micro Scale)
Show Figures

Figure 1

Open AccessFeature PaperArticle
Performance Improvement of a Grid-Tied Neutral-Point-Clamped 3-φ Transformerless Inverter Using Model Predictive Control
Processes 2019, 7(11), 856; https://doi.org/10.3390/pr7110856 - 15 Nov 2019
Abstract
Grid-connected photovoltaic (PV) systems are now a common part of the modern power network. A recent development in the topology of these systems is the use of transformerless inverters. Although they are compact, cheap, and efficient, transformerless inverters suffer from chronic leakage current. [...] Read more.
Grid-connected photovoltaic (PV) systems are now a common part of the modern power network. A recent development in the topology of these systems is the use of transformerless inverters. Although they are compact, cheap, and efficient, transformerless inverters suffer from chronic leakage current. Various researches have been directed toward evolving their performance and diminishing leakage current. This paper introduces the application of a model predictive control (MPC) algorithm to govern and improve the performance of a grid-tied neutral-point-clamped (NPC) 3-φ transformerless inverter powered by a PV panel. The transformerless inverter was linked to the grid via an inductor/capacitor (LC) filter. The filter elements, as well as the internal impedance of the grid, were considered in the system model. The discrete model of the proposed system was determined, and the algorithm of the MPC controller was established. Matlab’s simulations for the proposed system, controlled by the MPC and the ordinary proportional–integral (PI) current controller with sinusoidal pulse width modulation (SPWM), were carried out. The simulation results showed that the MPC controller had the best performance for earth leakage current, total harmonic distortion (THD), and the grid current spectrum. Also, the efficiency of the system using the MPC was improved compared to that using a PI current controller with SPW modulation. Full article
(This article belongs to the Special Issue Optimization for Control, Observation and Safety)
Show Figures

Figure 1

Open AccessFeature PaperArticle
Characterization and Modelling Studies of Activated Carbon Produced from Rubber-Seed Shell Using KOH for CO2 Adsorption
Processes 2019, 7(11), 855; https://doi.org/10.3390/pr7110855 - 14 Nov 2019
Abstract
Global warming due to the emission of carbon dioxide (CO2) has become a serious problem in recent times. Although diverse methods have been offered, adsorption using activated carbon (AC) from agriculture waste is regarded to be the most applicable one due [...] Read more.
Global warming due to the emission of carbon dioxide (CO2) has become a serious problem in recent times. Although diverse methods have been offered, adsorption using activated carbon (AC) from agriculture waste is regarded to be the most applicable one due to numerous advantages. In this paper, the preparation of AC from rubber-seed shell (RSS), an agriculture residue through chemical activation using potassium hydroxide (KOH), was investigated. The prepared AC was characterized by nitrogen adsorption–desorption isotherms measured in Micrometrices ASAP 2020 and FESEM. The optimal activation conditions were found at an impregnation ratio of 1:2 and carbonized at a temperature of 700 °C for 120 min. Sample A6 is found to yield the largest surface area of 1129.68 m2/g with a mesoporous pore diameter of 3.46 nm, respectively. Using the static volumetric technique evaluated at 25 °C and 1.25 bar, the maximum CO2 adsorption capacity is 43.509 cm3/g. The experimental data were analyzed using several isotherm and kinetic models. Owing to the closeness of regression coefficient (R2) to unity, the Freundlich isotherm and pseudo-second kinetic model provide the best fit to the experimental data suggesting that the RSS AC prepared is an attractive source for CO2 adsorption applications. Full article
(This article belongs to the Special Issue Green Technologies: Bridging Conventional Practices and Industry 4.0)
Show Figures

Figure 1

Open AccessArticle
Optimization of Baicalin, Wogonoside, and Chlorogenic Acid Water Extraction Process from the Roots of Scutellariae Radix and Lonicerae japonicae Flos Using Response Surface Methodology (RSM)
Processes 2019, 7(11), 854; https://doi.org/10.3390/pr7110854 - 14 Nov 2019
Abstract
In this study, a simultaneous water extraction process for baicalin, wogonoside, and chlorogenic acid has been optimized. The effect of extraction temperature, extraction time, and liquid–solid ratio was scrutinized by single factor experiments and further analyzed by Box–Behnken design (BBD) approach using response [...] Read more.
In this study, a simultaneous water extraction process for baicalin, wogonoside, and chlorogenic acid has been optimized. The effect of extraction temperature, extraction time, and liquid–solid ratio was scrutinized by single factor experiments and further analyzed by Box–Behnken design (BBD) approach using response surface methodology (RSM). The extraction yield of investigated compounds was determined by high performance liquid chromatography (HPLC). Single-factor experiments and response surface analysis results revealed that the optimized conditions are: Liquid to solid ratio 25:1 (mL/g), extraction temperature 93 °C, extraction time 2.4 h, and the extraction cycle two. Importantly, it has been noted that under the above conditions, concentrations of baicalin, wogonoside, and chlorogenic were 0.078, 0.031, and 0.013 mg/mL, respectively, and the overall desirability (OD) value was 0.76 which was higher than the non-optimized conditions and the deviation from the predicted OD value was only 2.44%. Conclusively, it has been suggested that the model was stable and feasible, and fit for extraction of baicalin, wogonoside, and chlorogenic acid from Scutellariae Radix and Lonicerae (L.) japonicae Flos. Full article
(This article belongs to the Special Issue Advances in Green Chemistry Analytical Techniques)
Show Figures

Figure 1

Open AccessArticle
Valorization of Industrial Vegetable Waste Using Dilute HCl Pretreatment
Processes 2019, 7(11), 853; https://doi.org/10.3390/pr7110853 - 14 Nov 2019
Abstract
A solid vegetable waste stream was subjected to dilute acid (HCl) pretreatment with the goal of converting the waste into a form that is amenable to biochemical processes which could include microbial lipids, biohydrogen, and volatile organic acids production. Specifically, this study was [...] Read more.
A solid vegetable waste stream was subjected to dilute acid (HCl) pretreatment with the goal of converting the waste into a form that is amenable to biochemical processes which could include microbial lipids, biohydrogen, and volatile organic acids production. Specifically, this study was conducted to identify the most suitable pretreatment condition that maximizes the yield or concentration of sugars while minimizing the production of compounds which are inhibitory to microbes (i.e., furfural, hydroxymethylfurfural, and organic acids). Temperatures from 50–150 °C and HCl loading from 0–7 wt % were studied to using an orthogonal central composite response surface design with eight center points. The effects of the variables under study on the resulting concentrations of sugars, organic acids, and furans were determined using the quadratic response surface model. Results indicated that the biomass used in this study contains about 5.7 wt % cellulose and 83.8 wt % hemicellulose/pectin. Within the experimental design, the most suitable pretreatment condition was identified to be at 50 °C and 3.5 wt % HCl. A kinetic study at this condition indicated process completion at 30 mins. that produced a hydrolyzate that contains 31.30 ± 0.44 g/L sugars and 7.40 ± 0.62 g/L organic acids. At this condition, a yield of ~0.47 g sugar/g of dry solid vegetable waste was obtained. The absence of furans suggests the suitability of the resulting hydrolyzate as feedstock for biochemical processes. The results suggested that the sugar concentration of the pretreated biomass is highly affected by the presence of other compounds such as amines, amino acids, and proteins. The effect however, is minimal at low levels of HCl where the highest total sugar production was observed. Full article
Show Figures

Figure 1

Open AccessFeature PaperArticle
Development of an Electric Arc Furnace Simulator Based on a Comprehensive Dynamic Process Model
Processes 2019, 7(11), 852; https://doi.org/10.3390/pr7110852 - 14 Nov 2019
Abstract
A simulator and an algorithm for the automatic creation of operation charts based on process conditions were developed on the basis of an existing comprehensive electric arc furnace process model. The simulator allows direct user input and real-time display of results during the [...] Read more.
A simulator and an algorithm for the automatic creation of operation charts based on process conditions were developed on the basis of an existing comprehensive electric arc furnace process model. The simulator allows direct user input and real-time display of results during the simulation, making it usable for training and teaching of electric arc furnace operators. The automatic control feature offers a quick and automated evaluation of a large number of scenarios or changes in process conditions, raw materials, or equipment used. The operation chart is adjusted automatically to give comparable conditions at tapping and allows the assessment of the necessary changes in the operating strategy as well as their effect on productivity, energy, and resource consumption, along with process emissions. Full article
(This article belongs to the Special Issue Process Modeling in Pyrometallurgical Engineering)
Show Figures

Figure 1

Open AccessArticle
Thermo-Diffusion and Multi-Slip Effect on an Axisymmetric Casson Flow over a Unsteady Radially Stretching Sheet in the Presence of Chemical Reaction
Processes 2019, 7(11), 851; https://doi.org/10.3390/pr7110851 - 14 Nov 2019
Abstract
The objective of this article is to investigate the impacts of thermo-diffusion effect on unsteady axisymmetric Casson flow over a time-dependent radially stretching sheet with a multi-slip parameter and the force of chemical reaction. We employed an established similarity transformation to this non-linear [...] Read more.
The objective of this article is to investigate the impacts of thermo-diffusion effect on unsteady axisymmetric Casson flow over a time-dependent radially stretching sheet with a multi-slip parameter and the force of chemical reaction. We employed an established similarity transformation to this non-linear partial differential system to convert it into a system of ordinary differential equations. The numerical results are attained for this system by using KELLER-BOX implicit finite difference scheme. It has great reliability and accuracy even a very short time period for computational simulation. The impacts of influential flow parameters on fluid flow are sketched through graphs and the numerical results are thoroughly argued. The temperature, velocity and wall concentration control parameters are analyzed. (i) It is witnessed that chemical reaction is not favorable to enhance the velocity profile. (ii) Multi-slip parameters vary inversely with velocity profile. (iii) The fluid concentration in its boundary layer decreases with the increase of heavier species, the parameter of the reaction rate and the exponent of power law for fluids having Prandtl number = 10.0, 15.0, 20.0 and 25.0. Moreover, the skin-friction-coefficient factor and Nusselt-number are compared with the published work. A strong numerical solution agreement is being observed. Full article
(This article belongs to the Special Issue Optimization of Heat and Mass Exchange)
Show Figures

Figure 1

Open AccessArticle
Structural Influence and Interactive Binding Behavior of Dopamine and Norepinephrine on the Greek-Key-Like Core of α-Synuclein Protofibril Revealed by Molecular Dynamics Simulations
Processes 2019, 7(11), 850; https://doi.org/10.3390/pr7110850 - 13 Nov 2019
Abstract
The pathogenesis of Parkinson’s disease (PD) is closely associated with the aggregation of α-synuclein (αS) protein. Finding the effective inhibitors of αS aggregation has been considered as the primary therapeutic strategy for PD. Recent studies reported that two neurotransmitters, dopamine (DA) and norepinephrine [...] Read more.
The pathogenesis of Parkinson’s disease (PD) is closely associated with the aggregation of α-synuclein (αS) protein. Finding the effective inhibitors of αS aggregation has been considered as the primary therapeutic strategy for PD. Recent studies reported that two neurotransmitters, dopamine (DA) and norepinephrine (NE), can effectively inhibit αS aggregation and disrupt the preformed αS fibrils. However, the atomistic details of αS-DA/NE interaction remain unclear. Here, using molecular dynamics simulations, we investigated the binding behavior of DA/NE molecules and their structural influence on αS44–96 (Greek-key-like core of full length αS) protofibrillar tetramer. Our results showed that DA/NE molecules destabilize αS protofibrillar tetramer by disrupting the β-sheet structure and destroying the intra- and inter-peptide E46–K80 salt bridges, and they can also destroy the inter-chain backbone hydrogen bonds. Three binding sites were identified for both DA and NE molecules interacting with αS tetramer: T54–T72, Q79–A85, and F94–K96, and NE molecules had a stronger binding capacity to these sites than DA. The binding of DA/NE molecules to αS tetramer is dominantly driven by electrostatic and hydrogen bonding interactions. Through aromatic π-stacking, DA and NE molecules can bind to αS protofibril interactively. Our work reveals the detailed disruptive mechanism of protofibrillar αS oligomer by DA/NE molecules, which is helpful for the development of drug candidates against PD. Given that exercise as a stressor can stimulate DA/NE secretion and elevated levels of DA/NE could delay the progress of PD, this work also enhances our understanding of the biological mechanism by which exercise prevents and alleviates PD. Full article
(This article belongs to the Special Issue Molecular Dynamics Modeling and Simulation)
Show Figures

Figure 1

Open AccessArticle
Dynamic Semi-Quantitative Risk Research in Chemical Plants
Processes 2019, 7(11), 849; https://doi.org/10.3390/pr7110849 - 12 Nov 2019
Abstract
When a major accident occurs in a chemical industry park, it directly affects the personal safety of operators and neighboring residents and causes major losses; therefore, we should take measures to strengthen the management of chemical industry parks. This article proposes and analyzes [...] Read more.
When a major accident occurs in a chemical industry park, it directly affects the personal safety of operators and neighboring residents and causes major losses; therefore, we should take measures to strengthen the management of chemical industry parks. This article proposes and analyzes a new dynamic semi-quantitative risk calculation model for chemical plants that can be applied digitally. This model provides a sustainable, standardized, and comprehensive management strategy for the safety management of chemical plants and chemical industry park managers. The model and its determined parameters were applied to the safety management of chemical companies within the chemical industry park of Quzhou, Zhejiang Province. From the point of view of the existing semi-quantitative model, the existing problems of the current model are analyzed, the current model is optimized, and a new dynamic semi-quantitative calculation model scheme is proposed. The new model uses an analytical hierarchy process targeting the factors affecting the risks in chemical plants, and chemical plant semi-quantitative dynamic calculation system consisting of the operator, process/equipment, risk, building environment, safety management, and domino effect, and the comprehensive risk of the chemical plant was calculated. The model is ultimately a real-time quantitative value, but its calculation process can compare and analyze the causes of high risk in a chemical plant as they relate to these six factors. Its implementation requires only software, which will greatly help chemical plant safety management. Full article
(This article belongs to the Special Issue Industry 4.0 and Sustainable Supply Chain Management)
Show Figures

Figure 1

Open AccessArticle
Evaluation of Municipal Solid Wastes Based Energy Potential in Urban Pakistan
Processes 2019, 7(11), 848; https://doi.org/10.3390/pr7110848 - 12 Nov 2019
Abstract
Solid waste management needs re-evaluating in developing countries like Pakistan, which currently employs landfilling as a first option. Over time, increasing population will result in decreasing space for landfill sites, ultimately increasing the cost of landfilling, while increasing accumulated waste will cause pollution. [...] Read more.
Solid waste management needs re-evaluating in developing countries like Pakistan, which currently employs landfilling as a first option. Over time, increasing population will result in decreasing space for landfill sites, ultimately increasing the cost of landfilling, while increasing accumulated waste will cause pollution. Locating and preparing a sanitary landfill includes the securing of large sectors and also everyday activity with the end goal to limit potential negative impacts. Energy production from municipal solid waste (MSW) is a perceptive idea for large cities, such as Karachi, as waste, which is an undesirable output that adds to land and air pollution, is transformed into a vital source of energy. The current study strives to provide a destination to solid waste by evaluating the energy potential that waste provides for power generation by the process of incineration. A sustainable energy generation plant based on the Rankine cycle is proposed. This study evaluates the various landfill sites in the case study area to determine their sustainability for a waste to energy (WtE) plant. The implementation of the proposed plant will not only provide an ultimate destination to waste but also generate 121.9 MW electricity at 25% plant efficiency. Thus, the generated electricity can be used to run a WtE plant and meet the energy requirements of the residents. Full article
(This article belongs to the Special Issue Biomass Processing and Conversion Systems)
Show Figures

Figure 1

Open AccessFeature PaperArticle
Techno-Economic Implications of Fed-Batch Enzymatic Hydrolysis
Processes 2019, 7(11), 847; https://doi.org/10.3390/pr7110847 - 12 Nov 2019
Abstract
Fed-batch enzymatic hydrolysis has the potential to improve the overall process of converting cellulosic biomass into ethanol. This paper utilizes a process simulation approach to identify and quantify techno-economic differences between batch and fed-batch enzymatic hydrolysis in cellulosic ethanol production. The entire process [...] Read more.
Fed-batch enzymatic hydrolysis has the potential to improve the overall process of converting cellulosic biomass into ethanol. This paper utilizes a process simulation approach to identify and quantify techno-economic differences between batch and fed-batch enzymatic hydrolysis in cellulosic ethanol production. The entire process of converting corn stover into ethanol was simulated using SuperPro Designer simulation software. The analysis was conducted for a plant capacity of 2000 metric tons of dry biomass per day. A literature review was used to identify baseline parameters for the process. The sensitivity of the ethanol production cost to changes in sugar conversion efficiency, plant capacity, biomass cost, power cost, labor cost, and enzyme cost was evaluated using the process simulation. For the base scenario, the ethanol unit production cost was approximately $0.10/gallon lower for fed-batch hydrolysis. The greatest differences were seen in facilities costs, labor costs, and capital costs. Using a fed-batch operation decreased facilities costs by 41%, labor costs by 21%, and capital costs by 15%. The sensitivity analysis found that cost of biomass had the greatest effect on ethanol production cost, and in general, the results support the proposition that fed-batch enzymatic hydrolysis does improve the techno-economics of cellulosic ethanol production. Full article
Show Figures

Figure 1

Open AccessArticle
Theoretical Analysis of Forced Segmented Temperature Gradients in Liquid Chromatography
Processes 2019, 7(11), 846; https://doi.org/10.3390/pr7110846 - 12 Nov 2019
Abstract
An equilibrium model is applied to study the effect of forced temperature gradients introduced through heat exchange via specific segments of the wall of a chromatographic column operating with a liquid mobile phase. For illustration of the principle, the column is divided into [...] Read more.
An equilibrium model is applied to study the effect of forced temperature gradients introduced through heat exchange via specific segments of the wall of a chromatographic column operating with a liquid mobile phase. For illustration of the principle, the column is divided into two segments in such a manner that the first segment is kept at a fixed reference temperature, while the temperature of the second segment can be changed stepwise through fixed heating or cooling over the column wall to modulate the migration speeds of the solute concentration profiles. The method of characteristics is used to obtain the solution trajectories analytically. It is demonstrated that appropriate heating or cooling in the second segment can accelerate or decelerate the specific concentration profiles in order to improve certain performance criteria. The results obtained verify that the proposed analysis is well suited to evaluate the application of forced segmented temperature gradients. The suggested gradient procedure provides the potential to reduce the cycle time and, thus, improving the production rate of the chromatographic separation process compared to conventional isothermal (isocratic) operation. Full article
(This article belongs to the Special Issue Advanced Methods in Process and Systems Engineering)
Show Figures

Figure 1

Open AccessArticle
Novel Parallel Heterogeneous Meta-Heuristic and Its Communication Strategies for the Prediction of Wind Power
Processes 2019, 7(11), 845; https://doi.org/10.3390/pr7110845 - 11 Nov 2019
Abstract
Wind and other renewable energy protects the ecological environment and improves economic efficiency. However, it is difficult to accurately predict wind power because of the randomness and volatility of wind. This paper proposes a new parallel heterogeneous model to predict the wind power. [...] Read more.
Wind and other renewable energy protects the ecological environment and improves economic efficiency. However, it is difficult to accurately predict wind power because of the randomness and volatility of wind. This paper proposes a new parallel heterogeneous model to predict the wind power. Parallel meta-heuristic saves computation time and improves solution quality. Four communication strategies, which include ranking, combination, dynamic change and hybrid, are introduced to balance exploration and exploitation. The dynamic change strategy is to dynamically increase or decrease the members of subgroup to keep the diversity of the population. The benchmark functions show that the algorithms have excellent performance in exploration and exploitation. In the end, they are applied to successfully realize the prediction for wind power by training the parameters of the neural network. Full article
(This article belongs to the Special Issue Optimization Algorithms Applied to Sustainable Production Processes)
Show Figures

Figure 1

Open AccessArticle
Effects of Processing Conditions on the Simultaneous Extraction and Distribution of Oil and Protein from Almond Flour
Processes 2019, 7(11), 844; https://doi.org/10.3390/pr7110844 - 11 Nov 2019
Abstract
The enzyme-assisted aqueous extraction process (EAEP) is an environmentally friendly strategy that simultaneously extracts oil and protein from several food matrices. The aim of this study was to investigate the effects of pH (6.5–9.5), temperature (45–55 °C), solids-to-liquid ratio (SLR) (1:12–1:8), and amount [...] Read more.
The enzyme-assisted aqueous extraction process (EAEP) is an environmentally friendly strategy that simultaneously extracts oil and protein from several food matrices. The aim of this study was to investigate the effects of pH (6.5–9.5), temperature (45–55 °C), solids-to-liquid ratio (SLR) (1:12–1:8), and amount of enzyme (0.5–1.0%) on the extraction and separation of oil and protein from almond flour using a fractional factorial design. Oil and protein extraction yields from 61 to 75% and 64 to 79% were achieved, respectively. Experimental conditions resulting in higher extractability were subsequently replicated for validation of the observed effects. Oil and protein extraction yields of 75 and 72% were achieved under optimized extraction conditions (pH 9.0, 50 °C, 1:10 SLR, 0.5% (w/w) of enzyme, 60 min). Although the use of enzyme during the extraction did not lead to significant increase in extraction yields, it did impact the extracted protein functionality. The use of enzyme and alkaline pH (9.0) during the extraction resulted in the production of more soluble peptides at low pH (5.0), highlighting possible uses of the EAEP skim protein in food applications involving acidic pH. The implications of the use of enzyme during the extraction regarding the de-emulsification of the EAEP cream warrant further investigation. Full article
(This article belongs to the Special Issue Green Separation and Extraction Processes)
Show Figures

Graphical abstract

Open AccessArticle
Wind Power Short-Term Forecasting Hybrid Model Based on CEEMD-SE Method
Processes 2019, 7(11), 843; https://doi.org/10.3390/pr7110843 - 11 Nov 2019
Abstract
Accurately predicting wind power is crucial for the large-scale grid-connected of wind power and the increase of wind power absorption proportion. To improve the forecasting accuracy of wind power, a hybrid forecasting model using data preprocessing strategy and improved extreme learning machine with [...] Read more.
Accurately predicting wind power is crucial for the large-scale grid-connected of wind power and the increase of wind power absorption proportion. To improve the forecasting accuracy of wind power, a hybrid forecasting model using data preprocessing strategy and improved extreme learning machine with kernel (KELM) is proposed, which mainly includes the following stages. Firstly, the Pearson correlation coefficient is calculated to determine the correlation degree between multiple factors of wind power to reduce data redundancy. Then, the complementary ensemble empirical mode decomposition (CEEMD) method is adopted to decompose the wind power time series to decrease the non-stationarity, the sample entropy (SE) theory is used to classify and reconstruct the subsequences to reduce the complexity of computation. Finally, the KELM optimized by harmony search (HS) algorithm is utilized to forecast each subsequence, and after integration processing, the forecasting results are obtained. The CEEMD-SE-HS-KELM forecasting model constructed in this paper is used in the short-term wind power forecasting of a Chinese wind farm, and the RMSE and MAE are as 2.16 and 0.39 respectively, which is better than EMD-SE-HS-KELM, HS-KELM, KELM and extreme learning machine (ELM) model. According to the experimental results, the hybrid method has higher forecasting accuracy for short-term wind power forecasting. Full article
(This article belongs to the Special Issue Energy, Economic and Environment for Industrial Production Processes)
Show Figures

Figure 1

Open AccessFeature PaperArticle
New Aspects on the Modeling of Dithiolactone-Mediated Radical Polymerization of Vinyl Monomers
Processes 2019, 7(11), 842; https://doi.org/10.3390/pr7110842 - 10 Nov 2019
Abstract
A kinetic model for the dithiolactone-mediated radical polymerization of vinyl monomers based on the persistent radical effect and reversible addition (negligible fragmentation) was used to calculate the polymerization rate and describe molar mass development in the polymerization of methyl methacrylate at 60 °C, [...] Read more.
A kinetic model for the dithiolactone-mediated radical polymerization of vinyl monomers based on the persistent radical effect and reversible addition (negligible fragmentation) was used to calculate the polymerization rate and describe molar mass development in the polymerization of methyl methacrylate at 60 °C, using 2,2-azobisisobutyronitrile (AIBN) as an initiator, as well as dihydro-5-phenyl-2(3H)-thiophenethione (DTL1) and dihydro-2(3H)-thiophenethione (DTL2) as controllers. The model was implemented in the PREDICI commercial software. A good agreement between experimental data and model predictions was obtained. Full article
(This article belongs to the Special Issue Modeling and Simulation of Polymerization Processes)
Show Figures

Graphical abstract

Open AccessArticle
Inhibition of Key Enzymes Linked to Obesity and Cytotoxic Activities of Whole Plant Extracts of Vernonia mesplilfolia Less
Processes 2019, 7(11), 841; https://doi.org/10.3390/pr7110841 - 10 Nov 2019
Abstract
The whole plant of Vernonia mespilifolia is widely used as a traditional remedy for obesity in South Africa. The aim of this study was to investigate the anti-obesity and cytotoxic effects of Vernonia mespilifolia extracts in vitro. The α-amylase, α-glucosidase, and lipase [...] Read more.
The whole plant of Vernonia mespilifolia is widely used as a traditional remedy for obesity in South Africa. The aim of this study was to investigate the anti-obesity and cytotoxic effects of Vernonia mespilifolia extracts in vitro. The α-amylase, α-glucosidase, and lipase inhibitory activities of aqueous and ethanol extracts of Vernonia mespilifolia were investigated, while the cytotoxic effects of these extracts were analyzed using Hoechst 33342 and propidium iodide (PI) dual staining on a human cervical HeLa cell line. The results showed that the LC50 (the concentration of a material will kill 50% of test organisms) values of aqueous and ethanol extracts of Vernonia mespilifolia were >200 and 149 µg/mL, respectively, to HeLa cells. Additionally, the ethanol extract exhibited the strongest inhibitory effect on the pancreatic lipase (Half-maximal inhibitory concentration (IC50) = 331.16 µg/mL) and on α-amylase (IC50 = 781.72 µg/mL), while the aqueous extract has the strongest α-glucosidase (IC50 = 450.88 µg/mL). Our results suggest that Vernonia mespilifolia’s acclaimed anti-obesity effects could be ascribed to its ability to inhibit both carbohydrate and fat digesting enzymes. Full article
(This article belongs to the Section Biological Systems)
Show Figures

Figure 1

Open AccessArticle
Salp Swarm Optimization Algorithm-Based Controller for Dynamic Response and Power Quality Enhancement of an Islanded Microgrid
Processes 2019, 7(11), 840; https://doi.org/10.3390/pr7110840 - 10 Nov 2019
Abstract
The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not [...] Read more.
The islanded mode of the microgrid (MG) operation faces more power quality challenges as compared to grid-tied mode. Unlike the grid-tied MG operation, where the voltage magnitude and frequency of the power system are regulated by the utility grid, islanded mode does not share any connection with the utility grid. Hence, a proper control architecture of islanded MG is essential to control the voltage and frequency, including the power quality and optimal transient response during different operating conditions. Therefore, this study proposes an intelligent and robust controller for islanded MG, which can accomplish the above-mentioned tasks with the optimal transient response and power quality. The proposed controller utilizes the droop control in addition to the back to back proportional plus integral (PI) regulator-based voltage and current controllers in order to accomplish the mentioned control objectives efficiently. Furthermore, the intelligence of the one of the most modern soft computational optimization algorithms called salp swarm optimization algorithm (SSA) is utilized to select the best combination of the PI gains (kp and ki) and dc side capacitance (C), which in turn ensures optimal transient response during the distributed generator (DG) insertion and load change conditions. Finally, to evaluate the effectiveness of the proposed control approach, its outcomes are compared with that of the previous approaches used in recent literature on basis of transient response measures, quality of solution and power quality. The results prove the superiority of the proposed control scheme over that of the particle swarm optimization (PSO) and grasshopper optimization algorithm (GOA) based MG controllers for the same operating conditions and system configuration. Full article
Show Figures

Figure 1

Open AccessFeature PaperArticle
Modern Modeling Paradigms Using Generalized Disjunctive Programming
Processes 2019, 7(11), 839; https://doi.org/10.3390/pr7110839 - 10 Nov 2019
Abstract
Models involving decision variables in both discrete and continuous domain spaces are prevalent in process design. Generalized Disjunctive Programming (GDP) has emerged as a modeling framework to explicitly represent the relationship between algebraic descriptions and the logical structure of a design problem. However, [...] Read more.
Models involving decision variables in both discrete and continuous domain spaces are prevalent in process design. Generalized Disjunctive Programming (GDP) has emerged as a modeling framework to explicitly represent the relationship between algebraic descriptions and the logical structure of a design problem. However, fewer formulation examples exist for GDP compared to the traditional Mixed-Integer Nonlinear Programming (MINLP) modeling approach. In this paper, we propose the use of GDP as a modeling tool to organize model variants that arise due to characterization of different sections of an end-to-end process at different detail levels. We present an illustrative case study to demonstrate GDP usage for the generation of model variants catered to process synthesis integrated with purchasing and sales decisions in a techno-economic analysis. We also show how this GDP model can be used as part of a hierarchical decomposition scheme. These examples demonstrate how GDP can serve as a useful model abstraction layer for simplifying model development and upkeep, in addition to its traditional usage as a platform for advanced solution strategies. Full article
Show Figures

Figure 1

Open AccessFeature PaperArticle
Symmetry Detection for Quadratic Optimization Using Binary Layered Graphs
Processes 2019, 7(11), 838; https://doi.org/10.3390/pr7110838 - 09 Nov 2019
Abstract
Symmetry in mathematical optimization may create multiple, equivalent solutions. In nonconvex optimization, symmetry can negatively affect algorithm performance, e.g., of branch-and-bound when symmetry induces many equivalent branches. This paper develops detection methods for symmetry groups in quadratically-constrained quadratic optimization problems. Representing the optimization [...] Read more.
Symmetry in mathematical optimization may create multiple, equivalent solutions. In nonconvex optimization, symmetry can negatively affect algorithm performance, e.g., of branch-and-bound when symmetry induces many equivalent branches. This paper develops detection methods for symmetry groups in quadratically-constrained quadratic optimization problems. Representing the optimization problem with adjacency matrices, we use graph theory to transform the adjacency matrices into binary layered graphs. We enter the binary layered graphs into the software package nauty that generates important symmetric properties of the original problem. Symmetry pattern knowledge motivates a discretization pattern that we use to reduce computation time for an approximation of the point packing problem. This paper highlights the importance of detecting and classifying symmetry and shows that knowledge of this symmetry enables quick approximation of a highly symmetric optimization problem. Full article
Show Figures

Figure 1

Open AccessArticle
A Mechanistic Model of Mass Transfer in the Extraction of Bioactive Compounds from Intact Sorghum Pericarp
Processes 2019, 7(11), 837; https://doi.org/10.3390/pr7110837 - 09 Nov 2019
Abstract
The extraction of phytochemical compounds from intact red sorghum grains was developed as an alternative process for producing bioactive material in the pharmaceutical industry. A mechanistic model is needed to better understand the process and enable predictive simulations for designing commercial-scale extraction systems. [...] Read more.
The extraction of phytochemical compounds from intact red sorghum grains was developed as an alternative process for producing bioactive material in the pharmaceutical industry. A mechanistic model is needed to better understand the process and enable predictive simulations for designing commercial-scale extraction systems. This paper presents a mathematical model for predicting phytochemical concentrations in the solvent and inside the pericarp of the grain at different positions during the extraction. The model is based on the mass transfer mechanism from inside the pericarp to its solid surface by diffusion, and then from the surface to a solvent during the extraction of bioactive compounds. It was numerically solved while using finite-difference approximation. The parameters considered were effective diffusivity inside the pericarp (Dep), mass transfer coefficient from the pericarp surface to the solvent (kc), and distribution coefficient (H). The model simulates the extraction performance, including the yield and bioactive compounds’ concentrations in the extract and inside the pericarp at various positions and times. A sensitivity analysis of the changes in each involved parameter provided sufficient information for increasing the performance of the model. A validation test that compared the results of the simulation with those of established analytical solutions showed that the model has high accuracy. Hence, the model can be applied in quantitative evaluations to improve productivity in the pharmaceutical industry. Full article
(This article belongs to the Section Computational Methods)
Show Figures

Graphical abstract

Open AccessArticle
Spatiotemporal Dynamics of Carbon Storage in Response to Urbanization: A Case Study in the Su-Xi-Chang Region, China
Processes 2019, 7(11), 836; https://doi.org/10.3390/pr7110836 - 09 Nov 2019
Abstract
Terrestrial ecosystem carbon storage plays an important role in mitigating global warming. Understanding the characteristics and drivers of changes in carbon storage can provide a scientific basis for urban planning and management. The objective of this study was to reveal the ways in [...] Read more.
Terrestrial ecosystem carbon storage plays an important role in mitigating global warming. Understanding the characteristics and drivers of changes in carbon storage can provide a scientific basis for urban planning and management. The objective of this study was to reveal the ways in which urbanization influences the spatial and temporal variations in carbon storage. In this study, we investigated the changes in carbon storage from 1990–2000, 2000–2010, and 2010–2018 in the Su-Xi-Chang region, which is a typical fast-growing urban agglomeration in China, based on the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) model. Moreover, we analyzed the impacts of urbanization-induced land-use changes on carbon storage. The results showed that in terms of space and time, the greatest loss of carbon storage occurred in developing urban areas and during the rapidly urbanizing stage. Our study revealed that the reduction in cultivated land was the greatest contributor to carbon stock losses. In addition, we found that some types of land use conversion can enhance carbon storage. Based on the results, some suggestions are proposed aimed at promoting urban sustainable development. This study also provides insights into enhancing urban sustainability for other urban agglomerations throughout the world. Full article
(This article belongs to the Special Issue Design and Control of Sustainable Systems)
Show Figures

Figure 1

Open AccessArticle
Modifying Nanoporous Carbon through Hydrogen Peroxide Oxidation for Removal of Metronidazole Antibiotics from Simulated Wastewater
Processes 2019, 7(11), 835; https://doi.org/10.3390/pr7110835 - 08 Nov 2019
Abstract
This study examined change in pore structure and microstructure of nanoporous carbon after surface oxidation and how it affects the adsorption performance of metronidazole antibiotics. The surface oxidation was performed by hydrogen peroxide at 60 °C. The properties of porous carbon were investigated [...] Read more.
This study examined change in pore structure and microstructure of nanoporous carbon after surface oxidation and how it affects the adsorption performance of metronidazole antibiotics. The surface oxidation was performed by hydrogen peroxide at 60 °C. The properties of porous carbon were investigated by N2-sorption analysis (pore structure), scanning electron microscopy (surface morphology), the Boehm titration method (quantification of surface functional group), and Fourier transform infrared spectroscopy (type of surface functional group). The results showed that the oxidation of porous carbon by hydrogen peroxide has a minor defect in the carbon pore structure. Only a slight decrease in specific surface area (8%) from its original value (973 m2g−1) was seen but more mesoporosity was introduced. The oxidation of porous carbon with hydrogen peroxide modified the amount of oxide groups i.e., phenol, carboxylic acid and lactone. Moreover, in the application the oxidized carbon exhibited a higher the metronidazole uptake capacity of up to three-times manifold with respect to the pristine carbon. Full article
(This article belongs to the Special Issue Gas, Water and Solid Waste Treatment Technology)
Show Figures

Graphical abstract

Open AccessArticle
Optimal Design of Experiments for Liquid–Liquid Equilibria Characterization via Semidefinite Programming
Processes 2019, 7(11), 834; https://doi.org/10.3390/pr7110834 - 08 Nov 2019
Abstract
Liquid–liquid equilibria (LLE) characterization is a task requiring considerable work and appreciable financial resources. Notable savings in time and effort can be achieved when the experimental plans use the methods of the optimal design of experiments that maximize the information obtained. To achieve [...] Read more.
Liquid–liquid equilibria (LLE) characterization is a task requiring considerable work and appreciable financial resources. Notable savings in time and effort can be achieved when the experimental plans use the methods of the optimal design of experiments that maximize the information obtained. To achieve this goal, a systematic optimization formulation based on Semidefinite Programming is proposed for finding optimal experimental designs for LLE studies carried out at constant pressure and temperature. The non-random two-liquid (NRTL) model is employed to represent species equilibria in both phases. This model, combined with mass balance relationships, provides a means of computing the sensitivities of the measurements to the parameters. To design the experiment, these sensitivities are calculated for a grid of candidate experiments in which initial mixture compositions are varied. The optimal design is found by maximizing criteria based on the Fisher Information Matrix (FIM). Three optimality criteria (D-, A- and E-optimal) are exemplified. The approach is demonstrated for two ternary systems where different sets of parameters are to be estimated. Full article
(This article belongs to the Section Chemical Systems)
Show Figures

Figure 1

Open AccessArticle
Performance Evaluation Using Multivariate Non-Normal Process Capability
Processes 2019, 7(11), 833; https://doi.org/10.3390/pr7110833 - 08 Nov 2019
Abstract
Process capability indices (PCIs) have always been used to improve the quality of products and services. Traditional PCIs are based on the assumption that the data obtained from the quality characteristic (QC) under consideration are normally distributed. However, most data on manufacturing processes [...] Read more.
Process capability indices (PCIs) have always been used to improve the quality of products and services. Traditional PCIs are based on the assumption that the data obtained from the quality characteristic (QC) under consideration are normally distributed. However, most data on manufacturing processes violate this assumption. Furthermore, the products and services of the manufacturing industry usually have more than one QC; these QCs are functionally correlated and, thus, should be evaluated together to evaluate the overall quality of a product. This study investigates and extends the existing multivariate non-normal PCIs. First, a multivariate non-normal PCI model from the literature is modeled and validated. An algorithm to generate non-normal multivariate data with the desired correlations is also modeled. Then, this model is extended using two different approaches that depend on the well-known Box–Cox and Johnson transformations. The skewness reduction is further improved by applying heuristics algorithms. These two approaches outperform the investigated model from the literature because they can provide more precise results regardless of the skewness type. The comparison is made based on the generated data and a case study from the literature. Full article
Show Figures

Figure 1

Previous Issue
Next Issue
Back to TopTop