Pythagorean fuzzy incidence graphs with application in illegal wildlife trade

Chemical engineers can model numerous interactions in a process using incidence graphs. They are used to methodically map out a whole network of interconnected processes and controllers to describe each component's impact on the others. It makes it easier to visualize potential process paths or a series of impacts. A Pythagorean fuzzy set is an effective tool to overcome ambiguity and vagueness. In this paper, we introduce the concept of Pythagorean fuzzy incidence graphs. We discuss the incidence path and characterize the strongest incidence path in Pythagorean fuzzy incidence graphs. Furthermore, we propose the idea of Pythagorean fuzzy incidence cycles and Pythagorean fuzzy incidence trees in Pythagorean fuzzy incidence graphs and give some essential results. We illustrate the notions of Pythagorean fuzzy incidence cut vertices, Pythagorean fuzzy incidence bridges, and Pythagorean fuzzy incidence cut pairs. We also establish some results about Pythagorean fuzzy incidence cut pairs. Moreover, we study the types of incidence pairs and determine some crucial results concerning strong incidence pairs in the Pythagorean fuzzy incidence graph. We also obtain the characterization of Pythagorean fuzzy incidence cut pairs using $\alpha$-strong incidence pairs and find the relation between Pythagorean fuzzy incidence trees and $\alpha$-strong incidence pairs. Finally, we provide the application of Pythagorean fuzzy incidence graphs in the illegal wildlife trade

Process simulation of bis (2- Hydroxyethyl) terephthalate and its recovery using two-stage evaporation systems

To preserve the petroleum feedstock and eliminate the environmental problems peculiar to polyethene terephthalate (PET) bottles littering the environment. Chemical recycling method was adopted to convert PET into useful products of prosperous sizeable industrial application. This work employed ASPEN PLUS V8.8 to simulate chemical glycolysis depolymerisation process of PET plastic wastes, using plug flow reactor for commercial production of pure bis (2- hydroxyethyl) terephthalate (BHET). The data for modelling were gotten from the experimental PET glycolysis depolymerisation work. Excess ethylene glycol (EG) was used to degrade PET waste with zinc acetate (Zn(Ac)2) as the active catalyst. The optimum operating conditions of the reaction were mean particle size PET of 127.5 μm, EG:PET (w/w) ratio of 5:1,469 K temperature, 101325 N/m 2 pressure and 3 h residence time. Reaction results were 100 % depolymerisation of PET, 85.24 % yield of BHET and 14.76 % Oligomer. Purification of the BHET was done with two stages evaporation processes using flash columns and crystallizer. Higher temperature and lower pressure were observed to increase the efficiency of the evaporators, but the heat duties increased and momentarily reduced the BHET recovery. BHET recovery was observed to decrease with increase in temperature in the case of crystallisation operation. This work achieved a higher yield and purity of BHET, a higher EG removal for re-use and less heat duties demanded in comparison to previous works. The processes with its operating conditions can be used for future scaling up of commercial processes

Hydrodynamics and particle mixing/segregation measurements in an industrial gas phase olefin polymerization reactor using image processing technique and CFD-PBM model

Particle size distribution (PSD) has a significant impact on the performance of fluidized bed reactors due to uneven distribution in the segregation and mixing phenomena. This paper develops a new method of digital image processing that investigates the hydrodynamics of an industrial gas phase olefin polymerization reactor and studies the fluidization structure of a wide range of particle size distribution in an industrial gas phase polymerization reactor by means of a CFD-PBM coupled model, where the direct quadrature method of moments (DQMOM) was implemented to solve the population balance model. It was shown that the applied parameter assumptions and closure laws were appropriately chosen to satisfactorily predict the available operational data in terms of pressure drop and bed height. The transient CFD-PBM/DQMOM coupled model and image analysis technique are then implemented extensively to analyze bubble fluidization structure and segregation phenomena at different velocities. The particle segregation indicates that the small bubbles present in the bed are unable to induce vigorous mixing at low superficial gas velocity while particle mixing improves at a velocity above the minimum fluidization velocity. Further, the predicted results show higher axial segregation phenomena when compared to the radial direction

Comparing the accuracy of density forecasts from competing GARCH models

In this research we introduce an analyzing procedure using the Kullback-Leibler information criteria (KLIC) as a statistical tool to evaluate and compare the predictive abilities of possibly misspecified density forecast models. The main advantage of this statistical tool is that we use the censored likelihood functions to compute the tail minimum of the KLIC, to compare the performance of a density forecast models in the tails. Use of KLIC is practically attractive as well as convenient, given its equivalent of the widely used LR test. We include an illustrative simulation to compare a set of distributions, including symmetric and asymmetric distribution, and a family of GARCH volatility models. Our results on simulated data show that the choice of the conditional distribution appears to be a more dominant factor in determining the adequacy and accuracy (quality) of density forecasts than the choice of volatility model

Fuzzy-GMC Control of Gas-Phase Propylene Copolymerization in Fluidized Bed Reactor

A modified two-phase model for gas phase propylene and ethylene copolymerization was chosen to represent the process in a fluidized bed reactor. This model considered the entrainment of solid particles in the reactor, as a modification to the original two-phase model assumptions. The non-linearity of this process makes it difficult to control just by using conventional controller such as PID. A hybrid control strategy (a simple designed fuzzy logic controller (FLC) integrated with generic model control (GMC)) is designed to control the temperature of the reactor. This advanced control system was compared with the GMC and conventional PID controller. The simulation results showed that the hybrid controller (Fuzzy-GMC) performed better than both GMC and PID in terms of both servo and regulatory control

Fuzzy-GMC Control of Gas-Phase Propylene Copolymerization in Fluidized Bed Reactor

A modified two-phase model for gas phase propylene and ethylene copolymerization was chosen to represent the process in a fluidized bed reactor. This model considered the entrainment of solid particles in the reactor, as a modification to the original two-phase model assumptions. The non-linearity of this process makes it difficult to control just by using conventional controller such as PID. A hybrid control strategy (a simple designed fuzzy logic controller (FLC) integrated with generic model control (GMC)) is designed to control the temperature of the reactor. This advanced control system was compared with the GMC and conventional PID controller. The simulation results showed that the hybrid controller (Fuzzy-GMC) performed better than both GMC and PID in terms of both servo and regulatory control

Vapor pressure of aqueous methyldiethanolamine mixed with ionic liquids

Vapor pressure of aqueous methyldiethanolamine (MDEA) mixed with various concentrations of 1-butyl-3-methyl-imidazolium tetrafluoroborate ([bmim][BF4]) and 1-butyl-3-methyl-imidazoliumdicyanamide ([bmim][DCA]) have been measured and compared with conventional solvents. A standard response surface methodology (RSM) design, namely central composite design (CCD) has been applied in this work to investigate the effects of temperature and concentration of Piperazine, [bmim][BF4] and [bmim][DCA] on the vapor pressure of aqueous 4 kmol m−3 MDEA. The vapor pressure data of aqueous 4 kmol m−3 MDEA mixed with ionic liquids ranging from 0 to 2.0 kmol m−3 and temperatures ranging from 30 to 80 °C, showed that the ionic liquids reduced the vapor pressure of solvents with the order of [bmim][DCA] > [bmim][BF4]. The experimental values are in good agreement with the values predicted by the models. The model results showed that the quadratic model was suitable and sufficient for predicting the vapor pressure of solutions in the investigated ranges of temperature and concentration

A review on surface modification of activated carbon for carbon dioxide adsorption

The influence of surface modification of activated carbon with gaseous ammonia on adsorption properties toward carbon dioxide (CO2) was reviewed. It was apparent from the literature survey that the surface chemistry of activated carbon strongly affects the adsorption capacity. In general, CO2 adsorption capacity of activated carbon can be increased by the introduction of basic nitrogen functionalities into the carbon surface. Accordingly, in this review the impact of changes in surface chemistry and formation of specific surface groups on adsorption properties of activated carbon were studied.Two different methods, heat treatment and ammonia treatment (amination) for producing activated carbon with basic surface were compared. Amination was found to be suitable modification technique for obtaining efficient CO2 adsorbents. Finally, the common characterization methods were also mentioned

A CFD-PBM coupled model of hydrodynamics and mixing/segregation in an industrial gas-phase polymerization reactor

The particle size distribution (PSD) has a significant influence on the performance of fluidized bed reactors, as uneven distribution usually results from segregation and mixing tendencies. The objective of this paper is to study the segregation of wide range of particle size distribution in an industrial gas phase polymerization reactor by means of a CFD–PBM coupled model, where the direct quadrature method of moments (DQMOM) was implemented to solve the population balance model. It was shown that the model is able to satisfactorily predict the available operational data in terms of pressure drop and bed height. Model sensitivities of discretization scheme, maximum solid packing and fluidization/de-fluidization were also studied. The transient CFD–PBM/DQMOM coupled model is then utilized extensively to analyze minimum fluidization velocity, fluidization behavior and segregation phenomena at different velocities. The results suggested that third-order MUSCL discretization scheme, maximum solid packing value which is 0.01 higher than specific solid volume fraction and also fluidization process were mathematically and physically consistent with real observation. In addition, the segregation is strongly affected at minimum fluidization velocity range of particles. The PSD becomes well-mixed at high gas velocity while the quasi-layer inversion was predicted in low gas velocity

Solubility of CO2 in aqueous solutions of glycerol and monoethanolamine

For decades, carbon dioxide emissions have been an environmental and health issue. Amines like Monoethanolamine (MEA) have long been favoured in strategies based on chemical absorption aimed at CO2 capture and thus reduction of its harmful environmental impacts. However, some drawbacks, such as toxicity, low stability and high cost limit widespread adoption of this technology. New and green solvents are a possible solution to this issue. As a part of the present study, CO2 solubility in aqueous solutions of different molar ratios of MEA and glycerol as a green solvent was studied. The CO2 absorption was performed at three different temperatures (303, 318, and 333 K) at normal atmospheric pressure, while CO2 partial pressure was varied from 1 to 15 kPa, and the gas flow rate in the mixture was changed from 350 to 700 ml/min. The response surface methodology (RSM) based on central composite design (CCD) was used to design the experiment and explore the effects of four independent parameters (molar concentration of MEA, molar concentration of glycerol, temperature, and gas flow rate) on the solubility of CO2 in solution. Analysis of variance (ANOVA) results showed a good agreement between the experimental data and the statistical model. The maximum solubility occurred for 4 M MEA + 2 M glycerol at 333 K and 350 ml/min CO2 flow rate. The CO2 solubility values pertaining to different pressures and concentrations were in good agreement with the general absorption trend. However, as the temperature increased, so did the loading. The findings further revealed that the optimum CO2 solubility was obtained at low glycerol to MEA ratio, as this ensured the solubility at elevated temperatures. As glycerol is a viscous fluid, it can be confirmed that it is a suitable solvent at low pressures and high temperatures. Therefore, it can be a viable alternative solution for post-combustion CO2 capture. In addition, an artificial neural network (ANN) model and correlations of CO2 solubility with CO2 partial pressure for all the studied solvent mixtures were developed in this study. Both the ANN model and the correlations fit the experimental CO2 solubility data reasonably well