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Queueing theory is implemented for modeling and analyzing actual conditions in industries and real-world problems. In many cases, the input is converted to the desired output after several successive steps. Lack of space, feedback and vacation are the main characters of these processes. This article deals with the modeling and analyzing the steady-state behavior of an $$M/G/1$$ retrial queueing system with first essential and $$k-1$$ optional phases of service. Also, the probabilistic feedback to orbit at each phase and Bernoulli vacation at the end of $$k$$ -th phase may occur in this system. If the customers find the server busy or on vacation, they join to the orbit. In this article, after finding the probability generating functions of the system and orbit sizes, some important performance measures are found. Also, the system reliability is defined. Eventually, to demonstrate the capability of the proposed model, the sensitivity analysis of cost indices and performance measures via some model parameters (arrival/retrial/vacation rate) in different reliability levels are investigated in two applicable examples. Additionally, for optimizing the performance of the system, some technical suggestions are presented.

The main object of this research is to perform computational fluid dynamics simulation of CO2 capturing from hydrogen-rich streams by aqueous DEA solution in a T-Junction microchannel contactor with 250 μm diameter and 5 mm length at dynamic conditions. To develop a comprehensive mathematical framework to simulate the flow hydrodynamics and mass transfer characteristics of system, the continuity and Navier-Stokes equations, two phase transport, and reaction rate model are coupled in COMSOL Multiphysics software. The developed model is solved and the effects of gas and liquid velocities as well as amine concentration on the CO2 absorption rate, hydrogen purification fraction, and flow hydrodynamic are investigated. The absorption process consists of CO2 diffusion from bubble bulk toward the bubble boundary, CO2 solubility in the liquid boundary, diffusion from the boundary into the liquid bulk, and reaction with the amine molecules. The results show that when the gas and liquid streams are mixed in the junction point to form a bubble, the gas cross-section area becomes narrow, and the fluid velocity increases due to the applied force on the bubble by the liquid layers. It appears that increasing the DEA concentration in the inlet from 5% to 20% increases hydrogen purification fraction from 42.3 to 66.4%, and up to 96.7% hydrogen purity is achieved by 20% aqueous solution of DEA.

The main object of this research is heterogenous modeling of benzene alkylation in three phase reactors based on the mass and energy balance equations by coupling the kinetic and equilibrium models and optimization the process conditions to enhance production capacity. In the first step, the alkylation reactors are simulated considering a three-phase model including heat and mass transfer resistances in the solid catalyst, gas and liquid phases. To prove the accuracy of developed model and adopted assumptions, the simulation results are compared with the plant data. Based on the simulation results, the benzene conversion and ethylbenzene selectivity in the alkylation reactors are 15.03 and 94.60% at the conventional condition. In the second step, considering the temperature of inlet streams to the reactors as decision variables, an optimization problem is formulated to maximize the ethylbenzene production rate as the objective function. Based on the simulation results, applying optimal condition on the system improves the ethylbenzene production by 1.33% at the same ethylene conversion compared to the conventional condition.

The purpose of presented research is the mathematical simulation and sensitivity analysis of ethylene dichloride synthesis (EDC) through direct chlorination of ethylene in a bubble column reactor at steady state condition. In the first step, the reactor is heterogeneously simulated based on the energy and mass balance equations by coupling the mass and energy, kinetic, equilibrium, and population balance models. In the considered process, the gaseous ethylene and chlorine are dispersed and dissolved in the liquid medium and converted to EDC at the presence of a homogeneous catalyst. The population balance model is applied to calculate the heat and mass transfer area along the reactor. To investigate the accuracy of established model, the results of simulation are compared with the plant data. It is confirmed that temperature, pressure, rate of mass transfer, breakage, and coalescence phenomena change the bubble diameter and distribution in the chlorination reactor. In the second step, the effects of operating pressure and temperature on the EDC production rate are investigated by the developed model. In the third step, considering EDC production rate as the cost function the optimal operating temperature of reactor is developed at steady state condition. Based on the obtained results, the optimal operating temperature is 357 K and EDC production at the optimal condition is 23.79 mol s−1.

The main objective of this research is to improve the CO2 solubility and absorption rate of conventional alkanolamines including monoethanolamine (MEA) and methyldiethanolamine (MDEA) by 1,4–diaminobutane (DAB) as a promoter. Typically, the presence of two primary functional groups, lack of strict hindrance, and low molecular weight make DAB an efficient solvent to absorb CO2. In the first step, the absorption kinetic of DAB is investigated theoretically and a rate equation is proposed based on the zwitterion mechanism. In the second step, the equilibrium capacity of MEA and MDEA is promoted by DAB experiment in an isothermal stirred batch reactor in the pressure range 20–100 kPa, temperature range 303–313 K, and promoter volume fraction 0–10%. Then, the effective loading and regenerability of prepared samples are investigated by continuous cyclic absorption and regeneration in the designed reactor. The experimental results show that increasing DAB concentration in the MEA and MDEA as base solutions increases the CO2 absorption rate and equilibrium capacity. © 2020 Society of Chemical Industry and John Wiley & Sons, Ltd.

In this research an process flowsheet is introduced for carbon dioxide conversion to methanol and a mathematical framework is prepared to analyze the operability of proposed plant. The main steps in the designed process are syngas production through methane tri-reframing, syngas purification, methanol synthesis in the isothermal reactor and syngas recycling. To develop a detail framework, the methane and syngas conversion sections are heterogeneously simulated based on the energy and mass conservation laws, and integrated with the considered equilibrium-based model for separation sections. To prove the correctness of developed model, the simulations results are compared with the experimental data at the same condition. Then, an optimization problem is formulated to determine the optimal operating condition of designed process considering methanol production capacity as objective. Since feeding policy is a key strategy to shift tri-reforming reactions toward the desired condition, the applied single-bed tri-reformer in the designed process is substituted by a multi-bed reactor and methanol production capacity is calculated. It concludes that applying the multi-bed reformer changes the tri-reforming reactions toward the hydrogen synthesis side and increases the methanol production rate from 200 to 265 ton day−1.

The main aim of this research is supporting the moving bed radial flow reactors in the propane dehydrogenation unit by membrane modules to produce ultra-pure hydrogen and increasing equilibrium conversion. The propane dehydrogenation is a thermodynamically limited and endothermic reaction, which decreasing hydrogen concentration and increasing operating temperature in the system could increase equilibrium conversion. In the first step, the conventional and membrane supported reactors are heterogeneously modeled based on the mass and energy conservation laws considering catalyst decay. To verify the precision of developed model, the results of simulation are compared with the available plant data. Then, the performance of designed membrane configuration is compared with the conventional process at the same feed condition. It appears that the activity of catalyst decreases along the reactors due to coke build up on the catalyst surface, and it results in the lower propane conversion. The results show that supporting the conventional reactors by hydrogen permselective membrane module increases propane conversion up to 3.09%.

The main object of this research is CO2 conversion to dimethyl ether (DME) based on the coupling methane tri-reforming and DME synthesis units and investigation the performance of developed process by a detail mathematical model. In the developed process, CH4 and CO2 as low-cost feedstocks are converted to DME as green and economic energy carrier that has a lower environment, infrastructure, and transportation issues compared to CH4. In the proposed process, the syngas produced through methane tri-reforming feeds to the DME reactor without any rigorous separation. To investigate the efficiency of the developed process, the conversion section of plant is modeled based on the mass and energy balance equations considering heat and mass transfer resistances, while the separation unit is simulated by an equilibrium-based model. In the next step, an optimization problem is formulated to calculate the optimal operating conditions of process to achieve maximum DME production considering process limitations. The simulation results show that considering some quench points on the tri-reformer to distribute the feed stream along the reactor increases DME production capacity from 150.9 to 243.5 ton day−1.

Low-cycle fatigue behavior of open-cell aluminum foams under compression–compression loading using finite element analyses of created representative volume elements (RVE) and experiments have been investigated in this study. The foam is open-cell type made of aluminum AA6101-T6. Initially, static experimental tests are conducted to determine the yield stress of open-cell aluminum foam, according to ISO 13314 standard. Five different loading levels are selected for the experiments. These loading ranges are empirically selected in which they cause local plastic strains in the cells structures leading to low-cycle fatigue behavior. An algorithm is developed to calculate the low-cycle fatigue life of aluminum foam models. Fatigue tests are also performed for the foam samples under compression cyclic loading using the same selective stress ranges. The predicted fatigue life from numerical analyses are verified by comparing with the experimental results.

In this research, demulsification performance of Ethoxylated coco-amine and Ethyl cellulose mixture is investigated at various concentrations. The efficiency of agents is formulated mathema...

Remaining useful life prediction of a system is one of the most important and critical items to achieve the optimal condition-based maintenance for availability and reliability increase, and maintenance reduction. We develop an artificial neural network (ANN) based approach to increase accuracy for the prediction of a system/component remaining useful life. The ANN model takes the working time/age and some parameters produced by a condition monitoring process at the present and previous inspection points as the inputs, and the percentage of the life is produced as the output. Also, different distribution functions, such as Weibull, Birnbaum–Saunders, Gamma, Wakeby, Logistic and Log–normal function are utilized to adjust each condition monitoring data for a failure history, and the adjusted values are applied to determine the training set so as to decrease the noise factors influences unrelated to the degradation of the equipment. The ANN method is validated using the collected vibration monitoring data from a particular machine (pump bearings in the field). Finally, the performance of the distribution functions on the results of the ANN output is compared and the more effective functions are defined.

The main idea of this research is the modification of methane tri-reforming reactor to increase syngas production capacity. Since methane tri-reforming is an integration of steam reforming, dry reforming, and partial oxidation, the feeding policy is a key solution to shift reaction network toward the desired condition. In this regard, the conventional fixed bed reactor is divided into three equal beds in series, and the optimal distribution of steam, carbon dioxide and oxygen between beds is calculated to maximize hydrogen production. The conventional and proposed configurations are heterogeneously modeled based on the mass and energy conservation laws at steady state condition. Then, the accuracy of the developed model and considered assumptions is proved. To calculate the optimal condition of the proposed multi-bed tri-reformer, a single objective optimization problem is formulated considering process limitations. Based on the optimization results steam and carbon dioxide injection between beds increases hydrogen production about 2.93% at the same catalyst loading. The main advantages of the proposed configuration are higher hydrogen production, adequate hydrogen to carbon monoxide ratio, and higher carbon dioxide conversion. The results shows that carbon dioxide conversion in the proposed multi-bed configuration is about 16%.

The main goal of this research is the modeling and optimization of an industrial hydrogen unit in a domestic oil refinery at steady state condition. The considered process consists of steam methane reforming furnace, low and high temperature shift converters, CO2 absorption column and methanation reactor. In the first step, the reactors are heterogeneously modeled based on the mass and energy balance equations considering heat and mass transfer resistances in the gas and catalyst phases. The CO2 absorption column is simulated based on the equilibrium non-ideal approach. In the second step, a single objective optimization problem is formulated to maximize hydrogen production in the plant considering operating and economic constraints. The feed temperature, firebox temperature, and steam flow rate in the reformer, feed temperature in shift converters, lean amine flow rate in the absorption column, and feed temperature in the methanator are selected as decision variables. The calculated effectiveness factors and mass transfer coefficients prove that the methane reforming is inertia-particle mass transfer control, while shift and methanation reactions are surface reaction control. The simulation results show that applying the optimal condition on the system increases hydrogen production capacity from 85.93 to 105.5 mol s−1.

The main object of this study is modeling and simulation of isooctane production through isobutane alkylation in a multi stage fixed bed reactor at steady state condition. A heterogeneous one-dimen...

Background: Antioxidants are one of the important additives in food samples due to their role in protecting human cells against the effects of free radicals. The analysis of antioxidants is essential due to the role of antioxidants in improving body health. Objective: A square wave voltammetric sensor was fabricated for the determination of tert-butylhydroxyanisole (TBHA) based on the application of CdO/SWCNTs and 1-methyl-3-butylimidazolium chloride as mediators for the modification of carbon paste electrode (MBCl/CdO/SWCNTs/CPE). The MBCl/CdO/SWCNTs/CPE improved the sensitivity of TBHA ~ 6.7 times and showed a linear dynamic range 0.07-600 µM with detection limit 0.02 µA for the analysis of TBHA. The pH investigation confirmed that electro-oxidation of TBHA occurred by exchanging two electrons and two protons. In addition, the MBCl/CdO/SWCNTs/CPE was used for determination of TBHA in food samples.

Sparse code multiple access (SCMA) is a non-orthogonal multiple access (NOMA) uplink solution that overloads resource elements (RE's) with more than one user. Given the success of orthogonal frequency division multiplexing (OFDM) systems, SCMA will likely be deployed as a multiple access scheme over OFDM, called an SCMA-OFDM system. One of the major challenges with OFDM systems is the high peak-to-average power ratio (PAPR) problem, which is typically studied through the PAPR statistics for a system with a large number of independently modulated sub-carriers (SCs). In the context of SCMA systems, the PAPR problem has been studied before through the SCMA codebook design for certain narrowband scenarios, applicable more for low-rate users. However, we show that for high-rate users in wideband systems, it is more meaningful to study the PAPR statistics. In this paper, we highlight some novel aspects to the PAPR statistics for SCMA-OFDM systems that is different from the vast body of existing PAPR literature in the context of traditional OFDM systems. The main difference lies in the fact that the SCs are not independently modulated in SCMA-OFDM systems. Instead, the SCMA codebook uses multi-dimensional constellations, leading to a statistical dependency between the data carrying SCs. Further, the SCMA codebook dictates that an UL user can only transmit on a subset of the available SCs. We highlight the joint effect of the two major factors that influence the PAPR statistics - the phase bias in the multi-dimensional constellation design along with the resource allocation strategy. The choice of modulation scheme and SC allocation strategy are static configuration options, thus allowing for PAPR reduction opportunities in SCMA-OFDM systems through the setting of static configuration parameters. Compared to the class of PAPR reduction techniques in the OFDM literature that rely on multiple signalling and probabilistic techniques, these gains come with no computational overhead. In this paper, we also examine these PAPR reduction techniques and their applicability to SCMA-OFDM systems.

Flow measurement is an essential requirement for monitoring and controlling oil movements through pipelines and facilities. However, delivering reliably accurate measurements through certain meters requires cumbersome calculations that can be simplified by using supervised machine learning techniques exploiting optimizers. In this study, a dataset of 6292 data records with seven input variables relating to oil flow through 40 pipelines plus processing facilities in southwestern Iran is evaluated with hybrid machine-learning-optimizer models to predict a wide range of oil flow rates (Qo) through orifice plate meters. Distance-weighted K-nearest-neighbor (DWKNN) and multi-layer perceptron (MLP) algorithms are coupled with artificial-bee colony (ABC) and firefly (FF) swarm-type optimizers. The two-stage ABC-DWKNN Plus MLP-FF model achieved the highest prediction accuracy (root mean square errors = 8.70 stock-tank barrels of oil per day) for oil flow rate through the orifice plates, thereby removing dependence on unreliable empirical formulas in such flow calculations.

In this research, a novel aqueous solvent, i.e., nanoparticle-enhanced ionic liquid (NEIL), is proposed for CO2 capture by mixing of MEA as the base fluid and [Bmim]BF4 ionic liquid and TiO2 nanoparticles as chemical additives. Then, the flow hydrodynamics, mass transfer characteristics, and CO2 absorption performance of the proposed solvent are investigated in a T-shaped microchannel structure by Computational Fluid Dynamics technique at steady-state condition. To present a detailed model, the Navier–Stokes and continuity equations are combined with a two-phase laminar flow module considering mass transfer between heterogeneous phases. Then, the effects of [Bmim]BF4 and TiO2 mass fraction on CO2 loading, bubble formation, and velocity profile are investigated at different gas and liquid holdups at ionic liquid fraction 0 % to 10% and nanoparticle fraction 0 to 0.1%. It concludes that the purification fraction reaches a maximum at TiO2 weight fraction 0.04% and applying solvent with high nanoparticle content decreases purification fraction. In general, the proposed solvent and the considered contactor present adequate performance to absorb CO2 from the gas mixture.

In this paper, the optimal allocation of constant and switchable capacitors is presented simultaneously in two operation modes, grid-connected and islanded, for a microgrid. Different load levels are considered by employing non-dispatchable distributed generations. The objective function includes minimising the energy losses cost, the cost of peak power losses, and the cost of the capacitor. The optimization problem is solved using the spotted hyena optimizer (SHO) algorithm to determine the optimal size and location of capacitors, considering different loading levels and the two operation modes. In this study, a three-level load and various types of loads, including constant power, constant current, and constant impedance are considered. The proposed method is implemented on a 24-bus radial distribution network. To evaluate the performance of the SHO, the results are compared with GWO and the genetic algorithm (GA). The simulation results demonstrate the superior performance of the SHO in reducing the cost of losses and improving the voltage profile during injection and non-injection of reactive power by distributed generations in two operation modes. The total cost and net saving values for DGs only with the capability of active power injection is achieved 105,780 $ and 100,560.54 $, respectively and for DGs with the capability of active and reactive power injection is obtained 89,568 $ and 76,850.46 $, respectively using the SHO. The proposed method has achieved more annual net savings due to the lower cost of losses than other optimization methods.

This research has focused on modeling and optimization of a radial flow tubular reactor to produce methanol from synthesis gas (syngas) at steady state condition. A heterogeneous one-dimensional model is developed based on the material and energy balance laws to predict the performance of proposed radial flow configuration. To verify the accuracy of developed model, the simulation results of a conventional Lurgi type reactor are compared with the available plant data. In the optimization stage, methanol production capacity is maximized considering the feed temperature, cooling side temperature and feed pressure as decision variables using the genetic algorithm method. Then, the performance of optimized radial flow reactor is compared with the conventional radial flow configuration. The comparison between efficiency of optimized radial flow, conventional radial and axial flow reactors shows an acceptable enhancement in the syngas conversion to methanol and lower pressure drop in the optimized radial flow reactor.

The main goal of this research is modification of the Claus process to produce ultrapure hydrogen through hydrogen sulfide decomposition. The furnace and catalytic reactors in the Claus process are...

This study aimed at producing the biodegradable composite from lignocellulose nanofibers (LCNFs) and Pebax®thermoplastic elastomer. For this purpose, LCNFs at different levels of 0, 1, 3, and 5% were considered. The LCNFs were prepared by benzyl alcohol and then mixed with Pebax®. The liquid phase of the LCNFs and soluble polymer was prepared and then the masterbatches were mixed in an internal mixer (Model 815802, Brabender, Germany). The mixtures from the internal mixer were put into a hot press and test samples were compress-molded. The physical properties results indicated that water absorption and thickness swelling decreased by the addition of more amount of LCNF. By the addition of LCNFs to polymer, the tensile strength and modulus and impact strength were increased compared to samples without LCNF. No regular trend of enthalpy changes was observed as the content of LCNF changed. When the LCNF concentration was increased to 5%, the crystallization temperature was increased. As the LCNF concentration increased to 3%, the glass transition temperature ( Tg) was decreased, whereas by incorporating more LCNFs, the Tgwas increased. The result of the Fourier transform infrared spectra showed the peaks at 1740 cm−1which indicated the presence of polyamide bonds. Also, new peaks were observed in the range of 1400–1500 cm−1that was probably related to the presence of C−C bonds of glucose at LCNFs chains.

In this research, a pseudo steady state model is developed based on the mass and energy balance equations to simulate conversion section of a styrene monomer production plant. The conversion section includes three radial flow reactors in series, equipped with inter stage coolers. Typically, dehydrogenation catalyst experiences deactivation due to loss and migration of promoters, and increasing temperature and steam flow rate are practical solutions to prevent production decay in the plant. In the first step, accuracy of the simulation results is proved against plant data. Since there are different paths to overcome catalyst decay and maintain production capacity at desired level, the main challenge is selection and sequence of manipulated variables to control production capacity considering minimum effort. In this research, a real time optimization strategy is proposed to calculate the optimal trajectory of manipulated variables to control production and selectivity at desired level based on the optimal control theory. The optimization results indicated applying obtained optimal trajectories on the system increases production capacity about 16.13%.

The main goal of this research is to investigate the CO2 solubility and regeneration of aqueous solution of methyl diethanolamine (MDEA) and monoethanolamine (MEA) mixed by 1,5-Diamino-2-methylpentane (DAMP) as absorption promoter. In the first step, the absorption capacity and rate of the solutions are experimented in an isothermal batch reactor at various MDEA to MEA ratios, and DAMP concentration. The CO2 cyclic capacity of solutions is investigated by performing CO2 absorption at 30 °C and solvent regeneration at 70 °C. Then, the effect of DAMP concentration on the boiling point, density, mass loading and pH of aqueous mixture of MEA and MDEA is analyzed. The experimental results show that increasing DAMP concentration in the samples increases the absorption rate and capacity of base solution. The results of cyclic absorption and desorption tests show that there is not a considerable difference between cyclic capacity of the base and promoted solutions at 70 °C.

This work evaluates the efficiency of the aqueous mixture of Methyl Diethanolamine (MDEA) and Diethanolamine (DEA) at various mass concentrations to remove CO2 and H2S from natural gas in an industrial sweetening unit in Fajr Jam Gas Refining Company located in the south of Iran and gives recommendations for modifying the process. The sweetening unit includes absorber and desorption towers, flash drum, lean and rich amine exchanger, kettle type reboiler and a reflux drum. The considered process is simulated by Promax simulator (version 3.2) taking into account operational constraints and sustainability of the environment. The validity of simulation has been evaluated by comparison between simulation results and the plant data. The main objective of this work is the modification of natural gas sweetening unit to achieve lower energy consumption. Thus, the effect of amine circulating rate and MDEA to DEA ratio on steam consumption in the regeneration tower, CO2 and H2S concentration in the treated gas, and the acid gas loadings have been investigated. Therefore, substitution of DEA solvent in the unit with the aqueous mixture of DEA and MDEA is proposed. In the examined cases, the mass concentration of MDEA and DEA lies between 15 and 45 wt% and 0–30 wt%, respectively, with the reference cases having MDEA 0 wt% and DEA 31.6 wt%. The results show that in the proposed cases of alternative mixtures including cases 1 (MDEA15 wt% and DEA 30 wt%), 2 (MDEA 20 wt% and DEA 25 wt%), and 3 (MDEA 25 wt% and DEA 20 wt%) the amount of reduction in amine circulation rate are between 11.1%v/v and 19.4%v/v compared to the original amine circulation rate. Likewise, steam consumption decreases between 24.4 %wt/wt and 27 %wt/wt. Influence of anti-foam injection for the different cases were also studied and it was found that anti-foam with the concentration of 5000 ppmv is more suitable for the optimum operation and is a more cost effective.

The main goal of this research is modeling and real time optimization of an industrial steam methane reformer considering catalyst deactivation. In the first step, the reformer is heterogeneously modeled based on the mass and energy balance equations considering a detailed kinetic model. To prove the accuracy of developed model, the simulation results are compared with the available plant data at steady state condition. In the second step, based on the mechanism of catalyst deactivation, a first order decay model is proposed and the parameters of the model are calculated to minimize the absolute difference between calculated methane conversion and plant data. In the third step, an optimal control problem is formulated to maintain hydrogen production capacity at the desired level. Based on the formulated optimization problem, optimal dynamic trajectories of feed temperature and steam to methane ratio are calculated considering two strategies. Then, the performance of developed optimization procedure is proved considering furnace temperature and feed concentration as disturbance. The simulation results show that operating at the proposed optimal condition increases hydrogen production about 11.6%. In addition, the process emission performance defined as hydrogen to carbon dioxide ratio in the product is 6.72 and 7.03 at the conventional and optimized conditions, respectively.

The prediction of the mechanical behavior of metallic foams with realistic microstructure and the effects of various boundary conditions on the mechanical behavior is an important and challenging issue in modeling representative volume elements (RVEs). A numerical investigation is conducted to determine the effects of various boundary conditions and cell wall cross sections on the compressive mechanical properties of aluminum foam, including the stiffness, plateau stress and onset strain of densification. The open-cell AA6101-T6 aluminum foam Duocel is used in the analyses in this study. Geometrical characteristics including the cell size, foam relative density, and cross-sectional shape and thickness of the cell walls are extracted from images of the foam. Then, the obtained foam microstructure is analyzed as a 2D model. The ligaments are modeled as shear deformable beams with elastic-plastic material behavior. To prevent interpenetration of the nodes and walls inside the cells with large deformations, self-contact-type frictionless interaction is stipulated between the internal surfaces. Sensitivity analyses are performed using several boundary conditions and cells wall cross-sectional shapes. The predicted results from the finite element analyses are compared with the experimental results. Finally, the most appropriate boundary conditions, leading to more consistent results with the experimental data, are introduced.

The main goal of this research is modeling and optimal control of ethylbenzene dehydrogenation reactors to obtain optimal dynamic trajectories of feed temperature and steam flow rate to achieve maximum process performance. In this regard, a pseudo dynamic model is developed for ethylbenzene dehydrogenation reactors based on the mass and energy balance equations considering catalyst deactivation. The process consists of three radial flow reactors, equipped with inter-stage heat exchangers to manipulate feed temperature. To develop an accurate model, a catalyst decay model is selected and the parameters of considered model is calculated based on the plant data. After model validation, a dynamic optimization problem is formulated to achieve maximum styrene capacity and uniform production level as objectives, considering feed temperature and inlet steam flow rate as decision variables. To calculate the optimal trajectory of decisions, a quadratic time dependent correlation is considered for each decision variable and optimal values of coefficients are determined based on the formulated optimization problem. The simulation results show that feed temperature and inlet steam flow rate should be increased gradually during the process run time. It is appeared that, production capacity is improved about 26.42% compared to the conventional condition.

The main objective of this study is modeling and optimization of methanol oxidation over iron-molybdenum oxide catalyst in a fixed bed reactor. The considered process is modeled based on the mass and energy balance equations at steady state condition. To verify accuracy of the proposed model and considered assumptions, the simulation results are compared with the plant data. Then, the effect of feed temperature, coolant temperature and air-to-methanol molar ratio on the reactor performance is investigated. In addition, considering formaldehyde production capacity and selectivity as objectives, a multi-objective optimization problem is formulated considering feed and coolant temperature, and air to methanol ratio as decision variables. Based on the developed mathematical model of the process and multi-objective optimization model, Pareto optimal front is obtained by non-sorting multi-objective genetic algorithm. Then, the single optimal point is selected from developed optimal Pareto front by TOPSIS decision-making method. The performance of the optimized reactor is compared with the conventional reactor at steady state condition.

This work demonstrates the fabrication of a carbon paste electrode containing NiO/CNTs modified with 1-methyl-3-butylimidazolium bromide as the binder (CPE/1-M-3BIBr/NiO/CNTs), and its applications related to the highly sensitive detection of carmoisine. The CPE/1-M-3BIBr/NiO/CNTs system was successfully utilized for the nanomolar determination of carmoisine at pH = 7.0. The CPE/1-M-3BIBr/NiO/CNTs successfully resolved the oxidation signals of carmoisine and tartrazine with a peak separation of 450 mV. This is the first time that an application of an electrochemical sensor for the simultaneous determination of carmoisine and tartrazine, two important azo dyes, has been reported. In addition, wide dynamic linear concentration ranges (70–650 μM for carmoisine and 0.1–750 μM for tartrazine), low detection limits (20 nM for carmoisine and 0.06 μM tartrazine) and excellent reproducibility were reported. The CPE/1-M-3BIBr/NiO/CNTs were successfully used for the analysis of carmoisine and tartrazine in dried fruit and soft drink samples.

In this study, the performance of industrial axial flow adiabatic reactors to produce styrene through ethylbenzene dehydrogenation on the potassium-promoted iron catalyst studied at steady state condition. The dehydrogenation reactors have been modeled heterogeneously based on the one-dimensional mass and energy governing laws and considering a detailed kinetic model. The catalytic and thermal kinetic models have been applied in the mathematical model of process. To prove the accuracy of the considered model and assumptions, the simulation results are compared with the plant data at the same process condition. Also, Genetic algorithm as a powerful method in the global optimization has been considered to maximize styrene production as the objective function. The inlet feed temperature to each reactor is selected as attainable decision variables due to severe effect of temperature on the equilibrium and kinetic constant. This configuration has enhanced styrene production rate by 1.2% compared to industrial adiabatic reactor.

This study investigated the effect of milk packet waste (Tetra Pak™) and maleic anhydride–grafted polyethylene (MAPE) on the physical and mechanical properties of wood–plastic composites. Tetra Pak was used in four levels (0, 10, 20, and 30%) and MAPE was applied in two levels (0 and 3%). The morphology of the samples was characterized using the scanning electron microscope technique. The results showed that adding Tetra Pak and MAPE to samples increased the flexural strength and modulus of elasticity and reduced 24-h water absorption and thickness swelling. The results were also confirmed by electron microscopy images.

The main goal of this research is to investigate absorption rate and capacity of carbon dioxide in aqueous mixtures of DAMP(1,5-Diamino-2-methylpentane)+MDEA(Methyl-diethanolamine), DAMP+MEA(Monoethanolamine), DAH(1,6-Diaminohexane)+MDEA and DAH+MEA in an isothermal stirred batch reactor. The experiments are designed in temperature ranging from 30 to 50 °C, at low pressure and various molar ratios. The results show that although there is an interaction between diamine and conventional amines at low diamine concentration, after a minimum absorption point, increasing DAMP and DAH concentration in conventional amines increases absorption capacity of solutions in all temperatures. Then, a rate equation is developed to predict absorption rate of aqueous solution of DAMP based on Zwitterion mechanism. The kinetic constant and order of reaction are determined considering the absolute difference between measured and predicted rate as the objective function. The results show that the reaction is first order with respect to amine concentration and third order in overall.

Thermolysis and air gasification are the best thermal alternatives to manage waste tires, which can cause a significant environmental impact. In this research, waste tire thermolysis and air gasification processes are modeled based on the thermodynamic framework. To determine the final product distribution, the Gibbs free energy function is minimized considering mass balance equations as equality constraints. To account the mass balance constraints in the objective function, the penalty method is used. To prove the accuracy of the developed model, predicted adiabatic temperature and product distribution through propane combustion and air gasification of a rubber-wood are compared with the reported data in the literature. Then, the effect of pressure, temperature and air to fuel ratio on the performance of thermolysis and gasification processes is investigated. Finally, the optimum condition of tire thermolysis and gasification are determined. The results show that maximum hydrogen efficiency in the pyrolysis and gasification process is 35.45% and 98.03%, respectively. The results prove performance of air gasification over thermolysis process to convert waste tire.

The main goal of this research is modeling and optimization of an industrial modified Claus process to achieve maximum sulfur recovery. The modified Claus process consists thermal conversion in furnace and catalytic conversion in two series fixed bed reactors. The furnace and catalytic reactors are modeled based on the mass and energy conservation laws at steady state condition. To prove the accuracy of the developed mathematical model, simulation results of conventional process are compared with the available plant data. Then, the optimal condition of Claus process is calculated considering sulfur recovery as the objective function using Genetic algorithm as a useful method in global optimization. The attainable decision variables are inlet temperature of furnace and fixed bed reactors, feed distribution along the furnace and flow rate of air in the furnace. The simulation results show that sulfur recovery is improved about 4.63% in the optimized process compared to the conventional process. In addition, performance of auto-thermal reactor as a substitute for conventional adiabatic reactors is investigated to enhance sulfur recovery and reducing sulfur contaminants emission in the Claus process.

A carbon paste electrode modified with 1-methyl-3-butylimidazolium bromide and CuO decorated single-wall carbon nanotubes (1-M-3-BIBr/CuO/SWCNTs/CPE) was utilized for nanomolar determination of amaranth in the presence of nitrite using square wave voltammetric (SWV) method. The structure of CuO/SWCNTs was investigated by SEM method. 1-M-3-BIBr/CuO/SWCNTs/CPE exhibited an enhancement in electro-oxidation current and active surface area. Also, 1-M-3-BIBr/CuO/SWCNTs/CPE exhibited indicated high catalytic activity toward the electro-oxidation of amaranth and simultaneous determination of it in the presence of nitrite. The 1-M-3-BIBr/CuO/SWCNTs/CPE achieved dynamic ranges 0.004–750 μM and 1.0–10,000 μM between the oxidation currents and the concentration of amaranth and nitrite, respectively. We obtained the detection limit of 1.0 nM and 0.5 μM for amaranth and nitrite, respectively. The 1-M-3-BIBr/CuO/SWCNTs/CPE was successfully applied to analysis of amaranth and nitrite in foodstuffs.

Crude oil is a mixture of hydrocarbons, dispersed water droplets, salt, and sediment in a continuous oil phase. Presence of natural surfactants, and applied drag forces on the dispersed water during the oil production, form a stable water-in oil emulsion. Although many demulsifier agents have been developed to break the crude oil emulsion, economic and environmental problems have limited their application. In this research, cellulose-based compounds are used as demulsifier due to their unique properties. They are biodegradable, non-toxic, and environmentally friendly. The efficiency of α-cellulose, microcrystalline cellulose, ethylcellulose at different viscosity grades, and the mixture of ethylcellulose and ethoxylated coco amine are investigated to break the crude oil emulsion through bottle test. According to the experimental data, although ethylcellulose is efficient to break emulsion, low dehydration rate is the main disadvantage of that agent. Moreover, to achieve the maximum dehydration capacity and rate, the optimal demulsifier formulation is obtained based on the experimental results. Finally, the effect of temperature, agent composition, and demulsifier concentration are evaluated on the dehydration capacity and rate of selected agents. The results show that the mixture containing ethylcellulose 46 mPa s and ethoxylated coco amine presents the higher dehydration rate and capacity.

Reliability analysis is very important in a practical engineering system. As these systems in space industry such as spacecraft and satellite are used to increase analysis accuracy, the system should be modeled carefully. Since the systems can impress the mission succession. In the real world, usually systems have multilevel performance and components have multimode failures. But often the binary-state model is used to determination of the reliability of the system. Although, the binary-state is simple and useful, so it cannot capture real states of a system. Therefore, calculation accuracy is decreased and mission risk is increased. Especially, if functions and operations in a mission or a system have a dependency, for example, the operations sequentially were occurred. The solar array mechanism is an important sub-system in a satellite, since if this system is failed, power generation may be stopped and satellite is failed. In this paper, a new method is proposed to model and assess reliability via the Universal generating function (UGF) for a solar array mechanism. The capability of this model for evaluation and determination of the reliability of the solar array mechanism as the multi-state system is shown, that subsystems/components work in a logical order or sequence. In comparison to Boolean algebra and crude Monte Carlo methods, the accuracy of this method is acceptable.

Compressive stress-strain behavior of open cell aluminum foam has been investigated using experimental and multiscale modeling methods. Mechanical behavior of cellular materials intensively depends on their microscopic structure and architecture which may degrade under loadings. To analyze the mechanical response of a full scale and complex aluminum foam component, one may develop multiscale modeling. In this way the degraded material properties are calculated through the analyses of a representative volume element (RVE) considering the micro-structural characteristic, architectural parameters and loading. In this study, open-celled AA6101-T6 aluminum foam is considered for the analyses. Geometrical characteristics of the foam using microscopic images are extracted, including thickness of cell walls, cell size, relative density and cross section of cell walls. The micro model is defined as RVE with nonlinear geometric and material behaviors considering the possible contacts between struts and it is conditioned on macroscopic quantity using appropriate boundary conditions. To validate the proposed model, different experiments have been performed for foam specimens with and without circular hole under compressive quasi-static loading. Finally, multiscale modeling has been proposed to analyze the foam components with complex and irregular shapes. It is shown that in order to model foams considering all the heterogeneities, even with larger size and having non-uniform stress field the use of currently existed finite-element and micro-structural models are not sufficient and the proposed multi-scale modeling which leads to acceptable results can be used for such analyses.

Fault tree analysis is one of the most useful techniques in reliability analysis of multistate systems that analyze and handle complex systems via Monte Carlo simulations or mathematical approaches. Traditional fault tree cannot depict the exact evaluation of components and systems failures with respect to simplex analysis. On the other hand, the exact evaluation of system reliability with unknown data owning to components and elements is still difficult. Therefore, in this paper, in order to overcome this problem as for the quantitative analysis of fault trees, the reliability analysis of a multistate system (i.e. Launch Emergency Detection System) based on fault tree analysis and fuzzy failure rates is studied. Accordingly, using fuzzy arithmetic, events time-to-failure are generated and then the Top Event time to failure is calculated. Finally, the results of the analytical solution are compared with the results attained by presented approach and shows that, in spite of less effort and time consuming, this method has more accuracy and suitable for all real industrial and complex systems. This paper has further developed the method of FTA for the most generic case where both the system and the components have multiple failure states.

In this research, the performance of three ionic liquids namely Trioctylmethylammonium chloride, Trioctylmethylammonium bromide and 1-Hexadecyltrimethylammonium bromide are evaluated as the demulsifier agents to break crude oil emulsion through the bottle test method. Then, the response surface method (RSM) is applied to investigate the effect of demulsifier concentration, temperature, pH and fresh water ratio on the dehydration efficiency of the prepared agents. The experiments are designed based on the central composite design method (CCD). To find the optimum conditions of input variables, an accurate model is developed to predict the dehydration efficiency of agents based on the statistical testing of various models by the analysis of variance (ANOVA). The results shows that temperature and pH of aqueous phase are two main parameters in the demulsification process and the maximum dehydration is attained at neutral value of pH and nearly the maximum temperature in the all samples. Then, the optimum operating conditions of agents are determined by RSM.

The main aim of the present study is to develop a detail mathematical model to investigate the performance of an industrial electrostatic desalting process. The dehydration process consists of a mixing valve and an electrostatic coalescer drum. The equipments are modeled based on the population balance equation considering a detail circuit model in the coalescer drum. The electrode plates and crude oil emulsion are considered as a complex of parallel capacitors and dielectric material, respectively. To prove the accuracy of the model and assumptions, the outlet water cut from the coalescer drum is compared with the plant data. Then the effect of temperature, fresh water rate and current frequency on the strength of applied electric field on the emulsion, voltage decay, size distribution of water droplets and outlet water cut in the treated crude oil is investigated based on the developed model. The simulation results show that increasing current frequency from 50 to 300 Hz reduces water cut in the treated crude oil from 0.12% to 0.09%, respectively.

In this research, the efficiencies of two methods, including quantum dots (QDs) based photocatalysis and magnetic nanoparticles (MNPs) based adsorption for the decolorization of Victoria blue R (VBR) were investigated and compared, experimentally. Synthesis of functionalized zinc sulfide (ZnS) QDs and iron oxide (Fe3O4) MNPs was carried out by a simple chemical precipitation method. 2-mercaptoethanol (ME) and sodium dodecyl sulfate (SDS) were applied for capping and surface modification of ZnS QDs and Fe3O4 MNPs, respectively. The prepared nanoparticles have been characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), transmission electron microscopy (TEM). The mean particle size of ZnS QDs and Fe3O4 MNPs were approximated to be 1–3 nm and 50–80 nm, respectively. In the photocatalytic and adsorption investigations, influence of affecting parameters on the removal efficiencies was studied and optimized. According to the results, both methods can be considered as green, simple and efficient strategies for the removal of organic dyes. However, comparative investigation of the characteristics of the methods demonstrated that the efficiency of the QDs based photodegradation method for the removal of VBR is higher than MNPs based adsorption process. It was also found that the maximum decolorization of 95% and 65% can be achieved after 20 and 45 min at optimum pH 10, 7.5, in the presence of 8 and 10 mg of QDs and MNPs for 30 mg/L of VBR, respectively. Finally, isotherm adsorption model and photodegradation mechanism were discussed, too.

The aim of this study is to evaluate the impact of nano-SiO2 and bark flour (BF) on the natural fiber–plastic composites engineering properties made from high density polyethylene (HDPE) and beech wood flour (WF). For this purpose, WF and BF in 60 mesh size and weight ratio of (50, 0 %), (30, 20 %), (10, 40 %) and (0, 50 %) respectively were mixed with HDPE. In order to increase the interfacial adhesion between the filler and the matrix, the maleic anhydride grafted polyethylene was constantly used at 3 wt% for all formulations as a coupling agent. The nano-SiO2 particles with weight ratio of 0, 1, 2, and 4 % were also utilized to enhance the composites properties. The materials were mixed in an internal mixer (HAAKE) and then the bark and/or wood–plastic composite samples were made utilizing an injection molding machine. The physical tests including water absorption and thickness swelling, and mechanical tests including bending characteristics and un-notched impact strength were carried out on the samples based on ASTM standard. The results indicated that as the BF content increased in the composite, mechanical and physical properties were reduced, but the given properties were increased with the addition of nano-SiO2. The addition of nano-SiO2 had a negative impact on the physical properties, but when it was up to 2 %, it increased the impact strength.

The present study seeks to investigate the effect of beverage storage carton (Tetra Pak™) waste and maleic anhydride-grafted polyethylene (MAPE), coordinated to light polyethylene on the mechanical properties of wood–plastic composites. Four levels of Tetra Pak™ (0%, 10%, 20%, and 30%) and two levels MAPE (0% and 3%) were used. At first, the materials were mixed in a Haake internal mixer and then the samples were made through the injection molding method. The results showed that the composites containing 30% of Tetra Pak™ and 3% MAPE have the highest strength and tensile modulus. Moreover, the sample Tetra Pak™ and containing 3% of MAPE has the highest impact resistance. These results have been confirmed by scanning electron microscopy.

In this research, a conventional shell and tube reactor is supported by the hydrogen and vapor membrane tubes for water vapor removal and hydrogen permeation in the single step DME synthesis process. The proposed dual membrane structure is heterogeneously modeled based on the mass and energy conservation laws at steady state condition. To prove the accuracy of the developed model and assumptions, the simulation results of the conventional DME reactor are compared with the available data. Then, the performance and operability of the proposed structure is compared with the hydrogen membrane, water membrane and conventional reactors. The simulation results show that the DME production capacity in the dual membrane reactor is improved about 17.2% compared to the conventional process. Higher DME production rate due to shift the thermodynamic equilibrium limitations, and lower CO2 production are the main advantages of the proposed reactor.

This research focuses on carbon dioxide absorption using aqueous solution of 1,5-diamino-2-methylpentane (DAMP) in an isothermal batch reactor. Equilibrium CO2 loading by the proposed aqueous solution is measured at the temperature range 30–50 °C, CO2 partial pressure range 5–150 kPa, and different solvent concentrations. To prove the performance of the proposed diamine to capture CO2, absorption and desorption capacity, absorption rate and cyclic capacity of 1,5-diamino-2-methylpentan is measured and compared with MEA and MDEA. The experimental results show that the equilibrium CO2 loading of 1,5-diamino-2-methylpentane, MDEA and MEA are 0.86, 0.43 and 0.54 at 30 °C, respectively. Lower volatility of 1,5-diamino-2-methylpentane compared to MEA results in a lower solvent loss through CO2 removal process. Applying the proposed amine in the absorption towers can decrease solvent circulating rate and required equilibrium stages.