Hybrid dynamic modeling of 4-CBA hydrogenation fixed-bed catalytic reactor of PTA production plant

In this paper, a dynamic hybrid model of 4-carboxybenzaldehyde (4-CBA) hydrogenation fixed-bed catalytic reactor of Purified Terephthalic Acid (PTA) production plant has been developed. At the first step, the deactivation model of the reaction system has been predicted by using artificial neural network (ANN) technique. Then, the deactivation model estimated by ANN as black box incorporated to first principle model (FPM) as white box. Therefore, the established hybrid model has been utilized to model the hydrogenation reactor of PTA plant. Finally, the simulated results have been compared with the industrial reactor data. It has been concluded that hybrid model is more precise than a FPM model

Current status and future prospects of renewable and sustainable energy in North America: Progress and challenges

Energy is an important drive for the economic development and social growth. The energy demand has remarkably escalated due to technological developments in various governmental, industrial, and municipal activities. In light of such a fast growth, the fuel prices and control of greenhouse gas emission are the leading driving forces for more effective enhancement in the utilization of renewable energy sources. This reflects the importance of mitigation of global energy demands and climate change, which are the most significant factors in the modern days. In this review paper, a detailed overview in the development and evolution of renewable and sustainable energy supply is provided in terms of their types, characteristics and applications, production processes, advantages, and disadvantages. Moreover, the impacts of the renewable energies on health and environment, along with the relevant policies and regulations are discussed. Further, there is a detailed focus on the emerging technologies, and theoretical and practical challenges in the development of renewable energies are analyzed. Particularly, this review provides information on renewable and sustainable energy status and prospects in North America. Central large-scale technology and distributed configuration of the renewable energies might be improved in the North American countries to effectively utilize the renewable energies to produce electricity, biomass-based fuels, and heating in both local/rural and industrial divisions. In addition to employment opportunities stemmed from manufacturing of the renewable energies, its significant impact on the economic development can be enhanced in all three nations through development of the sources.Post-print / Final draf

Optimization of supercritical carbon dioxide extraction of Passiflora seed oil

This study investigates extraction of Passiflora seed oil by using supercritical carbon dioxide. Artificial neural network (ANN) and response surface methodology (RSM) were applied for modeling and the prediction of the oil extraction yield. Moreover, process optimization were carried out by using both methods to predict the best operating conditions, which resulted in the maximum extraction yield of the Passiflora seed oil. The maximum extraction yield of Passiflora seed oil was estimated by ANN to be 26.55% under the operational conditions of temperature 56.5 °C, pressure 23.3 MPa, and the extraction time 3.72 h; whereas the optimum oil extraction yield was 25.76% applying the operational circumstances of temperature 55.9 °C, pressure 25.8 MPa, and the extraction time 3.95 h by RSM method. In addition, mean-squared-error (MSE) and relative error methods were utilized to compare the predicted values of the oil extraction yield obtained from both models with the experimental data. The results of the comparison reveal the superiority of ANN model compared to RSM model

Performance analysis of crude terephthalic acid hydropurification in an industrial trickle-bed reactor experiencing catalyst deactivation

In this work, a dynamic model of an industrial trickle-bed reactor for hydrogenation reactions of 4-carboxybenzaldehyde has been developed. In this case, a heterogeneous plug-flow model has been considered to predict the dynamic behavior of the catalytic hydropurification reactor of Purified Terephthalic Acid production plant. Furthermore, deactivation model of carbon coated palladium catalyst of the reactor (0.5. wt.% Pd/C, type D3065, supplied by Chimet SpA) has been devised based on the actual plant data. The catalyst of the proposed industrial reactor is deactivated after 360. days. The simulation results indicate that the concentration of 4-carboxybenzaldehyde is very influential. In addition, concentration of para-toluic is not as destructive as that of 4-carboxybenzaldehyde so that it lessens the lifetime of catalyst about 40. days if its concentration in normal operation builds up more than 1.6 times. Besides, the concentration of reactor feed should not be increased to boost the rate of production since this makes the lifetime of the catalyst shorter. If the production rate enhances about 18%, the lifetime of the catalyst drops more than 6. months. The hydropurification reactor control is the most crucial part of the purification unit operation. Thus, in addition to the reactor operation assessment, this dynamic model can be used to evaluate the purification section performance at any time to continue producing on-spec product. Also, it might be used in future in the formulation of model based control strategies for the reactor control

Dynamic assessment and optimization of catalytic hydroprocessing process: sensitivity analysis and practical tips

Among the processes in petrochemical industry, hydroprocessing is an imperative process to produce clean fuels. This process is still being improved despite its 70-year maturity. Catalyst deactivation is a key aspect in the design and operation of catalytic processes in petrochemical industry. In this research, a dynamic heterogeneous model is presented to evaluate the performance of an industrial hydropurification/hydrotreating process in the purified terephthalic acid (PTA) production plant. This process includes a trickle-bed reactor (TBR) packed with palladium supported on carbon (0.5wt.% Pd/C) catalyst. In fact, this chemical production unit represents a three-phase catalytic system where some chemical reactions take place. Therefore, an accurate and meticulous analysis is required to develop a proper mathematical model, taking into account all transport phenomena occurring in the system. The model considers the axial back-mixing, flow non-ideality, and the catalyst deactivation. Model development leads to a set of partial differential equations consisting of nonlinear equations of the reaction rates, nonlinear expression of the catalyst deactivation rate, mass balance of each component in the reaction mixture, and energy balance of each phase. The model parameters are calculated using suitable correlations. The set of partial differential equations is solved using proper numerical techniques, including method of lines and finite difference method, in MATLAB software environment. First, the model reliability is assessed through the comparison of the model results with the industrial data. The validation phase confirms that the model results are accurate, and the developed model can be used for further process evaluation. A sensitivity analysis is then implemented to assess the effects of different operating parameters on the performance of the hydropurification/hydrotreating process. The results reveal that axial dispersion model is more accurate than the plug flow model. Moreover, 4- carboxybenzaldehyde (4-CBA) impurity in the reactor feed is the most detrimental parameter, affecting the catalytic performance. It is found that reduction in the catalyst particle size can improve the catalyst performance by about 16%, and an increase in the catalyst particle porosity can enhance the catalyst lifetime by around 8%. In this condition, the catalyst bed pressure drop is maintained at an acceptable level. In addition, 13% increase in the hydrogen partial pressure enhances the catalyst lifetime by about 20%. It should be noted that pressure increase might lead to the reactor pressure fluctuation, leading to an increase in the PTA powder turbidity. Therefore, reactor operation control is a critical factor. Considering other hydrodynamic parameters, a decrease in liquid hourly space velocity and the catalyst bed porosity improves the system performance in terms of catalyst lifetime and product quality. An increase in the liquid-solid mass transfer and contacting efficiency has a slight positive impact on the catalytic system performance. Product quality control can be carried out more properly if the feed impurity concentration is managed/controlled efficiently. In this research, a practical strategy is presented to effectively mix the feed streams having varying concentrations of the impurities (e.g., high and low concentrations of 4-CBA). This can be achieved by suggesting a proper ratio control, keeping the feed composition and flowrate at normal operating conditions. This strategy can also be employed to deal with the off-spec PTA powder product. In addition, the effect of temperature on the sintering mechanism of the Pd/C catalyst deactivation is investigated. The results reveal that temperature increase can accelerate the decline rate of the Pd/C catalyst surface area. The reduced activity of Pd/C catalyst is in an acceptable agreement with the normalized ratio of reduction in the surface area of pure Pd with increasing temperature. In the last phase, an efficient methodology is proposed to assess the hydroprocessing process in terms of energy and exergy performance. The process simulation and exergy analysis are conducted using Aspen Plus® and MATLAB software packages. The results are in a satisfactory agreement with the industrial data. It is concluded that the optimal operating conditions result in 15% reduction in the exergy destruction; the optimal scenario can also reduce the operation costs and the carbon tax at 9.96% ($20.5/h) and 14.75$14.54/h), respectively

Numerical Analysis of Influential Parameters on the Performance of Vertical-Cylindrical Refinery Furnaces

AbstractAn integrated heat transfer modeling of vertical-cylindrical refinery furnaces was carried out to determine the influential parameters on the fired heaters efficiency as well as the process and flue gas temperature variations. The model was developed considering separate sections of the heater encompassing heat of the flue gas. The model was solved by an iterative procedure with initial boundary conditions. The developed model along with its solution was compiled in MATLAB R2013a environment. The parameters involved into the devised model form the basis for the determination of the most influential parameters on the performance of fired heaters. The sensitivity analysis was accomplished via examining five parameters including excess air, tube pitch, inlet air temperature, fuel composition, and fuel flow rate. Model validation reveals that the model results reasonably agree with the experimental data with less than 4% deviation. The sensitivity analysis demonstrated that varying the five influential parameters by 5% from a base case altered the furnace efficiency by 2.69%, 0.93%, 0.22%, 0.21%, and 0.07%, respectively. The devised model can be employed to reduce computing time and technical costs afforded by the use of computational fluid dynamics (CFD) analysis

A Dynamic Heterogeneous Dispersion Model Evaluates Performance of Industrial Catalytic Hydrotreating Systems

Catalyst deactivation is one of the main challenges in industrial reaction operations. In this paper, a dynamic heterogeneous model is developed for the crude terephthalic acid hydropurification process. The model incorporates the effects of axial mixing and deactivation of the commercial catalyst of palladium supported on carbon on efficiency of the hydropurification operation. The transport phenomena governing equations lead to a series of partial differential equations which are simultaneously solved. The model validation is accomplished using the industrial data. The proposed model satisfactorily simulates the real process, and it is more accurate than the plug flow model to forecast the process behaviors. A decline in the catalyst particle size improves the catalyst performance; an increase in the catalyst porosity prolongs the catalyst lifetime, while maintaining an acceptable pressure drop in the catalyst bed. It is concluded that the effective control of <i>p</i>-xylene oxidation reactor (in terms of process conditions) and inlet temperature rise lead to more efficient purification process