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The ethylene production is regarded one of the most significant issues for chemical industries and improving its production operation can bring several benefits. Thus, the market demand for ethylene production has accelerated the improvement of a more rigorous and reliable thermal cracking model of such process. In the present study, developing a rigorous mathematical model for an industrial naphtha cracker is investigated based on experimental data combining with a kinetic model describes the coke formation on the internal reactor tubes.The best kinetic model obtained is applied for predicting the products yield, the gas temperature and the optimal temperature profiles along the reactor to maximize the profit of the process. The influence of process factors on the optimal solutions (mainly, coil outlet temperature (COT), steam to naphtha ratio (S/N) and feed flow rate on the product yields have also been discussed here, and new results of the reactor with the optimal cost and temperature profile are obtained.Modeling, simulation and optimal design via optimization of the industrial thermal cracking reactor has been carried out by gPROMS software. The optimization problems are solved employing a Successive Quadratic Programming (SQP) method formulated as a Non-Linear Programming (NLP) problem.

In this work, adsorption desulfurization is considered for making cleaner fuel. New efficient adsorbents have been designed by using two active metal oxides mainly potassium permanganate (KMnO4) and potassium phosphate (KPO4·3H2O) on Activated Carbon (AC). Ultrasonic assisted impregnation method (IWI) is used in designing the adsorbents offering high pore volume, pore size, surface chemistry, and high surface area. Use of ultrasonic method increases the dispersion of the active material (groups) on AC leading to increased number of collisions between O-atom on AC-support resulting in high sulfur removal from fuel. KMnO4 on AC shows higher adsorption capacity towards sulfur than KPO4·3H2O at the same operating conditions. New results with respect to sulfur removal has obtained compared with those obtained by previous studies. Finally, the adsorption kinetic parameters of such process are developed. Thomas and Yoon–Nelson models and the experimental data are used for this purpose using linear and non-linear regression analysis. Yoon–Nelson kinetic model fits well with the experiments data better than Thomas kinetic model in the entire adsorption column system.

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In this work, an optimization framework is used to obtain useful model for an ammonia synthesis reactor that can be confidently applied to reactor design, operation and control. The main objective in the optimal design of such reactor is the estimation of the optimal reactor length for obtaining the maximum profit from the reactor at the best top temperature with satisfying the process constraints. gPROMS package has been used for modelling, simulation and optimal design via optimization. The optimization problem is posed as a Non-Linear Programming (NLP) problem and is solved using a Successive Quadratic Programming (SQP) method. New results are obtained for reactor length and optimal cost of the reactor. The effect of various top temperatures on the reactor performance is investigated and the simulation of ammonia reactor at each top temperature that provides further insight of the process has also been presented.

Oxidative desulfurization process (ODS), enhanced with a novel metal oxide (Ag ions) as an active component over nano-zeolite that has not been reported in the literature, is used here to improve the fuel quality by removing mercaptan (as a model sulfur compound in the light naphtha). Nano-crystalline (nano-support (Nano-zeolite)) composite is prepared by Incipient Wetness Impregnation method loaded with a metal salt to obtain 0.5, 1 and 1.5% of Ag2O3 over Nano-zeolite. The new homemade nano-catalysts (Ag2O3/Nano-zeolite) prepared are characterized by Brunauer–Emmett–Teller (BET) (surface area, pore volume and pore size), X-ray Diffraction (XRD), Fourier Transform Infra Red (FTIR), and Scanning Electron Microscopy (SEM) analysis. The ODS process is then used to evaluate the performance of the catalysts for the removal of sulfur at different reaction temperatures (80–140 °C) and reaction times (30–50 min) in a batch reactor using the air as oxidant. 87.4% of sulfur removal has been achieved using 1% silver oxide loaded on Nano zeolite (1% of Ag2O3/Nano-zeolite) giving a clear indication that our newly designed catalyst is highly efficient catalyst  in the removal of sulfur compound (mercaptan) from naphtha. A new mechanism of chemical reaction for sulfur removal by oxygen using the new homemade catalyst (Ag2O3/Nano-zeolite) prepared has been suggested in this study. The best kinetic model parameters of the relevant reactions are also estimated in this study using pseudo first order technique based on the experimental results. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

Bai-Hasan wide distillate derived from Bai-Hasan crude oil (having a boiling range from initial boiling point to 823K), was hydrotreated in a Trickle Bed Reactor using the commercial cobaltmolybdenum on alumina (Co-Mo/γ-Al 2 O 3 ) as a catalyst. The reactor temperature was varied from 603 to 673K and the liquid hourly space velocity (LHSV) from 0.6 to 1.9 hr -1 , keeping constant hydrogen to oil ratio (H 2 /Oil) and hydrogen pressure at 350 L/L and 3MPa, respectively. In order to obtain useful models for hydrodesulfurization (HDS) process, the accurate estimation of kinetic model of the relevant reaction scheme were required. Thus, kinetic model of sulfur removal was studied by using an optimization technique based on pilot plant experiment. The minimization of the sum of the squared errors (SSE) between the experimental and estimated concentrations of sulfur compound in the products was used as an objective function to determine the kinetic parameters via non-linear regressions. The predicted product concentration showed very well agreement with the experimental data for a wide range of operating conditions with absolute average errors less than 5%.

To maintain a healthy environment and way of life in the modern world, clean fuel must be produced. It is important to totally and successfully remove sulfur-containing harmful compounds from fuel oil in order to comply with the new sulfur legislation. Numerous methods have been proposed in the literature for desulfurizing fuel oil. In this study, activated carbon (AC), which is regarded as a significant porous material, is derived from agro-wastes such as apricot shells (AS) and is loaded with different combinations of active metals. Nickel–Cobalt–Manganese (NCM) over AC is firstly prepared and evaluated experimentally. Then, several concentrations of Molybdenum (1%, 2% and 3%) are separately added to NCM to generate three novel composite mesoporous nano-catalysts (NCMM_1, NCMM_2 and NCMM_3). Several tests have been carried out to determine the catalysts’ properties, such as BETsurface area, pore volume, FTIR, TGA and SEM, XRF and XRD. These catalysts are then used in the batch oxidative desulfurization process to remove sulfur compounds from wide cut oil (from IBP to 345 °C). The pilot plant conditions were as follows: air flow rate = 120 L/h, reaction temperature = 363 K and reaction time of 1 h for all catalysts. Remarkable characteristics have been noticed, and it was discovered that the nano-catalyst NCMM_2 performed better in terms of degree of sulfur removal compared to other nano-catalysts.