Journal of Chemical and Petroleum Engineering
Year:2024 | Volume:58 | Issue:1|Papers Count:12

A response surface methodology (RSM) with 3 levels and 4 variables was used to model and optimize the n-heptane isomerization kinetic process over Pt-HZSM-5/HMS catalysts in a fixed bed micro reactor. 30 sets of isomerization rate tests were performed at different conditions of H2 flow rate (20-45 ccmin−1), n-heptane flow rate (2-4.5 cch−1), the temperatures (200-350 °C), and the weight percent of HZSM-5 (10-40%). It was observed that the amounts of HZSM-5 into Pt-HMS structure has the greatest effect on the rate of reaction. The surface and contour plots confirm that the rates do not considerably change versus temperature, n-heptane and H2 flow rates. 0.24 molg−1s−1 is the highest reaction rate obtained in the 4.5 cch−1 n-heptane and 45 cc min−1 H2 flow rate. The RSM was effective for predicting and optimizing this process. The modelling results also show both power-law and Langmuir–Hinshelwood models are in agreement with the experimental data.

Gas purification is necessary for many industrial processes, and the using of zeolite adsorbents is one of the low-cost methods in this field. The aim of this work is to synthesize three types of zeolite/quasi-zeolite through hydrothermal technique and evaluate their efficiency in the performance of hydrogen gas purification. The gas mixture contained hydrogen, carbon dioxide and methane. The results indicated that at different pressures, the adsorption of the desired gases at lower temperatures is more favorable. Although all three adsorbents had great performance, for all three adsorbents, carbon dioxide adsorption was higher than methane adsorption, and the order of efficiency was as follows: NaA>SAPO-34>BaA. However, SAPO-34 owned a more superior functioning in absorbing methane, and the performance was as follows: SAPO-34>NaA>BaA. It should be remarked that at pressures less than 300 kPa, the adsorption of the desired gases in the BaA adsorbent reached a higher value faster and shows the superb acting of this adsorbent at low pressures.

Oil refineries have become increasingly more efficient over time. Therefore, huge efforts are being made to invest in better processes and technologies that save energy and maximize the production of high-value products, particularly, gasoline. In this study, two scenarios are proposed to upgrade the Sarir Oil Refinery for increasing its capacity from 10,000 BPD to 120,000 BPD by adding new units of vacuum distillation and Delayed Coking or Fluid Catalytic Cracking (FCC) unit. The production rates of all units are obtained through material balance calculations. Finally, an economical evaluation is carried out to determine if the proposed projects meet the profitability criteria of the refinery and to decide which refinery scenario is techno-economically feasible and maximizes the production of gasoline more than the other. The observational results revealed that the best refinery scenario is the one that uses atmospheric distillation and FCC units as it has less payout time (3.6 years), higher internal rate of return (110%) and higher production of gasoline.

Condensate and liquid blockage is a serious problem in gas condensate reservoirs as it reduces gas production. There are many methods to solve this problem, however, most of them are temporary or expensive. Wettability alteration of reservoir rocks from a liquid-wet state to a gas-wet state via nanoparticles is a long-lasting, cheap, and environmentally friendly solution to condensate blockage. With the aim of promoting this treatment in field scales, this review article presents a report of almost all the research carried out in this area. The results of different research teams are compared and the advantages and disadvantages of each research are detailed. Furthermore, the mechanisms and effects of gas-wetting alteration are fully explained, and the existence of an optimum wettability state is discussed. We found that silica nanoparticles are the most commonly used type of nanoparticles in wettability alteration towards a gas wet state due to their effectiveness and endurance. Most importantly, we present two new theories about the application of nanoparticles in the wettability alteration process of condensate reservoirs. First, it may be possible to inject nanoparticles into reservoirs via foam which not only stabilizes foam but also increases the effectiveness of wettability alteration treatment. Second, nanoparticles can be used to alter the wettability and prevent fines migration and sand production simultaneously. This review can be utilized as a reference in expanding the use of nanoparticles in gas-wetting alteration in field scales.

This study investigates the influence of cereal dextrin on two kinetic parameters of methane hydrate formation. Methane hydrate, solid structure formed by gas and water molecules, are gaining attention for its energy potential and climate regulation. Overcoming challenges like high-pressure requirements, slow formation rates, and economic viability is crucial. The study introduces cereal dextrin as a biodegradable kinetic promoter. In order to explore the influence of cereal dextrin on the formation of gas hydrate, a series of experiments were conducted using a stirred batch cell with a total volume of 169 cm3. The temperature of the cell was carefully controlled at 275.15 K, while the initial pressure was set at 7.5 MPa. Results show dextrin positively influences water to hydrate conversion (WHC) and hydrate volume fraction (HVF). After 100 minutes of hydrate growth, 1% dextrin increases WHC by 150.5% and HVF by 127.8%. The findings suggest dextrin, at 1 wt%, is an optimal concentration for enhancing the kinetics of methane hydrate formation, offering potential applications in energy and environmental fields.

Life cycle assessment is a suitable tool to examine and measure of the environmental aspects of the production of a product from the beginning to its formation. In this study, the environmental impacts of the production process of 1 ton of formalin in an industrial unit producing formalin with the approach of life cycle assessment and the requirements of the international standard ISO14040:2006, the use of SimaPro9 software and three evaluation methods Eco-indicator 99, IMPACT 2002+ and EDIP 2003 were investigated in the period of 2019-2020. The results of modeling with the Eco-indicator 99 method showed that the environmental impact of using methanol is 86% of the total environmental impact of the formalin production process. 80% of this impact comes from the consumption of fossil fuels in the production of methanol. The results obtained from the modeling of the formalin production process by applying the characteristic coefficients of the EDIP 2003 method indicate that the destruction of the ozone layer is the most important effect of the formalin production process and methanol has an 82% effect on the environmental effects of the formalin production process. Among them, more than 28% of the harmful effect of methanol consumption is on the destruction of the ozone layer. The results of modeling with the IMPACT 2002+ method show that 83% of the environmental impacts of the life cycle of formalin production are caused by the consumption of methanol, and the consumption of non-renewable energy sources has an impact of 60% on this value.

The Adomian decomposition method (ADM) is a powerful mathematical technique to find closed-form solutions to nonlinear functional equations including ODEs, PDEs, differential-difference, integral, integro-differential, algebraic, and transcendental equations or systems of such equations. It features a particular infinite series for the representation of nonlinear terms of the equation under study, referred to as the Adomian polynomials. Nevertheless, the computation of such polynomials manually, devoid of any assistance from computational resources, can often be a laborious and protracted endeavor. In this paper, an innovative Python code is proposed, which exploits the SymPy library to perform the involved symbolic calculus operations to generate the Adomian polynomials of any given nonlinear expressions. The use of the code would substantially facilitate the implementation of the ADM to the equations arising in various branches of science and engineering. A number of nonlinear expressions are decomposed to their relevant Adomian polynomials for the sake of demonstration.

This study is focused on identifying the formations, whether are they reservoir formations or not. The effective porosity and permeability evaluating of the oil reservoir is the most important methods to recognize the formations. In this study, the effective porosity and permeability of the Yamama formation in an oil field of southern Iraq can be calculated by applying, the neutron-density and the sonic logs. The calculated effective porosity of the formation ranged between (6% - 17%), and the porosity in the joints was less than (0.04). The permeability in Yamama Formation calculated by three methods: Timur, Morris Biggs oil, and Schlumberger methods. By comparing the values of the permeability calculated by these methods, it was found that the methods of Timor and Schlumberger gave the same results, and also when the permeability calculated by these methods compared with the permeability of the cores, the method of Timur and Schlumberger closer than the results of the cores. So, the Schlumberger and Timor method is the one used in calculating the permeability. The permeability values for most of Yamama formation range from: 0.1 -10 md, and the permeability in the joints was less than 0.001 md.

Today, zeolitic catalysts play an important role in catalytic processes such as cracking, alkylation, etc. However, shaping these catalysts for industrial applications remains a challenge. Despite extensive research in this area in recent years, the number of studies is limited, and detailed information is scarce. Consequently, this study aims to increase awareness of the challenges associated with catalyst shaping and to contribute to the body of knowledge in this field. Following an introduction to the fundamental concepts and shaping techniques, our focus in this review has been on the binder agent, whereby we have categorized the effects of binders that can influence catalyst performance. We demonstrate that while binders may not necessarily possess catalytic properties, the chemical interaction between the binder and the catalyst, as well as the extrusion process, can significantly impact the physicochemical characteristics of the final catalyst, including its acid characteristics, pore characteristics, distribution of loaded metals, and so on. Moreover, depending on the desired properties of the catalyst, different sequences can be employed to utilize the binder. Finally, we identify research gaps in this domain and present recommendations for future studies.

Silver nanoparticles (Ag NPs) as a new antibiotic generation were green produced using Arabic gum, as capping and stabilizing agents, under microwave heating. Results indicated that using 0.5 mL of 3 mM silver nitrate solution and 0.5 mL of Arabic gum solution (1 % W/V), and microwave heating time of 150 s, Ag NPs were fabricated minimum broad emission peak (λmax) and maximum concentration of 424±2 nm and 25±2 ppm, respectively. Transmission electron microscopy and dynamic light scattering analyses specified that the fabricated spherical Ag NPs using these optimal synthetic parameters had particle size, polydispersity index and zeta potential values of the 89 nm, 0.238 and +50 mV. Furthermore, antibacterial test indicated that diameters of the formed clear zones around the holes having Ag NPs were 13 and 15 mm, toward Escherichia coli and Staphilococcus aurous, respectively. Antifungal assessment also shown that synthesized Ag NPs could strongly inhibit the growth of Aspergillus flavus mycelia in the plate during incubation for 7 days. Synthesized Ag NPs using the obtained optimum conditions can be widely used in the food, pharmaceutical and cosmetics areas, due to those high antimicrobial activities.

The effectiveness of nitrate removal was assessed in a 9.5 L packed bed column bioreactor through the evaluation of various feeding strategies and initial concentrations. The bioreactor was filled with zeolite mineral particles and initially treated with Thiobacillus denitrificans. Multiple hydraulic retention times were investigated to determine the efficiency of nitrate removal. The results demonstrate that the designed bioreactor is capable of achieving an 87% reduction in nitrate levels within a three-hour timeframe. This indicates that the bioreactor system can effectively remove nitrate ions from water, even when the initial nitrate content is as high as 400 mg/L, which exceeds the standard limit of 45 mg/L. The computational fluid dynamics (CFD) model yielded satisfactory results, confirming the effectiveness of the bioreactor design. It revealed that the optimal length of the bioreactor is suitable for influents containing 400 mg/L of nitrate. However, for influents with lower nitrate concentrations or when employing lower hydraulic retention times (HRTs), the bioreactor can be constructed with shorter heights. This CFD model can serve as a valuable tool for future studies, particularly in scaling up the bioreactor system.

Green corrosion inhibitors, such as Luffa Cylindrica leaf extract, have demonstrated outstanding inhibitory efficiency on mild steel in acidic environments. However, their effective design and optimization are limited and time-consuming owing to the associated uncertainties. Quantifying these uncertainties remains a challenge due to the requirement of many model realisations to capture and represent the true distribution of uncertainty. This study built a Response Surface Model (RSM) approximation of corrosion inhibition efficiency (IE) for effective optimization and uncertainty propagation. To quantify the uncertainties, we explored two stochastic methods: Monte Carlo Simulation (MCS) and Markowitz classical theory with the Genetic Algorithm (GA). The two approaches differ in propagation, sampling, and the number of realizations. MCS uses the approximation RSM with 10,000 randomly generated realizations, whereas the Markowitz technique uses the mean-variance objective function with just 100 realizations. Markowitz's classical theory revealed a 50 and 99.9% chance that the IE of Luffa Cylindrica leaf extract is 79.7 and 76.5%, respectively while MCS indicates at least 10 and 90% probabilities that the IE of Luffa Cylindrica leaf extract is 85.16 and 74.14%, respectively. When compared to the 88.4% efficiency previously reported for the same extract, the two techniques indicate less than 10% chances for IE. As a result, for the actual implementation of green inhibitors, their assessment must include uncertainty analysis.