simulation

Nitrogen production units are one of the most important units in refineries, which have different functions according to the needs and existing conditions. In the present study, the aim is to optimize the energy consumption in the nitrogen production unit by changing the operating conditions by HYSYS software (V14-2024). The advantage and novelty of this article is that because the amount and purity of the feed has not changed and due to the importance of energy consumption in refinery units, a large amount of energy reduction observed in the process of the unit. To determine the objective function in the software, the amount of energy of the equipment including coolers, feed compressor, condenser and Reboiler selected. Afterwards, all these values ​​added together in one cell to determine the objective function.  The simulation results showed the optimization of energy consumption by 17.4% compared to the initial value.

Gel propellants have the advantages of both liquid and solid propellants and present a promising future for the aerospace industry. Many gel propellants have shear-thinning behavior, which complicates their behavior in propulsion systems, especially the atomization process. On the other hand, the toxicity of many gel propellants makes the study of their dynamic behavior difficult. In the present work, non-toxic gel simulants were first prepared using a variety of gelling agents. Next, a gel simulant with a behavior similar to UDMH's basic gel fuel was selected from the prepared simulants. The dynamic behavior of the selected simulant gel was studied by different shear-thinning fluid models, and the most suitable rheological model was chosen. Eventually, the simulant gel dynamic behavior was simulated in a pressure swirl injector using the selected rheological model, and the results were compared to the experimental data. The results indicated that the simulant gel made from 0.85 wt.% of HPMC gelling agent is very similar to the basic UDMH gel in terms of dynamic behavior and power law index. Furthermore, among the rheological models, the Carreau-Yasuda model was able to predict the selected gel simulant behavior in a wide range of shear rates. A comparison of the experimental tests and numerical simulation of the gel simulant flow inside the swirl injector revealed that using the calculated constants of the Carreau-Yasuda model can predict the simulant gel dynamic behavior and the functional characteristics such as mass flow rate, discharge coefficient, and spray cone angle with less than 6% error.

With the advancement of technology, food packaging has gradually changed to make changes for the consumer's convenience. Self-heating packages allow customers to heat drinks by using exothermic reactions. In this study, a cylinder made of 316L stainless steel was used to heat 200 mL tea and 200 mL low-fat pasteurized milk using silicon dioxide and aluminum reactions. For this purpose, after pouring the reactive material and closing the cylinder lid, the heating process began by placing it inside the beverage. As a result, the temperature inside the cylinder after 82 s (1 minute and 22 s) increased from 28.1 °C to 122.6 °C and this amount of heat led to an increase in the temperature of the tea from 26.3 °C to 40.9 °C in 277 s (4 min and 37 s). Also, after 563 s (9 min and 23 s), the milk temperature increased from 24.8 °C to 38.1 °C. Then, the heating of the cylinder containing this reaction inside the mentioned beverages was simulated and modeled using COMSOL Multiphysics software. It has been determined that the experimental data and simulated models were properly fitted.

The anti-cancer properties of fermented Wheat Germ Extract (FWGE) have been proven due to the active ingredient benzoquinones, especially 2, 6-dimethoxybenzoquinone (2, 6-DMBQ).  In this research, the development of the FWGE production process with a higher content of 2, 6-DMBQ with respect to the bench-scale was considered and simulated by SuperPro Designer (SPD) software. To evaluate the effect of wheat germ granulation, the fermentation process was performed in 250 mL and 2-liter shake flasks and 3.6- and 13-liter bioreactors. Then, the possibility of yeast complete separation in the final product was investigated by combining centrifugation in 3000 g and pressure filtration with linen, polyester, polypropylene, and cellulose membranes. A comparison of the dryer type effect including oven, spray dryer, freeze dryer, and rotary vacuum dryer in terms of drying time and final moisture content of FWGE showed that the spray dryer gives the product with the least humidity 5 (w/w)% in the lowest time 15 min. Examination of the effect of granulation also showed that at higher scales, non-granulated wheat germ produces more 2,6-DMBQ. Yeast complete removal from the final product was achieved using initial centrifugation at 3000 g and then a filter press with a combination of polypropylene membranes 8-10 µm, polyester 5 µm, and a polymer membrane 1-2 µm. Finally, the production process on scales of 10, 100, and 1000 liters was simulated by SPD software. On the basis of investment cost, the return rate of investment (ROI) equaled 4, 1.9, and 0.4 years on scales of 10, 100, and 1000 liters, respectively. These results showed that the scale-up of the FWGE production process significantly decreases the ROI and can be considered a high-value-added production line at higher scales.

In this work, the oil treatment plant of the Rumaila oil field in Iraq was simulated using Aspen HYSYS. Industrial data from the plant was applied to validate the simulation results. The process was optimized in single-objective and multi-objective modes using a genetic algorithm. The process was optimized for reducing CO2, H2S, and CH4 in the outlet oil flow and the energy of the heater simultaneously by changing the molar flow and temperature of dry crude oil and water. The result shows that by decreasing the temperature of the dry crude oil and water, the amount of the consumed energy will decrease to a large extent, but the amount of H2S, and CH4 in the outlet oil will decrease. Also, it can be concluded that by separating more CO2, H2S, and CH4 in the outlet oil, the temperature should be increased and as a result, the consumption of the energy will be increased. The single-objective optimization results showed that the amount of CO2, H2S, and CH4 was decreased by 46.52%, 43.,94%, and 27.8%, respectively. On the other hand, the results from multi-objective optimizations illustrated a lower reduction in the amounts of CO2, H2S, and CH4. Consequently, it was concluded that single-objective optimization results were better than multi-objective optimizations.

Cyanidation of gold depends on the amount of oxygen in the reaction medium. In this study, the interaction of O2 molecules with crystalline surfaces of gold (110surf0 and 110surf+1 surfaces) is investigated by using density functional theory (DFT). The results showed that the interaction of O2 with Au2 cluster was weak, which leads to overlapping orbitals of the 5dz2-Au and the pz-O2. Oxygen reacts vertically with the surface was almost similar to its reaction with the Au2 cluster. However, the parallel interaction of O2 on the (110surf0) and (110surf+1) surfaces of Au is stronger than the vertical interaction state. Also, the interaction energy of CN- with (110surf+1) surface obtained about 13 kJ/mol more than (110surf0) surface.

This s tudy focuses on the chemical analysis and prediction of Polyethylene Terephthalate (PET) nanoplas tics toxicity on aquatic organisms, considering the influence of particle size and properties. The effect PET NPs of different sizes (1, 4, 9, 16 and 25 nm coded NP1 to NP5) on aquatic organisms such as Terpedo californica (electric ray fish) and Danio rerio (zebrafish) as model species was evaluated by virtual chemical techniques and machine learning methodology based on Multilayer Perceptrons Artificial Neural Networks (MLP ANN) and Support Vector Machine. The PET NPs was built and characterized in silico and then docked on the acetylcholines terase (TcAChE) and cytochrome P450 (Zf CYP450) of the organisms, respectively. The results showed that the binding affinities of the NPs increased s teadily from – 7.1 kcal mol-1 to – 9.9 kcal mol-1 for NP1 to NP4 and experienced a drop at NP5 (– 8.9 kcal mol-1) for TcAChE. The Zf CYP450 also had a similar pattern ranging from -5.2 kcal mol-1 to -8.1 kcal mol-1. The MLP ANN showed an accuracy of 85.9 % and 77.3 %. In comparison, SVM showed a better PET NPs toxicity prediction with an accuracy of 99.5 % and 99.4% based on the inherent properties of TcAChE and Zf CYP450, respectively.

This s tudy focuses on the chemical analysis and prediction of Polyethylene Terephthalate (PET) nanoplas tics toxicity on aquatic organisms, considering the influence of particle size and properties. The effect PET NPs of different sizes (1, 4, 9, 16 and 25 nm coded NP1 to NP5) on aquatic organisms such as Terpedo californica (electric ray fish) and Danio rerio (zebrafish) as model species was evaluated by virtual chemical techniques and machine learning methodology based on Multilayer Perceptrons Artificial Neural Networks (MLP ANN) and Support Vector Machine. The PET NPs was built and characterized in silico and then docked on the acetylcholines terase (TcAChE) and cytochrome P450 (Zf CYP450) of the organisms, respectively. The results showed that the binding affinities of the NPs increased s teadily from – 7.1 kcal mol-1 to – 9.9 kcal mol-1 for NP1 to NP4 and experienced a drop at NP5 (– 8.9 kcal mol-1) for TcAChE. The Zf CYP450 also had a similar pattern ranging from -5.2 kcal mol-1 to -8.1 kcal mol-1. The MLP ANN showed an accuracy of 85.9 % and 77.3 %. In comparison, SVM showed a better PET NPs toxicity prediction with an accuracy of 99.5 % and 99.4% based on the inherent properties of TcAChE and Zf CYP450, respectively.