Prediction of carbon dioxide separation from gas mixtures in petroleum industries using the Levenberg–Marquardt algorithm

In this study, two mathematical models for hydrate formation process to separate carbon dioxide by a combination of two different kinds of organic and surfactant promoters are presented. Promoters such as sodium dodecyl sulfate, sodium dodecyl benzene sulfonate, and dodecyl trimethyl ammonium chloride as surfactant promoters; also, tetrahydrofuran, cyclopentane, 1,3-dioxolane, and 2-methyl tetrahydrofuran as organic promoters have been used in recent years. The results showed that a combination of 3000 ppm of surfactant promoters and 4 wt% organic promoters had the highest separation rate of carbon dioxide and; consequently, the investigated models were based on this optimum condition. As a matter of fact, by using these simulations the hydrate formation behavior was predicted with high accuracy; moreover, conducting consuming experiments is not essential anymore. To sum up, in the present research both Vandermonde matrix model and Levenberg-Marquardt algorithm were applied to predict the hydrate formation behavior; in addition, their results were precisely considered and validated with experimental data.     

Phase Transformations of α-Alumina Made from Waste Aluminum via a Precipitation Technique

We report on a recycling project in which α-Al₂O₃ was produced from aluminum cans because no such work has been reported in literature. Heated aluminum cans were mixed with 8.0 M of H₂SO₄ solution to form an Al₂(SO₄)₃ solution. The Al₂(SO₄)₃ salt was contained in a white semi-liquid solution with excess H₂SO₄; some unreacted aluminum pieces were also present. The solution was filtered and mixed with ethanol in a ratio of 2:3, to form a white solid of Al₂(SO₄)₃·18H₂O. The Al₂(SO₄)₃·18H₂O was calcined in an electrical furnace for 3 h at temperatures of 400–1400 °C. The heating and cooling rates were 10 °C/min. XRD was used to investigate the phase changes at different temperatures and XRF was used to determine the elemental composition in the alumina produced. A series of different alumina compositions, made by repeated dehydration and desulfonation of the Al₂(SO₄)₃·18H₂O, is reported. All transitional alumina phases produced at low temperatures were converted to α-Al₂O₃ at high temperatures. The X-ray diffraction results indicated that the α-Al₂O₃ phase was realized when the calcination temperature was at 1200 °C or higher.     

A new predictor parameter for production rate of ornamental stones

Bulletin of Engineering Geology and the Environment - In this study, a new predictor parameter (NPP), which is based on the product of uniaxial compressive strength (UCS) and Mohs hardness (MH),...     

Core–shell structured Cu@Pt nanoparticles as effective electrocatalyst for ethanol oxidation in alkaline medium

Core–shell nanoparticles of Cu@Pt/C electrocatalysts were synthesized using various Pt:Cu atomic ratios with NaBH₄ as a reducing agent. The crystal structure and surface morphology were studied using X-ray diffraction (XRD) and transmission electron microscopy (TEM). The incorporation of copper in Cu@Pt/C electrocatalysts was found to shift all Pt diffraction planes in the negative direction with expanding the crystal lattice dimensions. The electrocatalytic activity of various Cu@Pt/C electrocatalysts was investigated using cyclic voltammetry, chronoamperometry and electrochemical impedance spectroscopy. Cu@Pt/C electrocatalysts containing Pt:Cu atomic ratios of 1:0.5 and 1:2 showed an enhanced electrochemical performance for ethanol oxidation when related to Pt/C.     

The Effect of Ti on Mechanical Properties of Extruded In-Situ Al-15 pct Mg2Si Composite

This work was carried out to investigate the effect of different Ti concentrations as a modifying agent on the microstructure and tensile properties of an in-situ Al-15 pctMg₂Si composite. Cast, modified, and homogenized small ingots were extruded at 753 K (480 °C) at the extrusion ratio of 18:1 and ram speed of 1 mm/s. Various techniques including metallography, tensile testing, and scanning electron microscopy were used to characterize the mechanical behavior, microstructural observations, and fracture mechanisms of this composite. The results showed that 0.5 pctTi addition and homogenizing treatment were highly effective in modifying Mg₂Si particles. The results also exhibited that the addition of Ti up to 0.5 pct increases both ultimate tensile strength (UTS) and tensile elongation values. The highest UTS and elongation values were found to be 245 MPa and 9.5 pct for homogenized and extruded Al-15 pctMg₂Si-0.5 pctTi composite, respectively. Fracture surface examinations revealed a transition from brittle fracture mode in the as-cast composite to ductile fracture in homogenized and extruded specimens. This can be attributed to the changes in size and morphology of Mg₂Si intermetallic and porosity content.     

On the prediction of solubility of alkane in carbon dioxide using the LSSVM algorithm

The increasing global energy demand and declination of oil reservoir in recent years cause the researchers attention focus on the enhancement of oil recovery approaches. One of the extensive applicable methods for enhancement of oil recovery, which has great efficiency and environmental benefits, is carbon dioxide injection. The CO₂ injection has various effects on the reservoir fluid, which causes enhancement of recovery. One of these effects is extraction of lighter components of crude oil, which straightly depends on solubility of hydrocarbons in carbon dioxide. In order to better understand of this parameter, in this study, Least squares support vector machine (LSSVM) algorithm was developed as a novel predictive tool to estimate solubility of alkane in CO₂ as function of carbon number of alkane, carbon dioxide density, pressure, and temperature. The predicting model outputs were compared with the extracted experimental solubility from literature statistically and graphically. The comparison showed the great ability and high accuracy of developed model in prediction of solubility.     

Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks

To optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, it is essential to use accurate and efficient means to evaluate system reliability against probabilistic events. The predominant approach to quantify the impact of natural disasters on infrastructure systems is the Monte Carlo approach, which still suffers from high computational cost, especially when applied to large systems. This article presents a deep learning framework for accelerating seismic reliability analysis, on a transportation network case study. Two distinct deep neural network surrogates are constructed and studied: (1) a classifier surrogate that speeds up the connectivity determination of networks and (2) an end‐to‐end surrogate that replaces modules such as roadway status realization, connectivity determination, and connectivity averaging. Numerical results from k‐terminal connectivity analysis of a California transportation network subject to a probabilistic earthquake event demonstrate the effectiveness of the proposed surrogates in accelerating reliability analysis while achieving accuracies of at least 99%.     

Inhibition of Listeria monocytogenes and Salmonella by Combinations of Oriental Mustard,Malic Acid,and EDTA

The antimicrobial activities of oriental mustard extract alone or combined with malic acid and EDTA were investigated against Salmonella spp. or Listeria monocytogenes at different temperatures. Five strain Salmonella or L. monocytogenes cocktails were separately inoculated in Brain Heart Infusion broth containing 0.5% (w/v) aqueous oriental mustard extract and incubated at 4 °C to 21 °C for 21 d. For inhibitor combination tests, Salmonella Typhimurium 02:8423 and L. monocytogenes 2–243 were individually inoculated in Mueller Hinton broth containing the mustard extract with either or both 0.2% (w/v) malic acid and 0.2% (w/v) EDTA and incubated at 10 °C or 21 °C for 10 to 14 d. Mustard extract inhibited growth of the L. monocytogenes cocktail at 4 °C up to 21 d (2.3 log₁₀ CFU/mL inhibition) or at 10 °C for 7 d (2.4 log₁₀ CFU/mL inhibition). Salmonella spp. viability was slightly, but significantly reduced by mustard extract at 4 °C by 21 d. Although hydrolysis of sinigrin in mustard extract by both pathogens was 2 to 6 times higher at 21 °C than at 4 °C to 10 °C, mustard was not inhibitory at 21 °C, perhaps because of the instability of its hydrolysis product (allyl isothiocyanate). At 21 °C, additive inhibitory effects of mustard extract with EDTA or malic acid led to undetectable levels of S. Typhimurium and L. monocytogenes by 7 d and 10 d, respectively. At 10 °C, S. Typhimurium was similarly susceptible, but combinations of antimicrobials were not more inhibitory to L. monocytogenes than the individual agents.     

Spectral Fourier–Galerkin benchmark solution for natural convection in an inclined saturated porous medium

This paper presents some novel problems associated with the steady natural convection flow in an inclined square cavity filled with a saturated porous medium. The proposed method is a high-accurate spectral method based on the Fourier–Galerkin technique. The numerical results have demonstrated the advantage for the following reasons. (a) The high-accurate method deals with inclined geometries successfully. (b) The streamlines, isotherms, and the average Nusselt numbers are affected significantly by the inclination of the cavity for high values of Rayleigh number. (c) In contrast with the finite element method a highly accurate and efficient solution with less computational effort is obtained.