Model tree approach for predicting uniaxial compressive strength and Young’s modulus of carbonate rocks

Bulletin of Engineering Geology and the Environment - The uniaxial compressive strength (UCS) and Young’s modulus (E) of rock are important parameters for evaluating the strength,...     

Controlled Preparation and Characterization of Nigella Sativa Electrospun Pad for Controlled Release

Silicon - Nigella sativa (NS) oil is an anti-inflammatory agent in the traditional medicine. In the present study, novel electrospun mats contained NS oil/polyacrylonitrile as a sustained release...     

A new hybrid ANFIS–PSO model for prediction of peak particle velocity due to bench blasting

In this paper, a novel hybrid approach is proposed for predicting peak particle velocity (PPV) due to bench blasting in open pit mines. The proposed approach is based on the combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO). In this approach, the PSO is used to improve the performance of ANFIS. Furthermore, a model is developed based on support vector regression (SVR) approach. The models are trained and tested based on actual data compiled from 120 blast rounds in Sarcheshmeh copper mine. To determine the accuracy and efficiency of ANFIS–PSO and SVR models, a statistical model (USBM equation) is applied. According to the obtained results, both techniques can be used to predict the PPV, but the comparison of models shows that the ANFIS–PSO model provides better results. Root mean square error (RMSE), variance account for (VAF), and coefficient of determination (R ²) indices were obtained as 1.83, 93.37 and 0.957 for ANFIS–PSO model, respectively.     

Effect of process conditions on Fischer–Tropsch synthesis product selectivity over an industrial iron-based catalyst in slurry reactor

The authors present the application of the statistical model in CO hydrogenation to CH₄, C₂-C₄ and C₅₊ over industrial iron-based catalyst (100 Fe/5 Cu/4.2 K/25 SiO₂) in a 1-L stirred tank slurry reactor. The effect of different reaction conditions, including temperatures (T = 493, 513 and 533 K), pressures (P = 0.8, 1.5, 2.25, and 2.5 MPa), synthesis gas feed molar ratios (H₂/CO = 0.67 and 2), and gas space velocity (GSV) from 0.52 to 23.5 Ndm³/g-Fe/h on selectivity investigated via a statistical models. The proposed selectivity model is very useful in the oil, gas, and petrochemical industries and can be used for interpretation of experimental data, comparison of performance of different reactor conditions, and reactor modeling and simulation studies. Furthermore, interaction between operating parameters such as pressure, temperature, H₂/CO, and GSV was investigated in selectivity models. A CUBIC polynomial was successfully fitted to the experimental data. It was concluded that C₅₊ selectivity shifts to higher with increasing total pressure (H₂/CO) ratio and decreasing temperature. Decreased H₂/CO ratio and temperature and increasing in the reactor pressure cause CH₄ formation decrease. Temperature and pressure fluctuations vary product distribution. As it is observed, the insignificant term in C₂-C₄ selectivity is pressure. With the models obtained from regression we can reach to the optimum condition for favorite products such as C₂-C₄ or C₅₊. So that optimization must be done to illustrate the optimum conditions. It was obtained that the maximum amount of C₅₊ and C₂-C₄ and minimum amount of methane achieved in T = 528.97 K, P = 1.23 bar, H₂/CO = 2, and GSV = 23.49 Ndm³/g-Fe/h.     

Optimized Dispersive Liquid–Liquid Microextraction and Determination of Sorbic Acid and Benzoic Acid in Beverage Samples by Gas Chromatography

A new rapid method for direct determination of trace levels of sorbic and benzoic acids was developed by dispersive liquid–liquid microextraction and gas chromatography with flame ionization detection. In the proposed approach, the separation procedure of sorbic and benzoic acids was performed on a general chromatographic column without any prior derivatization processes. Some effective parameters on the microextraction recovery were studied and optimized utilizing multilevel factorial and central composite experimental designs. The best concurrent extraction efficiency acquired using ethanol and chloroform as dispersive and extraction solvents. Central composite design (CCD) resulted in the optimized values of microextraction parameters as follows: 1.0 mL of dispersive and 0.1 mL of extraction solvents, ionic salt concentration of 50 g?L^?1 at pH 4. Under optimum conditions, the calibration curve was linear over the range 0.5–20 mg L^?1. Relative standard deviation was 11% and 13% for five repeated determinations for sorbic and benzoic acids, respectively. Limits of detection were acquired as 0.2 mg L^?1 for sorbic acid and 0.5 mg L^?1 for benzoic acid. The average recoveries were 31% and 39% for sorbic and benzoic acids, respectively. The method was successfully applied to the determination of sorbic and benzoic acids as preservatives in beverage samples.     

Evaluation of fibroblast attachment in root conditioning with Er,Cr:YSGG laser versus EDTA: A SEM study

The regeneration of periodontal support is a main concern in periodontal therapy. This study aims to investigate the efficacy of Er, Cr:YSGG laser and EDTA based conditioning in attachment of fibroblast on root surfaces. This in vitro study was conducted on 81 root plates (6 mm × 4 mm × 1 mm) prepared from 27 single‐rooted human mature teeth. The samples were divided into three groups: (1) Er, Cr: YSGG laser conditioning with a G6 tip (2.78 µm, 0.75 W, pulse duration of 140 µs, repetition rate of 20 Hz) for 5–7 s; (2) EDTA conditioning (17%, pH: 8) for 1 min; and (3) the control group which were exposed neither to EDTA nor laser. The viability and proliferation rates assessments were performed using MTT assay on days 3 and 5. In addition, the level of cell attachment was studied using scanning electron microscopy. The data indicated Er, Cr:YSGG conditioning increased cell viability by lapse of time (from days 3–5), with significantly better cell attachment compared to the other groups on days 3 and 5 (P < 0.05). In addition, increasing cell attachment in the EDTA conditioning group compared with the control group was statistically significant on day 5 but not on day 3 (P < 0.05). In conclusion, Er, Cr:YSGG laser conditioning can promote enhance fibroblast attachment on dentinal root surfaces more than EDTA. Microsc. Res. Tech. 78:317–322, 2015. © 2015 Wiley Periodicals, Inc.     

EXPERIMENTAL STUDIES AND MODELING OF HEAT GENERATION IN METAL MACHINING

Heat generation in the cutting zones due to plastic deformation and friction in the cutting region governs insert wear, tensile residual stresses on the machined component surface and may give rise to undesired tolerances and short component life. Therefore, it is crucial that the heat generation is kept under control during metal cutting. In this study an analytical model for prediction of heat generation in the primary and secondary deformation zones is compared with results from finite element simulations and temperature measurements using IR-CCD camera. The used cutting data are altered to study the temperature influence from tool geometry and feed when machining stainless steel SANMAC316L and low carbon steel AISI 1045.