Automated design of a new integrated intelligent computing paradigm for constructing a constitutive model applicable to predicting rock fractures

Making a relation between strains and stresses is an important subject in the rock engineering field. Shear behaviors of rock fractures have been extensively investigated by different researchers. Literature mostly consists of constitutive models in the form of empirical functions that represent experimental data using mathematical regression techniques. As an alternative, this study aims to present a new integrated intelligent computing paradigm to form a constitutive model applicable to rock fractures. To this end, an RBFNN-GWO model is presented, which integrates the radial basis function neural network (RBFNN) with grey wolf optimization (GWO). In the proposed model, the hyperparameters and weights of RBFNN were tuned using the GWO algorithm. The efficiency of the designed RBFNN-GWO was examined comparing it with the RBFNN-GA model (a combination of RBFNN and the Genetic Algorithm). The proposed models were trained based on the results of a systematic set of 84 direct shear tests gathered from the literature. The finding of the current study demonstrated the efficiency of both the RBFNN-GA and RBFNN-GWO models in predicting the dilation angle, peak shear displacement, and stress as the rock fracture properties. Among the two models proposed in this study, the statistical results revealed the superiority of RBFNN-GWO over RBFNN-GA in terms of prediction accuracy.

     

Reliability Prediction of Composite Tubular Structure Under Mechanical Loading by Finite Element Method

The diversified use of filamentary composites in harsh marine environments, recorded in recent years, has prompted researchers to focus their work on the reliability prediction. Through failure criteria, Tsai–Wu and the maximum stress, the reliability of multilayer tubular structures under mechanical loading is the subject of this paper, where Monte Carlo method estimated the failure probability. A sensitivity analysis was performed in order to identify the influence of the different parameters, such as materials’ properties, geometry, manufacturing and loading, on the reliability of the composite cylindrical structure studied. To achieve a high accuracy of the results, we have carried out 105 simulations. The results showed great influence on pressure loading, ply thickness and finally winding angle of filament composite.     

A Taguchi design approach for the enhancement of a detergent-biocompatible alkaline thermostable protease production by Streptomyces mutabilis strain TN-X30

The ability of microorganisms to grow at high temperature, alkaline pH, and high salinity makes them an attractive target for enzyme-production with several industrial applications. One strain TN-X30 has been selected as protease producer and identified as Streptomyces mutabilis after a phenotypic and molecular study. Its production of protease was improved using Taguchi L27 design. The strategy was carried out to identify the optimum levels and the interaction of the screened factors. Following this step, maximum protease activity (10,895 U/ml) was achieved after 6-days of incubation. The TN-X30 protease activity had an optimum of pH and temperature of 10 and 65°C, respectively. Thermodynamic parameters at 60°C were enthalpy 14.26 kJ/mol, entropy −220 J/mol/K, and Gibbs free energy 90.53 kJ/mol. TN-X30 protease production displayed a 16-fold increase reaching 175,000 U/ml in a 100-L fermentor. Furthermore, the lyophilization in presence of sorbitol enhanced the stability of the TN-X30 protease which remained active at 75% after 24-months of storage. The lyophilized TN-X30 protease exhibited exceptional stability indexes in presence of some known commercialized detergent components as NEODOL® 25-7, Dehydol® LT 7, Na₂ CMC, Galaxy LAS, Galaxy LES 70, Galaxy 110, Galaxy CAPB Plus, and Sulfacid K. The lyophilized enzyme also displayed high stability with respect to both solid and liquid detergents. Finally, TN-X30 protease exhibited remarkable destaining of blood, egg, and chocolate stained cloth pieces. These findings may promote TN-X30 protease for use as bioadditive in detergent formulation, thereby reducing environmental chemical threat.     

Efficient GPU-based parallelization of solvation calculation for the blind docking problem

The Journal of Supercomputing - Molecular docking techniques are widely used in computational drug discovery. Most of these techniques simulate the way that a ligand interacts with a protein target...     

Removal of cyanide in aqueous solution by oxidation with hydrogen peroxide in presence of copper-impregnated activated carbon

This work is devoted to the removal of free cyanide from aqueous solution by oxidation with hydrogen peroxide H₂O₂ catalyzed by copper-impregnated activated carbon. Effects of initial molar ratio [H₂O₂]₀/[CN⁻]₀, copper-impregnated activated carbon amount, pH and the temperature on cyanide removal have been investigated.The presence of copper-impregnated activated carbon has increased the reaction rate showing thus a catalytic activity. The rate of cyanides removal increases with the raise of the initial molar ratio [H₂O₂]₀/[CN⁻]0 and decreases with the increase in the pH from 8 to 12. The increase in the copper-impregnated activated carbon amount from 1.5 to 10 g/L in reaction solution has a beneficial effect. Beyond this value, the impact of activated carbon amount is not anymore significant. The temperature does not have a significant effect between 20 and 35 °C. The four successive times re-use of catalyst shows a good stability. The kinetics of cyanide removal has been found to be of pseudo-second-order with respect to cyanide and the rate constants have been determined. This process seems very interesting because the rate of cyanides removal is very fast, the reaction does not use soluble metal catalyst and it consumes only hydrogen peroxide as chemical product.     

Treatment of olive mill washing water by ultrafiltration

Olive oil production requires important quantities of washing water containing low oil concentrations, but classical processes used to recover or to eliminate this oil are ineffective. This study presents a membrane technique to treat olive oil mill washing water using different commercial ultrafiltration membranes: one organic (PCI) and two ceramic (Ceraver) membranes. The influence of the hydrodynamic parameters (transmembrane pressure and flow rate) and the cut‐off membranes on the efficiency of the ultrafiltration process was evaluated, and it was shown the organic PCI membrane could reduce pollution due to organic matter by decreasing the value of the Chemical oxygen demand by about 90%. Moreover, the nature of the ultrafine pore membrane appeared to be an important parameter which may strongly increase or decrease the capacity of the membrane. The membrane cut‐off did not have a strong influence on the performance of the process but if the membrane pores were too large the stability of the dynamically formed membrane decreased at transmembrane pressures greater than 0.2 MPa.     

Hydrogen solid storage: First-principles study of ZrNiH3

The ZrNiH₃ compound is a good candidate for hydrogen storage. In this work we used the first-principles calculation to study this compound. The crystal structures, the electronic properties and the optimization of the internal parameters are treated by the FP-LAPW method implanted in the WIEN2K code. The enthalpies of the dehydrogenation of the ZrNiH₃ compound are calculated. We found that the enthalpy is about −42.89 kJ/mol H, greater but similar to the experimental value of −34.3 kJ/mol H. Potential reasons for this discrepancy are discussed.