In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate k_p (10^-12g².cm^-4.s^-1) in Incoloy 800H at 900^oC . ANN was used for estimating the predicted values of hot corrosion rate k_p (10^-12g².cm^-4.s^-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg

The effect of solution heat treatment on the mechanical properties of Aluminum-Copper alloy. (2024-T3) by the rolling process is investigated. The solution heat treatment was implemented by heating the sheets to 480 C° and quenching them by water; then forming by rolling for many passes. And then natural aging is done for one month. Mechanical properties (tensile strength and hardness) are evaluated and the results are compared with the metal without treatment during the rolling process. ANSYS analysis is used to show the stresses distribution in the sheet during the rolling process.  It has been seen that good mechanical properties are evident in the alloy without heat treatment due to the strain hardening and also the mechanical

The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (k_La), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

This study present, the density of alum chrom in water and in aqueous solution of poly (ethylene glycol) (1500) at different temperature (288.15, 293.15, 298.15) k. Experimental values of density was used to calculate the apparent molar volume (Vθ), limiting apparent molar volume Vθ˚, experimental slope (Sv) and the partial molar volume at infinite dilution of transfer of solute Δνθ˚. These results have been interpreted the molecular interaction in term of ion- solvent, ion– ion interaction. The structure making /breaking capacities have been inferred from the sign of the second derivative of limiting partial molar volume with respect temperature at constant pressure. Alum has been formed to act as structure breaker in water and aq

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin

In this study, biodiesel was prepared from chicken fat via a transesterification reaction using Mussel shells as a catalyst. Pretreatment of chicken fat was carried out using non‐catalytic esterification to reduce the free fatty acid content from 36.28 to 0.96 mg KOH/g oil using an ethanol/ fat mole ratio equal to 115:1. In the transesterification reaction, the studied variables were methanol: oil mole ratio in the range of (6:1 ‐ 30:1), catalyst loading in the range of (9‐15) wt%, reaction temperature (55‐75 °C), and reaction time (1‐7) h. The heterogeneous alkaline catalyst was greenly synthesized from waste mussel shells throughout a calcin