An artificial neural network (ANN) was applied to study
the hierarchy
of significance of process variables affecting the degradation of
amoxicillin (AMX) in a heterogeneous photo-Fenton process. Catalyst
and H2O2 dosages were found to be the most significant
variables followed by degradation time and concentration of AMX. The
significant variables were optimized and the optimum condition to
achieve degradation of 97.87% of 40 ppm AMX was 21.54% excess H2O2 dosage, 2.24 g of catalyst in 10 min. A mathematical
model (MM) for the degradation of AMX was developed on the basis of
the combined results of the ANN and the optimization studies. The
MM result showed that increases in both catalyst and H2O2 dosage enhanced the rate of AMX degradation as shown
by the rate constants evaluated from the model. The highest rate constant
at the optimum conditions was 122 M–1 S–1. These results provided invaluable insights into the catalytic degradation
of AMX in photo-Fenton process.
Welding process is considered as a thermal-mechanical-metallurgical coupled problem. In this study, finite element method (FEM) is adopted for predicting the temperature history in Metal Inert Gas (MIG) welding of 5mm thick aluminium 6082 alloy. The Goldak’s double ellipsoidal moving heat source model was used to analyse the influence of peak temperature to the radial distance from the center of the heat source and the thickness of the plate. Temperature-dependent thermal properties of aluminium alloy 6082 in T6 condition and the convective and radiative boundary conditions were included in the model. The finite element code, ANSYS along with APDL command subroutines was employed to obtain the numerical results. The effect of heat input and welding speed on the weld pool shape and temperature distribution were investigated. Finally, the predicted temperature distribution and the size of heat-affected zone were compared with the experimental results. The comparison shows that they are in good agreement.
A new group of fuzzy masks is proposed in this study to perform edge detection of images. A group of 3-pixel masks is used to detect edges in four directions. The resulting images retain more edges and show better continuity of the edges compared to the ones produced by the conventional 3 x 3 fuzzy masks. This is accomplished more efficiently using fewer fuzzy rules. Furthermore, thinning functions incorporated yielded edges with good continuity and optimal thickness.
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