FE and ANN

Heterogeneous Fenton-like removal of Acid Red 17 (AR17) from aqueous solution was investigated. Feimpregnated nanoporous clinoptilolite (Fe-NP-Clin) was prepared by an impregnation method and used as a catalyst. A complete characterization including X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), inductively coupled plasma (ICP), and Brunauer–Emmett–Teller (BET) analyses was done to describe the physical and chemical properties of NP-Clin and Fe-NP-Clin samples.

17p langthannam 29-12-2021 12 0   Download

In this study, a feed-forward back-propagation Artificial Neural Network (ANN) is used to predict the stress relaxation and behavior of creep for bimaterial microcantilever beam for sensing device. Results obtained from ANSYS® 8.1 finite element (FE) simulations, which show good agreement with experimental work [1], is used to train the neural network. Parametric studies are carried out to analyze the effects of creep on the microcantilever beam in term of curvature and stress developed with time.

8p 12120609 01-06-2020 9 1   Download

This paper presents an approach of linking finite element method with artificial neural network to predict J-Integral parameter in desirable airfoil condition. Finite Element (FE) and Artificial Neural Network (ANN) have been employed for the purpose.

8p tohitohi 19-05-2020 4 0   Download

Highly tensile manganese steel is in great demand owing to its high tensile strength under shock loads. All workpieces are produced through casting, because it is highly difficult to machine. The probabilistic aspects of its casting, its variable composition, and the different casting techniques must all be considered for the optimisation of its mechanical properties. A hybrid strategy is therefore proposed which combines decision trees and artificial neural networks (ANNs) for accurate and reliable prediction models for ore crushing plate lifetimes.

12p caygaocaolon1 13-11-2019 20 0   Download