Application of ANFIS for analytical modeling of JICJIC of functionally graded steels

In the present study, fracture toughness (in terms of JICJIC) of ferritic and austenitic functionally graded steel produced by electroslag remelting has been modeled in crack divider configuration by adaptive network-based fuzzy inference systems (ANFISs). To produce functionally graded steels, two slices of plain carbon steel and austenitic stainless steels were spot welded and used as electroslag remelting electrodes. Functionally graded steel containing graded layers of ferrite and austenite may be fabricated via diffusion of alloying elements during remelting stage. To build the model for graded ferritic and austenitic steels, training, testing and validation using respectively 174 and 120 experimental data were conducted. According to the input parameters, in the ANFIS model, the Vickers microhardness of each layer was predicted. A good fit equation which correlates the Vickers microhardness of each layer to its corresponding chemical composition was achieved by the optimized network for both ferritic and austenitic graded steels. Afterward, the Vickers microhardness of each layer was related to the yield stress of the corresponding layer and by assuming the Holloman relation for the stress–strain curve of each layer, the area under each stress–strain curve was acquired. Finally, by applying the rule of mixtures, fracture toughness of functionally graded steels in crack divider configuration was found through a numerical method. The obtained results from the proposed model are in good agreement with those acquired from the experiments.