Prediction of age-hardening behaviour of LM4 and its composites using artificial neural networks
نویسندگان
چکیده
Abstract This research work highlights the prediction of hardness behaviour age-hardened LM4 and its composites fabricated using a two-stage stir casting method with TiB2 Si3N4. MATLAB - Artificial Neural Networks is used to predict age-hardening composites. Experiments (hardness tensile tests) are conducted collect data for training an ANN model as well investigate effect reinforcements treatment on The results show that increment in reinforcement wt.%, there enhancement ultimate strength (UTS) values within monolithic As-cast hybrid display 37 54% improvement compared as-cast LM4. Heat-treated samples, specifically those treated peak aging MSHT 100°C aging, perform better than samples other heat-treated terms UTS hardness. Compared LM4, MSHT, aged 85 202% VHN. Hybrid hardness, while 3 wt.% (L3TB) UTS, (MSHT aging) L3TB 68% when developed trained five inputs (wt.% TiB2, Si3N4, type solutionizing, temperature, time) one output (VHN) different algorithms number hidden neurons age hardening Among them, Lavenberg-Marquardt (LM) algorithm normalized 30 performs shows least average error 1.588364. confirmation test confirms can %error 0.14 unseen data.
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ژورنال
عنوان ژورنال: Materials research express
سال: 2023
ISSN: ['2053-1591']
DOI: https://doi.org/10.1088/2053-1591/acf64d