Artificial Neural Network for Predicting Hardness of Multistage Solutionized and Artificially Aged LM4 + TiB2 Composites

Abstract

Aluminium casting alloy LM4 (EN 1706 AC-45200) composites with TiB 2 (1, 2, and 3 wt.%) as reinforcements were produced using the two-stage stir casting method. OM and SEM study shows uniform and homogeneous reinforcement distribution in LM4 + TiB 2 composites. As-cast composites were subjected to single-stage solution treatment at 520°C for 2 h and multistage solution treatment at 495 and 520°C for 2 and 4 h, followed by hot water quenching at 60°C and aging at 100 and 200°C for different time intervals. The hardness of as-cast and artificially aged composites were compared in both conditions. Compared to as-cast LM4 alloy, 20-45% improvement in hardness was observed for LM4 + TiB 2 as-cast composites. 60-150% improvement in hardness was observed in artificially aged LM4 + 3 wt.% TiB 2 composites when aged at 100 and 200°C during peak aged conditions. TEM images confirmed the presence of primary strengthening solute-rich phases after age hardening treatment such as θ'-Al 2 Cu and θ"-Al 3 Cu, which are responsible for hardness increment. An artificial neural network (ANN) model was created to predict the hardness trend of these composite samples using MATLAB R2021b, and results proved that the ANN model developed can be utilized as an effective tool to predict the hardness of treated composite samples.

Optimization and prediction of the hardness behaviour of LM4 + Si3N4 composites using RSM and ANN: A comparative study

“…This is because after solutionizing, a homogeneous solid solution is generated, which is transformed into supersaturated solid solution once quenched and this phase is soft and unstable, so, it exhibits lower hardness values than as-cast specimens [23]. MSHT + artificially aged specimens displayed better hardness than as-cast and SSHT + artificially aged specimens because of the presence of more number of precipitates formed, the results of which are in line with the other studies [24], [25]. Specimens aged at 100°C outperformed specimens aged at 200°C when hardness is compared, but the time taken to reach peak hardness is more for specimens aged at 100°C than aged at 200°C, this phenomenon can be explained by aging kinetics [26].…”

Experimental Investigation to Confirm the Presence of TiB2 Reinforcements in the Matrix and Effect of Artificial Aging on Hardness and Tensile Properties of Stir-Cast LM4-TiB2 Composite

“…To achieve better mechanical properties from the cast composites, the distribution of reinforcements in the matrix material should be uniform, and reinforcement agglomeration should be avoided. As per the literature [25], it was confirmed from optical microscope (OM) images that reinforcement was distributed uniformly in the matrix material and that particle agglomeration was not seen (1-3 wt.%), whereas in LM4 + TiB 2 (5 wt.%), composite agglomeration was observed [26]. Hence, it is not explored here for further analysis.…”

Prediction of age-hardening behaviour of LM4 and its composites using artificial neural networks

“…The VHN values of heat-treated composite samples follow a similar trend as in the case of LM4. Our previous studies discuss these composites' aging behavior [23]- [25]. Figures 4 and 5 show the peak aged hardness values and peak aging time of LM4 and its composites.…”

“…These cast composites are machined to the required shapes and are subjected to precipitation hardening treatments; here, for the solutionizing part, we have subjected the samples to both single-stage (SSHT) and multistage (MSHT) solutionizing followed by artificial aging at 100 and 200 °C. The aging process is carried out until peak age is attained [25]. Peak aging is determined based on the Vickers Hardness Number (VHN) values.…”