Durability analysis on properties of water soaked PNNCs and CS-ANN model for wear property analysis of PNNCs

The work aims to prepare and characterize polyester nanoclay nanocomposite (PNNCs) with various weight percentages (0, 2, 4). Nanoclay resin are blended using a mechanical stirrer followed by sonicator. blend is molded as specimens per ASTM standards. addition of improved tensile strength 12% 16% flexural 4% 10%. After 60 days soaking in, the retention rate pure PE, 2PNNC, 4PNNC 84.9%, 89.8%, 90.6%, respectively. At same time, rates 86.7%, 90.2%, 91.9%, SEM images analyzed know reasons for specimen failure under load. ExpDec1 (“One-phase exponential decay function time constant parameter”) model used on experimental data determine composite’s durability. values produced relatively close one another. In all specimens, error percentage predicted during 80 100 water varies very little (less than 1%). study proposes CS-ANN (Cuckoo Search-Artificial Neural Network) architecture predict mass loss. Test results prove that much closer results. Cuckoo Search Algorithm (CSA) along ANN optimize fine-tune hyperparameters according data. loss curves substantially proposed be best fit