Akademik Veri Yönetim Sistemi
Automotive Composites Conference and Exhibition, Michigan, Amerika Birleşik Devletleri, 02 Kasım 2021
Nowadays, "hybrid
composites" containing multi-component additive / reinforcer instead of
single matrix and single reinforcing element attract more attention in new
product designs. For the hybrid composite
materials to be widely used in a critical load bearing application, they must
undergo extensive fatigue tests. However, this situation increases the cost as
it requires extensive test programs and a long process. This study is aimed to
produce the desired quality the hybrid material without a large number of
productions. Particle swarm optimization (PSO), an artificial intelligence
technique based on heuristic algorithm, is used to determine the best
formulation in a simulation environment for the hybrid composite. This study
enables finding the rates of optimum usage for hybrid composite production
containing two or more additives / reinforcing materials before production and
lays the groundwork for research to be carried out in the correct working
ranges. As a result, it is obtained to both reduce the cost and speed up the
production process with a success over than 90% by making pre-simulations using
artificial intelligent optimization algorithms.