The impact energy analysis by genetic algorithm and response surface methods to study the plastic composite,compatibilizer, and recycled poly effects

Journal of Thermal Analysis and Calorimetry - This study attempts to develop a high-performance wood plastic composite (WPC) in terms of impact strength, tensile strength, and tensile modulus. For...     

Estimation of mechanical properties of LDPE/LLDPE/SEBS nanocomposite reinforced with calcium carbonate nanoparticles by Ch mathematical model

Journal of Thermal Analysis and Calorimetry - Doing experiments in order to determine mechanical properties of nanocomposites costs a lot. Therefore, finding the ways by which the properties of the...     

Controlled elitist multi-objective genetic algorithm joined with neural network to study the effects of nano-clay percentage on cell size and polymer foams density of PVC/clay nanocomposites

The parameters of foaming and nano-clay percentage on the density of polymer foam and cell size with the PVC field is studied. Cell size and density have a significant impact on the strength of foam and its insulation (including sounds and thermal insulation). By optimizing cell size and density, foam can be produced with the best mechanical properties. In foaming process of the nanocomposite samples by mass method, the design variables (input parameters) are foaming time and temperature and MMT content. The controlled elitist multi-objective GA is applied to minimize both the foam density and the cell size. To that end, the population size and the Pareto fraction are selected as 100 and 0.5, respectively. The noninferior solution obtained by the controlled elitist multi-objective GA is illustrated. When both the MMT and the temperature are high, the resulting foam does not have ideal characteristics.