“…Polypropylene (PP) as one of the most important commodity thermoplastic polymer have useful properties such as high thermal stability, low density, chemical resistance, good processability and high strength . The industrial use of this polymer is still limited because of its low tensile modulus and poor impact resistance, especially at high strain rate and low temperatures . Blending PP with rubbers such as ethylene‐propylene diene monomer (EPDM) gives tougher materials suitable for automotive, aerospace and medical applications where excellent mechanical, thermal and chemical properties are needed .…”
“…Polypropylene (PP) as one of the most important commodity thermoplastic polymer have useful properties such as high thermal stability, low density, chemical resistance, good processability and high strength . The industrial use of this polymer is still limited because of its low tensile modulus and poor impact resistance, especially at high strain rate and low temperatures . Blending PP with rubbers such as ethylene‐propylene diene monomer (EPDM) gives tougher materials suitable for automotive, aerospace and medical applications where excellent mechanical, thermal and chemical properties are needed .…”
“…Based on the developed for model the response, a near optimal point can then be deduced. RSM is often applied in the characterization and optimization of processes . Elatharasan et al studied the effect of FSW parameters on aluminum alloy using RSM.…”
In this article, effects of friction stir processing parameters such as tool rotational speed, traverse speed, shoulder temperature, and number of passes on tensile modulus and impact strength of polypropylene/ ethylene-propylene diene monomer/clay nanocomposite has been investigated. The Box-Behnken design with four factors at three levels was used for design of experiments. The response surface methodology was employed to develop models capable of predicting the effect of input variable on responses. A multi-layer artificial neural network with back propagation algorithm and 4 -8 -10 -2 topology was also selected for modeling. A set of data on friction stir parameters and experimental results of the mechanical properties were used to train and test the artificial neural network. POLYM. COMPOS., 38:E421-E432,
Thermoplastic elastomeric nanocomposites due to their excellent mechanical, thermal, and chemical properties have a wide application in airplane, shipbuilding, and automotive industries and medical apparatus. Friction stir processing (FSP) is a novel technique for the fabrication of composites, nanocomposites and microstructural modifications. In this paper, polypropylene/ethylene-propylene-diene monomer (PP/EPDM) nanocomposite with 5 wt% nanoclay are fabricated by FSP to determine the effect of process parameters such as tool rotational speed, traverse speed, shoulder temperature, and number of passes on total work of fracture of this nanocomposite. Response surface methodology (RSM) and Box-Behnken design were used to develop a mathematical model relating the process parameters to the total work of fracture. The results show that the total work of fracture increased with increasing the rotational speed and number of passes and decreasing the shoulder temperature. A maximum total work of fracture of 50.3 N/mm was obtained at traverse speed of 42 mm/min when other parameters were at their center level. The maximum total work of fracture of 61.8 N/mm is achieved at rotational speed of 1,200 rpm, traverse speed of 40 mm/min, shoulder temperature of 1008C, and number of passes of 3. POLYM.
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