Optimization of mechanical properties of <scp>PP/EPDM/</scp> clay nanocomposite fabricated by friction stir processing with response surface methodology and neural networks

Nakhaei, Mohammadreza; Mostafapour, Amir; Naderi, Ghasem

doi:10.1002/pc.23942

Cited by 24 publications

(19 citation statements)

References 24 publications

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“…One of the great advantages of RSM is the reduction of the total required numbers of experiments for a system in which the mutual interactions of variables are being analyzed . This method has been widely applied to optimize several responses in the area of polymer composite studies in which there are different material or procedural input parameters contributing to responses …”

Section: Introductionsupporting

confidence: 73%

An approach to the optimization of mechanical properties of polypropylene/nitrile butadiene rubber/halloysite nanotube/polypropylene‐g‐maleic anhydride nanocomposites using response surface methodology

et al. 2020

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In this article, response surface methodology (RSM) has been applied to simultaneously optimize the tensile and impact strength of polypropylene (PP)/nitrile butadiene rubber (NBR)/halloysite nanotubes (HNTs)/maleic anhydride (MA)‐grafted‐PP nanocomposites. Three levels of material parameters, including NBR (10, 20, and 30 wt%), HNTs (1, 3, and 5 wt%), and PP‐g‐MA (3, 9, and 15 wt%) as compatibilizers were used to design the experiments according to Box‐Behnken design. In order to investigate the morphology of nanocomposite samples, a scanning electron microscope was used. The model predicted that both the tensile strength and impact strength of nanocomposite were peaked between middle and high levels of HNTs content. There was also a peak for NBR loading in the main effect plot of impact strength. Two‐way interactions of all parameters were significantly affecting both responses. Based on RSM models using the desirability function, the optimum values of input parameters leading to optimized tensile strength and impact strength were predicted to be 17.87, 4.35, and 15 wt% for NBR, HNT, and PP‐g‐MA, respectively. Confirmation experiments were in good agreement with the predicted values.

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Section: Introductionsupporting

confidence: 73%

An approach to the optimization of mechanical properties of polypropylene/nitrile butadiene rubber/halloysite nanotube/polypropylene‐g‐maleic anhydride nanocomposites using response surface methodology

et al. 2020

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“…In addition, it is difficult to determine the optimum combination of parameters to predict the improved mechanical properties. To solve this problem, design of experiment (DOE) method was used [38][39][40][41][42][43][44][45][46].…”

Section: Introductionmentioning

confidence: 99%

Modeling and optimization of tensile strength and modulus of polypropylene/kenaf fiber biocomposites using Box–Behnken response surface method

Yaghoobi

Fereidoon

2017

Polymer Composites

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The aim of this work includes modeling and optimization of the tensile properties of natural fiber biocomposites using the concept of experimental design. A three‐factor, three‐level Box–Behnken design, which is subset of the response surface methodology (RSM), has been applied to present mathematical models. The effect of three independent variables; kenaf fiber load, fiber length and polypropylene‐grafted maleic anhydride (PP‐g‐MA) compatibilizer content have been investigated on the tensile strength and modulus of polypropylene/kenaf fiber/PP‐g‐MA biocomposite. These models can be used as an interesting method for analytically evaluating both the tensile strength values and their corresponding tensile modulus as function of independent variables. The optimization results, obtained using the optimization part of Design‐Expert Software, showed that the most optimal tensile strength and tensile modulus were to be 32.70 MPa and 2,182.33 MPa, respectively; and achieved at 28.95 wt% of the kenaf fiber, fiber length of 6.22 mm and PP‐g‐MA content of 5 wt%. The obtained R2 values and normal probability plots indicated a good agreement between the experimental results and those predicted by the model (above 0.95 for all the responses). Moreover, the tensile modulus of the biocomposite was analyzed by means of micromechanical models. The performance of the Halpin–Tsai and Cox–Krenchel models in predicting the tensile modulus of biocomposites was compared with available experimental results. In addition, the fracture surface morphologies and wettability of the samples were investigated by scanning electron microscopy (SEM) and contact angle measurement, respectively. It was found that the fiber load and PP‐g‐MA compatibilizer content play a significant role in the tensile properties and morphology of the biocomposites, as proven by SEM and contact angle measurement. POLYM. COMPOS., 39:E463–E479, 2018. © 2017 Society of Plastics Engineers

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“…These plots can be useful for checking the capability of a model to fit the data set [2,36]. The points located on the normal probability plots of the residuals should form a straight line if the model is sufficient [37]. All the figures indicate that the residuals form a straight line in agreement that the errors are normally distributed.…”

Section: Analysis Of Variance For All Responsesmentioning

confidence: 98%

Using constrained mixture design method for optimizing the properties of organoclay filled ethylene-octene copolymer nanocomposites

Tayefi

Razavi‐Nouri

Sabet

2020

Mater. Res. Express

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The mixture design method was used to model the physical and mechanical properties of ethyleneoctene copolymer (EOC) nanocomposite containing organically modified montmorillonite (OMT) which were cross-linked dynamically by various amounts of dicumyl peroxide (DCP). A mixture design technique with three components was employed to assess the correlations between the selected properties of the nanocomposites and the component values. For this purpose, EOC, OMT and DCP content were selected as the components. The influences of these components were studied on the tensile strength, modulus at 100% strain, strain at break, x-ray peak intensity and the initial slope of the logarithm of storage modulus versus the logarithm of angular frequency of the nanocomposites prepared. The regression equations of the models as well as contour plots were generated for the properties studied. Good agreements were found between the experimental results and those predicted by the models. The contour plots of each property were overlaid within the applied constraints to discover the combination of factor ranges that provided the nanocomposite with optimal performance.

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Optimization of mechanical properties of PP/EPDM/ clay nanocomposite fabricated by friction stir processing with response surface methodology and neural networks

Cited by 24 publications

References 24 publications

An approach to the optimization of mechanical properties of polypropylene/nitrile butadiene rubber/halloysite nanotube/polypropylene‐g‐maleic anhydride nanocomposites using response surface methodology

An approach to the optimization of mechanical properties of polypropylene/nitrile butadiene rubber/halloysite nanotube/polypropylene‐g‐maleic anhydride nanocomposites using response surface methodology

Modeling and optimization of tensile strength and modulus of polypropylene/kenaf fiber biocomposites using Box–Behnken response surface method

Using constrained mixture design method for optimizing the properties of organoclay filled ethylene-octene copolymer nanocomposites

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