Full factorial design approach to carbon nanotubes synthesis by CVD method in argon environment

Determination of parameters affecting aerodynamic performance in S833 airfoil

“…Multiple regression analysis; As a result of the experiments, backward extraction method was used by using 8 values (2 3 full factorial) obtained for two levels of each parameter. In the regression analysis, it was aimed to explain the relationship between the variables functionally and to define this relationship with a model [16].…”

“…With the increase in surface roughness value, a significant decrease in performance was observed. Surface roughness delays the stall angle and decreases the lift [4,16]. When the binary interaction graphs of the factors (Fig.…”

“…The most important limitation that limits our study is the acceptance that all areas of the airfoil surface will be exposed to an equal level of pollution. In the working conditions, there was no equal amount of contamination or deterioration at each point on the airfoil surface [16]. Different scales of roughness can be applied to different parts of the airfoil surface and their effects on aerodynamic performance can be investigated [16].…”

“…In the working conditions, there was no equal amount of contamination or deterioration at each point on the airfoil surface [16]. Different scales of roughness can be applied to different parts of the airfoil surface and their effects on aerodynamic performance can be investigated [16]. Which surface areas are more susceptible to contamination can be determined by critical roughness amounts.…”

“…Full factorial experiments are used to accurately evaluate the main and quadratic interaction effects of experimental factors on target compounds [15]. Thus, the full factorial experimental design gives a more practical and reliable result than fractional factorial experiments such as Taguchi [16]. Factorial design is also advantageous in terms of investigating interactions or changes between factors [17].…”