Answer:
Step-by-step explanation:
From the given information:
Original diameter of the sample = 10 mm
Diameter increases by 0.4 mm
It means that the New diameter[tex]= 10+0.4 = 10.4 mm[/tex]
The change in diameter = new diameter - original diameter [tex]= (10.4 - 10) mm[/tex]
Transverse strain = [tex]\dfrac{change \ in \ diameter }{original \ diameter}[/tex]
= [tex]\dfrac{(10.4 - 10) }{10}[/tex]
= 0.04 mm
Original height = 3 mm
Reduction in the height = 20%
New height = [tex]3 -( 3*20) mm= 2.4 mm[/tex]
Change in height = new height - original height
[tex]= (2.4 - 3) mm[/tex]
Longitudinal strain = [tex]\dfrac{change \ in \ height }{original \ height}[/tex]
[tex]=\dfrac{(2.4 - 3)}{3}[/tex]
= - 0.2 mm
Now;
Poisson’s ratio of sample = [tex]- \dfrac{transverse \ strain }{ longitudinal \ strain}[/tex]
= [tex]\dfrac{- (0.04) }{ (-0.2)}[/tex]
= 0.2
From the given statement, Poisson’s ratio of sample is less than 0.1
However, in the estimation of our data, it is 0.2
This implies that It fails the screening test.
