Answer:
percentage change in volume is 2.60%
water level rise is 4.138 mm
Explanation:
given data
volume of water V = 500 L
temperature T1 = 20°C
temperature T2 = 80°C
vat diameter = 2 m
to find out
percentage change in volume and how much water level rise
solution
we will apply here bulk modulus equation that is ratio of change in pressure to rate of change of volume to change of pressure
and we know that is also in term of change in density also
so
E =
................1
And
............2
here ρ is density
and we know ρ for 20°C = 998 kg/m³
and ρ for 80°C = 972 kg/m³
so from equation 2 put all value


dV = 0.0130 m³
so now % change in volume will be
dV % =
× 100
dV % =
× 100
dV % = 2.60 %
so percentage change in volume is 2.60%
and
initial volume v1 =
................3
final volume v2 =
................4
now from equation 3 and 4 , subtract v1 by v2
v2 - v1 =
dV =
put here all value
0.0130 =
dl = 0.004138 m
so water level rise is 4.138 mm
Answer:
Modulus of resilience will be 
Explanation:
We have given yield strength 
Elastic modulus E = 104 GPa
We have to find the modulus
Modulus of resilience is given by
Modulus of resilience
, here
is yield strength and E is elastic modulus
Modulus of resilience
Answer:
D
Explanation:
took test failed question D is the right answer
Answer:
By running multiple regression with dummy variables
Explanation:
A dummy variable is a variable that takes on the value 1 or 0. Dummy variables are also called binary
variables. Multiple regression expresses a dependent, or response, variable as a linear
function of two or more independent variables. The slope is the change in the response variable. Therefore, we have to run a multiple regression analysis when the variables are measured in the same measurement.The number of dummy variables you will need to capture a categorical variable
will be one less than the number of categories. When there is no obvious order to the categories or when there are three or more categories and differences between them are not all assumed to be equal, such variables need to be coded as dummy variables for inclusion into a regression model.