Answer and Explanation:
considering a rigid system
fixed volume V = C
water at P1=22bar and T1=375ºC
at 22 bar Tsat =217.2ºC
so...
T1>Tsat
thus
Steam is superheated (phase at this condition)
Specific Volume, V1
V1= Vg * [ Tsup/Tsat]
V1= 0.090663* ((375+273)/(217.2+273))
V1= 0.1198 m³/kg (specific volume under this condition)
V=C, T2=195ºC
from Mollier Diagram we have that..
P2= 6bar (quality and enthalpy)
h2= 2840 KJ/kg
Superheated Steam
Most minerals can be characterized and classified by their unique physical properties: hardness, luster, color, streak, specific gravity, cleavage, fracture, and tenacity.
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X because it’s at the origin x and y
Answer:
0.14% probability of observing more than 4 errors in the carpet
Explanation:
When we only have the mean, we use the Poisson distribution.
In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:
![P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}](https://tex.z-dn.net/?f=P%28X%20%3D%20x%29%20%3D%20%5Cfrac%7Be%5E%7B-%5Cmu%7D%2A%5Cmu%5E%7Bx%7D%7D%7B%28x%29%21%7D)
In which
x is the number of sucesses
e = 2.71828 is the Euler number
is the mean in the given interval.
The number of weaving errors in a twenty-foot by ten-foot roll of carpet has a mean of 0.8.
This means that ![\mu = 0.8](https://tex.z-dn.net/?f=%5Cmu%20%3D%200.8)
What is the probability of observing more than 4 errors in the carpet
Either we observe 4 or less errors, or we observe more than 4. The sum of the probabilities of these outcomes is 1. So
![P(X \leq 4) + P(X > 4) = 1](https://tex.z-dn.net/?f=P%28X%20%5Cleq%204%29%20%2B%20P%28X%20%3E%204%29%20%3D%201)
We want P(X > 4). Then
![P(X > 4) = 1 - P(X \leq 4)](https://tex.z-dn.net/?f=P%28X%20%3E%204%29%20%3D%201%20-%20P%28X%20%5Cleq%204%29)
In which
![P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4)](https://tex.z-dn.net/?f=P%28X%20%5Cleq%204%29%20%3D%20P%28X%20%3D%200%29%20%2B%20P%28X%20%3D%201%29%20%2B%20P%28X%20%3D%202%29%20%2B%20P%28X%20%3D%203%29%20%2B%20P%28X%20%3D%204%29)
![P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}](https://tex.z-dn.net/?f=P%28X%20%3D%20x%29%20%3D%20%5Cfrac%7Be%5E%7B-%5Cmu%7D%2A%5Cmu%5E%7Bx%7D%7D%7B%28x%29%21%7D)
![P(X = 0) = \frac{e^{-0.8}*(0.8)^{0}}{(0)!} = 0.4493](https://tex.z-dn.net/?f=P%28X%20%3D%200%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B0%7D%7D%7B%280%29%21%7D%20%3D%200.4493)
![P(X = 1) = \frac{e^{-0.8}*(0.8)^{1}}{(1)!} = 0.3595](https://tex.z-dn.net/?f=P%28X%20%3D%201%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B1%7D%7D%7B%281%29%21%7D%20%3D%200.3595)
![P(X = 2) = \frac{e^{-0.8}*(0.8)^{2}}{(2)!} = 0.1438](https://tex.z-dn.net/?f=P%28X%20%3D%202%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B2%7D%7D%7B%282%29%21%7D%20%3D%200.1438)
![P(X = 3) = \frac{e^{-0.8}*(0.8)^{3}}{(3)!} = 0.0383](https://tex.z-dn.net/?f=P%28X%20%3D%203%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B3%7D%7D%7B%283%29%21%7D%20%3D%200.0383)
![P(X = 4) = \frac{e^{-0.8}*(0.8)^{4}}{(4)!} = 0.0077](https://tex.z-dn.net/?f=P%28X%20%3D%204%29%20%3D%20%5Cfrac%7Be%5E%7B-0.8%7D%2A%280.8%29%5E%7B4%7D%7D%7B%284%29%21%7D%20%3D%200.0077)
![P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 0.4493 + 0.3595 + 0.1438 + 0.0383 + 0.0077 = 0.9986](https://tex.z-dn.net/?f=P%28X%20%5Cleq%204%29%20%3D%20P%28X%20%3D%200%29%20%2B%20P%28X%20%3D%201%29%20%2B%20P%28X%20%3D%202%29%20%2B%20P%28X%20%3D%203%29%20%2B%20P%28X%20%3D%204%29%20%3D%200.4493%20%2B%200.3595%20%2B%200.1438%20%2B%200.0383%20%2B%200.0077%20%3D%200.9986)
![P(X > 4) = 1 - P(X \leq 4) = 1 - 0.9986 = 0.0014](https://tex.z-dn.net/?f=P%28X%20%3E%204%29%20%3D%201%20-%20P%28X%20%5Cleq%204%29%20%3D%201%20-%200.9986%20%3D%200.0014)
0.14% probability of observing more than 4 errors in the carpet
Answer: eccentricity of loading with respect to the centroid. - Member out-of ... columns. Figure 1. Buckling of axially loaded compression members. • The critical ... Effective length for minor (y) axis buckling = Ky Ly = 1.0 x 20 = 20 ft. = 240 in. Step III. ... Column AB has a design factor load Pu = 450 kips
Explanation: