Answer:
Answered below.
Explanation:
A) Both spheroidite & tempered martensite possess sphere - like cementite particles within their microstructure known as a ferrite matrix. However, the difference is that these particles are much larger for spheroidite than tempered.
B) Tempered martensite is much harder and stronger than spheroidite primarily because there is much more ferrite - cementite phase boundary area for its sphere - like cementite particles.
This is because the greater the boundary area, the more the hardness.
Answer:
Q = 125.538 W
Explanation:
Given data:
D = 30 cm
Temperature
degree celcius
![T_S = 220 + 273 = 473 K](https://tex.z-dn.net/?f=T_S%20%3D%20%20220%20%2B%20273%20%3D%20473%20K)
Heat coefficient = 12 W/m^2 K
Efficiency 80% = 0.8
![Q = hA(T_S - T_{\infty}) \eta](https://tex.z-dn.net/?f=Q%20%3D%20hA%28T_S%20-%20T_%7B%5Cinfty%7D%29%20%5Ceta)
![= 12(\frac{\pi}{4} 0.3^2) (473 - 288) 0.8](https://tex.z-dn.net/?f=%3D%2012%28%5Cfrac%7B%5Cpi%7D%7B4%7D%200.3%5E2%29%20%28473%20-%20288%29%200.8)
Q = 125.538 W
Answer:
Explanation: Clutch Plate.
Clutch Cover.
Clutch Bearing (Release bearing)
Release Fork (clutch fork)
Answer:
second-law efficiency = 62.42 %
Explanation:
given data
temperature T1 = 1200°C = 1473 K
temperature T2 = 20°C = 293 K
thermal efficiency η = 50 percent
solution
as we know that thermal efficiency of reversible heat engine between same temp reservoir
so here
efficiency ( reversible ) η1 = 1 -
............1
efficiency ( reversible ) η1 = 1 -
so efficiency ( reversible ) η1 = 0.801
so here second-law efficiency of this power plant is
second-law efficiency =
second-law efficiency =
second-law efficiency = 62.42 %
Answer:
Explanation:
var generator = new Random(1);
// Now the nextGaussian() function returns a normal distribution of random numbers with the following parameters: a mean of zero and a standard deviation of one
var draw = function() {
var num = generator.nextGaussian();
var standardDeviation = 60;
var mean = 2003;
// Multiply by the standard deviation and add the mean.
var x = standardDeviation * num + mean;
noStroke();
fill(214, 159, 214, 10);
ellipse(x, 200, 16, 16); };
Hope this will be helpful