Answer:
778.4°C
Explanation:
I = 700
R = 6x10⁻⁴
we first calculate the rate of heat that is being transferred by the current
q = I²R
q = 700²(6x10⁻⁴)
= 490000x0.0006
= 294 W/M
we calculate the surface temperature
Ts = T∞ +
Ts =
The surface temperature is therefore 778.4°C if the cable is bare
Answer:
The solution code is written in Python:
- def convertCSV(number_list):
- str_list = []
- for num in number_list:
- str_list.append(str(num))
-
- return ",".join(str_list)
- result = convertCSV([22,33,44])
- print(result)
Explanation:
Firstly, create a function "convertCSV" with one parameter "number_list". (Line 1)
Next, create an empty list and assign it to a new variable <em>str_list</em>. (Line 2)
Use for-loop to iterate through all the number in the <em>number_list</em>.(Line 4). Within the loop, each number is converted to a string using the Python built-in function <em>str() </em>and then use the list append method to add the string version of the number to <em>str_list</em>.
Use Python string<em> join() </em>method to join all the elements in the str_list as a single string. The "," is used as a separator between the elements (Line 7) . At the end return the string as an output.
We can test the function by calling the function and passing [22,33,34] as an argument and we shall see "22,33,44" is printed as an output. (Line 9 - 10)
Answer:
a)
b)
Explanation:
Previous concepts
The cumulative distribution function (CDF) F(x),"describes the probability that a random variableX with a given probability distribution will be found at a value less than or equal to x".
The exponential distribution is "the probability distribution of the time between events in a Poisson process (a process in which events occur continuously and independently at a constant average rate). It is a particular case of the gamma distribution".
Part a
Let X the random variable of interest. We know on this case that
And we know the probability denisty function for x given by:
In order to find the cdf we need to do the following integral:
Part b
Assuming that , then the density function is given by:
And for this case we want this probability:
And evaluating the integral we got: