Answer:
≅ 111 KN
Explanation:
Given that;
A medium-sized jet has a 3.8-mm-diameter i.e diameter (d) = 3.8
mass = 85,000 kg
drag co-efficient (C) = 0.37
(velocity (v)= 230 m/s
density (ρ) = 1.0 kg/m³
To calculate the thrust; we need to determine the relation of the drag force; which is given as:
= 
× CρAv²
where;
ρ = density of air wind.
C = drag co-efficient
A = Area of the jet
v = velocity of the jet
From the question, we can deduce that the jet is in motion with a constant speed; as such: the net force acting on the jet in the air = 0
SO, 
We can as well say:
We can now replace 
in the above equation.
Therefore, = × CρAv²
The A which stands as the area of the jet is given by the formula:
We can now have a new equation after substituting our A into the previous equation as:
= × Cρ 
Substituting our data from above; we have:
= × 
= 
= 110,990N
in N (newton) to KN (kilo-newton) will be:
= 
= 110.990 KN
≅ 111 KN
In conclusion, the jet engine needed to provide 111 KN thrust in order to cruise at 230 m/s at an altitude where the air density is 1.0 kg/m³.
Answer:
The answer is below
Explanation:
a) The weight of the combined system is the sum of the weight of the water and the weight of the tank
b) Since the weight of a system can be divided into smaller portions, hence weight is an extensive property.
c) When analyzing the acceleration of gases as they flow through a nozzle, the geometry of the nozzle which is an open system can be chosen as our system.
d) Given that:
Answer:
Yes, the flow is turbulent.
Explanation:
Reynolds number gives the nature of flow. If he Reynolds number is less than 2000 then the flow is laminar else turbulent.
Given:
Diameter of pipe is 10mm.
Velocity of the pipe is 1m/s.
Temperature of water is 200°C.
The kinematic viscosity at temperature 200°C is 
m2/s.
Calculation:
Step1
Expression for Reynolds number is given as follows:
Here, v is velocity, 
is kinematic viscosity, d is diameter and Re is Reynolds number.
Substitute the values in the above equation as follows:
Re=64226.07579
Thus, the Reynolds number is 64226.07579. This is greater than 2000.
Hence, the given flow is turbulent flow.
Use protective gear. Use insulated tools, Wear flame resistant clothing, safety glasses, and insulation gloves, Remove watches or other jewelry, Stand on an insulation mat. 03. Never connect the insulation tester to energized conductors or energized equipment and always follow the manufacturer's recommendations. When installing new electrical machinery or equipment, testing insulation resistance is important for two reasons. First, it ensures that the insulation is in adequate condition to begin operation. ... The test is accomplished by applying DC voltage through the de-energized circuit using an insulation tester. Insulation resistance should be approximately one megohm for each 1,000 volts of operating voltage, with a minimum value of one megohm. For example, a motor rated at 2,400 volts should have a minimum insulation resistance of 2.4 megohms.
Features of Multidimensional scaling(MDS) from scratch is described below.
Explanation:
Multidimensional scaling (MDS) is a way to reduce the dimensionality of data to visualize it. We basically want to project our (likely highly dimensional) data into a lower dimensional space and preserve the distances between points.
If we have some highly complex data that we project into some lower N dimensions, we will assign each point from our data a coordinate in this lower dimensional space, and the idea is that these N dimensional coordinates are ordered based on their ability to capture variance in the data. Since we can only visualize things in 2D, this is why it is common to assess your MDS based on plotting the first and second dimension of the output.
If you look at the output of an MDS algorithm, which will be points in 2D or 3D space, the distances represent similarity. So very close points = very similar, and points farther away from one another = less similar.
Working of MDS
The input to the MDS algorithm is our proximity matrix. There are two kinds of classical MDS that we could use: Classical (metric) MDS is for data that has metric properties, like actual distances from a map or calculated from a vector
.Nonmetric MDS is for more ordinal data (such as human-provided similarity ratings) for which we can say a 1 is more similar than a 2, but there is no defined (metric) distance between the values of 1 and 2.
Uses
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a dataset. MDS is used to translate "information about the pairwise 'distances' among a set of n objects or individuals" into a configuration of n points mapped into an abstract Cartesian space.
