A study of a high-pressure inlet fogging method for a gas turbine engine analyzed a complete second-order model for y , heat rate (kilojoules per kilowatt per hour) of a gas turbine as a function of two quantitative variables • x1 , cycle speed (revolutions per minute) • x2 , cycle pressure ratio and a qualitative predictor, engine type, at three levels (traditional, advanced, and aeroderivative).
Minimization
In mathematics, traditional optimization problems are typically expressed in terms of minimization. When we talk about minimizing or maximizing a function, we refer to the maximum and minimum possible values of that function. This can be expressed in terms of global or local range. The definition of minimization in the thesaurus is the process of reducing something to a small amount, value, or position. Minimization (noun) is an instance of belittling or disparagement.
Maxima and Minima
The extreme points of a function are the maximum and the minimum points of the function. A maximum is attained when the function takes the maximum value and a minimum is attained when the function takes the minimum value.
Derivatives
A derivative means a change. Geometrically it can be represented as a line with some steepness. Imagine climbing a mountain which is very steep and 500 meters high. Is it easier to climb? Definitely not! Suppose walking on the road for 500 meters. Which one would be easier? Walking on the road would be much easier than climbing a mountain.
Concavity
In calculus, concavity is a descriptor of mathematics that tells about the shape of the graph. It is the parameter that helps to estimate the maximum and minimum value of any of the functions and the concave nature using the graphical method. We use the first derivative test and second derivative test to understand the concave behavior of the function.
![A study of a high-pressure inlet fogging method for a gas turbine
engine analyzed a complete second-order model for y , heat rate
(kilojoules per kilowatt per hour) of a gas turbine as a function of two
quantitative variables
• x1 , cycle speed (revolutions per minute)
• X2 , cycle pressure ratio
and a qualitative predictor, engine type, at three levels (traditional,
advanced, and aeroderivative).
We define two dummy variables
S 1
0 if not
{
if advanced
1
if aeroderivative
X3 =
and
X4
if not
If the engine type is traditional, then x3 =
and x4
When you plug in these two values in the
complete second-order model equation, you will get the model
equation for traditional engine type.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F9de95467-8766-4670-8442-783f9816c074%2Fa36311c9-0c31-460e-8778-8bd4dd264dd0%2Fah95nff_processed.png&w=3840&q=75)
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