The constant is the number; the variable is the letter.
The question is about an oxymoronic expression. A constant cannot be a variable and a variable cannot be a constant!
Constant variable
The opposite of the word "constant" is "variable".
The constant variable.
The condition for maximum efficiency of a d.c. machine is that VARIABLE LOSSES must be equal to CONSTANT LOSSES i.e., variable losses = constant losses..
The constant is the number; the variable is the letter.
Constant losses Those losses in a d.c. generator which remain constant at all loads are known as constant losses. The constant losses in a d.c. generator are: (a) iron losses (b) mechanical losses (c) shunt field losses
Basically two types: 1. Copper losses:- when the transformer is loaded, current flows in primary and secondary winding, there is loss of electrical energy due to the resistance of the primary winding, and secondary winding and they are called variable losses. These losses depend upon the loading conditions of the transformers. Therefore, these losses are also called as variable losses. 2. Iron losses or core losses:-The losses that occur in the core are known as core losses or iron losses. Two types of iron losses are: > eddy current loss > Hysteresis loss.
The question is about an oxymoronic expression. A constant cannot be a variable and a variable cannot be a constant!
Constant variable
A constant is not a variable at all, and none of its factors was a variable. It is constant.
The opposite of the word "constant" is "variable".
A constant is a variable that does not change. The correct term is constant variable.
Logic fault ---> no such thing as a constant variable (by axiom: def of variable) []
The definition of constant variable is a variable whose value cannot be changed once it has been assigned a value for an experiment. It is the variable held steady, or constant, for a specific experiment.
The factor that is kept constant in an experiment is called the controlled variable. It is important to keep this variable constant to accurately measure the effect of the independent variable on the dependent variable.