Finding the Unit Vector Orthogonal to a Defined Plane

In summary, you are trying to find the unit vector orthogonal to a plane defined by the points (1,0,0), (0,2,0), and (0,0,3). The method that occurred to you was to find two of the sides of the triangle.
  • #1
teclo
117
0
hello, I'm taking electrodynamics, and to begin we're doing vector algebra/calculus.

here's the problem I'm faced with. there's a triangle defined by the points.

(1,0,0)
(0,2,0)
(0,0,3)

the task at hand is finding the unit vector orthogonal to the defined plane. the method that occurred to me was to find two of the sides of the triange. from there, i could divide the resulting vector by the magnitude (abcos(theta)), giving me n-hat.

in any case, it's been along time since trig, and I'm not sure how i should get the angle theta between the two selected sides. maybe I'm not doing it right, i don't know. any advise would be appreciated!

cheers
 
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  • #2
I can't understand what you're suggesting, but here's a hint for a way to do it.

HINT: Cross product.
 
  • #3
yes, call the x-y line vector a, x-z vector b

a X b = |ab|cos theta n(hat)

n(hat) would equal [aXb]/|ab|cos theta

no?

the question remains on how to get the angle. i can't seem to recall and a friend is borrowing my trig/algebra book.
 
  • #4
Try taking the determinant.

[tex]a\times b=\left|\begin{array}{ccc}i & j & k \\ 1 & -2 & 0 \\ 0 & 2 -& 3\end{array}\right|[/tex]

This will give you one vector orthogonal to the triangle.
 
  • #5
teclo said:
yes, call the x-y line vector a, x-z vector b

a X b = |ab|cos theta n(hat)

n(hat) would equal [aXb]/|ab|cos theta

no?
Almost. The magnitude of a X b is |ab|sin(theta), not cos(theta). But use apmcavoy's way. Get the vector by the determinant "method", and simply calculate its norm with use of "3-D pythagoras".
 
  • #6
For me the easiest way is to find the equation of the plane in the form of

ax + by + cz + d = 0.

It follows that the unit vector n-hat ix (a,b,c)
 
  • #7
thanks, I'm retarded. i had the cross product defined, i just didn't think to make a unit vector out of it. it was pretty trivial dividing my result by 7. thanks again.

cheers
 

Related to Finding the Unit Vector Orthogonal to a Defined Plane

1. What is vector algebra?

Vector algebra is a branch of mathematics that deals with the manipulation and properties of vectors. Vectors are mathematical objects that have both magnitude and direction, and can be represented graphically as arrows.

2. What are the basic operations in vector algebra?

The basic operations in vector algebra include addition, subtraction, scalar multiplication, and vector multiplication. Addition and subtraction involve combining vectors to find a resultant vector, while scalar multiplication involves multiplying a vector by a scalar quantity. Vector multiplication includes dot product and cross product, which are used to find the angle between two vectors and the perpendicular vector to two given vectors, respectively.

3. How is vector algebra used in real life?

Vector algebra has various real-life applications, such as in physics, engineering, and computer graphics. It is used to represent physical quantities like velocity, force, and acceleration, as well as in calculating the direction and magnitude of forces acting on objects. In computer graphics, vector algebra is used to manipulate and transform objects in a 3D space.

4. What are unit vectors in vector algebra?

Unit vectors are vectors with a magnitude of 1 and are used to indicate direction. They are typically denoted by a hat (^) symbol on top of the vector's variable, such as or . Unit vectors are useful in vector algebra as they can be used to represent any vector by multiplying it with its magnitude.

5. Can vectors be added or subtracted if they have different dimensions?

No, vectors with different dimensions cannot be added or subtracted. In vector algebra, all the vectors involved in an operation must have the same number of dimensions. This means that they must have the same number of components (e.g. x, y, z) or the same number of entries in their column or row matrices.

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