vectors and the geometry of space
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10. VECTORS AND THE GEOMETRY OF SPACE. VECTORS AND THE GEOMETRY OF SPACE. 10.2 Vectors. In this section, we will learn about: Vectors and their applications. VECTOR. - PowerPoint PPT PresentationTRANSCRIPT
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VECTORS AND THE GEOMETRY OF SPACE
10
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10.2Vectors
VECTORS AND THE GEOMETRY OF SPACE
In this section, we will learn about:
Vectors and their applications.
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The term vector is used by scientists to
indicate a quantity (such as displacement
or velocity or force) that has both magnitude
and direction.
VECTOR
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A vector is often represented by
an arrow or a directed line segment.
The length of the arrow represents the magnitude of the vector.
The arrow points in the direction of the vector.
REPRESENTING A VECTOR
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We denote a vector by either:
Printing a letter in boldface (v)
Putting an arrow above the letter ( )
DENOTING A VECTOR
v
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For instance, suppose a particle
moves along a line segment from
point A to point B.
VECTORS
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The corresponding displacement vector v
has initial point A (the tail) and terminal point
B (the tip).
We indicate this by writing v = .
VECTORS
AB��������������
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Notice that the vector u = has the same
length and the same direction as v even
though it is in a different position. We say u and v are equivalent (or equal)
and write u = v.
VECTORS
CD��������������
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The zero vector, denoted by 0, has
length 0.
It is the only vector with no specific direction.
ZERO VECTOR
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Suppose a particle moves from A to B.
So, its displacement vector is .
COMBINING VECTORS
AB��������������
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Then, the particle changes direction,
and moves from B to C—with displacement
vector .
COMBINING VECTORS
BC��������������
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The combined effect of these
displacements is that the particle
has moved from A to C.
COMBINING VECTORS
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The resulting displacement vector
is called the sum of and .
We write:
COMBINING VECTORS
AC��������������
AB��������������
BC��������������
AC AB BC ������������������������������������������
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In general, if we start with vectors u and v,
we first move v so that its tail coincides with
the tip of u and define the sum of u and v
as follows.
ADDING VECTORS
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If u and v are vectors positioned so the initial
point of v is at the terminal point of u, then
the sum u + v is the vector from the initial
point of u to the terminal point of v.
VECTOR ADDITION—DEFINITION
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The definition of vector addition is
illustrated here.
VECTOR ADDITION
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You can see why this definition is
sometimes called the Triangle Law.
TRIANGLE LAW
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Here, we start with the same vectors u and v
as earlier and draw another copy of v with
the same initial point as u.
VECTOR ADDITION
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Completing the parallelogram,
we see that:
u + v = v + u
VECTOR ADDITION
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VECTOR ADDITION
This also gives another way to construct
the sum:
If we place u and v so they start at the same point, then u + v lies along the diagonal of the parallelogram with u and v as sides.
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PARALLELOGRAM LAW
This is called the Parallelogram
Law.
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Draw the sum of the vectors a and b
shown here.
VECTOR ADDITION Example 1
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VECTOR ADDITION
First, we translate b and place its tail at the tip
of a—being careful to draw a copy of b that
has the same length and direction.
Example 1
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Then, we draw the vector a + b starting at
the initial point of a and ending at the terminal
point of the copy of b.
VECTOR ADDITION Example 1
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VECTOR ADDITION
Alternatively, we could place b so it starts
where a starts and construct a + b by
the Parallelogram Law.
Example 1
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It is possible to multiply a vector
by a real number c.
MULTIPLYING VECTORS
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In this context, we call the real
number c a scalar—to distinguish
it from a vector.
SCALAR
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For instance, we want 2v to be the same
vector as v + v, which has the same direction
as v but is twice as long.
In general, we multiply a vector by a scalar
as follows.
MULTIPLYING SCALARS
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If c is a scalar and v is a vector, the scalar
multiple cv is:
The vector whose length is |c| times the length
of v and whose direction is the same as v if
c > 0 and is opposite to v if c < 0.
If c = 0 or v = 0, then cv = 0.
SCALAR MULTIPLICATION—DEFINITION
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The definition is illustrated here.
We see that real numbers work like scaling factors here.
That’s why we call them scalars.
SCALAR MULTIPLICATION
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Notice that two nonzero vectors are
parallel if they are scalar multiples of
one another.
SCALAR MULTIPLICATION
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In particular, the vector –v = (–1)v has the
same length as v but points in the opposite
direction.
We call it the negative of v.
SCALAR MULTIPLICATION
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SUBTRACTING VECTORS
By the difference u – v of two vectors,
we mean:
u – v = u + (–v)
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So, we can construct u – v by first drawing
the negative of v, –v, and then adding it to
u by the Parallelogram Law.
SUBTRACTING VECTORS
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Alternatively, since v + (u – v) = u,
the vector u – v, when added to v,
gives u.
SUBTRACTING VECTORS
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So, we could construct u by means of
the Triangle Law.
SUBTRACTING VECTORS
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If a and b are the vectors shown here,
draw a – 2b.
SUBTRACTING VECTORS Example 2
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First, we draw the vector –2b pointing in
the direction opposite to b and twice as long.
Next, we place it with its tail at the tip of a.
SUBTRACTING VECTORS Example 2
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Finally, we use the Triangle Law to
draw a + (–2b).
SUBTRACTING VECTORS Example 2
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COMPONENTS
For some purposes, it’s best to
introduce a coordinate system and
treat vectors algebraically.
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COMPONENTS
Let’s place the initial point of a vector a
at the origin of a rectangular coordinate
system.
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Then, the terminal point of a has coordinates
of the form (a1, a2) or (a1, a2, a3).
This depends on whether our coordinate system is two- or three-dimensional.
COMPONENTS
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COMPONENTS
These coordinates are called
the components of a and we write:
a = ‹a1, a2› or a = ‹a1, a2, a3›
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We use the notation ‹a1, a2› for the ordered
pair that refers to a vector so as not to confuse
it with the ordered pair (a1, a2) that refers to
a point in the plane.
COMPONENTS
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For instance, the vectors shown here are
all equivalent to the vector whose
terminal point is P(3, 2).
3,2OP ��������������
COMPONENTS
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What they have in common is that the terminal
point is reached from the initial point by a
displacement of three units to the right and
two upward.
COMPONENTS
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We can think of all these geometric vectors
as representations of the algebraic vector
a = ‹3, 2›.
COMPONENTS
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POSITION VECTOR
The particular representation from
the origin to the point P(3, 2) is called
the position vector of the point P.
OP��������������
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POSITION VECTOR
In three dimensions, the vector
a = = ‹a1, a2, a3›
is the position vector of the point P(a1, a2, a3).
OP��������������
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COMPONENTS
Let’s consider any other representation
of a, where the initial point is A(x1, y1, z1) and
the terminal point is B(x2, y2, z2).
AB��������������
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COMPONENTS
Then, we must have:
x1 + a1 = x2, y1 + a2 = y2, z1 + a3 = z2
Thus,
a1 = x2 – x1, a2 = y2 – y1, a3 = z2 – z1
Thus, we have the following result.
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COMPONENTS
Given the points A(x1, y1, z1) and B(x2, y2, z2),
the vector a with representation is:
a = ‹x2 – x1, y2 – y1, z2 – z1›
Equation 1
AB��������������
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COMPONENTS
Find the vector represented by the directed
line segment with initial point A(2, –3, 4) and
terminal point B(–2, 1, 1).
By Equation 1, the vector corresponding to is:
a = ‹–2 –2, 1 – (–3), 1 – 4› = ‹–4, 4, –3›
AB��������������
Example 3
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LENGTH OF VECTOR
The magnitude or length of the vector v
is the length of any of its representations.
It is denoted by the symbol |v| or║v║.
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LENGTH OF VECTOR
By using the distance formula to compute
the length of a segment , we obtain
the following formulas.
OP��������������
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LENGTH OF 2-D VECTOR
The length of the two-dimensional (2-D)
vector a = ‹a1, a2› is:
2 21 2| |a a a
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LENGTH OF 3-D VECTOR
The length of the three-dimensional (3-D)
vector a = ‹a1, a2, a3› is:
2 2 21 2 3| |a a a a
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ALGEBRAIC VECTORS
How do we add vectors
algebraically?
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ADDING ALGEBRAIC VECTORS
The figure shows that, if a = ‹a1, a2›
and b = ‹b1, b2›, then the sum is
a + b = ‹a1 + b1, a2 + b2›
at least for the case
where the components
are positive.
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ADDING ALGEBRAIC VECTORS
In other words, to add
algebraic vectors, we add
their components.
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SUBTRACTING ALGEBRAIC VECTORS
Similarly, to subtract vectors,
we subtract components.
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ALGEBRAIC VECTORS
From the similar triangles in the figure,
we see that the components of ca are
ca1 and ca2.
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MULTIPLYING ALGEBRAIC VECTORS
So, to multiply a vector by a scalar,
we multiply each component by that
scalar.
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2-D ALGEBRAIC VECTORS
If a = ‹a1, a2› and b = ‹b1, b2›, then
a + b = ‹a1 + b1, a2 + b2›
a – b = ‹a1 – b1 , a2 – b2›
ca = ‹ca1, ca2›
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3-D ALGEBRAIC VECTORS
Similarly, for 3-D vectors,
1 2 3 1 2 3 1 1 2 2 3 3
1 2 3 1 2 3 1 1 2 2 3 3
1 2 3 1 2 3
, , , , , ,
, , , , , ,
, , , ,
a a a b b b a b a b a b
a a a b b b a b a b a b
c a a a ca ca ca
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ALGEBRAIC VECTORS
If a = ‹4, 0, 3› and b = ‹–2, 1, 5›,
find:
|a| and the vectors a + b, a – b, 3b, 2a + 5b
Example 4
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ALGEBRAIC VECTORS
2 2 24 0 3
= 25
= 5
Example 4
|a|
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ALGEBRAIC VECTORS
+ = 4, 0, 3 + 2, 1, 5
= 4 + ( 2), 0 + 1, 3 + 5
= 2, 1, 8
a bExample 4
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ALGEBRAIC VECTORS
= 4, 0, 3 2, 1, 5
= 4 ( 2), 0 1, 3 5
= 6, 1, 2
a bExample 4
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ALGEBRAIC VECTORS
3 = 3 2, 1, 5
= 3( 2), 3(1), 3(5)
= 6, 3, 15
bExample 4
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ALGEBRAIC VECTORS
2 + 5 = 2 4, 0, 3 5 2, 1, 5
= 8, 0, 6 10, 5, 25
= 2, 5, 31
a bExample 4
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COMPONENTS
We denote:
V2 as the set of all 2-D vectors
V3 as the set of all 3-D vectors
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COMPONENTS
More generally, we will later need to
consider the set Vn of all n-dimensional
vectors.
An n-dimensional vector is an ordered n-tuple
a = ‹a1, a2, …, an›
where a1, a2, …, an are real numbers that are called the components of a.
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COMPONENTS
Addition and scalar multiplication are
defined in terms of components just as
for the cases n = 2 and n = 3.
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PROPERTIES OF VECTORS
If a, b, and c are vectors in Vn and c and d
are scalars, then
1. + = + 2. + ( + ) = ( + ) +
3. + 0 = 4. + ( ) = 0
5. ( + ) = + 6. ( + ) = +
7. ( ) = ( ) 8. 1 =
c c c c d c d
cd c d
a b b a a b c a b c
a a a a
a b a b a a a
a a a a
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PROPERTIES OF VECTORS
These eight properties of vectors can
be readily verified either geometrically or
algebraically.
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PROPERTY 1
For instance, Property 1 can be seen from
this earlier figure.
It’s equivalent to the Parallelogram Law.
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PROPERTY 1
It can also be seen as follows for the case
n = 2:
a + b = ‹a1, a2› + ‹b1, b2›
= ‹a1 + b1, a2 + b2›
= ‹b1 + a1, b2 + a2›
= ‹b1, b2› + ‹a1, a2›
= b + a
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PROPERTY 2
We can see why Property 2 (the associative
law) is true by looking at this figure and
applying the Triangle Law several times, as
follows.
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PROPERTY 2
The vector is obtained either by first
constructing a + b and then adding c or by
adding a to the vector b + c.
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VECTORS IN V3
Three vectors in V3 play
a special role.
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VECTORS IN V3
Let
i = ‹1, 0, 0›
j = ‹0, 1, 0›
k = ‹0, 0, 1›
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STANDARD BASIS VECTORS
These vectors i, j, and k are called
the standard basis vectors.
They have length 1 and point in the directions of the positive x-, y-, and z-axes.
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STANDARD BASIS VECTORS
Similarly, in
two dimensions,
we define:
i = ‹1, 0›
j = ‹0, 1›
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STANDARD BASIS VECTORS
If a = ‹a1, a2, a3›, then we can write:
1 2 3
1 2 3
1 2 3
, ,
,0,0 0, ,0 0,0,
1,0,0 0,1,0 0,0,1
a a a
a a a
a a a
a
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STANDARD BASIS VECTORS Equation 2
1 2 3a a a a i j k
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STANDARD BASIS VECTORS
Thus, any vector in V3
can be expressed in terms
of i, j, and k.
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STANDARD BASIS VECTORS
For instance,
‹1, –2, 6› = i – 2j + 6k
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STANDARD BASIS VECTORS
Similarly, in two dimensions, we can
write:
a = ‹a1, a2› = a1i + a2j
Equation 3
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COMPONENTS
Compare the geometric interpretation
of Equations 2 and 3 with the earlier
figures.
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COMPONENTS
If a = i + 2j – 3k and b = 4i + 7k,
express the vector 2a + 3b in terms
of i, j, and k.
Example 5
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COMPONENTS
Using Properties 1, 2, 5, 6, and 7 of vectors,
we have:
2a + 3b = 2(i + 2j – 3k) + 3(4i + 7k)
= 2i + 4j – 6k + 12i + 21k
= 14i + 4j + 15k
Example 5
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UNIT VECTOR
A unit vector is a vector whose
length is 1.
For instance, i, j, and k are all unit vectors.
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UNIT VECTORS
In general, if a ≠ 0, then the unit vector
that has the same direction as a is:
1| |
| | | |
au a
a a
Equation 4
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UNIT VECTORS
In order to verify this, we let c = 1/|a|.
Then, u = ca and c is a positive scalar; so, u has the same direction as a.
Also, 1| | | | | || | | | 1
| |c c u a a a
a
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UNIT VECTORS
Find the unit vector in
the direction of the vector
2i – j – 2k.
Example 6
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UNIT VECTORS
The given vector has length
So, by Equation 4, the unit vector with the same direction is:
2 2 2| 2 2 | 2 ( 1) ( 2)
9 3
i j k
1 2 1 23 3 3 3(2 2 ) i j k i j k
Example 6
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APPLICATIONS
Vectors are useful in many aspects of
physics and engineering.
In Chapter 13, we will see how they describe the velocity and acceleration of objects moving in space.
Here, we look at forces.
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FORCE
A force is represented by a vector because
it has both a magnitude (measured in pounds
or newtons) and a direction.
If several forces are acting on an object, the resultant force experienced by the object is the vector sum of these forces.
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FORCE
A 100-lb weight hangs from two wires.
Find the tensions (forces) T1 and T2
in both wires and their magnitudes
Example 7
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FORCE
First, we express T1 and T2
in terms of their horizontal and
vertical components.
Example 7
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FORCE
From the figure, we see that:
T1 = –|T1| cos 50° i + |T1| sin 50° j
T2 = |T2| cos 32° i + |T2| sin 32° j
E. g. 7—Eqns. 5 & 6
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FORCE
The resultant T1 + T2 of the tensions
counterbalances the weight w.
So, we must have:
T1 + T2 = –w
= 100 j
Example 7
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FORCE
Thus,
(–|T1| cos 50° + |T2| cos 32°) i
+ (|T1| sin 50° + |T2| sin 32°) j
= 100 j
Example 7
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FORCE
Equating components, we get:
–|T1| cos 50° + |T2| cos 32° = 0
|T1| sin 50° + |T2| sin 32° = 100
Example 7
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FORCE
Solving the first of these equations for |T2|
and substituting into the second,
we get:
11
| | cos50| | sin 50 sin 32 100
cos32
T
T
Example 7
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FORCE
So, the magnitudes of the tensions are:
1
100| | 85.64 lb
sin 50 tan 32 cos50
T
12
| | cos50| | 64.91 lb
cos32
T
T
Example 7
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FORCE
Substituting these values in Equations 5
and 6, we obtain the tension vectors
T1 ≈ –55.05 i + 65.60 j
T2 ≈ 55.05 i + 34.40 j
Example 7