SlideShare a Scribd company logo
1 of 13
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 1
Course: B.Tech- II
Subject: Engineering Mathematics II
Unit-4
RAI UNIVERSITY, AHMEDABAD
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 2
Unit-IV: VECTOR DIFFERENTIATION
Sr. No. Name of the Topic Page No.
1 Scalar and Vector Point Function 2
2 Vector Differential Operator Del 3
3 Gradient of a Scalar Function 3
4 Normal and Directional Derivative 3
5 Divergence of a vector function 6
6 Curl 8
7 Reference Book 12
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 3
VECTOR DIFFERENTIATION
 Introduction:
If vector r is a function of a scalar variable t, then we write
𝑟⃗ = 𝑟⃗(𝑡)
If a particle is moving along a curved path then the position vector 𝑟⃗ of the
particle is a function of 𝑡. If the component of 𝑓(𝑡) along 𝑥 − 𝑎𝑥𝑖𝑠,
𝑦 − 𝑎𝑥𝑖𝑠, 𝑧 − 𝑎𝑥𝑖𝑠 are𝑓1(𝑡), 𝑓2(𝑡), 𝑓3(𝑡) respectively.
Then,
𝑓(𝑡)⃗⃗⃗⃗⃗⃗⃗⃗⃗ = 𝑓1 ( 𝑡) 𝑖̂ + 𝑓2( 𝑡) 𝑗̂ + 𝑓3 ( 𝑡) 𝑘̂
1.1 Scalarand Vector Point Function :
Point function: A variable quantity whose value at any point in a region of
spacedepends upon the position of the point, is called a point function.
There are two types of point functions.
1) Scalarpoint function:
If to each point 𝑃(𝑥, 𝑦, 𝑧) of a region 𝑅 in spacethere corresponds a
unique scalar 𝑓(𝑃) , then 𝑓 is called a scalar point function.
For example:
The temperature distribution in a heated body, density of a bodyand
potential due to gravity are the examples of a scalar point function.
2) Vector point function:
If to each point 𝑃(𝑥, 𝑦, 𝑧) of a region 𝑅 in spacethere corresponds a
unique vector 𝑓(𝑃) , then 𝑓 is called a vector point function.
For example:
The velocities of a moving fluid, gravitational force are the examples
of vector point function.
2.1 VectorDifferential Operator Del 𝒊. 𝒆. 𝛁
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 4
The vector differential operator Del is denoted by 𝛁. It is defined as
𝛁 = 𝒊̂
𝝏
𝝏𝒙
+ 𝒋̂
𝝏
𝝏𝒚
+ 𝒌̂
𝝏
𝝏𝒛
Note: 𝛁 is read Del or nebla.
3.1 Gradient of a ScalarFunction:
If ∅(𝑥, 𝑦, 𝑧) be a scalar function then 𝑖̂
𝜕∅
𝜕𝑥
+ 𝑗̂
𝜕∅
𝜕𝑦
+ 𝑘̂ 𝜕∅
𝜕𝑧
is called the gradient
of the scalar function ∅.
And is denoted by grad ∅.
Thus, grad ∅ = 𝒊̂
𝝏∅
𝝏𝒙
+ 𝒋̂
𝝏∅
𝝏𝒚
+ 𝒌̂ 𝝏∅
𝝏𝒛
grad ∅ = (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
) ∅(𝑥, 𝑦, 𝑧)
grad ∅ = 𝛁 ∅
4.1 Normal and DirectionalDerivative:
1) Normal:
If ∅( 𝑥, 𝑦, 𝑧) = 𝑐 represents a family of surfaces for different values of
the constant 𝑐. On differentiating ∅, we get 𝑑∅ = 0
But 𝑑∅ = ∇ ∅ . 𝑑𝑟⃗
So ∇∅. 𝑑𝑟 = 0
The scalar productof two vectors ∇∅ and 𝑑𝑟⃗ being zero, ∇ ∅ and 𝑑𝑟⃗
are perpendicular to each other. 𝑑𝑟⃗ is in the direction of tangent to the
giving surface.
Thus ∇∅ is a vector normal to the surface ∅( 𝑥, 𝑦, 𝑧) = 𝑐.
2) Directionalderivative:
The componentof ∇∅ in the direction of a vector 𝑑⃗ is equal to ∇∅. 𝑑⃗
and is called the directional derivative of ∅ in the direction of 𝑑⃗.
𝜕∅
𝜕𝑟
= lim
𝛿𝑟→0
𝛿∅
𝛿𝑟
Where, 𝛿𝑟 = 𝑃𝑄
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 5
𝜕∅
𝜕𝑟
is called the directional derivative of ∅ at 𝑃 in the direction of 𝑃𝑄.
4.2 Examples:
Example 1: If ∅ = 3𝑥2
𝑦 − 𝑦3
𝑧2
; find grad ∅ at the point (1,-2, 1).
Solution:
grad ∅ = ∇∅
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
)(3𝑥2
𝑦 − 𝑦3
𝑧2
)
= 𝑖̂
𝜕
𝜕𝑥
(3𝑥2
𝑦 − 𝑦3
𝑧2) + 𝑗̂
𝜕
𝜕𝑦
(3𝑥2
𝑦 − 𝑦3
𝑧2) + 𝑘̂ 𝜕
𝜕𝑧
(3𝑥2
𝑦 − 𝑦3
𝑧2
)
= 𝑖̂(6𝑥𝑦) + 𝑗̂(3𝑥2
− 3𝑦2
𝑧2)+ 𝑘̂(−2𝑦3
𝑧)
grad ∅ at (1,−2,1)
= 𝑖̂(6)(1)(−2) + 𝑗̂[(3)(1) − 3(4)(1)] + 𝑘̂(−2)(−8)(−1)
= −12𝑖̂ − 9𝑗̂ − 16𝑘̂
Example 2: Find the directional derivative of 𝑥2
𝑦2
𝑧2
at the point (1,−1,1)
in the direction of the tangent to the curve
𝑥 = 𝑒 𝑡
, 𝑦 = sin 2𝑡 + 1, 𝑧 = 1 − 𝑐𝑜𝑠𝑡 𝑎𝑡 𝑡 = 0.
Solution: Let ∅ = 𝑥2
𝑦2
𝑧2
Direction Derivative of ∅ = ∇∅
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
)( 𝑥2
𝑦2
𝑧2)
∇∅ = 2𝑥𝑦2
𝑧2
𝑖̂ + 2𝑦𝑥2
𝑧2
𝑗̂ + 2𝑧𝑥2
𝑦2
𝑘̂
Directional Derivative of ∅ at (1,1,-1)
= 2(1)(1)2
(−1)2
𝑖̂ + 2(1)(1)2
(−1)2
𝑗̂ + 2(−1)(1)2(1)2
𝑘̂
= 2𝑖̂ + 2𝑗̂ − 2𝑘̂ _________ (1)
𝑟⃗ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂ = 𝑒 𝑡
𝑖̂ + ( 𝑠𝑖𝑛2𝑡 + 1) 𝑗̂ + (1 − 𝑐𝑜𝑠𝑡)𝑘̂
𝑇⃗⃗ =
𝑑𝑟⃗
𝑑𝑡
= 𝑒 𝑡
𝑖̂ + 2 𝑐𝑜𝑠2𝑡 𝑗̂ + 𝑠𝑖𝑛𝑡 𝑘̂
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 6
Tangent vector,
Tangent ( 𝑎𝑡 𝑡 = 0) = 𝑒0
𝑖̂ + 2 (cos0) 𝑗̂ + (𝑠𝑖𝑛0)𝑘̂
= 𝑖̂ + 2𝑗̂ __________ (2)
Required directional derivative along tangent = (2 𝑖̂ + 2𝑗̂ − 2𝑘̂)
(𝑖̂+2𝑗̂)
√1+4
[ 𝑓𝑟𝑜𝑚 (1) 𝑎𝑛𝑑 (2)]
=
2+4+0
√5
=
6
√5
_______Ans.
Example 3: Verify ∇̅ × [ 𝑓(𝑟)𝑟⃗] = 0
Solution:
∇̅ × [ 𝑓(𝑟)𝑟⃗] = [𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
] × [ 𝑓(𝑟)𝑟⃗]
= [𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
] × 𝑓( 𝑟)(𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂)
= [𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
] × [𝑓( 𝑟) 𝑥𝑖̂ + 𝑓( 𝑟) 𝑦𝑗̂ + 𝑓( 𝑟) 𝑧𝑘̂]
= |
𝑖̂ 𝑗̂ 𝑘̂
𝜕
𝜕𝑥
𝜕
𝜕𝑦
𝜕
𝜕𝑧
𝑓( 𝑟) 𝑥 𝑓( 𝑟) 𝑦 𝑓( 𝑟) 𝑧
|
= [𝑧
𝜕𝑓(𝑟)
𝜕𝑦
− 𝑦
𝜕
𝜕𝑧
𝑓(𝑟)] 𝑖̂ − [𝑧
𝜕
𝜕𝑥
𝑓( 𝑟) − 𝑥
𝜕
𝜕𝑧
𝑓(𝑟)] 𝑗̂ + [𝑦
𝜕
𝜕𝑥
𝑓( 𝑟) − 𝑥
𝜕
𝜕𝑦
𝑓(𝑟)] 𝑘̂
= [𝑧
𝑑
𝑑𝑟
𝑓( 𝑟)
𝜕𝑟
𝜕𝑦
− 𝑦
𝑑
𝑑𝑟
𝑓( 𝑟)
𝜕𝑟
𝜕𝑧
] 𝑖̂ − [𝑧
𝑑
𝑑𝑟
𝑓( 𝑟)
𝜕𝑟
𝜕𝑥
− 𝑥
𝑑
𝑑𝑟
𝑓( 𝑟)
𝜕𝑟
𝜕𝑧
] 𝑗̂ + [𝑦
𝑑
𝑑𝑟
𝑓( 𝑟)
𝜕𝑟
𝜕𝑥
−
𝑥
𝑑
𝑑𝑟
𝑓( 𝑟)
𝜕𝑟
𝜕𝑦
] 𝑘̂
=
𝑓′( 𝑟)
𝑟
[( 𝑦𝑧− 𝑦𝑧) 𝑖̂ − ( 𝑥𝑧 − 𝑥𝑧) 𝑗̂ + (𝑥𝑦 − 𝑥𝑦)𝑘̂] = 0 ____ Proved.
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 7
4.3 Exercise:
1) Find a unit vector normal to the surface 𝑥2
+ 3𝑦2
+ 2𝑧2
=
6 𝑎𝑡 𝑃(2,0,1).
2) Find the direction derivative of
1
𝑟
in the direction 𝑟⃗ where
𝑟⃗⃗⃗ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂.
3) If 𝑟⃗⃗⃗ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂, show that
a) grad 𝑟 =
𝑟⃗⃗⃗
𝑟
b) grad (
1
𝑟
) = −
𝑟⃗⃗⃗
𝑟3
4) Find the rate of change of ∅ = 𝑥𝑦𝑧 in the direction normal to the
surface 𝑥2
𝑦 + 𝑦2
𝑥 + 𝑦𝑧2
= 3 at the point (1, 1, 1).
5.1 DIVERGENCE OF A VECTOR FUNCTION:
The divergence of a vector point function 𝐹⃗ is denoted by div 𝐹 and is
defined as below.
Let 𝐹⃗ = 𝐹1 𝑖̂ + 𝐹2 𝑗̂ + 𝐹3 𝑘̂
div 𝐹⃗ = ∇⃗⃗⃗. 𝐹⃗ = (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
)(𝑖̂ 𝐹1 + 𝑗̂ 𝐹2 + 𝑘̂ 𝐹3)
=
𝜕𝐹1
𝜕𝑥
+
𝜕𝐹2
𝜕𝑦
+
𝜕𝐹3
𝜕𝑧
It is evident that div 𝐹 is scalar function.
Note:If the fluid is compressible, there can be no gain or loss in the volume
element. Hence
div 𝑽̅ = 𝟎
Here, V is called a Solenoidal vector function. And this equation is called
equation of continuity or conservation of mass.
Example 1: If 𝑢 = 𝑥2
+ 𝑦2
+ 𝑧2
, 𝑎𝑛𝑑 𝑟̅ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂, then find div (𝑢𝑟̅)
in terms of u.
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 8
Solution: div ( 𝑢𝑟̅) = (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
)[( 𝑥2
+ 𝑦2
+ 𝑧2)(𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂)]
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
). [( 𝑥2
+ 𝑦2
+ 𝑧2) 𝑥𝑖̂ + ( 𝑥2
+ 𝑦2
+ 𝑧2) 𝑦𝑗̂ +
( 𝑥2
+ 𝑦2
+ 𝑧2) 𝑧𝑘̂]
=
𝜕
𝜕𝑥
( 𝑥3
+ 𝑥𝑦2
+ 𝑥𝑧2) +
𝜕
𝜕𝑦
( 𝑥2
𝑦 + 𝑦3
+ 𝑦𝑧2) +
𝜕
𝜕𝑧
( 𝑥2
𝑧 + 𝑦2
𝑧+ 𝑧3)
= (3𝑥2
+ 𝑦2
+ 𝑧2) + ( 𝑥2
+ 3𝑦2
+ 𝑧2) + ( 𝑥2
+ 𝑦2
+ 3𝑧2)
= 5( 𝑥2
+ 𝑦2
+ 𝑧2)
= 5𝑢 ___________Ans.
Example 2: Find the directional derivative of the divergence of 𝑓̅( 𝑥, 𝑦, 𝑧) =
𝑥𝑦𝑖̂ + 𝑥𝑦2
𝑗̂ + 𝑧2
𝑘̂ at the point (2, 1, 2) in the direction of the outer normal to
the sphere 𝑥2
+ 𝑦2
+ 𝑧2
= 9.
Solution: 𝑓̅( 𝑥, 𝑦, 𝑧) = 𝑥𝑦𝑖̂ + 𝑥𝑦2
𝑗̂ + 𝑧2
𝑘̂
Divergence of 𝑓̅( 𝑥, 𝑦, 𝑧) = ∇.̅ 𝑓̅ = (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
). (𝑥𝑦𝑖̂ + 𝑥𝑦2
𝑗̂ + 𝑧2
𝑘̂)
= 𝑦 + 2𝑥𝑦 + 2𝑧
Directional derivative of divergence of (𝑦 + 2𝑥𝑦 + 2𝑧)
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
)(𝑦 + 2𝑥𝑦 + 2𝑧)
= 2𝑦𝑖̂ + (1 + 2𝑥) 𝑗̂ + 2𝑘̂ __________(i)
Directional derivative at the point (2,1,2) = 2𝑖̂ + 5𝑗̂ + 2𝑘̂
Normal to the sphere = (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
)( 𝑥2
+ 𝑦2
+ 𝑧2
− 9)
= 2𝑥𝑖̂ + 2𝑦𝑗̂ + 2𝑧𝑘̂
Normal at the point (2,1,2) = 4𝑖̂ + 2𝑗̂ + 4𝑘̂ __________(ii)
Directional derivative along normal at (2,1,2) = (2𝑖̂ + 5𝑗̂ + 2𝑘̂).
(4𝑖̂+2𝑗̂+4𝑘̂)
√16+4+16
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 9
[ 𝐹𝑟𝑜𝑚 ( 𝑖),(𝑖𝑖)]
=
1
6
(8 + 10 + 8)
=
13
3
____________Ans.
5.2 Exercise:
1) If 𝑣̅ =
𝑥𝑖̂+ 𝑦𝑗̂+ 𝑧𝑘̂
√𝑥2+𝑦2+𝑧2
, find the value of div 𝑣̅.
2) Find the directional derivative of div (𝑢⃗⃗) at the point (1, 2, 2) in the
direction of the outer normal of the sphere 𝑥2
+ 𝑦2
+ 𝑧2
= 9 for 𝑢⃗⃗ =
𝑥4
𝑖̂ + 𝑦4
𝑗̂ + 𝑧4
𝑘̂.
6.1 CURL:
The curl of a vector point function 𝐹 is defined as below
Curl 𝐹̅ = ∇̅ × 𝐹̅ (𝐹̅ = 𝐹1 𝑖̂ + 𝐹2 𝑗̂ +
𝐹3 𝑘̂)
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
) × 𝐹1 𝑖̂ + 𝐹2 𝑗̂ + 𝐹3 𝑘̂
= |
𝑖̂ 𝑗̂ 𝑘̂
𝜕
𝜕𝑥
𝜕
𝜕𝑦
𝜕
𝜕𝑧
𝐹1 𝐹2 𝐹3
|
= 𝑖̂ (
𝜕𝐹3
𝜕𝑦
−
𝜕𝐹2
𝜕𝑧
) − 𝑗̂ (
𝜕𝐹3
𝜕𝑥
−
𝜕𝐹1
𝜕𝑧
)+ 𝑘̂ (
𝜕𝐹2
𝜕𝑥
−
𝜕𝐹1
𝜕𝑦
)
Curl 𝐹̅ is a vector quantity.
Note:Curl 𝑭̅ = 𝟎, the field 𝐹 is termed as irrotational.
Example 1: Find the divergence and curl of
𝑣̅ = ( 𝑥𝑦𝑧) 𝑖̂ + (3𝑥2
𝑦) 𝑗̂ + ( 𝑥𝑧2
− 𝑦2
𝑧) 𝑘̂ 𝑎𝑡 (2,−1,1)
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 10
Solution: Here, we have
𝑣̅ = ( 𝑥𝑦𝑧) 𝑖̂ + (3𝑥2
𝑦) 𝑗̂ + ( 𝑥𝑧2
− 𝑦2
𝑧) 𝑘̂
Div 𝑣̅ = ∇∅
Div 𝑣̅ =
𝜕
𝜕𝑥
( 𝑥𝑦𝑧) +
𝜕
𝜕𝑦
(3𝑥2
𝑦) +
𝜕
𝜕𝑧
( 𝑥𝑧2
− 𝑦2
𝑧)
= 𝑦𝑧 + 3𝑥2
+ 2𝑥𝑧 − 𝑦2
𝑣̅(2,−1,1) = −1 + 12+ 4 − 1 = 14
Curl 𝑣̅ = |
𝑖̂ 𝑗̂ 𝑘̂
𝜕
𝜕𝑥
𝜕
𝜕𝑦
𝜕
𝜕𝑧
𝑥𝑦𝑧 3𝑥2
𝑦 𝑥𝑧2
− 𝑦2
𝑧
|
= −2𝑦𝑧𝑖̂ − ( 𝑧2
− 𝑥𝑦) 𝑗̂ + (6𝑥𝑦 − 𝑥𝑧) 𝑘̂
= −2𝑦𝑧𝑖̂ + ( 𝑥𝑦 − 𝑧2) 𝑗̂ + (6𝑥𝑦 − 𝑥𝑧) 𝑘̂
Curl at (2, -1, 1)
= 2(−1)(1)𝑖̂ + {2(−1) − 1} 𝑗̂ + {6(2)(−1) − 2(1)} 𝑘̂
= 2𝑖̂ − 3𝑗̂ − 14𝑘̂ __________Ans.
Example 2: Prove that
( 𝑦2
− 𝑧2
+ 3𝑦𝑧 − 2𝑥)𝑖̂ + (3𝑥𝑦 + 2𝑥𝑦) 𝑗̂ + (3𝑥𝑦 − 2𝑥𝑧 + 2𝑧)𝑘̂ is both
Solenoidal and irrotational.
Solution:
Let 𝐹̅ = ( 𝑦2
− 𝑧2
+ 3𝑦𝑧 − 2𝑥)𝑖̂ + (3𝑥𝑦 + 2𝑥𝑦) 𝑗̂ + (3𝑥𝑦 − 2𝑥𝑧+ 2𝑧)𝑘̂
For Solenoidal, we have to prove ∇.̅ 𝐹̅ = 0.
Now,
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 11
∇.̅ 𝐹̅ = [𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
] . [( 𝑦2
− 𝑧2
+ 3𝑦𝑧 − 2𝑥) 𝑖̂ + (3𝑥𝑦 + 2𝑥𝑦) 𝑗̂ +
(3𝑥𝑦 − 2𝑥𝑧 + 2𝑧)𝑘̂]
= −2 + 2𝑥 − 2𝑥 + 2
= 0
Thus, 𝐹̅ is Solenoidal.
For irrotational, we have to prove Curl 𝐹̅ = 0
Now, Curl 𝐹̅ =
|
𝑖̂ 𝑗̂ 𝑘̂
𝜕
𝜕𝑥
𝜕
𝜕𝑦
𝜕
𝜕𝑧
( 𝑦2
− 𝑧2
+ 3𝑦𝑧− 2𝑥) (3𝑥𝑦 + 2𝑥𝑦) (3𝑥𝑦 − 2𝑥𝑧 + 2𝑧)
|
= (3𝑧+ 2𝑦 − 2𝑦 + 3𝑧) 𝑖̂ − (−2𝑧+ 3𝑦 − 3𝑦 + 2𝑧) 𝑗̂ + (3𝑧+ 2𝑦 − 2𝑦 − 3𝑧)𝑘̂
= 0𝑖̂ + 0𝑗̂ + 0𝑘̂
= 0
Thus, 𝐹̅ is irrotational.
Hence, 𝐹̅ is both Solenoidal and irrotational. __________ Proved.
Example 3: Find the scalar potential (velocity potential) function 𝑓 for 𝐴⃗ =
𝑦2
𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2
𝑘̂.
Solution: We have, 𝐴⃗ = 𝑦2
𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2
𝑘̂.
Curl 𝐴⃗ = ∇ × 𝐴⃗
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
) × (𝑦2
𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2
𝑘̂).
= |
𝑖̂ 𝑗̂ 𝑘̂
𝜕
𝜕𝑥
𝜕
𝜕𝑦
𝜕
𝜕𝑧
𝑦2
2𝑥𝑦 −𝑧2
|
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 12
= 𝑖̂(0) − 𝑗̂(0) + 𝑘̂(2𝑦 − 2𝑦)
= 0
Hence, 𝐴⃗ is irrotational.
To find the scalar potential function 𝑓.
𝐴⃗ = ∇ 𝑓
𝑑𝑓 =
𝜕𝑓
𝜕𝑥
𝑑𝑥 +
𝜕𝑓
𝜕𝑦
𝑑𝑦 +
𝜕𝑓
𝜕𝑧
𝑑𝑧
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
). (𝑖̂ 𝑑 𝑥 + 𝑗̂ 𝑑 𝑦 + 𝑘̂ 𝑑𝑧)
= (𝑖̂
𝜕
𝜕𝑥
+ 𝑗̂
𝜕
𝜕𝑦
+ 𝑘̂ 𝜕
𝜕𝑧
) 𝑓. 𝑑𝑟⃗
= ∇𝑓. 𝑑𝑟⃗
= 𝐴⃗. 𝑑𝑟⃗ (𝐴 = ∇ 𝑓)
= (𝑦2
𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2
𝑘̂).(𝑖̂ 𝑑 𝑥 + 𝑗̂ 𝑑 𝑦 + 𝑘̂ 𝑑𝑧)
= 𝑦2
𝑑𝑥 + 2𝑥𝑦 𝑑𝑦 − 𝑧2
𝑑𝑧
= 𝑑( 𝑥𝑦2) − 𝑧2
𝑑𝑧
𝑓 = ∫ 𝑑( 𝑥𝑦2) − ∫ 𝑧2
𝑑𝑧
∴ 𝑓 = 𝑥𝑦2
−
𝑧3
3
+ 𝑐 ________ Ans.
6.2 Exercise:
1) If a vector field is given by 𝐹⃗ = ( 𝑥2
− 𝑦2
+ 𝑥) 𝑖̂ − (2𝑥𝑦 + 𝑦)𝑗̂. Is this
field irrotational? If so, find its scalar potential.
Unit-4 VECTOR DIFFERENTIATION
RAI UNIVERSITY, AHMEDABAD 13
2) Determine the constants a and b such that the curl of vector 𝐴̅ =
(2𝑥𝑦 + 3𝑦𝑧) 𝑖̂ + ( 𝑥2
+ 𝑎𝑥𝑧 − 4𝑧2) 𝑗̂ − (3𝑥𝑦 + 𝑏𝑦𝑧)𝑘̂ is zero.
3) A fluid motion is given by𝑣̅ = ( 𝑦 + 𝑧) 𝑖̂ + ( 𝑧 + 𝑥) 𝑗̂ + (𝑥 + 𝑦)𝑘̂. Show
that the motion is irrotational and hence find the velocity potential.
4) Given that vector field 𝑉̅ = ( 𝑥2
− 𝑦2
+ 2𝑥𝑧) 𝑖̂ + ( 𝑥𝑧 − 𝑥𝑦 + 𝑦𝑧) 𝑗̂ +
(𝑧2
+ 𝑥2
)𝑘̂ find curl 𝑉. Show that the vectors given by curl 𝑉 at
𝑃0(1,2,−3) 𝑎𝑛𝑑 𝑃1 (2,3,12) are orthogonal.
5) Supposethat 𝑈⃗⃗⃗, 𝑉⃗⃗ and 𝑓 are continuously differentiable fields then
Prove that, div(𝑈⃗⃗⃗ × 𝑉⃗⃗) = 𝑉⃗⃗. 𝑐𝑢𝑟𝑙 𝑈⃗⃗⃗ − 𝑈⃗⃗⃗. 𝑐𝑢𝑟𝑙 𝑉⃗⃗.
7.1 REFERECE BOOKS:
1) Introduction to Engineering Mathematics
By H. K. DASS. & Dr. RAMA VERMA
S. CHAND
2) Higher Engineering Mathematics
By B.V. RAMANA
Mc Graw Hill Education
3) Higher Engineering Mathematics
By Dr. B.S. GREWAL
KHANNA PUBLISHERS
4) http://elearning.vtu.ac.in/P7/enotes/MAT1/Vector.pdf

More Related Content

What's hot

Methods of variation of parameters- advance engineering mathe mathematics
Methods of variation of parameters- advance engineering mathe mathematicsMethods of variation of parameters- advance engineering mathe mathematics
Methods of variation of parameters- advance engineering mathe mathematicsKaushal Patel
 
Wigner-Ville Distribution: In Perspective of Fault Diagnosis
Wigner-Ville Distribution:  In Perspective of Fault DiagnosisWigner-Ville Distribution:  In Perspective of Fault Diagnosis
Wigner-Ville Distribution: In Perspective of Fault DiagnosisJungho Park
 
Btech_II_ engineering mathematics_unit5
Btech_II_ engineering mathematics_unit5Btech_II_ engineering mathematics_unit5
Btech_II_ engineering mathematics_unit5Rai University
 
Section 10: Lagrange's Theorem
Section 10: Lagrange's TheoremSection 10: Lagrange's Theorem
Section 10: Lagrange's TheoremKevin Johnson
 
Gauss Forward And Backward Central Difference Interpolation Formula
 Gauss Forward And Backward Central Difference Interpolation Formula  Gauss Forward And Backward Central Difference Interpolation Formula
Gauss Forward And Backward Central Difference Interpolation Formula Deep Dalsania
 
Interpolation In Numerical Methods.
 Interpolation In Numerical Methods. Interpolation In Numerical Methods.
Interpolation In Numerical Methods.Abu Kaisar
 
Exact & non differential equation
Exact & non differential equationExact & non differential equation
Exact & non differential equationSiddhi Shrivas
 
Study Material Numerical Differentiation and Integration
Study Material Numerical Differentiation and IntegrationStudy Material Numerical Differentiation and Integration
Study Material Numerical Differentiation and IntegrationMeenakshisundaram N
 
GATE Engineering Maths : Vector Calculus
GATE Engineering Maths : Vector CalculusGATE Engineering Maths : Vector Calculus
GATE Engineering Maths : Vector CalculusParthDave57
 
Direct and inverse variations
Direct and inverse variationsDirect and inverse variations
Direct and inverse variationsAnmol Pant
 
Numerical Methods: curve fitting and interpolation
Numerical Methods: curve fitting and interpolationNumerical Methods: curve fitting and interpolation
Numerical Methods: curve fitting and interpolationNikolai Priezjev
 
Interpolation with unequal interval
Interpolation with unequal intervalInterpolation with unequal interval
Interpolation with unequal intervalDr. Nirav Vyas
 
Gate mathematics questions all branch by s k mondal
Gate mathematics questions all branch by s k mondalGate mathematics questions all branch by s k mondal
Gate mathematics questions all branch by s k mondalAashishv
 

What's hot (20)

Methods of variation of parameters- advance engineering mathe mathematics
Methods of variation of parameters- advance engineering mathe mathematicsMethods of variation of parameters- advance engineering mathe mathematics
Methods of variation of parameters- advance engineering mathe mathematics
 
Wigner-Ville Distribution: In Perspective of Fault Diagnosis
Wigner-Ville Distribution:  In Perspective of Fault DiagnosisWigner-Ville Distribution:  In Perspective of Fault Diagnosis
Wigner-Ville Distribution: In Perspective of Fault Diagnosis
 
Btech_II_ engineering mathematics_unit5
Btech_II_ engineering mathematics_unit5Btech_II_ engineering mathematics_unit5
Btech_II_ engineering mathematics_unit5
 
Section 10: Lagrange's Theorem
Section 10: Lagrange's TheoremSection 10: Lagrange's Theorem
Section 10: Lagrange's Theorem
 
Gauss Forward And Backward Central Difference Interpolation Formula
 Gauss Forward And Backward Central Difference Interpolation Formula  Gauss Forward And Backward Central Difference Interpolation Formula
Gauss Forward And Backward Central Difference Interpolation Formula
 
taylors theorem
taylors theoremtaylors theorem
taylors theorem
 
B.Tech-II_Unit-V
B.Tech-II_Unit-VB.Tech-II_Unit-V
B.Tech-II_Unit-V
 
Numerical analysis ppt
Numerical analysis pptNumerical analysis ppt
Numerical analysis ppt
 
Rolles theorem
Rolles theoremRolles theorem
Rolles theorem
 
Interpolation In Numerical Methods.
 Interpolation In Numerical Methods. Interpolation In Numerical Methods.
Interpolation In Numerical Methods.
 
Exact & non differential equation
Exact & non differential equationExact & non differential equation
Exact & non differential equation
 
Inverse laplace transforms
Inverse laplace transformsInverse laplace transforms
Inverse laplace transforms
 
Study Material Numerical Differentiation and Integration
Study Material Numerical Differentiation and IntegrationStudy Material Numerical Differentiation and Integration
Study Material Numerical Differentiation and Integration
 
Interpolation
InterpolationInterpolation
Interpolation
 
GATE Engineering Maths : Vector Calculus
GATE Engineering Maths : Vector CalculusGATE Engineering Maths : Vector Calculus
GATE Engineering Maths : Vector Calculus
 
Direct and inverse variations
Direct and inverse variationsDirect and inverse variations
Direct and inverse variations
 
APPLICATION OF INTEGRATION
APPLICATION OF INTEGRATIONAPPLICATION OF INTEGRATION
APPLICATION OF INTEGRATION
 
Numerical Methods: curve fitting and interpolation
Numerical Methods: curve fitting and interpolationNumerical Methods: curve fitting and interpolation
Numerical Methods: curve fitting and interpolation
 
Interpolation with unequal interval
Interpolation with unequal intervalInterpolation with unequal interval
Interpolation with unequal interval
 
Gate mathematics questions all branch by s k mondal
Gate mathematics questions all branch by s k mondalGate mathematics questions all branch by s k mondal
Gate mathematics questions all branch by s k mondal
 

Viewers also liked

BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICSRai University
 
BSC_Computer Science_Discrete Mathematics_Unit-I
BSC_Computer Science_Discrete Mathematics_Unit-IBSC_Computer Science_Discrete Mathematics_Unit-I
BSC_Computer Science_Discrete Mathematics_Unit-IRai University
 
B.Tech-II_Unit-III
B.Tech-II_Unit-IIIB.Tech-II_Unit-III
B.Tech-II_Unit-IIIKundan Kumar
 
BCA_Semester-II-Discrete Mathematics_unit-iv Graph theory
BCA_Semester-II-Discrete Mathematics_unit-iv Graph theoryBCA_Semester-II-Discrete Mathematics_unit-iv Graph theory
BCA_Semester-II-Discrete Mathematics_unit-iv Graph theoryRai University
 
Btech_II_ engineering mathematics_unit2
Btech_II_ engineering mathematics_unit2Btech_II_ engineering mathematics_unit2
Btech_II_ engineering mathematics_unit2Rai University
 
BSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICSRai University
 
BSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICSRai University
 
BSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICSRai University
 
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICSRai University
 
BCA_Semester-II-Discrete Mathematics_unit-ii_Relation and ordering
BCA_Semester-II-Discrete Mathematics_unit-ii_Relation and orderingBCA_Semester-II-Discrete Mathematics_unit-ii_Relation and ordering
BCA_Semester-II-Discrete Mathematics_unit-ii_Relation and orderingRai University
 
MCA_UNIT-4_Computer Oriented Numerical Statistical Methods
MCA_UNIT-4_Computer Oriented Numerical Statistical MethodsMCA_UNIT-4_Computer Oriented Numerical Statistical Methods
MCA_UNIT-4_Computer Oriented Numerical Statistical MethodsRai University
 
BSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICSRai University
 
MCA_UNIT-2_Computer Oriented Numerical Statistical Methods
MCA_UNIT-2_Computer Oriented Numerical Statistical MethodsMCA_UNIT-2_Computer Oriented Numerical Statistical Methods
MCA_UNIT-2_Computer Oriented Numerical Statistical MethodsRai University
 
Diploma_Basic_Mathematics_Unit-III
Diploma_Basic_Mathematics_Unit-IIIDiploma_Basic_Mathematics_Unit-III
Diploma_Basic_Mathematics_Unit-IIIRai University
 
B.tech ii unit-1 material curve tracing
B.tech ii unit-1 material curve tracingB.tech ii unit-1 material curve tracing
B.tech ii unit-1 material curve tracingRai University
 

Viewers also liked (20)

BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
 
BSC_Computer Science_Discrete Mathematics_Unit-I
BSC_Computer Science_Discrete Mathematics_Unit-IBSC_Computer Science_Discrete Mathematics_Unit-I
BSC_Computer Science_Discrete Mathematics_Unit-I
 
B.Tech-II_Unit-IV
B.Tech-II_Unit-IVB.Tech-II_Unit-IV
B.Tech-II_Unit-IV
 
B.Tech-II_Unit-I
B.Tech-II_Unit-IB.Tech-II_Unit-I
B.Tech-II_Unit-I
 
merged_document
merged_documentmerged_document
merged_document
 
B.Tech-II_Unit-III
B.Tech-II_Unit-IIIB.Tech-II_Unit-III
B.Tech-II_Unit-III
 
BCA_Semester-II-Discrete Mathematics_unit-iv Graph theory
BCA_Semester-II-Discrete Mathematics_unit-iv Graph theoryBCA_Semester-II-Discrete Mathematics_unit-iv Graph theory
BCA_Semester-II-Discrete Mathematics_unit-iv Graph theory
 
Unit 1 Introduction
Unit 1 IntroductionUnit 1 Introduction
Unit 1 Introduction
 
Btech_II_ engineering mathematics_unit2
Btech_II_ engineering mathematics_unit2Btech_II_ engineering mathematics_unit2
Btech_II_ engineering mathematics_unit2
 
BSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-4_DISCRETE MATHEMATICS
 
BSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-3_DISCRETE MATHEMATICS
 
BSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-1_DISCRETE MATHEMATICS
 
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-5_DISCRETE MATHEMATICS
 
BCA_Semester-II-Discrete Mathematics_unit-ii_Relation and ordering
BCA_Semester-II-Discrete Mathematics_unit-ii_Relation and orderingBCA_Semester-II-Discrete Mathematics_unit-ii_Relation and ordering
BCA_Semester-II-Discrete Mathematics_unit-ii_Relation and ordering
 
MCA_UNIT-4_Computer Oriented Numerical Statistical Methods
MCA_UNIT-4_Computer Oriented Numerical Statistical MethodsMCA_UNIT-4_Computer Oriented Numerical Statistical Methods
MCA_UNIT-4_Computer Oriented Numerical Statistical Methods
 
BSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICSBSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICS
BSC_COMPUTER _SCIENCE_UNIT-2_DISCRETE MATHEMATICS
 
MCA_UNIT-2_Computer Oriented Numerical Statistical Methods
MCA_UNIT-2_Computer Oriented Numerical Statistical MethodsMCA_UNIT-2_Computer Oriented Numerical Statistical Methods
MCA_UNIT-2_Computer Oriented Numerical Statistical Methods
 
Course pack unit 5
Course pack unit 5Course pack unit 5
Course pack unit 5
 
Diploma_Basic_Mathematics_Unit-III
Diploma_Basic_Mathematics_Unit-IIIDiploma_Basic_Mathematics_Unit-III
Diploma_Basic_Mathematics_Unit-III
 
B.tech ii unit-1 material curve tracing
B.tech ii unit-1 material curve tracingB.tech ii unit-1 material curve tracing
B.tech ii unit-1 material curve tracing
 

Similar to Vector Differentiation Guide

Application of Integration
Application of IntegrationApplication of Integration
Application of IntegrationRaymundo Raymund
 
Complex differentiation contains analytic function.pptx
Complex differentiation contains analytic function.pptxComplex differentiation contains analytic function.pptx
Complex differentiation contains analytic function.pptxjyotidighole2
 
graphs of quadratic function grade 9.pptx
graphs of quadratic function grade 9.pptxgraphs of quadratic function grade 9.pptx
graphs of quadratic function grade 9.pptxMeryAnnMAlday
 
Differential Calculus- differentiation
Differential Calculus- differentiationDifferential Calculus- differentiation
Differential Calculus- differentiationSanthanam Krishnan
 
Differential Geometry for Machine Learning
Differential Geometry for Machine LearningDifferential Geometry for Machine Learning
Differential Geometry for Machine LearningSEMINARGROOT
 
Semana 24 funciones iv álgebra uni ccesa007
Semana 24 funciones iv álgebra uni ccesa007Semana 24 funciones iv álgebra uni ccesa007
Semana 24 funciones iv álgebra uni ccesa007Demetrio Ccesa Rayme
 
Change variablethm
Change variablethmChange variablethm
Change variablethmJasonleav
 
Very brief highlights on some key details 2
Very brief highlights on some key details 2Very brief highlights on some key details 2
Very brief highlights on some key details 2foxtrot jp R
 
3 capitulo-iii-matriz-asociada-sem-14-t-l-d
3 capitulo-iii-matriz-asociada-sem-14-t-l-d3 capitulo-iii-matriz-asociada-sem-14-t-l-d
3 capitulo-iii-matriz-asociada-sem-14-t-l-dFernandoDanielMamani1
 
Engineering Analysis -Third Class.ppsx
Engineering Analysis -Third Class.ppsxEngineering Analysis -Third Class.ppsx
Engineering Analysis -Third Class.ppsxHebaEng
 
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric Space
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceSome Common Fixed Point Results for Expansive Mappings in a Cone Metric Space
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceIOSR Journals
 
Lesson 3: Problem Set 4
Lesson 3: Problem Set 4Lesson 3: Problem Set 4
Lesson 3: Problem Set 4Kevin Johnson
 
Dual Spaces of Generalized Cesaro Sequence Space and Related Matrix Mapping
Dual Spaces of Generalized Cesaro Sequence Space and Related Matrix MappingDual Spaces of Generalized Cesaro Sequence Space and Related Matrix Mapping
Dual Spaces of Generalized Cesaro Sequence Space and Related Matrix Mappinginventionjournals
 
Functions of severable variables
Functions of severable variablesFunctions of severable variables
Functions of severable variablesSanthanam Krishnan
 

Similar to Vector Differentiation Guide (20)

Application of Integration
Application of IntegrationApplication of Integration
Application of Integration
 
Basic calculus (ii) recap
Basic calculus (ii) recapBasic calculus (ii) recap
Basic calculus (ii) recap
 
Complex differentiation contains analytic function.pptx
Complex differentiation contains analytic function.pptxComplex differentiation contains analytic function.pptx
Complex differentiation contains analytic function.pptx
 
PRODUCT RULES
PRODUCT RULESPRODUCT RULES
PRODUCT RULES
 
graphs of quadratic function grade 9.pptx
graphs of quadratic function grade 9.pptxgraphs of quadratic function grade 9.pptx
graphs of quadratic function grade 9.pptx
 
Differential Calculus- differentiation
Differential Calculus- differentiationDifferential Calculus- differentiation
Differential Calculus- differentiation
 
Z transforms
Z transformsZ transforms
Z transforms
 
Differential Geometry for Machine Learning
Differential Geometry for Machine LearningDifferential Geometry for Machine Learning
Differential Geometry for Machine Learning
 
Fismat chapter 4
Fismat chapter 4Fismat chapter 4
Fismat chapter 4
 
Semana 24 funciones iv álgebra uni ccesa007
Semana 24 funciones iv álgebra uni ccesa007Semana 24 funciones iv álgebra uni ccesa007
Semana 24 funciones iv álgebra uni ccesa007
 
Week_3-Circle.pptx
Week_3-Circle.pptxWeek_3-Circle.pptx
Week_3-Circle.pptx
 
Change variablethm
Change variablethmChange variablethm
Change variablethm
 
Very brief highlights on some key details 2
Very brief highlights on some key details 2Very brief highlights on some key details 2
Very brief highlights on some key details 2
 
3 capitulo-iii-matriz-asociada-sem-14-t-l-d
3 capitulo-iii-matriz-asociada-sem-14-t-l-d3 capitulo-iii-matriz-asociada-sem-14-t-l-d
3 capitulo-iii-matriz-asociada-sem-14-t-l-d
 
Engineering Analysis -Third Class.ppsx
Engineering Analysis -Third Class.ppsxEngineering Analysis -Third Class.ppsx
Engineering Analysis -Third Class.ppsx
 
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric Space
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric SpaceSome Common Fixed Point Results for Expansive Mappings in a Cone Metric Space
Some Common Fixed Point Results for Expansive Mappings in a Cone Metric Space
 
A05330107
A05330107A05330107
A05330107
 
Lesson 3: Problem Set 4
Lesson 3: Problem Set 4Lesson 3: Problem Set 4
Lesson 3: Problem Set 4
 
Dual Spaces of Generalized Cesaro Sequence Space and Related Matrix Mapping
Dual Spaces of Generalized Cesaro Sequence Space and Related Matrix MappingDual Spaces of Generalized Cesaro Sequence Space and Related Matrix Mapping
Dual Spaces of Generalized Cesaro Sequence Space and Related Matrix Mapping
 
Functions of severable variables
Functions of severable variablesFunctions of severable variables
Functions of severable variables
 

More from Rai University

Brochure Rai University
Brochure Rai University Brochure Rai University
Brochure Rai University Rai University
 
Bdft ii, tmt, unit-iii, dyeing & types of dyeing,
Bdft ii, tmt, unit-iii,  dyeing & types of dyeing,Bdft ii, tmt, unit-iii,  dyeing & types of dyeing,
Bdft ii, tmt, unit-iii, dyeing & types of dyeing,Rai University
 
Bsc agri 2 pae u-4.4 publicrevenue-presentation-130208082149-phpapp02
Bsc agri  2 pae  u-4.4 publicrevenue-presentation-130208082149-phpapp02Bsc agri  2 pae  u-4.4 publicrevenue-presentation-130208082149-phpapp02
Bsc agri 2 pae u-4.4 publicrevenue-presentation-130208082149-phpapp02Rai University
 
Bsc agri 2 pae u-4.3 public expenditure
Bsc agri  2 pae  u-4.3 public expenditureBsc agri  2 pae  u-4.3 public expenditure
Bsc agri 2 pae u-4.3 public expenditureRai University
 
Bsc agri 2 pae u-4.2 public finance
Bsc agri  2 pae  u-4.2 public financeBsc agri  2 pae  u-4.2 public finance
Bsc agri 2 pae u-4.2 public financeRai University
 
Bsc agri 2 pae u-4.1 introduction
Bsc agri  2 pae  u-4.1 introductionBsc agri  2 pae  u-4.1 introduction
Bsc agri 2 pae u-4.1 introductionRai University
 
Bsc agri 2 pae u-3.3 inflation
Bsc agri  2 pae  u-3.3  inflationBsc agri  2 pae  u-3.3  inflation
Bsc agri 2 pae u-3.3 inflationRai University
 
Bsc agri 2 pae u-3.2 introduction to macro economics
Bsc agri  2 pae  u-3.2 introduction to macro economicsBsc agri  2 pae  u-3.2 introduction to macro economics
Bsc agri 2 pae u-3.2 introduction to macro economicsRai University
 
Bsc agri 2 pae u-3.1 marketstructure
Bsc agri  2 pae  u-3.1 marketstructureBsc agri  2 pae  u-3.1 marketstructure
Bsc agri 2 pae u-3.1 marketstructureRai University
 
Bsc agri 2 pae u-3 perfect-competition
Bsc agri  2 pae  u-3 perfect-competitionBsc agri  2 pae  u-3 perfect-competition
Bsc agri 2 pae u-3 perfect-competitionRai University
 

More from Rai University (20)

Brochure Rai University
Brochure Rai University Brochure Rai University
Brochure Rai University
 
Mm unit 4point2
Mm unit 4point2Mm unit 4point2
Mm unit 4point2
 
Mm unit 4point1
Mm unit 4point1Mm unit 4point1
Mm unit 4point1
 
Mm unit 4point3
Mm unit 4point3Mm unit 4point3
Mm unit 4point3
 
Mm unit 3point2
Mm unit 3point2Mm unit 3point2
Mm unit 3point2
 
Mm unit 3point1
Mm unit 3point1Mm unit 3point1
Mm unit 3point1
 
Mm unit 2point2
Mm unit 2point2Mm unit 2point2
Mm unit 2point2
 
Mm unit 2 point 1
Mm unit 2 point 1Mm unit 2 point 1
Mm unit 2 point 1
 
Mm unit 1point3
Mm unit 1point3Mm unit 1point3
Mm unit 1point3
 
Mm unit 1point2
Mm unit 1point2Mm unit 1point2
Mm unit 1point2
 
Mm unit 1point1
Mm unit 1point1Mm unit 1point1
Mm unit 1point1
 
Bdft ii, tmt, unit-iii, dyeing & types of dyeing,
Bdft ii, tmt, unit-iii,  dyeing & types of dyeing,Bdft ii, tmt, unit-iii,  dyeing & types of dyeing,
Bdft ii, tmt, unit-iii, dyeing & types of dyeing,
 
Bsc agri 2 pae u-4.4 publicrevenue-presentation-130208082149-phpapp02
Bsc agri  2 pae  u-4.4 publicrevenue-presentation-130208082149-phpapp02Bsc agri  2 pae  u-4.4 publicrevenue-presentation-130208082149-phpapp02
Bsc agri 2 pae u-4.4 publicrevenue-presentation-130208082149-phpapp02
 
Bsc agri 2 pae u-4.3 public expenditure
Bsc agri  2 pae  u-4.3 public expenditureBsc agri  2 pae  u-4.3 public expenditure
Bsc agri 2 pae u-4.3 public expenditure
 
Bsc agri 2 pae u-4.2 public finance
Bsc agri  2 pae  u-4.2 public financeBsc agri  2 pae  u-4.2 public finance
Bsc agri 2 pae u-4.2 public finance
 
Bsc agri 2 pae u-4.1 introduction
Bsc agri  2 pae  u-4.1 introductionBsc agri  2 pae  u-4.1 introduction
Bsc agri 2 pae u-4.1 introduction
 
Bsc agri 2 pae u-3.3 inflation
Bsc agri  2 pae  u-3.3  inflationBsc agri  2 pae  u-3.3  inflation
Bsc agri 2 pae u-3.3 inflation
 
Bsc agri 2 pae u-3.2 introduction to macro economics
Bsc agri  2 pae  u-3.2 introduction to macro economicsBsc agri  2 pae  u-3.2 introduction to macro economics
Bsc agri 2 pae u-3.2 introduction to macro economics
 
Bsc agri 2 pae u-3.1 marketstructure
Bsc agri  2 pae  u-3.1 marketstructureBsc agri  2 pae  u-3.1 marketstructure
Bsc agri 2 pae u-3.1 marketstructure
 
Bsc agri 2 pae u-3 perfect-competition
Bsc agri  2 pae  u-3 perfect-competitionBsc agri  2 pae  u-3 perfect-competition
Bsc agri 2 pae u-3 perfect-competition
 

Recently uploaded

Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxRoyAbrique
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Educationpboyjonauth
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeThiyagu K
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxpboyjonauth
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesFatimaKhan178732
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationnomboosow
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991RKavithamani
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxSayali Powar
 

Recently uploaded (20)

Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdfTataKelola dan KamSiber Kecerdasan Buatan v022.pdf
TataKelola dan KamSiber Kecerdasan Buatan v022.pdf
 
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptxContemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
Contemporary philippine arts from the regions_PPT_Module_12 [Autosaved] (1).pptx
 
Introduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher EducationIntroduction to ArtificiaI Intelligence in Higher Education
Introduction to ArtificiaI Intelligence in Higher Education
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
Measures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and ModeMeasures of Central Tendency: Mean, Median and Mode
Measures of Central Tendency: Mean, Median and Mode
 
Introduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptxIntroduction to AI in Higher Education_draft.pptx
Introduction to AI in Higher Education_draft.pptx
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
Separation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and ActinidesSeparation of Lanthanides/ Lanthanides and Actinides
Separation of Lanthanides/ Lanthanides and Actinides
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
Interactive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communicationInteractive Powerpoint_How to Master effective communication
Interactive Powerpoint_How to Master effective communication
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
Industrial Policy - 1948, 1956, 1973, 1977, 1980, 1991
 
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptxPOINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
POINT- BIOCHEMISTRY SEM 2 ENZYMES UNIT 5.pptx
 
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
Mattingly "AI & Prompt Design: Structured Data, Assistants, & RAG"
 

Vector Differentiation Guide

  • 1. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 1 Course: B.Tech- II Subject: Engineering Mathematics II Unit-4 RAI UNIVERSITY, AHMEDABAD
  • 2. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 2 Unit-IV: VECTOR DIFFERENTIATION Sr. No. Name of the Topic Page No. 1 Scalar and Vector Point Function 2 2 Vector Differential Operator Del 3 3 Gradient of a Scalar Function 3 4 Normal and Directional Derivative 3 5 Divergence of a vector function 6 6 Curl 8 7 Reference Book 12
  • 3. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 3 VECTOR DIFFERENTIATION  Introduction: If vector r is a function of a scalar variable t, then we write 𝑟⃗ = 𝑟⃗(𝑡) If a particle is moving along a curved path then the position vector 𝑟⃗ of the particle is a function of 𝑡. If the component of 𝑓(𝑡) along 𝑥 − 𝑎𝑥𝑖𝑠, 𝑦 − 𝑎𝑥𝑖𝑠, 𝑧 − 𝑎𝑥𝑖𝑠 are𝑓1(𝑡), 𝑓2(𝑡), 𝑓3(𝑡) respectively. Then, 𝑓(𝑡)⃗⃗⃗⃗⃗⃗⃗⃗⃗ = 𝑓1 ( 𝑡) 𝑖̂ + 𝑓2( 𝑡) 𝑗̂ + 𝑓3 ( 𝑡) 𝑘̂ 1.1 Scalarand Vector Point Function : Point function: A variable quantity whose value at any point in a region of spacedepends upon the position of the point, is called a point function. There are two types of point functions. 1) Scalarpoint function: If to each point 𝑃(𝑥, 𝑦, 𝑧) of a region 𝑅 in spacethere corresponds a unique scalar 𝑓(𝑃) , then 𝑓 is called a scalar point function. For example: The temperature distribution in a heated body, density of a bodyand potential due to gravity are the examples of a scalar point function. 2) Vector point function: If to each point 𝑃(𝑥, 𝑦, 𝑧) of a region 𝑅 in spacethere corresponds a unique vector 𝑓(𝑃) , then 𝑓 is called a vector point function. For example: The velocities of a moving fluid, gravitational force are the examples of vector point function. 2.1 VectorDifferential Operator Del 𝒊. 𝒆. 𝛁
  • 4. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 4 The vector differential operator Del is denoted by 𝛁. It is defined as 𝛁 = 𝒊̂ 𝝏 𝝏𝒙 + 𝒋̂ 𝝏 𝝏𝒚 + 𝒌̂ 𝝏 𝝏𝒛 Note: 𝛁 is read Del or nebla. 3.1 Gradient of a ScalarFunction: If ∅(𝑥, 𝑦, 𝑧) be a scalar function then 𝑖̂ 𝜕∅ 𝜕𝑥 + 𝑗̂ 𝜕∅ 𝜕𝑦 + 𝑘̂ 𝜕∅ 𝜕𝑧 is called the gradient of the scalar function ∅. And is denoted by grad ∅. Thus, grad ∅ = 𝒊̂ 𝝏∅ 𝝏𝒙 + 𝒋̂ 𝝏∅ 𝝏𝒚 + 𝒌̂ 𝝏∅ 𝝏𝒛 grad ∅ = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ) ∅(𝑥, 𝑦, 𝑧) grad ∅ = 𝛁 ∅ 4.1 Normal and DirectionalDerivative: 1) Normal: If ∅( 𝑥, 𝑦, 𝑧) = 𝑐 represents a family of surfaces for different values of the constant 𝑐. On differentiating ∅, we get 𝑑∅ = 0 But 𝑑∅ = ∇ ∅ . 𝑑𝑟⃗ So ∇∅. 𝑑𝑟 = 0 The scalar productof two vectors ∇∅ and 𝑑𝑟⃗ being zero, ∇ ∅ and 𝑑𝑟⃗ are perpendicular to each other. 𝑑𝑟⃗ is in the direction of tangent to the giving surface. Thus ∇∅ is a vector normal to the surface ∅( 𝑥, 𝑦, 𝑧) = 𝑐. 2) Directionalderivative: The componentof ∇∅ in the direction of a vector 𝑑⃗ is equal to ∇∅. 𝑑⃗ and is called the directional derivative of ∅ in the direction of 𝑑⃗. 𝜕∅ 𝜕𝑟 = lim 𝛿𝑟→0 𝛿∅ 𝛿𝑟 Where, 𝛿𝑟 = 𝑃𝑄
  • 5. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 5 𝜕∅ 𝜕𝑟 is called the directional derivative of ∅ at 𝑃 in the direction of 𝑃𝑄. 4.2 Examples: Example 1: If ∅ = 3𝑥2 𝑦 − 𝑦3 𝑧2 ; find grad ∅ at the point (1,-2, 1). Solution: grad ∅ = ∇∅ = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 )(3𝑥2 𝑦 − 𝑦3 𝑧2 ) = 𝑖̂ 𝜕 𝜕𝑥 (3𝑥2 𝑦 − 𝑦3 𝑧2) + 𝑗̂ 𝜕 𝜕𝑦 (3𝑥2 𝑦 − 𝑦3 𝑧2) + 𝑘̂ 𝜕 𝜕𝑧 (3𝑥2 𝑦 − 𝑦3 𝑧2 ) = 𝑖̂(6𝑥𝑦) + 𝑗̂(3𝑥2 − 3𝑦2 𝑧2)+ 𝑘̂(−2𝑦3 𝑧) grad ∅ at (1,−2,1) = 𝑖̂(6)(1)(−2) + 𝑗̂[(3)(1) − 3(4)(1)] + 𝑘̂(−2)(−8)(−1) = −12𝑖̂ − 9𝑗̂ − 16𝑘̂ Example 2: Find the directional derivative of 𝑥2 𝑦2 𝑧2 at the point (1,−1,1) in the direction of the tangent to the curve 𝑥 = 𝑒 𝑡 , 𝑦 = sin 2𝑡 + 1, 𝑧 = 1 − 𝑐𝑜𝑠𝑡 𝑎𝑡 𝑡 = 0. Solution: Let ∅ = 𝑥2 𝑦2 𝑧2 Direction Derivative of ∅ = ∇∅ = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 )( 𝑥2 𝑦2 𝑧2) ∇∅ = 2𝑥𝑦2 𝑧2 𝑖̂ + 2𝑦𝑥2 𝑧2 𝑗̂ + 2𝑧𝑥2 𝑦2 𝑘̂ Directional Derivative of ∅ at (1,1,-1) = 2(1)(1)2 (−1)2 𝑖̂ + 2(1)(1)2 (−1)2 𝑗̂ + 2(−1)(1)2(1)2 𝑘̂ = 2𝑖̂ + 2𝑗̂ − 2𝑘̂ _________ (1) 𝑟⃗ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂ = 𝑒 𝑡 𝑖̂ + ( 𝑠𝑖𝑛2𝑡 + 1) 𝑗̂ + (1 − 𝑐𝑜𝑠𝑡)𝑘̂ 𝑇⃗⃗ = 𝑑𝑟⃗ 𝑑𝑡 = 𝑒 𝑡 𝑖̂ + 2 𝑐𝑜𝑠2𝑡 𝑗̂ + 𝑠𝑖𝑛𝑡 𝑘̂
  • 6. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 6 Tangent vector, Tangent ( 𝑎𝑡 𝑡 = 0) = 𝑒0 𝑖̂ + 2 (cos0) 𝑗̂ + (𝑠𝑖𝑛0)𝑘̂ = 𝑖̂ + 2𝑗̂ __________ (2) Required directional derivative along tangent = (2 𝑖̂ + 2𝑗̂ − 2𝑘̂) (𝑖̂+2𝑗̂) √1+4 [ 𝑓𝑟𝑜𝑚 (1) 𝑎𝑛𝑑 (2)] = 2+4+0 √5 = 6 √5 _______Ans. Example 3: Verify ∇̅ × [ 𝑓(𝑟)𝑟⃗] = 0 Solution: ∇̅ × [ 𝑓(𝑟)𝑟⃗] = [𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ] × [ 𝑓(𝑟)𝑟⃗] = [𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ] × 𝑓( 𝑟)(𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂) = [𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ] × [𝑓( 𝑟) 𝑥𝑖̂ + 𝑓( 𝑟) 𝑦𝑗̂ + 𝑓( 𝑟) 𝑧𝑘̂] = | 𝑖̂ 𝑗̂ 𝑘̂ 𝜕 𝜕𝑥 𝜕 𝜕𝑦 𝜕 𝜕𝑧 𝑓( 𝑟) 𝑥 𝑓( 𝑟) 𝑦 𝑓( 𝑟) 𝑧 | = [𝑧 𝜕𝑓(𝑟) 𝜕𝑦 − 𝑦 𝜕 𝜕𝑧 𝑓(𝑟)] 𝑖̂ − [𝑧 𝜕 𝜕𝑥 𝑓( 𝑟) − 𝑥 𝜕 𝜕𝑧 𝑓(𝑟)] 𝑗̂ + [𝑦 𝜕 𝜕𝑥 𝑓( 𝑟) − 𝑥 𝜕 𝜕𝑦 𝑓(𝑟)] 𝑘̂ = [𝑧 𝑑 𝑑𝑟 𝑓( 𝑟) 𝜕𝑟 𝜕𝑦 − 𝑦 𝑑 𝑑𝑟 𝑓( 𝑟) 𝜕𝑟 𝜕𝑧 ] 𝑖̂ − [𝑧 𝑑 𝑑𝑟 𝑓( 𝑟) 𝜕𝑟 𝜕𝑥 − 𝑥 𝑑 𝑑𝑟 𝑓( 𝑟) 𝜕𝑟 𝜕𝑧 ] 𝑗̂ + [𝑦 𝑑 𝑑𝑟 𝑓( 𝑟) 𝜕𝑟 𝜕𝑥 − 𝑥 𝑑 𝑑𝑟 𝑓( 𝑟) 𝜕𝑟 𝜕𝑦 ] 𝑘̂ = 𝑓′( 𝑟) 𝑟 [( 𝑦𝑧− 𝑦𝑧) 𝑖̂ − ( 𝑥𝑧 − 𝑥𝑧) 𝑗̂ + (𝑥𝑦 − 𝑥𝑦)𝑘̂] = 0 ____ Proved.
  • 7. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 7 4.3 Exercise: 1) Find a unit vector normal to the surface 𝑥2 + 3𝑦2 + 2𝑧2 = 6 𝑎𝑡 𝑃(2,0,1). 2) Find the direction derivative of 1 𝑟 in the direction 𝑟⃗ where 𝑟⃗⃗⃗ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂. 3) If 𝑟⃗⃗⃗ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂, show that a) grad 𝑟 = 𝑟⃗⃗⃗ 𝑟 b) grad ( 1 𝑟 ) = − 𝑟⃗⃗⃗ 𝑟3 4) Find the rate of change of ∅ = 𝑥𝑦𝑧 in the direction normal to the surface 𝑥2 𝑦 + 𝑦2 𝑥 + 𝑦𝑧2 = 3 at the point (1, 1, 1). 5.1 DIVERGENCE OF A VECTOR FUNCTION: The divergence of a vector point function 𝐹⃗ is denoted by div 𝐹 and is defined as below. Let 𝐹⃗ = 𝐹1 𝑖̂ + 𝐹2 𝑗̂ + 𝐹3 𝑘̂ div 𝐹⃗ = ∇⃗⃗⃗. 𝐹⃗ = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 )(𝑖̂ 𝐹1 + 𝑗̂ 𝐹2 + 𝑘̂ 𝐹3) = 𝜕𝐹1 𝜕𝑥 + 𝜕𝐹2 𝜕𝑦 + 𝜕𝐹3 𝜕𝑧 It is evident that div 𝐹 is scalar function. Note:If the fluid is compressible, there can be no gain or loss in the volume element. Hence div 𝑽̅ = 𝟎 Here, V is called a Solenoidal vector function. And this equation is called equation of continuity or conservation of mass. Example 1: If 𝑢 = 𝑥2 + 𝑦2 + 𝑧2 , 𝑎𝑛𝑑 𝑟̅ = 𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂, then find div (𝑢𝑟̅) in terms of u.
  • 8. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 8 Solution: div ( 𝑢𝑟̅) = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 )[( 𝑥2 + 𝑦2 + 𝑧2)(𝑥𝑖̂ + 𝑦𝑗̂ + 𝑧𝑘̂)] = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ). [( 𝑥2 + 𝑦2 + 𝑧2) 𝑥𝑖̂ + ( 𝑥2 + 𝑦2 + 𝑧2) 𝑦𝑗̂ + ( 𝑥2 + 𝑦2 + 𝑧2) 𝑧𝑘̂] = 𝜕 𝜕𝑥 ( 𝑥3 + 𝑥𝑦2 + 𝑥𝑧2) + 𝜕 𝜕𝑦 ( 𝑥2 𝑦 + 𝑦3 + 𝑦𝑧2) + 𝜕 𝜕𝑧 ( 𝑥2 𝑧 + 𝑦2 𝑧+ 𝑧3) = (3𝑥2 + 𝑦2 + 𝑧2) + ( 𝑥2 + 3𝑦2 + 𝑧2) + ( 𝑥2 + 𝑦2 + 3𝑧2) = 5( 𝑥2 + 𝑦2 + 𝑧2) = 5𝑢 ___________Ans. Example 2: Find the directional derivative of the divergence of 𝑓̅( 𝑥, 𝑦, 𝑧) = 𝑥𝑦𝑖̂ + 𝑥𝑦2 𝑗̂ + 𝑧2 𝑘̂ at the point (2, 1, 2) in the direction of the outer normal to the sphere 𝑥2 + 𝑦2 + 𝑧2 = 9. Solution: 𝑓̅( 𝑥, 𝑦, 𝑧) = 𝑥𝑦𝑖̂ + 𝑥𝑦2 𝑗̂ + 𝑧2 𝑘̂ Divergence of 𝑓̅( 𝑥, 𝑦, 𝑧) = ∇.̅ 𝑓̅ = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ). (𝑥𝑦𝑖̂ + 𝑥𝑦2 𝑗̂ + 𝑧2 𝑘̂) = 𝑦 + 2𝑥𝑦 + 2𝑧 Directional derivative of divergence of (𝑦 + 2𝑥𝑦 + 2𝑧) = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 )(𝑦 + 2𝑥𝑦 + 2𝑧) = 2𝑦𝑖̂ + (1 + 2𝑥) 𝑗̂ + 2𝑘̂ __________(i) Directional derivative at the point (2,1,2) = 2𝑖̂ + 5𝑗̂ + 2𝑘̂ Normal to the sphere = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 )( 𝑥2 + 𝑦2 + 𝑧2 − 9) = 2𝑥𝑖̂ + 2𝑦𝑗̂ + 2𝑧𝑘̂ Normal at the point (2,1,2) = 4𝑖̂ + 2𝑗̂ + 4𝑘̂ __________(ii) Directional derivative along normal at (2,1,2) = (2𝑖̂ + 5𝑗̂ + 2𝑘̂). (4𝑖̂+2𝑗̂+4𝑘̂) √16+4+16
  • 9. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 9 [ 𝐹𝑟𝑜𝑚 ( 𝑖),(𝑖𝑖)] = 1 6 (8 + 10 + 8) = 13 3 ____________Ans. 5.2 Exercise: 1) If 𝑣̅ = 𝑥𝑖̂+ 𝑦𝑗̂+ 𝑧𝑘̂ √𝑥2+𝑦2+𝑧2 , find the value of div 𝑣̅. 2) Find the directional derivative of div (𝑢⃗⃗) at the point (1, 2, 2) in the direction of the outer normal of the sphere 𝑥2 + 𝑦2 + 𝑧2 = 9 for 𝑢⃗⃗ = 𝑥4 𝑖̂ + 𝑦4 𝑗̂ + 𝑧4 𝑘̂. 6.1 CURL: The curl of a vector point function 𝐹 is defined as below Curl 𝐹̅ = ∇̅ × 𝐹̅ (𝐹̅ = 𝐹1 𝑖̂ + 𝐹2 𝑗̂ + 𝐹3 𝑘̂) = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ) × 𝐹1 𝑖̂ + 𝐹2 𝑗̂ + 𝐹3 𝑘̂ = | 𝑖̂ 𝑗̂ 𝑘̂ 𝜕 𝜕𝑥 𝜕 𝜕𝑦 𝜕 𝜕𝑧 𝐹1 𝐹2 𝐹3 | = 𝑖̂ ( 𝜕𝐹3 𝜕𝑦 − 𝜕𝐹2 𝜕𝑧 ) − 𝑗̂ ( 𝜕𝐹3 𝜕𝑥 − 𝜕𝐹1 𝜕𝑧 )+ 𝑘̂ ( 𝜕𝐹2 𝜕𝑥 − 𝜕𝐹1 𝜕𝑦 ) Curl 𝐹̅ is a vector quantity. Note:Curl 𝑭̅ = 𝟎, the field 𝐹 is termed as irrotational. Example 1: Find the divergence and curl of 𝑣̅ = ( 𝑥𝑦𝑧) 𝑖̂ + (3𝑥2 𝑦) 𝑗̂ + ( 𝑥𝑧2 − 𝑦2 𝑧) 𝑘̂ 𝑎𝑡 (2,−1,1)
  • 10. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 10 Solution: Here, we have 𝑣̅ = ( 𝑥𝑦𝑧) 𝑖̂ + (3𝑥2 𝑦) 𝑗̂ + ( 𝑥𝑧2 − 𝑦2 𝑧) 𝑘̂ Div 𝑣̅ = ∇∅ Div 𝑣̅ = 𝜕 𝜕𝑥 ( 𝑥𝑦𝑧) + 𝜕 𝜕𝑦 (3𝑥2 𝑦) + 𝜕 𝜕𝑧 ( 𝑥𝑧2 − 𝑦2 𝑧) = 𝑦𝑧 + 3𝑥2 + 2𝑥𝑧 − 𝑦2 𝑣̅(2,−1,1) = −1 + 12+ 4 − 1 = 14 Curl 𝑣̅ = | 𝑖̂ 𝑗̂ 𝑘̂ 𝜕 𝜕𝑥 𝜕 𝜕𝑦 𝜕 𝜕𝑧 𝑥𝑦𝑧 3𝑥2 𝑦 𝑥𝑧2 − 𝑦2 𝑧 | = −2𝑦𝑧𝑖̂ − ( 𝑧2 − 𝑥𝑦) 𝑗̂ + (6𝑥𝑦 − 𝑥𝑧) 𝑘̂ = −2𝑦𝑧𝑖̂ + ( 𝑥𝑦 − 𝑧2) 𝑗̂ + (6𝑥𝑦 − 𝑥𝑧) 𝑘̂ Curl at (2, -1, 1) = 2(−1)(1)𝑖̂ + {2(−1) − 1} 𝑗̂ + {6(2)(−1) − 2(1)} 𝑘̂ = 2𝑖̂ − 3𝑗̂ − 14𝑘̂ __________Ans. Example 2: Prove that ( 𝑦2 − 𝑧2 + 3𝑦𝑧 − 2𝑥)𝑖̂ + (3𝑥𝑦 + 2𝑥𝑦) 𝑗̂ + (3𝑥𝑦 − 2𝑥𝑧 + 2𝑧)𝑘̂ is both Solenoidal and irrotational. Solution: Let 𝐹̅ = ( 𝑦2 − 𝑧2 + 3𝑦𝑧 − 2𝑥)𝑖̂ + (3𝑥𝑦 + 2𝑥𝑦) 𝑗̂ + (3𝑥𝑦 − 2𝑥𝑧+ 2𝑧)𝑘̂ For Solenoidal, we have to prove ∇.̅ 𝐹̅ = 0. Now,
  • 11. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 11 ∇.̅ 𝐹̅ = [𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ] . [( 𝑦2 − 𝑧2 + 3𝑦𝑧 − 2𝑥) 𝑖̂ + (3𝑥𝑦 + 2𝑥𝑦) 𝑗̂ + (3𝑥𝑦 − 2𝑥𝑧 + 2𝑧)𝑘̂] = −2 + 2𝑥 − 2𝑥 + 2 = 0 Thus, 𝐹̅ is Solenoidal. For irrotational, we have to prove Curl 𝐹̅ = 0 Now, Curl 𝐹̅ = | 𝑖̂ 𝑗̂ 𝑘̂ 𝜕 𝜕𝑥 𝜕 𝜕𝑦 𝜕 𝜕𝑧 ( 𝑦2 − 𝑧2 + 3𝑦𝑧− 2𝑥) (3𝑥𝑦 + 2𝑥𝑦) (3𝑥𝑦 − 2𝑥𝑧 + 2𝑧) | = (3𝑧+ 2𝑦 − 2𝑦 + 3𝑧) 𝑖̂ − (−2𝑧+ 3𝑦 − 3𝑦 + 2𝑧) 𝑗̂ + (3𝑧+ 2𝑦 − 2𝑦 − 3𝑧)𝑘̂ = 0𝑖̂ + 0𝑗̂ + 0𝑘̂ = 0 Thus, 𝐹̅ is irrotational. Hence, 𝐹̅ is both Solenoidal and irrotational. __________ Proved. Example 3: Find the scalar potential (velocity potential) function 𝑓 for 𝐴⃗ = 𝑦2 𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2 𝑘̂. Solution: We have, 𝐴⃗ = 𝑦2 𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2 𝑘̂. Curl 𝐴⃗ = ∇ × 𝐴⃗ = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ) × (𝑦2 𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2 𝑘̂). = | 𝑖̂ 𝑗̂ 𝑘̂ 𝜕 𝜕𝑥 𝜕 𝜕𝑦 𝜕 𝜕𝑧 𝑦2 2𝑥𝑦 −𝑧2 |
  • 12. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 12 = 𝑖̂(0) − 𝑗̂(0) + 𝑘̂(2𝑦 − 2𝑦) = 0 Hence, 𝐴⃗ is irrotational. To find the scalar potential function 𝑓. 𝐴⃗ = ∇ 𝑓 𝑑𝑓 = 𝜕𝑓 𝜕𝑥 𝑑𝑥 + 𝜕𝑓 𝜕𝑦 𝑑𝑦 + 𝜕𝑓 𝜕𝑧 𝑑𝑧 = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ). (𝑖̂ 𝑑 𝑥 + 𝑗̂ 𝑑 𝑦 + 𝑘̂ 𝑑𝑧) = (𝑖̂ 𝜕 𝜕𝑥 + 𝑗̂ 𝜕 𝜕𝑦 + 𝑘̂ 𝜕 𝜕𝑧 ) 𝑓. 𝑑𝑟⃗ = ∇𝑓. 𝑑𝑟⃗ = 𝐴⃗. 𝑑𝑟⃗ (𝐴 = ∇ 𝑓) = (𝑦2 𝑖̂ + 2𝑥𝑦𝑗̂ − 𝑧2 𝑘̂).(𝑖̂ 𝑑 𝑥 + 𝑗̂ 𝑑 𝑦 + 𝑘̂ 𝑑𝑧) = 𝑦2 𝑑𝑥 + 2𝑥𝑦 𝑑𝑦 − 𝑧2 𝑑𝑧 = 𝑑( 𝑥𝑦2) − 𝑧2 𝑑𝑧 𝑓 = ∫ 𝑑( 𝑥𝑦2) − ∫ 𝑧2 𝑑𝑧 ∴ 𝑓 = 𝑥𝑦2 − 𝑧3 3 + 𝑐 ________ Ans. 6.2 Exercise: 1) If a vector field is given by 𝐹⃗ = ( 𝑥2 − 𝑦2 + 𝑥) 𝑖̂ − (2𝑥𝑦 + 𝑦)𝑗̂. Is this field irrotational? If so, find its scalar potential.
  • 13. Unit-4 VECTOR DIFFERENTIATION RAI UNIVERSITY, AHMEDABAD 13 2) Determine the constants a and b such that the curl of vector 𝐴̅ = (2𝑥𝑦 + 3𝑦𝑧) 𝑖̂ + ( 𝑥2 + 𝑎𝑥𝑧 − 4𝑧2) 𝑗̂ − (3𝑥𝑦 + 𝑏𝑦𝑧)𝑘̂ is zero. 3) A fluid motion is given by𝑣̅ = ( 𝑦 + 𝑧) 𝑖̂ + ( 𝑧 + 𝑥) 𝑗̂ + (𝑥 + 𝑦)𝑘̂. Show that the motion is irrotational and hence find the velocity potential. 4) Given that vector field 𝑉̅ = ( 𝑥2 − 𝑦2 + 2𝑥𝑧) 𝑖̂ + ( 𝑥𝑧 − 𝑥𝑦 + 𝑦𝑧) 𝑗̂ + (𝑧2 + 𝑥2 )𝑘̂ find curl 𝑉. Show that the vectors given by curl 𝑉 at 𝑃0(1,2,−3) 𝑎𝑛𝑑 𝑃1 (2,3,12) are orthogonal. 5) Supposethat 𝑈⃗⃗⃗, 𝑉⃗⃗ and 𝑓 are continuously differentiable fields then Prove that, div(𝑈⃗⃗⃗ × 𝑉⃗⃗) = 𝑉⃗⃗. 𝑐𝑢𝑟𝑙 𝑈⃗⃗⃗ − 𝑈⃗⃗⃗. 𝑐𝑢𝑟𝑙 𝑉⃗⃗. 7.1 REFERECE BOOKS: 1) Introduction to Engineering Mathematics By H. K. DASS. & Dr. RAMA VERMA S. CHAND 2) Higher Engineering Mathematics By B.V. RAMANA Mc Graw Hill Education 3) Higher Engineering Mathematics By Dr. B.S. GREWAL KHANNA PUBLISHERS 4) http://elearning.vtu.ac.in/P7/enotes/MAT1/Vector.pdf