Engineering Mathematics Reference Guide (MATH 181 • MATH 182 • MATH 283)
This unified reference document provides a clean, formula-only reference manual for students across single-variable and multivariable engineering calculus.
1. Pre-Calculus, Algebra, & Geometry
1.1 Algebra & Factoring Formulas
Difference of Squares: a 2 − b 2 = ( a − b ) ( a + b ) a^2 - b^2 = (a - b)(a + b) a 2 − b 2 = ( a − b ) ( a + b )
Difference of Cubes: a 3 − b 3 = ( a − b ) ( a 2 + a b + b 2 ) a^3 - b^3 = (a - b)(a^2 + ab + b^2) a 3 − b 3 = ( a − b ) ( a 2 + ab + b 2 )
Sum of Cubes: a 3 + b 3 = ( a + b ) ( a 2 − a b + b 2 ) a^3 + b^3 = (a + b)(a^2 - ab + b^2) a 3 + b 3 = ( a + b ) ( a 2 − ab + b 2 )
Binomial Expansions:
( a + b ) 2 = a 2 + 2 a b + b 2 (a + b)^2 = a^2 + 2ab + b^2 ( a + b ) 2 = a 2 + 2 ab + b 2
( a − b ) 2 = a 2 − 2 a b + b 2 (a - b)^2 = a^2 - 2ab + b^2 ( a − b ) 2 = a 2 − 2 ab + b 2
( a + b ) 3 = a 3 + 3 a 2 b + 3 a b 2 + b 3 (a + b)^3 = a^3 + 3a^2b + 3ab^2 + b^3 ( a + b ) 3 = a 3 + 3 a 2 b + 3 a b 2 + b 3
( a − b ) 3 = a 3 − 3 a 2 b + 3 a b 2 − b 3 (a - b)^3 = a^3 - 3a^2b + 3ab^2 - b^3 ( a − b ) 3 = a 3 − 3 a 2 b + 3 a b 2 − b 3
Quadratic Formula: For a x 2 + b x + c = 0 ax^2 + bx + c = 0 a x 2 + b x + c = 0 , x = − b ± b 2 − 4 a c 2 a x = \frac{-b \pm \sqrt{b^2 - 4ac}}{2a} x = 2 a − b ± b 2 − 4 a c
1.2 Exponents & Logarithms
a x + y = a x a y , a x − y = a x a y , ( a x ) y = a x y , a − x = 1 a x , a 1 / n = a n a^{x+y} = a^x a^y, \quad a^{x-y} = \frac{a^x}{a^y}, \quad (a^x)^y = a^{xy}, \quad a^{-x} = \frac{1}{a^x}, \quad a^{1/n} = \sqrt[n]{a} a x + y = a x a y , a x − y = a y a x , ( a x ) y = a x y , a − x = a x 1 , a 1/ n = n a
ln ( x y ) = ln x + ln y , ln ( x y ) = ln x − ln y , ln ( x r ) = r ln x \ln(xy) = \ln x + \ln y, \quad \ln\left(\frac{x}{y}\right) = \ln x - \ln y, \quad \ln(x^r) = r\ln x ln ( x y ) = ln x + ln y , ln ( y x ) = ln x − ln y , ln ( x r ) = r ln x
ln ( 1 ) = 0 , ln ( e ) = 1 , e ln x = x , ln ( e x ) = x \ln(1) = 0, \quad \ln(e) = 1, \quad e^{\ln x} = x, \quad \ln(e^x) = x ln ( 1 ) = 0 , ln ( e ) = 1 , e l n x = x , ln ( e x ) = x
Change of Base: log a x = ln x ln a = log 10 x log 10 a \log_a x = \frac{\ln x}{\ln a} = \frac{\log_{10} x}{\log_{10} a} log a x = l n a l n x = l o g 10 a l o g 10 x
1.3 Geometric Formulas
Shape / Solid
Perimeter / Surface Area
Area / Volume
Circle (Radius r r r )
C = 2 π r = π d C = 2\pi r = \pi d C = 2 π r = π d
A = π r 2 A = \pi r^2 A = π r 2
Triangle (Base b b b , Height h h h )
P = a + b + c P = a + b + c P = a + b + c
A = 1 2 b h A = \frac{1}{2}bh A = 2 1 bh
Trapezoid (Bases a , b a, b a , b , Height h h h )
P = a + b + c + d P = a + b + c + d P = a + b + c + d
A = a + b 2 h A = \frac{a + b}{2}h A = 2 a + b h
Sphere (Radius r r r )
A = 4 π r 2 A = 4\pi r^2 A = 4 π r 2
V = 4 3 π r 3 V = \frac{4}{3}\pi r^3 V = 3 4 π r 3
Right Circular Cylinder (r , h r, h r , h )
A = 2 π r 2 + 2 π r h A = 2\pi r^2 + 2\pi rh A = 2 π r 2 + 2 π r h (total)
V = π r 2 h V = \pi r^2 h V = π r 2 h
Right Circular Cone (r , h r, h r , h )
A = π r 2 + π r r 2 + h 2 A = \pi r^2 + \pi r\sqrt{r^2 + h^2} A = π r 2 + π r r 2 + h 2
V = 1 3 π r 2 h V = \frac{1}{3}\pi r^2 h V = 3 1 π r 2 h
Rectangular Box (l , w , h l, w, h l , w , h )
A = 2 ( l w + l h + w h ) A = 2(lw + lh + wh) A = 2 ( l w + l h + w h )
V = l w h V = lwh V = l w h
1.4 Trigonometric Functions & The Unit Circle
Fundamental Identities
Reciprocal & Quotient:
tan θ = sin θ cos θ , cot θ = cos θ sin θ , sec θ = 1 cos θ , csc θ = 1 sin θ \tan\theta = \frac{\sin\theta}{\cos\theta}, \quad \cot\theta = \frac{\cos\theta}{\sin\theta}, \quad \sec\theta = \frac{1}{\cos\theta}, \quad \csc\theta = \frac{1}{\sin\theta} tan θ = cos θ sin θ , cot θ = sin θ cos θ , sec θ = cos θ 1 , csc θ = sin θ 1
Pythagorean Identities:
sin 2 θ + cos 2 θ = 1 , 1 + tan 2 θ = sec 2 θ , 1 + cot 2 θ = csc 2 θ \sin^2\theta + \cos^2\theta = 1, \quad 1 + \tan^2\theta = \sec^2\theta, \quad 1 + \cot^2\theta = \csc^2\theta sin 2 θ + cos 2 θ = 1 , 1 + tan 2 θ = sec 2 θ , 1 + cot 2 θ = csc 2 θ
Even/Odd Symmetries:
sin ( − θ ) = − sin θ , cos ( − θ ) = cos θ , tan ( − θ ) = − tan θ \sin(-\theta) = -\sin\theta, \quad \cos(-\theta) = \cos\theta, \quad \tan(-\theta) = -\tan\theta sin ( − θ ) = − sin θ , cos ( − θ ) = cos θ , tan ( − θ ) = − tan θ
Sum, Difference, & Angle Formulas
Sum & Difference:
sin ( A ± B ) = sin A cos B ± cos A sin B \sin(A \pm B) = \sin A \cos B \pm \cos A \sin B sin ( A ± B ) = sin A cos B ± cos A sin B
cos ( A ± B ) = cos A cos B ∓ sin A sin B \cos(A \pm B) = \cos A \cos B \mp \sin A \sin B cos ( A ± B ) = cos A cos B ∓ sin A sin B
tan ( A ± B ) = tan A ± tan B 1 ∓ tan A tan B \tan(A \pm B) = \frac{\tan A \pm \tan B}{1 \mp \tan A \tan B} tan ( A ± B ) = 1 ∓ tan A tan B tan A ± tan B
Double-Angle Identities:
sin ( 2 θ ) = 2 sin θ cos θ \sin(2\theta) = 2\sin\theta\cos\theta sin ( 2 θ ) = 2 sin θ cos θ
cos ( 2 θ ) = cos 2 θ − sin 2 θ = 2 cos 2 θ − 1 = 1 − 2 sin 2 θ \cos(2\theta) = \cos^2\theta - \sin^2\theta = 2\cos^2\theta - 1 = 1 - 2\sin^2\theta cos ( 2 θ ) = cos 2 θ − sin 2 θ = 2 cos 2 θ − 1 = 1 − 2 sin 2 θ
tan ( 2 θ ) = 2 tan θ 1 − tan 2 θ \tan(2\theta) = \frac{2\tan\theta}{1 - \tan^2\theta} tan ( 2 θ ) = 1 − tan 2 θ 2 tan θ
Half-Angle / Power-Reduction Identities:
sin 2 θ = 1 − cos ( 2 θ ) 2 , cos 2 θ = 1 + cos ( 2 θ ) 2 , tan 2 θ = 1 − cos ( 2 θ ) 1 + cos ( 2 θ ) \sin^2\theta = \frac{1 - \cos(2\theta)}{2}, \quad \cos^2\theta = \frac{1 + \cos(2\theta)}{2}, \quad \tan^2\theta = \frac{1 - \cos(2\theta)}{1 + \cos(2\theta)} sin 2 θ = 2 1 − cos ( 2 θ ) , cos 2 θ = 2 1 + cos ( 2 θ ) , tan 2 θ = 1 + cos ( 2 θ ) 1 − cos ( 2 θ )
Product-to-Sum Identities:
sin A cos B = 1 2 [ sin ( A + B ) + sin ( A − B ) ] \sin A \cos B = \frac{1}{2}[\sin(A + B) + \sin(A - B)] sin A cos B = 2 1 [ sin ( A + B ) + sin ( A − B )]
cos A cos B = 1 2 [ cos ( A + B ) + cos ( A − B ) ] \cos A \cos B = \frac{1}{2}[\cos(A + B) + \cos(A - B)] cos A cos B = 2 1 [ cos ( A + B ) + cos ( A − B )]
sin A sin B = 1 2 [ cos ( A − B ) − cos ( A + B ) ] \sin A \sin B = \frac{1}{2}[\cos(A - B) - \cos(A + B)] sin A sin B = 2 1 [ cos ( A − B ) − cos ( A + B )]
2. Calculus I (Single-Variable Differential Calculus)
2.1 Limits & Continuity
Definition of Derivative: f ′ ( x ) = lim h → 0 f ( x + h ) − f ( x ) h = lim z → x f ( z ) − f ( x ) z − x f'(x) = \lim_{h \to 0} \frac{f(x+h) - f(x)}{h} = \lim_{z \to x}\frac{f(z) - f(x)}{z - x} f ′ ( x ) = lim h → 0 h f ( x + h ) − f ( x ) = lim z → x z − x f ( z ) − f ( x )
Continuity at x = a x = a x = a : f ( a ) f(a) f ( a ) is defined, lim x → a f ( x ) \lim_{x \to a} f(x) lim x → a f ( x ) exists, and lim x → a f ( x ) = f ( a ) \lim_{x \to a} f(x) = f(a) lim x → a f ( x ) = f ( a ) .
Special Limits:
lim θ → 0 sin θ θ = 1 , lim θ → 0 1 − cos θ θ = 0 , lim n → ∞ ( 1 + 1 n ) n = e \lim_{\theta \to 0} \frac{\sin\theta}{\theta} = 1, \quad \lim_{\theta \to 0} \frac{1 - \cos\theta}{\theta} = 0, \quad \lim_{n \to \infty}\left(1 + \frac{1}{n}\right)^n = e θ → 0 lim θ sin θ = 1 , θ → 0 lim θ 1 − cos θ = 0 , n → ∞ lim ( 1 + n 1 ) n = e
L'Hôpital's Rule: For indeterminate forms [ 0 0 ] \left[\frac{0}{0}\right] [ 0 0 ] or [ ± ∞ ± ∞ ] \left[\frac{\pm\infty}{\pm\infty}\right] [ ± ∞ ± ∞ ] , lim x → a f ( x ) g ( x ) = lim x → a f ′ ( x ) g ′ ( x ) \lim_{x \to a}\frac{f(x)}{g(x)} = \lim_{x \to a}\frac{f'(x)}{g'(x)} lim x → a g ( x ) f ( x ) = lim x → a g ′ ( x ) f ′ ( x )
2.2 Differentiation Rules
Constant Rule: d d x [ c ] = 0 \frac{d}{dx}[c] = 0 d x d [ c ] = 0
Power Rule: d d x [ x n ] = n x n − 1 \frac{d}{dx}[x^n] = n x^{n-1} d x d [ x n ] = n x n − 1
Constant Multiple: d d x [ c f ( x ) ] = c f ′ ( x ) \frac{d}{dx}[c f(x)] = c f'(x) d x d [ c f ( x )] = c f ′ ( x )
Sum & Difference: d d x [ f ( x ) ± g ( x ) ] = f ′ ( x ) ± g ′ ( x ) \frac{d}{dx}[f(x) \pm g(x)] = f'(x) \pm g'(x) d x d [ f ( x ) ± g ( x )] = f ′ ( x ) ± g ′ ( x )
Product Rule: d d x [ f ( x ) g ( x ) ] = f ′ ( x ) g ( x ) + f ( x ) g ′ ( x ) \frac{d}{dx}[f(x) g(x)] = f'(x)g(x) + f(x)g'(x) d x d [ f ( x ) g ( x )] = f ′ ( x ) g ( x ) + f ( x ) g ′ ( x )
Quotient Rule: d d x [ f ( x ) g ( x ) ] = f ′ ( x ) g ( x ) − f ( x ) g ′ ( x ) [ g ( x ) ] 2 \frac{d}{dx}\left[\frac{f(x)}{g(x)}\right] = \frac{f'(x)g(x) - f(x)g'(x)}{[g(x)]^2} d x d [ g ( x ) f ( x ) ] = [ g ( x ) ] 2 f ′ ( x ) g ( x ) − f ( x ) g ′ ( x )
Chain Rule: d d x [ f ( g ( x ) ) ] = f ′ ( g ( x ) ) g ′ ( x ) \frac{d}{dx}[f(g(x))] = f'(g(x)) g'(x) d x d [ f ( g ( x ))] = f ′ ( g ( x )) g ′ ( x )
2.3 Table of Derivatives
Function f ( x ) f(x) f ( x )
Derivative f ′ ( x ) f'(x) f ′ ( x )
Function f ( x ) f(x) f ( x )
Derivative f ′ ( x ) f'(x) f ′ ( x )
e x e^x e x
e x e^x e x
ln x \ln x ln x
1 x ( x > 0 ) \frac{1}{x} \quad (x > 0) x 1 ( x > 0 )
a x a^x a x
a x ln a a^x \ln a a x ln a
log a x \log_a x log a x
1 x ln a \frac{1}{x \ln a} x l n a 1
sin x \sin x sin x
cos x \cos x cos x
csc x \csc x csc x
− csc x cot x -\csc x \cot x − csc x cot x
cos x \cos x cos x
− sin x -\sin x − sin x
sec x \sec x sec x
sec x tan x \sec x \tan x sec x tan x
tan x \tan x tan x
sec 2 x \sec^2 x sec 2 x
cot x \cot x cot x
− csc 2 x -\csc^2 x − csc 2 x
arcsin x \arcsin x arcsin x
1 1 − x 2 \frac{1}{\sqrt{1 - x^2}} 1 − x 2 1
arccsc x \operatorname{arccsc} x arccsc x
− 1 ∣ x ∣ x 2 − 1 -\frac{1}{|x|\sqrt{x^2 - 1}} − ∣ x ∣ x 2 − 1 1
arccos x \arccos x arccos x
− 1 1 − x 2 -\frac{1}{\sqrt{1 - x^2}} − 1 − x 2 1
arcsec x \operatorname{arcsec} x arcsec x
1 ∣ x ∣ x 2 − 1 \frac{1}{|x|\sqrt{x^2 - 1}} ∣ x ∣ x 2 − 1 1
arctan x \arctan x arctan x
1 1 + x 2 \frac{1}{1 + x^2} 1 + x 2 1
arccot x \operatorname{arccot} x arccot x
− 1 1 + x 2 -\frac{1}{1 + x^2} − 1 + x 2 1
sinh x \sinh x sinh x
cosh x \cosh x cosh x
csch x \operatorname{csch} x csch x
− csch x coth x -\operatorname{csch} x \coth x − csch x coth x
cosh x \cosh x cosh x
sinh x \sinh x sinh x
sech x \operatorname{sech} x sech x
− sech x tanh x -\operatorname{sech} x \tanh x − sech x tanh x
tanh x \tanh x tanh x
sech 2 x \operatorname{sech}^2 x sech 2 x
coth x \coth x coth x
− csch 2 x -\operatorname{csch}^2 x − csch 2 x
2.4 Applications of Derivatives
Linearization / Tangent Line: L ( x ) = f ( a ) + f ′ ( a ) ( x − a ) L(x) = f(a) + f'(a)(x - a) L ( x ) = f ( a ) + f ′ ( a ) ( x − a )
Newton's Method: x n + 1 = x n − f ( x n ) f ′ ( x n ) x_{n+1} = x_n - \frac{f(x_n)}{f'(x_n)} x n + 1 = x n − f ′ ( x n ) f ( x n )
Mean Value Theorem: If f f f is continuous on [ a , b ] [a,b] [ a , b ] and differentiable on ( a , b ) (a,b) ( a , b ) , then there exists c ∈ ( a , b ) c \in (a,b) c ∈ ( a , b ) such that f ′ ( c ) = f ( b ) − f ( a ) b − a f'(c) = \frac{f(b) - f(a)}{b - a} f ′ ( c ) = b − a f ( b ) − f ( a ) .
Extreme Value Analysis:
Critical points occur where f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0 or f ′ ( c ) f'(c) f ′ ( c ) is undefined.
Second Derivative Test: If f ′ ( c ) = 0 f'(c) = 0 f ′ ( c ) = 0 :
f ′ ′ ( c ) > 0 ⟹ f''(c) > 0 \implies f ′′ ( c ) > 0 ⟹ Local Minimum (concave up)
f ′ ′ ( c ) < 0 ⟹ f''(c) < 0 \implies f ′′ ( c ) < 0 ⟹ Local Maximum (concave down)
f ′ ′ ( c ) = 0 ⟹ f''(c) = 0 \implies f ′′ ( c ) = 0 ⟹ Inconclusive
3. Calculus II (Integral Calculus, Techniques, Series, & Parametrics)
3.1 Fundamental Theorems & Basic Integrals
FTC Part 1: d d x [ ∫ a x f ( t ) d t ] = f ( x ) and d d x [ ∫ g ( x ) h ( x ) f ( t ) d t ] = f ( h ( x ) ) h ′ ( x ) − f ( g ( x ) ) g ′ ( x ) \frac{d}{dx}\left[ \int_{a}^{x} f(t)\,dt \right] = f(x) \quad \text{and} \quad \frac{d}{dx}\left[ \int_{g(x)}^{h(x)} f(t)\,dt \right] = f(h(x))h'(x) - f(g(x))g'(x) d x d [ ∫ a x f ( t ) d t ] = f ( x ) and d x d [ ∫ g ( x ) h ( x ) f ( t ) d t ] = f ( h ( x )) h ′ ( x ) − f ( g ( x )) g ′ ( x )
FTC Part 2 (Evaluation): ∫ a b f ( x ) d x = F ( b ) − F ( a ) = [ F ( x ) ] a b \int_{a}^{b} f(x)\,dx = F(b) - F(a) = [F(x)]_a^b ∫ a b f ( x ) d x = F ( b ) − F ( a ) = [ F ( x ) ] a b , where F ′ ( x ) = f ( x ) F'(x) = f(x) F ′ ( x ) = f ( x ) .
Net Change Theorem: ∫ a b f ′ ( t ) d t = f ( b ) − f ( a ) \int_a^b f'(t)\,dt = f(b) - f(a) ∫ a b f ′ ( t ) d t = f ( b ) − f ( a )
Average Value: f avg = 1 b − a ∫ a b f ( x ) d x f_{\text{avg}} = \frac{1}{b - a}\int_a^b f(x)\,dx f avg = b − a 1 ∫ a b f ( x ) d x
3.2 Table of Indefinite Integrals
Integrand f ( x ) f(x) f ( x )
Indefinite Integral ∫ f ( x ) d x \int f(x)\,dx ∫ f ( x ) d x
x n ( n ≠ − 1 ) x^n \quad (n \ne -1) x n ( n = − 1 )
x n + 1 n + 1 + C \frac{x^{n+1}}{n+1} + C n + 1 x n + 1 + C
1 x \frac{1}{x} x 1
ln ∣ x ∣ + C \ln|x| + C ln ∣ x ∣ + C
e k x e^{kx} e k x
1 k e k x + C \frac{1}{k}e^{kx} + C k 1 e k x + C
a x a^x a x
a x ln a + C \frac{a^x}{\ln a} + C l n a a x + C
sin ( k x ) \sin(kx) sin ( k x )
− 1 k cos ( k x ) + C -\frac{1}{k}\cos(kx) + C − k 1 cos ( k x ) + C
cos ( k x ) \cos(kx) cos ( k x )
1 k sin ( k x ) + C \frac{1}{k}\sin(kx) + C k 1 sin ( k x ) + C
sec 2 ( k x ) \sec^2(kx) sec 2 ( k x )
1 k tan ( k x ) + C \frac{1}{k}\tan(kx) + C k 1 tan ( k x ) + C
csc 2 ( k x ) \csc^2(kx) csc 2 ( k x )
− 1 k cot ( k x ) + C -\frac{1}{k}\cot(kx) + C − k 1 cot ( k x ) + C
sec x tan x \sec x \tan x sec x tan x
sec x + C \sec x + C sec x + C
csc x cot x \csc x \cot x csc x cot x
− csc x + C -\csc x + C − csc x + C
tan x \tan x tan x
ln ∣ sec x ∣ + C = − ln ∣ cos x ∣ + C \ln|\sec x| + C = -\ln|\cos x| + C ln ∣ sec x ∣ + C = − ln ∣ cos x ∣ + C
cot x \cot x cot x
ln ∣ sin x ∣ + C \ln|\sin x| + C ln ∣ sin x ∣ + C
sec x \sec x sec x
ln ∣ sec x + tan x ∣ + C \ln|\sec x + \tan x| + C ln ∣ sec x + tan x ∣ + C
csc x \csc x csc x
− ln ∣ csc x + cot x ∣ + C = ln ∣ csc x − cot x ∣ + C -\ln|\csc x + \cot x| + C = \ln|\csc x - \cot x| + C − ln ∣ csc x + cot x ∣ + C = ln ∣ csc x − cot x ∣ + C
1 a 2 − x 2 \frac{1}{\sqrt{a^2 - x^2}} a 2 − x 2 1
arcsin ( x a ) + C \arcsin\left(\frac{x}{a}\right) + C arcsin ( a x ) + C
1 a 2 + x 2 \frac{1}{a^2 + x^2} a 2 + x 2 1
1 a arctan ( x a ) + C \frac{1}{a}\arctan\left(\frac{x}{a}\right) + C a 1 arctan ( a x ) + C
1 x x 2 − a 2 \frac{1}{x\sqrt{x^2 - a^2}} x x 2 − a 2 1
1 a arcsec ( ∣ x ∣ a ) + C \frac{1}{a}\operatorname{arcsec}\left(\frac{|x|}{a}\right) + C a 1 arcsec ( a ∣ x ∣ ) + C
1 a 2 − x 2 \frac{1}{a^2 - x^2} a 2 − x 2 1
1 2 a ln ∣ x + a x − a ∣ + C \frac{1}{2a}\ln\left|\frac{x+a}{x-a}\right| + C 2 a 1 ln x − a x + a + C
3.3 Integration Techniques
Substitution Method (u u u -sub): ∫ f ( g ( x ) ) g ′ ( x ) d x = ∫ f ( u ) d u \int f(g(x))g'(x)\,dx = \int f(u)\,du ∫ f ( g ( x )) g ′ ( x ) d x = ∫ f ( u ) d u
Integration by Parts: ∫ u d v = u v − ∫ v d u \int u\,dv = uv - \int v\,du ∫ u d v = uv − ∫ v d u
Definite: ∫ a b u d v = [ u v ] a b − ∫ a b v d u \int_a^b u\,dv = [uv]_a^b - \int_a^b v\,du ∫ a b u d v = [ uv ] a b − ∫ a b v d u
Trigonometric Substitution:
For a 2 − x 2 \sqrt{a^2 - x^2} a 2 − x 2 : Substitute x = a sin θ x = a\sin\theta x = a sin θ , d x = a cos θ d θ dx = a\cos\theta\,d\theta d x = a cos θ d θ , identity: a 2 − x 2 = a cos θ \sqrt{a^2 - x^2} = a\cos\theta a 2 − x 2 = a cos θ
For a 2 + x 2 \sqrt{a^2 + x^2} a 2 + x 2 : Substitute x = a tan θ x = a\tan\theta x = a tan θ , d x = a sec 2 θ d θ dx = a\sec^2\theta\,d\theta d x = a sec 2 θ d θ , identity: a 2 + x 2 = a sec θ \sqrt{a^2 + x^2} = a\sec\theta a 2 + x 2 = a sec θ
For x 2 − a 2 \sqrt{x^2 - a^2} x 2 − a 2 : Substitute x = a sec θ x = a\sec\theta x = a sec θ , d x = a sec θ tan θ d θ dx = a\sec\theta\tan\theta\,d\theta d x = a sec θ tan θ d θ , identity: x 2 − a 2 = a tan θ \sqrt{x^2 - a^2} = a\tan\theta x 2 − a 2 = a tan θ
Improper p p p -Integrals: ∫ 1 ∞ 1 x p d x \int_{1}^{\infty} \frac{1}{x^p}\,dx ∫ 1 ∞ x p 1 d x converges if and only if p > 1 p > 1 p > 1 .
3.4 Applications of Integrals
Area Between Curves: A = ∫ a b ∣ f ( x ) − g ( x ) ∣ d x A = \int_a^b |f(x) - g(x)|\,dx A = ∫ a b ∣ f ( x ) − g ( x ) ∣ d x
Volumes of Solids of Revolution:
Disk Method (Axis ∥ x \parallel x ∥ x -axis): V = π ∫ a b [ R ( x ) ] 2 d x V = \pi \int_a^b [R(x)]^2\,dx V = π ∫ a b [ R ( x ) ] 2 d x
Washer Method: V = π ∫ a b ( [ R ( x ) ] 2 − [ r ( x ) ] 2 ) d x V = \pi \int_a^b \left( [R(x)]^2 - [r(x)]^2 \right)\,dx V = π ∫ a b ( [ R ( x ) ] 2 − [ r ( x ) ] 2 ) d x
Cylindrical Shells: V = 2 π ∫ a b ( radius ) ( height ) d x = 2 π ∫ a b x [ f ( x ) − g ( x ) ] d x V = 2\pi \int_a^b (\text{radius})(\text{height})\,dx = 2\pi \int_a^b x [f(x) - g(x)]\,dx V = 2 π ∫ a b ( radius ) ( height ) d x = 2 π ∫ a b x [ f ( x ) − g ( x )] d x
Arc Length (2D):
Cartesian: s = ∫ a b 1 + [ f ′ ( x ) ] 2 d x s = \int_a^b \sqrt{1 + [f'(x)]^2}\,dx s = ∫ a b 1 + [ f ′ ( x ) ] 2 d x
Parametric: s = ∫ α β [ x ′ ( t ) ] 2 + [ y ′ ( t ) ] 2 d t s = \int_\alpha^\beta \sqrt{[x'(t)]^2 + [y'(t)]^2}\,dt s = ∫ α β [ x ′ ( t ) ] 2 + [ y ′ ( t ) ] 2 d t
Polar: s = ∫ α β r 2 + ( d r d θ ) 2 d θ s = \int_\alpha^\beta \sqrt{r^2 + \left(\frac{dr}{d\theta}\right)^2}\,d\theta s = ∫ α β r 2 + ( d θ d r ) 2 d θ
Surface Area of Revolution: S = 2 π ∫ r d s S = 2\pi \int r\,ds S = 2 π ∫ r d s
Physical Applications:
Work: W = ∫ a b F ( x ) d x W = \int_a^b F(x)\,dx W = ∫ a b F ( x ) d x ; Hooke's Law: F ( x ) = k x ⟹ W = 1 2 k x 2 F(x) = kx \implies W = \frac{1}{2}k x^2 F ( x ) = k x ⟹ W = 2 1 k x 2
Hydrostatic Force: F = ∫ a b ρ g ( d − y ) w ( y ) d y F = \int_a^b \rho g (d - y) w(y)\,dy F = ∫ a b ρ g ( d − y ) w ( y ) d y
Centroid Coordinates: x ˉ = 1 A ∫ a b x [ f ( x ) − g ( x ) ] d x , y ˉ = 1 2 A ∫ a b ( [ f ( x ) ] 2 − [ g ( x ) ] 2 ) d x \bar{x} = \frac{1}{A}\int_a^b x[f(x)-g(x)]\,dx, \quad \bar{y} = \frac{1}{2A}\int_a^b \left([f(x)]^2 - [g(x)]^2\right)\,dx x ˉ = A 1 ∫ a b x [ f ( x ) − g ( x )] d x , y ˉ = 2 A 1 ∫ a b ( [ f ( x ) ] 2 − [ g ( x ) ] 2 ) d x
3.5 Infinite Sequences & Series
Convergence Tests Flowchart
Power Series, Taylor & Maclaurin Expansions
Taylor Series about x = a x = a x = a :
f ( x ) = ∑ n = 0 ∞ f ( n ) ( a ) n ! ( x − a ) n = f ( a ) + f ′ ( a ) ( x − a ) + f ′ ′ ( a ) 2 ! ( x − a ) 2 + ⋯ f(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(a)}{n!}(x - a)^n = f(a) + f'(a)(x - a) + \frac{f''(a)}{2!}(x - a)^2 + \cdots f ( x ) = n = 0 ∑ ∞ n ! f ( n ) ( a ) ( x − a ) n = f ( a ) + f ′ ( a ) ( x − a ) + 2 ! f ′′ ( a ) ( x − a ) 2 + ⋯
Maclaurin Series (a = 0 a = 0 a = 0 ): f ( x ) = ∑ n = 0 ∞ f ( n ) ( 0 ) n ! x n f(x) = \sum_{n=0}^{\infty} \frac{f^{(n)}(0)}{n!}x^n f ( x ) = ∑ n = 0 ∞ n ! f ( n ) ( 0 ) x n
Standard Maclaurin Series:
1 1 − x = ∑ n = 0 ∞ x n = 1 + x + x 2 + x 3 + ⋯ ( ∣ x ∣ < 1 ) \frac{1}{1 - x} = \sum_{n=0}^{\infty} x^n = 1 + x + x^2 + x^3 + \cdots \quad (|x| < 1) 1 − x 1 = n = 0 ∑ ∞ x n = 1 + x + x 2 + x 3 + ⋯ ( ∣ x ∣ < 1 )
e x = ∑ n = 0 ∞ x n n ! = 1 + x + x 2 2 ! + x 3 3 ! + ⋯ ( − ∞ < x < ∞ ) e^x = \sum_{n=0}^{\infty} \frac{x^n}{n!} = 1 + x + \frac{x^2}{2!} + \frac{x^3}{3!} + \cdots \quad (-\infty < x < \infty) e x = n = 0 ∑ ∞ n ! x n = 1 + x + 2 ! x 2 + 3 ! x 3 + ⋯ ( − ∞ < x < ∞ )
sin x = ∑ n = 0 ∞ ( − 1 ) n x 2 n + 1 ( 2 n + 1 ) ! = x − x 3 3 ! + x 5 5 ! − ⋯ ( − ∞ < x < ∞ ) \sin x = \sum_{n=0}^{\infty} (-1)^n \frac{x^{2n+1}}{(2n+1)!} = x - \frac{x^3}{3!} + \frac{x^5}{5!} - \cdots \quad (-\infty < x < \infty) sin x = n = 0 ∑ ∞ ( − 1 ) n ( 2 n + 1 )! x 2 n + 1 = x − 3 ! x 3 + 5 ! x 5 − ⋯ ( − ∞ < x < ∞ )
cos x = ∑ n = 0 ∞ ( − 1 ) n x 2 n ( 2 n ) ! = 1 − x 2 2 ! + x 4 4 ! − ⋯ ( − ∞ < x < ∞ ) \cos x = \sum_{n=0}^{\infty} (-1)^n \frac{x^{2n}}{(2n)!} = 1 - \frac{x^2}{2!} + \frac{x^4}{4!} - \cdots \quad (-\infty < x < \infty) cos x = n = 0 ∑ ∞ ( − 1 ) n ( 2 n )! x 2 n = 1 − 2 ! x 2 + 4 ! x 4 − ⋯ ( − ∞ < x < ∞ )
ln ( 1 + x ) = ∑ n = 1 ∞ ( − 1 ) n − 1 x n n = x − x 2 2 + x 3 3 − ⋯ ( − 1 < x ≤ 1 ) \ln(1 + x) = \sum_{n=1}^{\infty} (-1)^{n-1} \frac{x^n}{n} = x - \frac{x^2}{2} + \frac{x^3}{3} - \cdots \quad (-1 < x \le 1) ln ( 1 + x ) = n = 1 ∑ ∞ ( − 1 ) n − 1 n x n = x − 2 x 2 + 3 x 3 − ⋯ ( − 1 < x ≤ 1 )
arctan x = ∑ n = 0 ∞ ( − 1 ) n x 2 n + 1 2 n + 1 = x − x 3 3 + x 5 5 − ⋯ ( − 1 ≤ x ≤ 1 ) \arctan x = \sum_{n=0}^{\infty} (-1)^n \frac{x^{2n+1}}{2n+1} = x - \frac{x^3}{3} + \frac{x^5}{5} - \cdots \quad (-1 \le x \le 1) arctan x = n = 0 ∑ ∞ ( − 1 ) n 2 n + 1 x 2 n + 1 = x − 3 x 3 + 5 x 5 − ⋯ ( − 1 ≤ x ≤ 1 )
( 1 + x ) k = 1 + k x + k ( k − 1 ) 2 ! x 2 + k ( k − 1 ) ( k − 2 ) 3 ! x 3 + ⋯ ( ∣ x ∣ < 1 ) (1 + x)^k = 1 + kx + \frac{k(k-1)}{2!}x^2 + \frac{k(k-1)(k-2)}{3!}x^3 + \cdots \quad (|x| < 1) ( 1 + x ) k = 1 + k x + 2 ! k ( k − 1 ) x 2 + 3 ! k ( k − 1 ) ( k − 2 ) x 3 + ⋯ ( ∣ x ∣ < 1 )
4. Calculus III (Multivariable & Vector Calculus for Engineers)
4.1 3D Coordinate Geometry & Vectors
3D Distance Formula: d = ( x 2 − x 1 ) 2 + ( y 2 − y 1 ) 2 + ( z 2 − z 1 ) 2 d = \sqrt{(x_2 - x_1)^2 + (y_2 - y_1)^2 + (z_2 - z_1)^2} d = ( x 2 − x 1 ) 2 + ( y 2 − y 1 ) 2 + ( z 2 − z 1 ) 2
Sphere Equation: ( x − x 0 ) 2 + ( y − y 0 ) 2 + ( z − z 0 ) 2 = R 2 (x - x_0)^2 + (y - y_0)^2 + (z - z_0)^2 = R^2 ( x − x 0 ) 2 + ( y − y 0 ) 2 + ( z − z 0 ) 2 = R 2
Magnitude & Unit Vector:
∥ v ⃗ ∥ = v 1 2 + v 2 2 + v 3 2 , u ^ = v ⃗ ∥ v ⃗ ∥ \|\vec{v}\| = \sqrt{v_1^2 + v_2^2 + v_3^2}, \quad \hat{u} = \frac{\vec{v}}{\|\vec{v}\|} ∥ v ∥ = v 1 2 + v 2 2 + v 3 2 , u ^ = ∥ v ∥ v
Dot Product:
u ⃗ ⋅ v ⃗ = u 1 v 1 + u 2 v 2 + u 3 v 3 = ∥ u ⃗ ∥ ∥ v ⃗ ∥ cos θ \vec{u} \cdot \vec{v} = u_1 v_1 + u_2 v_2 + u_3 v_3 = \|\vec{u}\|\|\vec{v}\|\cos\theta u ⋅ v = u 1 v 1 + u 2 v 2 + u 3 v 3 = ∥ u ∥∥ v ∥ cos θ
Orthogonality Condition: u ⃗ ⊥ v ⃗ ⟺ u ⃗ ⋅ v ⃗ = 0 \vec{u} \perp \vec{v} \iff \vec{u} \cdot \vec{v} = 0 u ⊥ v ⟺ u ⋅ v = 0
Angle: cos θ = u ⃗ ⋅ v ⃗ ∥ u ⃗ ∥ ∥ v ⃗ ∥ \cos\theta = \frac{\vec{u} \cdot \vec{v}}{\|\vec{u}\|\|\vec{v}\|} cos θ = ∥ u ∥∥ v ∥ u ⋅ v
Scalar & Vector Projections:
scal u ⃗ v ⃗ = u ⃗ ⋅ v ⃗ ∥ u ⃗ ∥ \text{scal}_{\vec{u}}\vec{v} = \frac{\vec{u} \cdot \vec{v}}{\|\vec{u}\|} scal u v = ∥ u ∥ u ⋅ v
proj u ⃗ v ⃗ = ( u ⃗ ⋅ v ⃗ ∥ u ⃗ ∥ 2 ) u ⃗ = ( u ⃗ ⋅ v ⃗ u ⃗ ⋅ u ⃗ ) u ⃗ \text{proj}_{\vec{u}}\vec{v} = \left(\frac{\vec{u} \cdot \vec{v}}{\|\vec{u}\|^2}\right)\vec{u} = \left(\frac{\vec{u} \cdot \vec{v}}{\vec{u} \cdot \vec{u}}\right)\vec{u} proj u v = ( ∥ u ∥ 2 u ⋅ v ) u = ( u ⋅ u u ⋅ v ) u
orth u ⃗ v ⃗ = v ⃗ − proj u ⃗ v ⃗ \text{orth}_{\vec{u}}\vec{v} = \vec{v} - \text{proj}_{\vec{u}}\vec{v} orth u v = v − proj u v
Cross Product:
u ⃗ × v ⃗ = ∣ i ^ j ^ k ^ u 1 u 2 u 3 v 1 v 2 v 3 ∣ = ⟨ u 2 v 3 − u 3 v 2 , u 3 v 1 − u 1 v 3 , u 1 v 2 − u 2 v 1 ⟩ \vec{u} \times \vec{v} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ u_1 & u_2 & u_3 \\ v_1 & v_2 & v_3 \end{vmatrix} = \langle u_2 v_3 - u_3 v_2, \; u_3 v_1 - u_1 v_3, \; u_1 v_2 - u_2 v_1 \rangle u × v = i ^ u 1 v 1 j ^ u 2 v 2 k ^ u 3 v 3 = ⟨ u 2 v 3 − u 3 v 2 , u 3 v 1 − u 1 v 3 , u 1 v 2 − u 2 v 1 ⟩
Magnitude: ∥ u ⃗ × v ⃗ ∥ = ∥ u ⃗ ∥ ∥ v ⃗ ∥ sin θ \|\vec{u} \times \vec{v}\| = \|\vec{u}\|\|\vec{v}\|\sin\theta ∥ u × v ∥ = ∥ u ∥∥ v ∥ sin θ
Parallel Condition: u ⃗ ∥ v ⃗ ⟺ u ⃗ × v ⃗ = 0 ⃗ \vec{u} \parallel \vec{v} \iff \vec{u} \times \vec{v} = \vec{0} u ∥ v ⟺ u × v = 0
Geometric Area of Parallelogram = ∥ u ⃗ × v ⃗ ∥ = \|\vec{u} \times \vec{v}\| = ∥ u × v ∥ ; Area of Triangle = 1 2 ∥ u ⃗ × v ⃗ ∥ = \frac{1}{2}\|\vec{u} \times \vec{v}\| = 2 1 ∥ u × v ∥
Torque: τ ⃗ = r ⃗ × F ⃗ \vec{\tau} = \vec{r} \times \vec{F} τ = r × F
Triple Scalar Product & Volume:
u ⃗ ⋅ ( v ⃗ × w ⃗ ) = ∣ u 1 u 2 u 3 v 1 v 2 v 3 w 1 w 2 w 3 ∣ \vec{u} \cdot (\vec{v} \times \vec{w}) = \begin{vmatrix} u_1 & u_2 & u_3 \\ v_1 & v_2 & v_3 \\ w_1 & w_2 & w_3 \end{vmatrix} u ⋅ ( v × w ) = u 1 v 1 w 1 u 2 v 2 w 2 u 3 v 3 w 3
Parallelepiped Volume: V = ∣ u ⃗ ⋅ ( v ⃗ × w ⃗ ) ∣ V = |\vec{u} \cdot (\vec{v} \times \vec{w})| V = ∣ u ⋅ ( v × w ) ∣
Coplanarity Condition: u ⃗ , v ⃗ , w ⃗ \vec{u}, \vec{v}, \vec{w} u , v , w are coplanar ⟺ u ⃗ ⋅ ( v ⃗ × w ⃗ ) = 0 \iff \vec{u} \cdot (\vec{v} \times \vec{w}) = 0 ⟺ u ⋅ ( v × w ) = 0
4.2 Lines & Distances in 3D Space
Equations of a Line through P 0 ( x 0 , y 0 , z 0 ) P_0(x_0, y_0, z_0) P 0 ( x 0 , y 0 , z 0 ) with Direction v ⃗ = ⟨ a , b , c ⟩ \vec{v} = \langle a, b, c \rangle v = ⟨ a , b , c ⟩ :
Vector Equation: r ⃗ ( t ) = r ⃗ 0 + t v ⃗ = ⟨ x 0 + a t , y 0 + b t , z 0 + c t ⟩ \vec{r}(t) = \vec{r}_0 + t\vec{v} = \langle x_0 + at, y_0 + bt, z_0 + ct \rangle r ( t ) = r 0 + t v = ⟨ x 0 + a t , y 0 + b t , z 0 + c t ⟩
Parametric Equations: x = x 0 + a t , y = y 0 + b t , z = z 0 + c t x = x_0 + at, \quad y = y_0 + bt, \quad z = z_0 + ct x = x 0 + a t , y = y 0 + b t , z = z 0 + c t
Symmetric Equations: x − x 0 a = y − y 0 b = z − z 0 c ( a b c ≠ 0 ) \frac{x - x_0}{a} = \frac{y - y_0}{b} = \frac{z - z_0}{c} \quad (abc \ne 0) a x − x 0 = b y − y 0 = c z − z 0 ( ab c = 0 )
Shortest Distance from Point M M M to Line L L L (Point P ∈ L P \in L P ∈ L , Direction v ⃗ \vec{v} v ):
d = ∥ P M ⃗ × v ⃗ ∥ ∥ v ⃗ ∥ d = \frac{\|\vec{PM} \times \vec{v}\|}{\|\vec{v}\|} d = ∥ v ∥ ∥ P M × v ∥
Classification of Two 3D Lines L 1 ( r ⃗ 1 ( t ) = r ⃗ 01 + t v ⃗ 1 ) L_1(\vec{r}_1(t) = \vec{r}_{01} + t\vec{v}_1) L 1 ( r 1 ( t ) = r 01 + t v 1 ) and L 2 ( r ⃗ 2 ( s ) = r ⃗ 02 + s v ⃗ 2 ) L_2(\vec{r}_2(s) = \vec{r}_{02} + s\vec{v}_2) L 2 ( r 2 ( s ) = r 02 + s v 2 ) :
Parallel: v ⃗ 1 = k v ⃗ 2 \vec{v}_1 = k\vec{v}_2 v 1 = k v 2 . (Coincident if points on L 1 L_1 L 1 satisfy L 2 L_2 L 2 , otherwise Distinct Parallel).
Intersecting: v ⃗ 1 ≠ k v ⃗ 2 \vec{v}_1 \ne k\vec{v}_2 v 1 = k v 2 and the linear system r ⃗ 1 ( t ) = r ⃗ 2 ( s ) \vec{r}_1(t) = \vec{r}_2(s) r 1 ( t ) = r 2 ( s ) has a consistent unique solution ( t ∗ , s ∗ ) (t^*, s^*) ( t ∗ , s ∗ ) .
Skew: v ⃗ 1 ≠ k v ⃗ 2 \vec{v}_1 \ne k\vec{v}_2 v 1 = k v 2 and the linear system r ⃗ 1 ( t ) = r ⃗ 2 ( s ) \vec{r}_1(t) = \vec{r}_2(s) r 1 ( t ) = r 2 ( s ) is inconsistent (lines are non-parallel and non-intersecting).
4.3 Vector-Valued Functions, Curves, & Kinematics
Kinematic Hierarchy:
Position: r ⃗ ( t ) = ⟨ x ( t ) , y ( t ) , z ( t ) ⟩ \vec{r}(t) = \langle x(t), y(t), z(t) \rangle r ( t ) = ⟨ x ( t ) , y ( t ) , z ( t )⟩
Velocity: v ⃗ ( t ) = r ⃗ ′ ( t ) = ⟨ x ′ ( t ) , y ′ ( t ) , z ′ ( t ) ⟩ \vec{v}(t) = \vec{r}'(t) = \langle x'(t), y'(t), z'(t) \rangle v ( t ) = r ′ ( t ) = ⟨ x ′ ( t ) , y ′ ( t ) , z ′ ( t )⟩
Acceleration: a ⃗ ( t ) = r ⃗ ′ ′ ( t ) = v ⃗ ′ ( t ) = ⟨ x ′ ′ ( t ) , y ′ ′ ( t ) , z ′ ′ ( t ) ⟩ \vec{a}(t) = \vec{r}''(t) = \vec{v}'(t) = \langle x''(t), y''(t), z''(t) \rangle a ( t ) = r ′′ ( t ) = v ′ ( t ) = ⟨ x ′′ ( t ) , y ′′ ( t ) , z ′′ ( t )⟩
Scalar Speed: v ( t ) = ∥ v ⃗ ( t ) ∥ = ( x ′ ) 2 + ( y ′ ) 2 + ( z ′ ) 2 v(t) = \|\vec{v}(t)\| = \sqrt{(x')^2 + (y')^2 + (z')^2} v ( t ) = ∥ v ( t ) ∥ = ( x ′ ) 2 + ( y ′ ) 2 + ( z ′ ) 2
Arc Length & Intrinsic Parametrization:
Arc Length Integral: s = ∫ a b ∥ r ⃗ ′ ( t ) ∥ d t s = \int_{a}^{b} \|\vec{r}'(t)\|\,dt s = ∫ a b ∥ r ′ ( t ) ∥ d t
Accumulated Arc Length Function: s ( t ) = ∫ a t ∥ r ⃗ ′ ( u ) ∥ d u ⟹ d s d t = ∥ r ⃗ ′ ( t ) ∥ s(t) = \int_{a}^{t} \|\vec{r}'(u)\|\,du \implies \frac{ds}{dt} = \|\vec{r}'(t)\| s ( t ) = ∫ a t ∥ r ′ ( u ) ∥ d u ⟹ d t d s = ∥ r ′ ( t ) ∥
Unit Speed Property under r ⃗ ( s ) \vec{r}(s) r ( s ) : ∥ r ⃗ ′ ( s ) ∥ = 1 \|\vec{r}'(s)\| = 1 ∥ r ′ ( s ) ∥ = 1
TNB Frame & Curvature:
Unit Tangent Vector: T ^ ( t ) = r ⃗ ′ ( t ) ∥ r ⃗ ′ ( t ) ∥ \hat{T}(t) = \frac{\vec{r}'(t)}{\|\vec{r}'(t)\|} T ^ ( t ) = ∥ r ′ ( t ) ∥ r ′ ( t )
Principal Unit Normal Vector: N ^ ( t ) = T ^ ′ ( t ) ∥ T ^ ′ ( t ) ∥ \hat{N}(t) = \frac{\hat{T}'(t)}{\|\hat{T}'(t)\|} N ^ ( t ) = ∥ T ^ ′ ( t ) ∥ T ^ ′ ( t )
Binormal Vector: B ^ ( t ) = T ^ ( t ) × N ^ ( t ) \hat{B}(t) = \hat{T}(t) \times \hat{N}(t) B ^ ( t ) = T ^ ( t ) × N ^ ( t )
Curvature Formulas:
κ = ∥ T ^ ′ ( t ) ∥ ∥ r ⃗ ′ ( t ) ∥ = ∥ r ⃗ ′ ( t ) × r ⃗ ′ ′ ( t ) ∥ ∥ r ⃗ ′ ( t ) ∥ 3 = ∥ v ⃗ × a ⃗ ∥ v 3 \kappa = \frac{\|\hat{T}'(t)\|}{\|\vec{r}'(t)\|} = \frac{\|\vec{r}'(t) \times \vec{r}''(t)\|}{\|\vec{r}'(t)\|^3} = \frac{\|\vec{v} \times \vec{a}\|}{v^3} κ = ∥ r ′ ( t ) ∥ ∥ T ^ ′ ( t ) ∥ = ∥ r ′ ( t ) ∥ 3 ∥ r ′ ( t ) × r ′′ ( t ) ∥ = v 3 ∥ v × a ∥
For planar curve y = f ( x ) y = f(x) y = f ( x ) : κ ( x ) = ∣ f ′ ′ ( x ) ∣ [ 1 + ( f ′ ( x ) ) 2 ] 3 / 2 \kappa(x) = \frac{|f''(x)|}{[1 + (f'(x))^2]^{3/2}} κ ( x ) = [ 1 + ( f ′ ( x ) ) 2 ] 3/2 ∣ f ′′ ( x ) ∣
Radius of Curvature & Osculating Circle: ρ = 1 κ \rho = \frac{1}{\kappa} ρ = κ 1
Tangential & Normal Acceleration Decomposition:
a ⃗ ( t ) = a T T ^ ( t ) + a N N ^ ( t ) \vec{a}(t) = a_T \hat{T}(t) + a_N \hat{N}(t) a ( t ) = a T T ^ ( t ) + a N N ^ ( t )
a T = d d t ∥ v ⃗ ∥ = v ⃗ ⋅ a ⃗ ∥ v ⃗ ∥ a_T = \frac{d}{dt}\|\vec{v}\| = \frac{\vec{v} \cdot \vec{a}}{\|\vec{v}\|} a T = d t d ∥ v ∥ = ∥ v ∥ v ⋅ a
a N = κ ∥ v ⃗ ∥ 2 = ∥ v ⃗ × a ⃗ ∥ ∥ v ⃗ ∥ = ∥ a ⃗ ∥ 2 − a T 2 ( a N ≥ 0 ) a_N = \kappa \|\vec{v}\|^2 = \frac{\|\vec{v} \times \vec{a}\|}{\|\vec{v}\|} = \sqrt{\|\vec{a}\|^2 - a_T^2} \quad (a_N \ge 0) a N = κ ∥ v ∥ 2 = ∥ v ∥ ∥ v × a ∥ = ∥ a ∥ 2 − a T 2 ( a N ≥ 0 )
4.4 Multivariable Differential Calculus
Partial Derivatives: f x = ∂ f ∂ x = lim h → 0 f ( x + h , y ) − f ( x , y ) h , f y = ∂ f ∂ y = lim h → 0 f ( x , y + h ) − f ( x , y ) h f_x = \frac{\partial f}{\partial x} = \lim_{h \to 0}\frac{f(x+h, y) - f(x,y)}{h}, \quad f_y = \frac{\partial f}{\partial y} = \lim_{h \to 0}\frac{f(x, y+h) - f(x,y)}{h} f x = ∂ x ∂ f = lim h → 0 h f ( x + h , y ) − f ( x , y ) , f y = ∂ y ∂ f = lim h → 0 h f ( x , y + h ) − f ( x , y )
Clairaut's Theorem: If f x y f_{xy} f x y and f y x f_{yx} f y x are continuous, then f x y = f y x f_{xy} = f_{yx} f x y = f y x .
Tangent Plane to z = f ( x , y ) z = f(x,y) z = f ( x , y ) at ( x 0 , y 0 , z 0 ) (x_0, y_0, z_0) ( x 0 , y 0 , z 0 ) :
z − z 0 = f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 ) z - z_0 = f_x(x_0, y_0)(x - x_0) + f_y(x_0, y_0)(y - y_0) z − z 0 = f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 )
Linear Approximation & Total Differential:
L ( x , y ) = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 ) L(x,y) = f(x_0, y_0) + f_x(x_0, y_0)(x - x_0) + f_y(x_0, y_0)(y - y_0) L ( x , y ) = f ( x 0 , y 0 ) + f x ( x 0 , y 0 ) ( x − x 0 ) + f y ( x 0 , y 0 ) ( y − y 0 )
d z = ∂ z ∂ x d x + ∂ z ∂ y d y dz = \frac{\partial z}{\partial x}dx + \frac{\partial z}{\partial y}dy d z = ∂ x ∂ z d x + ∂ y ∂ z d y
Multivariable Chain Rule:
If z = f ( x , y ) z = f(x,y) z = f ( x , y ) where x = g ( t ) , y = h ( t ) x = g(t), y = h(t) x = g ( t ) , y = h ( t ) : d z d t = ∂ z ∂ x d x d t + ∂ z ∂ y d y d t \frac{dz}{dt} = \frac{\partial z}{\partial x}\frac{dx}{dt} + \frac{\partial z}{\partial y}\frac{dy}{dt} d t d z = ∂ x ∂ z d t d x + ∂ y ∂ z d t d y
If z = f ( x , y ) z = f(x,y) z = f ( x , y ) where x = g ( u , v ) , y = h ( u , v ) x = g(u,v), y = h(u,v) x = g ( u , v ) , y = h ( u , v ) : ∂ z ∂ u = ∂ z ∂ x ∂ x ∂ u + ∂ z ∂ y ∂ y ∂ u \frac{\partial z}{\partial u} = \frac{\partial z}{\partial x}\frac{\partial x}{\partial u} + \frac{\partial z}{\partial y}\frac{\partial y}{\partial u} ∂ u ∂ z = ∂ x ∂ z ∂ u ∂ x + ∂ y ∂ z ∂ u ∂ y
Gradient Vector & Directional Derivative:
∇ f = ⟨ ∂ f ∂ x , ∂ f ∂ y , ∂ f ∂ z ⟩ \nabla f = \left\langle \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y}, \frac{\partial f}{\partial z} \right\rangle ∇ f = ⟨ ∂ x ∂ f , ∂ y ∂ f , ∂ z ∂ f ⟩
D u ^ f = ∇ f ⋅ u ^ ( ∥ u ^ ∥ = 1 ) D_{\hat{u}}f = \nabla f \cdot \hat{u} \quad (\|\hat{u}\| = 1) D u ^ f = ∇ f ⋅ u ^ ( ∥ u ^ ∥ = 1 )
Maximum rate of increase is ∥ ∇ f ∥ \|\nabla f\| ∥∇ f ∥ , occurring in the direction of u ^ = ∇ f ∥ ∇ f ∥ \hat{u} = \frac{\nabla f}{\|\nabla f\|} u ^ = ∥∇ f ∥ ∇ f .
Tangent plane to level surface F ( x , y , z ) = C F(x,y,z) = C F ( x , y , z ) = C at P 0 P_0 P 0 : ∇ F ( P 0 ) ⋅ ⟨ x − x 0 , y − y 0 , z − z 0 ⟩ = 0 \nabla F(P_0) \cdot \langle x - x_0, y - y_0, z - z_0 \rangle = 0 ∇ F ( P 0 ) ⋅ ⟨ x − x 0 , y − y 0 , z − z 0 ⟩ = 0 .
Critical Points & Second Derivative Test:
Critical points occur where ∇ f ( x 0 , y 0 ) = 0 ⃗ \nabla f(x_0, y_0) = \vec{0} ∇ f ( x 0 , y 0 ) = 0 or is undefined.
Discriminant: D = f x x f y y − ( f x y ) 2 D = f_{xx}f_{yy} - (f_{xy})^2 D = f xx f y y − ( f x y ) 2
D > 0 and f x x > 0 ⟹ D > 0 \text{ and } f_{xx} > 0 \implies D > 0 and f xx > 0 ⟹ Local Minimum
D > 0 and f x x < 0 ⟹ D > 0 \text{ and } f_{xx} < 0 \implies D > 0 and f xx < 0 ⟹ Local Maximum
D < 0 ⟹ D < 0 \implies D < 0 ⟹ Saddle Point
D = 0 ⟹ D = 0 \implies D = 0 ⟹ Inconclusive
Lagrange Multipliers: To optimize f ( x , y , z ) f(x,y,z) f ( x , y , z ) subject to constraint g ( x , y , z ) = k g(x,y,z) = k g ( x , y , z ) = k :
∇ f = λ ∇ g and g ( x , y , z ) = k \nabla f = \lambda \nabla g \quad \text{and} \quad g(x,y,z) = k ∇ f = λ ∇ g and g ( x , y , z ) = k
4.5 Multiple Integrals & Coordinate Transformations
Double Integrals:
Rectangular: ∬ R f ( x , y ) d A = ∫ a b ∫ c d f ( x , y ) d y d x \iint_R f(x,y)\,dA = \int_a^b \int_c^d f(x,y)\,dy\,dx ∬ R f ( x , y ) d A = ∫ a b ∫ c d f ( x , y ) d y d x
Polar Coordinates (x = r cos θ , y = r sin θ , x 2 + y 2 = r 2 x = r\cos\theta, y = r\sin\theta, x^2 + y^2 = r^2 x = r cos θ , y = r sin θ , x 2 + y 2 = r 2 ):
∬ R f ( x , y ) d A = ∬ R f ( r cos θ , r sin θ ) r d r d θ \iint_R f(x,y)\,dA = \iint_R f(r\cos\theta, r\sin\theta)\,r\,dr\,d\theta ∬ R f ( x , y ) d A = ∬ R f ( r cos θ , r sin θ ) r d r d θ
Triple Integrals:
Rectangular: d V = d x d y d z dV = dx\,dy\,dz d V = d x d y d z
Cylindrical (x = r cos θ , y = r sin θ , z = z x = r\cos\theta, y = r\sin\theta, z = z x = r cos θ , y = r sin θ , z = z ):
d V = r d r d θ d z dV = r\,dr\,d\theta\,dz d V = r d r d θ d z
Spherical (x = ρ sin ϕ cos θ , y = ρ sin ϕ sin θ , z = ρ cos ϕ , x 2 + y 2 + z 2 = ρ 2 x = \rho\sin\phi\cos\theta, y = \rho\sin\phi\sin\theta, z = \rho\cos\phi, x^2 + y^2 + z^2 = \rho^2 x = ρ sin ϕ cos θ , y = ρ sin ϕ sin θ , z = ρ cos ϕ , x 2 + y 2 + z 2 = ρ 2 ):
d V = ρ 2 sin ϕ d ρ d ϕ d θ ( 0 ≤ ϕ ≤ π , 0 ≤ θ ≤ 2 π ) dV = \rho^2 \sin\phi\,d\rho\,d\phi\,d\theta \quad (0 \le \phi \le \pi, \; 0 \le \theta \le 2\pi) d V = ρ 2 sin ϕ d ρ d ϕ d θ ( 0 ≤ ϕ ≤ π , 0 ≤ θ ≤ 2 π )
Jacobian Transformation (2D & 3D):
J ( u , v ) = ∂ ( x , y ) ∂ ( u , v ) = ∣ ∂ x ∂ u ∂ x ∂ v ∂ y ∂ u ∂ y ∂ v ∣ ⟹ d A = ∣ J ( u , v ) ∣ d u d v J(u,v) = \frac{\partial(x,y)}{\partial(u,v)} = \begin{vmatrix} \frac{\partial x}{\partial u} & \frac{\partial x}{\partial v} \\ \frac{\partial y}{\partial u} & \frac{\partial y}{\partial v} \end{vmatrix} \implies dA = |J(u,v)|\,du\,dv J ( u , v ) = ∂ ( u , v ) ∂ ( x , y ) = ∂ u ∂ x ∂ u ∂ y ∂ v ∂ x ∂ v ∂ y ⟹ d A = ∣ J ( u , v ) ∣ d u d v
Physical Applications of Multiple Integrals:
Mass: M = ∬ D ρ ( x , y ) d A or M = ∭ E ρ ( x , y , z ) d V M = \iint_D \rho(x,y)\,dA \quad \text{or} \quad M = \iiint_E \rho(x,y,z)\,dV M = ∬ D ρ ( x , y ) d A or M = ∭ E ρ ( x , y , z ) d V
Center of Mass: x ˉ = 1 M ∬ D x ρ d A , y ˉ = 1 M ∬ D y ρ d A \bar{x} = \frac{1}{M}\iint_D x\rho\,dA, \quad \bar{y} = \frac{1}{M}\iint_D y\rho\,dA x ˉ = M 1 ∬ D x ρ d A , y ˉ = M 1 ∬ D y ρ d A
4.6 Vector Calculus (Fields, Integrals, & Big Theorems)
Vector Field Operations:
Gradient: ∇ f = ⟨ f x , f y , f z ⟩ \nabla f = \langle f_x, f_y, f_z \rangle ∇ f = ⟨ f x , f y , f z ⟩
Divergence: div F ⃗ = ∇ ⋅ F ⃗ = ∂ P ∂ x + ∂ Q ∂ y + ∂ R ∂ z \operatorname{div}\vec{F} = \nabla \cdot \vec{F} = \frac{\partial P}{\partial x} + \frac{\partial Q}{\partial y} + \frac{\partial R}{\partial z} div F = ∇ ⋅ F = ∂ x ∂ P + ∂ y ∂ Q + ∂ z ∂ R
Curl: curl F ⃗ = ∇ × F ⃗ = ∣ i ^ j ^ k ^ ∂ ∂ x ∂ ∂ y ∂ ∂ z P Q R ∣ = ⟨ R y − Q z , P z − R x , Q x − P y ⟩ \operatorname{curl}\vec{F} = \nabla \times \vec{F} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ \frac{\partial}{\partial x} & \frac{\partial}{\partial y} & \frac{\partial}{\partial z} \\ P & Q & R \end{vmatrix} = \left\langle R_y - Q_z, \; P_z - R_x, \; Q_x - P_y \right\rangle curl F = ∇ × F = i ^ ∂ x ∂ P j ^ ∂ y ∂ Q k ^ ∂ z ∂ R = ⟨ R y − Q z , P z − R x , Q x − P y ⟩
Conservative Criterion: F ⃗ = ∇ f ⟺ curl F ⃗ = 0 ⃗ \vec{F} = \nabla f \iff \operatorname{curl}\vec{F} = \vec{0} F = ∇ f ⟺ curl F = 0 (on simply connected domains).
Line Integrals:
Scalar: ∫ C f d s = ∫ a b f ( r ⃗ ( t ) ) ∥ r ⃗ ′ ( t ) ∥ d t \int_C f\,ds = \int_a^b f(\vec{r}(t)) \|\vec{r}'(t)\|\,dt ∫ C f d s = ∫ a b f ( r ( t )) ∥ r ′ ( t ) ∥ d t
Vector Work / Circulation: ∫ C F ⃗ ⋅ d r ⃗ = ∫ a b F ⃗ ( r ⃗ ( t ) ) ⋅ r ⃗ ′ ( t ) d t = ∫ C P d x + Q d y + R d z \int_C \vec{F} \cdot d\vec{r} = \int_a^b \vec{F}(\vec{r}(t)) \cdot \vec{r}'(t)\,dt = \int_C P\,dx + Q\,dy + R\,dz ∫ C F ⋅ d r = ∫ a b F ( r ( t )) ⋅ r ′ ( t ) d t = ∫ C P d x + Q d y + R d z
Fundamental Theorem for Line Integrals:
∫ C ∇ f ⋅ d r ⃗ = f ( r ⃗ ( b ) ) − f ( r ⃗ ( a ) ) \int_C \nabla f \cdot d\vec{r} = f(\vec{r}(b)) - f(\vec{r}(a)) ∫ C ∇ f ⋅ d r = f ( r ( b )) − f ( r ( a ))
Green's Theorem (2D Plane):
∮ C P d x + Q d y = ∬ D ( ∂ Q ∂ x − ∂ P ∂ y ) d A \oint_C P\,dx + Q\,dy = \iint_D \left( \frac{\partial Q}{\partial x} - \frac{\partial P}{\partial y} \right)\,dA ∮ C P d x + Q d y = ∬ D ( ∂ x ∂ Q − ∂ y ∂ P ) d A
Surface Integrals:
Scalar: ∬ S f d S = ∬ D f ( r ⃗ ( u , v ) ) ∥ r ⃗ u × r ⃗ v ∥ d A \iint_S f\,dS = \iint_D f(\vec{r}(u,v)) \|\vec{r}_u \times \vec{r}_v\|\,dA ∬ S f d S = ∬ D f ( r ( u , v )) ∥ r u × r v ∥ d A
Vector Flux: ∬ S F ⃗ ⋅ d S ⃗ = ∬ D F ⃗ ( r ⃗ ( u , v ) ) ⋅ ( r ⃗ u × r ⃗ v ) d A \iint_S \vec{F} \cdot d\vec{S} = \iint_D \vec{F}(\vec{r}(u,v)) \cdot (\vec{r}_u \times \vec{r}_v)\,dA ∬ S F ⋅ d S = ∬ D F ( r ( u , v )) ⋅ ( r u × r v ) d A
Stokes' Theorem:
∮ C F ⃗ ⋅ d r ⃗ = ∬ S ( ∇ × F ⃗ ) ⋅ d S ⃗ \oint_C \vec{F} \cdot d\vec{r} = \iint_S (\nabla \times \vec{F}) \cdot d\vec{S} ∮ C F ⋅ d r = ∬ S ( ∇ × F ) ⋅ d S
Divergence Theorem (Gauss's Theorem):
∬ S F ⃗ ⋅ d S ⃗ = ∭ E ( ∇ ⋅ F ⃗ ) d V \iint_S \vec{F} \cdot d\vec{S} = \iiint_E (\nabla \cdot \vec{F})\,dV ∬ S F ⋅ d S = ∭ E ( ∇ ⋅ F ) d V