Multivariate Calculus - Bruce E. Shapiro
Multivariate Calculus - Bruce E. Shapiro Multivariate Calculus - Bruce E. Shapiro
188 LECTURE 22. LINE INTEGRALS 5. The line integral around a closed curve is zero, i.e., ∮ F · dr = 0 for all closed curves C. Example 22.5 Determine if is a gradient field. C F = ( x 2 − y 2 , −2xy, z ) Solution. We calculate the curl F, ⎛ ⎞ ⎛ 0 −D z D y x 2 − y 2 ⎞ ⎛ ⎞ −D z (−2xy) + D y (z) ∇F = ⎝ D z 0 −D x ⎠ ⎝ −2xy ⎠ = ⎝ D z (x 2 − y 2 ) − D x (z) ⎠ −D y D x 0 z −D y (x 2 − y 2 ) + D x (−2xy) = (0, 0, 2y − 2y) = 0 Hence the field is a gradient field. Example 22.6 Determine if F = (−y, z, x) is a gradient field. Solution. ⎛ 0 −D z D y ∇F = ⎝ D z 0 −D x −D y D x 0 = (−1, −1, 1) ≠ 0 ⎞ ⎛ ⎞ ⎛ ⎞ −y −D z (z) + D y (x) ⎠ ⎝ z ⎠ = ⎝ D z (−y) − D x (x) ⎠ x −D y (−y) + D x (z) Hence the field is not a gradient field. Example 22.7 Find the potential function f(x, y, z) for the gradient field in example 22.5. Solution. The vector field is F = (x 2 − y 2 , −2xy, z) = (M, N, P ) where M = x 2 − y 2 , N = −2xy, and P = z. Since F is a gradient field, then for some scalar function f, f x = M = x 2 − y 2 (22.36) f y = N = −2xy (22.37) f z = P = z (22.38) Integrating the first equation with respect to x, ∫ ∫ f(x, y, z) = f x dx = (x 2 − y 2 )dx = 1 3 x3 − y 2 x + h(y, z) (22.39) Revised December 6, 2006. Math 250, Fall 2006
LECTURE 22. LINE INTEGRALS 189 The function h(y, z) is the constant of integration: we integrated over x, so the constant may still depend on y or z. Differentiate with respect to y: By equation 22.37 f y = −2xy + h y (y, z) (22.40) −2xy + h y (y, z) = −2xy h y (y, z) = 0 Therefore h does not depend on y, only on z, and we can write Differentiating with respect to z, f(x, y, z) = 1 3 x3 − y 2 x + h(z) (22.41) f z = dh dz (22.42) By equation 22.38 Hence From equation 22.41 ∫ h(z) = z dh dz = f z = z (22.43) ∫ h ′ (z)dz = z zdz = 1 2 z2 + C (22.44) f(x, y, z) = 1 3 x3 − y 2 x + 1 2 z2 + C (22.45) where C is any arbitrary constant. Math 250, Fall 2006 Revised December 6, 2006.
- Page 149 and 150: LECTURE 17. DOUBLE INTEGRALS OVER G
- Page 151 and 152: LECTURE 17. DOUBLE INTEGRALS OVER G
- Page 153 and 154: LECTURE 17. DOUBLE INTEGRALS OVER G
- Page 155 and 156: LECTURE 17. DOUBLE INTEGRALS OVER G
- Page 157 and 158: Lecture 18 Double Integrals in Pola
- Page 159 and 160: LECTURE 18. DOUBLE INTEGRALS IN POL
- Page 161 and 162: LECTURE 18. DOUBLE INTEGRALS IN POL
- Page 163 and 164: LECTURE 18. DOUBLE INTEGRALS IN POL
- Page 165 and 166: LECTURE 18. DOUBLE INTEGRALS IN POL
- Page 167 and 168: Lecture 19 Surface Area with Double
- Page 169 and 170: LECTURE 19. SURFACE AREA WITH DOUBL
- Page 171 and 172: LECTURE 19. SURFACE AREA WITH DOUBL
- Page 173 and 174: Lecture 20 Triple Integrals Triple
- Page 175 and 176: LECTURE 20. TRIPLE INTEGRALS 163 Fi
- Page 177 and 178: LECTURE 20. TRIPLE INTEGRALS 165 so
- Page 179 and 180: LECTURE 20. TRIPLE INTEGRALS 167 Tr
- Page 181 and 182: Lecture 21 Vector Fields Definition
- Page 183 and 184: LECTURE 21. VECTOR FIELDS 171 Defin
- Page 185 and 186: LECTURE 21. VECTOR FIELDS 173 Examp
- Page 187 and 188: Lecture 22 Line Integrals Suppose t
- Page 189 and 190: LECTURE 22. LINE INTEGRALS 177 Exam
- Page 191 and 192: LECTURE 22. LINE INTEGRALS 179 ener
- Page 193 and 194: LECTURE 22. LINE INTEGRALS 181 The
- Page 195 and 196: LECTURE 22. LINE INTEGRALS 183 so t
- Page 197 and 198: LECTURE 22. LINE INTEGRALS 185 wher
- Page 199: LECTURE 22. LINE INTEGRALS 187 The
- Page 203 and 204: Lecture 23 Green’s Theorem Theore
- Page 205 and 206: LECTURE 23. GREEN’S THEOREM 193 T
- Page 207 and 208: Lecture 24 Flux Integrals & Gauss
- Page 209 and 210: LECTURE 24. FLUX INTEGRALS & GAUSS
- Page 211 and 212: LECTURE 24. FLUX INTEGRALS & GAUSS
- Page 213 and 214: Lecture 25 Stokes’ Theorem We hav
- Page 215 and 216: LECTURE 25. STOKES’ THEOREM 203 S
188 LECTURE 22. LINE INTEGRALS<br />
5. The line integral around a closed curve is zero, i.e.,<br />
∮<br />
F · dr = 0<br />
for all closed curves C.<br />
Example 22.5 Determine if<br />
is a gradient field.<br />
C<br />
F = ( x 2 − y 2 , −2xy, z )<br />
Solution. We calculate the curl F,<br />
⎛<br />
⎞ ⎛<br />
0 −D z D y x 2 − y 2 ⎞ ⎛<br />
⎞<br />
−D z (−2xy) + D y (z)<br />
∇F = ⎝ D z 0 −D x<br />
⎠ ⎝ −2xy ⎠ = ⎝ D z (x 2 − y 2 ) − D x (z) ⎠<br />
−D y D x 0 z −D y (x 2 − y 2 ) + D x (−2xy)<br />
= (0, 0, 2y − 2y) = 0<br />
Hence the field is a gradient field. <br />
Example 22.6 Determine if F = (−y, z, x) is a gradient field.<br />
Solution.<br />
⎛<br />
0 −D z D y<br />
∇F = ⎝ D z 0 −D x<br />
−D y D x 0<br />
= (−1, −1, 1) ≠ 0<br />
⎞ ⎛ ⎞ ⎛<br />
⎞<br />
−y −D z (z) + D y (x)<br />
⎠ ⎝ z ⎠ = ⎝ D z (−y) − D x (x) ⎠<br />
x −D y (−y) + D x (z)<br />
Hence the field is not a gradient field. <br />
Example 22.7 Find the potential function f(x, y, z) for the gradient field in example<br />
22.5.<br />
Solution. The vector field is<br />
F = (x 2 − y 2 , −2xy, z) = (M, N, P )<br />
where M = x 2 − y 2 , N = −2xy, and P = z. Since F is a gradient field, then for<br />
some scalar function f,<br />
f x = M = x 2 − y 2 (22.36)<br />
f y = N = −2xy (22.37)<br />
f z = P = z (22.38)<br />
Integrating the first equation with respect to x,<br />
∫ ∫<br />
f(x, y, z) = f x dx = (x 2 − y 2 )dx = 1 3 x3 − y 2 x + h(y, z) (22.39)<br />
Revised December 6, 2006. Math 250, Fall 2006