문제 은행 · 미적분 · 대학 미적분 · 벡터 미적분

발산 정리

닫힌 곡면을 지나는 플럭스를 내부 발산의 삼중적분으로 바꾼다

유형·난이도는 우리말 풀이가 붙은 문제는 선생님이 정했고, 나머지는 자동 분류라 다를 수 있어요. 난이도가 정해지지 않은 문제는 난이도로 거를 때 빠집니다.

2문제 · 1 / 1쪽

1.CLP-4 · 4.2절 · 1번대학 수준우리말 번역

VV 를 정육면체

V={ (x,y,z) ∣ 0≤x≤1, 0≤y≤1, 0≤z≤1 }\begin{aligned} V=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le y\le 1,\ 0\le z\le 1\ \big\} \end{aligned}

라 하고, RR 를 정사각형

R={ (x,y) ∣ 0≤x≤1, 0≤y≤1 }\begin{aligned} R=\big\{ \ (x,y)\ \big|\ 0\le x\le 1,\ 0\le y\le 1\ \big\} \end{aligned}

라 하자. 또 f(x,y,z)f(x,y,z) 는 연속인 일계 편도함수를 가진다고 하자.

(a) 미적분의 기본정리를 이용하여

∭V∂f∂z(x,y,z) dx dy dz=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z =\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

임을 보이세요. (b) 발산정리를 이용하여

∭V∂f∂z(x,y,z) dx dy dz=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z =\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

임을 보이세요.

영어 원문 보기

Let VV be the cube

V={ (x,y,z) ∣ 0≤x≤1, 0≤y≤1, 0≤z≤1 }\begin{aligned} V=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le y\le 1,\ 0\le z\le 1\ \big\} \end{aligned}

and RR be the square

R={ (x,y) ∣ 0≤x≤1, 0≤y≤1 }\begin{aligned} R=\big\{ \ (x,y)\ \big|\ 0\le x\le 1,\ 0\le y\le 1\ \big\} \end{aligned}

and let f(x,y,z)f(x,y,z) have continuous first partial derivatives.

(a) Use the fundamental theorem of calculus to show that

∭V∂f∂z(x,y,z) dx dy dz=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z =\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned} (b) Use the divergence theorem to show that

∭V∂f∂z(x,y,z) dx dy dz=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z =\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

정답·풀이 보기

(a) 좌변을 zz 를 가장 안쪽 적분변수로 하는 반복적분으로 나타내면 다음과 같다.

∭V∂f∂z(x,y,z) dx dy dz=∫01dx∫01dy[∫01dz ∂f∂z(x,y,z)]=∫01dx∫01dy [f(x,y,1)−f(x,y,0)]미적분의 기본정리에 의해=∬R[f(x,y,1)−f(x,y,0)] dx dy=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z &=\int_0^1\mathrm{d}x\int_0^1\mathrm{d}y\left[\int_0^1\mathrm{d}z\ \frac{\partial f}{\partial z}(x,y,z)\right] \\ &=\int_0^1\mathrm{d}x\int_0^1\mathrm{d}y\ \big[f(x,y,1)-f(x,y,0)\big] \\ &\text{미적분의 기본정리에 의해} \\ &=\iint _R\big[f(x,y,1)-f(x,y,0)\big]\ \mathrm{d}x\,\mathrm{d}y \\ &=\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

(b) 벡터장 F(x,y,z)=f(x,y,z) k^\mathbf{F}(x,y,z) = f(x,y,z)\,\hat{\mathbf{k}} 를 정의하자. 그러면 F\mathbf{F} 의 발산은 ∇⋅F(x,y,z)=∂f∂z(x,y,z){ \boldsymbol{\nabla} }\cdot\mathbf{F}(x,y,z) = \frac{\partial f}{\partial z}(x,y,z) 이다. 정육면체 VV 의 경계는 다음 여섯 면의 합집합이다.

S1={ (x,y,z) ∣ 0≤x≤1, 0≤y≤1, z=1 }바깥쪽 법선벡터는 n^=k^S2={ (x,y,z) ∣ 0≤x≤1, 0≤y≤1, z=0 }바깥쪽 법선벡터는 n^=−k^S3={ (x,y,z) ∣ 0≤x≤1, 0≤z≤1, y=1 }바깥쪽 법선벡터는 n^=ȷ^S4={ (x,y,z) ∣ 0≤x≤1, 0≤z≤1, y=0 }바깥쪽 법선벡터는 n^=−ȷ^S5={ (x,y,z) ∣ 0≤y≤1, 0≤z≤1, x=1 }바깥쪽 법선벡터는 n^=ı^S6={ (x,y,z) ∣ 0≤y≤1, 0≤z≤1, x=0 }바깥쪽 법선벡터는 n^=−ı^\begin{aligned} S_1&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le y\le 1,\ z=1\ \big\}\quad \text{바깥쪽 법선벡터는 $\hat{\mathbf{n}}=\hat{\mathbf{k}}$} \\ S_2&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le y\le 1,\ z=0\ \big\}\quad \text{바깥쪽 법선벡터는 $\hat{\mathbf{n}}=-\hat{\mathbf{k}}$} \\ S_3&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le z\le 1,\ y=1\ \big\}\quad \text{바깥쪽 법선벡터는 $\hat{\mathbf{n}}=\hat{\boldsymbol{\jmath}}$} \\ S_4&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le z\le 1,\ y=0\ \big\}\quad \text{바깥쪽 법선벡터는 $\hat{\mathbf{n}}=-\hat{\boldsymbol{\jmath}}$} \\ S_5&=\big\{ \ (x,y,z)\ \big|\ 0\le y\le 1,\ 0\le z\le 1,\ x=1\ \big\}\quad \text{바깥쪽 법선벡터는 $\hat{\mathbf{n}}=\hat{\boldsymbol{\imath}}$} \\ S_6&=\big\{ \ (x,y,z)\ \big|\ 0\le y\le 1,\ 0\le z\le 1,\ x=0\ \big\}\quad \text{바깥쪽 법선벡터는 $\hat{\mathbf{n}}=-\hat{\boldsymbol{\imath}}$} \end{aligned}

그림

다음에 주목하자.

F⋅n^=f k^⋅n^={+fS1 위에서−fS2 위에서0S3, S4, S5, S6 위에서\begin{aligned} \mathbf{F}\cdot\hat{\mathbf{n}} = f\,\hat{\mathbf{k}}\cdot\hat{\mathbf{n}} = \begin{cases} +f &\text{$S_1$ 위에서} \\ -f &\text{$S_2$ 위에서} \\ 0 &\text{$S_3$, $S_4$, $S_5$, $S_6$ 위에서} \end{cases} \end{aligned}

따라서 발산정리에 의해 다음을 얻는다.

∭V∂f∂z(x,y,z) dx dy dz=∭V∇⋅F(x,y,z) dx dy dz=∬∂VF⋅n^ dS=∑j=16∬SjF⋅n^ dS=∬S1f dS−∬S2f dS=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z &=\iiint _V { \boldsymbol{\nabla} }\cdot\mathbf{F}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z \\ &= \iint _{\partial V} \mathbf{F}\cdot\hat{\mathbf{n}}\ \mathrm{d}S =\sum_{j=1}^6 \iint _{S_j} \mathbf{F}\cdot\hat{\mathbf{n}}\ \mathrm{d}S\\ &=\iint _{S_1} f\ \mathrm{d}S -\iint _{S_2} f\ \mathrm{d}S \\ &=\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

원본 교재 풀이(영어)

(a) Expressing the left hand side as an iterated integral, with zz as the innermost integration variable, we have

∭V∂f∂z(x,y,z) dx dy dz=∫01dx∫01dy[∫01dz ∂f∂z(x,y,z)]=∫01dx∫01dy [f(x,y,1)−f(x,y,0)]by the fundamental theorem of calculus=∬R[f(x,y,1)−f(x,y,0)] dx dy=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z &=\int_0^1\mathrm{d}x\int_0^1\mathrm{d}y\left[\int_0^1\mathrm{d}z\ \frac{\partial f}{\partial z}(x,y,z)\right] \\ &=\int_0^1\mathrm{d}x\int_0^1\mathrm{d}y\ \big[f(x,y,1)-f(x,y,0)\big] \\ &\text{by the fundamental theorem of calculus} \\ &=\iint _R\big[f(x,y,1)-f(x,y,0)\big]\ \mathrm{d}x\,\mathrm{d}y \\ &=\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

(b) Define the vector field F(x,y,z)=f(x,y,z) k^\mathbf{F}(x,y,z) = f(x,y,z)\,\hat{\mathbf{k}}. Then the divergence of F\mathbf{F} is ∇⋅F(x,y,z)=∂f∂z(x,y,z){ \boldsymbol{\nabla} }\cdot\mathbf{F}(x,y,z) = \frac{\partial f}{\partial z}(x,y,z). The boundary of the cube VV is the union of six faces

S1={ (x,y,z) ∣ 0≤x≤1, 0≤y≤1, z=1 }with outward normal n^=k^S2={ (x,y,z) ∣ 0≤x≤1, 0≤y≤1, z=0 }with outward normal n^=−k^S3={ (x,y,z) ∣ 0≤x≤1, 0≤z≤1, y=1 }with outward normal n^=ȷ^S4={ (x,y,z) ∣ 0≤x≤1, 0≤z≤1, y=0 }with outward normal n^=−ȷ^S5={ (x,y,z) ∣ 0≤y≤1, 0≤z≤1, x=1 }with outward normal n^=ı^S6={ (x,y,z) ∣ 0≤y≤1, 0≤z≤1, x=0 }with outward normal n^=−ı^\begin{aligned} S_1&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le y\le 1,\ z=1\ \big\}\quad \text{with outward normal $\hat{\mathbf{n}}=\hat{\mathbf{k}}$} \\ S_2&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le y\le 1,\ z=0\ \big\}\quad \text{with outward normal $\hat{\mathbf{n}}=-\hat{\mathbf{k}}$} \\ S_3&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le z\le 1,\ y=1\ \big\}\quad \text{with outward normal $\hat{\mathbf{n}}=\hat{\boldsymbol{\jmath}}$} \\ S_4&=\big\{ \ (x,y,z)\ \big|\ 0\le x\le 1,\ 0\le z\le 1,\ y=0\ \big\}\quad \text{with outward normal $\hat{\mathbf{n}}=-\hat{\boldsymbol{\jmath}}$} \\ S_5&=\big\{ \ (x,y,z)\ \big|\ 0\le y\le 1,\ 0\le z\le 1,\ x=1\ \big\}\quad \text{with outward normal $\hat{\mathbf{n}}=\hat{\boldsymbol{\imath}}$} \\ S_6&=\big\{ \ (x,y,z)\ \big|\ 0\le y\le 1,\ 0\le z\le 1,\ x=0\ \big\}\quad \text{with outward normal $\hat{\mathbf{n}}=-\hat{\boldsymbol{\imath}}$} \end{aligned}

figure

Observe that

F⋅n^=f k^⋅n^={+fon S1−fon S20on S3, S4, S5, S6\begin{aligned} \mathbf{F}\cdot\hat{\mathbf{n}} = f\,\hat{\mathbf{k}}\cdot\hat{\mathbf{n}} = \begin{cases} +f &\text{on $S_1$} \\ -f &\text{on $S_2$} \\ 0 &\text{on $S_3$, $S_4$, $S_5$, $S_6$} \end{cases} \end{aligned}

So the divergence theorem gives

∭V∂f∂z(x,y,z) dx dy dz=∭V∇⋅F(x,y,z) dx dy dz=∬∂VF⋅n^ dS=∑j=16∬SjF⋅n^ dS=∬S1f dS−∬S2f dS=∬Rf(x,y,1) dx dy−∬Rf(x,y,0) dx dy\begin{aligned} \iiint _V\frac{\partial f}{\partial z}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z &=\iiint _V { \boldsymbol{\nabla} }\cdot\mathbf{F}(x,y,z)\ \mathrm{d}x\,\mathrm{d}y\,\mathrm{d}z \\ &= \iint _{\partial V} \mathbf{F}\cdot\hat{\mathbf{n}}\ \mathrm{d}S =\sum_{j=1}^6 \iint _{S_j} \mathbf{F}\cdot\hat{\mathbf{n}}\ \mathrm{d}S\\ &=\iint _{S_1} f\ \mathrm{d}S -\iint _{S_2} f\ \mathrm{d}S \\ &=\iint _R f(x,y,1)\ \mathrm{d}x\,\mathrm{d}y - \iint _R f(x,y,0)\ \mathrm{d}x\,\mathrm{d}y \end{aligned}

한 번 더 — 비슷한 문제 풀기CLP-4 · 4.2절 · 36번
# 발산 정리증명·논술기본자동 분류
CLP-4 Vector Calculus CC BY-NC-SA 4.0우리말 번역: 빌드라인 스쿨 — AI 번역·자동 검토(원문과 같은 조건)
2.CLP-4 · 4.2절 · 2번대학 수준우리말 번역

(a) a\mathbf{a} 가 임의의 상수 벡터일 때, F=ϕ a\mathbf{F}=\phi\,\mathbf{a} 에 발산 정리를 적용하여 다음을 보이세요.

∭V∇ϕ dV=∬∂Vϕ n^ dS\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V=\iint _{\partial V}\phi\,\hat{\mathbf{n}}\,\mathrm{d}S (b) 부피가 ∣V∣|V| 인 입체 VV 의 무게중심 (xˉ,yˉ,zˉ)(\bar x,\bar y,\bar z) 가 다음과 같이 주어짐을 보이세요.

(xˉ,yˉ,zˉ)=12∣V∣∬∂V(x2+y2+z2) n^ dS(\bar x,\bar y,\bar z)=\frac{1}{2|V|}\iint _{\partial V} (x^2+y^2+z^2)\,\hat{\mathbf{n}}\,\mathrm{d}S

영어 원문 보기

(a) By applying the divergence theorem to F=ϕ a\mathbf{F}=\phi\,\mathbf{a}, where a\mathbf{a} is an arbitrary constant vector, show that

∭V∇ϕ dV=∬∂Vϕ n^ dS\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V=\iint _{\partial V}\phi\,\hat{\mathbf{n}}\,\mathrm{d}S (b) Show that the centroid (xˉ,yˉ,zˉ)(\bar x,\bar y,\bar z) of a solid VV with volume ∣V∣|V| is given by

(xˉ,yˉ,zˉ)=12∣V∣∬∂V(x2+y2+z2) n^ dS(\bar x,\bar y,\bar z)=\frac{1}{2|V|}\iint _{\partial V} (x^2+y^2+z^2)\,\hat{\mathbf{n}}\,\mathrm{d}S

정답·풀이 보기

(a) ϕ a\phi\,\mathbf{a} 의 발산은 ∇⋅(ϕ a)=∇ϕ⋅a+ϕ∇⋅a=∇ϕ⋅a{ \boldsymbol{\nabla} }\cdot(\phi\,\mathbf{a}) ={ \boldsymbol{\nabla} }\phi\cdot\mathbf{a}+\phi{ \boldsymbol{\nabla} }\cdot\mathbf{a}={ \boldsymbol{\nabla} }\phi\cdot\mathbf{a} 이다. a\mathbf{a} 가 상수이기 때문이다. 따라서 발산 정리에 의해

∬∂Vϕ a⋅n^ dS=∭V∇⋅(ϕ a) dV=∭V∇ϕ⋅a dV  ⟹  [∬∂Vϕn^ dS−∭V∇ϕ dV]⋅a=0\iint _{\partial V}\phi\,\mathbf{a}\cdot\hat{\mathbf{n}}\,\mathrm{d}S =\iiint _V{ \boldsymbol{\nabla} }\cdot(\phi\,\mathbf{a})\ \mathrm{d}V =\iiint _V { \boldsymbol{\nabla} }\phi\cdot\mathbf{a}\ \mathrm{d}V \implies \left[\iint _{\partial V}\phi\hat{\mathbf{n}}\,\mathrm{d}S -\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V\right]\cdot\mathbf{a}=0

이는 모든 벡터 a\mathbf{a} 에 대해 성립한다. 특히 a=ı^,ȷ^,k^\mathbf{a}=\hat{\boldsymbol{\imath}},\hat{\boldsymbol{\jmath}},\hat{\mathbf{k}} 로 놓으면 [∬∂Vϕn^ dS−∭V∇ϕ dV]\left[\iint _{\partial V}\phi\hat{\mathbf{n}}\,\mathrm{d}S -\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V\right] 의 세 성분이 모두 0이다. 따라서

∬∂Vϕ n^ dS−∭V∇ϕ dV=0\iint _{\partial V}\phi\,\hat{\mathbf{n}}\,\mathrm{d}S-\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V=0

(b) (a)에서 ϕ=x2+y2+z2\phi=x^2+y^2+z^2 이고 ∇ϕ=2x ı^+2y ȷ^+2z k^{ \boldsymbol{\nabla} }\phi = 2x\,\hat{\boldsymbol{\imath}}+2y\,\hat{\boldsymbol{\jmath}}+2z\,\hat{\mathbf{k}} 이므로

12∣V∣∬∂V(x2+y2+z2) n^ dS=12∣V∣∭V(2x ı^+2y ȷ^+2z k^) dV=(xˉ,yˉ,zˉ)\frac{1}{2|V|}\iint _{\partial V} (x^2+y^2+z^2)\,\hat{\mathbf{n}}\,\mathrm{d}S =\frac{1}{2|V|} \iiint _V (2x\,\hat{\boldsymbol{\imath}}+2y\,\hat{\boldsymbol{\jmath}}+2z\,\hat{\mathbf{k}})\,\mathrm{d}V =(\bar x,\bar y,\bar z)

원본 교재 풀이(영어)

(a) The divergence of ϕ a\phi\,\mathbf{a} is ∇⋅(ϕ a)=∇ϕ⋅a+ϕ∇⋅a=∇ϕ⋅a{ \boldsymbol{\nabla} }\cdot(\phi\,\mathbf{a}) ={ \boldsymbol{\nabla} }\phi\cdot\mathbf{a}+\phi{ \boldsymbol{\nabla} }\cdot\mathbf{a}={ \boldsymbol{\nabla} }\phi\cdot\mathbf{a}, since a\mathbf{a} is constant. So, by the divergence theorem,

∬∂Vϕ a⋅n^ dS=∭V∇⋅(ϕ a) dV=∭V∇ϕ⋅a dV  ⟹  [∬∂Vϕn^ dS−∭V∇ϕ dV]⋅a=0\iint _{\partial V}\phi\,\mathbf{a}\cdot\hat{\mathbf{n}}\,\mathrm{d}S =\iiint _V{ \boldsymbol{\nabla} }\cdot(\phi\,\mathbf{a})\ \mathrm{d}V =\iiint _V { \boldsymbol{\nabla} }\phi\cdot\mathbf{a}\ \mathrm{d}V \implies \left[\iint _{\partial V}\phi\hat{\mathbf{n}}\,\mathrm{d}S -\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V\right]\cdot\mathbf{a}=0

This is true for all vectors a\mathbf{a}. In particular, applying this with a=ı^,ȷ^,k^\mathbf{a}=\hat{\boldsymbol{\imath}},\hat{\boldsymbol{\jmath}},\hat{\mathbf{k}}, we have that all three components of [∬∂Vϕn^ dS−∭V∇ϕ dV]\left[\iint _{\partial V}\phi\hat{\mathbf{n}}\,\mathrm{d}S -\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V\right] are zero. So

∬∂Vϕ n^ dS−∭V∇ϕ dV=0\iint _{\partial V}\phi\,\hat{\mathbf{n}}\,\mathrm{d}S-\iiint _V { \boldsymbol{\nabla} }\phi\,\mathrm{d}V=0

(b) By part (a), with ϕ=x2+y2+z2\phi=x^2+y^2+z^2 and ∇ϕ=2x ı^+2y ȷ^+2z k^{ \boldsymbol{\nabla} }\phi = 2x\,\hat{\boldsymbol{\imath}}+2y\,\hat{\boldsymbol{\jmath}}+2z\,\hat{\mathbf{k}},

12∣V∣∬∂V(x2+y2+z2) n^ dS=12∣V∣∭V(2x ı^+2y ȷ^+2z k^) dV=(xˉ,yˉ,zˉ)\frac{1}{2|V|}\iint _{\partial V} (x^2+y^2+z^2)\,\hat{\mathbf{n}}\,\mathrm{d}S =\frac{1}{2|V|} \iiint _V (2x\,\hat{\boldsymbol{\imath}}+2y\,\hat{\boldsymbol{\jmath}}+2z\,\hat{\mathbf{k}})\,\mathrm{d}V =(\bar x,\bar y,\bar z)

한 번 더 — 비슷한 문제 풀기CLP-4 · 4.2절 · 15번
# 발산 정리증명·논술기본자동 분류
CLP-4 Vector Calculus CC BY-NC-SA 4.0우리말 번역: 빌드라인 스쿨 — AI 번역·자동 검토(원문과 같은 조건)