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Question: Let $\overrightarrow{V}=2\hat{i}+\hat{j}-\hat{k}$, $\overrightarrow{W}=\hat{i}+3\hat{k}$, $|\overrig...

Let V=2i^+j^k^\overrightarrow{V}=2\hat{i}+\hat{j}-\hat{k}, W=i^+3k^\overrightarrow{W}=\hat{i}+3\hat{k}, U=2|\overrightarrow{U}|=2. If U\overrightarrow{U} is a vector in x-y plane, then greatest value of ([UVW])2([\overrightarrow{U}\overrightarrow{V}\overrightarrow{W}])^2 is -

A

232

B

340

C

236

D

312

Answer

232

Explanation

Solution

The scalar triple product [UVW][\overrightarrow{U}\overrightarrow{V}\overrightarrow{W}] is given by U(V×W)\overrightarrow{U} \cdot (\overrightarrow{V} \times \overrightarrow{W}).

First, calculate the cross product V×W\overrightarrow{V} \times \overrightarrow{W}: V=2i^+j^k^\overrightarrow{V} = 2\hat{i}+\hat{j}-\hat{k} W=i^+3k^=i^+0j^+3k^\overrightarrow{W} = \hat{i}+3\hat{k} = \hat{i}+0\hat{j}+3\hat{k} V×W=i^j^k^211103=i^(13(1)0)j^(23(1)1)+k^(2011)\overrightarrow{V} \times \overrightarrow{W} = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ 2 & 1 & -1 \\ 1 & 0 & 3 \end{vmatrix} = \hat{i}(1 \cdot 3 - (-1) \cdot 0) - \hat{j}(2 \cdot 3 - (-1) \cdot 1) + \hat{k}(2 \cdot 0 - 1 \cdot 1) =i^(3)j^(6+1)+k^(01)=3i^7j^k^= \hat{i}(3) - \hat{j}(6 + 1) + \hat{k}(0 - 1) = 3\hat{i} - 7\hat{j} - \hat{k}.

Let P=V×W=3i^7j^k^\overrightarrow{P} = \overrightarrow{V} \times \overrightarrow{W} = 3\hat{i} - 7\hat{j} - \hat{k}. We are given that U\overrightarrow{U} is a vector in the x-y plane and U=2|\overrightarrow{U}| = 2. Let U=uxi^+uyj^\overrightarrow{U} = u_x\hat{i} + u_y\hat{j}. The condition U=2|\overrightarrow{U}| = 2 means ux2+uy2=2\sqrt{u_x^2 + u_y^2} = 2, or ux2+uy2=4u_x^2 + u_y^2 = 4.

The scalar triple product is [UVW]=UP=(uxi^+uyj^)(3i^7j^k^)[\overrightarrow{U}\overrightarrow{V}\overrightarrow{W}] = \overrightarrow{U} \cdot \overrightarrow{P} = (u_x\hat{i} + u_y\hat{j}) \cdot (3\hat{i} - 7\hat{j} - \hat{k}) =ux(3)+uy(7)+0(1)=3ux7uy= u_x(3) + u_y(-7) + 0(-1) = 3u_x - 7u_y.

We want to find the greatest value of ([UVW])2=(3ux7uy)2([\overrightarrow{U}\overrightarrow{V}\overrightarrow{W}])^2 = (3u_x - 7u_y)^2, subject to the constraint ux2+uy2=4u_x^2 + u_y^2 = 4.

We can use the Cauchy-Schwarz inequality. For two vectors a=(a1,a2)\vec{a} = (a_1, a_2) and b=(b1,b2)\vec{b} = (b_1, b_2), (ab)2a2b2(\vec{a} \cdot \vec{b})^2 \le |\vec{a}|^2 |\vec{b}|^2. Let a=(ux,uy)\vec{a} = (u_x, u_y) and b=(3,7)\vec{b} = (3, -7). Then ab=3ux7uy\vec{a} \cdot \vec{b} = 3u_x - 7u_y. a2=ux2+uy2=4|\vec{a}|^2 = u_x^2 + u_y^2 = 4. b2=32+(7)2=9+49=58|\vec{b}|^2 = 3^2 + (-7)^2 = 9 + 49 = 58.

Applying the Cauchy-Schwarz inequality: (3ux7uy)2(ux2+uy2)(32+(7)2)(3u_x - 7u_y)^2 \le (u_x^2 + u_y^2)(3^2 + (-7)^2) (3ux7uy)2(4)(58)(3u_x - 7u_y)^2 \le (4)(58) (3ux7uy)2232(3u_x - 7u_y)^2 \le 232.

The maximum value of (3ux7uy)2(3u_x - 7u_y)^2 is 232.

Alternatively, using parametrization: Let ux=2cosθu_x = 2\cos\theta and uy=2sinθu_y = 2\sin\theta. 3ux7uy=3(2cosθ)7(2sinθ)=6cosθ14sinθ3u_x - 7u_y = 3(2\cos\theta) - 7(2\sin\theta) = 6\cos\theta - 14\sin\theta. The expression acosθ+bsinθa\cos\theta + b\sin\theta has a maximum value of a2+b2\sqrt{a^2 + b^2} and a minimum value of a2+b2-\sqrt{a^2 + b^2}. Here, a=6a=6 and b=14b=-14. The maximum value of 6cosθ14sinθ6\cos\theta - 14\sin\theta is 62+(14)2=36+196=232\sqrt{6^2 + (-14)^2} = \sqrt{36 + 196} = \sqrt{232}.

So, the value of (3ux7uy)2(3u_x - 7u_y)^2 ranges from 00 to (232)2=232(\sqrt{232})^2 = 232. The greatest value is 232.