3D Geometry: Edge Cases and Subtle Traps (9)

hard 3 min read

Question

Find the shortest distance between the lines r=i^+2j^+3k^+λ(2i^+3j^+4k^)\vec{r} = \hat{i} + 2\hat{j} + 3\hat{k} + \lambda(2\hat{i} + 3\hat{j} + 4\hat{k}) and r=2i^+4j^+5k^+μ(3i^+4j^+5k^)\vec{r} = 2\hat{i} + 4\hat{j} + 5\hat{k} + \mu(3\hat{i} + 4\hat{j} + 5\hat{k}).

Solution — Step by Step

Line 1: passes through a1=(1,2,3)\vec{a}_1 = (1, 2, 3), direction b1=(2,3,4)\vec{b}_1 = (2, 3, 4). Line 2: passes through a2=(2,4,5)\vec{a}_2 = (2, 4, 5), direction b2=(3,4,5)\vec{b}_2 = (3, 4, 5).

b1×b2=i^j^k^234345=i^(1516)j^(1012)+k^(89)=i^+2j^k^\vec{b}_1 \times \vec{b}_2 = \begin{vmatrix} \hat{i} & \hat{j} & \hat{k} \\ 2 & 3 & 4 \\ 3 & 4 & 5 \end{vmatrix} = \hat{i}(15 - 16) - \hat{j}(10 - 12) + \hat{k}(8 - 9) = -\hat{i} + 2\hat{j} - \hat{k}

Magnitude: b1×b2=1+4+1=6|\vec{b}_1 \times \vec{b}_2| = \sqrt{1 + 4 + 1} = \sqrt{6}.

a2a1=(1,2,2)\vec{a}_2 - \vec{a}_1 = (1, 2, 2).

(a2a1)(b1×b2)=1(1)+2(2)+2(1)=1+42=1(\vec{a}_2 - \vec{a}_1) \cdot (\vec{b}_1 \times \vec{b}_2) = 1(-1) + 2(2) + 2(-1) = -1 + 4 - 2 = 1.

d=(a2a1)(b1×b2)b1×b2=16d = \frac{|(\vec{a}_2 - \vec{a}_1) \cdot (\vec{b}_1 \times \vec{b}_2)|}{|\vec{b}_1 \times \vec{b}_2|} = \frac{1}{\sqrt{6}}

Final answer: shortest distance =16= \dfrac{1}{\sqrt{6}} units.

Why This Works

The shortest distance between two skew lines is along their common perpendicular. The vector b1×b2\vec{b}_1 \times \vec{b}_2 points along this common perpendicular (perpendicular to both directions). Project a2a1\vec{a}_2 - \vec{a}_1 (the connector between any two specific points on the lines) onto this perpendicular direction, and take the magnitude. That’s the shortest distance.

If b1×b2=0\vec{b}_1 \times \vec{b}_2 = 0, the lines are parallel — different formula. If the dot product is zero but the cross product is not, the lines intersect (distance is 0).

Alternative Method

Parametrise: minimise P1P22|P_1 P_2|^2 where P1P_1 is on line 1 and P2P_2 is on line 2. Take partial derivatives with respect to λ\lambda and μ\mu, set them to zero, and find the critical λ,μ\lambda, \mu. Then compute the distance. This is heavy algebra but equivalent.

Edge case trap: if (a2a1)(b1×b2)=0(\vec{a}_2 - \vec{a}_1) \cdot (\vec{b}_1 \times \vec{b}_2) = 0, the lines are coplanar — they either intersect or are parallel. Always compute this scalar triple product first; a zero value tells us we don’t have skew lines.

Common Mistake

Forgetting the absolute value in the formula. The dot product can come out negative; distance is always positive. Also, students sometimes forget to divide by b1×b2|\vec{b}_1 \times \vec{b}_2|, treating it as a vector instead of a scalar. The output should be a number with units of length.

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