Related Formula
p = K( a + λ b)$$\vec{p} = K(\vec{a} + \lambda\vec{b})$$
p · a = 0$$\vec{p} \cdot \vec{a} = 0$$
Core Logic
Formulate a coplanar parameterization vector, apply the zero dot-product geometric orthogonality constraint to pin down the linear parameter, and then normalize.
Step 1: Define Coplanar Structural Form
Let the targeting vector path be:
p = K( a + λ b) = K( (1+2λ) i + (2+λ) j + (1-λ) k )$$\vec{p} = K(\vec{a} + \lambda\vec{b}) = K\left( (1+2\lambda)\hat{i} + (2+\lambda)\hat{j} + (1-\lambda)\hat{k} \right)$$
Step 2: Force Orthogonality Constraint
Impose p · a = 0$\vec{p} \cdot \vec{a} = 0$:
1(1+2λ) + 2(2+λ) + 1(1-λ) = 0$$1(1+2\lambda) + 2(2+\lambda) + 1(1-\lambda) = 0$$
1 + 2λ + 4 + 2λ + 1 - λ = 0 6 + 3λ = 0 λ = -2$$1 + 2\lambda + 4 + 2\lambda + 1 - \lambda = 0 \implies 6 + 3\lambda = 0 \implies \lambda = -2$$
Step 3: Substitute and Normalize
Substitute λ = -2$\lambda = -2$ back into the base formulation:
p = K(-3 i + 3 k)$$\vec{p} = K(-3\hat{i} + 3\hat{k})$$
Normalizing to turn this vector into a proper unit scale form:
c = ± - i + k√(2)$$\hat{c} = \pm \frac{-\hat{i} + \hat{k}}{\sqrt{2}}$$
Pattern Recognition
Finding coplanar vectors orthogonal to one base component matches taking cross expansions like ( a × b) × a$(\vec{a} \times \vec{b}) \times \vec{a}$ up to scalar metrics.
Chapter Mix
Class 12 Mathematics: Vector Algebra