Variational inequalities and obstacle problems
Derive one-sided optimality for a convex feasible set and solve a one-dimensional contact problem with a verified reaction force.
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The question for today
What you’ll understand
- Derive the variational inequality from feasible line segments.
- Establish existence and uniqueness for a closed convex obstacle set.
- Verify contact, noncontact, and reaction conditions in an explicit solution.
A membrane cannot pass through a rigid obstacle, so some variations are allowed only upward where contact occurs. Requiring the first variation to vanish for every direction would permit forbidden downward motion and give the wrong equation. The correct statement is a variational inequality over feasible competitors. For a strictly convex quadratic energy this inequality is both necessary and sufficient for the unique minimum. The unknown region of contact then separates places where the usual differential equation holds from places where the obstacle supplies an additional reaction.
Use a feasible segment rather than an arbitrary line
On the unit interval let the obstacle have nonpositive endpoint traces, and let the admissible set be functions in lying above it almost everywhere. The positive part of the obstacle is an admissible function, so the set is nonempty. In one dimension continuous representatives make the contact geometry meaningful. The set is norm closed and convex, hence weakly closed. Let the load be square integrable and use derivative energy minus the load pairing.
For any feasible competitor, the segment from a minimizer to that competitor stays feasible by convexity. Differentiate only in the forward segment direction. A minimum at the starting point gives a nonnegative right derivative rather than a zero two-sided derivative. This yields the variational inequality. Conversely, expand the quadratic energy around any candidate satisfying that inequality: the linear term is nonnegative and the remaining squared derivative term is nonnegative, proving global minimality and uniqueness.
Existence and the reaction interpretation
The direct method applies: the obstacle set is weakly closed, the quadratic energy is coercive by Poincaré and Cauchy–Schwarz, and its derivative norm term is weakly lower semicontinuous. Strict convexity on zero-trace functions gives uniqueness. The solution is initially a Sobolev function. Statements about classical second derivatives or smooth free boundaries require additional regularity assumptions and cannot be concluded from existence alone. Even smooth data can produce a solution whose second derivative jumps between contact and noncontact regions.
For a sufficiently regular solution, define the reaction . Feasible nonnegative variations show this is nonnegative in the distributional sense. Where the solution lies strictly above a continuous obstacle, compactly supported variations of either sign are permitted, forcing the reaction to vanish and restoring . Under enough regularity to multiply and interpret the terms, the contact condition is . In the general weak setting, formulate reaction and complementarity using dual pairings rather than assuming a pointwise multiplier function.
Verify a candidate across the contact boundary
An explicit candidate needs more than solving the noncontact differential equation. Check its endpoint traces, its position relative to the obstacle, and continuity of its derivative at a proposed contact boundary. A slope jump creates a distributional point reaction whose sign must be included; it cannot be ignored by checking second derivatives only away from the join. A continuously matched slope avoids such hidden delta contributions in the example below and makes the piecewise reaction a genuine bounded function.
Once a candidate has a nonnegative reaction supported where it touches the obstacle, integrate by parts against a feasible difference. On contact, the competitor cannot lie below the candidate, so the reaction pairing is nonnegative; elsewhere the reaction is zero. This proves the full variational inequality and therefore global minimality. The method is a certificate over all feasible competitors, not merely a plot of two curves or an assertion that the contact region looks plausible. Higher-dimensional regularity and free-boundary geometry are deeper questions beyond this one-dimensional construction.
Work it through
A membrane supported by a central obstacle
With zero load, minimize above the obstacle , using zero endpoint traces. Verify the candidate that is linear near each end and equals the obstacle in the center.
At a left joining point , match the line to the obstacle and its slope: and . Combining gives , so and . Symmetry gives the right join at .
Take on , on , and on . On the left, , with the corresponding reflected square on the right. The values and slopes match at both joins.
The reaction is zero on the linear pieces and two on the central contact interval. It is nonnegative and supported on contact, so for every feasible competitor.
This piecewise continuously differentiable candidate satisfies the full variational inequality and is the unique global minimizer. Its second derivative changes across the free boundary.
The living notebook
Explore the model
Interactive lab · function
A nonnegative gap at a contact join
The worked candidate's left gap is . Reset and set both instrument coefficient and position ; treating the instrument coordinate as displacement from the join, predict gap and slope . Reset and set both ; predict zero gap and zero slope at contact. The instrument shows this local gap parabola, not the full obstacle solution or an automatic contact solver.
- y at chosen x
- 0.608
- Tangent slope · 2ax
- 1.35
- Signed area · ax³/3
- 0.182
This lab uses only y = ax². Playback traces the curve within the fixed integration interval from 0 to x; it does not estimate numerical error or change the chosen point. Parameter changes pause playback and recompute the model at the current elapsed time. Reset restores both parameters and returns time to zero. Playback starts paused. Adjust either parameter, then choose Play or Step.
Look forA valid contact join requires nonnegative gap and the correct derivative matching, not just intersecting curves.
Pause & reason
Check your understanding
Your turn
Try it yourself
On with obstacle zero and load , minimize . Verify the solution and its reaction using the variational inequality.
Take a moment to make a prediction or work it out on paper. Open a hint when you need one.
Give me a hint
Every feasible function is nonnegative. Test the zero candidate before solving an unconstrained differential equation.
Compare with the solution
The candidate is feasible. For every , the inequality becomes , which holds. The reaction is , and complementarity holds because the candidate contacts the obstacle everywhere. Strict convexity gives uniqueness. The unconstrained equation would allow a negative deflection and would solve a different problem.
Keep the idea
Take it with you
- Convex feasible sets give a first-order inequality along feasible segments.
- For a convex quadratic energy, that inequality certifies the unique global minimizer.
- Reaction, gap, and derivative matching must all be checked across contact boundaries.
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