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Lax–Friedrichs flux under the invariant-interval CFL bound
Example
Assume , and additionally assume Dependent Choice when .
Let be a compact invariant interval, let , and choose finite with on and . The Lax–Friedrichs flux is consistent, nondecreasing in , nonincreasing in , and has coordinate Lipschitz bounds . Thus any bounded BV datum in and mesh family satisfying falls under Strong entropy convergence of monotone finite-volume schemes.
Facts & Assumptions
Given: Countable Choice , the compact interval , , constants with on , bounded BV data in , and the displayed numerical flux; additionally assume Dependent Choice when .
A continuous real-valued function on a compact interval is bounded, so a finite exists for on (A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value).
If is continuous on and differentiable on , then for some (The mean value theorem, as the case of Cauchy's: for continuous on with and differentiable on there is with ).
The full invariant-interval CFL condition uses the sum of coordinate Lipschitz bounds, and under —with DC additionally on the branch—the convergence theorem requires a positive lower bound for (Monotone finite-volume scheme and invariant-interval CFL, The Axiom of Countable Choice (), The axiom of dependent choice: a relation in which every element is related to something admits an -indexed chain, Strong entropy convergence of monotone finite-volume schemes).
is bounded and has finite translation variation (Bounded BV data on the real line).
Verification
On the diagonal, , so the flux is consistent. If , the first-coordinate difference is zero; if , the mean-value theorem gives Thus it is nondecreasing in its first coordinate.
If , the second-coordinate difference is zero; if , the mean-value theorem gives so it is nonincreasing in its second coordinate. The mean-value bounds on each variable also give .
Since is locally Lipschitz and the flux adds a linear term, is locally Lipschitz. The displayed flux is consistent by its diagonal formula, and steps 1.1 and 1.2 prove monotonicity with coordinate bounds whose sum is . Hence the displayed upper ratio gives the full CFL condition, while the lower ratio and bounded BV data satisfy the remaining hypotheses of [F3]. The convergence theorem applies.
Depends on
- Bounded BV data on the real line
- Monotone finite-volume scheme and invariant-interval CFL
- A continuous real-valued function on a nonempty compact metric space is bounded and attains a greatest and a least value
- The mean value theorem, as the case $g(x) = x$ of Cauchy's: for $f$ continuous on $[a,b]$ with $a < b$ and differentiable on $(a,b)$ there is $c \in (a,b)$ with $f(b) - f(a) = f'(c)(b-a)$
- The Axiom of Countable Choice ($\mathrm{AC}_\omega$)
- The axiom of dependent choice: a relation in which every element is related to something admits an $\mathbb{N}$-indexed chain
- Strong entropy convergence of monotone finite-volume schemes
Used by
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Sources
- Jérôme Droniou, A beginner’s course in finite volume approximation of scalar conservation laws, complete lecture note (standard reference, not scraped)
- Siddhartha Mishra, Ulrik S. Fjordholm and Rémi Abgrall, Numerical Methods for Conservation Laws, ETH lecture notes (standard reference, not scraped)