An optimization-based discontinuous Galerkinapproach for high-order shock tracking

Matthew J. Zahr† and Per-Olof Persson5th International Workshop on High Order CFD MethodsTest Case: CI1 - Inviscid Bow ShockGaylord Palms, Kissimmee, FlordiaJanuary 6, 2018

† Luis W. Alvarez Postdoctoral FellowDepartment of MathematicsLawrence Berkeley National Laboratory

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Proposed shock tracking method

• Key observationin a discontinuous Galerkin or finite volume setting, if (curved) face of an

element is perfectly aligned with the (unknown) shock, the Riemann solver willprovide appropriate stabilization and allow for high-order approximations of

the solution on both sides of the discontinuity

• Propose a PDE-constrained optimization framework to simultaneously alignmesh with shock and solve discrete PDE

Non-aligned (left) vs. discontinuity-aligned (right) mesh and corresponding solution

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Shock tracking optimization formulation

• Consider the spatial discretization of the conservation law

∇ · F(U(x)) = 0, x ∈ Ω → r(u, x) = 0

• U , x are the conservation law state vector and domain coordinate• x contains the coordinates of the continuous, high-order mesh nodes• u contains the discrete state vector corresponding to U at the mesh nodes

• Fundamental requirement on discretization: basis supports discontinutiesalong element faces, i.e., discontinuous Galerkin, finite volume

• Shock tracking formulation

minimizeu,x

f(u, x)

subject to r(u, x) = 0

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Shock tracking objective function

Requirements on objective functionobtains minimum when mesh

face aligned with shock andmonotonically decreases to

minimum in (large) neighborhood

f(u, x) = fshk(u, x) + αfmsh(x)

fshk(u, x) =

ne∑e=1

∫Ωe(x)

|u− ūe|2 dV

fmsh(x) =

ne∑e=1

∫Ωe(x)

||G||2F(det G)2/d+

0.64 0.65 0.66 0.670

2

4

6

8

·10−4

position of mesh edge closest to shock

Objective function as an element edge is smoothly swept across shock location for: fshk(u, x)( ), residual-based objective ( ), and Rankine-Hugniot-based objective ( ).

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Full space optimization solver for shock tracking

Cannot use nested approach to PDE optimization because it requires solvingr(u, x) = 0 for x 6= x∗ =⇒ crash

• Full space approach: u→ u∗ and x→ x∗ simultaneously• Define Lagrangian

L(u, x, λ) = f(u, x)− λTr(u, x)

• First-order optimality (KKT) conditions for full space optimization problem

∇uL(u∗, x∗, λ∗) = 0, ∇xL(u∗, x∗, λ∗) = 0, ∇λL(u∗, x∗, λ∗) = 0

• Apply (quasi-)Newton method1 to solve nonlinear KKT system for u∗, x∗, λ∗

• SNOPT used in this work2

1usually requires globalization such as linesearch or trust-region2leads to very inefficient implementation since cannot leverage data structures from DGdiscretization and cannot be parallelized

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O(hp+1) convergence rates demonstrated for Burgers’ equation

100 101 102 10310−8

10−6

10−4

10−2

100

Number of elements

L1error

Convergence of shock tracking method applied to the modified inviscid Burgers’ equation forpolynomial orders p = 1 ( ), p = 2 ( ), p = 3 ( ), p = 4 ( ), p = 5 ( ), p = 6 ( ). The expected

convergence rates of p+ 1 are obtained in most cases. The slopes of the best-fit lines to the datapoints in the asymptotic regime are: ∠ − 1.95 ( ), ∠ − 3.13 ( ), ∠ − 3.85 ( ), ∠ − 5.47

( ), ∠ − 4.36 ( ), ∠ − 8.67 ( ).

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Resolution of 2D supersonic flow with 102 quadratic elements

The solution of the CI1 bow shock problem. Left: Solution on non-aligned mesh with 102 linearelements and added viscosity (initial guess for shock tracking method). Middle/right: solutionusing shock tracking framework corresponding to mesh with 102 linear (middle) and quadratic(right) elements.

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Resolution of 2D supersonic flow with 102 quadratic elements

The solution of the CI1 bow shock problem. Left: Solution on non-aligned mesh with 102 linearelements and added viscosity (initial guess for shock tracking method). Middle/right: solutionusing shock tracking framework corresponding to mesh with 102 linear (middle) and quadratic(right) elements.

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Convergence to optimal solution and mesh

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Solver simultaneously minimizes objective and solves PDE

0 50 100 150 200 250 300 350 4000.4

0.6

0.8

1

1.2

1.4

1.6

1.8

Iteration

Objective

function

()

10−10

10−8

10−6

10−4

10−2

100

102

Residua

lnorm,||r

(u,x

)||∞

()

Convergence of residual and objective function

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Performance summary for shock tracking method

Polynomial order (p) 2Number of elements 102Degrees of freedom 2448

Enthalpy error (normalized) 0.000694 (0.0111)Stagnation pressure error (normalized) 0.0681 (1.09)

Cost (tau bench) 22.8

Shock tracking performance summary for mesh with 102 elements and polynomial ordersp = 1 and p = 2 with mesh regularization α = 0.05.

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Conclusions

Matthew J. Zahr and Per-Olof Persson, “An optimization-based discontinuousGalerkin approach for high-order accurate shock tracking.”, Monday, January8, 2018, 10:00AM-10:30AM, Sun 5 Room.

Upcoming improvements to method

• numerical flux consistent with integral form (jumps do not tend to 0)• solver that exploits problem structure and incorporates homotopy• local topology changes to reduce iterations and improve mesh quality• parallel implementation

Mach 2 flow around cylinder (left), Mach 4 flow around blunt body (middle), and L2 projection ofdiscontinuous function (right).

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References I

Zahr, M. J. and Persson, P.-O. (1/8/2018 – 1/12/2018b).

An optimization-based discontinuous Galerkin approach forhigh-order accurate shock tracking.

In AIAA Science and Technology Forum and Exposition (SciTech2018),Kissimmee, Florida. American Institute of Aeronautics and Astronautics.

Zahr, M. J. and Persson, P.-O. (2018a).

An optimization-based approach for high-order accuratediscretization of conservation laws with discontinuous solutions.

In review.

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