This page was generated from unit-3.3-scalardg/scalardg.ipynb.
3.3 Discontinuous Galerkin Discretizations for linear transport¶
We are solving the scalar linear transport problem
Find \(u: [0,T] \to V_D := \{ u \in L^2(\Omega), b \cdot \nabla u \in L^2(\Omega), u|_{\Gamma_{in}} = u_D\}\), s.t. \begin{equation} \int_{\Omega} \partial_t u v + b \cdot \nabla u v = \int_{\Omega} f v \qquad \forall v \in V_0 = \{ u \in L^2(\Omega), b \cdot \nabla u \in L^2(\Omega), u|_{\Gamma_{in}} = 0\} \end{equation}
[1]:
from ngsolve import *
import netgen.gui
As a first example, we consider the unit square \((0,1)^2\) and the advection velocity \(b = (1,2)\). Accordingly the inflow boundary is \(\Gamma_{in} = \{ x \cdot y = 0\}\).
[2]:
from netgen.geom2d import SplineGeometry
geo = SplineGeometry()
geo.AddRectangle( (0, 0), (1, 1),
bcs = ("bottom", "right", "top", "left"))
mesh = Mesh( geo.GenerateMesh(maxh=0.125))
Draw(mesh)
order = 4
Convection and boundary values:¶
To make cases with
CoefficientFunctions
we use theIfPos
-CoefficientFunction
.IfPos(a,b,c)
:a
decides on the evaluation. Ifa
is positiveb
is evaluated, otherwisec
.
[3]:
from math import pi
b = CoefficientFunction((1+sin(4*pi*y),2))
Draw(b,mesh,"wind")
from ngsolve.internal import visoptions; visoptions.scalfunction = "wind:0"
ubnd = IfPos(x-0.125,IfPos(0.625-x,1+cos(8*pi*x),0),0)
We consider an Upwind DG discretization (in space):
Find \(u: [0,T] \to V_h := \bigoplus_{T\in\mathcal{T}_h} \mathcal{P}^k(T)\) so that
Here \(\hat{u}\) is the Upwind flux, i.e. \(\hat{u} = u\) on the outflow boundary part \(\partial T_{out} = \{ x\in \partial T \mid b(x) \cdot n_T(x) \geq 0 \}\) of \(T\) and \(\hat{u} = u^{other}\) else, with \(u^{other}\) the value from the neighboring element.
There is quite a difference in the computational costs (compared to a standard DG formulation) depending on the question if the solution of linear systems is involved or only operator evaluations (explicit method).
We treat the explicit case here only
and refer to unit 2.8 for solving linear systems with DG formulations.
Explicit time stepping with a DG formulation¶
Explicit Euler:
In our first example we set \(u_0 = f = 0\).
Computing convection applications \(C u^n\)¶
We can define the bilinear form without setting up a matrix with storage. (
nonassemble=True
)A
BilinearForm
is allowed to be nonlinear in the 1st argument (for operator applications)
[4]:
VT = L2(mesh,order=order)
u,v = VT.TnT()
c = BilinearForm(VT, nonassemble=True)
To access the neighbor function we can use
u.Other()
, cf. unit 2.8.To incorporate boundary conditions (\(\hat{u}\) on inflow boundaries), we can use the argument
bnd
of.Other()
(not possible in unit 2.8 )If there is no neighbor element (boundary!) the
CoefficientFunction
bnd
is evaluated.
[5]:
n = specialcf.normal(mesh.dim)
upw_flux = b*n * IfPos(b*n, u, u.Other(bnd=ubnd))
dS = dx(element_boundary=True)
c += - b * grad(v) * u * dx + upw_flux * v * dS
Bilinearform for operator applications¶
Due to the nonassemble=True
in the constructor of the BilinearForm
we can use c.mat * x
to realize the operator application without assembling a matrix first:
[6]:
gfu = GridFunction(VT);
Draw(gfu,mesh,"u",sd=4,min=-0.1,max=2.1,autoscale=False)
res = gfu.vec.CreateVector()
[7]:
#Operator application (equivalent to assemble and mult but faster)
res.data = c.mat * gfu.vec
[8]:
# this does not work:
c2 = BilinearForm(VT)
res.data = c2.mat * gfu.vec
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-1-05fb163505bf> in <module>
1 # this does not work:
2 c2 = BilinearForm(VT)
----> 3 res.data = c2.mat * gfu.vec
TypeError: matrix not ready - assemble bilinearform first
Solving mass matrix problems (see also unit-2.11)¶
Need to invert the mass matrix
For DG methods the mass matrix is block diagonal, often even diagonal.
FESpace offers (if available):
Mass(rho)
: mass matrix as an operator (not a sparse matrix)Mass(rho).Inverse()
: inverse mass matrix as an operator (not a sparse matrix)
[9]:
invm = VT.Mass(1).Inverse()
print(invm)
Print base-matrix
The (simple) time loop¶
[10]:
%%time
#better: %%timeit
t = 0; gfu.vec[:] = 0
dt = 2e-4
tend = 0.6
while t < tend-0.5*dt:
res.data = invm @ c.mat * gfu.vec
gfu.vec.data -= dt * res
t += dt
Redraw(blocking=True)
CPU times: user 5.72 s, sys: 7.33 ms, total: 5.73 s
Wall time: 5.73 s
Skeleton formulation (cf. unit 2.8)¶
So far we considered the DG formulation with integrals on the boundary of each element. Instead one could formulate the problem in terms of facet integrals where every facet appears only once.
Then, the corresponding formulation is:
Find \(u: [0,T] \to V_h := \bigoplus_{T\in\mathcal{T}_h} \mathcal{P}^k(T)\) so that
Here \(\mathcal{F}^{inner}\) is the set of interior facets and \(\mathcal{F}^{bound}\) is the set of boundary facets.
integral types:¶
The facet integrals are divided into inner facets and boundary facets. To obtain these integrals we combine the DifferentialSymbol
dx
or ds
with skeleton=True
.
[11]:
dskel_inner = dx(skeleton=True)
dskel_bound = ds(skeleton=True)
# or:
dskel_inflow = ds(skeleton=True, definedon=mesh.Boundaries("left|bottom"))
dskel_outflow = ds(skeleton=True, definedon=mesh.Boundaries("right|top"))
Skeleton formulation of \(C\)¶
[12]:
c = BilinearForm(VT,nonassemble=True)
c += -b * grad(v) * u * dx
c += upw_flux * (v-v.Other()) * dskel_inner
c += b*n * IfPos(b*n,u,ubnd) * v * dskel_bound
#alternatively (if you know in/out beforehand):
#c += b*n * ubnd * v * dskel_inflow
#c += b*n * u * v * dskel_outflow
The (simple) time loop¶
[13]:
%%time
t = 0; gfu.vec[:]=0
while t < tend-0.5*dt:
gfu.vec.data -= dt * invm @ c.mat * gfu.vec
t += dt
Redraw(blocking=True)
CPU times: user 4.42 s, sys: 45.2 ms, total: 4.46 s
Wall time: 4.4 s
TraceOperator (Purpose: avoid neighbor access Other()
)¶
The trace operator maps from an FESpace
to a compatible FacetFESpace
by evaluating the traces.
The stored value on a facet is the sum of the traces of the aligned elements.
No need to access the neighbor (.Other()
) later on.
[14]:
VF = FacetFESpace(mesh, order=order)
V = FESpace( [VT, VF] )
[15]:
trace = VT.TraceOperator(VF, False)
print("The space VT has {} dofs.".format(VT.ndof))
print("The trace space VF has {} dofs.".format(VF.ndof))
print("trace represents an {} x {} operator".format(trace.height, trace.width))
The space VT has 2160 dofs.
The trace space VF has 1160 dofs.
trace represents an 1160 x 2160 operator
[16]:
gfuF = GridFunction(VF)
gfuF.vec.data = trace * gfu.vec
To make use of the trace operator, we split the previous (element_boundary
)formulation into three parts:
part 1: element local volume integrals (no interaction with neighbor elements) (on
VT
)part 2: couplings on the facets (on
VT
\(\times\)V
)part 3: (rhs + ) boundary terms (on
VT
)
[17]:
uT, vT = VT.TnT()
c1 = BilinearForm(space=VT, nonassemble=True) # part 1
c1 += -uT * b * grad(vT) * dx
uT,uF = V.TrialFunction()
c2 = BilinearForm(trialspace=V, testspace=VT, nonassemble=True) # part 2
# here uf-u = u_me + u_other - u_me is the neighbor value (0 at bnd)
c2 += b*n * IfPos(b*n, uT, uF-uT) * vT * dx(element_boundary=True)
rhs = LinearForm(VT) # part 3
rhs += b*n * IfPos(b*n, 0, ubnd) * vT * dskel_bound # dskel_inflow
rhs.Assemble()
[17]:
<ngsolve.comp.LinearForm at 0x7f5854d77a70>
Note that c1
and c2
act on different spaces. To make them compatible, we combine: * TraceOperator
: VT \(\to\) VF * Embedding
s: VT \(\to\) VT \(\times\) VF and VF \(\to\) VT \(\times\) VF (cf. unit 2.10)
The Embeddings are (with \(n_F = \operatorname{dim}(V_F)\), \(n_T = \operatorname{dim}(V_T)\), \(n_V=n_F+n_T\))
[18]:
embT = Embedding(V.ndof, V.Range(0))
embF = Embedding(V.ndof, V.Range(1))
embV = embT + embF @ trace
The operators can now be combined easily. Recall: * c1
: VT
\(\to\) VT
’ \(\quad\) \(\bullet\) c2
: VT
\(\times\) VF
\(\to\) VT
’ \(\quad\) \(\bullet\) \(\Rightarrow\) c
: VT
\(\to\) VT
’
[19]:
c = c1.mat + c2.mat @ embV
The time loop:
[20]:
%%time
t = 0; gfu.vec[:] = 0
invm = VT.Mass(1).Inverse()
r = gfu.vec.CreateVector(); r.data = invm * rhs.vec # <- the boundary data
while t < tend-0.5*dt:
gfu.vec.data -= dt * (invm @ c * gfu.vec + r)
t += dt
Redraw(blocking=True)
CPU times: user 4.64 s, sys: 62.3 ms, total: 4.71 s
Wall time: 4.64 s
Careful with one-liners!
The following will not work correctly: (gfu
appears left and right: order of ops is important!)
[21]:
%%time
t = 0; gfu.vec[:] = 0
while t < tend-0.5*dt:
gfu.vec.data -= dt * (r + invm @ c * gfu.vec)
t += dt;
Redraw(blocking=True)
CPU times: user 4.51 s, sys: 62.4 ms, total: 4.58 s
Wall time: 4.51 s
In doubt? Create a temporary vector:
[22]:
%%time
tmp = gfu.vec.CreateVector()
t = 0; gfu.vec[:] = 0
while t < tend-0.5*dt:
tmp.data = r + invm @ c * gfu.vec
gfu.vec.data -= dt * tmp
t += dt;
Redraw(blocking=True)
CPU times: user 4.55 s, sys: 0 ns, total: 4.55 s
Wall time: 4.55 s
Speed up with geom_free
integrals¶
With \(u(x) = \hat{u}(\hat{x})\), \(v(x) = \hat{v}(\hat{x})\) (directly mapped) and \(\mathbf{w}(x) = \frac{1}{|\operatorname{det}(F)|} F \cdot \hat{\mathbf{w}}(\hat{x})\) (Piola mapped) there holds
and similarly for the facet integrals.
Integrals are independent of the “physical element” (up to ordering) similar to integrals in unit-2.11.
\(\leadsto\) allows to prepare intermediate computations for a large class of elements at once.
Piola wind:
[23]:
gfwind = GridFunction(HDiv(mesh, order=order))
gfwind.Set(b)
b=gfwind; # <- overwrite old name "b"
Same as before, but with geom_free=True
flag:
[24]:
# part 1
uT, vT = VT.TnT()
c1 = BilinearForm(space=VT, nonassemble=True, geom_free=True)
c1 += -uT * b * grad(vT) * dx
# part 2
uT,uF = V.TrialFunction()
c2 = BilinearForm(trialspace=V, testspace=VT, nonassemble=True, geom_free=True)
# here uf-u = u_me + u_other - u_me is the neighbor value
c2 += b*n * IfPos(b*n, uT, uF-uT) * vT * dx(element_boundary=True)
[25]:
c = c1.mat + c2.mat @ embV
[26]:
%%time
t = 0; gfu.vec[:] = 0
while t < tend-0.5*dt:
gfu.vec.data -= dt * (invm @ c * gfu.vec + r)
t += dt
Redraw(blocking=True)
CPU times: user 2.47 s, sys: 28.7 ms, total: 2.5 s
Wall time: 2.48 s
[ ]: