PDESystem is the common symbolic PDE specification for the SciML ecosystem. It is currently being built as a component of the ModelingToolkit ecosystem,
The vision for the common PDE interface is that a user should only have to specify their PDE once, mathematically, and have instant access to everything as simple as a finite difference method with constant grid spacing, to something as complex as a distributed multi-GPU discrete Galerkin method.
The key to the common PDE interface is a separation of the symbolic handling from the numerical world. All of the discretizers should not "solve" the PDE, but instead be a conversion of the mathematical specification to a numerical problem. Preferably, the transformation should be to another ModelingToolkit.jl
AbstractSystem, but in some cases this cannot be done or will not be performant, so a
SciMLProblem is the other choice.
These elementary problems, such as solving linear systems
Ax=b, solving nonlinear systems
f(x)=0, ODEs, etc. are all defined by SciMLBase.jl, which then numerical solvers can all target these common forms. Thus someone who works on linear solvers doesn't necessarily need to be working on a Discontinuous Galerkin or finite element library, but instead "linear solvers that are good for matrices A with properties ..." which are then accessible by every other discretization method in the common PDE interface.
Similar to the rest of the
AbstractSystem types, transformation and analyses functions will allow for simplifying the PDE before solving it, and constructing block symbolic functions like Jacobians.
struct PDESystem <: AbstractMultivariateSystem
A system of partial differential equations.
The equations which define the PDE
The boundary conditions
The domain for the independent variables.
The independent variables
The dependent variables
defaults: The default values to use when initial conditions and/or parameters are not supplied in
type: type of the system
name: the name of the system
using ModelingToolkit @parameters x @variables t u(..) Dxx = Differential(x)^2 Dtt = Differential(t)^2 Dt = Differential(t) #2D PDE C=1 eq = Dtt(u(t,x)) ~ C^2*Dxx(u(t,x)) # Initial and boundary conditions bcs = [u(t,0) ~ 0.,# for all t > 0 u(t,1) ~ 0.,# for all t > 0 u(0,x) ~ x*(1. - x), #for all 0 < x < 1 Dt(u(0,x)) ~ 0. ] #for all 0 < x < 1] # Space and time domains domains = [t ∈ (0.0,1.0), x ∈ (0.0,1.0)] @named pde_system = PDESystem(eq,bcs,domains,[t,x],[u])
Domains are specifying by saying
indepvar in domain, where
indepvar is a single or a collection of independent variables, and
domain is the chosen domain type. A 2-tuple can be used to indicate an
Interval. Thus forms for the
indepvar can be like:
t ∈ (0.0,1.0) (t,x) ∈ UnitDisk() [v,w,x,y,z] ∈ VectorUnitBall(5)
Interval(a,b): Defines the domain of an interval from
DomainSets.jl, but a 2-tuple can be used instead)
The only functions which act on a PDESystem are the following:
discretize(sys,discretizer): produces the outputted
symbolic_discretize(sys,discretizer): produces a debugging symbolic description of the discretized problem.
DiffEqOperators.jl defines the
MOLFiniteDifference discretizer which performs a finite difference discretization using the DiffEqOperators.jl stencils. These stencils make use of NNLib.jl for fast operations on semi-linear domains.