Fix the Documentation build under ModelingToolkit v11

docs/Project.toml

@@ -6,21 +6,31 @@ ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
 ModelingToolkit = "961ee093-0014-501f-94e3-6117800e7a78"
 ModelingToolkitCourse = "d0ecabdd-fe99-481e-9814-e16fa9c541df"
 ModelingToolkitStandardLibrary = "16a59e39-deab-5bd0-87e4-056b12336739"
+NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+OrdinaryDiffEqBDF = "6ad6398a-0878-4a85-9266-38940aa047c8"
+OrdinaryDiffEqNonlinearSolve = "127b3ac7-2247-4354-8eb6-78cf4e7c58e8"
+OrdinaryDiffEqSDIRK = "2d112036-d095-4a1e-ab9a-08536f3ecdbf"
 Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+SciCompDSL = "91a8cdf1-4ca6-467b-a780-87fda3fff15e"
 Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
 Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 
 [compat]
 DataInterpolations = "5, 6, 8.10, 9.0"
-DifferentialEquations = "7, 8.0"
+DifferentialEquations = "8"
 Documenter = "1"
 ForwardDiff = "0.10, 1.4"
-ModelingToolkit = "9, 11.28"
-ModelingToolkitStandardLibrary = "2"
-OrdinaryDiffEq = "=6.74.1, 7.1"
+ModelingToolkit = "11.28"
+ModelingToolkitStandardLibrary = "2.29"
+NonlinearSolve = "4"
+OrdinaryDiffEq = "7.1"
+OrdinaryDiffEqBDF = "2"
+OrdinaryDiffEqNonlinearSolve = "2"
+OrdinaryDiffEqSDIRK = "2"
 Plots = "1"
+SciCompDSL = "1"
 Setfield = "1"
 Sundials = "4, 6.2"
 Symbolics = "5, 6, 7.28"

docs/make.jl

@@ -1,5 +1,4 @@
 using Documenter, ModelingToolkitCourse
-# NOTE: OrdinaryDiffEq limited to v6.74.1 because of bug https://github.com/SciML/OrdinaryDiffEq.jl/issues/2250
 
 pages = [
     "Home" => "index.md",
@@ -23,6 +22,7 @@ makedocs(
     linkcheck_ignore = [
         "https://epubs.siam.org/doi/10.1137/0903023",
         "https://link.springer.com/book/10.1007/978-3-642-05221-7",
+        "https://www.mathworks.com/help/simscape/ref/variablehydraulicchamber.html",
         "http://www.siam.org/journals/auth-info.php",
     ],
     format = Documenter.HTML(

docs/src/lectures/lecture1.md

@@ -86,6 +86,7 @@ Then we can solve by specifying the method, in this case we specify `NewtonRaphs
 
 ```@example l1
 using DifferentialEquations
+using NonlinearSolve
 
 p  = xᵢ₋₁ = 0.0 # initial condition if i=2, x[1]=0 
 u0 = xᵢ = xᵢ₋₁  # guess value for x[i]
@@ -186,6 +187,7 @@ ModelingToolkit.jl uses symbolic math from Symbolics.jl to provide automatic ind
 ```@example l1
 using ModelingToolkit
 using ModelingToolkit: t_nounits as t, D_nounits as D
+using SciCompDSL # provides the `@connector`/`@mtkmodel` component DSL
 nothing # hide
 ```
 
@@ -238,9 +240,8 @@ Notice how the 2nd derivative term `ẍ(t)` has been automatically determined fr
 We can now assemble a problem and solve it.  The initial conditions do not need to be supplied here because the `sys` contains the variable defaults from `vars`.  The solution object `sol` can now be indexed symbolically from any symbol of the system regardless if it's a solved variable, observable, or even a parameter.  This way, if for example doing a batch of simulations, each respective solution object can easily retrieve all respective information about the simulation.
 
 ```@example l1
-u0 = [] # <-- used to override defaults of ODESystem variables
-p = [] # <-- used to override defaults of ODESystem parameters
-prob = ODEProblem(odesys, u0, tspan, p)
+op = [] # <-- symbolic map used to override defaults of ODESystem variables and parameters
+prob = ODEProblem(odesys, op, tspan)
 sol = solve(prob; abstol=tol)
 plot(sol; idxs=ẍ, xlabel="time [s]", ylabel="ẍ [m/s^2]")
 ```
@@ -368,7 +369,7 @@ nothing # hide
 Now the `Mass` and `Damper` components can be assembled in a system and connected together (note: the `connect` equation).  Also note the parameters `v`, `m`, and `d` are defined to expose the properties which can be set as keyword arguments of the same name.  
 
 ```@example l1 
-@mtkmodel System begin
+@mtkmodel MassDamperSystem begin
     @parameters begin
         v
         m
@@ -383,7 +384,7 @@ Now the `Mass` and `Damper` components can be assembled in a system and connecte
     end
 end
 
-@mtkbuild sys = System(;v=100, m=5, d=3)
+@mtkbuild sys = MassDamperSystem(;v=100, m=5, d=3)
 nothing # hide
 ```
 
@@ -533,7 +534,7 @@ As with the `Reference` component, the force is a boundary condition and is leav
 Now let's assemble a *mass-spring-damper* system with the full collection of components.
 
 ```@example l1 
-@mtkmodel System begin
+@mtkmodel MassSpringDamperSystem begin
     @parameters begin
         v=0
         x=0
@@ -555,7 +556,7 @@ Now let's assemble a *mass-spring-damper* system with the full collection of com
     end
 end
 
-@mtkbuild sys = System()
+@mtkbuild sys = MassSpringDamperSystem()
 ```
 
 ![mass-spring-damper](../img/System2.png)
@@ -638,7 +639,7 @@ nothing # hide
 As an example, the `MassSpringDamper` component can be connected in series to make a complex system.  One can imagine then how this enables easy construction of complex models that can be quickly modified, extremely useful for the application of model based design.  
 
 ```@example l1
-@mtkmodel System begin
+@mtkmodel SeriesSystem begin
     @parameters begin
         v = 0
         x = 0
@@ -658,7 +659,7 @@ As an example, the `MassSpringDamper` component can be connected in series to ma
     end
 end
 
-@mtkbuild sys = System()
+@mtkbuild sys = SeriesSystem()
 nothing #hide
 ```
 

docs/src/lectures/lecture2.md

@@ -290,9 +290,9 @@ odesys_ṁ1
 Notice that now, with a simple change of the system input variable, `structural_simplify()` outputs a system with 4 states to be solved.  We can find the initial conditions needed for these states from `sol_x` and solve.
 
 ```@example l2
-u0 = [sol_x[s][1] for s in unknowns(odesys_ṁ1)]
-prob_ṁ1 = ODEProblem(odesys_ṁ1, u0, (0, t_end))
-@time sol_ṁ1 = solve(prob_ṁ1; initializealg=NoInit());
+u0 = [s => sol_x[s][1] for s in unknowns(odesys_ṁ1)]
+prob_ṁ1 = ODEProblem(odesys_ṁ1, u0, (0, t_end); build_initializeprob = false)
+@time sol_ṁ1 = solve(prob_ṁ1; initializealg=SciMLBase.NoInit());
 nothing # hide
 ```
 
@@ -307,8 +307,8 @@ If we now solve for case 2, we can study the impact the compressibility derivati
 
 ```@example l2
 @mtkbuild odesys_ṁ2 = ODESystem(eqs_ṁ2, t, vars, pars)
-prob_ṁ2 = ODEProblem(odesys_ṁ2, u0, (0, t_end))
-@time sol_ṁ2 = solve(prob_ṁ2; initializealg=NoInit());
+prob_ṁ2 = ODEProblem(odesys_ṁ2, u0, (0, t_end); build_initializeprob = false)
+@time sol_ṁ2 = solve(prob_ṁ2; initializealg=SciMLBase.NoInit());
 nothing # hide
 ```
 
@@ -333,13 +333,13 @@ plot(time, (sol_ṁ1(time)[x] .- sol_ṁ2(time)[x])/1e-3,
 Also note the difference in computation.  
 
 ```@repl l2
-sol_ṁ1.destats
+sol_ṁ1.stats
 ```
 
 As can be seen, including the detail of full compressibility resulted in more computation: more function evaluations, Jacobians, solves, and steps.
 
 ```@repl l2
-sol_ṁ2.destats
+sol_ṁ2.stats
 ```
 
 ### ModelingToolkitStandardLibrary.jl
@@ -350,6 +350,8 @@ import ModelingToolkitStandardLibrary.Mechanical.Translational as T
 import ModelingToolkitStandardLibrary.Hydraulic.IsothermalCompressible as IC
 import ModelingToolkitStandardLibrary.Blocks as B
 
+include("volume.jl") # <-- moving-wall `Volume` component
+
 using DataInterpolations
 mass_flow_fun = LinearInterpolation(sol_x[ṁ], sol_x.t)
 
@@ -370,9 +372,9 @@ function MassVolume(; name, dx, drho, dm)
     vars = []
     systems = @named begin
         fluid = IC.HydraulicFluid(; density = 876, bulk_modulus = 1.2e9)
-        mass = T.Mass(;v=dx,m=M,g=-g)
-        vol = IC.Volume(;area=A, x=x₀, p=p_int, dx, drho, dm) 
-        mass_flow = IC.MassFlow(;p_int)
+        mass = T.Mass(;m=M,g=-g)
+        vol = Volume(;area=A, x=x₀, p=p_int, dx, drho, dm) 
+        mass_flow = IC.MassFlow()
         mass_flow_input = B.TimeVaryingFunction(;f = mass_flow_fun)
     end
 
@@ -383,7 +385,8 @@ function MassVolume(; name, dx, drho, dm)
         connect(mass_flow.port, fluid)
     ]
 
-    return ODESystem(eqs, t, vars, pars; systems, name)
+    return ODESystem(eqs, t, vars, pars; systems, name,
+        initial_conditions = [mass.v => dx, mass.s => x₀])
 end
 
 dx = sol_x[ẋ][1]