fbbaebff9f
Full toolchain port. Numerical equivalence verified against MATLAB:
- main_mode_sweep.jl: every mode's final state matches MATLAB to 3-4 dp
- reach_operation.jl: per-halfspace margins match MATLAB exactly
- barrier_lyapunov.jl: per-halfspace bounds match (best Qbar from sweep
yields max|dT_c| = 33.228 K either side)
- barrier_compare_OL_CL.jl: OL gamma 1.038e13, CL gamma 1.848e4
matching the MATLAB result; LQR helps by ~20,000x on every halfspace.
Phase summary:
Phase 1: pke_solver.jl, plot_pke_results.jl (Plots.jl), main_mode_sweep.jl
Phase 2: reach_linear.jl, reach_operation.jl, barrier_lyapunov.jl,
barrier_compare_OL_CL.jl, load_predicates.jl
Phase 3 (this commit): delete plant-model/ entirely, delete reach
code from reachability/ keeping predicates.json + docs,
git mv julia-port/ -> code/, update root README + CLAUDE,
write code/CLAUDE.md and code/README.md, update reach
README + WALKTHROUGH file paths, journal preamble note
that pre-port entries reference MATLAB paths.
Why now: prompt-neutron stiffness in nonlinear reach made it clear we
need TMJets, which is Julia. Already had the Julia plant model
working and matching MATLAB. Two languages = two sources of truth =
two places to drift. One language, one truth.
Manifest.toml gitignored. .mat results gitignored.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
41 lines
1.4 KiB
Julia
41 lines
1.4 KiB
Julia
#!/usr/bin/env julia
|
|
#
|
|
# sim_sanity.jl — verify the Julia port matches the MATLAB result.
|
|
#
|
|
# Reproduces main.m Run 2 (ctrl_operation under 100% -> 80% Q_sg step)
|
|
# and prints the final state, which should agree with MATLAB to ~1e-3.
|
|
|
|
using Pkg
|
|
Pkg.activate(joinpath(@__DIR__, ".."))
|
|
|
|
using OrdinaryDiffEq
|
|
|
|
include(joinpath(@__DIR__, "..", "src", "pke_params.jl"))
|
|
include(joinpath(@__DIR__, "..", "src", "pke_th_rhs.jl"))
|
|
include(joinpath(@__DIR__, "..", "controllers", "controllers.jl"))
|
|
|
|
plant = pke_params()
|
|
x0 = pke_initial_conditions(plant)
|
|
|
|
Q_sg = t -> plant.P0 * (1.0 - 0.2 * (t >= 30))
|
|
ref = (; T_avg = plant.T_c0)
|
|
|
|
function rhs!(dx, x, p, t)
|
|
u = ctrl_operation(t, x, plant, ref)
|
|
pke_th_rhs!(dx, x, t, plant, Q_sg, u)
|
|
end
|
|
|
|
prob = ODEProblem(rhs!, x0, (0.0, 600.0))
|
|
sol = solve(prob, Rodas5(); reltol=1e-8, abstol=1e-10)
|
|
|
|
xf = sol.u[end]
|
|
CtoF(T) = T * 9/5 + 32
|
|
println("\n=== Julia port sanity — ctrl_operation under 100% -> 80% Q_sg step ===")
|
|
println(" Final t = ", sol.t[end])
|
|
println(" n = $(round(xf[1]; digits=4)) (expect ~0.800)")
|
|
println(" T_f = $(round(CtoF(xf[8]); digits=2)) F (expect ~616.6)")
|
|
println(" T_avg = $(round(CtoF(xf[9]); digits=2)) F (expect ~587.8)")
|
|
println(" T_cold = $(round(CtoF(xf[10]); digits=2)) F (expect ~561.4)")
|
|
u_final = ctrl_operation(sol.t[end], xf, plant, ref)
|
|
println(" u = $(round(u_final/plant.beta; digits=4)) \$ (expect ~-0.0068)")
|