#!/usr/bin/env julia # # reach_scram_pj.jl — nonlinear reach on scram, prompt-jump model. # # Scram obligation: from any operating-envelope state, drive total # reactivity below the shutdown-margin threshold (rho <= -0.01, i.e. # 1% dk/k subcritical) within T_max = 60 s. Constant control # u = -8*beta (rods slammed in). Q_sg = 3% P0 (decay-heat-level sink, # placeholder). # # X_exit halfspace (from reachability/predicates.json::shutdown_margin): # alpha_f * T_f + alpha_c * T_c <= 0.00402 # discharged when sup over reach set of LHS <= 0.00402. # # 9-state PJ model (10D with augmented time). using Pkg Pkg.activate(joinpath(@__DIR__, "..", "..")) using LinearAlgebra using ReachabilityAnalysis, LazySets using JSON using MAT # Plant constants — must match pke_params. const LAMBDA = 1e-4 const BETA_1, BETA_2, BETA_3, BETA_4, BETA_5, BETA_6 = 0.000215, 0.001424, 0.001274, 0.002568, 0.000748, 0.000273 const BETA = BETA_1 + BETA_2 + BETA_3 + BETA_4 + BETA_5 + BETA_6 const LAM_1, LAM_2, LAM_3, LAM_4, LAM_5, LAM_6 = 0.0124, 0.0305, 0.111, 0.301, 1.14, 3.01 const P0 = 1e9 const M_F, C_F, M_C, C_C, HA, W_M, M_SG = 50000.0, 300.0, 20000.0, 5450.0, 5e7, 5000.0, 30000.0 const ALPHA_F, ALPHA_C = -2.5e-5, -1e-4 const T_COLD0 = 290.0 const DT_CORE = P0 / (W_M * C_C) const T_HOT0 = T_COLD0 + DT_CORE const T_C0 = (T_HOT0 + T_COLD0) / 2 const T_F0 = T_C0 + P0 / HA const U_SCRAM = -8 * BETA # rod worth applied at scram const Q_SG_DECAY = 0.03 * P0 # constant decay-heat-level sink # X_exit threshold: shutdown_margin halfspace, mirrors predicates.json. const RHO_SDM = 0.01 # 1% dk/k const SDM_RHS = -RHO_SDM - U_SCRAM + ALPHA_F*T_F0 + ALPHA_C*T_C0 # ≈ 0.00402 # Taylorized scram RHS, PJ form. @taylorize function rhs_scram_pj_taylor!(dx, x, p, t) rho = U_SCRAM + ALPHA_F * (x[7] - T_F0) + ALPHA_C * (x[8] - T_C0) sum_lam_C = LAM_1*x[1] + LAM_2*x[2] + LAM_3*x[3] + LAM_4*x[4] + LAM_5*x[5] + LAM_6*x[6] denom = BETA - rho n = LAMBDA * sum_lam_C / denom inv_factor = sum_lam_C / denom dx[1] = BETA_1 * inv_factor - LAM_1 * x[1] dx[2] = BETA_2 * inv_factor - LAM_2 * x[2] dx[3] = BETA_3 * inv_factor - LAM_3 * x[3] dx[4] = BETA_4 * inv_factor - LAM_4 * x[4] dx[5] = BETA_5 * inv_factor - LAM_5 * x[5] dx[6] = BETA_6 * inv_factor - LAM_6 * x[6] dx[7] = (P0 * n - HA * (x[7] - x[8])) / (M_F * C_F) dx[8] = (HA * (x[7] - x[8]) - 2 * W_M * C_C * (x[8] - x[9])) / (M_C * C_C) dx[9] = (2 * W_M * C_C * (x[8] - x[9]) - Q_SG_DECAY) / (M_SG * C_C) dx[10] = one(x[1]) return nothing end # X_entry — small box around operating point: scram could fire from anywhere # in operation, but for demo we take a tight envelope and propagate. n_op = 1.0 C_op = [BETA_1/(LAM_1*LAMBDA), BETA_2/(LAM_2*LAMBDA), BETA_3/(LAM_3*LAMBDA), BETA_4/(LAM_4*LAMBDA), BETA_5/(LAM_5*LAMBDA), BETA_6/(LAM_6*LAMBDA)] .* n_op x_lo = [C_op[1] * 0.99, C_op[2] * 0.99, C_op[3] * 0.99, C_op[4] * 0.99, C_op[5] * 0.99, C_op[6] * 0.99, T_F0 - 1.0, T_C0 - 1.0, T_COLD0 - 1.0, 0.0] x_hi = [C_op[1] * 1.01, C_op[2] * 1.01, C_op[3] * 1.01, C_op[4] * 1.01, C_op[5] * 1.01, C_op[6] * 1.01, T_F0 + 1.0, T_C0 + 1.0, T_COLD0 + 1.0, 0.0] X0 = Hyperrectangle(low=x_lo, high=x_hi) println("\n=== Nonlinear scram reach, prompt-jump model ===") println(" X_entry: small box around operating point (n ≈ 1.0)") println(" Constant u = -8*beta = $(round(U_SCRAM; digits=4))") println(" Q_sg = 3% P0 (decay-heat sink)") println(" T_max = 60 s") println(" X_exit: alpha_f*T_f + alpha_c*T_c <= $(round(SDM_RHS; sigdigits=4)) (rho <= -$(RHO_SDM))") results = Dict{Float64, Any}() for T_probe in (10.0, 30.0, 60.0) println("\n--- Probe T = $T_probe s ---") sys = BlackBoxContinuousSystem(rhs_scram_pj_taylor!, 10) prob = InitialValueProblem(sys, X0) try alg = TMJets(orderT=4, orderQ=2, abstol=1e-9, maxsteps=100000) t_start = time() sol = solve(prob; T=T_probe, alg=alg) elapsed = time() - t_start flow = flowpipe(sol) n_sets = length(flow) println(" TMJets: $n_sets reach-sets in $(round(elapsed; digits=1)) s wall") flow_hr = overapproximate(flow, Hyperrectangle) # --- Per-step envelopes for plotting tubes --- n_steps = length(flow_hr) t_arr = zeros(n_steps) n_lo_ts = zeros(n_steps); n_hi_ts = zeros(n_steps) rho_lo_ts = zeros(n_steps); rho_hi_ts = zeros(n_steps) Tc_lo_ts = zeros(n_steps); Tc_hi_ts = zeros(n_steps) Tf_lo_ts = zeros(n_steps); Tf_hi_ts = zeros(n_steps) for (k, R) in enumerate(flow_hr) s = set(R) t_arr[k] = high(s, 10) sumLC_lo_k = LAM_1*low(s,1) + LAM_2*low(s,2) + LAM_3*low(s,3) + LAM_4*low(s,4) + LAM_5*low(s,5) + LAM_6*low(s,6) sumLC_hi_k = LAM_1*high(s,1) + LAM_2*high(s,2) + LAM_3*high(s,3) + LAM_4*high(s,4) + LAM_5*high(s,5) + LAM_6*high(s,6) rho_lo_k = U_SCRAM + ALPHA_F*(high(s,7) - T_F0) + ALPHA_C*(high(s,8) - T_C0) rho_hi_k = U_SCRAM + ALPHA_F*(low(s,7) - T_F0) + ALPHA_C*(low(s,8) - T_C0) denom_lo_k = BETA - rho_hi_k denom_hi_k = BETA - rho_lo_k n_lo_ts[k] = denom_lo_k > 0 ? LAMBDA * sumLC_lo_k / denom_hi_k : NaN n_hi_ts[k] = denom_lo_k > 0 ? LAMBDA * sumLC_hi_k / denom_lo_k : NaN rho_lo_ts[k] = rho_lo_k rho_hi_ts[k] = rho_hi_k Tc_lo_ts[k] = low(s, 8); Tc_hi_ts[k] = high(s, 8) Tf_lo_ts[k] = low(s, 7); Tf_hi_ts[k] = high(s, 7) end # Reconstruct n at last time step from C and T_c. last = set(flow_hr[end]) sumLC_lo = LAM_1*low(last,1) + LAM_2*low(last,2) + LAM_3*low(last,3) + LAM_4*low(last,4) + LAM_5*low(last,5) + LAM_6*low(last,6) sumLC_hi = LAM_1*high(last,1) + LAM_2*high(last,2) + LAM_3*high(last,3) + LAM_4*high(last,4) + LAM_5*high(last,5) + LAM_6*high(last,6) rho_lo = U_SCRAM + ALPHA_F*(low(last,7) - T_F0) + ALPHA_C*(high(last,8) - T_C0) rho_hi = U_SCRAM + ALPHA_F*(high(last,7) - T_F0) + ALPHA_C*(low(last,8) - T_C0) denom_lo = BETA - rho_hi denom_hi = BETA - rho_lo n_final_lo = LAMBDA * sumLC_lo / denom_hi n_final_hi = LAMBDA * sumLC_hi / denom_lo Tc_final = (low(last, 8), high(last, 8)) Tf_final = (low(last, 7), high(last, 7)) Tcold_final = (low(last, 9), high(last, 9)) # shutdown_margin halfspace LHS: alpha_f*T_f + alpha_c*T_c. # Coefficients negative → sup over the box at low(T_f), low(T_c). sdm_lhs_hi = ALPHA_F*low(last,7) + ALPHA_C*low(last,8) sdm_lhs_lo = ALPHA_F*high(last,7) + ALPHA_C*high(last,8) rho_max = U_SCRAM + ALPHA_F*(low(last,7) - T_F0) + ALPHA_C*(low(last,8) - T_C0) rho_min = U_SCRAM + ALPHA_F*(high(last,7) - T_F0) + ALPHA_C*(high(last,8) - T_C0) sdm_ok = sdm_lhs_hi <= SDM_RHS println(" n at T_probe (reconstructed): [$(round(n_final_lo; sigdigits=4)), $(round(n_final_hi; sigdigits=4))]") println(" T_c at T_probe: [$(round(Tc_final[1]; digits=2)), $(round(Tc_final[2]; digits=2))] °C") println(" T_f at T_probe: [$(round(Tf_final[1]; digits=2)), $(round(Tf_final[2]; digits=2))] °C") println(" rho at T_probe: [$(round(rho_min; sigdigits=4)), $(round(rho_max; sigdigits=4))] (shutdown margin = $(round(-rho_max; sigdigits=4)) dk/k)") println(" shutdown_margin LHS sup: $(round(sdm_lhs_hi; sigdigits=4)) vs RHS $(round(SDM_RHS; sigdigits=4)) → $(sdm_ok ? "✓ DISCHARGED" : "× not yet")") results[T_probe] = (status="OK", n_sets=n_sets, elapsed=elapsed, n_final=(n_final_lo, n_final_hi), Tc=Tc_final, Tf=Tf_final, Tcold=Tcold_final, sdm_lhs=(sdm_lhs_lo, sdm_lhs_hi), rho=(rho_min, rho_max), sdm_ok=sdm_ok, t_arr=t_arr, n_lo_ts=n_lo_ts, n_hi_ts=n_hi_ts, rho_lo_ts=rho_lo_ts, rho_hi_ts=rho_hi_ts, Tc_lo_ts=Tc_lo_ts, Tc_hi_ts=Tc_hi_ts, Tf_lo_ts=Tf_lo_ts, Tf_hi_ts=Tf_hi_ts) catch err msg = sprint(showerror, err) println(" FAILED: ", first(msg, 300)) results[T_probe] = (status="FAILED", err=first(msg, 300)) break end end println("\n=== Summary ===") for T_probe in (10.0, 30.0, 60.0) haskey(results, T_probe) || continue r = results[T_probe] if r.status == "OK" ok_str = r.sdm_ok ? "✓ shutdown_margin DISCHARGED" : "× shutdown_margin not yet" println(" T = $(T_probe) s: $(r.n_sets) sets, $(round(r.elapsed; digits=1))s wall — rho ∈ [$(round(r.rho[1]; sigdigits=3)), $(round(r.rho[2]; sigdigits=3))] $ok_str") else println(" T = $(T_probe) s: FAILED") end end mat_out = joinpath(@__DIR__, "..", "..", "..", "results", "reach_scram_pj_result.mat") saved = Dict{String, Any}("probe_horizons" => collect((10.0, 30.0, 60.0))) for T_probe in (10.0, 30.0, 60.0) haskey(results, T_probe) || continue r = results[T_probe] if r.status == "OK" saved["T_$(Int(T_probe))_n_lo"] = r.n_final[1] saved["T_$(Int(T_probe))_n_hi"] = r.n_final[2] saved["T_$(Int(T_probe))_Tc_lo"] = r.Tc[1] saved["T_$(Int(T_probe))_Tc_hi"] = r.Tc[2] saved["T_$(Int(T_probe))_Tf_lo"] = r.Tf[1] saved["T_$(Int(T_probe))_Tf_hi"] = r.Tf[2] saved["T_$(Int(T_probe))_Tcold_lo"] = r.Tcold[1] saved["T_$(Int(T_probe))_Tcold_hi"] = r.Tcold[2] saved["T_$(Int(T_probe))_sdm_lhs_hi"] = r.sdm_lhs[2] saved["T_$(Int(T_probe))_rho_max"] = r.rho[2] saved["T_$(Int(T_probe))_sdm_ok"] = r.sdm_ok ? 1.0 : 0.0 # Per-step time series for tube plotting. saved["T_$(Int(T_probe))_t_arr"] = r.t_arr saved["T_$(Int(T_probe))_n_lo_ts"] = r.n_lo_ts saved["T_$(Int(T_probe))_n_hi_ts"] = r.n_hi_ts saved["T_$(Int(T_probe))_rho_lo_ts"] = r.rho_lo_ts saved["T_$(Int(T_probe))_rho_hi_ts"] = r.rho_hi_ts saved["T_$(Int(T_probe))_Tc_lo_ts"] = r.Tc_lo_ts saved["T_$(Int(T_probe))_Tc_hi_ts"] = r.Tc_hi_ts saved["T_$(Int(T_probe))_Tf_lo_ts"] = r.Tf_lo_ts saved["T_$(Int(T_probe))_Tf_hi_ts"] = r.Tf_hi_ts end end saved["sdm_rhs"] = SDM_RHS saved["rho_sdm"] = RHO_SDM matwrite(mat_out, saved) println("\nSaved scram envelope summaries to $mat_out")