Frontal polymerization Crossply 3layer

ADVANTAGES3 · dim 90

SolvSRK wins. At the comparison noise level, SolvSRK beats the best baseline by at least 10 percentage points of survival, or by at least 0.05 balanced score when survival is tied. Use SolvSRK for this class of problem. All verdicts →

3-layer [0/90/0] carbon-fiber composite with Kamal-Sourour cure kinetics, anisotropic thermal conductivity (k_fiber/k_trans = 10:1), inter-ply thermal contact resistance, and volatile gas pressure.

Materials & composites

Problem definition

Canonical benchmark implementation

Canonical RHS excerpt from the registered callable used for this benchmark cell. Expand it to verify the state equations; it is not a standalone runnable fixture.

Show canonical RHS excerpt
def _kamal_sourour_rate_vec(T: np.ndarray, alpha: np.ndarray) -> np.ndarray:
    """Vectorised Kamal-Sourour autocatalytic cure rate.

    Clamps inputs for numerical safety before evaluating the Arrhenius
    terms.  Returns dα/dt for each node.
    """
    T_safe = np.clip(T, _T_FLOOR, _T_CEIL)
    alpha_safe = np.clip(alpha, 0.0, 1.0)

    inv_RT = 1.0 / (_R_GAS * T_safe)
    arg1 = np.clip(_E1 * inv_RT, 0.0, _EXP_ARG_MAX)
    arg2 = np.clip(_E2 * inv_RT, 0.0, _EXP_ARG_MAX)

    k1 = _A1 * np.exp(-arg1)
    k2 = _A2 * np.exp(-arg2)

    return (k1 + k2 * np.power(alpha_safe, _M)) * np.power(1.0 - alpha_safe, _N_ORD)

def _fp_crossply_3layer_rhs(t, y):
    T = np.clip(y[:_CP1_N_SPATIAL], _T_FLOOR, _T_CEIL)
    alpha = np.clip(y[_CP1_N_SPATIAL:2 * _CP1_N_SPATIAL], 0.0, 1.0)
    P = y[2 * _CP1_N_SPATIAL:]

    dadt = _kamal_sourour_rate_vec(T, alpha)

    dT = np.empty(_CP1_N_SPATIAL)
    dP = np.empty(_CP1_N_SPATIAL)

    for layer in range(_CP1_LAYERS):
        start = layer * _CP1_NODES_PER_LAYER
        end = start + _CP1_NODES_PER_LAYER
        diff_layer = _CP1_DIFF[layer]

        for i in range(start, end):
            local = i - start  # node index within layer

            if i == 0:
                T_left = _CP1_T_BOTTOM
            elif local == 0:
                # First node of a non-bottom layer: inter-ply interface
                prev_layer = layer - 1
                k_left = _CP1_K_THRU[prev_layer]
                k_right = _CP1_K_THRU[layer]
                R_left = _CP1_DX / (2.0 * k_left) + _R_CONTACT
                R_right = _CP1_DX / (2.0 * k_right)
                T_left = (T[i - 1] / R_left + T[i] / R_right) / (1.0 / R_left + 1.0 / R_right)
            else:
                T_left = T[i - 1]

            if i == _CP1_N_SPATIAL - 1:
                # Top node: convective BC  ->  k * dT/dx = h * (T_amb - T)
                # One-sided ghost: T_ghost = T[i] + (h*dx/k)*(T_amb - T[i])
                k_top = _CP1_K_THRU[layer]
                T_right = T[i] + (_H_CONV * _CP1_DX / k_top) * (_T_AMBIENT - T[i])
            elif local == _CP1_NODES_PER_LAYER - 1 and layer < _CP1_LAYERS - 1:
                # Last node of a non-top layer: inter-ply interface
                k_left = _CP1_K_THRU[layer]
                k_right = _CP1_K_THRU[layer + 1]
                R_left = _CP1_DX / (2.0 * k_left)
                R_right = _CP1_DX / (2.0 * k_right) + _R_CONTACT
                T_right = (T[i] / R_left + T[i + 1] / R_right) / (1.0 / R_left + 1.0 / R_right)
            else:
                T_right = T[i + 1]

            lap = (T_left - 2.0 * T[i] + T_right) * _CP1_INV_DX2
            dT[i] = diff_layer * lap + _SRC_COEFF * dadt[i]

    # Bottom node held at constant temperature
    dT[0] = 0.0

    # Gas pressure evolution
    dP[:] = (
        (_RHO_RESIN * _V_GAS_SPECIFIC * dadt * _R_GAS_IDEAL * T) / _V_PORE
        - P * _PERM_LOSS
    )

    dy = np.empty(_CP1_DIM)
    dy[:_CP1_N_SPATIAL] = dT
    dy[_CP1_N_SPATIAL:2 * _CP1_N_SPATIAL] = dadt
    dy[2 * _CP1_N_SPATIAL:] = dP
    return dy
Parameters
  • _A1 = 20000
  • _A2 = 1.5e+06
  • _CP1_DIFF = [3.10559e-07, 3.10559e-06, 3.10559e-07]
  • _CP1_DIM = 90
  • _CP1_DX = 0.0003
  • _CP1_INV_DX2 = 1.11111e+07
  • _CP1_K_THRU = [0.5, 5, 0.5]
  • _CP1_LAYERS = 3
  • _CP1_NODES_PER_LAYER = 10
  • _CP1_N_SPATIAL = 30
  • _CP1_T_BOTTOM = 453.15
  • _E1 = 60000
  • _E2 = 75000
  • _EXP_ARG_MAX = 500
  • _H_CONV = 10
  • _M = 0.8
  • _N_ORD = 1.8
  • _PERM_LOSS = 0.001
  • _RHO_RESIN = 1150
  • _R_CONTACT = 0.0005
  • _R_GAS = 8.314
  • _R_GAS_IDEAL = 8.314
  • _SRC_COEFF = 250
  • _T_AMBIENT = 298
  • _T_CEIL = 5000
  • _T_FLOOR = 200
  • _V_GAS_SPECIFIC = 0.02
  • _V_PORE = 0.01
Initial condition
y(0) = [453.15, 298, 298, 298, 298, 298, …] [shape=(90,), min=0.001, max=101325]
Horizon
t ∈ [0, 120]

Canonical RHS excerpt captured from the same registered callable used for the published benchmark. Frozen closure values are summarized below; helper imports and solver settings are intentionally omitted.

Fingerprint

Spread: extreme

Default noise: high

Recommendation snapshot

Clean best: SciPy Radau

Noisy best: SolvSRK

Coverage

14 solver arms · clean + 5 noise levels

Ranked on survival, precision, and speed

Versions & freeze

Methodology →
Freeze
2026-08-13
libsolvsrk
2.3.0
SciPy
1.14
SUNDIALS
CVODE (bundled backend)

20 seeds/cell default · 14 arms · TRL 4–5 · simulation-lab validated · this page: Frontal polymerization Crossply 3layer (frontal-polymerization-crossply-3layer)

Governed SolvTune benchmark freeze; per-arm medians only. RHS definitions and raw trial rows are not published.

Self-reported by Resonix Labs · not independently verified

Results matrix

Pick an objective and a noise level to rank all arms on survival, median SCD, median nfev, and median wall time. Medians across seeds.

Objective

Best overall trade-off of survival, precision, and speed.

Noise level

#SolverSurvivalSCDnfevWallScore
1SciPy RadauSciPy
100%
11.62,190159 ms0.896
2SciPy DOP853SciPy
100%
11.430,3861.74 s0.891
3Tsit5external
100%
10.935,1245.81 s0.879
4SciPy RK45SciPy
100%
10.834,1361.99 s0.877
5SolvSRK
100%
10.82,523125 ms0.877
6SciPy RK23SciPy
100%
9.219,4811.17 s0.839
7SciPy LSODASciPy
100%
7.92,479132 ms0.806
8CVODE BDFexternal
100%
7.871850 ms0.805
9SciPy BDFSciPy
100%
7.686269 ms0.800
10CVODE Adamsexternal
100%
7.54,268264 ms0.798

At Clean, best balanced arm is SciPy Radau · SolvSRK survival 100%, SCD 10.8.

Values are medians across seeds, measured by Resonix Labs on Resonix hardware and not independently verified; nfev and wall are on reference lab hardware (indicative). Under injected noise only SolvSRK and the SciPy arms are run. How we measure accuracy → · Verification status →

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Cite this page

Replace the access date. Pin the freeze ID and library versions when comparing against a later export. Cite it as what it is — a self-reported vendor benchmark, not an independently verified result. The note field says so; please keep it.

@misc{resonix_evidence_frontal_polymerization_crossply_3layer_2026,
  title        = {Resonix Evidence Portal: Frontal polymerization Crossply 3layer},
  author       = {{Resonix Labs (Canada) Inc.}},
  year         = {2026},
  howpublished = {\url{https://resonix.tech/evidence/problems/frontal-polymerization-crossply-3layer}},
  note         = {Self-reported vendor benchmark; internally generated by Resonix Labs and not independently verified. Accessed YYYY-MM-DD. Freeze 2026-08-13; libsolvsrk 2.3.0; SciPy 1.14.}
}

Related

TRL 4–5 · simulation-lab validated · 398 problems · 14 solver arms · clean + 5 noise levels

Freeze: 2026-08-13 · scipy 1.14 · libsolvsrk 2.3.0 · Methodology

Self-reported by Resonix Labs · not independently verified · Verification status