Sealed Electronics Enclosure Thermal (3-state)

ADVANTAGES1 · dim 3

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-state lumped thermal model for a sealed electronics enclosure. States: internal air temperature, wall temperature, cumulative heat. 15 W heat load into a PETG enclosure with natural convection. C_internal/R_int_wall vs C_wall/R_wall_amb — stiffness ratio ~5:1.

Thermal & heat transfer

Problem definition

Incropera & DeWitt, 'Fundamentals of Heat and Mass Transfer'; FTRD Technical Specification Section 7.4

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 rhs_sealed_enclosure_thermal(t: float, y: np.ndarray) -> np.ndarray:
    T_int, T_wall, Q_acc = y[0], y[1], y[2]
    Q_to_wall = (T_int - T_wall) / _R_INT_WALL
    Q_to_amb = (T_wall - _T_AMB) / _R_WALL_AMB
    dT_int = (_Q_IN - Q_to_wall) / _C_INT
    dT_wall = (Q_to_wall - Q_to_amb) / _C_WALL
    dQ = _Q_IN
    return np.array([dT_int, dT_wall, dQ])
Parameters
  • _C_INT = 50
  • _C_WALL = 30
  • _Q_IN = 15
  • _R_INT_WALL = 0.166666666667
  • _R_WALL_AMB = 1.66666666667
  • _T_AMB = 25
Initial condition
y(0) = [25, 25, 0]
Horizon
t ∈ [0, 3600]

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: low

Default noise: low

Recommendation snapshot

Clean best: SolvSRK

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: Sealed Electronics Enclosure Thermal (3-state) (sealed-electronics-enclosure-thermal-3-state)

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
1SolvSRK
100%
14.29,275199 ms0.958
2SciPy RadauSciPy
100%
13.81,09122 ms0.947
3TRBDF2external
100%
13.82,7225.12 s0.947
4Vern9external
100%
13.54,5143.87 s0.940
5Vern7external
100%
13.52,7823.98 s0.940
6CVODE Adamsexternal
100%
13.441610 ms0.939
7SciPy BDFSciPy
100%
13.041115 ms0.928
8SciPy LSODASciPy
100%
12.68173 ms0.920
9FBDFexternal
100%
12.53494.91 s0.917
10SciPy DOP853SciPy
100%
12.52,54615 ms0.916
11CVODE BDFexternal
100%
11.92738 ms0.903
12SciPy RK23SciPy
100%
11.32,20418 ms0.889
13SciPy RK45SciPy
100%
11.32,52216 ms0.888
14Tsit5external
100%
10.92,7241.01 s0.879

At Clean, best balanced arm is SolvSRK.

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 →

SolvScout · free

Profile your problem for free

This page shows one published benchmark cell. SolvScout fingerprints your ODE, compares it to the full corpus, and recommends a solver with the same survival / precision / speed ranking you see here — including when a SciPy arm wins.

SolvSRK · 30-day trial

Run the winner on your machine

SolvSRK is the stiffness-adaptive integrator behind the SolvSRK column in these tables. Create an account, activate a machine, and take a 30-day trial — same binary you'd ship after purchase.

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_sealed_electronics_enclosure_thermal_3_state_2026,
  title        = {Resonix Evidence Portal: Sealed Electronics Enclosure Thermal (3-state)},
  author       = {{Resonix Labs (Canada) Inc.}},
  year         = {2026},
  howpublished = {\url{https://resonix.tech/evidence/problems/sealed-electronics-enclosure-thermal-3-state}},
  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