BDA (BAL.FST.HI)

ADVANTAGES1 · dim 9

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 →

BDA (BAL.FST.HI) benchmark in the defense-autonomy domain.

Defense autonomy

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 rhs(t, y):
    x, yp, z = y[0], y[1], y[2]
    vx, vy, vz = y[3], y[4], y[5]
    omega = y[6]
    CD = y[7]
    integ = y[8]

    V = np.sqrt(vx**2 + vy**2 + vz**2 + 0.01)
    q_dyn = 0.5 * _RHO * V**2
    D = q_dyn * CD * A_ref / m

    wx = np.interp(t, _noise_ts, wind_noise[0])
    wy = np.interp(t, _noise_ts, wind_noise[1])
    wz = np.interp(t, _noise_ts, wind_noise[2])

    d = np.empty(9)

    # Position
    d[0] = vx
    d[1] = vy
    d[2] = vz

    # Velocity: drag + gravity + optional thrust + tumble-induced lift scatter
    f_thrust = thrust * integ
    d[3] = -D * vx / max(V, 0.01) + f_thrust * np.cos(heading) / m + wx
    d[4] = -D * vy / max(V, 0.01) + f_thrust * np.sin(heading) / m + wy
    d[5] = -D * vz / max(V, 0.01) + _G + wz

    # Tumble spin-up
    d[6] = (omega_target - omega) / tau_tumble

    # Drag coefficient transition
    d[7] = (CD_target - CD) / tau_damage

    # Integrity decay
    d[8] = -(integ - (0.0 if mode == "ballistic" else 0.3)) / 5.0 if mode != "intact" else 0.0

    return d
Parameters
  • A_ref = 0.05
  • CD_target = 1
  • _G = 9.81
  • _RHO = 1.225
  • _noise_ts = [0, 0.01, 0.02, 0.03, 0.04, 0.05, …] [shape=(3001,), min=0, max=30]
  • heading = 0.3
  • m = 3
  • mode = 'ballistic'
  • omega_target = 10
  • tau_damage = 0.5
  • tau_tumble = 1
  • thrust = 0
  • wind_noise = [0.0628651105467, -0.0660524316457, 0.320211325222, 0.0524500585765, -0.267834686581, 0.180797527455, …] [shape=(3, 3001), min=-1.94971086503, max=1.62859953736]
Initial condition
y(0) = [0, 0, -300, 47.7668244563, 14.7760103331, -5, 0, 0.3, 0]
Horizon
t ∈ [0, 30]

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: BDA (BAL.FST.HI) (bda-bal-fst-hi)

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%
10.9274,3673.01 s0.879
2SciPy LSODASciPy
100%
8.3151,365933 ms0.816
3SciPy BDFSciPy
100%
7.7129,4983.85 s0.802
4SciPy RK23SciPy
100%
7.4122,4651.06 s0.794
5CVODE Adamsexternal
100%
7.387,088828 ms0.794
6FBDFexternal
100%
7.1182,0037.63 s0.789
7CVODE BDFexternal
100%
7.0109,434966 ms0.785
8Vern9external
100%
6.5658,72214.88 s0.774
9Tsit5external
100%
6.2259,02616.15 s0.767
10SciPy RadauSciPy
100%
6.2383,7117.42 s0.766
11Vern7external
100%
5.9466,29211.40 s0.759
12SciPy DOP853SciPy
100%
5.9415,2863.08 s0.759
13SciPy RK45SciPy
100%
5.8164,1501.33 s0.757
14TRBDF2external
100%
4.575,3335.37 s0.725

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 →

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SolvSRK · 30-day trial

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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_bda_bal_fst_hi_2026,
  title        = {Resonix Evidence Portal: BDA (BAL.FST.HI)},
  author       = {{Resonix Labs (Canada) Inc.}},
  year         = {2026},
  howpublished = {\url{https://resonix.tech/evidence/problems/bda-bal-fst-hi}},
  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