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pith:PADXWFXX

pith:2025:PADXWFXX55NRIH6TRYIJ723S6V

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Data-driven modeling of multivariate stochastic trajectories -- Application to water waves

Romain Hasco\"et

Functional principal components combined with vine copulas and conditional tail models generate joint stochastic trajectories for water wave variables.

arxiv:2512.11948 v2 · 2025-12-12 · physics.flu-dyn · physics.data-an

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Claims

C1strongest claim

The stochastic trajectories of these three variables are modeled jointly. The vertical Lagrangian acceleration of the fluid is employed to enforce a wave-breaking filter in the stochastic model. The number of hyperparameters in the stochastic framework is reduced to three, and a stepwise calibration strategy is proposed for their adjustment. The capabilities of the model are illustrated by predicting the distributions of selected response variables and by generating synthetic trajectories.

C2weakest assumption

That the functional principal components extracted from the observed trajectories sufficiently capture the variability needed for accurate joint tail modeling, and that the vine copula plus Heffernan-Tawn framework faithfully represents the dependence structure in the DeRisk wave data without significant bias from the chosen feature reduction.

C3one line summary

A data-driven stochastic model for water wave kinematics is built by combining functional PCA feature reduction with vine copulas for the bulk distribution and Heffernan-Tawn conditional modeling for the tails, enabling synthetic trajectory generation under a breaking constraint.

References

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[1] Naess, Prediction of extremes related to the second-order, sum-frequency response of a TLP, in: ISOPE International Ocean and Polar Engineering Conference, ISOPE, 1992, pp 1992

[2] Faltinsen, Sea loads on ships and offshore structures, Vol 1993

[3] O. M. Faltinsen, J. Newman, T. Vinje, Nonlinear wave loads on a slender vertical cylinder, Journal of Fluid Mechanics 289 (1995) 179–198 1995

[4] E. E. Bachynski, T. Moan, Ringing loads on tension leg platform wind turbines, Ocean engi- neering 84 (2014) 237–248 2014

[5] P.Renaud, F.Hulin, A.Tassin, J.-F.Filipot, N.Jacques, Analysisofslammingloadsinducedby breaking waves on vertical cylinders using fully nonlinear wave kinematics and semi-analytical load model, Coasta 2025

Receipt and verification

First computed	2026-05-17T23:39:16.874191Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

78077b16f7ef5b141fd38e109feb72f554741a8cd9d30c2f663fc46fdfe7b394

Aliases

arxiv: 2512.11948 · arxiv_version: 2512.11948v2 · doi: 10.48550/arxiv.2512.11948 · pith_short_12: PADXWFXX55NR · pith_short_16: PADXWFXX55NRIH6T · pith_short_8: PADXWFXX

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curl -sH 'Accept: application/ld+json' https://pith.science/pith/PADXWFXX55NRIH6TRYIJ723S6V \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 78077b16f7ef5b141fd38e109feb72f554741a8cd9d30c2f663fc46fdfe7b394

Canonical record JSON

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    "abstract_canon_sha256": "214d7ca012b45de648fee2fb5b4a0e5ebb5faba27f08e77149a282ad352c2137",
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      "physics.data-an"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "primary_cat": "physics.flu-dyn",
    "submitted_at": "2025-12-12T18:46:37Z",
    "title_canon_sha256": "0405e6eed09983837c28b82e017037fc97cbe88321b1647c4591efe248cccaaf"
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