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pith:2026:XJGAZGC3MYS3LJQJKIEHMA3JE5
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Stochastic Smoothed Particle Hydrodynamics for Stochastic Mechanics Problems

Md Rushdie Ibne Islam, Mridul Tiwari, Sawan Kumar, Souvik Chakraborty

Stochastic SPH represents uncertainties via polynomial chaos and Karhunen-Loève expansions to turn stochastic PDEs into coupled deterministic ODEs solved on particles.

arxiv:2605.12540 v1 · 2026-05-08 · cs.CE

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Claims

C1strongest claim

S-SPH achieves up to three orders of magnitude reduction in computational cost relative to direct sampling approaches while demonstrating excellent agreement with Monte Carlo simulation statistics of mean and variance on benchmark problems.

C2weakest assumption

That the chosen polynomial chaos order and Karhunen-Loève truncation are sufficient to capture the statistics of the target uncertainties without significant truncation error, and that the ghost-particle boundary treatment remains stable and accurate once the stochastic coefficients are introduced.

C3one line summary

S-SPH extends mesh-free SPH to stochastic problems via polynomial chaos and KL expansions, delivering mean and variance statistics that match Monte Carlo at up to 1000 times lower cost on benchmark advection and Burgers flows.

References

55 extracted · 55 resolved · 0 Pith anchors

[1] Sph-exa2: Scaling smoothed particle hydrodynamics to exascale for cosmology and astrophysics, 2024 2024
[2] Smoothed particle magnetohydrodynamics: Applications to astrophysical problems.Frontiers in Astronomy and Space Sciences, 10, 2023 2023
[3] V . Springel. E pur si muove: Galilean-invariant cosmological hydrodynamical simulation.Monthly Notices of the Royal Astronomical Society, 401(2):791–851, 2010 2010
[4] Violeau.Smoothed Particle Hydrodynamics: A Meshfree Particle Method 2012
[6] Y . Ono, S. Nishida, and J. Kiyono. Sph simulation for seismic behavior of earth structures. In14th World Conference on Earthquake Engineering, 2008 2008
Receipt and verification
First computed 2026-05-18T03:10:02.357933Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

ba4c0c985b6625b5a60952087603692762aac2fe51fcc89b7171b5cbd48915aa

Aliases

arxiv: 2605.12540 · arxiv_version: 2605.12540v1 · doi: 10.48550/arxiv.2605.12540 · pith_short_12: XJGAZGC3MYS3 · pith_short_16: XJGAZGC3MYS3LJQJ · pith_short_8: XJGAZGC3
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/XJGAZGC3MYS3LJQJKIEHMA3JE5 \
  | 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: ba4c0c985b6625b5a60952087603692762aac2fe51fcc89b7171b5cbd48915aa
Canonical record JSON
{
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    "abstract_canon_sha256": "453c5d0078dc9bfd560f4de0a1986e7d6c51345ade9a809e81efa097fb8a3639",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CE",
    "submitted_at": "2026-05-08T03:42:02Z",
    "title_canon_sha256": "a6274fcb7f87d3cb8ea2070d8eb21f9201d8a252fcb8e654c7f7412b5e0bb677"
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