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.
A stochastic collocation method for elliptic partial differential equations with random input data.SIAM Journal on Numerical Analysis, 45(3):1005–1034
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Stochastic Smoothed Particle Hydrodynamics for Stochastic Mechanics Problems
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.