We present a stochastic, grid-based model incorporating a mechanistic model of fire spread, tailored for simulating the fire-driven forest landscapes of boreal Fennoscandia, based on the North American LANDIS model.
Recently, the stochastic sparse grid collocation method has emerged as an attractive alternative to SSFEM.
In this work, we investigate the emissions formation in an industrial gas-turbine combustion chamber using LES with an Eulerian stochastic sub-grid pdf model with reduced chemistry.
A data-driven method is introduced to formulate a two-dimensional grid stochastic energy consumption model for electric vehicles.
Task-level parallelism is used to concurrently evaluate the independent simulation models arising from a sparse grid stochastic collocation method.
This paper develops a sparse grid stochastic collocation method for the reliability analysis of structures with uncertain parameters and loads.
Furthermore, to address the increment of dimensionality induced by the random field, an anisotropic sparse grid stochastic collocation method is used for the efficient computation of the PC coefficients.
This paper propose a method to investigate the impact of stochastic uncertainty of grid-connected wind power generation on power system voltage stability by structure dynamic systems that include node voltages.
In [7, 8], a method of probabilistic analysis was proposed to directly calculate the probabilistic density function of critical eigenvalues of a large scale power system from the probabilistic density function of gird connected multiple sources of wind power generation to investigate the impact of stochastic uncertainty of grid-connected wind generation on power system small-signal stability [9].
At each step, an optimum fluid composition is obtained by a genetic process distributing the fluid particles on a grid by stochastic shots, followed in fine by a refining process.
The computational complexity of numerical models can be broken down into contributions ranging from spatial, temporal and stochastic resolution, e.g., spatial grid resolution, time step size and number of repeated simulations dedicated to quantify uncertainty.
