Gaussian process modeling for stochastic multi-fidelity simulators, with application to fire safety

To assess the possibility of evacuating a building in case of a fire, a standard method consists in simulating the propagation of fire, using finite difference methods and takes into account the random behavior of the fire, so that the result of a simulation is non-deterministic. The mesh fineness tunes the quality of the numerical model, and its computational cost. Depending on the mesh fineness, one simulation can last anywhere from a few minutes to several weeks. In this article, we focus on predicting the behavior of the fire simulator at fine meshes, using cheaper results, at coarser meshes. In the literature of the design and analysis of computer experiments, such a problem is referred to as multi-fidelity prediction. Our contribution is to extend to the case of stochastic simulators the Bayesian multi-fidelity model proposed by Picheny and Ginsbourger (2013) and Tuo et al. (2014).

• Publication year

  2016

• Venue

  arXiv: Methodology

• Publication date

  2016-05-09

• Fields of study

  Mathematics, Computer Science, Engineering, Environmental Science

• Identifiers
  arXiv 1605.02561
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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