We consider the problem of uncertainty quantification analysis of the output of underground flow simulations. We consider in particular fractured media described via the discrete fracture network model; within this framework, we address the relevant case of networks in which the geometry of the fractures is described by stochastic parameters. In this context, due to a possible lack of smoothness in the quantity of interest with respect to the stochastic parameters, well assessed techniques such as stochastic collocation may fail in providing reliable estimates of first-order moments of the quantity of interest. In this paper, we overcome this issue by applying the Multilevel Monte Carlo method, using as underlying solver an extremely robust method.

Uncertainty quantification in Discrete Fracture Network models: stochastic geometry / Berrone, Stefano; Canuto, Claudio; Pieraccini, Sandra; Scialo', Stefano. - In: WATER RESOURCES RESEARCH. - ISSN 1944-7973. - STAMPA. - 54:2(2018), pp. 1338-1352. [10.1002/2017WR021163]

Uncertainty quantification in Discrete Fracture Network models: stochastic geometry

BERRONE, Stefano;CANUTO, CLAUDIO;PIERACCINI, SANDRA;SCIALO', STEFANO
2018

Abstract

We consider the problem of uncertainty quantification analysis of the output of underground flow simulations. We consider in particular fractured media described via the discrete fracture network model; within this framework, we address the relevant case of networks in which the geometry of the fractures is described by stochastic parameters. In this context, due to a possible lack of smoothness in the quantity of interest with respect to the stochastic parameters, well assessed techniques such as stochastic collocation may fail in providing reliable estimates of first-order moments of the quantity of interest. In this paper, we overcome this issue by applying the Multilevel Monte Carlo method, using as underlying solver an extremely robust method.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2673700
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