Research Staff Member
Affiliation: School of Engineering
E-mail: D dot Crevillen-Garcia(at)warwick dot ac dot uk
- Methods for uncertainty quantification in computational fluid dynamics models: Monte Carlo, quasi Monte Carlo and multilevel Monte Carlo methods
- Gaussian process emulation of high-dimensional outputs. Bayesian regression and classification models
- Polynomial Chaos expansions, stochastic Galerkin and stochastic collocation methods for uncertainty quantification in systems of partial differential equations with random inputs
- Models for Metal Electrodeposition in Redox Flow Batteries: Kinetic Monte Carlo, Molecular Dynamics and Phase Field modelling
Recent Journal Publications
D. Crevillén-García, R.D. Wilkinson, A.A. Shah and H. Power (2017) Gaussian Process Modelling for Uncertainty Quantification in Convectively-Enhanced Dissolution Processes in Porous Media. Adv. Water Resour. 99, 1-14. http://dx.doi.org/10.1016/j.advwatres.2016.11.006. Download here
D. Crevillén-García and H. Power (2017) Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media. R. Soc. open sci. 4: 170203.
http://dx.doi.org/10.1098/rsos.170203. Download here
D. Crevillén-García (2018) Surrogate modelling for the prediction of spatial fields based on simultaneous dimensionality reduction of high-dimensional input/output spaces. R. Soc. open sci. 5: 171933. http://dx.doi.org/10.1098/rsos.171933. Download here
D. Crevillén-García, P.K. Leung, A. Rodchanarowan and A.A. Shah (2018) Uncertainty quantification for flow and transport in highly heterogeneous porous media based on simultaneous stochastic model dimensionality reduction. Transp Porous Med, 1-17. https://doi.org/10.1007/s11242-018-1114-2. Download here
D. Crevillén-García, P.K. Leung and A.A. Shah (2018) An emulator for kinetic Monte Carlo simulations of kinetically controlled metal electrodeposition. J. Phys.: Conf. Ser. 1053 012081. Download here.