A taxonomy of global optimization methods based on response surfaces, Journal of Global Optimization, vol.21, issue.4, pp.345-383, 2001. ,
DOI : 10.1023/A:1012771025575
Spectral methods for uncertainty quantification, 2010. ,
DOI : 10.1007/978-90-481-3520-2
The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations, SIAM Journal on Scientific Computing, vol.24, issue.2, pp.619-644, 2002. ,
DOI : 10.1137/S1064827501387826
URL : http://www.dtic.mil/get-tr-doc/pdf?AD=ADA460654
A polynomial dimensional decomposition for stochastic computing, International Journal for Numerical Methods in Engineering, vol.39, issue.4, pp.2191-2116, 2008. ,
DOI : 10.1007/978-1-4612-3094-6
Radial Basis Functions, 2003. ,
Statistics for spatial data, 1993. ,
DOI : 10.1002/9781119115151
Gaussian Processes in Machine Learning, 2006. ,
DOI : 10.1162/089976602317250933
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.363.7289
Aerodynamic shape optimization of civil structures: A CFD-enabled Kriging-based approach, Journal of Wind Engineering and Industrial Aerodynamics, vol.144, pp.154-164, 2015. ,
DOI : 10.1016/j.jweia.2015.03.011
Meta-model-based importance sampling for reliability sensitivity analysis. Structural Safety, pp.27-36, 2014. ,
DOI : 10.1016/j.strusafe.2013.08.010
A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models, Reliability Engineering & System Safety, vol.111, pp.232-240, 2012. ,
DOI : 10.1016/j.ress.2012.10.008
Uncertainty quantification for a sailing yacht hull, using multi-fidelity kriging, Computers & Fluids, vol.123, pp.185-201, 2015. ,
DOI : 10.1016/j.compfluid.2015.10.004
Nonlinear methods for inverse statistical problems, Computational Statistics & Data Analysis, vol.55, issue.1, pp.132-142, 2011. ,
DOI : 10.1016/j.csda.2010.05.030
URL : https://hal.inria.fr/inria-00441967/document
A new surrogate modeling technique combining Kriging and polynomial chaos expansions ??? Application to uncertainty analysis in computational dosimetry, Journal of Computational Physics, vol.286, pp.103-117, 2015. ,
DOI : 10.1016/j.jcp.2015.01.034
URL : https://hal.archives-ouvertes.fr/hal-01143146
Blind Kriging: A New Method for Developing Metamodels, Journal of Mechanical Design, vol.130, issue.3, 2008. ,
DOI : 10.1115/1.2829873
Adaptive surrogate modeling by ANOVA and sparse polynomial dimensional decomposition for global sensitivity analysis in fluid simulation, Journal of Computational Physics, vol.314, pp.557-589, 2016. ,
DOI : 10.1016/j.jcp.2016.03.026
URL : https://hal.archives-ouvertes.fr/hal-01286721
Sensitivity estimates for nonlinear mathematical models, Mathematical modelling & Computational Experiments, vol.1, pp.407-414, 1993. ,
Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Mathematics and Computers in Simulation, vol.55, issue.1-3, pp.271-280, 2001. ,
DOI : 10.1016/S0378-4754(00)00270-6
Adaptive-sparse polynomial dimensional decomposition methods for high-dimensional stochastic computing, Computer Methods in Applied Mechanics and Engineering, vol.274, pp.56-83, 2014. ,
DOI : 10.1016/j.cma.2014.01.027
URL : http://arxiv.org/pdf/1402.3330
A comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, vol.21, issue.2, pp.239-245, 1979. ,
DACE: a MATLAB kriging toolbox, version 2.0, 2002. ,
Optimal Latin-hypercube designs for computer experiments, Journal of Statistical Planning and Inference, vol.39, issue.1, pp.95-111, 1994. ,
DOI : 10.1016/0378-3758(94)90115-5
Adaptive Response Surface Method Using Inherited Latin Hypercube Design Points, Journal of Mechanical Design, vol.125, issue.2, pp.210-220, 2003. ,
DOI : 10.1115/1.1561044
URL : http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.1031.200&rep=rep1&type=pdf
Design and analysis of computer experiments. Statistical sciences, pp.409-435, 1989. ,
An adaptive Stochastic Finite Elements approach based on Newton???Cotes quadrature in simplex elements, Computers & Fluids, vol.38, issue.6, pp.1270-1288, 2009. ,
DOI : 10.1016/j.compfluid.2008.12.002
Refinement Criteria for Simplex Stochastic Collocation with Local Extremum Diminishing Robustness, SIAM Journal on Scientific Computing, vol.34, issue.3, pp.1522-1543, 2012. ,
DOI : 10.1137/100817498
Simplex Stochastic Collocation with Random Sampling and Extrapolation for Nonhypercube Probability Spaces, SIAM Journal on Scientific Computing, vol.34, issue.2 ,
DOI : 10.1137/100817504
Simplex stochastic collocation with ENO-type stencil selection for robust uncertainty quantification, Journal of Computational Physics, vol.239, pp.1-21, 2013. ,
DOI : 10.1016/j.jcp.2012.12.030
Mesh Adaptive Direct Search Algorithms for Constrained Optimization, SIAM Journal on Optimization, vol.17, issue.1, pp.188-217, 2006. ,
DOI : 10.1137/040603371
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.413.9526
A radial basis function method for global optimization, Journal of Global Optimization, vol.19, issue.3, pp.201-227, 2001. ,
DOI : 10.1023/A:1011255519438
A stochastic radial basis function method for the global optimization of expensive functions, IN- FORMS Journal on Computing, vol.19, issue.4, pp.497-509, 2007. ,
Stochastic radial basis function algorithms for largescale optimization involving expensive black-box objective and constraint functions, Comput. Oper. Res, vol.38, issue.5, pp.837-853, 2011. ,
A method for simulation based optimization using radial basis functions, Optimization and Engineering, vol.90, issue.4, pp.501-532, 2010. ,
DOI : 10.1007/978-3-642-82118-9
Metric construction by length distribution tensor and edge based error for anisotropic adaptive meshing, Journal of Computational Physics, vol.230, issue.7, pp.2391-2405, 2011. ,
DOI : 10.1016/j.jcp.2010.11.041
URL : https://hal.archives-ouvertes.fr/hal-00579536
Adaptive time-step with anisotropic meshing for incompressible flows, Journal of Computational Physics, vol.241, pp.195-211, 2013. ,
DOI : 10.1016/j.jcp.2012.12.010
URL : https://hal.archives-ouvertes.fr/hal-01470576
Introduction to Derivative-Free Optimization, Society for Industrial and Applied Mathematics, 2009. ,
DOI : 10.1137/1.9780898718768
The theory of regionalised variables and its applications, 1971. ,
Improving accuracy and compensating for uncertainty in surrogate modeling, 2009. ,
URL : https://hal.archives-ouvertes.fr/tel-00770844
Active Subspace Methods in Theory and Practice: Applications to Kriging Surfaces, SIAM Journal on Scientific Computing, vol.36, issue.4, pp.1500-1524, 2014. ,
DOI : 10.1137/130916138
URL : http://arxiv.org/pdf/1304.2070
A hybrid anchored-ANOVA ??? POD/Kriging method for uncertainty quantification in unsteady high-fidelity CFD simulations, Journal of Computational Physics, vol.324, pp.137-173, 2016. ,
DOI : 10.1016/j.jcp.2016.07.036
URL : https://hal.archives-ouvertes.fr/hal-01461789
A comparative study between kriging and adaptive sparse tensor-product methods for multi-dimensional approximation problems in aerodynamics design, ESAIM: Proceedings and Surveys, vol.48, pp.248-261, 2015. ,
DOI : 10.1051/proc/201448011
URL : https://hal.archives-ouvertes.fr/hal-01353245
Efficient global optimization of expensive black-box functions, Journal of Global Optimization, vol.13, issue.4, pp.455-492, 1998. ,
DOI : 10.1023/A:1008306431147
Bayesian-Based Method with Metamodels for Rebuilding Freestream Conditions in Atmospheric Entry Flows, AIAA Journal, vol.53, issue.3, pp.522190-2197, 2014. ,
DOI : 10.4208/cicp.2009.v6.p826
URL : https://hal.archives-ouvertes.fr/hal-00855898
Accurate and efficient modelling of high temperature nonequilibrium air flows, 2001. ,
Chemical-Kinetic Parameters of Hyperbolic Earth Entry, Journal of Thermophysics and Heat Transfer, vol.14, issue.12, pp.76-90, 2001. ,
DOI : 10.2514/2.6482
Towards the ultimate conservative difference scheme. V. A second-order sequel to Godunov's method, Journal of Computational Physics, vol.32, issue.1, pp.101-136, 1979. ,
DOI : 10.1016/0021-9991(79)90145-1
Upwind difference schemes for hyperbolic systems of conservation laws, Mathematics of Computation, vol.38, issue.158, pp.339-374, 1982. ,
DOI : 10.1090/S0025-5718-1982-0645656-0
The VKI Plasmatron Characteristics and Performance, Defense Technical Information Center, 2000. ,
Porous-Material Analysis Toolbox Based on OpenFOAM and Applications, Journal of Thermophysics and Heat Transfer, vol.28, issue.2, pp.191-202, 2014. ,
DOI : 10.2514/6.2008-3805
Comparing error estimation measures for polynomial and kriging approximation of noise-free functions. Structural and multidisciplinary optimization, pp.429-442, 2009. ,
Computationally Inexpensive Metamodel Assessment Strategies, AIAA Journal, vol.2, issue.3, pp.2053-2060, 2002. ,
DOI : 10.1007/978-1-4899-3095-8
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.89.9109