| Uncertainty quantification for a sailing yacht hull, using multi-fidelity kriging J de Baar, S Roberts, R Dwight, B Mallol Computers & Fluids 123, 185-201, 2015 | 59 | 2015 |
| Kriging regression of PIV data using a local error estimate JHS de Baar, M Percin, RP Dwight, BW van Oudheusden, H Bijl Experiments in fluids 55, 1-13, 2014 | 35 | 2014 |
| Improvements to gradient-enhanced Kriging using a Bayesian interpretation JHS de Baar, RP Dwight, H Bijl International Journal for Uncertainty Quantification 4 (3), 2014 | 33 | 2014 |
| Speeding up Kriging through fast estimation of the hyperparameters in the frequency-domain JHS De Baar, RP Dwight, H Bijl Computers & Geosciences 54, 99-106, 2013 | 30 | 2013 |
| Efficient uncertainty quantification with gradient-enhanced kriging: Applications in fsi JH De Baar, TP Scholcz, CV Verhoosel, RP Dwight, AH van Zuijlen, H Bijl Eccomas Vienna, 2012 | 30 | 2012 |
| Efficient uncertainty quantification for a hypersonic trailing-edge flap, using gradient-enhanced kriging S Bhattrai, JHS de Baar, AJ Neely Aerospace Science and Technology 80, 261-268, 2018 | 28 | 2018 |
| Exploiting adjoint derivatives in high-dimensional metamodels JHS de Baar, TP Scholcz, RP Dwight AIAA Journal 53 (5), 1391-1395, 2015 | 23 | 2015 |
| Multifidelity sparse-grid-based uncertainty quantification for the hokkaido nansei-oki tsunami JHS de Baar, SG Roberts Pure and Applied Geophysics 174, 3107-3121, 2017 | 19 | 2017 |
| Reproducing non-uniform surface temperature profiles on hypersonic cruise vehicles in impulsive wind tunnels J Vennik, AJ Neely, S Tuttle, R Choudhury, DR Buttsworth 21st AIAA International Space Planes and Hypersonics Technologies Conference …, 2017 | 16 | 2017 |
| Stochastic Surrogates for Measurements and Computer Models of Fluids JHS De Baar | 16 | 2014 |
| Wake reconstruction of flapping-wing MAV DelFly II in forward flight M Percin, HE Eisma, JHS de Baar, BW van Oudheusden, B Remes, ... International Micro Air Vehicle Conference and Flight Competition, 2012 | 11 | 2012 |
| A Sobol'Sequence Parametric Analysis of Rotor Thermal Bow in Gas Turbines EO Smith, JHS de Baar, AJ Neely Turbo Expo: Power for Land, Sea, and Air 51135, V07AT33A010, 2018 | 9 | 2018 |
| A gradient-enhanced sparse grid algorithm for uncertainty quantification JHS de Baar, B Harding International Journal for Uncertainty Quantification 5 (5), 2015 | 8 | 2015 |
| A tutorial on adaptive surrogate modeling R Dwight, J De Baar, I Azijli Introduction to Optimization and Multidisciplinary Design in Aeronautics and …, 2012 | 8 | 2012 |
| Impact of Surface Roughness Changes on Surface Wind Speed Over Western Europe: A Study With the Regional Climate Model RACMO LN Luu, E van Meijgaard, SY Philip, SF Kew, JHS de Baar, A Stepek Journal of Geophysical Research: Atmospheres 128 (12), e2022JD038426, 2023 | 6 | 2023 |
| Fast maximum likelihood estimate of the Kriging correlation range in the frequency domain JHS de Baar, RP Dwight, H Bijl IAMG Conference Salzburg, 2011 | 6 | 2011 |
| Enhanced experimental measurements of a gas turbine compressor rotor analogue undergoing thermal bow EO Smith, T Mulholland, J de Baar, A Neely International symposium on air breathing engines, 2017 | 5 | 2017 |
| Numerical simulation of a flapping micro aerial vehicle through wing deformation capture WB Tay, JHS De Baar, M Percin, S Deng, BW Van Oudheusden AIAA journal 56 (8), 3257-3270, 2018 | 4 | 2018 |
| An Acoustic Travelling Wave System for the Analysis of Blisk Mistuning JJ Grant, MR Cosmo, JF Hou, EO Smith, JHS de Baar Turbo Expo: Power for Land, Sea, and Air 51159, V07CT35A014, 2018 | 4 | 2018 |
| Efficient uncertainty quantification for an axial compressor, using adaptive multi-fidelity Kriging JHS de Baar, Z Leylek, AJ Neely ISABE 2017, 2017 | 4 | 2017 |
Richard DwightProfessor, TU DelftVerified email at tudelft.nl
