| The structural response of cylindrical shells to internal shock loading WM Beltman, EN Burcsu, JE Shepherd, L Zuhal | 95 | 1999 |
| Global sensitivity analysis via multi-fidelity polynomial chaos expansion PS Palar, LR Zuhal, K Shimoyama, T Tsuchiya Reliability Engineering & System Safety 170, 175-190, 2018 | 82 | 2018 |
| A comparative study of multi-objective expected improvement for aerodynamic design LR Zuhal, PS Palar, K Shimoyama Aerospace Science and Technology 91, 548-560, 2019 | 54 | 2019 |
| On the use of surrogate models in engineering design optimization and exploration: The key issues PS Palar, RP Liem, LR Zuhal, K Shimoyama Proceedings of the genetic and evolutionary computation conference companion …, 2019 | 45 | 2019 |
| Resolving multi objective stock portfolio optimization problem using genetic algorithm LR Zuhal 2010 The 2nd International Conference on Computer and Automation Engineering …, 2010 | 45 | 2010 |
| Gaussian process surrogate model with composite kernel learning for engineering design P Satria Palar, L Rizki Zuhal, K Shimoyama AIAA journal 58 (4), 1864-1880, 2020 | 43 | 2020 |
| Enhancing the explainability of regression-based polynomial chaos expansion by Shapley additive explanations PS Palar, LR Zuhal, K Shimoyama Reliability Engineering & System Safety 232, 109045, 2023 | 38 | 2023 |
| On dimensionality reduction via partial least squares for Kriging-based reliability analysis with active learning LR Zuhal, GA Faza, PS Palar, RP Liem Reliability Engineering & System Safety 215, 107848, 2021 | 29 | 2021 |
| Benchmarking multi-objective Bayesian global optimization strategies for aerodynamic design LR Zuhal, C Amalinadhi, YB Dwianto, PS Palar, K Shimoyama 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials …, 2018 | 23 | 2018 |
| Gaussian processes and support vector regression for uncertainty quantification in aerodynamics PS Palar, K Zakaria, LR Zuhal, K Shimoyama, RP Liem AIAA Scitech 2021 Forum, 0181, 2021 | 19 | 2021 |
| On kernel functions for bi-fidelity Gaussian process regressions PS Palar, L Parussini, L Bregant, K Shimoyama, LR Zuhal Structural and Multidisciplinary Optimization 66 (2), 37, 2023 | 16 | 2023 |
| On physics-informed deep learning for solving navier-stokes equations C Amalinadhi, PS Palar, R Stevenson, L Zuhal AIAA SCITECH 2022 Forum, 1436, 2022 | 16 | 2022 |
| On the impact of covariance functions in multi-objective Bayesian optimization for engineering design PS Palar, LR Zuhal, T Chugh, A Rahat AIAA Scitech 2020 Forum, 1867, 2020 | 16 | 2020 |
| Near field dynamics of wing tip vortices L Zuhal, M Gharib 15th AIAA Computational Fluid Dynamics Conference, 2710, 2001 | 16 | 2001 |
| Formation and near-field dynamics of a wing tip vortex LR Zuhal California Institute of Technology, 2001 | 14 | 2001 |
| Polynomial-chaos–kriging with gradient information for surrogate modeling in aerodynamic design LR Zuhal, K Zakaria, PS Palar, K Shimoyama, RP Liem AIAA journal 59 (8), 2950-2967, 2021 | 13 | 2021 |
| A particle interaction-based crack model using an improved smoothed particle hydrodynamics for fatigue crack growth simulations IM Wiragunarsa, LR Zuhal, T Dirgantara, IS Putra International Journal of Fracture 229 (2), 229-244, 2021 | 13 | 2021 |
| Multi-objective design space exploration using explainable surrogate models PS Palar, YB Dwianto, LR Zuhal, J Morlier, K Shimoyama, S Obayashi Structural and Multidisciplinary Optimization 67 (3), 38, 2024 | 12 | 2024 |
| Core Spreading Vortex Method for Simulating 3D Flow around Bluff Bodies. LR Zuhal, DV Dung, AJ Sepnov, H Muhammad Journal of Engineering & Technological Sciences 46 (4), 2014 | 12 | 2014 |
| Benchmarking constrained surrogate-based optimization on low speed airfoil design problems PS Palar, YB Dwianto, RG Regis, A Oyama, LR Zuhal Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 9 | 2019 |
