Adaptive multi-fidelity sampling for CFD-based optimisation via radial basis function metamodels

References

• Antognoli, Luca, Marco Bibuli, Matteo Diez, Danilo Durante, Simone Ficini, Salvatore Marrone, Angelo Odetti, Ivan Santic, and Andrea Serani. 2019. “A Synergetic Design Study of a Passenger-Hydrofoil Flapped Surface: Experimental and Computational Fluid Dynamics, Optimization, and Control.” In Proceedings of the 8th International Conference on Computational Methods in Marine Engineering (Marine 2019), 334–345.
   Google Scholar
• Baar, Jouke de, Stephen Roberts, Richard Dwight, and Benoit Mallol. 2015. “Uncertainty Quantification for a Sailing Yacht Hull, Using Multi-fidelity Kriging.” Computers & Fluids 123: 185–201.
   Web of Science ®Google Scholar
• Cai, Xiwen, Haobo Qiu, Liang Gao, Li Wei, and Xinyu Shao. 2017. “Adaptive Radial-Basis-Function-Based Multifidelity Metamodeling for Expensive Black-Box Problems.” AIAA Journal 55 (7): 2424–2436.
   Web of Science ®Google Scholar
• Diez, Matteo, Silvia Volpi, Andrea Serani, Frederick Stern, and Emilio F. Campana. 2019. Simulation-Based Design Optimization by Sequential Multi-criterion Adaptive Sampling and Dynamic Radial Basis Functions, 213–228. Cham: Springer International Publishing.
   Google Scholar
• Durand, Mathieu. 2012. “Light and Flexible Fluid/Structure Interaction, Application to Sailing Boats.” Theses, Ecole Centrale de Nantes (ECN). https://hal.archives-ouvertes.fr/tel-01203748.
   Google Scholar
• Han, Zhong-Hua, Stefan Görtz, and Ralf Zimmermann. 2013. “Improving Variable-fidelity Surrogate Modeling Via Gradient-enhanced Kriging and a Generalized Hybrid Bridge Function.” Aerospace Science and Technology 25 (1): 177–189.
   Web of Science ®Google Scholar
• Huang, Deng, Theodore T. Allen, William I. Notz, and R. Allen Miller. 2006. “Sequential Kriging Optimization Using Multiple-fidelity Evaluations.” Structural and Multidisciplinary Optimization 32 (5): 369–382.
   Web of Science ®Google Scholar
• Huband, S., P. Hingston, L. Barone, and L. While. 2006. “A Review of Multiobjective Test Problems and a Scalable Test Problem Toolkit.” IEEE Transactions on Evolutionary Computation 10 (5): 477–506.
   Web of Science ®Google Scholar
• Irvine Jr., M., J. Longo, and F. Stern. 2008. “Pitch and Heave Tests and Uncertainty Assessment for a Surface Combatant in Regular Head Waves.” Journal of Ship Research 52 (2): 146–163.
   Web of Science ®Google Scholar
• Jin, Ruichen, Wei Chen, and Timothy W. Simpson. 2001. “Comparative Studies of Metamodelling Techniques Under Multiple Modelling Criteria.” Structural and Multidisciplinary Optimization 23 (1): 1–13.
   Web of Science ®Google Scholar
• Jones, Donald R., Matthias Schonlau, and William J. Welch. 1998. “Efficient Global Optimization of Expensive Black-Box Functions.” Journal of Global Optimization 13 (4): 455–492.
   Web of Science ®Google Scholar
• Kennedy, M. C., and A. O'Hagan. 2000. “Predicting the Output From a Complex Computer Code When Fast Approximations Are Available.” Biometrika 87 (1): 1–13.
   Web of Science ®Google Scholar
• Kuya, Yuichi, Kenji Takeda, Xin Zhang, and Alexander I. J. Forrester. 2011. “Multifidelity Surrogate Modeling of Experimental and Computational Aerodynamic Data Sets.” AIAA Journal 49 (2): 289–298.
   Web of Science ®Google Scholar
• Leroyer, A., and M. Visonneau. 2005. “Numerical Methods for RANSE Simulations of a Self-propelled Fish-like Body.” Journal of Fluids and Structures 20 (7): 975–991. Fluid-Plate Interactions.
   Web of Science ®Google Scholar
• Liu, Haitao, Yew-Soon Ong, and Jianfei Cai. 2018. “A Survey of Adaptive Sampling for Global Metamodeling in Support of Simulation-based Complex Engineering Design.” Structural and Multidisciplinary Optimization 57 (1): 393–416.
   Web of Science ®Google Scholar
• Liu, Y., Y. Shi, Q. Zhou, and R. Xiu. 2016. “A Sequential Sampling Strategy to Improve the Global Fidelity of Metamodels in Multi-level System Design.” Structural and Multidisciplinary Optimization 53 (6): 1295–1313.
   Web of Science ®Google Scholar
• Mackman, T. J., and C. B. Allen. 2010. “Investigation of An Adaptive Sampling Method for Data Interpolation Using Radial Basis Functions.” International Journal for Numerical Methods in Engineering 83 (7): 915–938.
   Web of Science ®Google Scholar
• Ng, Leo Wai-Tsun, and Michael Eldred. 2012. “Multifidelity Uncertainty Quantification Using Non-Intrusive Polynomial Chaos and Stochastic Collocation.” In 53rd AIAA/ASME/ ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Structures, Structural Dynamics, and Materials and Co-located Conferences.
   Google Scholar
• Pellegrini, R., U. Iemma, C. Leotardi, E. F. Campana, and M. Diez. 2016. “Multi-Fidelity Adaptive Global Metamodel of Expensive Computer Simulations.” In 2016 IEEE Congress on Evolutionary Computation (CEC), July, 4444–4451.
   Google Scholar
• Pellegrini, R., A. Serani, M. Diez, J. Wackers, P. Queutey, and M. Visonneau. 2018. “Adaptive Sampling Criteria for Multi-fidelity Metamodels in CFD-based Shape Optimization.” In 7th European Conference on Computational Fluid Dynamics (ECFD 7), Glasgow, UK: 11-15 June.
   Google Scholar
• Pellegrini, Riccardo, Andrea Serani, Cecilia Leotardi, Umberto Iemma, Emilio F. Campana, and Matteo Diez. 2017. “Formulation and Parameter Selection of Multi-objective Deterministic Particle Swarm for Simulation-based Optimization.” Applied Soft Computing 58: 714–731.
   Web of Science ®Google Scholar
• Ploé, Patrick, Romain Lanos, Michel Visonneau, and Jeroen Wackers. 2017. “Bayesian Strategies for Simulation Based Optimisation and Response Surface Creation Using a Single Tool – Application to Hydrofoil Optimisation.” In Proceedings of the 7th International Conference on Computational Methods in Marine Engineering (Marine 2017).
   Google Scholar
• Queutey, Patrick, and Michel Visonneau. 2007. “An Interface Capturing Method for Free-Surface Hydrodynamic Flows.” Computers & Fluids 36 (9): 1481–1510.
   Web of Science ®Google Scholar
• Serani, Andrea, and Matteo Diez. 2018. “Shape Optimization under Stochastic Conditions by Design-Space Augmented Dimensionality Reduction.” In 19th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference (MA&O), AVIATION 2018, Atlanta, GA, USA, June 25–29.
   Google Scholar
• Serani, Andrea, Giovanni Fasano, Giampaolo Liuzzi, Stefano Lucidi, Umberto Iemma, Emilio F. Campana, Frederick Stern, and Matteo Diez. 2016a. “Ship Hydrodynamic Optimization by Local Hybridization of Deterministic Derivative-free Global Algorithms.” Applied Ocean Research 59: 115–128.
   Web of Science ®Google Scholar
• Serani, Andrea, Cecilia Leotardi, Umberto Iemma, Emilio Fortunato Campana, Giovanni Fasano, and Matteo Diez. 2016b. “Parameter Selection in Synchronous and Asynchronous Deterministic Particle Swarm Optimization for Ship Hydrodynamics Problems.” Applied Soft Computing 49: 313–334.
   Web of Science ®Google Scholar
• Serani, Andrea, Riccardo Pellegrini, Riccardo Broglia, Jeroen Wackers, Michel Visonneau, and Matteo Diez. 2019. “An Adaptive N-Fidelity Metamodel for Design and Operational-Uncertainty Space Exploration of Complex Industrail Problems.” In Proceedings of the 8th International Conference on Computational Methods in Marine Engineering (Marine 2019), 177–188.
   Google Scholar
• Stern, F., J. Longo, R. Penna, A. Olivieri, T. Ratcliffe, and H. Coleman. 2001. “International Collaboration on Benchmark CFD Validation Data for Surface Combatant DTMB Model 5415”. In Twenty-Third Symposium on Naval Hydrodynamics. Washington, DC: Office of Naval Research, Bassin d'Essais des Carenes, National Research Council.
   Google Scholar
• Viana, Felipe, and Raphael Haftka. 2010. “Surrogate-Based Optimization with Parallel Simulations using the Probability of Improvement.” In 13th AIAA/ISSMO Multidisciplinary Analysis Optimization Conference.
   Google Scholar
• Viana, Felipe A. C., T. W. Simpson, V. Balabanov, and T. Vasilli. 2014. “Special Section on Multidisciplinary Design Optimization: Metamodeling in Multidisciplinary Design Optimization: How Far Have We Really Come?” AIAA Journal 52 (4): 670–690.
   Web of Science ®Google Scholar
• Volpi, Silvia, Matteo Diez, Nicholas J. Gaul, Hyeongjin Song, Umberto Iemma, K. K. Choi, Emilio F. Campana, and Frederick Stern. 2015. “Development and Validation of a Dynamic Metamodel Based on Stochastic Radial Basis Functions and Uncertainty Quantification.” Structural and Multidisciplinary Optimization 51 (2): 347–368.
   Web of Science ®Google Scholar
• Wackers, Jeroen, Ganbo Deng, Emmanuel Guilmineau, Alban Leroyer, Patrick Queutey, and Michel Visonneau. 2014. “Combined Refinement Criteria for Anisotropic Grid Refinement in Free-surface Flow Simulation.” Computers and Fluids 92: 209–222.
   Web of Science ®Google Scholar
• Wackers, Jeroen, Ganbo Deng, Emmanuel Guilmineau, Alban Leroyer, Patrick Queutey, Michel Visonneau, Alexandro Palmieri, and Alfredo Liverani. 2017. “Can Adaptive Grid Refinement Produce Grid-independent Solutions for Incompressible Flows?” Journal of Computational Physics 344: 364–380.
   Web of Science ®Google Scholar
• Wackers, Jeroen, Emmanuel Guilmineau, and Michel Visonneau. 2017. “Unsteady Behaviour in RANS Simulation of the JBC and KVLCC2.” In Proceedings of the 20th Numerical Towing Tank Symposium – NuTTS 2017, Wageningen, The Netherlands.
   Google Scholar
• Wackers, Jeroen, Andrea Serani, Riccardo Pellegrini, Matteo Diez, and Michel Visonneau. 2019. “Adaptive Multifidelity Shape Optimization Based on Noisy CFD Data.” In Proceedings of the International Conference on Adaptive Modeling and Simulation ADMOS 2019.
   Google Scholar
• Yi, Seulgi, Hyung I. Kwon, and Seongim Choi. 2014. Efficient Global Optimization using a Multi-point and Multi-objective Infill Sampling Criteria.
   Google Scholar
• Zhao, L., K. K. Choi, and I. Lee. 2011. “Metamodeling Method Using Dynamic Kriging for Design Optimization.” AIAA Journal 49 (9): 2034–2046.
   Web of Science ®Google Scholar
• Zheng, Jun, Xinyu Shao, Liang Gao, Ping Jiang, and Zilong Li. 2013. “A Hybrid Variable-fidelity Global Approximation Modelling Method Combining Tuned Radial Basis Function Base and Kriging Correction.” Journal of Engineering Design 24 (8): 604–622.
   Web of Science ®Google Scholar