Publicou 6 edições por ano
ISSN Imprimir: 2152-5080
ISSN On-line: 2152-5099
Indexed in
RECURSIVE CO-KRIGING MODEL FOR DESIGN OF COMPUTER EXPERIMENTS WITH MULTIPLE LEVELS OF FIDELITY
RESUMO
We consider in this paper the problem of building a fast-running approximation−also called surrogate model−of a complex computer code. The co-kriging based surrogate model is a promising tool to build such an approximation when the complex computer code can be run at different levels of accuracy. We present here an original approach to perform a multi-fidelity co-kriging model which is based on a recursive formulation. We prove that the predictive mean and the variance of the presented approach are identical to the ones of the original co-kriging model. However, our new approach allows to obtain original results. First, closed-form formulas for the universal co-kriging predictive mean and variance are given. Second, a fast cross-validation procedure for the multi-fidelity co-kriging model is introduced. Finally, the proposed approach has a reduced computational complexity compared to the previous one. The multi-fidelity model is successfully applied to emulate a hydrodynamic simulator.
-
Chen Shishi, Jiang Zhen, Yang Shuxing, Apley Daniel W., Chen Wei, Nonhierarchical multi‐model fusion using spatial random processes, International Journal for Numerical Methods in Engineering, 106, 7, 2016. Crossref
-
Perdikaris P., Venturi D., Royset J. O., Karniadakis G. E., Multi-fidelity modelling via recursive co-kriging and Gaussian–Markov random fields, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 471, 2179, 2015. Crossref
-
Zaytsev Alexey, Reliable surrogate modeling of engineering data with more than two levels of fidelity, 2016 7th International Conference on Mechanical and Aerospace Engineering (ICMAE), 2016. Crossref
-
Pilania G., Gubernatis J.E., Lookman T., Multi-fidelity machine learning models for accurate bandgap predictions of solids, Computational Materials Science, 129, 2017. Crossref
-
Perdikaris Paris, Karniadakis George Em, Model inversion via multi-fidelity Bayesian optimization: a new paradigm for parameter estimation in haemodynamics, and beyond, Journal of The Royal Society Interface, 13, 118, 2016. Crossref
-
Bartoli Nathalie, Bouhlel Mohamed-Amine, Kurek Igor, Lafage Rémi, Lefebvre Thierry, Morlier Joseph, Priem Rémy, Stilz Vivien, Regis Rommel, Improvement of efficient global optimization with application to aircraft wing design, 17th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 2016. Crossref
-
Babaee H., Perdikaris P., Chryssostomidis C., Karniadakis G. E., Multi-fidelity modelling of mixed convection based on experimental correlations and numerical simulations, Journal of Fluid Mechanics, 809, 2016. Crossref
-
Habib Ahsanul, Singh Hemant Kumar, Ray Tapabrata, A multiple surrogate assisted evolutionary algorithm for optimization involving iterative solvers, Engineering Optimization, 50, 9, 2018. Crossref
-
Benamara Tariq, Breitkopf Piotr, Lepot Ingrid, Sainvitu Caroline, Villon Pierre, Multi-fidelity POD surrogate-assisted optimization: Concept and aero-design study, Structural and Multidisciplinary Optimization, 56, 6, 2017. Crossref
-
Perdikaris P., Raissi M., Damianou A., Lawrence N. D., Karniadakis G. E., Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 473, 2198, 2017. Crossref
-
Liu Haitao, Ong Yew-Soon, Cai Jianfei, Wang Yi, Cope with diverse data structures in multi-fidelity modeling: A Gaussian process method, Engineering Applications of Artificial Intelligence, 67, 2018. Crossref
-
Ezzat Ahmed Aziz, Pourhabib Arash, Ding Yu, Sequential Design for Functional Calibration of Computer Models, Technometrics, 60, 3, 2018. Crossref
-
Parussini L., Venturi D., Perdikaris P., Karniadakis G.E., Multi-fidelity Gaussian process regression for prediction of random fields, Journal of Computational Physics, 336, 2017. Crossref
-
Singh Prashant, Couckuyt Ivo, Elsayed Khairy, Deschrijver Dirk, Dhaene Tom, Multi-objective Geometry Optimization of a Gas Cyclone Using Triple-Fidelity Co-Kriging Surrogate Models, Journal of Optimization Theory and Applications, 175, 1, 2017. Crossref
-
Pan Wenxiao, Yang Xiu, Bao Jie, Wang Michelle, Optimizing Discharge Capacity of Li-O2Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization, Journal of The Electrochemical Society, 164, 11, 2017. Crossref
-
Xiao Manyu, Zhang Guohua, Breitkopf Piotr, Villon Pierre, Zhang Weihong, Extended Co-Kriging interpolation method based on multi-fidelity data, Applied Mathematics and Computation, 323, 2018. Crossref
-
Pang Guofei, Perdikaris Paris, Cai Wei, Karniadakis George Em, Discovering variable fractional orders of advection–dispersion equations from field data using multi-fidelity Bayesian optimization, Journal of Computational Physics, 348, 2017. Crossref
-
Liu Haitao, Ong Yew-Soon, Cai Jianfei, A survey of adaptive sampling for global metamodeling in support of simulation-based complex engineering design, Structural and Multidisciplinary Optimization, 57, 1, 2018. Crossref
-
Zhou Qi, Wang Yan, Choi Seung-Kyum, Jiang Ping, Shao Xinyu, Hu Jiexiang, Shu Leshi, A robust optimization approach based on multi-fidelity metamodel, Structural and Multidisciplinary Optimization, 57, 2, 2018. Crossref
-
Bonfiglio Luca, Perdikaris Paris, Brizzolara Stefano, Karniadakis George, A multi-fidelity framework for investigating the performance of super-cavitating hydrofoils under uncertain flow conditions, 19th AIAA Non-Deterministic Approaches Conference, 2017. Crossref
-
Gubernatis J. E., Lookman T., Machine learning in materials design and discovery: Examples from the present and suggestions for the future, Physical Review Materials, 2, 12, 2018. Crossref
-
Bonfiglio Luca, Perdikaris Paris, Águila Jose, Karniadakis George E., A probabilistic framework for multidisciplinary design: Application to the hydrostructural optimization of supercavitating hydrofoils, International Journal for Numerical Methods in Engineering, 116, 4, 2018. Crossref
-
Ghoreishi Seyede Fatemeh, Allaire Douglas L., Gaussian Process Regression for Bayesian Fusion of Multi-Fidelity Information Sources, 2018 Multidisciplinary Analysis and Optimization Conference, 2018. Crossref
-
Liu Haitao, Cai Jianfei, Ong Yew-Soon, Remarks on multi-output Gaussian process regression, Knowledge-Based Systems, 144, 2018. Crossref
-
Hampton Jerrad, Fairbanks Hillary R., Narayan Akil, Doostan Alireza, Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction, Journal of Computational Physics, 368, 2018. Crossref
-
Zhang Jiangjiang, Man Jun, Lin Guang, Wu Laosheng, Zeng Lingzao, Inverse Modeling of Hydrologic Systems with Adaptive Multifidelity Markov Chain Monte Carlo Simulations, Water Resources Research, 54, 7, 2018. Crossref
-
Lo Charles, Chow Paul, Multi-fidelity Optimization for High-Level Synthesis Directives, 2018 28th International Conference on Field Programmable Logic and Applications (FPL), 2018. Crossref
-
Abdallah Imad, Lataniotis Christos, Sudret Bruno, Parametric hierarchical kriging for multi-fidelity aero-servo-elastic simulators — Application to extreme loads on wind turbines, Probabilistic Engineering Mechanics, 55, 2019. Crossref
-
Zhang Dongkun, Yang Liu, Karniadakis George Em, Bi-directional coupling between a PDE-domain and an adjacent Data-domain equipped with multi-fidelity sensors, Journal of Computational Physics, 374, 2018. Crossref
-
Ranftl Sascha, Melito Gian Marco, Badeli Vahid, Reinbacher-Köstinger Alice, Ellermann Katrin, von der Linden Wolfgang, Bayesian Uncertainty Quantification with Multi-Fidelity Data and Gaussian Processes for Impedance Cardiography of Aortic Dissection, Entropy, 22, 1, 2019. Crossref
-
Jiang Ping, Zhou Qi, Shao Xinyu, Multi-fidelity Surrogate Models, in Surrogate Model-Based Engineering Design and Optimization, 2020. Crossref
-
Chocat Rudy, Beaucaire Paul, Debeugny Loïc, Lefebvre Jean-Pierre, Sainvitu Caroline, Breitkopf Piotr, Wyart Eric, Damage tolerance reliability analysis combining Kriging regression and support vector machine classification, Engineering Fracture Mechanics, 216, 2019. Crossref
-
Zheng Qiang, Zhang Jiangjiang, Xu Wenjie, Wu Laosheng, Zeng Lingzao, Adaptive Multifidelity Data Assimilation for Nonlinear Subsurface Flow Problems, Water Resources Research, 55, 1, 2019. Crossref
-
Marque-Pucheu Sophie, Perrin Guillaume, Garnier Josselin, Efficient sequential experimental design for surrogate modeling of nested codes, ESAIM: Probability and Statistics, 23, 2019. Crossref
-
Yang Xiu, Barajas-Solano David, Tartakovsky Guzel, Tartakovsky Alexandre M., Physics-informed CoKriging: A Gaussian-process-regression-based multifidelity method for data-model convergence, Journal of Computational Physics, 395, 2019. Crossref
-
Jakeman John D., Eldred Michael S., Geraci Gianluca, Gorodetsky Alex, Adaptive multi‐index collocation for uncertainty quantification and sensitivity analysis, International Journal for Numerical Methods in Engineering, 121, 6, 2020. Crossref
-
Absi Ghina N., Mahadevan Sankaran, Simulation Resource Optimization for Multi-Fidelity Model Calibration, AIAA Scitech 2019 Forum, 2019. Crossref
-
Gahrooei Mostafa Reisi, Paynabar Kamaran, Pacella Massimo, Colosimo Bianca Maria, An adaptive fused sampling approach of high-accuracy data in the presence of low-accuracy data, IISE Transactions, 51, 11, 2019. Crossref
-
Absi Ghina N., Mahadevan Sankaran, Simulation and Sensor Optimization for Multifidelity Dynamics Model Calibration, AIAA Journal, 58, 2, 2020. Crossref
-
Haugen Matz A., Stein Michael L., Sriver Ryan L., Moyer Elisabeth J., Future climate emulations using quantile regressions on large ensembles, Advances in Statistical Climatology, Meteorology and Oceanography, 5, 1, 2019. Crossref
-
Bonfiglio L., Perdikaris P., Brizzolara S., Karniadakis G.E., Multi-fidelity optimization of super-cavitating hydrofoils, Computer Methods in Applied Mechanics and Engineering, 332, 2018. Crossref
-
Nachar Stéphane, Boucard Pierre-Alain, Néron David, Bordeu Felipe, Coupling multi-fidelity kriging and model-order reduction for the construction of virtual charts, Computational Mechanics, 64, 6, 2019. Crossref
-
Cheng Kai, Lu Zhenzhou, Hierarchical surrogate model with dimensionality reduction technique for high‐dimensional uncertainty propagation, International Journal for Numerical Methods in Engineering, 121, 9, 2020. Crossref
-
Shu Leshi, Jiang Ping, Song Xueguan, Zhou Qi, Novel Approach for Selecting Low-Fidelity Scale Factor in Multifidelity Metamodeling, AIAA Journal, 57, 12, 2019. Crossref
-
Klyuchnikov Nikita, Burnaev Evgeny, Gaussian process classification for variable fidelity data, Neurocomputing, 397, 2020. Crossref
-
Biehler Jonas, Mäck Markus, Nitzler Jonas, Hanss Michael, Koutsourelakis Phaedon‐Stelios, Wall Wolfgang A., Multifidelity approaches for uncertainty quantification, GAMM-Mitteilungen, 42, 2, 2019. Crossref
-
Fernández-Godino M. Giselle, Dubreuil Sylvain, Bartoli Nathalie, Gogu Christian, Balachandar S., Haftka Raphael T., Linear regression-based multifidelity surrogate for disturbance amplification in multiphase explosion, Structural and Multidisciplinary Optimization, 60, 6, 2019. Crossref
-
Sarkar Soumalya, Mondal Sudeepta, Joly Michael, Lynch Matthew E., Bopardikar Shaunak D., Acharya Ranadip, Perdikaris Paris, Multifidelity and Multiscale Bayesian Framework for High-Dimensional Engineering Design and Calibration, Journal of Mechanical Design, 141, 12, 2019. Crossref
-
Talapatra Anjana, Boluki Shahin, Honarmandi Pejman, Solomou Alexandros, Zhao Guang, Ghoreishi Seyede Fatemeh, Molkeri Abhilash, Allaire Douglas, Srivastava Ankit, Qian Xiaoning, Dougherty Edward R., Lagoudas Dimitris C., Arróyave Raymundo, Experiment Design Frameworks for Accelerated Discovery of Targeted Materials Across Scales, Frontiers in Materials, 6, 2019. Crossref
-
Lee Seungjoon, Dietrich Felix, Karniadakis George E., Kevrekidis Ioannis G., Linking Gaussian process regression with data-driven manifold embeddings for nonlinear data fusion, Interface Focus, 9, 3, 2019. Crossref
-
Tran Anh, Wildey Tim, McCann Scott, sMF-BO-2CoGP: A Sequential Multi-Fidelity Constrained Bayesian Optimization Framework for Design Applications, Journal of Computing and Information Science in Engineering, 20, 3, 2020. Crossref
-
Cheng Kai, Lu Zhenzhou, Ling Chunyan, Zhou Suting, Surrogate-assisted global sensitivity analysis: an overview, Structural and Multidisciplinary Optimization, 61, 3, 2020. Crossref
-
Zheng Hongyu, Xie Fangfang, Ji Tingwei, Zhu Zaoxu, Zheng Yao, Multifidelity kinematic parameter optimization of a flapping airfoil, Physical Review E, 101, 1, 2020. Crossref
-
Pilania Ghanshyam, Balachandran Prasanna V., Gubernatis James E., Lookman Turab, Data-Based Methods for Materials Design and Discovery, 2020. Crossref
-
Wang Yan, McDowell David L., Uncertainty quantification in materials modeling, in Uncertainty Quantification in Multiscale Materials Modeling, 2020. Crossref
-
Babaee H., Bastidas C., DeFilippo M., Chryssostomidis C., Karniadakis G. E., A Multifidelity Framework and Uncertainty Quantification for Sea Surface Temperature in the Massachusetts and Cape Cod Bays, Earth and Space Science, 7, 2, 2020. Crossref
-
Zhou Qi, Wu Yuda, Guo Zhendong, Hu Jiexiang, Jin Peng, A generalized hierarchical co-Kriging model for multi-fidelity data fusion, Structural and Multidisciplinary Optimization, 62, 4, 2020. Crossref
-
Brevault Loïc, Balesdent Mathieu, Hebbal Ali, Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities, application to aerospace systems, Aerospace Science and Technology, 107, 2020. Crossref
-
Xu Yueqi, Song Xueguan, Zhang Chao, Hierarchical regression framework for multi-fidelity modeling, Knowledge-Based Systems, 212, 2021. Crossref
-
Chakraborty Souvik, Transfer learning based multi-fidelity physics informed deep neural network, Journal of Computational Physics, 426, 2021. Crossref
-
Ma Pulong, Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes, SIAM/ASA Journal on Uncertainty Quantification, 8, 4, 2020. Crossref
-
Lafzi Ali, Dabiri Sadegh, Dynamics of droplet migration in oscillatory and pulsating microchannel flows and prediction and uncertainty quantification of its lateral equilibrium position using multifidelity Gaussian processes, Physics of Fluids, 33, 6, 2021. Crossref
-
Hebbal Ali, Brevault Loïc, Balesdent Mathieu, Talbi El-Ghazali, Melab Nouredine, Multi-fidelity modeling with different input domain definitions using deep Gaussian processes, Structural and Multidisciplinary Optimization, 63, 5, 2021. Crossref
-
Egorova Olga, Hafizi Roohollah, Woods David C., Day Graeme M., Multifidelity Statistical Machine Learning for Molecular Crystal Structure Prediction, The Journal of Physical Chemistry A, 124, 39, 2020. Crossref
-
Muyskens Amanda, Schmidt Kathleen, Nelms Matthew, Barton Nathan, Florando Jeffrey, Kupresanin Ana, Rivera David, A practical extension of the recursive multi‐fidelity model for the emulation of hole closure experiments, Statistical Analysis and Data Mining: The ASA Data Science Journal, 14, 6, 2021. Crossref
-
Ellison M., DiazDelaO F.A., Ince N.Z., Willetts M., Robust optimisation of computationally expensive models using adaptive multi-fidelity emulation, Applied Mathematical Modelling, 100, 2021. Crossref
-
Qian Jiachang, Cheng Yuansheng, Zhang Anfu, Zhou Qi, Zhang Jinlan, Optimization design of metamaterial vibration isolator with honeycomb structure based on multi-fidelity surrogate model, Structural and Multidisciplinary Optimization, 64, 1, 2021. Crossref
-
Yoshida Tomohiro, Maezono Ryo, Hongo Kenta, Exploring Heat-Shielding Nanoparticle-Based Materials via First-Principles Calculations and Transfer Learning, ACS Applied Nano Materials, 4, 2, 2021. Crossref
-
Lu Chi-Ken, Shafto Patrick, Conditional Deep Gaussian Processes: Multi-Fidelity Kernel Learning, Entropy, 23, 11, 2021. Crossref
-
Ruan Xiongfeng, Jiang Ping, Zhou Qi, Hu Jiexiang, Shu Leshi, Variable-fidelity probability of improvement method for efficient global optimization of expensive black-box problems, Structural and Multidisciplinary Optimization, 62, 6, 2020. Crossref
-
Gorodetsky A. A., Jakeman J. D., Geraci G., MFNets: data efficient all-at-once learning of multifidelity surrogates as directed networks of information sources, Computational Mechanics, 68, 4, 2021. Crossref
-
Geraci Gianluca, Eldred Michael S., Gorodetsky Alex, Jakeman John, Recent advancements in Multilevel-Multifidelity techniques for forward UQ in the DARPA Sequoia project, AIAA Scitech 2019 Forum, 2019. Crossref
-
Stanek Lucas J., Bopardikar Shaunak D., Murillo Michael S., Multifidelity regression of sparse plasma transport data available in disparate physical regimes, Physical Review E, 104, 6, 2021. Crossref
-
Bhattacharjee Himaghna, Vlachos Dionisios G., Thermochemical Data Fusion Using Graph Representation Learning, Journal of Chemical Information and Modeling, 60, 10, 2020. Crossref
-
Konomi Bledar A., Karagiannis Georgios, Bayesian Analysis of Multifidelity Computer Models With Local Features and Nonnested Experimental Designs: Application to the WRF Model, Technometrics, 63, 4, 2021. Crossref
-
Zhou K., Tang J., Efficient characterization of dynamic response variation using multi-fidelity data fusion through composite neural network, Engineering Structures, 232, 2021. Crossref
-
Ryou Gilhyun, Tal Ezra, Karaman Sertac, Multi-fidelity black-box optimization for time-optimal quadrotor maneuvers, The International Journal of Robotics Research, 40, 12-14, 2021. Crossref
-
Huang Bing, von Lilienfeld O. Anatole, Ab Initio Machine Learning in Chemical Compound Space, Chemical Reviews, 121, 16, 2021. Crossref
-
Guo Zhendong, Wang Qineng, Song Liming, Li Jun, Parallel multi-fidelity expected improvement method for efficient global optimization, Structural and Multidisciplinary Optimization, 64, 3, 2021. Crossref
-
Lopez-Caballero Fernando, Probabilistic seismic analysis for liquefiable embankment through multi-fidelity codes approach, Soil Dynamics and Earthquake Engineering, 149, 2021. Crossref
-
Jin Yaochu, Wang Handing, Sun Chaoli, Knowledge Transfer in Data-Driven Evolutionary Optimization, in Data-Driven Evolutionary Optimization, 975, 2021. Crossref
-
Guo Shuai, Silva Camilo F., Polifke Wolfgang, Robust identification of flame frequency response via multi-fidelity Gaussian process approach, Journal of Sound and Vibration, 502, 2021. Crossref
-
Romor Francesco, Tezzele Marco, Rozza Gianluigi, Multi‐fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces, PAMM, 20, S1, 2021. Crossref
-
Batra Rohit, Pilania Ghanshyam, Uberuaga Blas P., Ramprasad Rampi, Multifidelity Information Fusion with Machine Learning: A Case Study of Dopant Formation Energies in Hafnia, ACS Applied Materials & Interfaces, 11, 28, 2019. Crossref
-
Jin Seung-Seop, Kim Sung Tae, Park Young-Hwan, Combining point and distributed strain sensor for complementary data-fusion: A multi-fidelity approach, Mechanical Systems and Signal Processing, 157, 2021. Crossref
-
Lin Quan, Hu Dawei, Hu Jiexiang, Cheng Yuansheng, Zhou Qi, A screening-based gradient-enhanced Gaussian process regression model for multi-fidelity data fusion, Advanced Engineering Informatics, 50, 2021. Crossref
-
Wiens Avery E., Copan Andreas V., Schaefer Henry F., Multi-fidelity Gaussian process modeling for chemical energy surfaces, Chemical Physics Letters, 737, 2019. Crossref
-
Zhang Sheng, Yang Xiu, Tindel Samy, Lin Guang, Augmented Gaussian random field: Theory and computation, Discrete & Continuous Dynamical Systems - S, 15, 4, 2022. Crossref
-
Valladares Homero, Li Tianyi, Zhu Likun, El-Mounayri Hazim, Hashem Ahmed M., Abdel-Ghany Ashraf E., Tovar Andres, Gaussian process-based prognostics of lithium-ion batteries and design optimization of cathode active materials, Journal of Power Sources, 528, 2022. Crossref
-
Jia Bin, Xin Ming, Incremental Uncertainty Propagation with Multi-Fidelity Gaussian Process, AIAA SCITECH 2022 Forum, 2022. Crossref
-
Pilania Ghanshyam, Balachandran Prasanna V., Gubernatis James E., Lookman Turab, Multi-Fidelity Learning, in Data-Based Methods for Materials Design and Discovery, 2020. Crossref
-
Khatouri Hanane, Benamara Tariq, Breitkopf Piotr, Demange Jean, Metamodeling techniques for CPU-intensive simulation-based design optimization: a survey, Advanced Modeling and Simulation in Engineering Sciences, 9, 1, 2022. Crossref
-
Kaps Arne, Czech Catharina, Duddeck Fabian, A hierarchical kriging approach for multi-fidelity optimization of automotive crashworthiness problems, Structural and Multidisciplinary Optimization, 65, 4, 2022. Crossref
-
Liu Xinwang, Zhao Weiwen, Wan Decheng, Multi-fidelity Co-Kriging surrogate model for ship hull form optimization, Ocean Engineering, 243, 2022. Crossref
-
Stroh Rémi, Bect Julien, Demeyer Séverine, Fischer Nicolas, Marquis Damien, Vazquez Emmanuel, Sequential Design of Multi-Fidelity Computer Experiments: Maximizing the Rate of Stepwise Uncertainty Reduction, Technometrics, 64, 2, 2022. Crossref
-
Seidl D. Thomas, Valiveti Dakshina M., Peridynamics and surrogate modeling of pressure-driven well stimulation, International Journal of Rock Mechanics and Mining Sciences, 154, 2022. Crossref
-
Palar Pramudita S., Parussini Lucia, Bregant Luigi, Shimoyama Koji, Izzaturrahman Muhammad F., Baehaqi Febrian A., Zuhal Lavi, Composite Kernel Functions for Surrogate Modeling using Recursive Multi-Fidelity Kriging, AIAA SCITECH 2022 Forum, 2022. Crossref
-
Ye Wenxing, Tan Matthias Hwai Yong, Multi‐fidelity Gaussian process modeling with boundary information, Applied Stochastic Models in Business and Industry, 38, 2, 2022. Crossref
-
Menon Nandana, Mondal Sudeepta, Basak Amrita, Multi-Fidelity Surrogate-Based Process Mapping with Uncertainty Quantification in Laser Directed Energy Deposition, Materials, 15, 8, 2022. Crossref
-
Petsagkourakis Panagiotis, Chachuat Benoit, Antonio del Rio-Chanona Ehecatl, Safe Real-Time Optimization using Multi-Fidelity Gaussian Processes, 2021 60th IEEE Conference on Decision and Control (CDC), 2021. Crossref
-
Zhang Lili, Wu Yuda, Jiang Ping, Choi Seung-Kyum, Zhou Qi, A multi-fidelity surrogate modeling approach for incorporating multiple non-hierarchical low-fidelity data, Advanced Engineering Informatics, 51, 2022. Crossref
-
Thenon A., Gervais V., Le Ravalec M., Sequential design strategy for kriging and cokriging-based machine learning in the context of reservoir history-matching, Computational Geosciences, 26, 5, 2022. Crossref
-
Newberry Felix, Hampton Jerrad, Jansen Kenneth, Doostan Alireza, Bi-fidelity reduced polynomial chaos expansion for uncertainty quantification, Computational Mechanics, 69, 2, 2022. Crossref
-
Korondi Péter Zénó, Marchi Mariapia, Parussini Lucia, Quagliarella Domenico, Poloni Carlo, Multi-Objective Design Optimisation of an Airfoil with Geometrical Uncertainties Leveraging Multi-Fidelity Gaussian Process Regression, in Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications, 8, 2021. Crossref
-
Prakash Supraj, Raman Venkatramanan, Multi-fidelity Modeling-based Estimation of Rotating Detonation Engine Performance, AIAA SCITECH 2022 Forum, 2022. Crossref
-
Morales Elisa, Korondi Péter Zénó, Quagliarella Domenico, Tognaccini Renato, Marchi Mariapia, Parussini Lucia, Poloni Carlo, Multi-fidelity Surrogate Assisted Design Optimisation of an Airfoil under Uncertainty Using Far-Field Drag Approximation, in Advances in Uncertainty Quantification and Optimization Under Uncertainty with Aerospace Applications, 8, 2021. Crossref
-
Grassi Francesco, Manganini Giorgio, Garraffa Michele, Mainini Laura, Resource Aware Multifidelity Active Learning for Efficient Optimization, AIAA Scitech 2021 Forum, 2021. Crossref
-
Howard Amanda A., Yu Tong, Wang Wei, Tartakovsky Alexandre M., Physics-informed CoKriging model of a redox flow battery, Journal of Power Sources, 542, 2022. Crossref
-
Striegel Christoph, Biehler Jonas, Wall Wolfgang A., Kauermann Göran, A Multifidelity Function-on-Function Model Applied to an Abdominal Aortic Aneurysm, Technometrics, 64, 3, 2022. Crossref
-
Kishi Yuki, Kanazaki Masahiro, Makino Yoshikazu, Supersonic Forward-Swept Wing Design Using Multifidelity Efficient Global Optimization, Journal of Aircraft, 59, 4, 2022. Crossref
-
Sharma Somya, Thompson Marten, Laefer Debra, Lawler Michael, McIlhany Kevin, Pauluis Olivier, Trinkle Dallas R., Chatterjee Snigdhansu, Machine Learning Methods for Multiscale Physics and Urban Engineering Problems, Entropy, 24, 8, 2022. Crossref
-
Li Zengcong, Zhang Shu, Li Hongqing, Tian Kuo, Cheng Zhizhong, Chen Yan, Wang Bo, On-line transfer learning for multi-fidelity data fusion with ensemble of deep neural networks, Advanced Engineering Informatics, 53, 2022. Crossref
-
Han Tianhong, Ahmed Kaleem S., Gosain Arun K., Tepole Adrian Buganza, Lee Taeksang, Multi-Fidelity Gaussian Process Surrogate Modeling of Pediatric Tissue Expansion, Journal of Biomechanical Engineering, 144, 12, 2022. Crossref
-
Pidaparthi Bharath, Missoum Samy, A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Classification Inconsistency, Journal of Computing and Information Science in Engineering, 23, 1, 2023. Crossref
-
Tsilifis Panagiotis, Pandita Piyush, Ghosh Sayan, Wang Liping, Multifidelity Model Calibration in Structural Dynamics Using Stochastic Variational Inference on Manifolds, Entropy, 24, 9, 2022. Crossref
-
Shi Maolin, Liang Zhenwei, Zhang Jian, Xu Lizhang, Song Xueguan, A robust prediction method based on Kriging method and fuzzy c-means algorithm with application to a combine harvester, Structural and Multidisciplinary Optimization, 65, 9, 2022. Crossref
-
Wan Hua‐Ping, Zhang Zi‐Nan, Luo Yaozhi, Ren Wei‐Xin, Todd Michael D., Analytical uncertainty quantification approach based on adaptive generalized co‐Gaussian process model , International Journal for Numerical Methods in Engineering, 2022. Crossref
-
Freitas Rodolfo S.M., Lima Ágatha P.F., Chen Cheng, Rochinha Fernando A., Mira Daniel, Jiang Xi, Towards predicting liquid fuel physicochemical properties using molecular dynamics guided machine learning models, Fuel, 329, 2022. Crossref
-
Saunders Robert, Rawlings Anna, Birnbaum Andrew, Iliopoulos Athanasios, Michopoulos John, Lagoudas Dimitris, Elwany Alaa, Additive Manufacturing Melt Pool Prediction and Classification via Multifidelity Gaussian Process Surrogates, Integrating Materials and Manufacturing Innovation, 2022. Crossref