| Role of ozone doping in the explosion limits of hydrogen-oxygen mixtures: Multiplicity and catalyticity W Liang, Y Wang, CK Law Combustion and Flame 205, 7-10, 2019 | 33 | 2019 |
| An experimental and modeling study on auto-ignition of ammonia in an RCM with N2O and H2 addition W Liao, Z Chu, Y Wang, S Li, B Yang Proceedings of the Combustion Institute 39 (4), 4377-4385, 2023 | 27 | 2023 |
| Exploring the low-temperature oxidation chemistry with ozone addition in an RCM: A case study on ethanol W Liao, S Kang, Z Chu, Z Liu, Y Wang, B Yang Combustion and Flame 237, 111727, 2022 | 23 | 2022 |
| Chemical insights into the two-stage ignition behavior of NH3/H2 mixtures in an RCM W Liao, Y Wang, Z Chu, C Tao, B Yang Combustion and Flame 256, 112985, 2023 | 11 | 2023 |
| OptEx: an integrated framework for experimental design and combustion kinetic model optimization Z Zhou, K Lin, Y Wang, J Wang, CK Law, B Yang Combustion and Flame 245, 112298, 2022 | 11 | 2022 |
| Using active subspace-based similarity analysis for design of combustion experiments K Lin, Z Zhou, Y Wang, CK Law, B Yang Proceedings of the Combustion Institute 39 (4), 5177-5186, 2023 | 9 | 2023 |
| A kinetic investigation on low-temperature ignition of propane with ozone addition in an RCM W Liao, Z Chu, Y Wang, B Yang Proceedings of the Combustion Institute 39 (1), 395-403, 2023 | 9 | 2023 |
| Predicting octane number from species profiles: A deep learning model Y Wang, W Dong, W Liang, B Yang, CK Law Proceedings of the Combustion Institute 39 (4), 5269-5277, 2023 | 6 | 2023 |
| High-efficiency design of combustion kinetic experiments based on genetic algorithm Z Zhou, C Huang, K Lin, Y Wang, CK Law, B Yang Proceedings of the Combustion Institute 39 (4), 5219-5228, 2023 | 5 | 2023 |
| Investigating auto-ignition characteristics and kinetic modeling of NH3/CH4 mixtures using an RCM W Liao, Y Wang, Z Chu, B Yang Combustion and Flame 260, 113257, 2024 | 4 | 2024 |
| Clustering algorithm for experimental datasets using global sensitivity-based affinity propagation (GSAP) Y Wang, C Tao, Z Zhou, K Lin, CK Law, B Yang Combustion and Flame 259, 113121, 2024 | 3 | 2024 |
| Multi-fidelity neural network for uncertainty quantification of chemical reaction models C Liu, K Lin, Y Wang, B Yang Combustion and Flame 258, 113074, 2023 | 1 | 2023 |
| An experimental and modeling study on the ozone-assisted low-temperature ignition of methylcyclohexane in an RCM W Liao, Z Chu, Y Wang, B Yang Combustion and Flame 255, 112926, 2023 | 1 | 2023 |
| Efficient combustion kinetic parameter optimization via variational inference Y Wang, C Liu, C Tao, CK Law, B Yang Proceedings of the Combustion Institute 40 (1-4), 105550, 2024 | | 2024 |
| Artificial neural network-based Hamiltonian Monte Carlo for high-dimensional Bayesian Inference of reaction kinetics models C Liu, Y Wang, C Tao, CK Law, B Yang Proceedings of the Combustion Institute 40 (1-4), 105590, 2024 | | 2024 |
| Forward and reverse uncertainty analyses for RRKM/master equation based kinetic predictions: A case study of ethyl with oxygen Q Hou, Y Wang, X Yao, Y Zhu, X Wu, C Huang, Y Wu, B Yang, F Zhang International Journal of Chemical Kinetics, 2024 | | 2024 |
| Exemplar-based Clustering Algorithms for Experimental Datasets Based on Affinity Propagation and Global Sensitivity Analysis Y Wang, Z Zhou, K Lin, C Tao, C K Law, B Yang 14th Asia-Pacific Conference on Combustion, 2022 | | 2022 |
| Active subspace-based similarity analysis for different combustion measurements K Lin, Z Zhou, Y Wang, B Yang 13th Asia-Pacific Conference on Combustion 2021, 2021 | | 2021 |
Bin YangTsinghua University在 tsinghua.edu.cn 的电子邮件经过验证
