A physics-based approach to modeling real-fuel combustion chemistry–II. Reaction kinetic models of jet and rocket fuels R Xu, K Wang, S Banerjee, J Shao, T Parise, Y Zhu, S Wang, A Movaghar, ... Combustion and Flame 193, 520-537, 2018 | 345 | 2018 |
Towards a comprehensive optimization of engine efficiency and emissions by coupling artificial neural network (ANN) with genetic algorithm (GA) Y Li, M Jia, X Han, XS Bai Energy 225, 120331, 2021 | 108 | 2021 |
A Physics-based approach to modeling real-fuel combustion chemistry–III. Reaction kinetic model of JP10 Y Tao, R Xu, K Wang, J Shao, SE Johnson, A Movaghar, X Han, JW Park, ... Combustion and Flame 198, 466-476, 2018 | 97 | 2018 |
Temperature approximations in chemical kinetics studies using single pulse shock tubes X Han, JM Mehta, K Brezinsky Combustion and Flame 209, 1-12, 2019 | 34 | 2019 |
Visual inspection with federated learning X Han, H Yu, H Gu Image Analysis and Recognition: 16th International Conference, ICIAR 2019 …, 2019 | 34 | 2019 |
A high pressure shock tube study of pyrolysis of real jet fuel Jet A X Han, M Liszka, R Xu, K Brezinsky, H Wang Proceedings of the combustion institute 37 (1), 189-196, 2019 | 33 | 2019 |
Effect of fuel molecular structure and premixing on soot emissions from n-heptane and 1-heptene flames X Fu, X Han, K Brezinsky, S Aggarwal Energy & Fuels 27 (10), 6262-6272, 2013 | 31 | 2013 |
Effect of unsaturated bond on NO x and PAH formation in n-heptane and 1-heptene triple flames X Han, SK Aggarwal, K Brezinsky Energy & Fuels 27 (1), 537-548, 2013 | 29 | 2013 |
An improved approach towards more robust deep learning models for chemical kinetics X Han, M Jia, Y Chang, Y Li Combustion and Flame 238, 111934, 2022 | 16 | 2022 |
Directed message passing neural network (D-MPNN) with graph edge attention (GEA) for property prediction of biofuel-relevant species X Han, M Jia, Y Chang, Y Li, S Wu Energy and AI 10, 100201, 2022 | 12 | 2022 |
Prediction and sensitivity analysis of the cetane number of different biodiesel fuels using an artificial neural network S Hao, X Han, H Liu, M Jia Energy & Fuels 35 (21), 17711-17720, 2021 | 6 | 2021 |
A Shock Tube Study of the Pyrolysis of Real Jet Fuels Jet A and JP10 X Han University of Illinois at Chciago, 2018 | 4 | 2018 |
Comprehensive influence of uncertainty propagation of chemical kinetic parameters on laminar flame speed prediction: a case study of dimethyl ether Y Chang, P Wang, S Huang, X Han, M Jia Combustion Theory and Modelling 27 (3), 441-458, 2023 | 1 | 2023 |
A hybrid sectional moment projection method for modeling soot particle dynamics in laminar premixed flames Z Zhang, X Han, M Wang, Z Wu, X Sun, S Wu Fuel 331, 125731, 2023 | 1 | 2023 |
A Numerical Investigation on Counterflow Flames of Biodiesel/Diesel Surrogate Blends X Han, SK Aggarwal Turbo Expo: Power for Land, Sea, and Air 55119, V01BT04A054, 2013 | | 2013 |
Effect of Unsaturated Bonds on NOx and PAH Emissions of Triple Flames X Han University of Illinois at Chicago, 2013 | | 2013 |
A numerical investigation of NOx emission from n-heptane and 1-heptene triple flames SK Aggarwal, X Han, K Brezinsky | | 2012 |