| LES/PDF modeling of turbulent premixed flames with locally enhanced mixing by reaction H Wang, T Pant, P Zhang Flow, Turbulence and Combustion 100, 147-175, 2018 | 30 | 2018 |
| A unified view of pilot stabilized turbulent jet flames for model assessment across different combustion regimes H Wang, P Zhang Proceedings of the Combustion Institute 36 (2), 1693-1703, 2017 | 22 | 2017 |
| Large eddy simulation of flows after a bluff body: Coherent structures and mixing properties P Zhang, C Han, Y Chen Journal of Fluids and Structures 42, 1-12, 2013 | 18 | 2013 |
| Variance consistent mean shift particle model for treating differential molecular diffusion in transported PDF methods for turbulent reactive flows P Zhang, H Wang Computers & Fluids 170, 53-76, 2018 | 16 | 2018 |
| Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems ML Pasini, P Zhang, ST Reeve, JY Choi Machine Learning: Science and Technology 3 (2), 025007, 2022 | 15 | 2022 |
| Propagation and extinction behavior of methane/air premixed flames through straight and converging-diverging microchannels S Biswas, P Zhang, H Wang, L Qiao Applied Thermal Engineering 148, 1395-1406, 2019 | 15 | 2019 |
| Consistency and convergence of Eulerian Monte Carlo field method for solving transported probability density function equation in turbulence modeling H Wang, P Zhang, T Pant Physics of Fluids 30 (11), 2018 | 15 | 2018 |
| Studies of the flow and turbulence fields in a turbulent pulsed jet flame using LES/PDF P Zhang, AR Masri, H Wang Combustion Theory and Modelling 21 (5), 897-924, 2017 | 15 | 2017 |
| Large eddy simulation of CH4/air lifted flame HAN Chao, P ZHANG, YE Tao-hong Journal of propulsion technology 35 (5), 654-660, 2014 | 14 | 2014 |
| Numerical study of methane/air jet flame in vitiated co-flow using tabulated detailed chemistry C Han, P Zhang, TH Ye, YL Chen Science China Technological Sciences 57, 1750-1760, 2014 | 13 | 2014 |
| PI3NN: Out-of-distribution-aware prediction intervals from three neural networks S Liu, P Zhang, D Lu, G Zhang arXiv preprint arXiv:2108.02327, 2021 | 11 | 2021 |
| Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules JY Choi, P Zhang, K Mehta, A Blanchard, M Lupo Pasini Journal of Cheminformatics 14 (1), 70, 2022 | 9 | 2022 |
| An out-of-distribution-aware autoencoder model for reduced chemical kinetics P Zhang, S Liu, D Lu, R Sankaran, G Zhang Discrete and Continuous Dynamical Systems-Series S 15 (4), 2021 | 9 | 2021 |
| A prediction interval method for uncertainty quantification of regression models P Zhang, S Liu, D Lu, G Zhang, R Sankaran Oak Ridge National Lab.(ORNL), Oak Ridge, TN (United States), 2021 | 7 | 2021 |
| A priori analysis of a power-law mixing model for transported PDF model based on high Karlovitz turbulent premixed DNS flames P Zhang, T Xie, H Kolla, H Wang, ER Hawkes, JH Chen, H Wang Proceedings of the Combustion Institute 38 (2), 2917-2927, 2021 | 7 | 2021 |
| A direct numerical simulation study of the dilution tolerance of propane combustion under spark-ignition engine conditions W Ge, FDF Chuahy, P Zhang, R Sankaran, D Splitter, D DelVescovo, T Lu, ... Combustion and Flame 247, 112495, 2023 | 5 | 2023 |
| Autoencoder Neural Network for chemically reacting systems P Zhang, R Sankaran Journal of Machine Learning for Modeling and Computing 3 (4), 2022 | 5 | 2022 |
| Reduced models for chemical kinetics derived from parallel ensemble simulations of stirred reactors P Zhang, R Sankaran, M Stoyanov, D Lebrun-Grandie, CE Finney AIAA Scitech 2020 Forum, 0177, 2020 | 5 | 2020 |
| Examination of probability distribution of mixture fraction in LES/FDF modelling of a turbulent partially premixed jet flame H Wang, P Zhang, J Tao Combustion Theory and Modelling 26 (2), 320-337, 2022 | 4 | 2022 |
| Computational workflow for accelerated molecular design using quantum chemical simulations and deep learning models AE Blanchard, P Zhang, D Bhowmik, K Mehta, J Gounley, ST Reeve, ... Smoky Mountains Computational Sciences and Engineering Conference, 3-19, 2022 | 3 | 2022 |
