Yaning Liu
Title
Cited by
Cited by
Year
Accurate and efficient prediction of fine‐resolution hydrologic and carbon dynamic simulations from coarse‐resolution models
GSH Pau, C Shen, WJ Riley, Y Liu
Water Resources Research 52 (2), 791-812, 2016
182016
Parametric uncertainty quantification in the Rothermel model with randomised quasi-Monte Carlo methods
Y Liu, E Jimenez, MY Hussaini, G Ökten, S Goodrick
International Journal of Wildland Fire 24 (3), 307-316, 2015
172015
Thermodynamic analysis of a novel supercritical compressed carbon dioxide energy storage system through advanced exergy analysis
Q He, H Liu, Y Hao, Y Liu, W Liu
Renewable energy 127, 835-849, 2018
162018
Optimization of a Monte Carlo variance reduction method based on sensitivity derivatives
Y Liu, MY Hussaini, G Ökten
Applied Numerical Mathematics 72, 160-171, 2013
132013
Evaluation of multiple reduced-order models to enhance confidence in global sensitivity analyses
Y Zhang, Y Liu, G Pau, S Oladyshkin, S Finsterle
International Journal of Greenhouse Gas Control 49, 217-226, 2016
122016
Accurate construction of high dimensional model representation with applications to uncertainty quantification
Y Liu, MY Hussaini, G Ökten
Reliability Engineering & System Safety 152, 281-295, 2016
112016
Global sensitivity analysis used to interpret biological experimental results
AM Jarrett, Y Liu, NG Cogan, MY Hussaini
Journal of Mathematical Biology 71 (1), 151-170, 2015
112015
Global sensitivity analysis for the Rothermel model based on high dimensional model representation
Y Liu, MY Hussaini, G Okten
4th Fire Behavior and Fuels Conference, 51-61, 2014
112014
Global sensitivity analysis for the Rothermel model based on high dimensional model representation
Y Liu, H MY, G Okten
Canadian Journal of Forest Research, 2014
112014
Non-Intrusive Methods for Probablistic Uncertainty Quantification and Global Sensitivity Analysis in Nonlinea Stochastic Phenomena
Y Liu
102013
The parabolic variational inequalities for variably saturated water flow in heterogeneous fracture networks
Z Ye, Q Jiang, C Yao, Y Liu, A Cheng, S Huang, Y Liu
Geofluids 2018, 2018
92018
Implicit sampling combined with reduced order modeling for the inversion of vadose zone hydrological data
Y Liu, GSH Pau, S Finsterle
Computers & Geosciences 108, 21-32, 2017
82017
A hybrid reduced-order model of fine-resolution hydrologic simulations at a polygonal tundra site
Y Liu, G Bisht, ZM Subin, WJ Riley, GSH Pau
Vadose Zone Journal 15 (2), 2016
72016
Evaluation of van Genuchten-Mualem model on the relative permeability for unsaturated flow in aperture-based fractures
J Sheng, T Huang, Z Ye, B Hu, Y Liu, Q Fan
Journal of Hydrology 576, 315-324, 2019
52019
Variance reduction method based on sensitivity derivatives, Part 2
E Jimenez, Y Liu, MY Hussaini
Applied Numerical Mathematics 74, 151-159, 2013
42013
Effects of cementitious grout components on rheological properties
J Liu, Y Li, G Zhang, Y Liu
Construction and Building Materials 227, 2019
32019
Uncertainty and robustness in weather derivative models
A Göncü, Y Liu, G Ökten, MY Hussaini
Monte Carlo and Quasi-Monte Carlo Methods, 351-365, 2016
32016
Numerical study on the hydrodynamic and thermodynamic properties of compressed carbon dioxide energy storage in aquifers
Y Li, H Yu, Y Liu, G Zhang, D Tang, Z Jiang
Renewable Energy 151, 1318-1338, 2020
22020
Compressed air energy storage in aquifers: basic principles, considerable factors, and improvement approaches
Y Li, Y Li, Y Liu, C Xiaoyuan
Reviews in Chemical Engineering, 2019
12019
Bayesian parameter inversion with implicit sampling for a vadose zone hydrological model
Y Liu, GSH Pau, S Finsterle
TOUGH Symposium 2015, 545-553, 2015
12015
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Articles 1–20