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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.
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Constrained large-eddy simulation of laminar-turbulent transition in channel flow
Published in Physics of Fluids, 2014
Recommended citation: Y. Zhao, Z. Xia*, Y. Shi, Z. Xiao, S. Chen. (2014). "Constrained large-eddy simulation of laminar-turbulent transition in channel flow." Physics of Fluids, 26, 095103.
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Assessment of the shear-improved Smagorinsky model in laminar-turbulent transitional channel flow
Published in Journal of Turbulence, 2015
Recommended citation: Z. Xia*, Y. Shi, Y. Zhao. (2015). "Assessment of the shear-improved Smagorinsky model in laminar-turbulent transitional channel flow." Journal of Turbulence, 16(10), 925–936.
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Evolution of material surfaces in the temporal transition in channel flow
Published in Journal of Fluid Mechanics, 2016
Recommended citation: Y. Zhao, Y. Yang*, S. Chen. (2016). "Evolution of material surfaces in the temporal transition in channel flow." Journal of Fluid Mechanics, 793, 840–876.
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Vortex reconnection in the late transition in channel flow
Published in Journal of Fluid Mechanics, 2016
Recommended citation: Y. Zhao, Y. Yang*, S. Chen. (2016). "Vortex reconnection in the late transition in channel flow." Journal of Fluid Mechanics, 802, R4.
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Sinuous distortion of vortex surfaces in the lateral growth of turbulent spots
Published in Physical Review Fluids, 2018
Recommended citation: Y. Zhao, S. Xiong, Y. Yang*, S. Chen. (2018). "Sinuous distortion of vortex surfaces in the lateral growth of turbulent spots." Physical Review Fluids, 3, 074701.
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Large-eddy simulation and RANS analysis of the end-wall flow in a linear low-pressure turbine cascade, part II: loss generation
Published in Journal of Turbomachinery, 2019
Recommended citation: M. Marconcini*, R. Pacciani, A. Arnone, V. Michelassi, R. Pichler, Y. Zhao, R. D. Sandberg. (2019). "Large-eddy simulation and RANS analysis of the end-wall flow in a linear low-pressure turbine cascade, part II: loss generation." Journal of Turbomachinery, 141, 051004.
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Large-eddy simulation and RANS analysis of the end-wall flow in a linear low-pressure turbine cascade, part I: flow and secondary vorticity fields under varying inlet condition
Published in Journal of Turbomachinery, 2019
Recommended citation: R. Pichler, Y. Zhao, R. D. Sandberg*, V. Michelassi, R. Pacciani, M. Marconcini, A. Arnone. (2019). "Large-eddy simulation and RANS analysis of the end-wall flow in a linear low-pressure turbine cascade, part I: flow and secondary vorticity fields under varying inlet condition." Journal of Turbomachinery, 141, 121005.
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Using a new entropy loss analysis to assess the accuracy of RANS predictions of a high-pressure turbine vane
Published in Journal of Turbomachinery, 2020
Recommended citation: Y. Zhao*, R. D. Sandberg. (2020). "Using a new entropy loss analysis to assess the accuracy of RANS predictions of a high-pressure turbine vane." Journal of Turbomachinery, 142, 081008.
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RANS turbulence model development using CFD-driven machine learning
Published in Journal of Computational Physics, 2020
Recommended citation: Y. Zhao*, H. D. Akolekar, J. Weatheritt, V. Michelassi, R. D. Sandberg. (2020). "RANS turbulence model development using CFD-driven machine learning." Journal of Computational Physics, 411, 109413.
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Bypass transition in boundary layers subject to strong pressure gradient and curvature effects
Published in Journal of Fluid Mechanics, 2020
Recommended citation: Y. Zhao*, R. D. Sandberg. (2020). "Bypass transition in boundary layers subject to strong pressure gradient and curvature effects." Journal of Fluid Mechanics, 888, A4 (Featured on cover).
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Data-driven scalar-flux model development with application to jet in cross flow
Published in International Journal of Heat and Mass Transfer, 2020
Recommended citation: J. Weatheritt, Y. Zhao, R. D. Sandberg*, S. Mizukami, K. Tanimoto. (2020). "Data-driven scalar-flux model development with application to jet in cross flow." International Journal of Heat and Mass Transfer, 147, 118931.
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High-fidelity simulations of a high-pressure turbine vane subject to large disturbances: effect of exit Mach number on losses
Published in Journal of Turbomachinery, 2021
Recommended citation: Y. Zhao*, R. D. Sandberg. (2021). "High-fidelity simulations of a high-pressure turbine vane subject to large disturbances: effect of exit Mach number on losses." Journal of Turbomachinery, 143, 091002.
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Data-driven turbulence modelling based on gene-expression programming
Published in Chinese Journal of Theoretical and Applied Mechanics, 2021
Recommended citation: Y. Zhao*, X. Xu. (2021). "Data-driven turbulence modelling based on gene-expression programming." Chinese Journal of Theoretical and Applied Mechanics, 53(10), 1–16 (in Chinese).
Data-driven model development for large-eddy simulation of turbulence using gene-expression programming
Published in Physics of Fluids, 2021
Recommended citation: H. Li, Y. Zhao*, J. Wang, R. D. Sandberg. (2021). "Data-driven model development for large-eddy simulation of turbulence using gene-expression programming." Physics of Fluids, 33, 125127.
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Integration of machine learning and computational fluid dynamics to develop turbulence models for improved low-pressure turbine wake mixing prediction
Published in Journal of Turbomachinery, 2021
Recommended citation: H. D. Akolekar*, Y. Zhao, R. D. Sandberg, R. Pacciani. (2021). "Integration of machine learning and computational fluid dynamics to develop turbulence models for improved low-pressure turbine wake mixing prediction." Journal of Turbomachinery, 143, 121001.
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Multi-objective CFD-driven development of coupled turbulence closure models
Published in Journal of Computational Physics, 2022
Recommended citation: F. Waschkowski*, Y. Zhao, R. D. Sandberg, J. Klewicki. (2022). "Multi-objective CFD-driven development of coupled turbulence closure models." Journal of Computational Physics, 452, 110922.
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Large-eddy simulation of particle-laden isotropic turbulence using machine-learned subgrid-scale model
Published in Physics of Fluids, 2022
Recommended citation: Q. Wu, Y. Zhao*, Y. Shi, S. Chen. (2022). "Large-eddy simulation of particle-laden isotropic turbulence using machine-learned subgrid-scale model." Physics of Fluids, 34, 065129 (Editor's Pick).
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Machine-learning for turbulence and heat-flux model development: a review of challenges associated with distinct physical phenomena and progress to date
Published in International Journal of Heat and Fluid Flow, 2022
Recommended citation: R. D. Sandberg*, Y. Zhao. (2022). "Machine-learning for turbulence and heat-flux model development: a review of challenges associated with distinct physical phenomena and progress to date." International Journal of Heat and Fluid Flow, 95, 108983 (Review).
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A coupled framework for symbolic turbulence models from deep learning
Published in International Journal of Heat and Fluid Flow, 2023
Recommended citation: C. Lav*, A. J. Banko, F. Waschkowski, Y. Zhao, C. J. Elkins, J. K. Eaton, R. D. Sandberg. (2023). "A coupled framework for symbolic turbulence models from deep learning." International Journal of Heat and Fluid Flow, 101, 109140.
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High-fidelity simulation study of the unsteady flow effects on high-pressure turbine blade performance
Published in Journal of Turbomachinery, 2023
Recommended citation: J. Leggett, Y. Zhao*, R. D. Sandberg. (2023). "High-fidelity simulation study of the unsteady flow effects on high-pressure turbine blade performance." Journal of Turbomachinery, 145(1), 011002.
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Data-driven nonlinear K–L turbulent mixing model via gene expression programming method
Published in Acta Mechanica Sinica, 2023
Recommended citation: H. Xie, Y. Zhao*, Y. Zhang*. (2023). "Data-driven nonlinear K–L turbulent mixing model via gene expression programming method." Acta Mechanica Sinica, 39, 322315.
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Effect of micro-grooves on drag reduction in Taylor–Couette flow
Published in Physics of Fluids, 2023
Recommended citation: B. Xu, H. Li, X. Liu, Y. Xiang, P. Lv, X. Tan, Y. Zhao, C. Sun, H. Duan*. (2023). "Effect of micro-grooves on drag reduction in Taylor–Couette flow." Physics of Fluids, 35, 063608.
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Direct numerical simulation of a high-pressure turbine stage: unsteady boundary layer transition and the resulting flow structures
Published in Journal of Turbomachinery, 2023
Recommended citation: T. Wang, Y. Zhao*, J. Leggett, R. D. Sandberg. (2023). "Direct numerical simulation of a high-pressure turbine stage: unsteady boundary layer transition and the resulting flow structures." Journal of Turbomachinery, 145(12), 121009.
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Toward more general turbulence models via multicase computational-fluid-dynamics-driven training
Published in AIAA Journal, 2023
Recommended citation: Y. Fang*, Y. Zhao, F. Waschkowski, A. S. H. Ooi, R. D. Sandberg. (2023). "Toward more general turbulence models via multicase computational-fluid-dynamics-driven training." AIAA Journal, 65(5).
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A data-driven approach for generalizing the laminar kinetic energy model for separation and bypass transition in low- and high-pressure turbines
Published in Journal of Turbomachinery, 2024
Recommended citation: Y. Fang*, Y. Zhao, H. D. Akolekar, A. S. H. Ooi, R. D. Sandberg, R. Pacciani, M. Marconcini. (2024). "A data-driven approach for generalizing the laminar kinetic energy model for separation and bypass transition in low- and high-pressure turbines." Journal of Turbomachinery, 146(9), 091005.
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Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks
Published in Theoretical and Applied Mechanics Letters, 2024
Recommended citation: H. Zhou, H. Li, Y. Zhao*. (2024). "Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks." Theoretical and Applied Mechanics Letters, 14(2), 100511.
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Evolutionary neural networks for learning turbulence closure models with explicit expressions
Published in Physics of Fluids, 2024
Recommended citation: H. Li, Y. Zhao*, F. Waschkowski, R. D. Sandberg. (2024). "Evolutionary neural networks for learning turbulence closure models with explicit expressions." Physics of Fluids, 36, 055126.
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Gradient information and regularization for gene expression programming to develop data-driven physics closure models
Published in Flow, Turbulence and Combustion, 2024
Recommended citation: F. Waschkowski*, H. Li, A. Deshmukh, T. Grenga, Y. Zhao, H. Pitsch, J. Klewicki, R. D. Sandberg. (2024). "Gradient information and regularization for gene expression programming to develop data-driven physics closure models." Flow, Turbulence and Combustion.
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A transformer-based convolutional method to model inverse cascade in forced two-dimensional turbulence
Published in Journal of Computational Physics, 2025
Recommended citation: H. Li, J. Xie, C. Zhang, Y. Zhang, Y. Zhao*. (2025). "A transformer-based convolutional method to model inverse cascade in forced two-dimensional turbulence." Journal of Computational Physics, 520, 113475.
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An intermittency-based Reynolds-averaged transition model for mixing flows induced by interfacial instabilities
Published in Journal of Fluid Mechanics, 2025
Recommended citation: H. Xie, H. Qi, M. Xiao, Y. Zhang*, Y. Zhao*. (2025). "An intermittency-based Reynolds-averaged transition model for mixing flows induced by interfacial instabilities." Journal of Fluid Mechanics, 1002, A31.
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Quantum implicit representation of vortex filaments in turbulence
Published in Journal of Fluid Mechanics, 2025
Recommended citation: C. Zhu, Z. Wang, S. Xiong*, Y. Zhao, Y. Yang. (2025). "Quantum implicit representation of vortex filaments in turbulence." Journal of Fluid Mechanics, 1014, A31.
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A detached-eddy simulation methodology for interfacial mixing flows
Published in Physica D: Nonlinear Phenomena, 2025
Recommended citation: H. Xie, M. Xiao, Y. Zhao*, Y. Zhang*, J. Wang, Y. Shi. (2025). "A detached-eddy simulation methodology for interfacial mixing flows." Physica D: Nonlinear Phenomena, 482, 134892.
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Advances in quantum computing for fluid dynamics
Published in Advances in Mechanics, 2025
Recommended citation: Z. Meng, Z. Lu, S. Xiong, Y. Zhao, Y. Yang*. (2025). "Advances in quantum computing for fluid dynamics." Advances in Mechanics, 55(3), 541–566 (in Chinese).
A compressible Reynolds-averaged mixing model considering turbulent composition and heat fluxes
Published in Journal of Fluid Mechanics, 2025
Recommended citation: H. Xie, T. Luo, Y. Zhao*, Y. Zhang*, J. Wang. (2025). "A compressible Reynolds-averaged mixing model considering turbulent composition and heat fluxes." Journal of Fluid Mechanics, 1019, A56.
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Quantum lattice Boltzmann method for simulating nonlinear fluid dynamics
Published in npj Quantum Information, 2025
Recommended citation: B. Wang, Z. Meng, Y. Zhao, Y. Yang*. (2025). "Quantum lattice Boltzmann method for simulating nonlinear fluid dynamics." npj Quantum Information, 11, 196.
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A high-fidelity and efficient framework for point-particle direct numerical simulation based on multi-block overset grids
Published in Computer Physics Communications, 2026
Recommended citation: T. Wang, B. Meng, B. Tian, Y. Zhao*. (2026). "A high-fidelity and efficient framework for point-particle direct numerical simulation based on multi-block overset grids." Computer Physics Communications, 322, 110059.
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Machine-learning-enhanced four-equation model for predicting roughness-induced transition
Published in AIAA Journal, 2026
Recommended citation: Y. Ge, X. Zhu, Y. Fang, Y. Zhao*. (2026). "Machine-learning-enhanced four-equation model for predicting roughness-induced transition." AIAA Journal.
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Frequency response of the unsteady separating boundary layer in a compressor cascade
Published in Acta Mechanica Sinica, 2026
Recommended citation: T. Wang, B. Lyu, Y. Zhao*. (2026). "Frequency response of the unsteady separating boundary layer in a compressor cascade." Acta Mechanica Sinica, in press.
Constructing wall turbulence using hierarchical hairpin vortices
Published in Physical Review Fluids, 2026
Recommended citation: W. Shen, Y. Ge, Z. Han, Y. Zhao*, Y. Yang*. (2026). "Constructing wall turbulence using hierarchical hairpin vortices." Physical Review Fluids, 11, 044604.
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Boundary layer transition induced by surface roughness distributed over a low-pressure turbine blade
Published in Journal of Turbomachinery, 2026
Recommended citation: X. Zhu, Y. Ge, Y. Zhao*, Z. Xiao, R. D. Sandberg. (2026). "Boundary layer transition induced by surface roughness distributed over a low-pressure turbine blade." Journal of Turbomachinery, 148(8), 081014.
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Progressive mixture-of-experts with autoencoder routing for continual RANS turbulence modelling
Published in Journal of Fluid Mechanics, 2026
Recommended citation: H. Ji, Y. Luo, H. Zhou, Y. Zhao*. (2026). "Progressive mixture-of-experts with autoencoder routing for continual RANS turbulence modelling." Journal of Fluid Mechanics, 1036, A54.
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Asymmetric particle transport in turbulent flows within concentric annular ducts
Published in Journal of Fluid Mechanics, 2026
Recommended citation: T. Wang, C. Zhang, Y. Zhao*. (2026). "Asymmetric particle transport in turbulent flows within concentric annular ducts." Journal of Fluid Mechanics, 1037, A18.
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Accelerating CFD-driven training of transition and turbulence models for turbine flows by one-shot and real-time transformer integration
Published in Computers & Fluids, 2026
Recommended citation: Y. Fang*, M. Reissmann, R. Pacciani, Y. Zhao, A. S. H. Ooi, M. Marconcini, H. D. Akolekar, R. D. Sandberg. (2026). "Accelerating CFD-driven training of transition and turbulence models for turbine flows by one-shot and real-time transformer integration." Computers & Fluids, 306, 106927.
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Low-wavenumber wall pressure fluctuations in turbulent flows within concentric annular ducts
Published in Journal of Fluid Mechanics, 2026
Recommended citation: Y. Zhao, T. Wang, B. Lyu*. (2026). "Low-wavenumber wall pressure fluctuations in turbulent flows within concentric annular ducts." Journal of Fluid Mechanics, 1037, A56.
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Simulating fluid vortex interactions on a superconducting quantum processor
Published in Nature Communications, 2026
Recommended citation: Z. Wang, J. Zhong, K. Wang, Z. Zhu, Z. Bao, C. Zhu, W. Zhao, Y. Zhao, Y. Yang, C. Song*, S. Xiong*. (2026). "Simulating fluid vortex interactions on a superconducting quantum processor." Nature Communications, 17, 2602.
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