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Your search keyword '"Jiao, Jianying"' showing total 23 results
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23 results on '"Jiao, Jianying"'

13. A gas regulator fault detecting method based on acoustic emission technology

Author

Yao Liu, Ming-xin Song, Fei Jiang, Fei-da Cai, Ya-peng Wei, Jiao Jianying, Song-ling Tan, and Honglang Li

Subjects
Millisecond, Acoustic emission, Control theory, Computer science, Feature extraction, Regulator, ComputerApplications_COMPUTERSINOTHERSYSTEMS, Pressure regulator, Fault (power engineering), Signal, Wavelet packet decomposition
Abstract

In this paper, a new method of gas pressure regulator fault diagnosis is proposed. The wavelet packet decomposition is used for feature extraction of the acoustic emission signal. Then, based on the model obtained in the BP neural network, early regulator fault can be detected. The experimental results prove the feasibility of this method. It can effectively improve the accuracy of the fault diagnosis of the regulator. In addition, the millisecond diagnostic cycle also makes this method have a high engineering value.

Published
2017
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15. Large eddy simulation using a dynamic mixing length subgrid-scale model

Author

Zhang Yunwei, Jiao Jianying, Gu Zhaolin, and Su Junwei

Subjects
Turbulence, K-epsilon turbulence model, Applied Mathematics, Mechanical Engineering, Computational Mechanics, Reynolds number, Mechanics, Dissipation, Computer Science Applications, Open-channel flow, Physics::Fluid Dynamics, symbols.namesake, Mechanics of Materials, symbols, Cutoff, Statistical physics, Scale model, Mathematics, Large eddy simulation
Abstract

SUMMARY A novel dynamic mixing length (DML) subgrid-scale model for large eddy simulations is proposed in this work to improve the cutoff length of the Smagorinsky model. The characteristic mixing length (or the characteristic wave number) is dynamically estimated for the subgrid-scale fluctuation of turbulence by the cutoff wave-number, kc, and the dissipation wave-number, kd. The dissipation wave number is derived from the kinetic energy spectrum equation and the dissipation spectrum equation. To prove the promise of the DML model, this model is used to simulate the lid-driven cubical cavity with max-velocity-based Reynolds numbers 8850 and 12,000, the channel flows with friction-velocity-based Reynolds numbers 180, 395, 590, and 950, and the turbulent flow past a square cylinder at the higher Reynolds number 21,400, respectively, compared with the Smagorinsky model and Germano et al.'s dynamic Smagorinsky model. Different numerical experiments with different Reynolds numbers show that the DML model can be used in simulations of flows with a wide range of Reynolds numbers without the occurrence of singular values. The DML model can alleviate the dissipation of the Smagorinsky model without the loss of its robustness. The DML model shows some advantages over Germano et al.'s dynamic Smagorinsky model in its high stability and simplicity of calculation because the coefficient of the DML model always stays positive. The characteristic mixing length in the DML model reflects the subgrid-scale fluctuation of turbulence in nature and thus the characteristic mixing length has a spatial and temporal distribution in turbulent flow. Copyright © 2011 John Wiley & Sons, Ltd.

Published
2011
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23. Tensor Hydraulic Conductivity Estimation for Heterogeneous Aquifers under Unknown Boundary Conditions.

Author

Jiao, Jianying and Zhang, Ye

Subjects
*HYDRAULIC conductivity, *AQUIFER pollution, *BOUNDARY value problems, *STEADY-state flow, *NONLINEAR equations
Abstract

A physically based inverse method is developed using hybrid formulation and coordinate transform to simultaneously estimate hydraulic conductivity tensors, steady-state flow field, and boundary conditions for a confined aquifer under ambient flow or pumping condition. Unlike existing indirect inversion techniques, the physically based method does not require forward simulations to assess model-data misfits. It imposes continuity of hydraulic head and Darcy fluxes in the model domain while incorporating observations (hydraulic heads, Darcy fluxes, or well rates) at measurement locations. Given sufficient measurements, it yields a well-posed inverse system of equations that can be solved efficiently with coarse grids and nonlinear optimization. When pumping and injection are active, well rates are used as measurements and flux sampling is not needed. The method is successfully tested on synthetic aquifer problems with regular and irregular geometries, different hydrofacies and flow patterns, and increasing conductivity anisotropy ratios. All problems yield stable inverse solutions under increasing head measurement errors. For a given set of observations, inversion accuracy is strongly affected by the conductivity anisotropy ratio. Conductivity estimation is also affected by flow pattern: within a hydrofacies, when Darcy flux component is very small, the corresponding directional conductivity perpendicular to streamlines becomes less identifiable. Finally, inversion is successful even if the location of aquifer boundaries is unknown. In this case, the inversion domain is defined by the location of the measurements. [ABSTRACT FROM AUTHOR]

Published
2015
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