Browsing by Author "Liu, Yu"
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- The development of a systematic experimental method for damage identificationLiu, Yu (Virginia Tech, 1993-12-05)The diagnostics of slight damage are extremely significant for providing the early warning damage information for in-service structures. This thesis presents the development of a systematic experimental method to identify structural damage by the experimental techniques. Three carbon fabric squared composite p1ates were used as the research objects. Two of them with light crack damage that can be classified as fiber breaking and matrix cracking were supposed to be identified through the dynamic experimental techniques. The tests of the frequency response functions (FRFs) of the investigated objects were conducted first to provide a general understanding of the dynamic properties of the material and the structures. Then the tests of the velocity fields at some specified frequencies are performed to acquire dynamic response data of the objects for the study purposes. A systematic method to process the experimental data has been developed first in this thesis. The best regressive mathematical models for the test velocity fields are built based on the linear polynomial regression procedures and statistical analysis. To perform damage identification, the correlation coefficient (CC) and spatial correlation coefficient (SCC) techniques based on the best-fitted models and the curvature models were used. Finally, the student t' statistical tests were applied to decide whether the two compared data sets are significantly different in statistical sense.
- Dynamic State Estimation for Power System Control and Protection IEEE Task Force on Power System Dynamic State and Parameter EstimationLiu, Yu; Singh, Abhinav Kumar; Zhao, Junbo; Meliopoulos, AP Sakis P. S.; Pal, Bikash; Ariff, Mohd Aifaa bin Mohd B. M.; Van Cutsem, Thierry; Glavic, Mevludin; Huang, Zhenyu; Kamwa, Innocent; Mili, Lamine M.; Mir, Abdul Saleem; Taha, Ahmad; Terzija, Vladimir; Yu, Shenglong (IEEE, 2021-05-12)Dynamic state estimation (DSE) accurately tracks the dynamics of a power system and provides the evolution of the system state in real-time. This paper focuses on the control and protection applications of DSE, comprehensively presenting different facets of control and protection challenges arising in modern power systems. It is demonstrated how these challenges are effectively addressed with DSE-enabled solutions. As precursors to these solutions, reformulation of DSE considering both synchrophasor and sampled value measurements and comprehensive comparisons of DSE and observers have been presented. The usefulness and necessity of DSE based solutions in ensuring system stability, reliable protection and security, and resilience by revamping of control and protection methods are shown through examples, practical applications, and suggestions for further development.
- A Novel Rough Wall Boundary Condition for LES of high Reynolds Number FlowsXiao, Heng; Liu, Yu; Sun, Rui; Devenport, William J. (Virginia Tech, 2015-06)The interactions between rough surfaces and fluid flows play an important role in turbulence simulation. The understanding of roughness elements at the wall (i.e., buildings and terrain features) to aerodynamics flow is crucial in wind energy from farm identification and assessment to turbine blade design. In this work, we propose a novel rough-wall boundary condition for LES to simulate flows over rough surfaces at high Reynolds numbers. The proposed rough-wall boundary condition consists of two parts: (1) smooth-wall modeling for high Reynolds number flow; (2) wall-modeling for roughness surface. To reduce the computational costs for high Reynolds number flow, a wall-modeling mesh is applied at the bottom of the boundary layer following (Kawai and Larsson 2012). In this procedure, the wall-modeling mesh will obtain velocity from LES mesh, solve for the shear stress according an equilibrium equation of boundary layer, and provides the calculated wall shear stress back to LES mesh. To verify the smooth wall-modeling LES part, the simulation of high Reynolds number flow in a channel is performed. The Reynolds number of the verification case is Re__8=u_c 8/u,,3.01x 10^5 and the thickness of the wall model is h_wm=0.18. The comparison of normalized streamwise velocity between the experiment, wall-modeling LES and pure LES are shown in the figure below. It is noted that the LES mesh of the modeling LES and pure LES are the same, but the wall-modeling LES will update the shear stress at the wall via wall modeling. Therefore, the wall-model LES results are the combination of the results of the wall-modeling part below h_wm and the LES part above h_wm. From the figure, it is can be seen that the wall modeling improves the results of LES when using relatively coarse grid at the boundary. Another part of the present model is the simulation of the influence of roughness elements. In the presented rough wall boundary condition, the flow around the roughness element, at the inner region of turbulent boundary layer, is not fully resolved. Instead, a one-layer roughness mesh is used to resolve the geometry of roughness elements. On the roughness mesh, the roughness geometry is adequately represented via the surface elevation. By projecting the instantaneous pressure onto the roughness surface, the instantaneous roughness shear stress is obtained. Since the smooth-wall and roughness shear stress are obtained, the total wall shear stress is obtained by adding the two parts. Then, the so obtained total wall shear stress is used to correct the flow at the near wall region. The LES mesh size, lix^+, liy^+ and liz^+ (in streamwise, wall-normal, and spanwise directions, respectively) in the present simulations can be as large as 50 to 4000, which is favorable for high-Reynolds number flow simulations in applications of wind turbines. Moreover, the presented wall model can solve roughness elements having size of K^+ ranging from 100 to several hundred wall units, which can be used to estimate the influence of roughness elements at different sizes. According to the results from the simulations, the presented rough wall-modeling boundary condition can perform high fidelity simulation for turbulent flow at higher Reynolds number by using a relatively low computational cost. The velocity profiles and Reynolds stress agree favorably with experimental data and numerical results in the literature. Therefore, the merits of the proposed rough-wall model are demonstrated.