RNG in turbulence and modeling of bypass transition

Two projects are considered: the Renormalization Group (RNG) analysis of turbulence modeling, and the calculation of bypass transition through turbulence modeling. RNG is a process which eliminates small scales on the uneliminated large scales as the change in the transport properties. It is because of this property of RNG that it was previously suggested that RNG could be used as a model builder in turbulence modeling. The possibility is studied of constructing RNG based turbulence models, and to try to proceed to do the modeling through RNG in parallel with the classical approach. The numerical predictions made by RNG models and by classical models is compared against data from Direct Numerical Simulation. While in an environment with freestream turbulence, the transition initiated by the instability of the laminar boundary layer to Tollmien-Schlichting waves is found to be a bypass one in which turbulent spots are formed without T-S wave amplification. The formation is a random process, and flow within a turbulent spot is almost fully turbulent. This suggests the possibility of using turbulence modeling to describe and predict the bypass transition

Rebels Lead to the Doctrine of the Mean: Opinion Dynamic in a Heterogeneous DeGroot Model

We study an extension of the DeGroot model where part of the players may be rebels. The updating rule for rebels is quite different with that of normal players (which are referred to as conformists): at each step a rebel first takes the opposite value of the weighted average of her neighbors' opinions, i.e. 1 minus that average (the opinion space is assumed to be [0,1] as usual), and then updates her opinion by taking another weighted average between that value and her own opinion in the last round. We find that the effect of rebels is rather significant: as long as there is at least one rebel in every closed and strongly connected group, under very weak conditions, the opinion of each player in the whole society will eventually tend to 0.5.Comment: 7 pages, Proceedings of The 6th International Conference on Knowledge, Information and Creativity Support Systems, Beijing, 201

A Convex Formulation for Spectral Shrunk Clustering

Spectral clustering is a fundamental technique in the field of data mining and information processing. Most existing spectral clustering algorithms integrate dimensionality reduction into the clustering process assisted by manifold learning in the original space. However, the manifold in reduced-dimensional subspace is likely to exhibit altered properties in contrast with the original space. Thus, applying manifold information obtained from the original space to the clustering process in a low-dimensional subspace is prone to inferior performance. Aiming to address this issue, we propose a novel convex algorithm that mines the manifold structure in the low-dimensional subspace. In addition, our unified learning process makes the manifold learning particularly tailored for the clustering. Compared with other related methods, the proposed algorithm results in more structured clustering result. To validate the efficacy of the proposed algorithm, we perform extensive experiments on several benchmark datasets in comparison with some state-of-the-art clustering approaches. The experimental results demonstrate that the proposed algorithm has quite promising clustering performance.Comment: AAAI201

Longitudinal static stability requirements for wing in ground effect vehicle

ABSTRACT:The issue of the longitudinal stability of a WIG vehicle has been a very critical design factor since the first experimental WIG vehicle has been built. A series of studies had been performed and focused on the longitudinal stability analysis. However, most studies focused on the longitudinal stability of WIG vehicle in cruise phase, and less is available on the longitudinal static stability requirement of WIG vehicle when hydrodynamics are considered: WIG vehicle usually take off from water. The present work focuses on stability requirement for longitudinal motion from taking off to landing. The model of dynamics for a WIG vehicle was developed taking into account the aerodynamic, hydrostatic and hydrodynamic forces, and then was analyzed. Following with the longitudinal static stability analysis, effect of hydrofoil was discussed. Locations of CG, aerodynamic center in pitch, aerodynamic center in height and hydrodynamic center in heave were illustrated for a stabilized WIG vehicle. The present work will further improve the longitudinal static stability theory for WIG vehicle

Toward accurate measurement of property-dependent galaxy clustering: II. Tests of the smoothed density-corrected VmaxV_{\rm max} method

We present a smoothed density-corrected $V_{\rm max}$ technique for building a random catalog for property-dependent galaxy clustering estimation. This approach is essentially based on the density-corrected $V_{\rm max}$ method of Cole(2011), with three improvements to the original method. To validate the improved method, we generate two sets of flux-limited samples from two independent mock catalogs with different $k+e$ corrections. By comparing the two-point correlation functions, our results demonstrate that the random catalog created by the smoothed density-corrected $V_{\rm max}$ approach provides a more accurate and precise measurement for both sets of mock samples than the commonly used $V_{\rm max}$ method and redshift shuffled method. For flux-limited samples and color-dependent subsamples, the accuracy of the projected correlation function is well constrained within $1\%$ on the scale $0.07 h^{-1}\rm Mpc$ to $30 h^{-1}\rm Mpc$. The accuracy of the redshift-space correlation function is less than $2\%$ as well. Currently, it is the only approach that holds promise for achieving the high-accuracy goal of clustering measures for next-generation surveys.Comment: 19 pages, 12 figures. Accepted for publication in Ap