Studies of unsteady viscous flows using a two-equation model of turbulence

A two equation model of turbulence, based on the turbulent kinetic energy and energy dissipation, suitable for prediction of unsteady viscous flows, was developed. Also, the performance of the two equation model was compared with simpler algebraic models such as the Baldwin-Lomax two layer eddy viscosity model, and a model by Johnson and King which accounts for upstream history of the turbulent kinetic energy. A brief discussion of this study is given

Boundary Condition of Polyelectrolyte Adsorption

The modification of the boundary condition for polyelectrolyte adsorption on charged surface with short-ranged interaction is investigated under two regimes. For weakly charged Gaussian polymer in which the short-ranged attraction dominates, the boundary condition is the same as that of the neutral polymer adsorption. For highly charged polymer (compressed state) in which the electrostatic interaction dominates, the linear relationship (electrostatic boundary condition) between the surface monomer density and the surface charge density needs to be modified.Comment: 4 page

Evaluation of three turbulence models for the prediction of steady and unsteady airloads

Two dimensional quasi-three dimensional Navier-Stokes solvers were used to predict the static and dynamic airload characteristics of airfoils. The following three turbulence models were used: the Baldwin-Lomax algebraic model, the Johnson-King ODE model for maximum turbulent shear stress, and a two equation k-e model with law-of-the-wall boundary conditions. It was found that in attached flow the three models have good agreement with experimental data. In unsteady separated flows, these models give only a fair correlation with experimental data

Analysis of viscous transonic flow over airfoil sections

A full Navier-Stokes solver has been used to model transonic flow over three airfoil sections. The method uses a two-dimensional, implicit, conservative finite difference scheme for solving the compressible Navier-Stokes equations. Results are presented as prescribed for the Viscous Transonic Airfoil Workshop to be held at the AIAA 25th Aerospace Sciences Meeting. The NACA 0012, RAE 2822 and Jones airfoils have been investigated for both attached and separated transonic flows. Predictions for pressure distributions, loads, skin friction coefficients, boundary layer displacement thickness and velocity profiles are included and compared with experimental data when possible. Overall, the results are in good agreement with experimental data

Hashing for large-scale structured data classification

University of Technology Sydney. Faculty of Engineering and Information Technology.With the rapid development of the information society and the wide applications of networks, almost incredibly large numbers bytes of data are generated every day from the social networks, business transactions and so on. In such cases, hashing technology, if done successfully, would greatly improve the performance of data management. The goal of this thesis is to develop hashing methods for large-scale structured data classification. First of all, this work focuses on categorizing and reviewing the current progress on hashing from a data classification perspective. Secondly, new hashing schemes are proposed by considering different data characteristics and challenges, respectively. Due to the popularity and importance of graph and text data, this research mainly focuses on these two kinds of structured data: 1) The first method is a fast graph stream classification method using Discriminative Clique Hashing (DICH). The main idea is to employ a fast algorithm to decompose a compressed graph into a number of cliques to sequentially extract clique-patterns over the graph stream as features. Two random hashing schemes are employed to compress the original edge set of the graph stream and map the unlimitedly increasing clique-patterns onto a fixed-size feature space, respectively. DICH essentially speeds up the discriminative clique-pattern mining process and solves the unlimited clique-pattern expanding problem in graph stream mining; 2) The second method is an adaptive hashing for real-time graph stream classification (ARC-GS) based on DICH. In order to adapt to the concept drifts of the graph stream, we partition the whole graph stream into consecutive graph chunks. A differential hashing scheme is used to map unlimited increasing features (cliques) onto a fixed-size feature space. At the final stage, a chunk level weighting mechanism is used to form an ensemble classifier for graph stream classification. Experiments demonstrate that our method significantly outperforms existing methods; 3) The last method is a Recursive Min-wise Hashing (RMH) for text structure. In this method, this study aims to quickly compute similarities between texts while also preserving context information. To take into account semantic hierarchy, this study considers a notion of “multi-level exchangeability”, and employs a nested-set to represent a multi-level exchangeable object. To fingerprint nested-sets for fast comparison, Recursive Min-wise Hashing (RMH) algorithm is proposed at the same computational cost of the standard min-wise hashing algorithm. Theoretical study and bound analysis confirm that RMH is a highly-concentrated estimator