Burst Detection in Turbulent Channel Flows Based on Large Eddy Simulation Databases

Reliable turbulent channel flow databases at several Reynolds numbers have been established by large eddy simulation (LES), with two of them validated by comparing with typical direct numerical simulation (DNS) results. Furthermore, the statistics, such as velocity profile, turbulent intensities and shear stress, were obtained as well as the temporal and spatial structure of turbulent bursts. Based on the LES databases available, the conditional sampling methods are used to detect the structures of burst events. A method to deterimine the grouping parameter from the probability distribution function (pdf) curve of the time separation between ejection events is proposed to avoid the errors in detected results. And thus, the dependence of average burst period on thresholds is considerably weakened. Meanwhile, the average burst-to-bed area ratios are detected. It is found that the Reynolds number exhibits little effect on the burst period and burst-to-bed area ratio.

Protein three-dimensional structural databases: Domains, structurally aligned homologues and superfamilies

This paper reports the availability of a database of protein structural domains (DDBASE), an alignment database of homologous proteins (HOMSTRAD) and a database of structurally aligned superfamilies (CAMPASS) on the World Wide Web (WWW). DDBASE contains information on the organization of structural domains and their boundaries; it includes only one representative domain from each of the homologous families. This database has been derived by identifying the presence of structural domains in proteins on the basis of inter-secondary structural distances using the program DIAL [Sowdhamini & Blundell (1995), Protein Sci. 4, 506-520]. The alignment of proteins in superfamilies has been performed on the basis of the structural features and relationships of individual residues using the program COMPARER [Sali & Blundell (1990), J. Mol. Biol. 212, 403-428]. The alignment databases contain information on the conserved structural features in homologous proteins and those belonging to superfamilies. Available data include the sequence alignments in structure-annotated formats and the provision for viewing superposed structures of proteins using a graphical interface. Such information, which is freely accessible on the WWW, should be of value to crystallographers in the comparison of newly determined protein structures with previously identified protein domains or existing families.

A shortest path algorithm for moving objects in spatial network databases

One of the most important kinds of queries in Spatial Network Databases (SNDB) to support location-based services (LBS) is the shortest path query. Given an object in a network, e.g. a location of a car on a road network, and a set of objects of interests, e.g. hotels,gas station, and car, the shortest path query returns the shortest path from the query object to interested objects. The studies of shortest path query have two kinds of ways, online processing and preprocessing. The studies of preprocessing suppose that the interest objects are static. This paper proposes a shortest path algorithm with a set of index structures to support the situation of moving objects. This algorithm can transform a dynamic problem to a static problem. In this paper we focus on road networks. However, our algorithms do not use any domain specific information, and therefore can be applied to any network. This algorithm’s complexity is O(klog2 i), and traditional Dijkstra’s complexity is O((i + k)2).

a shortest path algorithm for moving objects in spatial network databases

中国计算机学会