High Order Multi-Moment Constrained Finite Volume Method. Part I: Basic Formulation

A new high-order finite volume method based on local reconstruction is presented in this paper. The method, so-called the multi-moment constrained finite volume (MCV) method, uses the point values defined within single cell at equally spaced points as the model variables (or unknowns). The time evolution equations used to update the unknowns are derived from a set of constraint conditions imposed on multi kinds of moments, i.e. the cell-averaged value and the point-wise value of the state variable and its derivatives. The finite volume constraint on the cell-average guarantees the numerical conservativeness of the method. Most constraint conditions are imposed on the cell boundaries, where the numerical flux and its derivatives are solved as general Riemann problems. A multi-moment constrained Lagrange interpolation reconstruction for the demanded order of accuracy is constructed over single cell and converts the evolution equations of the moments to those of the unknowns. The presented method provides a general framework to construct efficient schemes of high orders. The basic formulations for hyperbolic conservation laws in 1- and 2D structured grids are detailed with the numerical results of widely used benchmark tests. (C) 2009 Elsevier Inc. All rights reserved.

Effect of sugar type on the survival of frozen-thawed rhesus monkey (Macaca mulatta) sperm

Sperm-freezing extenders supplemented with sugar or a combination of different sugars are widely used for the cryopreservation of nonhuman primate spermatozoa. Understanding which sugar or combination of sugars offers the highest level of cryoprotection w

Environmental mechanism of change in cyanobacterial species composition in the northeastern part of Lake Dianchi (China)

Environmental mechanism of change in cyanobacterial species composition in the northeastern part of Lake Dianchi (also called Macun Bay and Haidong Bay) was studied using canonical correlation analysis (CCA), but also bottom-up control and top-down control were fully discussed. Results from CCA suggest: (1) the abundance and dominance of Microcystis aeruginosa in Macun Bay and Haidong Bay are influenced by total phosphorus (TP), nitrate (NO3--N), nitrite (NO2--N), dissolved oxygen (DO) and water temperature (WT); (2) water temperature has a positive correlation with the abundance of M. aeruginosa and it also has negative correlations with the abundances of Anabaena flos-aquae and Aphanizomenonon flos-aquae; and (3) abundances of both Anabaena flos-aquae and Aphanizomenon flos-aquae have positive correlations with ammonia-N (NH4+-N). Furthermore, cyanobacterial species composition has no significant correlations with light and size-fractioned iron in this study. Grazers, cyanophages and viruses were able to control cyanobacterial blooms and change the composition of cyanobacterial species. Though we studied physical and chemical factors intensely enough, we still are not able to predict the change in the composition of cyanobacterial blooms, because of plankton system in a chaotic behavior.

Changes in the concentrations of size-fractioned iron and related environmental factors in the northeastern part of lake Dianchi (China)

To observe changes in the concentrations of size-fractionated iron and related environmental factors, experiments were conducted in the northeastern part of the shallow eutrophic lake Dianchi (China) from March 2003 to February 2004. Iron concentrations were measured for three size fractions: particulate iron (phi >0.22 mu m), colloidal iron (phi = 0.025-0.22 mu m) and soluble iron (phi < 0.025 mu m), and environmental factors (physicochemical and biological factors) were synchronously analyzed. Results showed that size-fractionated iron and the related environmental factors all varied with season. Colloidal iron accounted for only 5-9% of total iron, while particulate and soluble iron each accounted for 40-50% of total iron. The results suggested that size-fractionated iron can transform into each other, especially the highly reactive colloidal iron. Significant linear correlations were found between iron in different size fractions, and significant correlations were also obtained between chlorophyll a and environmental factors, such as TN, TP and secchi depth. No significant correlation between iron and chlorophyll a was found in this study.