A Density Control Based Adaptive Hexahedral Mesh Generation Algorithm

A density control based adaptive hexahedral mesh generation algorithm for three dimensional models is presented in this paper. The first step of this algorithm is to identify the characteristic boundary of the solid model which needs to be meshed. Secondly, the refinement fields are constructed and modified according to the conformal refinement templates, and used as a metric to generate an initial grid structure. Thirdly, a jagged core mesh is generated by removing all the elements in the exterior of the solid model. Fourthly, all of the surface nodes of the jagged core mesh are matching to the surfaces of the model through a node projection process. Finally, the mesh quality such as topology and shape is improved by using corresponding optimization techniques

Model validation of aeroelastic system for robust flutter prediction

The problems of uncertainty modeling and model validation of aeroelastic system are investigated. The parametric uncertainty is considered to denote the uncertainties in structure, and both parametric form and unmodeled dynamics are used to represent the influences and mechanism of uncertainties in unsteady aerodynamic forces. The Linear Fractional Transformation representation of the uncertain aeroelastic system is established to perform model validation and robust flutter analysis. A testing method for the existence of a validating model set in frequency-domain is developed, then the model validating sets are parameterized and the problem of searching the uncertainty magnitudes can be formulated as an optimization process. The influence of exogenous disturbances and noise, which are inevitable in actual testing environment and commonly unknown but energy bounded is considered, and consequently the conservatism of the uncertainty bounds is reduced. At last, for the uncertain aeroelastic system with the obtained uncertainty magnitudes, the robust flutter analysis based on structured singular value theory is performed to predict the robust stability boundary. The comparison of the results associated with two different uncertainty descriptions and the influences of disturbance and noise are discussed. Two numerical examples are presented and the results of the simulation demonstrate the validity of the developed method

Saikosaponins induced hepatotoxicity in mice via lipid metabolism dysregulation and oxidative stress: a proteomic study

Background Radix Bupleuri (RB) has been popularly used for treating many liver diseases such as chronic hepatic inflammation and viral Hepatitis in China. Increasing clinical and experimental evidence indicates the potential hepatotoxicity of RB or prescriptions containing RB. Recently, Saikosaponins (SS) have been identified as major bioactive compounds isolated from RB, which may be also responsible for RB-induced liver injury. Methods Serum AST, ALT and LDH levels were determined to evaluate SS-induced liver injury in mice. Serum and liver total triglyceride and cholesterol were used to indicate lipid metabolism homeostasis. Liver ROS, GSH, MDA and iNOS were used to examine the oxidative stress level after SS administration. Western blot was used to detect CYP2E1 expression. A 8-Plex iTRAQ Labeling Coupled with 2D LC - MS/MS technique was applied to analyze the protein expression profiles in livers of mice administered with different doses of SS for different time periods. Gene ontology analysis, cluster and enrichment analysis were employed to elucidate potential mechanism involved. HepG2 cells were used to identify our findings in vitro. Results SS dose- and time-dependently induced liver injury in mice, indicated by increased serum AST, ALT and LDH levels. According to proteomic analysis, 487 differentially expressed proteins were identified in mice administrated with different dose of SS for different time periods. Altered proteins were enriched in pathways such as lipid metabolism, protein metabolism, macro molecular transportation, cytoskeleton structure and response to stress. SS enhanced CYP2E1 expression in a time and dose dependent manner, and induced oxidative stress both in vivo and in vitro. Conclusion Our results identified hepatotoxicity and established dose-time course-liver toxicity relationship in mice model of SS administration and suggested potential mechanisms, including impaired lipid and protein metabolism and oxidative stress. The current study provides experimental evidence for clinical safe use of RB, and also new insights into understanding the mechanism by which SS and RB induced liver injury