Canine Fbg(Fibrinogen) ELISA Kit

The aim of the present work is to clarify the fine granular area (FGA) formation mechanism in two steels (tempered 34CrNiMo6 and X10CrNiMoV12-2-2) causing grain refinement in the early state of fatigue for internal crack initiation and propagation in the very high cycle fatigue regime at pure tension-compression loading (R=-1) and for applied mean stresses (R-1). Fatigue tests were performed with constant and variable amplitude at several R values using ultrasonic fatigue testing setups. Failed specimens were investigated using high-resolution scanning electron microscopy and focused ion beam technique with special attention paid to the crack origin and the surrounding microstructure. To prove models for FGA formation proposed in literature, a numerical model to evaluate effective R values and contact stresses between the fracture surfaces depending on the crack length has been realised. The aim of these investigations is to estimate the influence of crack closure effects on FGA formation. FGA formation due to repeating contact of the fracture surfaces according to the model postulated by Hong et al correlates well with the findings for numerical simulations.

We investigate the replica theory of the liquid-glass transition for a binary mixture of large and small additive hard spheres. We consider two different ansatze for this problem: the frozen glass ansatz (FGA) in which the exchange of large and small particles in a glass state is prohibited, and the exchange glass ansatz (EGA), in which it is allowed. We calculate the dynamical and thermodynamical glass transition points with the two ansatze. We show that the dynamical transition density of the FGA is lower than that of the EGA, while the thermodynamical transition density of the FGA is higher than that of the EGA. We discuss the algorithmic implications of these results for the density-dependence of the relaxation time of supercooled liquids. We particularly emphasize the difference between the standard Monte Carlo and swap Monte Carlo algorithms. Furthermore, we discuss the importance of particle exchange for estimating the configurational entropy.