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Currently, there are a lot of research activities dealing with gamma titanium aluminide (γ-TiAl) alloys as new materials for low pressure turbine (LPT) blades. Even though the scatter in mechanical properties of such intermetallic alloys is more distinctive as in conventional metallic alloys, stochastic investigations on γ -TiAl alloys are very rare. For this reason, we analyzed the scatter in static and dynamic mechanical properties of the cast alloy Ti-48Al-2Cr-2Nb. It was found that this alloy shows a size effect in strength which is less pronounced than the size effect of brittle materials. A weakest-link approach is enhanced for describing a scalable size effect under multiaxial stress states and implemented in a post processing tool for reliability analysis of real components. The presented approach is a first applicable reliability model for semi-brittle materials. The developed reliability tool was integrated into a multidisciplinary optimization of the geometry of a LPT blade. Some processes of the optimization were distributed in a wide area network, so that specialized tools for each discipline could be employed. The optimization results show that it is possible to increase the aerodynamic efficiency and the structural mechanics reliability at the same time, while ensuring the blade can be manufactured in an investment casting process.
Traffic simulations for virtual environments are concerned with the behavior of individual traffic participants. The complexity of behavior in these simulations is often rather simple to abide by the constraints of processing resources. In sophisticated traffic simulations, the behavior of individual traffic participants is also modeled, but the focus lies on the overall behavior of the entire system, e.g. to identify possible bottle necks of traffic flow [8].
Although p27 plays a central role in cell cycle regulation, its role in breast cancer prognosis is controversial. Furthermore, the p27 gene CDKN1B carries a polymorphism with unknown functional relevance. This study was designed to evaluate p27 expression and p27 genotyping with respect to early breast cancer prognosis. 279 patients with infiltrating metastasis-free breast cancer were included in this study. p27 expression was determined in tumor tissue specimens from 261 patients by immunohistochemistry. From 108 patients, the CDKN1B genotype was examined by PCR and subsequent direct sequencing. 55.2% of the tumors were considered p27 positive. p27 expression did not correlate with any of the established parameters except for nodal involvement but significantly correlated to prolonged disease-free survival. In 35% of the tumors analyzed, the CDKN1B gene showed a polymorphism at codon 109 (V109G). The V109G polymorphism correlated with greater nodal involvement. In the node-negative subgroup, V109G correlated significantly with a shortened disease-free survival. In conclusion, the determination of the CDKN1B genotype might be a powerful tool for the prognosis of patients with early breast cancer.
Using virtual environment systems for road safety education requires a realistic simulation of road traffic. Current traffic simulations are either too restricted in their complexity of agent behavior or focus on aspects not important in virtual environments. More importantly, none of them are concerned with modeling misbehavior of traffic participants which is part of every-day traffic and should therefore not be neglected in this context. We present a concept for a traffic simulation that addresses the need for more realistic agent behavior with regard to road safety education. The two major components of this concept are a simulation of persistent agents which minimizes computational overhead and a model of cognitive processes of human drivers combined with psychological personality profiles to allow for individual behavior and misbehavior.
Traditionally traffic simulations are used to predict traffic jams, plan new roads or highways, and estimate road safety. They are also used in computer games and virtual environments. There are two general concepts of modeling traffic: macroscopic and microscopic modeling. Macroscopic traffic models take vehicle collectives into account and do not consider individual vehicles. Parameters like average velocity and density are used to model the flow of traffic. In contrast, microscopic traffic models consider each vehicle individually. Therefore, vehicle specific parameters are of importance, e.g. current velocity, desired velocity, velocity difference to the lead vehicle, individual time gap.