There are numerous reasons for which concrete has become the most widely used construction material in buildings, one of them being its availability in different types, such as fiber-reinforced, lightweight, high strength, conventional and self-compacting concrete. This advantage is specially realized in high-rise building construction, where common construction practice is to use concretes of different types or strength classes in slabs and columns. Columns in such structures are generally made from concrete which is higher in compressive strength than the one used in floors or slabs. This raises issue of selection of concrete strength that should be used for estimating column capacity. Current paper tries to address this issue by testing nine (09) sandwich column specimens under axial loading. The floor concrete portion of the sandwich column was made of normal strength concrete, whereas column portions from comparatively higher strength concrete. Test results show that aspect ratio (h/b) influences the effective concrete strength of such columns. A previously adopted methodology of composite material analogy with some modifications has been found to predict well the capacity of columns where variation in floor and concrete strength is significant.
The lateral aspects of railway vehicle wheelset have a significant impact on railway wheelset dynamic systems. Lateral analysis usually causes wheelset slippage from the track resulting insufficient adhesion which can lead to creep. Significant disturbances are mostly caused in lateral direction due to speed. This paper uses the dual Kalman filter strategy to deal with noise issues and thus minimizes the error ratio during observation. A single Kalman filter reduces errors to a minimum extent while the second estimator decreases the maximum available chance of error. Using a third estimator provides no further improvement over the dual Kalman filter implementation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.