Slip distribution model along the anchorage length of prestressing strands

An analytical model to predict strand slips within both transmission and anchorage lengths in pretensioned prestressed concrete members is presented. This model has been derived from an experimental research work by analysing the bond behavior and determining the transmission and anchorage lengths of seven-wire prestressing steel strands in different concrete mixes. A testing technique based on measuring the prestressing strand force in specimens with different embedment lengths has been used. The testing technique allows measurement of free end slip as well as indirect determination of the strand slip at different cross sections of a member without interfering with bond phenomena. The experimental results and the proposed model for strand slip distribution have been compared with theoretical predictions according to different equations in the literature and with experimental results obtained by other researchers. © 2013 Elsevier Ltd.

Pattern Recognition Approach for Road Collision Hotspots Analysis: Case Study of Northern Ireland

In order to address road safety effectively, it is essential to understand all the factors, which
attribute to the occurrence of a road collision. This is achieved through road safety
assessment measures, which are primarily based on historical crash data. Recent advances
in uncertain reasoning technology have led to the development of robust machine learning
techniques, which are suitable for investigating road traffic collision data. These techniques
include supervised learning (e.g. SVM) and unsupervised learning (e.g. Cluster Analysis).
This study extends upon previous research work, carried out in Coll et al. [3], which
proposed a non-linear aggregation framework for identifying temporal and spatial hotspots.
The results from Coll et al. [3] identified Lisburn area as the hotspot, in terms of road safety,
in Northern Ireland. This study aims to use Cluster Analysis, to investigate and highlight any
hidden patterns associated with collisions that occurred in Lisburn area, which in turn, will
provide more clarity in the causation factors so that appropriate countermeasures can be put
in place.