Durability of similar self-compacting concrete batches produced in two different EU laboratories

The present study intends to evaluate the sensitivity of self-compacting concrete (SCC) mixtures, cast in two different laboratories of the European Union, with a focus on rheological parameters, mechanical characteristics and durability properties. Six SCC mixtures with different water-to-binder ratios and silica fume levels of cement replacement and two normally vibrated concrete (NVC) mixtures have been compared. It has been found that the reproducibility of similar mixtures is possible, when using different constituent materials that conform to the European Standards. Comparable rheological, mechanical and durability properties can be achieved. Open porosity and sorptivity appear to be more sensitive than chloride penetrability. © 2012 Elsevier Ltd. All rights reserved.

Reproducibility of self-compacting concrete batches between two different EU laboratories

Self Compacting Concrete (SCC) offers a wide variety of advantages during casting. Considering the worldwide uniformity of guidelines concerning the composition and casting instructions for the production of fresh SCC, there is a need to explore the reproducibility of similar self-compacting concrete batches between different countries. In the present study, the fresh properties of similar SCC batches produced in two different laboratories of the European Union are being compared and evaluated.

Weighted least squares with expectation-maximization algorithm for burst detection in U.K. water distribution systems

Flow measurement data at the district meter area (DMA) level has the potential for burst detection in the water distribution systems. This work investigates using a polynomial function fitted to the historic flow measurements based on a weighted least-squares method for automatic burst detection in the U.K. water distribution networks. This approach, when used in conjunction with an expectationmaximization (EM) algorithm, can automatically select useful data from the historic flow measurements, which may contain normal and abnormal operating conditions in the distribution network, e.g., water burst. Thus, the model can estimate the normal water flow (nonburst condition), and hence the burst size on the water distribution system can be calculated from the difference between the measured flow and the estimated flow. The distinguishing feature of this method is that the burst detection is fully unsupervised, and the burst events that have occurred in the historic data do not affect the procedure and bias the burst detection algorithm. Experimental validation of the method has been carried out using a series of flushing events that simulate burst conditions to confirm that the simulated burst sizes are capable of being estimated correctly. This method was also applied to eight DMAs with known real burst events, and the results of burst detections are shown to relate to the water company's records of pipeline reparation work. © 2014 American Society of Civil Engineers.