The skidding resistance potential of steel slag aggregates.

Steel slag, a by-product of the steel industry, has been used in road construction in South Yorkshire and the surrounding areas for the past 60 years. There is anecdotal evidence of good performance from these materials which is supported by the fact that they continue to be used today to the satisfaction of the user. The work undertaken resulted from the need to quantify performance characteristics and develop confidence in the use of steel slag aggregates.The work reported here relates to the skidding resistance potential of steel slag aggregate for use in highway surfaces. Results are presented for both the laboratory determination of the properties of steel slag and for the in-service behaviour of steel slag aggregate road surfaces.The results are analysed and reviewed and conclusions drawn. Recommendations are made for further work, as it is intended the work initiated here should continue in future years to build up a detailed and extensive data bank of knowledge on the skidding resistance potential of steel slag.The experimental work contained within this thesis is essentially presented in two sections :-i) Investigations relating to the laboratory determination of the polishing resistance of steel slag aggregate and efforts to improve the consistency of test results on this aggregate.ii) Investigations relating to the current on-road skid resistance of selected roads within the region, and using historic data to relate these findings to laboratory test and on-site service conditions..Within section (i) other work is discussed related to assessing the variability of the processed aggregate from different parts of the processing plant and different supplying sites.Additionally within section (i) the PSV characteristic of 3mm sized steel slag aggregate is determined and a polishing profile is suggested for steel slag aggregate during the course of a standard PSV test.The discussion and analysis sections attempt to inter-relate the findings of areas (i) and (ii) above and use historic data, when available, to assess longer term trends.