Abstract
Intelligent compaction is gaining popularity as a tool for evaluating soil compaction. Unfortunately, intelligent compaction equipment collects an overwhelming amount of data, especially for an inspector who is making decisions in the field. The goal of this approach is to identify optimal places to perform field compaction tests on the basis of relative compaction values. This paper presents a geographic information system application that analyzes and views intelligent compaction data to support in-field decision making. To facilitate the analysis, intelligent compaction data were converted from geographic coordinates into a regularized station and offset coordinate system. A grid of points at 1-ft intervals was placed over the intelligent compaction data, and spatial analysis tools were used to average the compaction values within various distances of the grid points. On the assumption that 95% of a soil lift must be compacted correctly, statistical analyses were performed to identify points that fell between the 4th and 6th percentiles of the compaction value. A positive outcome from field compaction tests at these locations would indicate that at least 95% of the lift was properly compacted; a negative outcome would indicate that less than 95% of the lift was compacted adequately and that additional compaction work was required.
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