TRB's National Cooperative Highway Research Program (NCHRP) Report 676: Intelligent Soil Compaction Systems explores intelligent compaction, a new method of achieving and documenting compaction requirements. Intelligent compaction uses continuous compaction-roller vibration monitoring to assess mechanistic soil properties, continuous modification/adaptation of roller vibration amplitude and frequency to ensure optimum compaction, and full-time monitoring by an integrated global positioning system to provide a complete GPS-based record of the compacted area--

A field investigation was conducted with four intelligent compaction/continuous compaction control rollers to characterize the spatial reporting of vibratory roller-measured soil properties and to investigate global positioning system (GPS)-based position reporting error. The key reporting characteristics examined include the spatial resolution of roller measurement values (MVs) and the volume/area reflected in each MV. Each vibration-based roller MV investigated is a reflection of soil properties over spatial dimensions that vary across manufacturers. The reporting resolution of roller MVs also varied across manufacturers. Three sources of GPS-determined position error were observed, namely, (1) accuracy of GPS, (2) unaccounted for physical offset of roller-mounted GPS receiver from the drum center, and (3) the spatial averaging of vibration data during roller MV calculation coupled with possible computational latency. The physical offset error was found to be as great as 1.0-2.0 m, while the error due to spatial averaging of vibration data coupled with latency ranged from 0.4 to 0.8 m. Both of these errors are significant but can be estimated and corrected by using a validation procedure described in the paper. Left uncorrected, these errors have a significant adverse effect on the analysis and interpretation of roller MV data when used in quality control/quality assurance specifications.

This report describes a study of intelligent compaction (IC) technologies, within the context of actual construction projects, for its potential as a component of INDOT's QC/QA for soils. The output from an IC-equipped roller compaction equipment is a real-time area mapping of the compacted lift stiffness as captured by the IC measure. Data was collected to evaluate the correlation between each of two IC measures-compaction meter value (CMV) and machine drive power (MDP)-and in situ embankment quality test measures, the chief in situ test being the dynamic cone penetrometer (DCP) test which INDOT uses for soil embankment acceptance testing. Researchers sought to understand how well the IC measures might assess embankment quality as currently evaluated by the in situ measures. Window-averaged IC measures were compared with the in situ DCP test points. For CMV, a variable correlation was found between the average CMV and DCP values from 74 in situ locations. Also, a limited head-to-head comparison of CMV and MDP with the in situ measures provided some indication that MDP should be studied further. Lessons were learned regarding the elimination of bias in future correlation studies, critical provisions to facilitate best data quality, and important aspects of data management. IC technology holds promise for monitoring the consistency of the soil compaction effort and flagging weak areas in real time during compaction operations. However, further insight is needed regarding the correlation of the DCP measure with both types of IC measures for various soil characterizations and field moisture conditions.

How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short computation times; to offer content that is accessible for engineers; and to be sufficiently general - so that readers can use the book for many different problems. The authors also describe how to make decisions under different types of uncertainty. The book offers a valuable resource for all practical engineers interested in better ways of gauging uncertainty, for students eager to learn and apply the new techniques, and for researchers interested in processing heterogeneous uncertainty.