A New Saturation-Based Framework for Compaction Quality Control
Publication: International Journal of Geomechanics
Volume 24, Issue 3
Abstract
Field compaction control is arguably the most common yet critical quality control procedure in geotechnical engineering. Since the early 1930s, the systematic process for performing quality control of compacted soils has often been implemented by measuring the in-place dry unit weight (or density) and as-compacted soil moisture content after placement in a fill. However, the current practice overlooks several facts resulting from comparing soil prepared and compacted in the laboratory to soils placed and compacted in the field. These issues include comparing the compaction energy in the lab versus what is applied in the field, and the behavior of saturated soils in the laboratory to the performance of unsaturated soils in the field. To address some of these gaps, this study presents a new saturation-based framework for compaction quality control. The aim of this new framework is to reduce the uncertainties and assumptions of the compaction control process and provide practicing engineers with further insight into the key engineering attributes of compacted soils. The proposed saturation-based approach compares a degree of saturation difference with a normalized dry unit weight ratio, making saturation upon compaction the controlling diagnostic variable and the focus of the monitoring effort. In essence, the optimal compaction conditions will be referenced to a characteristic saturation state near 80%. Compared with the conventional quality control system for field compaction, the saturation-based approach is developed with the same field and reference data collected for most earth fill projects. The results of this approach enhance the engineering judgment required to match the laboratory reference values to the field conditions. For the purposes of illustration, the proposed saturation-based framework is applied to compaction control data of a large earth dam and compared against the conventional method side by side.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
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© 2024 American Society of Civil Engineers.
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Received: Apr 6, 2023
Accepted: Sep 11, 2023
Published online: Jan 4, 2024
Published in print: Mar 1, 2024
Discussion open until: Jun 4, 2024
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