Stress History–Dependent Secondary Compression of San Francisco Bay Region Old Bay Clays

• Published in: Journal of geotechnical and geoenvironmental engineering Vol. 147; no. 7
• Main Authors: Wagner, Nathaniel, Largent, Micaela, Stewart, Jonathan P, Beyzaei, Christine, Murphy, Debra, Butkovich, Jeremy, Egan, John A
• Format: Journal Article
• Language: English
• Published: New York American Society of Civil Engineers 01-07-2021
• Subjects: Clay; Compression; Compression tests; Consolidation; Groundwater; Holocene; Intervals; Overconsolidation; Pleistocene; Soil swelling; Stress history; Technical Papers; Unloading; San Francisco Bay
• ISSN: 1090-0241; 1943-5606
• DOI: 10.1061/(ASCE)GT.1943-5606.0002525

AbstractOld Bay Clays are silty clays of Pleistocene age encountered along the margins of San Francisco Bay, beneath various sand formations, Holocene Bay Muds, and surficial fills. These materials are overconsolidated in their natural state. A recent project, Millennium Tower, produced intervals of loading in the Old Bay Clays that induced primary consolidation followed by secondary compression. A testing program was undertaken to characterize secondary compression characteristics of these materials for two conditions: (1) following primary consolidation in the virgin compression range, and (2) following unloading to modest overconsolidation ratios (associated with groundwater rebound and potential foundation modification). Following post-unloading swell of the soil, the rate of secondary compression slows relative to the initial (i.e., subsequent to primary consolidation) condition. We observed three approximately linear intervals of progressively faster compression rates in log time space, with the reset (or zero) time taken upon load application causing the preceding virgin compression. Two models of secondary compression response from the literature are unable to capture this general pattern of response. In one case, the model takes secondary compression rate with respect to log time as invariant; in the other case, the time variations of this rate do not match the data. This work presents a framework that captures this behavior.