Evaluation of data analysis methods for the CRS consolidation test

Patrick J. Fox, He Fu Pu, John T. Christian

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

The constant rate-of-strain (CRS) laboratory consolidation test is used to measure consolidation properties of fine-grained soils. Although the CRS test offers many advantages over the conventional incremental-loading consolidation test, uncertainties associated with the method of data analysis have presented an obstacle to more widespread use of the CRS test in practice. This paper presents results from a numerical investigation of the accuracy of linear and nonlinear data analysis methods for the CRS consolidation test. Numerical simulations were conducted using a validated large strain consolidation model for CRS loading conditions, published material properties for two reconstituted clay soils, and three applied strain rates. Based on the numerical results, recommendations are provided for analysis of CRS consolidation data, including changes to the ASTM D4186 equations for nonlinear data analysis. The most appropriate analysis method for soils with linear compressibility is the current ASTM D4186 linear theory method. The most appropriate analysis method for soils with nonlinear compressibility is the proposed modified nonlinear (MNL) theory method. These recommended congruent analysis methods provided good to excellent results for normally consolidated, steady-state conditions, including constant or variable coefficient of consolidation, but yielded large errors for overconsolidated conditions near the preconsolidation stress. As a precaution, CRS tests for overconsolidated soils should generally be conducted using lower strain rates.

Original languageEnglish (US)
Article number04014020
JournalJournal of Geotechnical and Geoenvironmental Engineering
Volume140
Issue number6
DOIs
StatePublished - 2014

All Science Journal Classification (ASJC) codes

  • Geotechnical Engineering and Engineering Geology
  • Environmental Science(all)

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