journal article·2021-12Open access

Sample dimension effect on equations controlling tensile and compressive strength of cement-stabilized sandy soil under optimal compaction conditions

José Wilson dos Santos Ferreira, Michéle Dal Toé Casagrande, Raquel Souza Teixeira

Abstract

The porosity/cement ratio (η/Civ) has been applied as a key parameter for the understanding of tensile and compressive strengths of a wide range of soils-cement mixtures, although the focus has been restricted to non-optimal compaction condition, which does not fully reflect the field execution process. Also, distinct sample dimensions have been utilized in the research area without taking this effect into account. Recognizing these needs, this study aims to evaluate the sample dimension effect on the equations controlling the mechanical behavior by η/Civ, under optimal compaction conditions. Using sandy soil, Unconfined Compressive Strength (UCS or qu) and Indirect Tensile Strength (ITS or qt) tests were performed from distinct curing period, cement type and content, based on conventional (127×100 mm) and reduced dimension (105×50 mm) specimens. The addition of both cements did not show significant variations in compaction parameters, which affected the η-qu and η-qt relations. The use of η/Civ ratio proved to be a suitable parameter for dosing, considering both sample dimensions under optimal compaction conditions. A unique exponent related to the increment of qu and qt along 7 and 28 curing days was obtained by each cement type, regardless of the sample dimension, leading to an average of 0.13 qt/qu relationship. Finally, mixtures molded in reduced dimension showed 20% higher strengths when compared to conventional dimension, despite the cement type and content, porosity, and curing period.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Geotechnical Engineering and Soil Stabilization · Grouting, Rheology, and Soil Mechanics · Soil and Unsaturated Flow

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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