UHPC modulus of elasticity: Assessment and new developments using companion materials and structural data

Abstract

The determination of the concrete modulus of elasticity (MOE) plays a crucial role in the analysis and design of structural reinforced and prestressed concrete elements. Various empirical MOE prediction equations have been developed for UHPC. However, most of the existing models have been typically calibrated or developed based on data from one type of UHPC and material tests only. As such, no previous work looked at the MOE prediction equations validity at a large-scale structural level and for the different range of UHPC mixtures that span from economic or non-proprietary lower-end mixtures to robust carbon nanofiber (CNF)-enhanced and high-end mixtures. This research fills this knowledge gap by revisiting the topic of UHPC MOE prediction equations using exclusive companion datasets of materials and full-scale structural tests that also incorporate, for the first time, four different types of UHPC mixtures. In this study, MOE values are estimated from experimentally determined axial stiffness of 22 full-scale UHPC columns with varying cross-sections in conjunction with hundreds of cylinders. The study first compared cylinders and columns-based MOE values, then used the extensive experimental datasets to assess recent and relevant UHPC MOE prediction equations, including what has been proposed for the AASHTO UHPC Structural Design Guide. The results show that while some of the existing prediction models are accurate for traditional UHPC mixtures, all models consistently underestimate MOE for CNF-enhanced UHPC and overestimate it for economic UHPC mixtures with local sand and cement. The paper concludes with a recommendation to account for UHPC mixture type and proposes new modifications for adopting MOE prediction equations for all types of UHPC.