Current models of the modulus of elasticity, E , of concrete recommended by the
American Concrete Institute (ACI) and the American Association of State Highway and
Transportation Officials (AASHTO) are derived only for normally vibrated concrete
(NVC). Because self consolidated concrete (SCC) mixtures used today differ from NVC
in the quantities and types of constituent materials, mineral additives, and chemical
admixtures, the current models may not take into consideration the complexity of SCC,
and thus they may predict the E of SCC inaccurately. Although some authors
recommend specific models to predict the E of SCC, they include only a single variable
of assumed importance, namely the compressive strength of concrete, c f ′ . However
there are other parameters that may need to be accounted for while developing a
prediction model for the E of SCC. In this research, a Bayesian variable selection
method is implemented to identify the significant parameters in predicting the E of SCC
and more accurate models for the E are generated using these variables. The models
have a parsimonious parameterization for ease of use in practice and properly account
for the prevailing uncertainties.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2467 |
| Date | 15 May 2009 |
| Creators | Bhattacharjee, Chandan |
| Contributors | Gardoni, Paolo, Trejo, David |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
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