Title:
Probabilistic Joint Shear Strength Models for Design of RC Beam-Column Connections
Author(s):
Jaehong Kim and James M. LaFave
Publication:
Structural Journal
Volume:
105
Issue:
6
Appears on pages(s):
770-780
Keywords:
Bayesian parameter estimation; lateral loading; shear failure.
DOI:
10.14359/20105
Date:
11/1/2008
Abstract:
An extensive experimental database is constructed for diverse types of reinforced concrete (RC) beam-column connections subjected to quasistatic cyclic lateral loading, with all included test subassemblies having eventually experienced joint shear failure. RC joint shear strength models are developed using the experimental database (after removing those subassemblies having inadequate confinement within the joint panel) in conjunction with a Bayesian parameter estimation method. The improved performance of the developed joint shear strength models is evaluated by comparison with other deterministic RC joint shear strength models (of both the codebased and the research variety). Finally, the ACI 352R-02 joint shear strength definition for design is modified for greater consistency, by following the general ACI 352R-02 approach but with adjusted joint shear strength factors.