- author = "Naci Caglar and Aydin Demir and Hakan Ozturk and Abdulhalim Akkaya",
- title = "A simple formulation for effective flexural stiffness of circular reinforced concrete columns",
- journal = "Engineering Applications of Artificial Intelligence",
- volume = "38",
- pages = "79--87",
- year = "2015",
- ISSN = "0952-1976",
-
DOI = "
doi:10.1016/j.engappai.2014.10.011",
-
URL = "
http://www.sciencedirect.com/science/article/pii/S0952197614002516",
- keywords = "genetic algorithms, genetic programming, Effective flexural stiffness, Moment-curvature, Reinforced concrete, Eurocode-8, TEC-2007",
- size = "9 pages",
-
abstract = "Concrete cracking reduces flexural and shear stiffness
of reinforced concrete (RC) members. Therefore
analysing RC structures without considering the
cracking effect may not represent actual behaviour.
Effective flexural stiffness resulting from concrete
cracking depends on some important parameters such as
confinement, axial load level, section dimensions and
material properties of concrete and reinforcing
steel.
In this study, a simple formula as a securer, quicker and more robust is proposed to determine the effective flexural stiffness of cracked sections of circular RC columns. This formula is generated by genetic programming (GP). The generalisation capabilities of the explicit formulations are compared by cross sectional analysis results and confirmed on a 3-D building model. Moreover the results from GP based formulation are compared with EC-8 and TEC-2007. It is demonstrated that the GP based model is highly successful to determine the effective flexural stiffness of circular RC columns.",
