Size effect on fire resistance of axially compressed reinforced concrete columns

Artificial neural networks, in interaction with fuzzy logic, genetic algorithms, and fuzzy neural networks, represent an example of a modern interdisciplinary field, especially when it comes to solving certain types of engineering problems that could not be solved using traditional modeling methods and statistical methods. They represent a modern trend in practical developments within the prognostic modeling field and, with acceptable limitations, enjoy a generally recognized perspective for application in construction. Results obtained from numerical analysis, which includes analysis of the behavior of reinforced concrete elements and linear structures exposed to actions of standard fire, were used for the development of a prognostic model with the application of fuzzy neural networks. As fire resistance directly affects the functionality and safety of structures, the significance which new methods and computational tools have on enabling quick, easy, and simple prognosis of the same is quite clear. This paper will consider the application of fuzzy neural networks by creating prognostic models for determining fire resistance of eccentrically loaded reinforced concrete columns.

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Empirical model for determining fire resistance of Reinforced Concrete columns

Construction and Building Materials ◽

10.1016/j.conbuildmat.2019.07.183 ◽

2019 ◽

Vol 225 ◽

pp. 838-852 ◽

Cited By ~ 2

Author(s):

Shujaat H. Buch ◽

Umesh K. Sharma

Keyword(s):

Reinforced Concrete ◽

Fire Resistance ◽

Empirical Model ◽

Concrete Columns ◽

Reinforced Concrete Columns

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Size Effect on the Seismic Performance of High-Strength Reinforced Concrete Columns with Different Shear Span-to-Depth Ratios

Mathematical Problems in Engineering ◽

10.1155/2018/2723198 ◽

2018 ◽

Vol 2018 ◽

pp. 1-19

Author(s):

Chunyi Yu ◽

Hua Ma ◽

Yongping Xie ◽

Zhenbao Li ◽

Zhenyun Tang

Keyword(s):

Reinforced Concrete ◽

Size Effect ◽

Seismic Performance ◽

Factor Of Safety ◽

Shear Failure ◽

High Strength ◽

Concrete Columns ◽

Reinforced Concrete Columns ◽

Local Factor ◽

Shear Span

The size effect on the seismic performance of conventional reinforced concrete columns has been observed in terms of flexural failure and shear failure. Under earthquake loading, slender columns experience flexural failure, and short columns experience flexure-shear failure and shear failure. However, the effect of section size on the seismic performance of high-strength reinforced concrete columns under the conditions of different shear span-to-depth ratios requires further confirmation. For this purpose, six high-strength reinforced concrete columns with shear span-to-depth ratios of 2 and 4 were subjected to cyclic loading in this study. The experimental results indicated that relative nominal flexural strength, energy dissipation coefficient, factor of safety, and local factor of safety all exhibited a strong size effect by decreasing with increasing column size. Furthermore, the size effect became stronger as the shear span-to-depth ratio was increased, except for average energy dissipation coefficient. The observed changes in the factor of safety were in good agreement with the Type 2 size effect model proposed by Bažant. Thus, based on the local factor of safety and Bažant’s Type 2 model, the code equation for moment capacity of different shear span-to-depth ratios was modified to provide a consistent factor of safety regardless of column size.

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