Data-Driven Prediction Models For Total Shear Strength of Reinforced Concrete Beams With Fiber Reinforced Polymers Using An Evolutionary Machine Learning Approach
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- @Article{TAGHIPOURANVARI:2023:engstruct,
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author = "Ataollah {Taghipour Anvari} and Saeed Babanajad and
Amir H. Gandomi",
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title = "Data-Driven Prediction Models For Total Shear Strength
of Reinforced Concrete Beams With Fiber Reinforced
Polymers Using An Evolutionary Machine Learning
Approach",
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journal = "Engineering Structures",
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volume = "276",
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pages = "115292",
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year = "2023",
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ISSN = "0141-0296",
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DOI = "doi:10.1016/j.engstruct.2022.115292",
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URL = "https://www.sciencedirect.com/science/article/pii/S0141029622013682",
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keywords = "genetic algorithms, genetic programming, Reinforced
concrete, Material, Fiber reinforced polymer, FRP,
Beam, Shear, Data-driven model, GEP",
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abstract = "The strength of Reinforced Concrete (RC) structural
elements may need to be improved due to building usage
changes or damages that occurred after exposure to
extreme loads. Fiber Reinforced Polymer (FRP) is
commonly being used to enhance the performance of
reinforced concrete beams due to several advantages
such as having high strength and being lightweight. To
perform the analysis and design of the members, there
is a need for accurate models to determine the total
shear strength of the structural elements strengthened
with FRP sheets. In this paper, genetic programming has
been successfully used to develop models to predict the
total shear strength of the reinforced concrete beams.
A strategy is adopted here to find a simple yet
accurate formula to estimate the shear strength. These
models can correlate the total shear strength of the
beams reinforced with FRP sheets to the geometric and
material properties of RC beams and FRP sheets, without
the need for expensive laboratory tests. A compressive
database of the total shear strength of the RC beams
with FRP sheets was created from the literature.
External validation and sensitivity analysis, using
various statistical criteria, were conducted to assess
the precision and validity of the proposed models.
Based on 785 RC beams strengthened by externally bonded
FRP sheets, tested between 1992 and 2022, two
data-driven models were developed to predict the total
shear strength of RC beams strengthened with FRP. The
calculated correlations for Models I and II are 0.883
and 0.940, respectively. Superior performance was
obtained compared to other models from the literature
in accuracy. The proposed models can be used for design
purposes and the development of structural solutions
for existing structures",
- }
Genetic Programming entries for
Ataollah Taghipour Anvari
Saeed K Babanajad
A H Gandomi
Citations