Shear crack control for a reinforced concrete T-beam using coupled stochastic-multi-objective optimization methods

Ayad Ramadan; Ayad Ramadan

doi:10.3934/matersci.2023057

AIMS Materials Science

2023, Volume 10, Issue 6: 1077-1089. doi: 10.3934/matersci.2023057

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Shear crack control for a reinforced concrete T-beam using coupled stochastic-multi-objective optimization methods

Ayad Ramadan ^,

Department of Mathematics, College of Science, Sulaimani University, KRG

Received: 21 August 2023 Revised: 27 October 2023 Accepted: 30 October 2023 Published: 29 November 2023

We use multi-objective optimization and numerical simulations to optimize the shear strength of a reinforced concrete T-beam. The optimization process involves four factors that are related to the Young's modulus of elasticity and density of both the steel reinforcement and the concrete. The factors, which have a limited range, are utilized in the construction of the regression equation that forecasts the reinforced concrete T-beam's ductility and elastic shear strain. Using ABAQUS finite element programs, 27 models were prepared for numerical analysis and simulation using the well-known sampling technique Box-Behnken design. To find the coefficients that correspond to the regression equations, MATLAB codes are utilized to solve complex matrices using the least squares method. Checking the regression equation's reliability to compare the outcomes of the numerical simulations and the regression equations, a reliability check for the regression equation has been implemented. Due to the simultaneous R² values of 1 and 1 for ductility and elastic shear strain, the reliability check was 100%. The optimization of the reinforced concrete T-beam's shear strength capacity can be easily determined, according to multi-objective optimization results, and the design of this structural system is highly controllable.
- elastic shear strain,
- ductility,
- box-Behnken design,
- regression,
- multi-criteria
Citation: Ayad Ramadan. Shear crack control for a reinforced concrete T-beam using coupled stochastic-multi-objective optimization methods[J]. AIMS Materials Science, 2023, 10(6): 1077-1089. doi: 10.3934/matersci.2023057

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Abstract

We use multi-objective optimization and numerical simulations to optimize the shear strength of a reinforced concrete T-beam. The optimization process involves four factors that are related to the Young's modulus of elasticity and density of both the steel reinforcement and the concrete. The factors, which have a limited range, are utilized in the construction of the regression equation that forecasts the reinforced concrete T-beam's ductility and elastic shear strain. Using ABAQUS finite element programs, 27 models were prepared for numerical analysis and simulation using the well-known sampling technique Box-Behnken design. To find the coefficients that correspond to the regression equations, MATLAB codes are utilized to solve complex matrices using the least squares method. Checking the regression equation's reliability to compare the outcomes of the numerical simulations and the regression equations, a reliability check for the regression equation has been implemented. Due to the simultaneous R² values of 1 and 1 for ductility and elastic shear strain, the reliability check was 100%. The optimization of the reinforced concrete T-beam's shear strength capacity can be easily determined, according to multi-objective optimization results, and the design of this structural system is highly controllable.

References

[1]	Ferreira CC, Barros MHFM, Barros AFM (2003) Optimal design of reinforced concrete T-section in bending. Eng Struct 25: 951–964. https://doi.org/10.1016/S0141-0296(03)00039-7 doi: 10.1016/S0141-0296(03)00039-7
[2]	Baghi H, Barros JA (2018) Design-oriented approach to predict shear strength of reinforced concrete beams. Struct Concrete 19: 98–115. https://doi.org/10.1002/suco.201700095 doi: 10.1002/suco.201700095
[3]	Rabczuk T, Belytschko T (2004) Cracking particles: A simplified meshfree method for arbitrary evolving cracks. Int J Numer Meth Engng 61: 2316–2343. http://dx.doi.org/10.1002/nme.1151 doi: 10.1002/nme.1151
[4]	Rabczuk T, Belytschko T (2007) A three dimensional large deformation meshfree method for arbitrary evolving cracks. Comput Methods Appl Mech Eng 196: 2777–2799. https://doi.org/10.1016/j.cma.2006.06.020 doi: 10.1016/j.cma.2006.06.020
[5]	Rabczuk T, Goangseup Zi, Bordas S, et al. (2010) A simple and robust three-dimensional cracking-particle method without enrichment. Comput Methods Appl Mech Eng 199: 2437. https://doi.org/10.1016/j.cma.2010.03.031 doi: 10.1016/j.cma.2010.03.031
[6]	Rhee I (2022) Failure analysis of steel fiber-reinforced concrete T-beams without shear stirrups. Appl Sci 12: 411. https://doi.org/10.3390/app12010411 doi: 10.3390/app12010411
[7]	Abd RT (2019) Prediction of the shear strength of concrete T-beams using artificial neural networks model. UTJES 10: 168–181. http://www.doi.org/10.31663/tqujes.10.1.354 doi: 10.31663/tqujes.10.1.354
[8]	Shahbazian A, Rabiefar H, Aminnejad B (2021) Shear strength determination in RC beams using ANN trained with tabu search training algorithm. Adv Civ Eng 2021: 1639214. https://doi.org/10.1155/2021/1639214 doi: 10.1155/2021/1639214
[9]	Shahbazpanahi S (2017) Mechanical analysis of a shear-cracked RC beam. Acta Sci-Technol 39: 285–290. https://doi:10.4025/actascitechnol.v39i3.29672 doi: 10.4025/actascitechnol.v39i3.29672
[10]	Shahbazpanahi S (2018) The development of a dynamic fracture propagation model for FRP-strengthened beam-column joints. J Vibroeng 20: 1382–1391. https://doi.org/10.21595/jve.2017.18686 doi: 10.21595/jve.2017.18686
[11]	Kaszubska M, Kotynia R (2022) Selected shear models based on the analysis of the critical shear crack for slender concrete beams without shear reinforcement. Materials 15: 8259. https://doi.org/10.3390/ma15228259 doi: 10.3390/ma15228259
[12]	Kaszubska M, Kotynia R, Barros JAO, et al. (2017) Shear behavior of concrete beams reinforced exclusively with longitudinal glass fiber reinforced polymer bars: Experimental research. Structural Concrete 19: 152–161. https://doi.org/10.1002/suco.201700174 doi: 10.1002/suco.201700174
[13]	Lopes AV, Lopes SMR (2023) Revisiting cracking in reinforced concrete beams: An updated analysis. Appl Sci 13: 3926. https://doi.org/10.3390/app13063926 doi: 10.3390/app13063926
[14]	Khuri AI, Mukhopadhyay S (2010) Response surface methodology. WIREs Comp Stat 2:128–149. https://doi.org/10.1002/wics.73 doi: 10.1002/wics.73
[15]	Ferreira SLC, Bruns RE, Ferreira HS, et al. (2007) Box-Behnken design: An alternative for the optimization of analytical methods. Anal Chim Acta 597: 179–186. https://doi.org/10.1016/j.aca.2007.07.011 doi: 10.1016/j.aca.2007.07.011
[16]	Sen C (1983) A new approach for multi-objective rural development planning. IEJ 30: 91–96.
[17]	Sen C (2018) Sen's multi-objective programming method and its comparison with other techniques. Am J Oper Res 8: 10–13. https://doi:10.5923/j.ajor.20180801.02 doi: 10.5923/j.ajor.20180801.02
[18]	Sen C (2018) Multi-objective optimization techniques: Misconceptions and clarifications. IJSIMR 6: 29–33. http://dx.doi.org/10.20431/2347-3142.0606004 doi: 10.20431/2347-3142.0606004
[19]	Sen C (2019) Improved scalarizing techniques for solving multi-objective optimization problems. Am J Oper Res 9: 8–11. http://doi:10.5923/j.ajor.20190901.02 doi: 10.5923/j.ajor.20190901.02
[20]	Sen C (2020) Improved averaging techniques for solving multi-objective optimization (MOO) problems. SN App Sci 2: 286. https://doi.org/10.1007/s42452-019-1892-3 doi: 10.1007/s42452-019-1892-3
[21]	Sulaiman NA, Rebaz B (2016) Using harmonic mean to solve multi-objective linear programming problems. Am J Oper Res 6: 25–30. http://doi:10.4236/ajor.2016.61004 doi: 10.4236/ajor.2016.61004

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