Abstract
This paper presents a particle swarm optimization based on constriction factor (CFPSO) technique used to perform the design optimization of reinforced concrete beams that satisfies Indian codal requirements of strength and serviceability. Optimal cross-sectional sizing and optimal percentage of reinforcement of an RC beam results in cost saving, but these cannot be standardized for the various factors that influence a given design. The objective function consists of the cost of concrete, rebars, and formwork as prevalent at the place of construction. Successful implementation of the algorithm clearly establishes CFPSO’s ability of performance as compared to standard particle swarm optimization with inertia weights in the case of RC beams. A number of examples have been presented to show the effectiveness of this formulation for achieving optimal design.
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Abbreviations
- fy :
-
Characteristic yield strength of steel in N/mm2
- fck :
-
Characteristic compressive strength of concrete in N/mm2
- Ast:
-
Area of steel in mm2
- Mu:
-
Bending moment due to self weight and given loading in kN-m
- M :
-
Maximum moment capacity in kN-m
- x u :
-
Actual position of neutral axis in mm
- x m :
-
Limiting position of neutral axis in mm
- d B :
-
Effective depth of beam in mm
- b B :
-
Width of beam in mm
- Con_Cover:
-
Effective cover to reinforcement
- δ_allowable:
-
Allowable deflection in mm
- δ_total:
-
Total deflection in mm
- P t :
-
Percentage of tension reinforcement
- r :
-
Effective depth to width ratio
- P min :
-
Minimum percentage of steel
- P max :
-
Maximum percentage of steel
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Chutani, S., Singh, J. (2021). Use of Constriction Factor-Based Particle Swarm Optimization in Design of Reinforced Concrete Beams. In: Singh, H., Singh Cheema, P.P., Garg, P. (eds) Sustainable Development Through Engineering Innovations. Lecture Notes in Civil Engineering, vol 113. Springer, Singapore. https://doi.org/10.1007/978-981-15-9554-7_49
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