Design optimisation of reinforced concrete pile foundation using generalised reduced gradient algorithm

Author:

Dauda Jamiu AdetayoORCID,Rahmon Suraj A.,Tijani Ibrahim A.ORCID,Mohammad Fouad,Okegbenro Wakeel O.

Abstract

PurposeThe purpose of this study is to find the optimum design of Reinforced Concrete (RC) pile foundation to enable efficient use of structural concrete with greater consequences for global environment and economy.Design/methodology/approachA non-linear optimisation technique based on the Generalised Reduced Gradient (GRG) algorithm was implemented to find the minimum cost of RC pile foundation in frictional soil. This was achieved by obtaining the optimum pile satisfying the serviceability and ultimate limit state requirements of BS 8004 and EC 7. The formulated structural optimisation procedure was applied to a case study project to assess the efficiency of the proposed design formulation.FindingsThe results prove that the GRG method in Excel solver is an active, fast, accurate and efficient computer programme to obtain optimum pile design. The application of the optimisation for the case study project shows up to 26% cost reduction compared to the conventional design.Research limitations/implicationsThe design and formulation of design constraints will be limited to provisions of BS 8004 and EC 7.Practical implicationsSince the minimum quantity of concrete was attained through optimisation, then minimum cement will be used and thus result in minimum CO2 emission. Therefore, the optimum design of concrete structures is a vital solution to limit the damage to the Earth's climate and the physical environment resulting from high carbon emissions.Originality/valueThe current study considers the incorporation of different soil ground parameters in the optimisation process rather than assuming any pile capacity value for the optimisation process.

Publisher

Emerald

Reference32 articles.

1. Optimisation of constrained nonlinear programming engineering problems: evaluation of alternative approaches,2019

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