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Genetic Algorithm for Embodied Energy Optimisation of Steel-Concrete Composite Beams

Author

Listed:
  • Alex H. Whitworth

    (WSP in the UK, WSP House, 70 Chancery Lane, London WC2A 1AF, UK)

  • Konstantinos Daniel Tsavdaridis

    (School of Civil Engineering, Faculty of Engineering and Physical Sciences, University of Leeds, Woodhouse Lane, Leeds LS2 9JT, UK)

Abstract

The optimisation of structural performance is acknowledged as a means of obtaining sustainable structural designs. A minimisation of embodied energy of construction materials is a key component in the delivery of sustainable future designs. This study attempts to understand the relationship between embodied energy and structural form of composite floor plates for tall buildings, and how this form can be optimised to minimise embodied energy. As a search method based upon the principles of genetics and natural selection, genetic algorithms (GA) have previously been used as novel means of optimising composite beams and composite frames for cost and weight objective functions. Parametric design models have also been presented as optimisation tools to optimise steel floor plates for both cost and embodied carbon. In this study, a Matlab algorithm is presented incorporating MathWorks global optimisation toolbox GA and utilising Eurocode 4 design processes to optimise a composite beam for five separate objective functions: maximise span length; minimise beam cross-section; minimise slab depth; minimise weight; minimise deflected shape for each of the objective functions. Candidate designs are to be assessed for embodied energy to determine individual relationships. This study shows that it is possible to reduce the embodied energy of steel–concrete composite beams by genetic algorithm optimisation whilst remaining compliant to given design codes.

Suggested Citation

  • Alex H. Whitworth & Konstantinos Daniel Tsavdaridis, 2020. "Genetic Algorithm for Embodied Energy Optimisation of Steel-Concrete Composite Beams," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:8:p:3102-:d:344787
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    Citations

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    Cited by:

    1. Laurentiu-Mihai Ionescu & Nicu Bizon & Alin-Gheorghita Mazare & Nadia Belu, 2020. "Reducing the Cost of Electricity by Optimizing Real-Time Consumer Planning Using a New Genetic Algorithm-Based Strategy," Mathematics, MDPI, vol. 8(7), pages 1-26, July.
    2. Da Wang & Benkun Tan & Shengtao Xiang & Xie Wang, 2022. "Fatigue Crack Propagation and Life Analysis of Stud Connectors in Steel-Concrete Composite Structures," Sustainability, MDPI, vol. 14(12), pages 1-19, June.
    3. Felipe Piana Vendramell Ferreira & Konstantinos Daniel Tsavdaridis & Carlos Humberto Martins & Silvana De Nardin, 2021. "Steel-Concrete Composite Beams with Precast Hollow-Core Slabs: A Sustainable Solution," Sustainability, MDPI, vol. 13(8), pages 1-25, April.

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