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Computer Aided Design in Composite Material Technology III pp 475–485Cite as

Optimal Design of Prestressed Concrete Composite Slab by Geometric Programming

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Abstract

Geometric programming (GP) has been found suitable for optimal design of many engineering systems. This paper presents a method based on GP for cost-optimal design of prestressed concrete panel composite slab. Precast prestressed concrete panels are used as formwork for .cast-in-situ reinforced concrete floor slab. The objective function of the optimization problem includes cost of concrete, prestressing, erection and reinforcing. The constraints are formulated based on allowable stresses, deflections and geometry of the structural systems. The optimization problem is solved to obtain the optimal values of the design variables.

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References

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Author information

Authors and Affiliations

  1. Dept. of Civil Engineering, National University of Singapore, 0511, Kent Ridge Crescent, Singapore

    N. C. Das Gupta & C. H. Yu

Authors
  1. N. C. Das Gupta
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  2. C. H. Yu
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Editor information

Editors and Affiliations

  1. Department of Mechanical Engineering, University of Delaware, 19716, Newark, DE, USA

    S. G. Advani

  2. Wessex Institute of Technology, Ashurst Lodge, S04 2AA, Southampton, UK

    W. R. Blain

  3. Faculteit Toegepaste Wetenschappen Dienst Analyse van Strukturen, Vrije Universiteit Brussels, Pleinlaan 2, B-1050, Belgium

    W. P. de Wilde

  4. Center for Composite Materials, University of Delaware, 19716, Newark, DE, USA

    J. W. Gillespie Jr.

  5. Department of Engineering Science and Mechanics, Virginia Polytechnic Institute and State University, 24061, Blacksburg, VA, USA

    O. H. Griffin Jr.

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© 1992 Computational Mechanics Publications

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Das Gupta, N.C., Yu, C.H. (1992). Optimal Design of Prestressed Concrete Composite Slab by Geometric Programming. In: Advani, S.G., Blain, W.R., de Wilde, W.P., Gillespie, J.W., Griffin, O.H. (eds) Computer Aided Design in Composite Material Technology III. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-2874-2_32

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  • DOI: https://doi.org/10.1007/978-94-011-2874-2_32

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-85166-781-9

  • Online ISBN: 978-94-011-2874-2

  • eBook Packages: Springer Book Archive

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