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A general purpose real-world structural design optimization computing platform

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Abstract

Structural optimization has matured from a narrow academic discipline, where researchers focused on optimum design of small idealized structural components and systems, to become the basis in modern design of complex structural systems. Some software applications in recent years have made these tools accessible to professional engineers, decision-makers and students outside the structural optimization research community. These software applications, mainly focused on aerospace, aeronautical, mechanical and naval structural systems, have incorporated the optimization component as an additional feature of the finite element software package. On the other hand though there is not a holistic optimization approach in terms of final design stage for real-world civil engineering structures such as buildings, bridges or more complex civil engineering structures. The optimization computing platform presented in this study is a generic real-world optimum design computing platform for civil structural systems and it is implemented within an innovative computing framework, founded on the current state of the art in topics like metaheuristic optimization, structural analysis and parallel computing. For demonstration purposes the application of the optimization computing platform in five real-world design projects is presented.

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References

  • AISC-ASD (1989) Manual of steel construction-allowable stress design, 9 th edn. American Institute of Steel Construction, Chicago

    Google Scholar 

  • Altair OptiStruct (2013) http://www.altairhyperworks.com/Product,19,OptiStruct.aspx. Accessed Sept 2013

  • Ang AH-S, Tang WH (1984) Probabilistic concepts in engineering planing and design. Decision, risk and reliability, vol II. Wiley, New York

    Google Scholar 

  • ARUP (2013) http://www.arup.com/. Accessed Sept 2013

  • ASCE/SEI Standard 41-06 (2006) Seismic rehabilitation of existing buildings, prepublication edition. Structural Engineering Institute, American Society of Civil Engineers

  • ATC-58 (2009) Guidelines for seismic performance assessment of buildings. Applied Technology Council, Redwood City

    Google Scholar 

  • Barricelli NA (1962) Numerical testing of evolution theories. Acta Biotheor 16:69–126

    Article  Google Scholar 

  • BS5950 (2000) Structural use of steelwork in building, part 1: code of Practice for Design - Rolled and Welded Sections, British Standards Institution

  • Charmpis DC, Lagaros ND, Papadrakakis M (2005) Multi-database exploration of large design spaces in the framework of cascade evolutionary structural sizing optimization. Comput Methods Appl Mech Eng 194(30-33):3315–3330

    Article  MATH  Google Scholar 

  • Daskalakis K (2013). http://www.konstantiosdaskalakis.com Accessed Sept 2013

  • Der Kiureghian A (2005) First- and second-order reliability methods. In: Nikolaidis E, Ghiocel DM, Singhal S (eds) Chapter 14 in Engineering design reliability handbook. CRC Press, Boca Raton

    Google Scholar 

  • Dorigo M, Stützle T (2004) Ant Colony Optimization. The MIT Press

  • Ebrahimi M, Farmani MR, Roshanian J (2011) Multidisciplinary design of a small satellite launch vehicle using particle swarm optimization. Struct Multidiscip Optim 44(6):773–784

    Article  Google Scholar 

  • EC2 (2004) Eurocode 2: Design of concrete structures-part 1: general rules and rules for buildings. European Committee for Standardisation, Brussels, Belgium, The European Standard EN 1992-1-1

  • EC3 (2005) Eurocode 3: Design of steel structures, part 1.1: general rules and rules for buildings. European Committee for Standardisation, Brussels, Belgium, The European Standard EN 1993-1-1

  • EC8 (2004) Eurocode 8: design of structures for earthquake resistance. European Committee for Standardisation, Brussels, Belgium, The European Standard EN 1998–1

  • FEMA-356 (2000) Prestandard and commentary for the seismic rehabilitation of buildings. Federal Emergency Management Agency, Washington DC, SAC Joint Venture

  • FEMA-445 (2006) Next-generation performance-based seismic design guidelines, program plan for new and existing buildings. Federal Emergency Management Agency, Washington

  • Geem ZW (2010) Recent advances in harmony search algorithm. Studies in Computational Intelligence, Springer

  • Genesis (2013) http://www.vrand.com/Genesis.html. Accessed Sept 2013

  • Ghobarah A, Abou-Elfath H, Biddah A (1999) Response-based damage assessment of structures. Earthq Eng Struct Dyn 28(1):79–104

    Article  Google Scholar 

  • Giovenale P, Cornell CA, Esteva L (2004) Comparing the adequacy of alternative ground motion intensity measures for the estimation of structural responses. Earthq Eng Struct Dyn 33(8):951–979

    Article  Google Scholar 

  • Hansen N, Ostermeier A (2001) Completely derandomized self-adaptation in evolution strategies. Evol Comput 9(2):159–195

    Article  Google Scholar 

  • Herzog, De Meuron (2013) http://www.herzogdemeuron.com. Accessed Sept 2013

  • Holland J (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbour

    Google Scholar 

  • Hornlein HREM, Schittkowski K (1993) Software systems for structural optimization. International Series of Numerical Mathematics, Birkhauser

    Book  Google Scholar 

  • Igel C, Hansen N, Roth S (2007) Covariance matrix adaptation for multi-objective optimization. Evol Comput 15(1):1–28

    Article  Google Scholar 

  • Karaboga D, Basturk B (2008) On the performance of artificial bee colony algorithm. Appl Soft Comput 8(1):687–697

    Article  Google Scholar 

  • Kennedy J, Eberhart RC, Shi Y (2001) Swarm intelligence, series in evolutionary computation. Morgan Kaufmann Publishers

  • Kotinis M, Kulkarni A (2012) Multi-objective shape optimization of transonic airfoil sections using swarm intelligence and surrogate models. Struct Multidiscip Optim 45(5):747–758

    Article  Google Scholar 

  • Lagaros ND (2010) Multicomponent incremental dynamic analysis considering variable incident angle. Struct Infrastruct Eng 6(1–2):77–94

    Article  Google Scholar 

  • Lagaros ND (2013) http://users.ntua.gr/nlagaros/. Accessed Sept 2013

  • Lagaros ND, Karlaftis MG (2011) A critical assessment of metaheuristics for scheduling emergency infrastructure inspections. Swarm Evol Comput 1(3):147–163

    Article  Google Scholar 

  • Lagaros ND, Papadrakakis M (2012) Applied soft computing for optimum design of structures. Struct Multidiscip Optim 45:787–799

    Article  MATH  Google Scholar 

  • Le Riche R, Haftka RT (2012) On global optimization articles in SMO. Struct Multidiscip Optim 46(5):627–629

    Article  Google Scholar 

  • Liu P-L, Der Kiureghian A (1986) Multivariate distribution models with prescribed marginals and covariances. Probab Eng Mech 1(2):105–112

    Article  Google Scholar 

  • LS-DYNA (2013) http://www.lstc.com. Accessed Sept 2013

  • Michalewicz Z (2012) Genetic algorithms + data structures = evolution programs, 3rd Edition. Springer

  • Mitropoulou ChCh, Fourkiotis Y, Lagaros ND, Karlaftis MG (2013) Metaheuristics in structural design optimization. In: Gandomi AH, Yang X-S, Talatahari S, Alavi AH (eds) Metaheuristic applications in structures and infrastructures. Elsevier, pp 79–102

  • MSC Software (2013) http://www.mscsoftware.com. Accessed September 2013

  • Ponsich A, Coello CAC (2011) Differential Evolution performances for the solution of mixed-integer constrained process engineering problems. Appl Soft Comput J 11(1):399–409

    Article  Google Scholar 

  • PTW Architects (2013) http://www.ptw.com.au. Accessed Sept 2013

  • Rechenberg I (1973) Evolutionsstrategie – Optimierung technischer systeme nach prinzipien der biologischen Evolution. Fromman-Holzboog

  • Reh S, Beley J-D, Mukherjee S, Khor EH (2006) Probabilistic finite element analysis using ANSYS. Struct Saf 28(1–2):17–43

    Article  Google Scholar 

  • SAP2000 (2013) http://www.csiamerica.com/sap2000. Accessed Sept 2013

  • SCADA Pro (2013) http://www.scadapro.eu/. Accessed Sept 2013

  • Schuëller GI (2006) Developments in stochastic structural mechanics. Arch Appl Mech 75(10–12):755–773

    Article  MATH  Google Scholar 

  • Thomson W (1887) On the division of space with minimum partitional area. Acta Math 11(1–4):121–134

    Article  MathSciNet  Google Scholar 

  • Storn RM, Price KV (1997) Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces. J Glob Optim 11:341–359

    Article  MATH  MathSciNet  Google Scholar 

  • Sullivan TJ, Calvi GM, Priestley MJN, Kowalsky MJ (2003) The limitations and performances of different displacement based design methods. J Earthq Eng 7(1):201–241

    Google Scholar 

  • Tsompanakis Y, Lagaros ND, Papadrakakis M (2007) Structural optimization considering uncertainties. Taylor & Francis

  • Vamvatsikos D, Cornell CA (2002) Incremental dynamic analysis. Earthq Eng Struct Dyn 31(3):491–514

    Article  Google Scholar 

  • van Laarhoven PJ, Aarts EH (2010) Simulated annealing: theory and applications (mathematics and its applications). Kluwer Academic Publishers

  • Weaire D, Phelan R (1994) A counter-example to Kelvin’s conjecture on minimal surfaces. Philos Mag Lett 69:107–110

    Article  Google Scholar 

  • Yang X-S (2011) Metaheuristic optimization: algorithm analysis and open problems. Experimental Algorithms. Lect Notes Comput Sci 6630:21–32

    Article  Google Scholar 

  • Yang XS (2008) Nature-inspired metaheuristic algorithms. Luniver Press, Frome

    Google Scholar 

  • YTONG (2004) Earthquake resistant design of load-bearing Ytong structures. Ytong Manual, Xella Porobeton

Download references

Acknowledgments

The author would like to thank Harris Maragkos and Nikolaos Bakas; the first one for providing the .SDB files for the test examples considered in this study, and both of them for helping to link the optimization computing platform with SAP2000 software.

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Correspondence to Nikos D. Lagaros.

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Lagaros, N.D. A general purpose real-world structural design optimization computing platform. Struct Multidisc Optim 49, 1047–1066 (2014). https://doi.org/10.1007/s00158-013-1027-1

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