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Optimisation of tensile membrane structures under uncertain wind loads using PCE and kriging based metamodels

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Abstract

Tensile membrane structures (TMS) are light-weight flexible structures that are designed to span long distances with structural efficiency. The stability of a TMS is jeopardised under heavy wind forces due to its inherent flexibility and inability to carry out-of-plane moment and shear. A stable TMS under uncertain wind loads (without any tearing failure) can only be achieved by a proper choice of the initial prestress. In this work, a double-loop reliability-based design optimisation (RBDO) of TMS under uncertain wind load is proposed. Using a sequential polynomial chaos expansion (PCE) and kriging based metamodel, this RBDO reduces the cost of inner-loop reliability analysis involving an intensive finite element solver. The proposed general approach is applied to the RBDO of two benchmark TMS and its computational efficiency is demonstrated through these case studies. The method developed here is suggested for RBDO of large and complex engineering systems requiring costly numerical solution.

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References

  • Allen D (1971) The prediction sum of squares as a criterion for selecting prediction variables. Tech rep., Department of Statistics, University of Kentucky

  • Ang AHS, Tang WHS (2007) Probability concepts in engineering. Wiley, New York

    Google Scholar 

  • Aoues Y, Chateauneuf A (2009) Benchmark study of numerical methods for reliability-based design optimization. Struct Multidiscip Optim 41(2):277–294

    Article  MathSciNet  MATH  Google Scholar 

  • ASCE (2010a) ASCE/SEI 55-10 tensile membrane structures american society of civil engineers. Reston, USA

  • ASCE (2010b) ASCE/SEI 7-10 Minimum Design Loads for Building and Other Structures American Society of Civil Engineers. Reston

  • Au SK, Beck JL (2001) Estimation of small failure probabilities in high dimensions by subset simulation. Prob Eng Mech 16(4):263–277

    Article  Google Scholar 

  • Barnes MR (1999) Form finding and analysis of tension structures by dynamic relaxation. Int J Space Struct 14(2):89–104

    Article  Google Scholar 

  • Blatman G, Sudret B (2010) An adaptive algorithm to build up sparse polynomial chaos expansions for stochastic finite element analysis. Probab Eng Mech 25(2):183–197

    Article  Google Scholar 

  • Blatman G, Sudret B (2011) Adaptive sparse polynomial chaos expansion based on least angle regression. J Comput Phys 230(6):2345–2367

    Article  MathSciNet  MATH  Google Scholar 

  • Chaudhuri A, Haftka RT (2014) Efficient global optimization with adaptive target setting. AIAA J 52 (7):1573–1577

    Article  Google Scholar 

  • Couckuyt I, Dhaene T, Demeester P (2014) oodace toolbox: a flexible object-oriented kriging implementation. J Mach Learn Res 15:3183–3186

    MATH  Google Scholar 

  • Du X, Chen W (2004) Sequential optimization and reliability assessment method for efficient probabilistic design. J Mech Des Trans ASME 126(2):225–233

    Article  Google Scholar 

  • Dubourg V, Sudret B, Bourinet J (2011) Reliability-based design optimization using kriging surrogates and subset simulation. Struct Multidiscip Optim 44(5):673–690

    Article  Google Scholar 

  • Dutta S, Ghosh S, Inamdar MM (2017a) Polynomial chaos-based optimisation for a tensile membrane structure under uncertain wind forces. In: Proceedings of the 12th International Conference on Structural Safety & Reliability (ICOSSAR 2017), Vienna, Austria

  • Dutta S, Ghosh S, Inamdar MM (2017b) Reliability-based design optimisation of frame-supported tensile membrane structures. ASCE-ASME J Risk Uncertain Eng Syst Part A: Civil Eng 3(2):G4016001

    Article  Google Scholar 

  • Ellingwood B (1981) Wind and snow load statistics for probabilistic design. J Struct Div ASCE 107 (ST7):1345–1350

    Google Scholar 

  • Ellingwood BR, Tekie PB (1999) Wind load statistics for probability-based structural design. ASCE J Struct Eng 125(4):453–463

    Article  Google Scholar 

  • Filomeno Coelho R, Lebon J, Bouillard P (2011) Hierarchical stochastic metamodels based on moving least squares and polynomial chaos expansion: application to the multiobjective reliability-based optimization of space truss structures. Struct Multidiscip Optim 43(5):707–729

    Article  MathSciNet  MATH  Google Scholar 

  • Forrester AIJ, Keane AJ (2009) Recent advances in surrogate-based optimization. Progress Aeros Sci 45 (1-3):50–79

    Article  Google Scholar 

  • Forrester AIJ, Sobester A, Keane AJ (2008) Engineering design via surrogate modelling: a practical guide. Wiley, Chichester

    Book  Google Scholar 

  • Ghanem R, Spanos PD (1991) Stochastic finite elements: a spectral approach. Springer-Verlag, Berlin

    Book  MATH  Google Scholar 

  • Gosling PD, Bridgens BN, Albrecht A, Alpermann H, Angeleri A, Barnes M, Bartle N, Canobbio R, Dieringer F, Gellin S, Lewis WJ, Mageau N, Mahadevan R, Marion J, Marsden P, Milligan E, Phang YP, Sahlin K, Stimpfle B, Suire O, Uhlemann J (2013a) Analysis and design of membrane structures: results of a round robin exercise. Eng Struct 48:313–328

    Article  Google Scholar 

  • Gosling PD, Bridgens BN, Zhang L (2013b) Adoption of a reliability approach for membrane structure analysis. Struct Saf 40:39–50

    Article  Google Scholar 

  • Hao P, Wang B, Li G, Meng Z, Wang L (2015) Hybrid framework for reliability-based design optimization of imperfect stiffened shells. AIAA J 53(10):2878–2889

    Article  Google Scholar 

  • Hao P, Wang B, Tian K, Li G, Du K, Niu F (2016) Efficient optimization of cylindrical stiffened shells with reinforced cutouts by curvilinear stiffeners. AIAA J 54(4):1350–1363

    Article  Google Scholar 

  • Hao P, Wang Y, Liu C, Wang B, Wu H (2017) A novel non-probabilistic reliability-based design optimization algorithm using enhanced chaos control method. Comput Methods Appl Mech Eng 318:572–593

    Article  MathSciNet  Google Scholar 

  • Hu W, Choi KK, Cho H (2016) Reliability-based design optimization of wind turbine blades for fatigue life under dynamic wind load uncertainty. Struct Multidiscip Optim 54(4):953–970

    Article  Google Scholar 

  • Huang Z, Wang C, Chen J, Tian H (2011) Optimal design of aeroengine turbine disc based on kriging surrogate models. Comput Struct 89(1-2):27–37

    Article  Google Scholar 

  • Huntington CG (2013) Tensile fabric structures: design, analysis and construction. American Society of Civil Engineers

  • Jin R, Du X, Chen W (2003) The use of metamodeling techniques for optimization under uncertainty. Struct Multidiscip Optim 25(2):99–116

    Article  Google Scholar 

  • Kennedy J, Eberhart RC (2001) Swarm intelligence. Morgan Kaufmann Publishers Inc., San Francisco

    Google Scholar 

  • Kirjner-Neto C, Polak E, Der Kiureghian A (1998) An outer approximations approach to reliability-based optimal design of structures. J Optim Theory Appl 98(1):1–16

    Article  MathSciNet  MATH  Google Scholar 

  • Kuschel N, Rackwitz R (1997) Two basic problems in reliability-based structural optimization. Math Methods Oper Res 46(3):309–333

    Article  MathSciNet  MATH  Google Scholar 

  • Lewis WJ (2003) Tension structures form and behaviour. Thomas Telford Publishing, London

    Book  Google Scholar 

  • Lewis WJ (2013) Modeling of fabric structures and associated design issues. ASCE J Architect Eng 19(2):81–88

    Article  Google Scholar 

  • Li G, Meng Z, Hu H (2015) An adaptive hybrid approach for reliability-based design optimization. Struct Multidiscip Optim 51(5):1051–1065

    Article  MathSciNet  Google Scholar 

  • Li W, Yang L (1994) An effective optimization procedure based on structural reliability. Comput Struct 52(5):1061–1071

    Article  MATH  Google Scholar 

  • Marelli S, Sudret B (2014) UQLab: a framework for uncertainty quantification in MATLAB. In: Beer M, Au SK, Hall JW (eds) Vulnerability, Risk Analysis and Management (ICVRAM2014). American Society of Civil Engineers, USA, pp 2554–2563

  • Melchers RE (2002) Structural reliability analysis and prediction. Wiley, New York

    Google Scholar 

  • Miller RG (1974) The jackknife – a review. Biometrika 61(1):1–15

    MathSciNet  MATH  Google Scholar 

  • Molinaro AM, Simon R, Pfeiffer RM (2005) Prediction error estimation: a comparison of resampling methods. Bioinformatics 21(15):3301–3307

    Article  Google Scholar 

  • Moustapha M, Sudret B, Bourinet J, Guillaume B (2016) Quantile-based optimization under uncertainties using adaptive kriging surrogate models. Struct Multidiscip Optim 54(6):1403–1421

    Article  MathSciNet  Google Scholar 

  • Nowak AS, Collins KR (2013) Reliability of structures, 2nd edn. CRC Press, Boca Raton

    Google Scholar 

  • Papadrakakis M, Lagaros ND (2002) Reliability-based structural optimization using neural networks and monte carlo simulation. Comput Methods Appl Mech Eng 191(32):3491–3507

    Article  MATH  Google Scholar 

  • Qu X, Haftka R T (2004) Reliability-based design optimization using probabilistic sufficiency factor. Struct Multidiscip Optim 27(5):314–325

    Article  Google Scholar 

  • Rackwitz R (2001) Reliability analysis-a review and some perspective. Struct Saf 23(4):365–395

    Article  Google Scholar 

  • Ren X, Yadav V, Rahman S (2016) Reliability-based design optimization by adaptive-sparse polynomial dimensional decomposition. Struct Multidiscip Optim 53(3):425–452

    Article  MathSciNet  Google Scholar 

  • Royset JO, Der Kiureghian A, Polak E (2001) Reliability-based optimal structural design by the decoupling approach. Reliab Eng Syst Saf 73(3):213–221

    Article  Google Scholar 

  • Santner TJ, Williams BJ, Notz WI (2003) The design and analysis of computer experiments. Springer series in statistics. Springer-Verlag, Berlin

    Book  MATH  Google Scholar 

  • Schöbi R, Sudret B, Wiart J (2015) Polynomial-chaos-based kriging. Int J Uncertain Quantif 5 (2):171–193

    Article  MathSciNet  Google Scholar 

  • Schuëller GI, Jensen HA (2008) Computational methods in optimization considering uncertainties - an overview. Comput Methods Appl Mech Eng 198(1):2–13

    Article  MATH  Google Scholar 

  • Sobol IM (2001) Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math Comput Simul 55(1–3):271–280

    Article  MathSciNet  MATH  Google Scholar 

  • Soize C, Ghanem R (2005) Physical systems with random uncertainties: chaos representations with arbitrary probability measure. SIAM J Sci Comput 26(2):395–410

    Article  MathSciNet  MATH  Google Scholar 

  • Topping BHV, Iványi P (2007) Computer-aided design of cable membrane structures. Saxe-Coburg Publications

  • Valdebenito MA, Schuëller GI (2010) A survey on approaches for reliability-based optimization. Struct Multidiscip Optim 42(5):645–663

    Article  MathSciNet  MATH  Google Scholar 

  • Venkataraman P (2009) Applied optimization with MATLAB programming. Wiley, New York

    Google Scholar 

  • Youn BD, Wang P (2008) Bayesian reliability-based design optimization using eigenvector dimension reduction (edr) method. Struct Multidiscip Optim 36(2):107–123

    Article  Google Scholar 

  • Zhang D, Han X, Jiang C, Liu J, Li Q (2017) Time-dependent reliability analysis through response surface method. J Mech Des Trans ASME 139(4):041404

    Article  Google Scholar 

  • Zou T, Mahadevan S (2006) A direct decoupling approach for efficient reliability-based design optimization. Struct Multidiscip Optim 31(3):190–200

    Article  Google Scholar 

Download references

Acknowledgements

The second author (SG) would like to thank Prof. Bruno Sudret, IBK, D-BAUG, ETH Zürich, for his lectures and notes on uncertainty quantification using PCE, and for the licence of the UQLab toolbox.

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Correspondence to Siddhartha Ghosh.

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Dutta, S., Ghosh, S. & Inamdar, M.M. Optimisation of tensile membrane structures under uncertain wind loads using PCE and kriging based metamodels. Struct Multidisc Optim 57, 1149–1161 (2018). https://doi.org/10.1007/s00158-017-1802-5

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  • DOI: https://doi.org/10.1007/s00158-017-1802-5

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