DOI QR코드

DOI QR Code

An iterative hybrid random-interval structural reliability analysis

  • Fang, Yongfeng ;
  • Xiong, Jianbin ;
  • Tee, Kong Fah
  • Received : 2014.04.20
  • Accepted : 2014.05.07
  • Published : 2014.12.25

Abstract

An iterative hybrid structural dynamic reliability prediction model has been developed under multiple-time interval loads with and without consideration of stochastic structural strength degradation. Firstly, multiple-time interval loads have been substituted by the equivalent interval load. The equivalent interval load and structural strength are assumed as random variables. For structural reliability problem with random and interval variables, the interval variables can be converted to uniformly distributed random variables. Secondly, structural reliability with interval and stochastic variables is computed iteratively using the first order second moment method according to the stress-strength interference theory. Finally, the proposed method is verified by three examples which show that the method is practicable, rational and gives accurate prediction.

Keywords

structure;interval load;random strength;strength degradation;hybrid model;dynamic reliability

References

  1. Allaix, D.L., Carbone, V.I. (2011), "An improvement of the response surface method", Struct. Saf., 33(2):165-172. https://doi.org/10.1016/j.strusafe.2011.02.001
  2. Ayyub, B.M. and Lai, K.L. (1992), "Structural reliability assessment with ambiguity and vagueness in failure", Naval Eng. J., 104(3): 21-35.
  3. Ben-Haim, Y. (1994), "A non-probabilistic concept of reliability", Structural Safety, 14(4): 227-245. https://doi.org/10.1016/0167-4730(94)90013-2
  4. Ditlevsen, O., Madsen, H.O.(1996). Structural Reliability Methods, Wiley, Chichester.
  5. Du, X.P., Sudjianto, A., Huang, B.Q. (2005), "Reliability-based design with the mixture of random and interval variable", Transact. ASME, 127(12), 1068-1077 https://doi.org/10.1115/1.1992510
  6. Du, X.P., Sudjianto, A., Huang, B.Q. (2005), "Reliability-based design with the mixture of random and interval variable", Transact. ASME, 127(12), 1068-1077. https://doi.org/10.1115/1.1992510
  7. Ellishkoff, I. (1995), "Essay on uncertainties in elastic and viscoelastic structures: from A M Freudenthal's criticisms to modern convex modeling", Comput. Struct., 56(6), 871-895. https://doi.org/10.1016/0045-7949(94)00499-S
  8. Elishakoff, I. (1995), "Discussion on a non-probabilistic concept of reliability", Struct. Saf., 17(3), 195-199. https://doi.org/10.1016/0167-4730(95)00010-2
  9. Fang, Y.F, Chen, J.J., Yan, B.and Ma, H.B. (2012). "Model for prediction of structural dynamic non-probabilistic reliability", Journal of Xidian University, 39(6), 170-175.
  10. Fang, Y.F., Chen, J.J. and Tee, K.F. (2013),"Analysis of structural dynamic reliability based on the probability density evolution method", Struct. Eng. Mech., 45(2), 201-209. https://doi.org/10.12989/sem.2013.45.2.201
  11. Guo, S.X., Lu, Z.Z. and Feng, Y.S. (2001), "A non-probabilistic model of structural reliability based on interval analysis", Chinese J. Comput. Mech., 18(1): 56-60.
  12. Gao, W. (2007), "Interval finite element analysis using interval factor method", Comput.Mech., 39(4), 709-717. https://doi.org/10.1007/s00466-006-0055-8
  13. Gao, W. (2007), "Natural frequency and mode shape analysis of structures with uncertainty", Mech. Syst. Signal Proc., 21(1): 24-39. https://doi.org/10.1016/j.ymssp.2006.05.007
  14. Kang, S.C., Koh, H.M, Choo, J.F. (2010), "An efficient response surface method using moving least squares approximation for structural reliability analysis", Probab. Eng. Mech., 35(4), 355-371.
  15. Jiang, Q. and Chen, C.H. (2003), "A numerical algorithm of fuzzy reliability", Reliab. Eng. Syst. Saf., 80(3), 299-307. https://doi.org/10.1016/S0951-8320(03)00055-3
  16. Jiang, C., Lu, G.Y., Han, X. and Liu L.X (2008), "A new reliability analysis method for uncertain structures with random and interval variables", Int. J. Machine Mater. Des., 8(1), 169-182.
  17. Madsen, H.O.(1985) "First order vs. second order reliability analysis of series structures", Struct. Saf., 7(2):207-214.
  18. Madsen, H.O., Krenk, S. and Lind, N.C. (1986), Methods of Structural Safety, Prentice-Hall, Englewood Cliffs
  19. Qiu, Z.P. (2005), Convex Method Based on Non-Probabilistic Set-Theory and its Application, National Defence Industry Press, Beijing.
  20. Schaff, J.R. and Davidson, B.D. (1997), "Life prediction methodology for composite structures", J. Compos. Mater., 31(2), 127-157.
  21. Shui-Hua Jiang, Dian-Qing Li, Chuang-Bing Zhou and Li-Min Zhang(2014), "Capabilities of stochastic response surface method and response surface method in reliability analysis", Struct. Eng. Mech., 49(1), 48-56.
  22. Tee, K.F., Khan, L.R. and Chen, H.P. (2013), "Probabilistic failure analysis of underground flexible pipes", Struct. Eng. Mech., 47(2), 167-183. https://doi.org/10.12989/sem.2013.47.2.167
  23. Tee, K.F., Li, C.Q. and Mahmoodian, M. (2011), "Prediction of time-variant probability of failure for concrete sewer pipes", Proceeding of the 12th International Conference on Durability of Building Materials and Components, Porto, Portugal, April 12-15
  24. Zhu, Z.Q., Chen, J.J., Liang Z.T. and Lin L.G. (2008), "Finite element and reliability analyses for antenna structures with the mixture of random and interval variables", Chinses High Technol. Lett., 16(6), 624-631.

Cited by

  1. Time-variant structural fuzzy reliability analysis under stochastic loads applied several times vol.55, pp.3, 2015, https://doi.org/10.12989/sem.2015.55.3.525
  2. Structural robust optimization design based on convex model vol.7, 2017, https://doi.org/10.1016/j.rinp.2017.08.013
  3. Statistical model and structural reliability analysis for onshore gas transmission pipelines vol.82, 2017, https://doi.org/10.1016/j.engfailanal.2017.08.008
  4. Reliability-based design optimization for problems with interval distribution parameters vol.55, pp.2, 2017, https://doi.org/10.1007/s00158-016-1505-3
  5. An efficient simulation method for reliability analysis of systems with expensive-to-evaluate performance functions vol.55, pp.5, 2015, https://doi.org/10.12989/sem.2015.55.5.979
  6. Reliability sensitivities with fuzzy random uncertainties using genetic algorithm vol.60, pp.3, 2016, https://doi.org/10.12989/sem.2016.60.3.413
  7. Improved Nonprobabilistic Global Optimal Solution Method and Its Application in Bridge Reliability Assessment vol.2019, pp.1687-8094, 2019, https://doi.org/10.1155/2019/8290317

Acknowledgement

Supported by : National Natural Science Foundation of China