Volume 4 Issue 3
Oct.  2011
Turn off MathJax
Article Contents
Li-ping WANG, Yan-ke ZHANG, Chang-ming JI, Ji-qing LI. 2011: Risk calculation method for complex engineering system. Water Science and Engineering, 4(3): 345-355. doi: 10.3882/j.issn.1674-2370.2011.03.010
Citation: Li-ping WANG, Yan-ke ZHANG, Chang-ming JI, Ji-qing LI. 2011: Risk calculation method for complex engineering system. Water Science and Engineering, 4(3): 345-355. doi: 10.3882/j.issn.1674-2370.2011.03.010

Risk calculation method for complex engineering system

doi: 10.3882/j.issn.1674-2370.2011.03.010
Funds:  This work was supported by the National Water Pollution Control and Management Technology Major Projects (Grant No. 2009ZX07423-001), the National Natural Science Foundation of China (Grants No. 51179069 and 40971300), and the Fundamental Research Funds for the Central Universities (Grants No. 10QX43, 09MG16, and 10QG23).
More Information
  • Corresponding author: Yan-ke ZHANG
  • Received Date: 2010-10-15
  • Rev Recd Date: 2011-01-18
  • This paper presents a rapid and simple risk calculation method for large and complex engineering systems, the simulated maximum entropy method (SMEM), which is based on integration of the advantages of the Monte Carlo and maximum entropy methods, thus avoiding the shortcoming of the slow convergence rate of the Monte Carlo method in risk calculation. Application of SMEM in the calculation of reservoir flood discharge risk shows that this method can make full use of the known information under the same conditions and obtain the corresponding probability distribution and the risk value. It not only greatly improves the speed, compared with the Monte Carlo method, but also provides a new approach for the risk calculation in large and complex engineering systems.

     

  • loading
  • Cai, J., Tan, K. S., Weng, C. G., and Zhang, Y. 2008. Optimal reinsurance under VaR and CTE risk measures. Insurance: Mathematics and Economics, 43(1), 185-196. [doi: 10.1016/j.insmatheco.2008.05.011]
    Coleman, A. L., and Miglior, S. 2008. Risk factors for glaucoma onset and progression. Survey of Ophthalmology, 53(s6), 3-10. [doi: 10.1016/j.survophthal.2008.08.006]
    Feng, P., Xu, X. G., Wen, T. F., and Zheng, P. 2009. Risk analysis of researvoir operation with considering flood forecast error. Journal of Hydroelectric Engineering, 28(3), 47-51. (in Chinese)
    Huang, B. Q., and Du, X. P. 2008. Probabilistic uncertainty analysis by mean-value first order Saddlepoint approximation. Reliability Engineering and System Safety, 93(2), 325-336. [doi:10.1016/j.ress.2006.   10.021]
    Kennedy, C. R., and Mortimer, D. 2007. Risk management in IVF. Best Practice and Research: Clinical Obstetrics and Gynaecology, 21(4), 691-712. [doi: 10.1016/j.bpobgyn.2007.02.009]
    Khadam, I. M., and Kaluarachchi, J. J. 2003. Multi-criteria decision analysis with probabilistic risk assessment for the management of contaminated ground water. Environmental Impact Assessment Review, 23(6), 683-721. [ doi: 10.1016/S0195-9255(03)00117-3]
    Mailhot, A., and Villeneuve, J. P. 2003. Mean-value second-order uncertainty analysis method: Application to water quality modelling. Advances in Water Resources, 26(5), 491-499.  [doi:10.1016/S0309-1708(03) 00006-X]
    Mo, C. X., Liu, F. G., Yu, M., Ma, R. Y., and Sun, G. K. 2008. Risk analysis for earth dam overtopping. Water Science and Engineering, 1(2), 76-87. [doi: 10.3882/j.issn.1674-2370.2008.02.008]
    Ni, F. Q., Liu, G. D., Tan, Y. S., and Deng, Y. 2010. Spatial variation of health risk of groundwater for drinking water supply in Mingshan County, Ya’an City, China. Water Science and Engineering, 3(4), 454-466. [doi: 10.3882/j.issn.1674-2370.2010.04.008]
    Pike, R. H., and Ho, S. S. M. 1991. Risk analysis in capital budgeting: Barriers and benefits. Omega, 19(4), 235-245. [doi: 10.1016/0305-0483(91)90042-R]
    Planas, E., Arnaldos, J., Silvetti, B., Vallée, A., and Casal, J. 2006. A risk severity index for industrial plants and sites. Journal of Hazardous Materials, 130(3), 242-250. [doi: 10.1016/j.jhazmat.2005.07.015]
    Siddall, J. N. 1983. Probabilistic Engineering Design: Principles and Applications. New York: Marcel  Dekker, Inc.
    Smid, J. H., Verloo, D., Barker, G. C., and Havelaar, A. H. 2010. Strengths and weaknesses of Monte Carlo simulation models and Bayesian belief networks in microbial risk assessment. International Journal of Food Microbiology, 139(s1), 57-63. [ doi: 10.1016/j.ijfoodmicro.2009.12.015]
    Wang, D., and Zhu, Y. S. 2002. Review and expectation of application of risk analysis to water resource systems. Journal of Hohai University (Natural Sciences), 30(2), 71-77. (in Chinese)
    Xi, Q. Y. 2006. The Study of Flood Safety Risk Rate Model and Flood Control Standard of Reservoirs (Group). Ph. D. Dissertation. Xi’an: Xi’an University of Technology. (in Chinese)
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (2157) PDF downloads(2687) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return