Reliability analysis on civil engineering project based on integrated adaptive simulation annealing and gray correlation method

Xiao-ping BAI, Ya-nan LIU

PDF(319 KB)
PDF(319 KB)
Front. Struct. Civ. Eng. ›› 2016, Vol. 10 ›› Issue (4) : 462-471. DOI: 10.1007/s11709-016-0361-y
RESEARCH ARTICLE
RESEARCH ARTICLE

Reliability analysis on civil engineering project based on integrated adaptive simulation annealing and gray correlation method

Author information +
History +

Abstract

Dynamic reliability is a very important issue in reliability research. The dynamic reliability analysis for the project is still in search of domestic and international research in the exploration stage. By now, dynamic reliability research mainly concentrates on the reliability assessment; the methods mainly include dynamic fault tree, extension of event sequence diagram and Monte Carlo simulation, and et al. The paper aims to research the dynamic reliability optimization. On the basis of analysis of the four quality influence factors in the construction engineering, a method based on gray correlation degree is employed to calculate the weights of factors affecting construction process quality. Then the weights are added into the reliability improvement feasible index (RIFI). Furthermore, a novel nonlinear programming mathematic optimization model is established. In the Insight software environment, the Adaptive Simulated Annealing (ASA) algorithm is used to get a more accurate construction subsystem optimal reliability under different RIFI conditions. In addition, the relationship between construction quality and construction system reliability is analyzed, the proposed methods and detailed processing can offer a useful reference for improving the construction system quality level.

Keywords

civil engineering / dynamic reliability / grey relational degree / adaptive simulated annealing algorithm

Cite this article

Download citation ▾
Xiao-ping BAI, Ya-nan LIU. Reliability analysis on civil engineering project based on integrated adaptive simulation annealing and gray correlation method. Front. Struct. Civ. Eng., 2016, 10(4): 462‒471 https://doi.org/10.1007/s11709-016-0361-y

References

[1]
Zio E. Reliability engineering: Old problems and new challenges. Reliability Engineering & System Safety. Reliability Engineering, 2009, 94(2): 125–141
[2]
Ettefagh M M, Behkamkia D, Pedrammehr S, Asadi K. Reliability analysis of the bridge dynamic response in a stochastic vehicle-bridge interaction. KSCE journal of civil engineering, 2015, 19 (1): 220–232
[3]
Balakrishnan N, Jiang N, Tsai T R, Lio Y L, Chen D G. Reliability inference on composite dynamic systems based on burr type-XII distribution. IEEE Transactions on Reliability, 2015, 64(1): 144–153
[4]
Eryilmaz S, Bozbulut A R. An algorithmic approach to the dynamic reliability analysis of non-repairable multi-state weighted k-out-of-n: G system. Reliability Engineering & System Safety, 2014, 131(1): 61–65
[5]
Tarasov A, Delany S J, Mac Namee B. Dynamic estimation of worker reliability in crowdsourcing for regression tasks: Making it work. Expert Systems with Applications, 2014, 41(14): 6190–6210
[6]
Grigoriu M,Samorodnitsky G. Reliability of dynamic systems in random environment by extreme value theory. Probabilistic engineering mechanics, 2014, 38 (SI): 54–69
[7]
Lu N, Shi Y F, Tian M. Investigation of optimal disposition of reliability in complex network system of constructional engineering. Journal of Lanzhou University of Technology, 2002, 28(4): 108–111 (in Chinese)
[8]
Su C, Xu Y Q. Research on theory and methods of dynamic reliability modeling for complex electromechanical products. Manufacture Information Engineering of China, 2006, 35(9): 24–32
[9]
Wang C, Zhou J Z, Chang L. Research of fuzzy reliability integration analysis in Three Gorges Project Giant concrete construction system. Water Resources and Power, 2007, 25(1): 83–86
[10]
Castillo E, Mı’nguezb R, Castillo C. Sensitivity analysis in optimization and reliability problems. Reliability Engineering & System Safety, 2008, 93(12): 1788–1800
[11]
Lu W Z, Olifsson T, Lars S. A lean-agilemodel of homebuilders’ production systems. Construction Management and Economics, 2011, 29(1): 25–35
[12]
Wang Q Q, Zhang Y M, Wang Y B, LV H. Dynamic reliability analysis of complex random vibration system. Journal of Vibration Measurement & Diagnosis, 2013, 33 (4): 670–675, 727–728
[13]
Duan R X, Fan J H. Reliability evaluation of data communication system based on dynamic fault tree under epistemic uncertainty. Mathematical Problems in Engineering, 2014, 3: 1–10
[14]
Zhan X J, Jiang L Z, Pan B S. Reliability optimization of dynamic characteristic of multi-axis CNC machine tool bed. Journal of Mechanical & Electrical Engineering, 2014, 31 (3), 334–337, 353
[15]
Vu-Bac N, Lahmer T, Keitel H, Zhao J, Zhuang X, Rabczuk T. Stochastic predictions of bulk properties of amorphous polyethylene based on molecular dynamics simulations. Mechanics of Materials, 2014, 68: 70–84
[16]
Vu-Bac N, Lahmer T, Zhang Y, Zhuang X, Rabczuk T. Stochastic predictions of interfacial characteristic of polymeric nanocomposites (PNCs). Composites. Part B, Engineering, 2014, 59: 80–95
[17]
Tao R, Tam C. System reliability optimization model for construction projects via system reliability theory. Automation in Construction, 2012, 31(22): 340–347
[18]
Alias Z, Zawawi E, Yusof K, Aris N M. Determining critical success factors of project management practice, A conceptual framework. Procedia Social & Behavioral Sciences, 2014, 61–69
[19]
Vu-Bac N, Silani M, Lahmer T, Zhuang X, Rabczuk T. A unified framework for stochastic predictions of mechanical properties of polymeric nanocomposites. Computational Materials Science, 2015, 96: 520–535
[20]
Vu-Bac N, Rafiee R, Zhuang X, Lahmer T, Rabczuk T. Uncertainty quantification for multiscale modeling of polymer nanocomposites with correlated parameters. Composites. Part B, Engineering, 2015, 68: 446–464

RIGHTS & PERMISSIONS

2016 Higher Education Press and Springer-Verlag Berlin Heidelberg
AI Summary AI Mindmap
PDF(319 KB)

Accesses

Citations

Detail

Sections
Recommended

/