Time-dependent concurrent reliability-based design optimization integrating experiment-based model validation
- 251 Downloads
This paper presents new time-dependent concurrent reliability-based design optimization methods for improving the confidence of design results with reduced experimental cost and increased computational efficiency. The sensitive time-dependent design parameters are first selected through the developed functional Analysis of Variance. The sensitive design parameters are then validated by constructing the experimental error function based on experimental data, and the function of the mean between experiments and computer models. The sub-domains are next determined, and the time-dependent concurrent reliability-based design optimization is finally constructed and solved based on the MCS method. A case study is used to illustrate and testify our proposed methods.
KeywordsTime-dependent sensitivity analysis Design optimization Model validation Concurrent design Experimental data
This work was supported by the National Natural Science Foundation of China under the Contract No. 11472075 and 51405067.
- Hills RG, Truncano TG, “Statistical validation of engineering and scientific models: a maximum likelihood based metric,” SAND2002–1783, Sandia National Laboratories, Albuquerque, 2002Google Scholar
- Hu Z, Du X (2013) A sampling approach to extreme values of stochastic processes for reliability analysis. ASME J Mech Design 135(7):1–8Google Scholar
- Wang Z, Huang H-Z, Liu Y (2010b) A unified framework for integrated optimization under uncertainty. ASME J Mech Design 132(5):051008.1–051008.8Google Scholar
- Wang Z, Zhang X, Huang H-Z, Mourelatos ZP (2016) A simulation method to estimate two types of time-varying failure rate of dynamic systems. ASME J Mech Design 128(12):121404.1–121404.10Google Scholar
- Wang H, Chen L, Li E (2017a) Time dependent sheet metal forming optimization by using Gaussian process assisted firefly algorithm. Int J Mater Form. https://doi.org/10.1007/s12289-017-1352-9
- Wang H, Chen L, Ye F, Chen L (2017b) Global sensitivity analysis for fiber reinforced composite fiber path based on D-MORPH-HDMR algorithm. Struct Multidiscip O 56(3):697–712Google Scholar
- Xi Z, Fu F, Yang RJ (2012) Model validation metric and model bias characterization for dynamic system responses under uncertainty. ASME 2012 International Design Engineering Technical Conference & Computers and Information in Engineering Conference, Chicago, IL, USAGoogle Scholar