![]() Radial basis neural networks showed the best overall performance in global exploration characteristics as well as tendency to find the approximate optimal solution for the majority of tested problems. The surrogate models were analyzed in terms of global exploration (accuracy over the domain space) and local exploitation (ease of finding the global optimum point). The important findings are illustrated using Box-plots. The three surrogate models, namely, response surface approximation, Kriging, and radial basis neural networks were tested. The analysis was carried out for two types of problems: (1) thermal-fluid design problems (optimizations of convergent-divergent micromixer coupled with pulsatile flow and boot-shaped ribs), and (2) analytical test functions (six-hump camel back, Branin-Hoo, Hartman 3, and Hartman 6 functions). The present study aimed at evaluating the performance characteristics of various surrogate models depending on the Latin hypercube sampling (LHS) procedure (sample size and spatial distribution) for a diverse set of optimization problems. The exploration/exploitation properties of surrogate models depend on the size and distribution of design points in the chosen design space. Yamada, Y.: Materials for Springs.Latin hypercube sampling is widely used design-of-experiment technique to select design points for simulation which are then used to construct a surrogate model. Svensson, T.: Prediction uncertainties at variable amplitude fatigue. Stephens, R.I., Fatemi, A., Stephens, R.P., Fuchs, H.O.: Metal Fatigue in Engineering, 2nd edn. Reimpell, J., Stoll, H., Betzler, J.W.: The Automotive Chassis: Engineering Principles, 2nd edn. Ramberg, W., Osgood, W.R.: NACA Technical Note No. Olsson, A., Sandberg, G., Dahlblom, O.: On Latin hypercube sampling for structural reliability analysis. Myers, R.H., Montgomery, D.C.: Response Surface Methodology, 2nd edn. Society of Automotive Engineers, Warrandale (1968) Morrow, J.: Fatigue Design Handbook Advances in Engineering. Montgomery, D.C.: Design and Analysis of Experiments. ![]() McKay, M.D., Conover, W.J., Beckman, R.J.: A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Vieweg & Teubner Verlag, Springer Fachmedien Wiesbaden GmbH, Wiesbaden (2011) Heißing, B., Ersoy, M.: Chassis Handbook, 1st edn. 232(10), 1838–1850 (2018b)īoardman, B.: Crack initiation fatigue-data, analysis, trends and estimation. 94(5–8), 2125–2136 (2018a)Ītig, A., Ben Sghaier, R., Seddik, R., Fathallah, R.: A simple analytical bending stress model of parabolic leaf spring. 33, 575–594 (2010)Ītig, A., Sghaier, R.B., Seddik, R., Fathallah, R.: Probabilistic methodology for predicting the dispersion of residual stresses and Almen intensity considering shot peening process uncertainties. īen Sghaier, R., Bouraoui, C., Fathallah, R., Degallaix, G.: Probabilistic prediction of high cycle fatigue reliability of high strength steel Butt-welded joints. The effects of probabilistic variables on the fatigue life results have been studied in order to enhance the fatigue behavior of parabolic leaf spring.Ītig, A., Ben Sghaier, R., Seddik, R., Fathallah, R.: Reliability-based high cycle fatigue design approach of parabolic leaf spring. The number of cycles to failure distribution has been presented and characterized. The dispersion of geometrical dimensions, materials properties and cyclic loading parameters have been taken into consideration. The proposed approach has been applied on a finite element and a response surface model of parabolic leaf spring. The strain based approach and Morrow fatigue criterion have been used to compute the number of cycles to failure. In this work, a stochastic approach based on Latin hypercube simulation method has been performed to predict the fatigue life of parabolic leaf spring. Nevertheless, the estimation of fatigue life is usually affected by many inherent uncertainties which must be considered in a fatigue design approach. Therefore, fatigue life assessment and prediction represent an important aspect during parabolic leaf spring design stage. Fatigue phenomenon is one of the main causes of parabolic leaf spring failure.
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