Crashworthiness design of foam-filled bitubal structures with uncertainty

Fang, Jianguang; Gao, Yunkai; Sun, Guangyong; Zhang, Yuting; Li, Qing

doi:10.1016/j.ijnonlinmec.2014.08.005

Cited by 77 publications

(30 citation statements)

References 67 publications

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“…Several works, [34,36,38,[65][66][67][68][69], investigated two indicators of crashworthiness that could be optimized simultaneously. The main purpose of this study is to optimize aluminium foamfilled double tubes for maximum crashworthiness performance i. e., the maximum SEA and the minimum PCF, under axial and angle impact loadings.…”

Section: Multi Objective Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Optimization of foam-filled double circular tubes under axial and oblique impact loading conditions

Djamaluddin

Abdullah

Ariffin

et al. 2015

Thin-Walled Structures

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Section: Multi Objective Optimizationmentioning

confidence: 99%

“…To measure the degree of approximation of the radial basis functions metamodel to the FEA results, the Relative Error (RE) [68] can be evaluated as:…”

Section: Model Validationmentioning

confidence: 99%

Optimization of foam-filled double circular tubes under axial and oblique impact loading conditions

Djamaluddin

Abdullah

Ariffin

et al. 2015

Thin-Walled Structures

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“…The surrogate model is to construct an approximate function from a series of sampling points, which are typically determined using design of experiment (DoE) methods. In this study, 100 sets of sampling data were generated using the optimal latin hypercube sampling (OLHS) approach [16,[36][37][38][39][40][41].…”

Section: Definition Of Optimization Problemmentioning

confidence: 99%

Fatigue optimization with combined ensembles of surrogate modeling for a truck cab

et al. 2014

Self Cite

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In this study, we propose the ensembles of surrogates for an industrial application of fatigue optimization problem that aims to maximize a truck cab's fatigue life. After validating the numerical model, different ensembles of surrogates comprised polynomial response surface (PRS), radial basis function (RBF) and Kriging (KRG) models are established to approximate the fatigue life function. A hybrid PSO algorithm, which integrates the standard PSO with sequential quadratic programming (SQP), is implemented here to seek a quasiglobal optimum. Compared with individual surrogates, the ensembles of surrogates can attain more competent optima and yield a smaller surrogate error at the optimal point. Moreover, the hybrid PSO technique proves to search the better optima than the standard PSO in the fatigue optimization problem considered. Finally, it is found that a more accurate surrogate model may not necessarily produce a better optimum for the ensembles of surrogates, thus multiple ensembles are recommended without increasing much extra computational cost.

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“…[1] To protect passengers from injuries when collisions occur, various energy-absorbing structures have been designed and installed in unmanned areas of railcars. [2,3] Due to their significant advantages, thin-walled tubes are widely used as impact energy-absorbing structures. Multiple experiments about deformation patterns of circular tubes have been carried out, under axial and lateral loading.…”

Section: Introductionmentioning

confidence: 99%

Structural Optimum Design of a Railcar Coupler Energy Absorbing Device

Li¹,

Yan²,

Wen³

et al. 2017

dtetr

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Abstract. In this paper, we carried out a structural optimization of an railcar coupler energy absorbing device. we established a finite element (FE) model and validated it by experimental results. We used a central composite design (CCD) and Hammersley design of experiments (DOE) to take samples for the variables. Based on these samples, we built an approximation model with the moving least squares method (MLAM). The maximum error percentage of the model was 2.30%. The main effect analysis indicated that the thickness T had the more significant effect on the average mean force (Favg) and the specific energy absorption (SEA). Considering the average mean force, fracture and buckling of the structure as constraints, we carried out parameter optimization using the global response surface method (GRSM) to gain a higher SEA. Finally, we obtained the optimum parameters (T = 7.72 mm, ɑ = 29.34º) with the SEA value of 35.28 kJ/kg. The value of SEA increased by 56.18%.

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Crashworthiness design of foam-filled bitubal structures with uncertainty

Cited by 77 publications

References 67 publications

Optimization of foam-filled double circular tubes under axial and oblique impact loading conditions

Optimization of foam-filled double circular tubes under axial and oblique impact loading conditions

Fatigue optimization with combined ensembles of surrogate modeling for a truck cab

Structural Optimum Design of a Railcar Coupler Energy Absorbing Device

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