Crashworthiness design for functionally graded foam-filled bumper beam. (July 2015)

• Record Type: Journal Article
• Authors: Xiao, Zhi; Fang, Jianguang; Sun, Guangyong; Li, Qing
• Is Part Of: Advances in engineering software. Volume 85(2015)
• Page Start: 81
• Page End: 95
• Publication Date: 2015-07
• Subjects: Bumper beam -- Functionally graded foam (FGF) -- Crashworthiness -- Energy absorption -- Multiobjective optimization -- Kriging model; Computer-aided engineering -- Periodicals; Engineering -- Computer programs -- Periodicals; Engineering -- Software -- Periodicals; Periodicals; 620.0028553
• DOI: 10.1016/j.advengsoft.2015.03.005
• Languages: English
• ISSNs: 0965-9978

Abstract

Highlights: Presented a novel bumper beam filled with functionally graded foam (FGF). Conducted the experimental validation of FGF bumper beam at both component and full vehicle levels. Performed a parametric study of FGF bumper beam. Performed a multiobjective crashworthiness optimization for FGF bumper beam. Abstract: Automotive bumper beam is an important component to protect passenger and vehicle from injury and damage induced by severe collapse. Recent studies showed that foam-filled structures have significant advantages in light weight and high energy absorption. In this paper, a novel bumper beam filled with functionally graded foam (FGF) is considered here to explore its crashworthiness. To validate the FGF bumper beam model, the experiments at both component and full vehicle levels are conducted. Parametric study shows that gradient exponential parameter m that controls the variation of foam density has significant effect on bumper beam's crashworthiness; and the crashworthiness of FGF-filled bumper beam is found much better than that of uniform foam (UF) filled and hollow bumper beam. The multiobjective optimization of FGF-filled bumper beam is also performed by considering specific energy absorption ( SEA ) and peak impact force as the design objectives, and the wall thickness t, foam densities ρf 1 and ρf 2 (foam densities at the end and at mid cross section, respectively) and gradient exponential parameter m as design variables. The Kriging surrogate modeling technique and multiobjective particle swarm optimization (MOPSO) algorithm were implemented to optimize the FGF-filled bumper beam. The optimized FGF-filled bumper beam is of great advantages and it can avoid the harmful local bending behavior and absorb more energy than UF filled and hollow bumper beam. Finally, the optimized FGF-filled bumper beam is installed to a passenger car model, and the results demonstrate that the FGF-filled bumper beam ensures the crashworthiness performance of the passenger car while reduces weight about 14.4% compared with baseline bumper beam.