Parametric modeling and multiobjective crashworthiness design optimization of a new front longitudinal beam
Structural and Multidisciplinary Optimization, ISSN: 1615-1488, Vol: 59, Issue: 5, Page: 1789-1812
2019
- 48Citations
- 19Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The front longitudinal beam (FLB) is the most important energy-absorbing and crashing force–transmitting structure of a vehicle under front-impact collision. For better weight reduction and crashworthiness of the FLB, a new structure, variable rolled blank–variable cross-sectional shape FLB (VRB-VCS FLB), is proposed. It has both the continuous variation of thickness and variable cross-sectional shape in space. As the thickness distribution and cross-sectional shape change continuously, the proposed structure evolves into three distinct forms, i.e., the uniform-thickness FLB, variable rolled blank FLB, and variable cross-sectional shape FLB. However, literature on parametric modeling and crashworthiness design optimization of the VRB-VCS FLB is very limited. This paper proposes a parametric modeling method of VRB-VCS FLB with manufacturing constraints. Multiobjective crashworthiness design optimization is performed to explore the lightweightness and crashworthiness performance of the VRB-VCS FLB. Firstly, thickness distribution and cross-sectional shape parameters are defined. Secondly, local parametric subsystem front-impact model is established to balance accuracy and efficiency. Thirdly, a multiobjective optimization model of VRB-VCS FLB is constructed. Finally, a fully automated design of experiment platform is established to improve the data collection efficiency, and epsilon-support vector regression technique and non-dominated sorting genetic algorithm II are utilized to search the Pareto optimal frontier. The numerical results show that the lightweightness and crashworthiness of the VRB-VCS FLB are significantly improved when compared with the uniform-thickness FLB.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85056894811&origin=inward; http://dx.doi.org/10.1007/s00158-018-2134-9; http://link.springer.com/10.1007/s00158-018-2134-9; http://link.springer.com/content/pdf/10.1007/s00158-018-2134-9.pdf; http://link.springer.com/article/10.1007/s00158-018-2134-9/fulltext.html; https://dx.doi.org/10.1007/s00158-018-2134-9; https://link.springer.com/article/10.1007/s00158-018-2134-9
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know