Improving pedestrian safety via the optimization of composite hood structures for automobiles based on the equivalent static load method

Kim, Dong-Hyun; Jung, Ku-Hyun; Kim, Dug-Joong; Park, Sung-Hyeon; Kim, Do-Hyoung; Lim, Jae-Yong; Nam, Byeung-Gun; Kim, Kwang Ho

doi:10.1016/j.compstruct.2017.06.016

Cited by 34 publications

(12 citation statements)

References 20 publications

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“…In TO of hood frames, which we target in this paper, both static and crash load cases play an important role [40]. Therefore, a direct use of gradient-based techniques for such a multidisciplinary TO is not possible due to the noisiness and discontinuous character of the optimization criteria.…”

Section: Structural Topology Optimizationmentioning

confidence: 99%

CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications

Bujny

Ramnath

Shah

et al. 2022

IEEE Trans. Evol. Computat.

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Large-scale, high-quality data sets are central to the development of advanced machine learning techniques that increase the effectiveness of existing optimization methods or even inspire novel ones. Especially in the engineering domain such high quality data sets are rare due to confidentiality concerns and generation costs, be it computational or manual efforts. We therefore introduce the OSU-Honda Automobile Hood Dataset (CarHoods10k), an industry-grade 3D vehicle hood data set of over 10000 shapes along with mechanical performance data that were validated against real-world hood designs by industry experts. CarHoods10k offers researchers and practitioners the unique opportunity to develop novel methods on realistic data with relevance to real-world vehicle design. To illustrating central use cases, we first apply methods from geometric deep learning to learn a compact latent representation for design space exploration. Second, we use machine learning models to predict mechanical hood performance from the learned latent representation. We thus demonstrate the effectiveness of machine learning for building metamodels, which are used in design optimization whenever possible to replace costly engineering simulations. Third, we integrate CarHoods10k in a topology optimization approach based on evolutionary algorithms to demonstrate its capability to search for high-performing structures, while maintaining manufacturability constraints.

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Section: Structural Topology Optimizationmentioning

confidence: 99%

CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications

Bujny

Ramnath

Shah

et al. 2022

IEEE Trans. Evol. Computat.

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“…The nonlinear dynamic response optimization can be converted to an iterative "linear optimization ↔ nonlinear analysis" process by using the ESL. Many researchers carried out crashworthiness design of automobile frontal structure [20], roof structure [21], front hood panel [22][23][24], and B-pillar [25]. The ESL method bring convenience to solve topometry.…”

Section: Introductionmentioning

confidence: 99%

Topometry Optimization of Energy Absorbing Structure through Targeting Force-Displacement Method considering Tailor Rolled Blank Process

Wang

Lin

et al. 2022

International Journal of Aerospace Engineering

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Inspired by topometry optimization, this work proposed a new design approach that mixed of targeting force-displacement (TFD) method and tailor rolled blank (TRB) process for thin-walled energy absorption structures, which has vast applied prospects in the aerospace and automotive industries. This method not only overcomes manufacturing difficulty caused by the TFD method based on topometry optimization but also provides a new idea for TRB energy absorption structure. The optimized results can be transferred to the computer aided design environment without additional postprocessing. Firstly, a uniform thickness constraint is introduced to make the designed structure have constant thickness distribution along desired direction; topometry optimization is carried out to use TFD method. Secondly, a method that can automatically divide the design domain is developed. The adjacent elements with smaller thickness differences are merged to form TRB subdomains based on the optimization results of forestep, and the TFD method is used again. Finally, TRB finite element modeling codes is developed. According to the second step, modeling of the transition zone is added to finally form the TRB structure that meets the requirements of manufacturing. This method is used to optimize the crashworthiness of the thin-walled tube under axial and oblique loading. Numerical results demonstrate the effectiveness of this method. Therefore, this method can be used to design high-efficiency energy absorber on aircraft or automobile, such as the strut of aircraft and energy absorption box of automobile.

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“…In the latest research studies, carbon fiber-reinforced plastic (CFRP) composites have been increasingly utilized instead of conventional metallic materials in the automotive industry due to their advantageous properties like high strength, high stiffness, lightweight, and excellent energy absorption [3][4][5][6][7][8]. Kiran et al proposed the method of using composite instead of metallic materials in automobile chassis and analyzed the static structure of equivalent stress and displacement of composite structural parts [9].…”

Section: Introductionmentioning

confidence: 99%

“…Kiran et al proposed the method of using composite instead of metallic materials in automobile chassis and analyzed the static structure of equivalent stress and displacement of composite structural parts [9]. Kim et al designed carbon fiber-reinforced composites and hybrid fiberglass-reinforced composite hood by finite element analysis and proved that composite hood had better performance in crashworthiness and weight reduction than traditional steel and aluminum hood [4].…”

Section: Introductionmentioning

confidence: 99%

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Multiobjective Optimization of Carbon Fiber‐Reinforced Plastic Composite Bumper Based on Adaptive Genetic Algorithm

Gao

Liang

Shi

et al. 2019

Mathematical Problems in Engineering

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Genetic algorithm (GA) is a common optimization technique that has two fatal limitations: low convergence speed and premature convergence to the local optimum. As an effective method to solve these drawbacks, an adaptive genetic algorithm (AGA) considering adaptive crossover and mutation operators is proposed in this paper. Verified by two test functions, AGA shows higher convergence speed and stronger ability to search the global optimal solutions than GA. To meet the crashworthiness and lightweight demands of automotive bumper design, CFRP material is employed in the bumper beam instead of traditional aluminum. Then, a multiobjective optimization procedure incorporating AGA and the Kriging surrogate model is developed to find the optimal stacking angle sequence of CFRP. Compared with the conventional aluminum bumper, the optimized CFRP bumper exhibits better crashworthiness and achieves 43.19% weight reduction.

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Improving pedestrian safety via the optimization of composite hood structures for automobiles based on the equivalent static load method

Cited by 34 publications

References 20 publications

CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications

CarHoods10k: An Industry-Grade Data Set for Representation Learning and Design Optimization in Engineering Applications

Topometry Optimization of Energy Absorbing Structure through Targeting Force-Displacement Method considering Tailor Rolled Blank Process

Multiobjective Optimization of Carbon Fiber‐Reinforced Plastic Composite Bumper Based on Adaptive Genetic Algorithm

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