Finite element based improvement of a light truck design to optimize crashworthiness

Chen, D. Y.; Wang, L. M.; Wang, C. Z.; Li, Yuan; Zhang, T. Y.; Zhang, Z. Z.

doi:10.1007/s12239-015-0004-7

Cited by 28 publications

(8 citation statements)

References 13 publications

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“…The bolt between the connected parts has been simulated by using the one-dimensional (1D) rigid element integrated with the beam element. To simultaneously ensure the convergence and the computational cost of the FE simulation, the basic element size of the whole FE model has been set to be 10 mm as suggested in the published work by Chen et al 16 The whole model includes a total of 689,742 elements, containing 585,367 quadrilateral elements, 10,536 triangular elements, and around 65,439 solid elements. The number of triangular elements and tetrahedron elements in the model has been limited within 5% of the total number to ensure the mesh quality.…”

Section: Full-scale Fe Modelingmentioning

confidence: 99%

Crashworthiness analysis and multi-objective optimization of a commercial vehicle frame: A mixed meta-modeling-based method

Wang

Wang³

et al. 2018

Advances in Mechanical Engineering

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In this study, a mixed meta-modeling-based optimization method has been proposed and applied to a commercial vehicle for crashworthiness design subjected to the frontal crash. A full-scale finite element model of the commercial vehicle has been built and validated by a crash test. The front frame parts have been separated to build a sub-model for crashworthiness optimization. Sensitivity analysis has been performed to find the design factors contributing most to crash performance by using design of experiments. With the reduced dimensions of design space, meta-models of crashworthiness criteria (i.e. specific energy absorption, peak crush force, and peak crush acceleration) have been built by using polynomial response surface and radial basis function networks, respectively. The meta-models with higher global fidelity in design space have been adopted to formulate the multi-objective optimization problem of crashworthiness design, which has then been solved by using Non-dominated Sorting Genetic Algorithm-II. The obtained Pareto front has been discussed and validated with that achieved by Strength Pareto Evolutionary Algorithm 2. The normalized optimal solution from the Pareto front has resulted in 11.15% increase in specific energy absorption and 13.2% decrease in peak crush force for the frame and has led to an obvious improvement in occupant protection and energy absorption for the whole vehicle, verifying that the proposed method is effective for vehicle crashworthiness optimization.

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Section: Full-scale Fe Modelingmentioning

confidence: 99%

Crashworthiness analysis and multi-objective optimization of a commercial vehicle frame: A mixed meta-modeling-based method

Wang

Wang³

et al. 2018

Advances in Mechanical Engineering

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“…These design problems usually have the typical characteristics of complexity and uncertainty. Many design approaches have been introduced to deal with such difficulties and some papers especially explained the vehicle and its parts design processes (Kim et al, 2014;Chen et al, 2015;Ma et al, 2013, Sahoo et al, 2015Yoon et al, 2013). The methodical design approach (MDA) has also been used to design engineering products recommending various special systematic methods for designers.…”

Section: Introductionmentioning

confidence: 99%

The design process of the complex Special Utility Vehicle using the methodical design approach

Çavdar

Börklü

Çavdar

et al. 2019

JAMDSM

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This paper describes the designing and manufacturing process of a complex special utility vehicle (SUV) using the methodical design approach for which the basics were explained decades ago in Germany. The application steps of the design methodology with comprehensive data are clearly outlined and the experiences gained during the project along with the authors' experiences in design research and design practice over 25 years are generously shared. This paper contributes to the methodical approach laid by Pahl & Beitz with an industrial example proving its applicability in real engineering design applications. The proposed solutions for difficulties encountered in the process are especially valuable and applicable for SMEs (small and medium-sized enterprises) in the field. Such details are reported with comprehensive discussions in this paper.

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“…The Grid applications also have diverse resource requirements [ 11 – 13 ]. For example, automotive crash simulation analysis needs multidisciplinary finite element solver RADIOSS and pre-processing software HyperMesh, and CPU+GPU coordinated parallel computing [ 11 , 12 ]. These application requirements are not provided by all Grid computing centers.…”

Section: Introductionmentioning

confidence: 99%

Application-aware deadline constraint job scheduling mechanism on large-scale computational grid

Tang

Liao

2018

PLoS ONE

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Recently, computational Grids have proven to be a good solution for processing large-scale, computation intensive problems. However, the heterogeneity, dynamics of resources and diversity of applications requirements have always been important factors affecting their performance. In response to these challenges, this work first builds a Grid job scheduling architecture that can dynamically monitor Grid computing center resources and make corresponding scheduling decisions. Second, a Grid job model is proposed to describe the application requirements. Third, this paper studies the characteristics of commercial interconnection networks used in Grids and forecast job transmission time. Fourth, this paper proposes an application-aware job scheduling mechanism (AJSM) that includes periodic scheduling flow and a heuristic application-aware deadline constraint job scheduling algorithm. The rigorous performance evaluation results clearly demonstrate that the proposed application-aware job scheduling mechanism can successful schedule more Grid jobs than the existing algorithms. For successful scheduled jobs, our proposed AJSM method is the best algorithm for job average processing time and makespan.

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Finite element based improvement of a light truck design to optimize crashworthiness

Cited by 28 publications

References 13 publications

Crashworthiness analysis and multi-objective optimization of a commercial vehicle frame: A mixed meta-modeling-based method

Crashworthiness analysis and multi-objective optimization of a commercial vehicle frame: A mixed meta-modeling-based method

The design process of the complex Special Utility Vehicle using the methodical design approach

Application-aware deadline constraint job scheduling mechanism on large-scale computational grid

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