Aiguo Cheng

A mass-redistributed finite element method (MR-FEM) for acoustic problems using triangular mesh

The accuracy of numerical results using standard finite element method (FEM) in acoustic problems will deteriorate with increasing frequency due to the dispersion error. Such dispersion error depends on the balance between the stiffness and mass of discretization equation systems. This paper reports an improved finite element method (FEM) for solving acoustic problems by re-distributing the mass in the mass matrix to tune the balance, aiming to minimize the dispersion errors. This is done by shifting the integration point locations when computing the entries of the mass matrix, while ensuring the mass conservation. The new method is verified through the detailed numerical error analysis, and a strategy is also proposed for the best mass redistribution in terms of minimizing dispersion error. The relative dispersion error of present mass-redistributed finite element method (MR-FEM) is found to be much smaller than the FEM solution, in both theoretical prediction and numerical examination. The present MR-FEM works well by using the linear triangular elements that can be generated automatically, which enables automation in computation and saving computational cost in mesh generation. Numerical examples demonstrate the advantages of MR-FEM, in comparison with the standard FEM using the same triangular meshes and quadrilateral meshes.

Multi-objective system reliability-based optimization method for design of a fully parametric concept car body

ABSTRACT This article investigates multi-objective optimization under reliability constraints with applications in vehicle structural design. To improve computational efficiency, an improved multi-objective system reliability-based design optimization (MOSRBDO) method is developed, and used to explore the lightweight and high-performance design of a concept car body under uncertainty. A parametric model knowledge base is established, followed by the construction of a fully parametric concept car body of a multi-purpose vehicle (FPCCB-MPV) based on the knowledge base. The structural shape, gauge and topology optimization are then designed on the basis of FPCCB-MPV. The numerical implementation of MOSRBDO employs the double-loop method with design optimization in the outer loop and system reliability analysis in the inner loop. Multi-objective particle swarm optimization is used as the outer loop optimization solver. An improved multi-modal radial-based importance sampling (MRBIS) method is utilized as the system reliability solver for multi-constraint analysis in the inner loop. The accuracy and efficiency of the MRBIS method are demonstrated on three widely used test problems. In conclusion, MOSRBDO has been successfully applied for the design of a full parametric concept car body. The results show that the improved MOSRBDO method is more effective and efficient than the traditional MOSRBDO while achieving the same accuracy, and that the optimized body-in-white structure signifies a noticeable improvement from the baseline model.

Bending analysis and design optimisation of tailor-rolled blank thin-walled structures with top-hat sections

ABSTRACT The purpose of this paper is to provide efficient lightweight design for improving the loading carrying efficiency and energy absorption capability of tailor-rolled blank thin-walled structure with top-hat section (TRB-TH) under transverse loading. First, a new finite-element (FE) modelling method for the TRB-TH structure is proposed. The FE model is validated by performing quasi-static bending tests on two kinds of typical specimens. Second, the validated FE model is used to study the loading carrying efficiency and energy absorption capability of TRB-TH structures with variations in the thicknesses of constant thickness zone, lengths and positions of thickness transition zone by using global sensitivity analysis. Finally, to determine the optimal thickness distribution, multiobjective optimisation design is performed by integrating response surface method and non-dominated sorting genetic algorithm (NSGA-II) algorithm. The results have demonstrated that the TRB-TH structures can not only produce much better Pareto solutions than the traditional designed uniform thickness (UF-TH) counterparts, but also provide a better balance between lightweight and crashworthiness of energy absorbers simultaneously. The proposed approach can provide some useful guidance for designing the TRB-TH energy absorbers of vehicle body.

Design optimization of tailor-rolled blank thin-walled structures based on -support vector regression technique and genetic algorithm

ABSTRACT Tailor-rolled blank thin-walled (TRB-TH) structures have become important vehicle components owing to their advantages of light weight and crashworthiness. The purpose of this article is to provide an efficient lightweight design for improving the energy-absorbing capability of TRB-TH structures under dynamic loading. A finite element (FE) model for TRB-TH structures is established and validated by performing a dynamic axial crash test. Different material properties for individual parts with different thicknesses are considered in the FE model. Then, a multi-objective crashworthiness design of the TRB-TH structure is constructed based on the -support vector regression (-SVR) technique and non-dominated sorting genetic algorithm-II. The key parameters (C, and σ) are optimized to further improve the predictive accuracy of -SVR under limited sample points. Finally, the technique for order preference by similarity to the ideal solution method is used to rank the solutions in Pareto-optimal frontiers and find the best compromise optima. The results demonstrate that the light weight and crashworthiness performance of the optimized TRB-TH structures are superior to their uniform thickness counterparts. The proposed approach provides useful guidance for designing TRB-TH energy absorbers for vehicle bodies.

Design optimisation of composite bumper beam with variable cross-sections for automotive vehicle

ABSTRACT Considering vehicle crash safety, gas emission and the improvement in the energy efficiency, carbon fiber reinforced plastic (CFRP) composite materials have been increasingly used in automotive applications. Bumper beam, as a main structural component of automobile bumper subsystem, is expected to protect occupants and its nearby components. It is an effective way to develop the bumper beam using CFRP to meet higher requirements of crash safety and lightweight. In this study, a stiffness degraded model is proposed to predict low-velocity impact behavior of CFRP bumper beam under two different loading conditions. Based on the simulation results, a novel design scheme of CFRP bumper beam with variable cross-sections is proposed to further improve material utilization. Finally, an optimization procedure incorporating the RBF modeling technique and NSGA-II algorithm was implemented to obtain the multi-objective optimal design. The results yielded from the optimization demonstrate that the optimized bumper beam with variable cross-sections is superior to its uniform counterpart in lightweight and crashworthiness and consequently is recommended as a better approach to replace the conventional metallic bumper beam.

The artificial tree (AT) algorithm

Bionic intelligence algorithms have many advantages compared with traditional optimization algorithms. In this paper, inspired by the growth law of trees, a new bionic algorithm, named artificial tree (AT) algorithm is developed. In the proposed AT, the branch position is considered as the design variable. In addition, the branch is the solution, and the branch thickness is the indicator of the solution. The computing process of AT is achieved by simulating the transport of organic matters and the update of tree branches. The comparative analysis using thirty typical benchmark problems between AT algorithm and some well-known bionic intelligent methods is also performed. Based on numerical results, AT is found to be very effective in dealing with various problems. Display Omitted