薄壁管抗撞性能的多目标结构优化

以交通工具中部分锥形薄壁方管的安全装置作为研究对象,建立以薄壁管在碰撞过程中吸收能量最大化,比吸能最大化和初始碰撞力峰值最小化为多目标的优化问题.用锥形部分的几何参数作为设计变量,在保证不降低薄壁管吸能能力的情况下,通过对其结构的优化达到初始碰撞力峰值最小化的目的.论文采用有限元软件LS-DYNA得到不同几何参数模型的碰撞信息,用响应面法构造近似函数,同时引入权系数以表征各个目标在优化问题中的重要程度,并采用理想点法求解多目标优化问题,分析了锥形薄壁方管各几何参数对结构的能量吸收、比吸能和初始碰撞力峰值的影响,最终得到了给定权系数下的最优模型.     

汽车前保险杠缓冲吸能结构低速碰撞仿真分析

在低速碰撞中对某车型的汽车保险杠进行仿真分析,对保险杠模型进行简化,利用HyperMesh建立有限元模型,再提交给LS-DYNA进行计算,使用HyperView对碰撞结果进行处理得到相关响应参数,并对响应参数进行结果分析,进而确定在汽车保险杠发生低速碰撞时其最主要吸能的部件以及吸能部位的响应特性,为保险杠设计提供理论基础。     

基于Isight的仪表板横梁优化

在汽车仪表板横梁(Cross Car Beam,CCB)的设计开发初始阶段,选取一些设计参数作为设计变量,利用SFE建立针对这些变量的参数化模型,选取适当的DOE正交矩阵列表输出参数化模型.使用Kriging方法构建性能结果的响应面近似模型,通过主效应和贡献量的对比分析发现圆管梁的直径和壁厚是最关键的设计变量,为仪表板横梁的设计提供指导.借助Isight优化算法在整个样本空间中寻找最优结构设计并进行虚拟仿真验证,从而得到最优的实际产品结构.     

基于耐撞性的前纵梁截面优化设计

前纵梁是偏置碰撞测试中重要的吸能部件之一。本文对前纵梁截面形状进行了优化设计,以提高前纵梁的耐撞性。根据前纵梁截面尺寸参数得到设计变量,构建响应面模型,利用遗传算法计算得到优化结果。将优化所得的截面尺寸应用于某三厢轿车40%偏置碰撞分析中,结果表明,前纵梁耐撞性显著提高,碰撞侧B柱加速度峰值有效降低,整车被动安全性能得到提升。     

泡沫铝填充薄壁圆管吸能特性优化

为获得最大比吸能(Specific Energy Absorption, SEA)的泡沫铝填充薄壁圆管结构,以动态显式有限元分析为基础,结合响应面法(Response Surface Method,RSM),建立结构的SEA优化函数;利用MSC Dytran进行碰撞仿真,得出薄壁构件的SEA随构件薄壁厚度和截面直径变化的规律;以最大SEA为优化函数,对泡沫铝填充薄壁圆管的直径和壁厚进行优化. 轨道列车吸能装置的实际应用表明,该方法在降低吸能装置质量且优化模型不超出原模型最大压缩力的条件下,可以提高结构的变形能和SEA.     

基于正碰CAE分析的车身纵梁结构优化设计

对某车型进行50 km/h、100%正面碰撞CAE仿真分析,发现车身前纵梁溃缩变形不充分,导致B柱加速度峰值超过45g目标要求。对前纵梁结构和前防撞梁吸能盒进行优化,由CAE分析可知：车身前纵梁结构变形得到明显改善,B柱加速度峰值降低到45g以下,满足目标要求。该优化可有效提高车身正面碰撞的安全性能。     

集中质量-弹簧碰撞模型在汽车被动安全预研阶段的应用

为在车身开发的概念设计阶段明确车辆前碰的安全性目标加速度波形,提出以乘员伤害值确定整车正面碰撞波形的方法,建立包括驾乘人员的车辆集中质量-弹簧(Lumped Mass-Spring,LMS)模型.为确保LMS模型的有效性,将整车有限元模型仿真结果与运动学特性计算结果对比.通过对比前碰加速度波形、刚性墙力以及前舱总的压溃位移,对LMS模型的有效性进行验证.以乘员胸部的乘约效率为优化目标,基于已验证的LMS模型进行关键参数的试验设计分析,从而为车辆前结构的碰撞安全性能设计提供参考.     

基于显式有限元技术的梁截面抗撞性优化

本文基于显式有限元技术,采用响应面法,以结构的比吸能为优化函数,以提高吸能原件的抗撞性为目的,对正方形截面的金属薄壁梁进行了形状优化．经过数值分析,得出了正方形截面梁的比吸能关于壁厚和截面边长的变化规律,这些规律可以用于实际吸能原件的设计,并为进一步研究奠定了基础．     

抗冲击性能要求下一种新型夹心板的设计研究

防护板在舰船上的应用非常广泛,它对于提高舰船抵抗水下爆炸冲击波载荷性能、抗碰撞冲击性能等都具有重要作用.文中利用薄壁圆管的吸能特性设计了离散型和紧密型圆管夹心板,使用大型非线性有限元软件MSC.Dytran建立水域、炸药及防护板的三维有限元模型,并进行水下爆炸数值仿真计算,从板的吸能能力、加速度响应、变形量三个方面分析了两种夹心板和普通平板在水下爆炸载荷作用下的抗冲击性能,仿真计算结果表明离散型夹心板的抗爆性能优于紧密型夹心板和普通平板.     

某电动汽车驾驶员座椅后横梁平台化开发

针对电动汽车地板下方无法布置横梁、纵梁等结构,导致地板刚度较差的问题,在对比传统车型座椅横梁结构的基础上,提出一种贯穿式驾驶员座椅横梁结构。从刚度、模态、碰撞安全性能等角度出发,对座椅横梁结构进行优化设计。经有限元分析验证,优化后横梁结构在满足各项性能要求的同时可加工性也较好。该方法可为电动车座椅横梁平台化开发提供参考。     

Crashworthiness design for functionally graded foam-filled bumper beam

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 ρ_f1 and ρ_f2 (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.     

基于格子波尔兹曼方法的机舱散热耦合分析

为指导前保险杠格栅及开口设计,研究冷却系统在特定工况下的散热性能和流场分布,建立具有详细的发动机舱几何信息的整车模型,利用格子波尔兹曼方法模拟整车在数字风洞中的热性能,得到机舱内流场和温度场以及散热器出水温度.分析结果与实验数据一致性很好,因此格子波尔兹曼方法很适合解决具有复杂几何结构的机舱散热问题.基于对标模型,针对前保险杠格栅的开口和格栅形式提出改进优化建议.经过多轮优化,散热器的散热能力提升6.94%.     

Optimization of the new Saab 9-3 exposed to impact load using a space mapping technique

The aim of this work is to illustrate how a space mapping technique using surrogate models together with response surfaces can be used for structural optimization of crashworthiness problems. To determine the response surfaces, several functional evaluations must be performed and each evaluation can be computationally demanding. The space mapping technique uses surrogate models, i.e. less costly models, to determine these surfaces and their associated gradients. The full model is used to correct the gradients from the surrogate model for the next iteration. Thus, the space mapping technique makes it possible to reduce the total computing time needed to find the optimal solution. First, two analytical functions and one analytical structural optimization problem are presented to exemplify the idea of space mapping and to compare the efficiency of space mapping to traditional response surface optimization. Secondly, a sub-model of a complete vehicle finite element (FE) model is used to study different objective functions in vehicle crashworthiness optimization. Finally, the space mapping technique is applied to a structural optimization problem of a large industrial FE vehicle model, consisting of 350.000 shell elements and a computing time of 100 h. In this problem the intrusion in the passenger compartment area was reduced by 32% without compromising other crashworthiness parameters.     

Structural optimization of the cross-beam of a gantry machine tool based on grey relational analysis

Crossbeam structural design of gantry machine tool is a multi-level, multi-index and multi-scheme decision-making problem. In order to solve the above problem, the optimum seeking model of crossbeam structure was built through using the grey relational analysis and Analytic Hierarchy Process. The finite element analysis of the static and dynamic performance parameters for four kinds of crossbeam structural schemes designed had been done, and the optimal design scheme was selected by using the optimum seeking model. After conducting sensitivity analysis for the optimal crossbeam selected, the reasonable design variables were obtained, and the dynamic optimization design model of crossbeam was established. Six groups of non-inferior solutions were obtained after solving the optimization design model. The optimal solution was selected from the non-inferior solution set through using the crossbeam structural optimization method based on grey relational analysis again, which makes the crossbeam’s dynamic performance improving greatly. The dynamic experiments on the crossbeams before and after optimization design were conducted, then the experimental results show that the first four order natural frequencies of the crossbeam increase 17.56 %, 19.36 %, 17.04 % and 19.58 % respectively, which proves that the structural optimization design method based on grey relational analysis proposed in this paper is reasonable and practicable.     

An investigation of structural optimization in crashworthiness design using a stochastic approach

In this paper the response surface methodology (RSM) and stochastic optimization (SO) are compared with regard to their efficiency and applicability in crashworthiness design. Optimization of simple analytic expressions and optimization of a front rail structure are the applications used to assess the respective qualities of both methods. A low detail vehicle structure is optimized to demonstrate the applicability of the methods in engineering practice. The investigations reveal that RSM is better compared to SO for fewer than 10–15 design variables. The convergence behaviour of SO improves compared to RSM when the number of design variables is increased. A novel zooming method is proposed which improves the convergence behaviour. A combination of both the RSM and the SO is efficient, stochastic optimization could be used in order to determine appropriate starting points for an RSM optimization, which continues the optimization. Two examples are investigated using this combined method.     

Multi-objective optimization for bus body with strength and rollover safety constraints based on surrogate models

It is important to consider the performances of lightweight, stiffness, strength and rollover safety when designing a bus body. In this paper, the finite element (FE) analysis models including strength, stiffness and rollover crashworthiness of a bus body are first built and then validated by physical tests. Based on the FE models, the design of experiment is implemented and multiple surrogate models are created with response surface method and hybrid radial basis function according to the experimental data. After that, a multi-objective optimization problem (MOP) of the bus body is formulated in which the objective is to minimize the weight and maximize the torsional stiffness of the bus body under the constraints of strength and rollover safety. The MOP is solved by employing multi-objective evolutionary algorithms to obtain the Pareto optimal set. Finally, an optimal solution of the set is chosen as the final design and compared with the original design.     

基于行人保护FLEX-PLI腿型的车辆前结构改进分析

欧盟新车评价规程Euro NCAP中的TRL腿型验算即将被FLEX-PLI腿型验算替代，所以针对前者开发的某款车型在使用新标准验算时不能得到满分。运用计算机仿真对该车型前端结构进行改进：去除前保险杠吸能泡沫；重新设计W形结构的下腿部保护横梁，在碰撞点对应位置增加与FLEX-PLI腿型宽度相同的加强筋，加大下腿部保护横梁与前保横梁的距离；改进导风板局部结构。对改进后前端结构进行FLEX-PLI腿型验算，达到得分为满分的目标。     

Multivariable crashworthiness optimization of vehicle body by unreplicated saturated factorial design

Crashworthiness, influenced unequally by disparate factors such as the structural dimensions and the material parameters, represents a natural benchmark criterion to judge the passive safety quality of the automobile design. The unreplicated saturated factorial design has enjoyed a remarkable success in the factor screening of different industrial regions due to its huge benefits in the efficiency and accuracy. In order to single out the active factors which pose a profound impact on the crashworthiness, this paper introduces an unreplicated saturated factorial design to tackle the obstacle from the factor screening during the multivariable crashworthiness optimization design of the whole vehicle body. Three unreplicated saturated factorial design methods, including the normal or half-normal probability plot method, Dong93 method, and PSZ method, are employed to capture the active factors while D-optimal design is presented to obtain the design sampling points and to construct the response surface model for the crashworthiness optimization problem. Finally, multi-island genetic algorithm (MIGA) and sequential quadratic programming (SQP)-NLPQL are utilized to obtain the Pareto set of the optimal solution for the multivariable crashworthiness optimization design of the vehicle body under the full-scale frontal impact loading.