基于SGA-BP-GA方法的FPSO舷侧结构耐撞性能优化设计

由于船体结构及碰撞优化的复杂性,使得传统优化方法难以有效进行。基于遗传算法、模拟退火算法和BP神经网络,结合正交试验设计和ABAQUS参数化仿真技术,提出一种新的结构耐撞性优化方法——SGA-BP-GA。为了提高BP网络对结构耐撞性指标的预测精度和泛化能力,利用模拟退火算法的概率突跳特性克服遗传算法易早熟和陷于局部最优的缺点,在此基础上采用模拟退火遗传算法(SGA)对BP网络的权重进行优化。采用提出的SGA-BP-GA方法对FPSO舷侧结构耐撞性能进行优化设计,以验证其准确性与可行性。结果表明:与传统BP、GA-BP和SA-BP相比,SGA-BP具有更高的预测精度和泛化能力;与GA-BP-GA方法相比,SGA-BP-GA优化结果仍提高了5.34%;提出的SGA-BP-GA方法能够较好的适用于复杂的船体结构耐撞性优化设计。     

汽车前纵梁吸能盒结构耐撞性多目标优化

吸能盒上诱导槽的分布形式对汽车碰撞性能有很大影响。以汽车前纵梁吸能盒结构为对象,建立整车正面碰撞仿真模型,对吸能盒结构的耐撞性进行了多目标优化设计。以吸能盒上诱导槽之间的间距为设计变量,使用Hammersley方法采集样本点后,以车辆吸能盒的最大吸能量E、最大刚性墙反力F以及车身最大加速度a为目标函数,通过kriging法以及径向基法构建各目标函数的近似代理模型,并检验了近似模型的精度。采用第二代非劣排序遗传算法(NSGA-Ⅱ)进行了多目标优化。结果表明,与原模型相比,优化后的非均匀分布形式的诱导槽结构耐撞性改善明显,变形压缩模式更充分、有序。     

浅谈汽车前纵梁耐撞性结构改进

文章主要进行了汽车结构耐撞性研究,分析客车特别是轿车和微型客车的车身结构对碰撞能量的吸收特性,寻求改善车身结构耐撞性的方法,使得车身结构在外力冲击下能以预计的方式变形,其变形量能控制在一定的范围内,在保证乘员安全空间的前提下,车身变形吸收的能量最大,从而使传递给车内乘员的碰撞能量降低到最小,尽可能使乘员所受的加速度最小。     

机械冲击耐撞性与稳健设计

碰撞冲击是机电产品损坏失效的常见原因,轻则造成产品外形丧失美观,重则造成产品内在功能失效,甚至机毁人亡,因而机械产品的耐撞性受到日益广泛的关注。本文从产品跌落冲击和运载工具碰撞两个领域论述了机械系统碰撞动力学和耐撞性设计研究的发展、两领域耐撞性研究的阶段性和特点,分析了机械冲击耐撞性中的冲击参数到性能参数传递过程中的不确定性,进而探讨了机械系统产品耐撞性稳健设计优化框架。     

基于拓扑优化与诱导结构的抗撞结构优化设计EI北大核心CSCD

鉴于耐撞性拓扑方法在实际使用中只能获得抗撞结构的初级拓扑构型,导致抗撞结构的碰撞安全性仍有进一步提升空间的问题,以耐撞性拓扑优化为基础,获得了抗撞结构的初级拓扑构型,在初级拓扑构型的适当位置设置诱导结构,得到最终吸能单元构型,再利用稳健性设计方法获取最终构型的最优尺寸参数,较好地弥补了基于最大吸能原则的耐撞性拓扑方法的不足。算例表明,所提的优化设计方法灵活有效,基于该方法得到的抗撞结构可以更好地满足设计要求。     

汽车车身耐撞性设计参数的区间稳健性优化

基于区间分析,提出了一种考虑公差的汽车车身耐撞性稳健优化设计模型,可在有效降低耐撞性能对设计参数波动敏感性的同时实现公差范围的最大化。该模型首先利用对称公差来描述汽车碰撞模型中车身关键耐撞部件的主要尺寸、位置和形状等设计参数本身的不确定性,然后将参数设计和公差设计相结合,建立了以稳健性评价指标和公差评价指标为优化目标,设计变量名义值和公差同步优化的多目标优化模型。再次,利用区间可能度处理不确定约束,将该优化模型转换为确定性多目标优化模型。最后,将该模型应用于两个汽车耐撞性优化设计问题,并通过序列二次规划法和改进的非支配排序遗传算法进行求解,结果表明该方法及稳健优化设计模型可行且实用。     

灰色关联及熵权法对碳纤维增强树脂复合材料防撞梁的耐撞性优化设计

为改善和提升汽车的轻量化和耐撞性,针对碳纤维增强树脂基复合材料特性提出一种基于灰色关联分析与熵权法结合的复合材料防撞梁结构的设计策略。建立了考虑整车实际工况的数值简化模型,并通过碳纤维增强树脂复合材料力学性能试验确定了T300碳纤维/5113环氧树脂复合材料的材料力学性能,为碰撞工况下碳纤维增强树脂保险杠防撞梁模型计算提供真实准确的材料参数。基于正面碰撞仿真模型,采用哈默斯雷试验设计方法确立60组样本点建立了设计变量与响应之间的关系,采用熵权法求出各响应指标的权重值,结合灰色关联分析对碳纤维增强树脂复合材料防撞梁的耐撞性和轻量化进行优化设计,获取防撞梁结构的最优尺寸参数组合,确定优化方案。研究结果显示,与初始防撞梁相比,优化方案吸能量峰值提高了11.4%,峰值力降低了48%,质量减少了56.5%。该方法在满足安全性指标的前提下实现了汽车轻量化优化设计。      

飞行器机身结构耐撞性分析与设计

耐撞性不仅是飞行器设计中的重要问题,而且还是其取得适航证的必要条件。该文对美国、欧盟和日本等在耐撞性研究方面的研究进行了总结,阐述了耐撞性设计中采用的数值模拟和试验研究方法及其主要问题。主要针对各种飞行器结构耐撞性设计方法进行介绍,对比了轻型固定翼飞机、直升机和大中型民用飞机的耐撞性设计特点。能量吸收结构是耐撞性设计的关键问题之一,对提高飞行器机身能量吸收能力的机身底部结构、机身加强框和客舱地板撑杆结构等设计方法进行详细介绍,总结了飞行器耐撞性可靠性分析和优化设计方法。最后对飞行器结构耐撞性设计的发展作了展望。     

基于等效静态载荷法的汽车前端结构抗撞性尺寸和形貌优化

为了减少在低速正碰下汽车的维修成本以及实现汽车前端结构的轻量化。采用等效静态载荷方法对汽车前端结构的尺寸和形状进行了抗撞性优化设计,以整个结构质量最小为优化的目标函数,以前部结构主要部件的厚度尺寸以及节点坐标形貌为设计变量,以侵入量以及加强筋的冲压工艺要求为约束进行了碰撞优化设计。等效静态载荷法将非线性瞬态碰撞优化问题转化为多工况线性静态优化问题,数值算例证明等效静态载荷法可高效地求解碰撞优化问题,并得到高精度的最优解。     

A型不锈钢地铁车体耐撞性研究

轨道车辆车体基本性能的研究需要考虑多方面的因素,车体耐碰撞性是重要指标之一。以A型不锈钢地铁车体为研究对象,基于LS-DYNA碰撞仿真平台,分析了车辆在不同碰撞速度下车体的耐撞性能;然后,采用逼近法,获取了该型地铁车的最大碰撞安全速度,为车体的耐撞性设计提供了理论支撑。     

A system methodology for optimization design of the structural crashworthiness of a vehicle subjected to a high-speed frontal crash

The structural crashworthiness design of vehicles has become an important research direction to ensure the safety of the occupants. To effectively improve the structural safety of a vehicle in a frontal crash, a system methodology is presented in this study. The surrogate model of Online support vector regression (Online-SVR) is adopted to approximate crashworthiness criteria and different kernel functions are selected to enhance the accuracy of the model. The Online-SVR model is demonstrated to have the advantages of solving highly nonlinear problems and saving training costs, and can effectively be applied for vehicle structural crashworthiness design. By combining the non-dominated sorting genetic algorithm II and Monte Carlo simulation, both deterministic optimization and reliability-based design optimization (RBDO) are conducted. The optimization solutions are further validated by finite element analysis, which shows the effectiveness of the RBDO solution in the structural crashworthiness design process. The results demonstrate the advantages of using RBDO, resulting in not only increased energy absorption and decreased structural weight from a baseline design, but also a significant improvement in the reliability of the design.     

Crashworthiness design optimization using successive response surface approximations

 Finite Element (FE) method is among the most powerful tools for crash analysis and simulation. Crashworthiness design of structural members requires repetitive and iterative application of FE simulation. This paper presents a crashworthiness design optimization methodology based on efficient and effective integration of optimization methods, FE simulations, and approximation methods. Optimization methods, although effective in general in solving structural design problems, loose their power in crashworthiness design. Objective and constraint functions in crashworthiness optimization problems are often non-smooth and highly non-linear in terms of design variables and follow from a computationally costly (FE) simulation. In this paper, a sequential approximate optimization method is utilized to deal with both the high computational cost and the non-smooth character. Crashworthiness optimization problem is divided into a series of simpler sub-problems, which are generated using approximations of objective and constraint functions. Approximations are constructed by using statistical model building technique, Response Surface Methodology (RSM) and a Genetic algorithm. The approximate optimization method is applied to solve crashworthiness design problems. These include a cylinder, a simplified vehicle and New Jersey concrete barrier optimization. The results demonstrate that the method is efficient and effective in solving crashworthiness design optimization problems. Received: 30 January 2002 / Accepted: 12 July 2002 Sponsorship for this research by the Federal Highway Administration of US Department of Transportation is gratefully acknowledged. Dr. Nielen Stander at Livermore Software Technology Corporation is also gratefully acknowledged for providing subroutines to create D-optimal experimental designs and the simplified vehicle model.     

Interval-Based Uncertain Multi-Objective Optimization Design of Vehicle Crashworthiness

In this paper, an uncertain multi-objective optimization method is suggested to deal with crashworthiness design problem of vehicle, in which the uncertainties of the parameters are described by intervals. Considering both lightweight and safety performance, structural weight and peak acceleration are selected as objectives. The occupant distance is treated as constraint. Based on interval number programming method, the uncertain optimization problem is transformed into a deterministic optimization problem. The approximation models are constructed for objective functions and constraint based on Latin Hypercube Design (LHD). Thus, the interval number programming method is combined with the approximation model to solve the uncertain optimization problem of vehicle crashworthiness efficiently. The present method is applied to two practical full frontal impact (FFI) problems.     

Evaluation of response surface methodologies used in crashworthiness optimization

Optimization of car structures is of great interest to the automotive industry. This work is concerned with structural optimization of a car body with the intent to increase the crashworthiness properties of the vehicle or decrease weight with the crashworthiness properties unaffected. In this work two different methodologies of constructing an intermediate approximation to the optimization problem are investigated, i.e. classical response surface methodology and Kriging. The major difference between the two methodologies is how the residuals between the true function value and the polynomial surface approximation value at a design point are treated.Several different optimization problems have been investigated, both analytical problems as well as finite element impact problems.The major conclusion is that even if the same kind of updating scheme is used both for Kriging and linear classic response surface methodology, Kriging improves the sequential behaviour of the optimization algorithm in the beginning of the optimization process. Problems may occur if a constraint is violated after several iterations and then classic response surface methodology seems to more easily be able to find a design point which satisfies the constraint.     

Multiobjective crashworthiness optimization design of functionally graded foam-filled tapered tube based on dynamic ensemble metamodel

Foam-filled thin-walled structures have recently gained attention with increasing interest due to their excellent energy absorption capacity. In this study, a new type of foam-filled thin-walled structure called as functionally graded foam-filled tapered tube (FGFTT) is proposed. FGFTT consists of graded density foam and thin-walled tapered tube. In order to investigate the energy absorption characteristics of FGFTTs, the numerical simulations for two kinds of FGFTTs subjected to axial dynamical loading are carried out by nonlinear finite element code LS-DYNA. In addition, a new kind of multiobjective crashworthiness optimization method employing the dynamic ensemble metamodeling method together with the multiobjective particle swarm optimization (MOPSO) algorithm is presented. This new kind of multiobjective crashworthiness optimization method is then used to implement the crashworthiness optimization design of FGFTTs. Meanwhile, the crashworthiness optimization designs of FGFTTs are implemented by using traditional multiobjective crashworthiness optimization method, which employs metamodels such as polynomial response surface (PRS), radial basis function (RBF), kriging (KRG), support vector regression (SVR) or the ensemble with the static design of experiment (DOE). Finally, by comparing the optimal designs of FGFTTs obtained by using the new multiobjective crashworthiness optimization method and the traditional one, the results show that the proposed new crashworthiness optimization method is more feasible.     

CRASHWORTHINESS ANALYSIS AND DESIGN USING RIGID–FLEXIBLE MULTIBODY DYNAMICS WITH APPLICATION TO TRAIN VEHICLES

Different formulations based on multibody dynamics are shown to be suitable for the development of a methodology for the impact simulation and crashworthiness design of railway vehicles. The proposed design methodology comprises different computer-aided tools of increasing complexity and accuracy which can be used with greater advantage and efficiency in the different design stages of railway stock. In general, the crashworthiness design methods and associated multibody dynamic tools which are presented in this paper require information to be obtained from numerical or experimental crush tests of specific structural components, subassemblies and critical energy absorption devices normally located in car extremities. This hybrid feature lends to the present design process various efficiency gains as a result of a better understanding of the crash and different collapse mechanisms and ease of use. To access the merits of the present methodologies some new designs are discussed and the application of the proposed numerical tools is illustrated for different structural configurations of car extremities. A formulation for the sensitivity analysis and optimization of planar constrained mechanical systems is also presented. An example of crashworthiness design of an end underframe model of a railway car is solved to demonstrate the use of the methodology. © 1997 by John Wiley & Sons, Ltd.     

Probability-based least square support vector regression metamodeling technique for crashworthiness optimization problems

This paper presents a crashworthiness design optimization method based on a metamodeling technique. The crashworthiness optimization is a highly nonlinear and large scale problem, which is composed various nonlinearities, such as geometry, material and contact and needs a large number expensive evaluations. In order to obtain a robust approximation efficiently, a probability-based least square support vector regression is suggested to construct metamodels by considering structure risk minimization. Further, to save the computational cost, an intelligent sampling strategy is applied to generate sample points at the stage of design of experiment (DOE). In this paper, a cylinder, a full vehicle frontal collision is involved. The results demonstrate that the proposed metamodel-based optimization is efficient and effective in solving crashworthiness, design optimization problems.     

Al/CFRP混合薄壁结构耐撞性能可靠性优化设计

轻量化是实现汽车产业向安全、节能、环保发展的一个重要途径。Al/CFRP（carbon fiber reinforced plastic，碳纤维增强复合材料）混合材料能够在提升轻量化效果的同时兼顾材料成本和结构耐撞性能。为探索方形截面Al/CFRP混合薄壁结构的最佳组合方式，首先，制备了Al方管、CFRP方管和Al/CFRP混合方管，并开展准静态压溃实验。然后，建立能够精确模拟Al/CFRP混合方管压溃响应的有限元模型。最后，将试验设计方法、代理模型技术、多目标优化算法和蒙特卡罗模拟技术相结合，对Al/CFRP混合方管分别进行多目标确定性与可靠性优化设计，并对效果较好的可靠性优化解进行仿真验证。准静态压溃实验结果表明，Al/CFRP混合方管具有优异的耐撞性能；优化结果表明，可靠性优化解的约束可靠度相比于确定性优化解提高了10.96%，大大降低了失效概率，具有更强的实用性。研究结果有望对Al/CFRP混合薄壁吸能构件的优化设计提供参考。     

A hybrid cellular automaton–bi-directional evolutionary optimization algorithm for topological optimization of crashworthiness

This article proposes a new algorithm for topological optimization under dynamic loading which combines cellular automata with bi-directional evolutionary structural optimization (BESO). The local rules of cellular automata are used to update the design variables, which avoids the difficulty of obtaining gradient information under nonlinear collision conditions. The intermediate-density design problem of hybrid cellular automata is solved using the BESO concept of 0–1 binary discrete variables. Some improvement strategies are also proposed for the hybrid algorithm to solve certain problems in nonlinear topological optimization, e.g. numerical oscillation. Some typical examples of crashworthiness problems are provided to illustrate the efficiency of the proposed method and its ability to find the final optimal solution. Finally, numerical results obtained using the proposed algorithms are compared with reference examples taken from the literature. The results show that the hybrid method is computationally efficient and stable.     

Optimization of foam-filled bitubal structures for crashworthiness criteria

Thin-walled structures have been widely used as key components in automobile and aerospace industry to improve the crashworthiness and safety of vehicles while maintaining overall light-weight. This paper aims to explore the design issue of thin-walled bitubal column structures filled with aluminum foam. As a relatively new filler material, aluminum foam can increase crashworthiness without sacrificing too much weight. To optimize crashworthiness of the foam-filled bitubal square column, the Kriging meta-modeling technique is adopted herein to formulate the objective and constraint functions. The genetic algorithm (GA) and Non-dominated Sorting Genetic Algorithm II (NSGA II) are used to seek the optimal solutions to the single and multiobjective optimization problems, respectively. To compare with other thin-walled configurations, the design optimization is also conducted for empty bitubal column and foam-filled monotubal column. The results demonstrate that the foam-filled bitubal configuration has more room to enhance the crashworthiness and can be an efficient energy absorber.