着陆缓冲系统中吸能结构的耐撞性优化
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摘要
着陆缓冲系统广泛地应用在航空、航天和国防工业等领域中,其缓冲吸能结构的吸能特性好坏直接影响着陆缓冲系统的缓冲性能,设计出吸能特性好、质量轻且能满足实际缓冲特性要求的缓冲吸能结构具有重大的实际意义。着陆缓冲系统中常用的缓冲吸能结构有金属薄壁结构和气囊结构。本文以有限元仿真为基础,采用理论与试验相结合的方法研究了金属薄壁结构中的蜂窝结构和蜂窝填充管结构以及气囊结构中的多室气囊的吸能特性,并采用合适的优化设计方法对国家重大工程中相关结构进行了耐撞性优化。主要研究内容如下：
(1)提出了一种基于近似模型和多目标粒子群算法的金属蜂窝结构耐撞性优化设计方法。为了设计出轴向吸能特性最优的六边形金属蜂窝缓冲结构,我们以六边形金属蜂窝的元胞胞壁长、胞壁厚和胞壁夹角为优化设计变量,以其比吸能和峰值压缩应力为优化目标,对该结构的吸能特性进行了耐撞性多目标优化。在优化过程中,首先采用优化拉丁方法在设计变量空间中进行采样,然后应用LS-DYNA计算出每个样本点对应的蜂窝轴向压缩比吸能和峰值应力。根据这些样本点信息,分别构造了目标函数的多项式函数模型、径向基函数模型、Kriging模型、MARS模型和SVR模型,同时对比这些近似模型的精度,发现比吸能的二阶多项式函数模型和峰值应力的三阶多项式函数模型的精度相对最高。最后,基于精度相对最高的目标函数近似模型,采用多目标粒子群算法对六边形金属蜂窝进行了耐撞性多目标优化,获得了不同峰值压缩应力约束条件下的一系列最优六边形金属蜂窝结构。
(2)采用简化的超折叠单元理论推导出了三种常用元胞构型金属蜂窝一一正六边形蜂窝、加强正六边形蜂窝和弯曲元胞蜂窝的轴向平均压缩应力理论公式,进而根据推导出的理论公式进一步计算出了这三种常用预压缩蜂窝材料的比吸能大小。同时,我们把预压缩蜂窝的比吸能和峰值压缩应力作为优化目标,把蜂窝材料的元胞胞壁长和胞壁厚作为优化变量,采用多目标粒子群优化算法对三种预压缩常用蜂窝进行了优化设计。根据该多目标优化结果,可以得到不同峰值压缩应力限制的一系列最优蜂窝结构。此外,根据优化结果我们发现正六边形蜂窝的吸能特性相对最好。
(3)提出了一种基于六等级评价方法的耐撞性评价方法和一种基于近似模型和多目标粒子群算法的蜂窝填充管耐撞性优化设计方法。基于六等级评价方法,分别对蜂窝填充正多边形单层管和蜂窝填充正多边形双层管的轴向压缩比吸能和载荷效率进行了等级评价,从而找出了相对吸能最优的蜂窝填充正多边形管为正九边形管,进而对蜂窝填充正九边形管进行了耐撞性多目标优化。在优化过程中,我们构建了蜂窝填充正九边形单层管和双层管的比吸能以及峰值压缩力的多项式函数近似模型。基于多项式函数近似模型,我们采用多目标粒子群算法对蜂窝填充正九边形单层管和双层管进行了耐撞性优化,分别得到了它们比吸能和峰值压缩力的Pareto最优解集。根据它们的Pareto最优解集,可以分别获得不同压缩力约束条件下的一系列最优蜂窝填充正九边形单层管和蜂窝填充正九边形双层管。此外,我们还发现在相同的压缩力峰值约束条件下,最优蜂窝填充正九边形单层管的单位质量吸能比最优蜂窝填充正九边形双层管的高。这说明在本文所考虑的工况中,蜂窝填充正九边形单层管的吸能特性比蜂窝填充正九边形双层管的好。
(4)提出了一种基于Wierzbicki的蜂窝平均压缩应力公式和多目标粒子群算法的腿式着陆器蜂窝缓冲装置的优化设计方法。采用Wierzbicki的蜂窝平均压缩应力公式计算了腿式着陆器缓冲装置中的蜂窝结构的轴向压缩平均压缩应力和比吸能。从而基于该理论解,采用多目标粒子群算法对腿式着陆器中蜂窝缓冲装置的元胞胞壁厚和胞壁长进行了多目标耐撞性优化。根据优化结果,结合能量守恒原理计算出了缓冲蜂窝的最小轴向长度,从而实现了蜂窝缓冲装置的优化设计。应用该方法对某型四支撑腿着陆器中的主缓冲筒内铝蜂窝进行了优化设计。最后运用经试验验证的有限元力学模型对优化结果进行了分析,分析结果表明该优化设计的缓冲装置能很好地满足工程设计要求。
(5)提出了一种基于近似模型和多目标粒子群算法的多室气囊缓冲系统优化设计方法。在该多室气囊优化设计方法中,以多室气囊中各个气囊的体积、初始充气压力、排气压力和排气面积为优化设计变量,以被缓冲设备的质心加速度以及气囊比吸能为优化目标,采用多目标粒子群算法对多室气囊缓冲系统进行耐撞性多目标优化。本文应用该多室气囊系统优化设计方法分别对重装空投设备非连通多室气囊缓冲装置以及火星着陆连通多室气囊缓冲装置进行了优化设计。在重装空投设备非连通多室气囊缓冲装置的优化设计过程中,首先采用优化拉丁方法在设计变量空间中进行采样,然后应用LS-DYNA计算出每个样本点对应的目标函数值。从而基于采样点信息,采用ERR结构选择技术构建了目标函数的简化的四阶多项式函数近似模型。最后采用多目标粒子群算法获得了目标函数的Pareto最优解集,根据Pareto最优解集,可以得到重装空投设备非连通多室气囊缓冲装置的最优设计。在火星着陆连通多室气囊缓冲装置的优化设计过程中,首先采用全因子法在设计变量空间中进行采样,然后应用LS-DYNA计算出每个样本点对应的目标函数值。从而基于采样点信息,构建了目标函数的多项式函数近似模型。基于近似模型,我们采用多目标粒子群算法对火星着陆连通多室气囊进行了多目标耐撞性优化,获得了目标函数的Pareto最优解集。根据Pareto最优解集,可以得到火星着陆连通多室气囊缓冲装置的最优设计。此外,我们运用了试验验证的火星着陆连通多室气囊缓冲系统有限元力学模型对优化结果进行了分析,分析结果表明该优化设计的多室气囊系统能很好地满足工程设计要求。
Landing system has been widely used in aircraft, aerospace, military and other industries. The cushioning characteristics of a landing system mainly depend on the energy absorption capacity of its energy absorbing structures. It is significant to design an energy absorbing structure with excellent energy absorption capacity, highly light weight and satisfaction with the paractical cushioning requirement. The commonly used energy absorbing structures in landing system are metal thin-walled structures and airbag structures. Based on the finite element analysis (FEA), we mainly investigate the energy absorption characteristics of honeycomb structure and honeycomb-filled tubular structure as well as multi-chamber airbag structure using theoretical and experimental methods in this dissertation. In addition, we optimize the energy absorbing capacity of these energy absorbing structures using the suitable optimization method. The detailed research works of this dissertation are listed as follows:
(1) A crashworthiness optimization design method for metal honeycomb structure based on metamodel and multi-objective particle swarm optimization (MOPSO) algorithm is proposed. In order to design a metal hexagonal honeycomb structure with maximum energy absorbing capacity among all kinds of hexagonal honeycomb structures, we multi-optimize the energy absorbing capacity of the hexagonal honeycomb structures. In our study, the cell wall width, the cell wall thickness and the branch angle are choosed as the design variables while the specifical energy absorption (SEA) and the peak crushing stress (PCS) are selected as the optimization objectives. During the optimization process, the optimal Latin hypercube design (OLHD) method is used for sampling design points in design space firstly. Then, the SEA and PCS of the corresponding honeycomb structure of the sampling points are obtained by employing the nonlinear finite element code LS-DYNA. Based on the informations of these sampling points, the Polynomial functions, Radial Basis Functions (RBF), Kriging, Multivariate Adaptive Regression Splines (MARS) and Support Vector Regression (SVR) are utilized to formulate the metamodels of the two optimal objectives SEA and PCS, respectively. By comparing the accuracy of these metalmodels, we find that the quadratic and cubic polynomial functions are the most accurate ones among these metamodels for predicting SEA and PCS. According to the accurate metamodels of SEA and PCS, the crashworthiness of the metal hexagonal honeycomb structure is multi-optimized by utilizing MOPSO algorithm. A series of optimal designs of metal hexagonal honeycomb structures with the PCSs constrained under different values are finally obtained.
(2) The mean crushing stresses of three commonly used honeycombs (regular hexagonal honeycomb, reinforced regular hexagonal honeycomb and flex honeycomb) are calculated by using the Simplified Super Folding Element (SSFE) theory. Based on the theoretical solutions of the mean crushing stresses, the SEAs of three pre-crushed commonly used honeycombs are calculated, respectively. In our following optimization, the cell wall width and the cell wall thickness are choosed as the design variables while the specifical energy absorption (SEA) and the peak crushing stress (PCS) are selected as the optimization objectives. Then, the crashworthiness of three commonly used pre-crushed honeycombs is optimized by using MOPSO algorithm. According to the multiobjective optimization results, the optimal designs of three commonly used honeycombs with the PCSs constrained under different values can be obtained. In addition, we find that the energy aborption capcity of regular hexagonal honeycomb structure is the most excellent one among that of three kinds of honeycombs.
(3) A six-level judgement method for crashworthiness evaluation and a crashworthiness optimization design method for honeycomb-filled polygonal tubes based on metamodel and MOPSO algorithm are proposed. After ranking the levels of the SEA and crash load efficiency (CLE) of HSPTs and HBPTs under axial loading based on the six-level judgement method, it is found that the honeycomb-filled single and honeycomb-filled bitubular tubes with enneagonal configuration have comparative most excellent energy absorption characteristics among the considered cases. Next, the HSPTs and HBPTs with enneagonal configuration are optimized by adopting MOPSO algorithm to achieve maximum SEA capacity and minimum peak crushing force (PCF). During the process of optimization, accurate metamodels of SEA and PCF of the HSPTs and HBPTs with enneagonal configuration are established. After optimization, we obtain the Pareto fronts of SEA and PCF for the HSPTs and HBPTs with enneagonal configuration. According to the Pareto fronts, the optimal designs of HSPTs and HBPTs with enneagonal configuration are obtained when their PCFs are constrained under different values. By comparing the Pareto fronts of two kinds of honeycomb-filled tubes, we find that the energy absorption capability per unit mass of the optimized honeycomb-filled single enneagonal tubes is more powerful than that of the honeycomb-filled bitubular enneagonal tubes while the PCF constrained under the same level. This indicates that the honeycomb-filled single enneagonal tube is superior to the honeycomb-filled bitubular enneagonal tube in the considered cases.
(4) A crashworthiness optimization design method for cushioning honeycomb in the legged lander based on Wierzbicki's mean crushing stress (MCS) expression for honeycomb is proposed. According to Wierzbicki's expression for mean crushing stress (MCS) of honeycomb, we calculate the MCS and SEA of the honeycomb energy absorbing structure in the legged lander. Based on these theoretical solutions, we optimize the crashwothiness of the honeycomb energy absorbing structure in the legged lander using MOPSO algorithm while the cell wall with and cell wall thickness of the honeycomb structur are selected as the design variables. By using the energy equivalent principle, we can obtain the minimum length of the honeycomb structure according to the previous optimal results. Thus, the optimal solution to the cell wall width, cell wall thickness and the length of the honeycomb energy absorbing structure can be obtained. Then, we optimize the aluminium honeycomb structure in the primary strut of the legged lander with four landing legs. Finally, the optimal design is investigated using finite element analysis with finite element model validated by experiment. The numerical results show that the optimal design not only impoves the energy absorbing capacity but also meets the practical engineering demand very well.
(5) A crashworthiness optimization design method based on metamodel and MOPSO algorithm for multi-chamber airbag cushioning system is proposed. For the optimization model of the multi-chamber airbag cushioning system, the volume, initial pressure, vented pressure and vented area of each airbag are chosen as the design variables and the acceleration of the centre of gravity (CG) of the cushioned landing equipment and the SEA of the airbag system are selected as the optimization objectives. Then, the crashworthiness of multi-chamber airbag cushioning system is multi-optimized using MOPSO. By using this proposed multi-chamber airbag cushioning system optimization method, we optimize the non-connected multi-chamber airbag cushioning system for airdropping heavy equipment and the connected multi-chamber airbag cushioning system for Mars landing. During the optimization process of the non-connected multi-chamber airbag cushioning system for airdropping heavy equipment, the initial pressure, vented pressure and vented area of the each single airbag are chosen as the design variables. And the acceleration of the centre of gravity (CG) of the cushioned landing equipment and the SEA of the airbag system are selected as the optimization objectives. In order to establish the metamodel of the optimization objectives, we sample the design points using OLHD method and obtain the objective function values using FEA through LS-DYNA. Then, the simplified quartic polynomial function metamodels of the optimization objectives of non-connected multi-chamber airbag system are established by employing the error reduction ratio (ERR) structure-selection techniques. Finally, non-connected multi-chamber airbag cushioning system is optimized on the basis of the metamodels by adopting the MOPSO algorithm to achieve minimum peak acceleration as well as minimum peak rebound velocity of the CG of the landing equipment. Based on the Pareto front obtained by the optimization, we can get the optimal design of non-connected multi-chamber airbag cushioning system for airdropping heavy equipment. During the optimization process of the connected multi-chamber airbag cushioning system for Mars landing, the initial pressure, volume of the single airbag and the connected area between airbag subsystems are chosen as the design variables. And the acceleration of the centre of gravity (CG) of the cushioned landing equipment and the SEA of the airbag system are selected as the optimization objectives. In order to establish the metamodel of the optimization objectives, we sample the design points using the full factorial design method and obtain the objective function values using FEA through LS-DYNA. Then, the polynomial function metamodels of the optimization objectives of connected multi-chamber airbag system are established. Finally, the connected multi-chamber airbag cushioning system is optimized on the basis of the metamodels by adopting the MOPSO algorithm to achieve minimum peak acceleration of the CG of the landing equipment as well as maximum SEA of the airbag system. Based on the Pareto front obtained by the optimization, we can get the optimal design of the connected multi-chamber airbag cushioning system for Mars landing. In additon, we implemented the numerical simulation for the optimal design of the Mars landing connected multi-chamber airbag using the finite element model, which has been validated by experiment. The numerical results show that the energy absorbing capacity of the optimal design of the multi-chamber airbag cushioning system is improved when meeting the demand of the overload of the landing equipment in the practical engineering.
(1)提出了一种基于近似模型和多目标粒子群算法的金属蜂窝结构耐撞性优化设计方法。为了设计出轴向吸能特性最优的六边形金属蜂窝缓冲结构,我们以六边形金属蜂窝的元胞胞壁长、胞壁厚和胞壁夹角为优化设计变量,以其比吸能和峰值压缩应力为优化目标,对该结构的吸能特性进行了耐撞性多目标优化。在优化过程中,首先采用优化拉丁方法在设计变量空间中进行采样,然后应用LS-DYNA计算出每个样本点对应的蜂窝轴向压缩比吸能和峰值应力。根据这些样本点信息,分别构造了目标函数的多项式函数模型、径向基函数模型、Kriging模型、MARS模型和SVR模型,同时对比这些近似模型的精度,发现比吸能的二阶多项式函数模型和峰值应力的三阶多项式函数模型的精度相对最高。最后,基于精度相对最高的目标函数近似模型,采用多目标粒子群算法对六边形金属蜂窝进行了耐撞性多目标优化,获得了不同峰值压缩应力约束条件下的一系列最优六边形金属蜂窝结构。
(2)采用简化的超折叠单元理论推导出了三种常用元胞构型金属蜂窝一一正六边形蜂窝、加强正六边形蜂窝和弯曲元胞蜂窝的轴向平均压缩应力理论公式,进而根据推导出的理论公式进一步计算出了这三种常用预压缩蜂窝材料的比吸能大小。同时,我们把预压缩蜂窝的比吸能和峰值压缩应力作为优化目标,把蜂窝材料的元胞胞壁长和胞壁厚作为优化变量,采用多目标粒子群优化算法对三种预压缩常用蜂窝进行了优化设计。根据该多目标优化结果,可以得到不同峰值压缩应力限制的一系列最优蜂窝结构。此外,根据优化结果我们发现正六边形蜂窝的吸能特性相对最好。
(3)提出了一种基于六等级评价方法的耐撞性评价方法和一种基于近似模型和多目标粒子群算法的蜂窝填充管耐撞性优化设计方法。基于六等级评价方法,分别对蜂窝填充正多边形单层管和蜂窝填充正多边形双层管的轴向压缩比吸能和载荷效率进行了等级评价,从而找出了相对吸能最优的蜂窝填充正多边形管为正九边形管,进而对蜂窝填充正九边形管进行了耐撞性多目标优化。在优化过程中,我们构建了蜂窝填充正九边形单层管和双层管的比吸能以及峰值压缩力的多项式函数近似模型。基于多项式函数近似模型,我们采用多目标粒子群算法对蜂窝填充正九边形单层管和双层管进行了耐撞性优化,分别得到了它们比吸能和峰值压缩力的Pareto最优解集。根据它们的Pareto最优解集,可以分别获得不同压缩力约束条件下的一系列最优蜂窝填充正九边形单层管和蜂窝填充正九边形双层管。此外,我们还发现在相同的压缩力峰值约束条件下,最优蜂窝填充正九边形单层管的单位质量吸能比最优蜂窝填充正九边形双层管的高。这说明在本文所考虑的工况中,蜂窝填充正九边形单层管的吸能特性比蜂窝填充正九边形双层管的好。
(4)提出了一种基于Wierzbicki的蜂窝平均压缩应力公式和多目标粒子群算法的腿式着陆器蜂窝缓冲装置的优化设计方法。采用Wierzbicki的蜂窝平均压缩应力公式计算了腿式着陆器缓冲装置中的蜂窝结构的轴向压缩平均压缩应力和比吸能。从而基于该理论解,采用多目标粒子群算法对腿式着陆器中蜂窝缓冲装置的元胞胞壁厚和胞壁长进行了多目标耐撞性优化。根据优化结果,结合能量守恒原理计算出了缓冲蜂窝的最小轴向长度,从而实现了蜂窝缓冲装置的优化设计。应用该方法对某型四支撑腿着陆器中的主缓冲筒内铝蜂窝进行了优化设计。最后运用经试验验证的有限元力学模型对优化结果进行了分析,分析结果表明该优化设计的缓冲装置能很好地满足工程设计要求。
(5)提出了一种基于近似模型和多目标粒子群算法的多室气囊缓冲系统优化设计方法。在该多室气囊优化设计方法中,以多室气囊中各个气囊的体积、初始充气压力、排气压力和排气面积为优化设计变量,以被缓冲设备的质心加速度以及气囊比吸能为优化目标,采用多目标粒子群算法对多室气囊缓冲系统进行耐撞性多目标优化。本文应用该多室气囊系统优化设计方法分别对重装空投设备非连通多室气囊缓冲装置以及火星着陆连通多室气囊缓冲装置进行了优化设计。在重装空投设备非连通多室气囊缓冲装置的优化设计过程中,首先采用优化拉丁方法在设计变量空间中进行采样,然后应用LS-DYNA计算出每个样本点对应的目标函数值。从而基于采样点信息,采用ERR结构选择技术构建了目标函数的简化的四阶多项式函数近似模型。最后采用多目标粒子群算法获得了目标函数的Pareto最优解集,根据Pareto最优解集,可以得到重装空投设备非连通多室气囊缓冲装置的最优设计。在火星着陆连通多室气囊缓冲装置的优化设计过程中,首先采用全因子法在设计变量空间中进行采样,然后应用LS-DYNA计算出每个样本点对应的目标函数值。从而基于采样点信息,构建了目标函数的多项式函数近似模型。基于近似模型,我们采用多目标粒子群算法对火星着陆连通多室气囊进行了多目标耐撞性优化,获得了目标函数的Pareto最优解集。根据Pareto最优解集,可以得到火星着陆连通多室气囊缓冲装置的最优设计。此外,我们运用了试验验证的火星着陆连通多室气囊缓冲系统有限元力学模型对优化结果进行了分析,分析结果表明该优化设计的多室气囊系统能很好地满足工程设计要求。
Landing system has been widely used in aircraft, aerospace, military and other industries. The cushioning characteristics of a landing system mainly depend on the energy absorption capacity of its energy absorbing structures. It is significant to design an energy absorbing structure with excellent energy absorption capacity, highly light weight and satisfaction with the paractical cushioning requirement. The commonly used energy absorbing structures in landing system are metal thin-walled structures and airbag structures. Based on the finite element analysis (FEA), we mainly investigate the energy absorption characteristics of honeycomb structure and honeycomb-filled tubular structure as well as multi-chamber airbag structure using theoretical and experimental methods in this dissertation. In addition, we optimize the energy absorbing capacity of these energy absorbing structures using the suitable optimization method. The detailed research works of this dissertation are listed as follows:
(1) A crashworthiness optimization design method for metal honeycomb structure based on metamodel and multi-objective particle swarm optimization (MOPSO) algorithm is proposed. In order to design a metal hexagonal honeycomb structure with maximum energy absorbing capacity among all kinds of hexagonal honeycomb structures, we multi-optimize the energy absorbing capacity of the hexagonal honeycomb structures. In our study, the cell wall width, the cell wall thickness and the branch angle are choosed as the design variables while the specifical energy absorption (SEA) and the peak crushing stress (PCS) are selected as the optimization objectives. During the optimization process, the optimal Latin hypercube design (OLHD) method is used for sampling design points in design space firstly. Then, the SEA and PCS of the corresponding honeycomb structure of the sampling points are obtained by employing the nonlinear finite element code LS-DYNA. Based on the informations of these sampling points, the Polynomial functions, Radial Basis Functions (RBF), Kriging, Multivariate Adaptive Regression Splines (MARS) and Support Vector Regression (SVR) are utilized to formulate the metamodels of the two optimal objectives SEA and PCS, respectively. By comparing the accuracy of these metalmodels, we find that the quadratic and cubic polynomial functions are the most accurate ones among these metamodels for predicting SEA and PCS. According to the accurate metamodels of SEA and PCS, the crashworthiness of the metal hexagonal honeycomb structure is multi-optimized by utilizing MOPSO algorithm. A series of optimal designs of metal hexagonal honeycomb structures with the PCSs constrained under different values are finally obtained.
(2) The mean crushing stresses of three commonly used honeycombs (regular hexagonal honeycomb, reinforced regular hexagonal honeycomb and flex honeycomb) are calculated by using the Simplified Super Folding Element (SSFE) theory. Based on the theoretical solutions of the mean crushing stresses, the SEAs of three pre-crushed commonly used honeycombs are calculated, respectively. In our following optimization, the cell wall width and the cell wall thickness are choosed as the design variables while the specifical energy absorption (SEA) and the peak crushing stress (PCS) are selected as the optimization objectives. Then, the crashworthiness of three commonly used pre-crushed honeycombs is optimized by using MOPSO algorithm. According to the multiobjective optimization results, the optimal designs of three commonly used honeycombs with the PCSs constrained under different values can be obtained. In addition, we find that the energy aborption capcity of regular hexagonal honeycomb structure is the most excellent one among that of three kinds of honeycombs.
(3) A six-level judgement method for crashworthiness evaluation and a crashworthiness optimization design method for honeycomb-filled polygonal tubes based on metamodel and MOPSO algorithm are proposed. After ranking the levels of the SEA and crash load efficiency (CLE) of HSPTs and HBPTs under axial loading based on the six-level judgement method, it is found that the honeycomb-filled single and honeycomb-filled bitubular tubes with enneagonal configuration have comparative most excellent energy absorption characteristics among the considered cases. Next, the HSPTs and HBPTs with enneagonal configuration are optimized by adopting MOPSO algorithm to achieve maximum SEA capacity and minimum peak crushing force (PCF). During the process of optimization, accurate metamodels of SEA and PCF of the HSPTs and HBPTs with enneagonal configuration are established. After optimization, we obtain the Pareto fronts of SEA and PCF for the HSPTs and HBPTs with enneagonal configuration. According to the Pareto fronts, the optimal designs of HSPTs and HBPTs with enneagonal configuration are obtained when their PCFs are constrained under different values. By comparing the Pareto fronts of two kinds of honeycomb-filled tubes, we find that the energy absorption capability per unit mass of the optimized honeycomb-filled single enneagonal tubes is more powerful than that of the honeycomb-filled bitubular enneagonal tubes while the PCF constrained under the same level. This indicates that the honeycomb-filled single enneagonal tube is superior to the honeycomb-filled bitubular enneagonal tube in the considered cases.
(4) A crashworthiness optimization design method for cushioning honeycomb in the legged lander based on Wierzbicki's mean crushing stress (MCS) expression for honeycomb is proposed. According to Wierzbicki's expression for mean crushing stress (MCS) of honeycomb, we calculate the MCS and SEA of the honeycomb energy absorbing structure in the legged lander. Based on these theoretical solutions, we optimize the crashwothiness of the honeycomb energy absorbing structure in the legged lander using MOPSO algorithm while the cell wall with and cell wall thickness of the honeycomb structur are selected as the design variables. By using the energy equivalent principle, we can obtain the minimum length of the honeycomb structure according to the previous optimal results. Thus, the optimal solution to the cell wall width, cell wall thickness and the length of the honeycomb energy absorbing structure can be obtained. Then, we optimize the aluminium honeycomb structure in the primary strut of the legged lander with four landing legs. Finally, the optimal design is investigated using finite element analysis with finite element model validated by experiment. The numerical results show that the optimal design not only impoves the energy absorbing capacity but also meets the practical engineering demand very well.
(5) A crashworthiness optimization design method based on metamodel and MOPSO algorithm for multi-chamber airbag cushioning system is proposed. For the optimization model of the multi-chamber airbag cushioning system, the volume, initial pressure, vented pressure and vented area of each airbag are chosen as the design variables and the acceleration of the centre of gravity (CG) of the cushioned landing equipment and the SEA of the airbag system are selected as the optimization objectives. Then, the crashworthiness of multi-chamber airbag cushioning system is multi-optimized using MOPSO. By using this proposed multi-chamber airbag cushioning system optimization method, we optimize the non-connected multi-chamber airbag cushioning system for airdropping heavy equipment and the connected multi-chamber airbag cushioning system for Mars landing. During the optimization process of the non-connected multi-chamber airbag cushioning system for airdropping heavy equipment, the initial pressure, vented pressure and vented area of the each single airbag are chosen as the design variables. And the acceleration of the centre of gravity (CG) of the cushioned landing equipment and the SEA of the airbag system are selected as the optimization objectives. In order to establish the metamodel of the optimization objectives, we sample the design points using OLHD method and obtain the objective function values using FEA through LS-DYNA. Then, the simplified quartic polynomial function metamodels of the optimization objectives of non-connected multi-chamber airbag system are established by employing the error reduction ratio (ERR) structure-selection techniques. Finally, non-connected multi-chamber airbag cushioning system is optimized on the basis of the metamodels by adopting the MOPSO algorithm to achieve minimum peak acceleration as well as minimum peak rebound velocity of the CG of the landing equipment. Based on the Pareto front obtained by the optimization, we can get the optimal design of non-connected multi-chamber airbag cushioning system for airdropping heavy equipment. During the optimization process of the connected multi-chamber airbag cushioning system for Mars landing, the initial pressure, volume of the single airbag and the connected area between airbag subsystems are chosen as the design variables. And the acceleration of the centre of gravity (CG) of the cushioned landing equipment and the SEA of the airbag system are selected as the optimization objectives. In order to establish the metamodel of the optimization objectives, we sample the design points using the full factorial design method and obtain the objective function values using FEA through LS-DYNA. Then, the polynomial function metamodels of the optimization objectives of connected multi-chamber airbag system are established. Finally, the connected multi-chamber airbag cushioning system is optimized on the basis of the metamodels by adopting the MOPSO algorithm to achieve minimum peak acceleration of the CG of the landing equipment as well as maximum SEA of the airbag system. Based on the Pareto front obtained by the optimization, we can get the optimal design of the connected multi-chamber airbag cushioning system for Mars landing. In additon, we implemented the numerical simulation for the optimal design of the Mars landing connected multi-chamber airbag using the finite element model, which has been validated by experiment. The numerical results show that the energy absorbing capacity of the optimal design of the multi-chamber airbag cushioning system is improved when meeting the demand of the overload of the landing equipment in the practical engineering.
引文
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