多工况悬架下摆臂结构优化设计方法研究

采用了多种优化设计方法,以某悬架结构为例进行了结构优化设计方法研究.通过对车辆行驶工况和对车体空间布置的分析,建立了拓扑优化可设计域和非可设计域,完成了悬架结构的拓扑优化设计,并建立了工程结构.基于强度分布与应力干涉理论,将可靠性理论和优化方法相结合,进行了可靠性优化设计.其优化结果与尺寸优化和形状优化结果进行了对比,证明了优化设计方法的有效性和可行性,为工程结构提供了一种新设计思路.     

Tin and tin–titanium as catalyst components for reversible hydrogen storage of sodium aluminium hydride

This paper is concerned with the effects of adding tin and/or titanium dopant to sodium aluminium hydride for both dehydrogenation and re-hydrogenation reactions during their reversible storage of molecular hydrogen. Temperature programmed decomposition (TPD) measurements show that the dehydrogenation kinetics of NaAlH₄ are significantly enhanced upon doping the material with 2 mol% of tributyltin hydride, Sn(Bu)₃H but the tin catalyst dopant is shown to be inferior than titanium. On the other hand, in this preliminary work, a significant synergetic catalytic effect is clearly revealed in material co-doped with both titanium and tin catalysts which shows the highest reversible rates of dehydrogenation and re-hydrogenation (after their hydrogen depletion). The re-hydrogenation rates of depleted Sn/Ti/NaAlH₄ evaluated at both 9.5 and 140 bars hydrogen are also found to be favourable compared to the Ti/NaAlH₄, which clearly suggest the importance of the catalyst choice. Basing on these results some mechanistic insights for the catalytic reversible dehydrogenation and re-hydrogenation processes of Sn/Ti/NaAlH₄ are therefore made.     

An enhanced artificial hummingbird algorithm and its application in truss topology engineering optimization

In view of the shortcomings such as slow search speed, low optimization precision and premature convergence of artificial hummingbird algorithm, an enhanced artificial hummingbird algorithm based on golden sine factor named DGSAHA is proposed. Firstly, chaos mapping is used to generate the initial candidate solution to increase the diversity of the population, which lays the foundation for the global search. Then, perturb the individuals by means of the differential variation between individuals on the group, thereby enhancing the diversity of the population, preserving the excellent individuals, eliminating the inferior individuals, and guiding the search process to approach the global optimal solution, avoiding the phenomenon of premature convergence. Finally, the golden sine factor were introduced in the guided foraging stage is conducive to the full exploration of the global optimal solution, reducing the search space for individuals to approach the optimal solution. And, it facilitates the balance between “exploration” and “exploitation” of algorithm. Thereby, the accuracy and speed of the DGSAHA can be improved to a certain extent. 25 classic functions, the CEC2014 and CEC2019 benchmark functions were tested, and several representative meta-heuristic algorithms and its improved algorithm are compared for evaluate the validity of DGSAHA. Meanwhile, the dimensional scalability of the variable-dimensional test function is discussed. The results of non-parametric statistical analysis and performance index show that DGSAHA in this paper has better comprehensive optimization performance, significantly improves the search speed and convergence precision, and has strong ability to get rid of the local optimal solution. Finally, the performance of DGSAHA and the practicability of truss structure are answered by three engineering examples of plane and space truss topology optimization problem. This optimization problem considers not only the static constraints such as stress, displacement and buckling, but also the dynamic constraints of frequency and motion stability. In order to avoid singularity and unnecessary analysis, the stiffness, mass and load matrices are reconstructed in finite element analysis. A lighter truss structure than the existing solution is obtained. The validity, extensibility and practicability of the algorithm are further illustrated.     

基于完全信息多人动态博弈的车道选择模型

针对集群车辆驾驶员的车道选择行为,着眼物联网背景,综合考虑车辆集群态势、驾驶倾向性等影响驾驶员行为的因素,建立基于完全信息多人动态博弈的车道选择模型。通过分析不同策略组合下的驾驶员收益,运用逆向归纳法,求解子博弈精炼纳什均衡,得到驾驶员的最优车道选择策略。应用实车实验等手段验证模型,结果表明,所建模型能够较为客观地反映驾驶员车道选择行为及交通流特性。     

Multiple objective dynamic programming with forward filtering

In this paper we present a heuristic method for reducing the computational burden in multiple objective dynamic programming (MODP). Using techniques originally suggested for multiple objective linear programming, the solution set for each state (stage) are filtered, giving a representative subset of the set of efficient ways of attaining that state (stage). The method allows for considerable reductions in the amount of storage required to solve the problem, and in the dimensionality of the problem in solution space. It does not guarantee that all the identified solutions are non-dominated; however, the examples presented suggest that the representation of the subset of all efficient solutions is a good one.     

Increased magnetization of reduced graphene oxide by nitrogen-doping

N-doped graphene (NG) has been prepared by annealing reduced graphene oxide (RGO) in ammonia. The magnetic properties of RGO and NG have been studied. The results showed that doping RGO with N at a relatively low temperature (⩽600 °C) can increase its magnetization, and which can be increased by 64.1% at the annealing temperature of 500 °C.     

火花点火激发自燃着火稳定燃烧边界条件的试验

火花点火激发自燃着火(SIAI)燃烧具有火花点火和自燃着火两段着火特性,能够有效控制燃烧过程的压升率,可以显著拓展HCCI燃烧方式的可适用负荷范围.但SIAI燃烧的稳定燃烧比较困难,需要对混合气状态进行精确控制.在一台双缸汽油机上通过控制进气温度和喷油量实现了对混合气状态和能量密度的灵活控制,研究了SIAI稳定燃烧的边界条件.结果表明,SIAI燃烧的稳定实现需要满足:理论空燃比附近的空燃比以保证点火稳定;压缩上止点处的混合气温度在950～1,050,K内以保证自燃的实现;压缩上止点处混合气能量密度在12.5～22.5,MJ/m3内以实现自燃并抑制爆震.     

Load balancing for cluster systems under heavy-tailed and temporal dependent workloads

Large-scaled cluster systems have been employed in various areas by offering pools of fundamental resources. Efficient allocation of the shared resources in a cluster system is a critical but challenging issue, which has been extensively studied in the past few years. Despite the fact that existing load balancing policies, such as Random, Join Shortest Queue and size-based polices, are widely implemented in actual systems due to their simplicity and efficiency, the performance benefits of these policies diminish when workloads are highly variable and temporally correlated. In this paper, we propose a new load balancing policy, named ADuS, which attempts to partition jobs according to their present sizes and further rank the servers based on their loads. By dispatching jobs of similar sizes to the corresponding ranked servers, ADuS can adaptively balance user traffic and system load in a cluster and thus achieve significant performance benefits. Extensive trace-driven simulations using both synthetic and real traces show the effectiveness and robustness of ADuS under many different environments.