A progressive approach to predict shot peening process parameters for forming integral panel of Al7050-T7451

In this paper, a progressive approach to predict the multiple shot peening process parameters for complex integral panel is proposed. Firstly, the invariable parameters in the forming process including shot size, mass flow, peening distance and peening angle are determined according to the empirical and machine type. Then, the optimal value of air pressure for the whole shot peening is selected by the experimental data. Finally, the feeding speed for every shot peening path is predicted by regression equation. The integral panel part with thickness from 2 mm to 5 mm and curvature radius from 3200 mm to 16000 mm is taken as a research object, and four experiments are conducted. In order to design specimens for acquiring the forming data, one experiment is conducted to compare the curvature radius of the plate and stringer-structural specimens, which were peened along the middle of the two stringers. The most striking finding of this experiment is that the outer shape error range is below 3.9%, so the plate specimens can be used in predicting feeding speed of the integral panel. The second experiment is performed and results show that when the coverage reaches the limit of 80%, the minimum feeding speed is 50 mm/s. By this feeding speed, the forming curvature radius of the specimens with different thickness from the third experiment is measured and compared with the research object, and the optimal air pressure is 0.15 MPa. Then, the plate specimens with thickness from 2 mm to 5 mm are peened in the fourth experiment, and the measured curvature radius data are used to calculate the feeding speed of different shot peening path by regressive analysis method. The algorithm is validated by forming a test part and the average deviation is 0.496 mm. It is shown that the approach can realize the forming of the integral panel precisely.     

基于改进粒子群优化模糊控制的MPPT算法研究

在光照强度和温度变化时,常规的最大功率点跟踪(MPPT)算法难以快速准确地跟踪光伏系统最大功率点。针对此问题,设计了一种改进粒子群优化算法(PSO)的模糊控制器。首先,依据常规MPPT特性,设计了一种带调整因子的模糊控制算法以快速收敛到最大功率点；然后,采用参数自适应PSO对设计的模糊控制器调整因子进行动态优化。仿真结果表明:所设计的参数自适应PSO优化模糊控制器能快速准确地跟踪最大功率点,保证了MPPT的动态响应速度和稳态精度,提高了光伏系统的工作效率。     

蜻蜓起飞过程飞行特征实验

针对蜻蜓自由起飞过程和准自由起飞过程进行实验观测,采用两个光轴相互垂直的高速摄像机进行拍摄,通过特征点匹配和三维重构方法准确地捕捉了两种起飞过程中蜻蜓身体和翅膀的运动参数,并进行运动特征分析与对比。实验结果表明:蜻蜓在自由起飞过程中采用同步振翅,离地后逐步转换成异步振翅(约110°),最大瞬时竖直加速度可以达到20m/s2;在准自由起飞过程中采用异步振翅(相位差180°),之后相位差逐步降低,最大瞬时竖直加速度为12m/s2;此外发现同步振翅、大攻角下拍及大拍动角有利于升力的产生。      

Inverse identification of constitutive parameters of Ti2AlNb intermetallic alloys based on cooperative particle swarm optimization

Ti₂AlNb intermetallic alloy is a relatively newly developed high-temperature-resistant structural material, which is expected to replace nickel-based super alloys for thermally and mechanically stressed components in aeronautic and automotive engines due to its excellent mechanical properties and high strength retention at elevated temperature. The aim of this work is to present a fast and reliable methodology of inverse identification of constitutive model parameters directly from cutting experiments. FE-machining simulations implemented with a modified Johnson-Cook (TANH) constitutive model are performed to establish the robust link between observables and constitutive parameters. A series of orthogonal cutting experiments with varied cutting parameters is carried out to allow an exact comparison to the 2D FE-simulations. A cooperative particle swarm optimization algorithm is developed and implemented into the Matlab programs to identify the enormous constitutive parameters. Results show that the simulation observables (i.e., cutting forces, chip morphologies, cutting temperature) implemented with the identified optimal material constants have high consistency with those obtained from experiments, which illustrates that the FE-machining models using the identified parameters obtained from the proposed methodology could be predicted in a close agreement to the experiments. Considering the wide range of the applied unknown parameters number, the proposed inverse methodology of identifying constitutive equations shows excellent prospect, and it can be used for other newly developed metal materials.     

基于MapReduce的CME参数识别模型并行计算技术

日冕物质抛射（Coronal Mass Ejection，CME）参数识别模型是太阳风预报过程的重要组成部分.在空间环境预报业务中，为提高太阳风预报的准确率，需要提高CME参数识别的精度.模型以计算任务串行的方式运行，运算效率低导致模型运算时间长，不能满足这种需求.CME参数识别模型的物理运算过程相互不独立，其在单节点上的运行方式不能满足并行化要求.基于MapReduce的并行计算框架，改进了CME参数识别模型的计算流程，提出CDMR（CME detection under MapReduce）方法，实现了CME参数识别模型的并行计算，并对比分析CME参数识别模型在串行计算和MapReduce并行计算下的运行时间，提高了模型的识别精度和计算效率.      

基于航空煤油重整的SOFC-GT混合动力系统性能

建立了基于航空煤油重整固体氧化物燃料电池-涡轮发动机（SOFC-GT）混合动力系统仿真模型,比较了两种回热方式的重整装置以及不同涡轮布置位置时的系统性能变化,优选出最佳的混合动力系统架构。进一步分析了压气机压比、燃料利用率、燃油流量以及空气流量等运行参数对SOFC-GT混合动力系统性能的影响。研究结果表明：设计点工况下,最佳混合动力系统的发电效率能达到45%,体现出良好的系统性能;当燃料利用率为082时混合动力系统的效率和功率最高;随着燃油流量(0051 1~0058 4 mol/s)的增加,混合动力系统的效率和功率均增加;而随着压气机压比(25~33)或者空气流量(37~44 mol/s)的增加,混合动力系统的效率和功率都减小。     

基于精益6滓的航空高强钢零件大尺寸面轮廓度 数控加工参数优化

针对某航空高强钢零件大尺寸面轮廓度数控加工合格率较低问题,利用精益6σ方法,依据DMAIC的研究路径,充分运用箱线图、等方差检验、单因子方差分析等方法和工具,分析了“人、机、料、法、环、测”6大方面的操作者、加工刀具、装夹方式、主轴转速、切削量、进给速度、切削方式7个因素,确定刀具尺寸、切削量、进给速度为关键影响因素;通过建立面轮廓度与7个影响因素之间的GLM模型,得出影响流程输出的3个关键影响因素的最佳组合,并在此基础上对工艺参数进行优化。结果表明:该零件的数控加工工艺流程改进后,减少了加工过程中的人工调试检查环节,缩短了加工调试验证时间,大尺寸面轮廓度数控加工合格率从80%提高到96%以上,取得了较好的经济效益。     

M40/4211 复合材料层合板铣削加工试验

通过分析碳纤维复合材料的性能特点及对切削加工性能的影响,提出了铣削刀具材料和几何结构形式的选用原则,介绍了几种适于碳纤维复合材料铣削的加工刀具。针对碳纤维复合材料中常用的M40/4211复合材料层合板进行加工缺陷试验和切削试验,总结出影响M40/4211复合材料层合板加工质量的因素及规律,得到每种刀具加工M40/4211复合材料层合板的最佳加工参数,较高的切削速度配合恰当的进给速度可以有效提高M40/4211复合材料层合板的加工质量和加工效率。     

结构特征参数对发动机支点同心度的影响研究

航空发动机静子支点作为转子的支撑部位,由于制造工艺、装配误差和长时间工作的影响,较易出现支点不同心的现象。基于形状和位置公差理论,建立了一种发动机支点同心度的计算模型,并对某发动机的支点同心度分布进行了仿真计算。通过分析影响支点同心度的关键结构参数和测量支点同心度试验,提出了同心度的控制方法。结果表明:采用本文所述理论计算和控制方法,可准确地判断出发动机支点同心度是否符合标准,以便有针对性地选择调整措施,进而提高了发动机的装配质量,有效避免转、静子不同轴引起的碰摩问题,减小了发动机整机振动出现的几率。