Collaborative optimization design of process parameter and structural topology for laser additive manufacturing

High-resolution laser additive manufacturing (LAM) significantly releases design freedom, promoting the development of topology optimization (TO) and advancing structural design methods. In order to fully take advantage of voxelated forming methods and establish the quantitative relationship between the mechanical properties of printing components and multiple process factors (laser- and process- parameters), the concurrent optimization design method based on LAM should cover the process-performance relationship. This study proposes a novel artificial intelligence-facilitated TO method for LAM to concurrently design microscale material property and macroscale structural topology of 3D components by adopting heuristic and gradient-based algorithms. The process–structure–property relationship of selective laser sintering is established by the back propagation neural network, and it is integrated into the TO algorithm for providing a systematic design scheme of structural topology and process parameter. Compared with the classical optimization method, numerical examples show that this method is able to improve the mechanical performance of the macrostructure significantly. In addition, the collaborative design method is able to be widely applied for complex functional part design and optimization, as well as case studies on artificial intelligence-facilitated product evaluation.     

一种非线性状态估计器的算法实现与解耦简化

本文以机载火控系统中的目标状态估计器(TSE)为例,探讨了一类非线性状态估计器的算法及简化方法。文中给出了TSE的数学模型,分析了其特点,并作了形式上的变换;而后用最优卡尔曼滤波算法实现了状态估计。最后,利用其结构特点,作了算法解耦,故大大减少了计算量和计算机内存,获得了令人满意的估值精度。     

基于相关性分析和神经网络的直接推力控制

传统的发动机控制是将一些可测量参数作为被控制量,如转速和压比,因为可由它们推算出推力。但由于推算的过程不准确,为保证发动机安全运行,在发动机的设计过程中常常保留了较大的裕度。而直接推力控制可以降低这些裕度,充分发挥发动机的性能。针对在飞行中推力无法直接测量的情况,本文使用了相关性分析和神经网络技术设计了非线性推力估计器,使用若干测量参数作为输入,实时计算出发动机的推力值。并针对发动机使用的实际情况,使设计出的估计器不但可以估计额定发动机的推力,而且可以估计非额定发动机的推力。在仿真结果中,估计出的推力跟踪上了正常和非额定发动机的推力。     

自适应遗传神经网络算法在推力估计器设计中的应用

为了在全包线内能够准确方便估计出航空发动机推力,提出了一种自适应遗传神经网络算法:将遗传算法和神经网络技术相结合充分发挥遗传算法和神经网络各自的全局收敛性和局部搜索快速性的优点,其中通过自适应概率遗传操作及局部寻优算子直接优化出神经网络拓扑结构及权值(包括阈值),克服了神经网络隐层节点需凭经验尝试的缺点和神经网络对初始权值(包括阈值)敏感的缺点,再应用神经网络对上述优化的权值(包括阈值)进行"精调",最后设计出全包线推力估计器.经验证,此推力估计器具有较高估计精度和良好泛化能力.      

Gradient pattern analysis of short solar radio bursts

We analyze the weak component of the localized temporal pattern variability of 3 GHz solar burst observed by the Ondrejov radiospectrograph. A complex, short and weak impulsive sample from the time series was analyzed by applying a method based on the gradient pattern analysis and discrete wavelet decomposition. By analyzing canonical temporal variability patterns we show that the new method can reliably characterize the phenomenological dynamical process of short time series (N ? 10³ measurements) as the radio burst addressed here. In the narrowest sense, by estimating the mutual information distance in the gradient spectra, we show that the fluctuation pattern of the short and weak 3 GHz impulsive solar burst, with energetic amplitudes <350 SFU, is closer to the intermittent and strong MHD turbulent variability pattern.     

基于梯度法和最大熵方法的变循环发动机加速控制规律设计

为了解决变循环发动机(VCE)加减速控制规律设计问题,提出了一种基于梯度法和最大熵方法的VCE加速控制规律优化设计方法.通过求加速时间对几何变量的导数确定几何变量调整的方向和步长,逐步得出加速过程的几何调节规律.计算VCE加速过程时,采用过渡态直接模拟方法保证发动机的喘振裕度、燃烧室油气比和涡轮进口总温均满足约束条件....     

Mobility control of unmanned aerial vehicle as communication relay in airborne multi-user systems

In this paper, a model-based adaptive mobility control method for an Unmanned Aerial Vehicle(UAV) acting as a communication relay is presented, which is intended to improve the network performance in airborne multi-user systems. The mobility control problem is addressed by jointly considering unknown Radio Frequency(RF) channel parameters, unknown multi-user mobility, and non-available Angle of Arrival(AoA) information of the received signal. A Kalman filter and a least-square-based estimation algorithm are used to predict the future user positions and estimate the RF channel parameters between the users and the UAV, respectively. Two different relay application cases are considered: end-to-end and multi-user communications. A line search algorithm is proposed for the former, with its stability given and proven, whereas a simplified gradient-based algorithm is proposed for the latter to provide a target relay position at each decision time step, decreasing the two-dimensional search to a one-dimensional search. Simulation results show that the proposed mobility control algorithms can drive the UAV to reach or track the optimal relay position movement, as well as improving network performance. The proposed method reflects the properties of using different metrics as objective network performance functions.     

基于核方法的航空发动机推力估计器设计

鉴于实现航空发动机的直接推力控制需要高精度及高可靠性的推力估计器,基于核方法,提出了结合全局核k-means聚类与鲁棒最小二乘支持向量回归机的推力估计器设计方案,通过核诱导的隐性映射将原始输入数据映射到特征空间,使数据样本特征信息被提取并放大,具有更好的可分性.在每个聚类内设计推力子估计器,用鲁棒代价函数代替最小二乘代价函数,增强了推力估计器的整体鲁棒性.通过对涡扇发动机的仿真试验表明,本推力估计器设计方法能够满足直接推力控制需要,与其它方法相比,在估计精度及鲁棒性上存在一定优势.     

几何分布产品定数截尾场合下参数的点估计

本文给出几何分布产品定数截尾场合下参数点估计的几种方法,并通过随机模拟的方法考察了估计的精度。     

Quantitative analyses of complexity and nonlinear trend of radio refractivity gradient in the troposphere

In this paper, the complexity and nonlinear trends of Radio Refractivity Gradient (RRG) in the troposphere over selected locations in Nigeria are analyzed and discussed extensively. The RRG is an important parameter in estimating path clearance and propagation effects such as ducting, surface reflection and multi-path on terrestrial line of-sights links. Also, radio wave signal propagating in the troposphere is affected by unpredictability of a weather condition which includes the variations of meteorological parameters such as temperature, pressure and relative humidity. The complex state of the atmosphere, which is the medium for the transmission of radio signals tend to have very strong influence such as scintillation and ducting on the quality of the radio signal, amplitude and phase. Variations in the meteorological parameters also induce variations in the refractive index of the atmosphere which in-turn results in the effect known as radio refractivity. For effective prediction and modeling of radio signal propagation, one should be able to characterize the nature and predictability of the computed RRG information. Chaotic Quantifiers (CQ) such as Phase Plot Reconstruction (PPR), Average Mutual Information (AMI), False Nearest Neighbor (FNN), Recurrence Plot (RP) and Recurrence Quantification Analyses (RQA) are used to assess the RRG. The information reveal, however, is based on the prediction techniques, design and frequency planning of microwave networks which may be useful for optimum performances during atmospheric turbulence.