公共设施投资的决策模型探讨

公共设施投资的成本与产生的社会福利如何比较，社会效益的提高有多大等等一系列基本问题为政府所关心。这一问题的解决需要通过结合公共经济学的原理与近几年出现的一些新观点做出系统的可行性分析模型加以解决。本文就是基于公共经济学的理论并结合了笔者的一些新的观点所作的常识性的探索。     

颈动脉内血流动力学特征受向前加速度影响的数值模拟

人们在日常或某些特殊条件下常会面临方向和大小发生迅速变化的加速度环境,已有研究发现加速度环境会影响心血管系统生理、病理特征。利用计算机模拟方法详细研究了向前加速度环境下人体颈动脉内的血流动力学参数变化规律。结果表明:加速度会对颈动脉内压力、压力梯度、壁面剪切应力等与血管生理、病理现象密切相关的血流动力学参数产生显著影响。研究结果为加速度环境下颈动脉生理、病理研究提供了一定的理论依据,也为航空航天领域加速度环境下人员防护提供参考。      

期望状态序列导向的深空探测器规划修复方法

Aiming at the challenges caused by the persistence, concurrency and energy consumption of probe actions, a plan repair method of deep space probe based on the expected state sequence is proposed. In this method, the expected state sequence is formed of the expected effect of the unfinished action and the expected precondition of the unexecuted action in the pre designed plan, according to the execution status of the action. The expected state sequence is an ordered set of states with mixed logic and energy, providing subgoals for plan repair and also transforming the plan repair problem into the state transition path searching problem. During the search, the plan repair strategy with energy supply priority is proposed, which separates the logic repair from energy repair to reduce the difficulty of solving the problem. And this method enables the probe to recover from plan failure autonomously. Finally, the effectiveness and rationality of the proposed method are verified through simulation by taking the Mars Orbiter as an example.     

月球表层采样样品智能确认方法

表层采样是月球采样探测的重要方式，样品智能确认有助于提升工作效率与复杂问题处理能力。结合月球表层采样铲挖工作过程，分析了铲挖过程中臂载相机图像的特点，模仿有人参与识别过程，提出了层次解耦的月球样品智能识别流程，利用深度学习方法构建了一类深度卷积识别网络，完整地描述了图像、特征、标记在网络中的正反传递关系，并在月球表层采样地面试验中进行了验证，结果表明该方法对不同光照、不同背景、不同过程、不同形态的样品，具有较好的泛化识别能力，误识别率优于8.1%，平均单幅识别时间约0.7 s。     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

Stall flutter prediction based on multi-layer GRU neural network

The modeling of dynamic stall aerodynamics is essential to stall flutter, due to the flow separation in a large-amplitude pitching oscillation process. A newly neural network based Reduced Order Model (ROM) framework for predicting the aerodynamic forces of an airfoil undergoing large-amplitude pitching oscillation at various velocities is presented in this work. First, the dynamic stall aerodynamics is calculated by solving RANS equations and the transitional SST-γ model. Afterwards, the stall flutter bifurcation behavior is calculated by the above CFD solver coupled with structural dynamic equation. The critical flutter speed and limit-cycle oscillation amplitudes are consistent with those obtained by experiments. A newly multi-layer Gated Recurrent Unit (GRU) neural network based ROM is constructed to accelerate the calculation of aerodynamic forces. The training and validation process are carried out upon the unsteady aerodynamic data obtained by the proposed CFD method. The well-trained ROM is then coupled with the structure equation at a specific velocity, the Limit-Cycle Oscillation (LCO) of stall flutter under this flow condition is predicted precisely and more quickly. In order to predict both the critical flutter velocity and LCO amplitudes after bifurcation at different velocities, a new ROM with GRU neural network considering the variation of flow velocities is developed. The stall flutter results predicted by ROM agree well with the CFD ones at different velocities. Finally, a brief sensitivity analysis of two structural parameters of ROM is carried out. It infers the potential of the presented modeling method to depict the nonlinearity of dynamic stall and stall flutter phenomenon.     

Collaborative image compression and classification with multi-task learning for visual Internet of Things

Widespread deployment of the Internet of Things(Io T) has changed the way that network services are developed, deployed, and operated. Most onboard advanced Io T devices are equipped with visual sensors that form the so-called visual Io T. Typically, the sender would compress images, and then through the communication network, the receiver would decode images, and then analyze the images for applications. However, image compression and semantic inference are generally conducted separately, and t...     

Al2O3—Ti系梯度功能材料的优化设计

对Ａｌ３Ｏ３－Ｔｉ系梯度功能材料在制备过程中产生的残余热应力进行了弹性有限元法分析。讨论了梯度层数目,梯度层厚度和成分梯度指数对应力大小和分布的影响,优化出了各项最佳参数。非线度功能材料与优化后的梯度功能材料的残余热应力对比结果显示;梯度功能材料缓和热应力的效果十分显著。     

政府采购扶持科技型中小企业发展的对策建议

我国科技型中小企业是科技创新的主要力量,但存在制约其发展的诸多问题,如融资难、科技投入不足、竞争力弱等,说明科技型中小企业需要得到政府的扶持。发达国家的成功经验可供我国参考,即具有明确的政府采购扶持中小企业的管理制度,具有有效的监督和申诉制度,积极扶持科技型中小企业开拓国内外政府采购市场。我国政府可利用政府采购来扶持科技型中小企业。具体对策是：完善政府采购的法律制度,加强对知识产权的保护力度,制定科技型产品及国货的认证制度,加大采购力度,建立中小企业管理委员会,完善政府采购监督机制。     

脉冲展宽对深空激光通信的影响与补偿研究

深空激光通信系统下行链路的脉冲位置调制PPM（Pulse Position Modulation）信号在经过大气信道传输和单光子探测器接收时,将出现脉冲展宽效应,引起通信系统性能下降。分析了大气信道中的淡积云云层散射、大气湍流与气溶胶散射和单光子探测器的抖动特性所引起的脉冲展宽效应。在此基础上,仿真分析了淡积云云层物理厚度对不同PPM调制阶数下通信速率的影响,并研究了单光子探测器引起的脉冲展宽产生的抖动损失。为补偿脉冲展宽的影响,提出了一种基于时隙似然比解调的补偿方法,通过仿真验证了该方法能够有效降低深空PPM激光通信链路中脉冲展宽对通信误码率的影响。该研究对分析和提升深空PPM激光通信系统的链路性能具有一定的参考意义。