Advanced analytical model for orbital aerodynamic prediction in LEO

The growing interest in low earth orbit (LEO) applications demands for accurate modeling of orbital aerodynamics. But classical analytical models of aerodynamic coefficients in free molecule flow, such as the Sentman’s model, Schamberg’s model and Schaaf-Chambre model, were built upon over simplistic gas-surface interaction models, which degrade the fidelity of aerodynamic prediction. This work presents a new analytical model of orbital aerodynamic coefficients based on the state-of-the-art Cercignani–Lampis–Lord (CLL) gas-surface interaction model, where lobular quasi-specular scattering pattern and separate accommodation degree for different velocity components can be well captured. A key component of the new model is a rigorous function approximation solution of the reflected normal momentum flux based on the CLL model which is derived for the first time and is validated within 1% for any hypothermal flow and surface accommodation conditions. Closed-form analytical solutions of aerodynamic coefficients for simple convex geometries are obtained and exhibit high accuracy (within 0.1%) in typical LEO scenarios. The new analytical model surpasses the classical models in some important aspects, such as overcoming the diffuse scattering hypothesis constraint, considering the variation of normal momentum exchange with the surface incidence angle and being applicable in any hypothermal flow situation. In virtue of the advanced CLL model and feasibility of coupling with the panel method technique, the new analytical model is promising to provide more accurate predictions on the orbital aerodynamic coefficients for LEO applications.     

Coupled evolution of piston asperity and cylinder bore contour of piston/cylinder pair in axial piston pump

The wear condition of the piston/cylinder pair is crucial to the performance and reliability of the axial piston pump. The hard piston surface, the soft cylinder bore surface, and the interface oil film affects each other during the wear process. Specifically, in the mixed lubrication region, the geometry of the hard piston surface asperity directly affects the wear of soft cylinder bore surface, while the asperities may deform or even degrade when penetrating and sliding against the cylinder bore. So far, there is no suitable method to simulate their coupled evolution. This paper proposed a wear process simulation model considering the real-time interaction between the elasto-plastic deformation of the piston surface asperity, the wear contour of the cylinder bore, and the lubrication condition of the interface. An offline library of the elasto-plastic constitutive behavior of the asperity based on the finite element method (FEM) is established as a part of the simulation model to precisely analyze the deformation and degradation of the asperity and quickly invoke them in the numerical wear process simulation. The simulation and experimental results show that the piston asperity and the cylinder bore contour converge to a steady state after running-in for about 0.5 h. The distribution of the simulated asperity degradation and wear depth is also verified by the experiment.     

Quantitative contribution of climate change and anthropological activities to vegetation carbon storage in the Dongting Lake basin in the last two decades

The Dongting Lake Basin is an important hydrological regulation and flood storage area in the Yangtze River Basin, which plays an important role in maintaining regional ecological security. The watershed vegetation and its carbon sequestration capacity have changed dramatically due to climate change and human activities in the last two decades. In this paper, the monthly and annual vegetation net primary productivity (NPP) of the Dongting Lake basin during 2000 to 2020 was firstly estimated using the improved Carnegie-Ames-Stanford Approach (CASA) model. Then the multi-year NPP change trend and its significance were analyzed based on Theil-Sen median and Mann-Kendall method. Subsequently, the Hurst index was used to simulate the vegetation NPP persistence in the study area. Finally, the driving mechanisms of vegetation NPP changes in the study area were explored using partial correlation coefficients and residual analysis. The results demonstrated that: 1) The annual average NPP in the basin showed a fluctuating and increasing trend from 273.54 to 718.30 g C/m²·yr¹ during 2000 to 2020, and except for autumn, all seasons (spring, summer, winter) and annual NPP series showed an upward trend. The spatial distribution of vegetation NPP is characterized by an asymmetrical horseshoe shape in general, with high values in the west, south and east parts, and low values in the Lake area; 2) During the study years, about 84.38 % of the basin area showed a significant and extremely significant increase of NPP; 3) The future trend of vegetation NPP in the basin shows that the area of decrease (22.79 %) is more than the area of increase (11.35 %). The Chang-Zhu-Tan urban agglomeration will generally show a continuous and extremely significant reduction trend, while parts of Dongting Lake will show a continuous and extremely significant increase trend; 4) The correlation between solar radiation and NPP is stronger than the other two meteorological factors (precipitation and temperature). Temperature has a significant inhibitory effect on NPP, solar radiation has a significant promoting effect on NPP, and the effect of precipitation on NPP was relatively complicated. The relative importance of meteorological factors on vegetation NPP was ranked as follows: solar radiation > precipitation > temperature. The impacts of both climate change and human activities on NPP changes showed great spatial variability, and the positive contributions (89.81 % for climate change and 82.87 % for human activities) were both greater than the negative contributions.     

变循环发动机风车起动建模及仿真研究

为了满足变循环发动机风车起动性能仿真的需求，建立了变循环发动机部件级风车起动模型。针对旋转部件等熵效率不连续的问题，提出使用换算扭矩代替等熵效率的方法，给出了旋转部件全转速特性拓展方法。提出了考虑点火及燃烧稳定性的燃烧室稳定性模型。考虑了变循环发动机的8个可调参数，采用差分进化算法对变循环发动机的风车及风车起动性能进行了优化。结果表明，风车状态时，变循环发动机在单外涵模态具有更高的核心机物理转速，有利于点火之后核心机物理转速快速趋于其慢车值。单外涵模态时，变循环发动机在风车状态的可调参数仅与飞行马赫数有关，为了保持较高的核心机物理转速，后涵道引射器外涵面积需随飞行马赫数的增加而减少，其余参数皆固定在其最佳值。飞行高度6km、马赫数0.8时，变循环发动机在单外涵模态下的风车起动时间为1.4s。风车起动过程中燃油流量的增长主要受燃烧稳定性所约束。通过对可调参数的优化，可使变循环发动机在风车起动过程中的关键性能参数最大程度的逼近其限制值，从而减少风车起动时间。     

Orbital error propagation considering atmospheric density uncertainty

Due to the influence of various errors, the orbital uncertainty propagation of artificial celestial objects while orbit prediction is required, especially in some applications such as conjunction analysis. In the orbital error propagation of artificial celestial objects in low Earth orbits (LEOs), atmospheric density uncertainty is one of the important factors that require special attention. In this paper, on the basis of considering the uncertainties of position and velocity, the atmospheric density uncertainty is also taken into account to further investigate the orbital error propagation of artificial celestial objects in LEOs. Artificial intelligence algorithms are introduced, the MC Dropout neural network and the heteroscedastic loss function are used to realize the correction of the empirical atmospheric density model, as well as to provide the quantification of model uncertainty and input uncertainty for the corrected atmospheric densities. It is shown that the neural network we built achieves good results in atmospheric density correction, and the uncertainty quantization obtained from the neural network is also reasonable. Moreover, using the Gaussian mixture model - unscented transform (GMM-UT) method, the atmospheric density uncertainty is taken into account in the orbital uncertainty propagation, by adding a sampled random term to the corrected atmospheric density when calculating atmospheric density. The feasibility of the GMM-UT method considering atmospheric density uncertainty is proved by the further comparison of abundant sampling points and GMM-UT results (with and without considering atmospheric density uncertainty).