An overview of the discussions of the working group on Low-Z stars is presented. Key questions addressed include how the abundances of lithium observed in these stars should be compared to that produced in the Big Bang. Evidence for and against a small star-to-star variation in Li abundances is reviewed, and whether such a variation, if real, necessarily indicates that stellar depletion has occurred, necessitating correction to the value compared to primordial nucleosynthesis calculations. A second key question concerns how and where the light elements are produced. Taken together, their abundance ratios strongly suggest that in low-Z stars the light elements other than 7Li are produced by cosmic ray spallation. The most recent evidence suggests that a minority of this spallation happens in the general interstellar medium, and that a larger fraction might happen in the immediate vicinity of Supernovae, possibly producing observable star-to-star variation. Finally, the question of the overall metallicity of the Galaxy is discussed. How homogeneous in space and time is its evolution? Can we identify subsystems or individual stars which indicate a pregalactic contribution to the galactic metallicity?
Charge exchange(CEX) ions could inflict severe damages on the ion thruster optical system. This article is aimed at investigating the characteristics of the CEX ions and their influences upon the optical system by means of particle-in- cell(PIC) ion simulation and Monte Carlo collision(MCC) methods. The results from numerical simulation indicate that despite the fact that CEX ions appear in the entire beamlet region near the ion optical system, the ones that present themselves downstream of the accelerator grid have good reason for attracting more attention. As their trajectories are significantly affected by the local electric field, a great number of CEX ions are accelerated toward grids resulting in sputtering erosion. When the influences of the CEX ions are considered in the numerical simulation, there could hardly be observed augments in the screen grid current, but the accelerator grid current increases from zero to 1. 4% of the beamlet current. It can be understood from the numerical simulation that the CEX ions formed in the region far downstream of the accelerator grid should be blamed for the erosion on the downstream surface of the accelerator grid. 相似文献
Results of a statistical variation of total ion density observed in the vicinity of epicenters as well as around magnetically conjugated points of earthquakes are presented in this paper. Two data sets are used: the ion density measured by DEMETER during about 6.5?years and the list of strong earthquakes (MW?≥?4.8) occurring globally during this period (14,764 earthquakes in total). First of all, ionospheric perturbations with 23–120?s observation time corresponding to spatial scales of 160–840?km are automatically detected by a software (64,287 anomalies in total). Second, it is checked if a perturbation could be associated either with the epicenter of an earthquake or with its magnetically conjugated point (distance?<?1500?km and time?<?15?days before the earthquake). The index Kp?<?3 is also considered in order to reduce the effect of the geomagnetic activity on the ionosphere during this period. The results show that it is possible to detect variations of the ionospheric parameters above the epicenter areas as well as above their conjugated points. About one third of the earthquakes are detected with ionospheric influence on both sides of the Earth. There is a trend showing that the perturbation length increases as the magnitude of the detected EQs but it is more obvious for large magnitude. The probability that a perturbation appears is higher on the day of the earthquake and then gradually decreases when the time before the earthquake increases. The spatial distribution of perturbations shows that the probability of perturbations appearing southeast of the epicenter before an earthquake is a little bit higher and that there is an obvious trend because perturbations appear west of the conjugated point of an earthquake. 相似文献
Lithium-ion batteries have become the third-generation space batteries and are widely utilized in a series of spacecraft. Remaining Useful Life (RUL) estimation is essential to a spacecraft as the battery is a critical part and determines the lifetime and reliability. The Relevance Vector Machine (RVM) is a data-driven algorithm used to estimate a battery’s RUL due to its sparse feature and uncertainty management capability. Especially, some of the regressive cases indicate that the RVM can obtain a better short-term prediction performance rather than long-term prediction. As a nonlinear kernel learning algorithm, the coefficient matrix and relevance vectors are fixed once the RVM training is conducted. Moreover, the RVM can be simply influenced by the noise with the training data. Thus, this work proposes an iterative updated approach to improve the long-term prediction performance for a battery’s RUL prediction. Firstly, when a new estimator is output by the RVM, the Kalman filter is applied to optimize this estimator with a physical degradation model. Then, this optimized estimator is added into the training set as an on-line sample, the RVM model is re-trained, and the coefficient matrix and relevance vectors can be dynamically adjusted to make next iterative prediction. Experimental results with a commercial battery test data set and a satellite battery data set both indicate that the proposed method can achieve a better performance for RUL estimation. 相似文献