Analysis of Magnetic Positioning for Liquid Oxygen Under Microgravity Condition

Due to the paramagnetic property of liquid oxygen,the Kelvin force can be induced in liquid oxygen under non-uniform magnetic field.Based on the volume of fluid(VOF)model,the positioning effect of the force in liquid oxygen tanks is analyzed under various Bond numbers(Bo)and magnetic Bond numbers(Bom).The results show that the magnetic field has the effect of repositioning the liquid oxygen in the tank when the gravity field is not enough or absent.Additionally,the gas-liquid interface has a periodic fluctuation during the process due to the inhomogeneous Kelvin force distribution,and more effective suppression of fluctuation can be achieved under the condition of a larger Bom.The new method of controlling gas-liquid interface of liquid oxygen tank under micro gravity condition is hoped to be developed in the future.

单级混合冷剂天然气液化流程㶲效率分析

文中主要介绍了单级混合制冷液化流程模拟及其㶲分析结果。利用HYSYS软件对天然气液化工艺进行过程模拟,验证得可靠的过程模型。以模拟数据为基础,提出液化天然气工艺的㶲效率计算模型,并研究了各因素对㶲效率的影响规律。结果表明:在一定范围内,升高天然气入口温度及制冷剂低压端压力,降低天然气入口压力及制冷剂高压端压力有助于提高工艺㶲效率。

Quantitative Assessment of the Effects of Climate Change and Human Activities on Grassland NPP in Altay Prefecture

Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative assessment of the relative contributions of climate change and human activities,which are considered as the dominant triggers of grassland degradation,to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture.In this paper,the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity(NPP_(A))and potential net primary productivity(NPP_(P))in the Altay Prefecture from 2000 to 2019.Meanwhile,the difference between potential NPP and actual NPP was employed to reflect the effects of human activities(NPP_(H))on the grassland.On this basis,we validated the viability of the simulated NPP using the Pearson correlation coefficient,investigated the spatiotemporal variability of grassland productivity,and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture.The results indicate three main points.(1)The simulated NPP_(A) was highly consistent with the MOD17 A3 dataset in spatial distribution.(2)Regions with an increased NPP_(A) accounted for 70.53% of the total grassland,whereas 29.47% of the total grassland area experienced a decrease.At the temporal scale,the NPP_(A) presented a slightly increasing trend(0.83 g C m^(-2) yr^(-1))over the study period,while the trends of NPP_(P) and NPP_(H) were reduced(-1.31 and-2.15 g C m^(-2) yr^(-1)).(3)Compared with climate change,human activities played a key role in the process of grassland restoration,as 66.98% of restored grassland resulted from it.In contrast,inter-annual climate change is the primary cause of grassland degradation,as it influenced 55.70% of degraded grassland.These results could shed light on the mechanisms of grassland variation caused by climate change and human activities,and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture.

Spatiotemporal Pattern and Driving Force Analysis of Vegetation Variation in Altay Prefecture based on Google Earth Engine

Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development.In the past 20 years,the ecological environment in Altay Prefecture has changed significantly due to global warming.Meanwhile,with increasing human activities,the spatiotemporal pattern and driving forces of vegetation variation in the area are uncertain and difficult to accurately assess.Hence,we quantified the vegetation growth by using the Normalized Difference Vegetation Index(NDVI)on the Google Earth Engine(GEE).Then,the spatiotemporal patterns of vegetation from 2000 to 2019 were analyzed at the pixel scale.Finally,significance threshold segmentation was performed using meteorological data based on the correlation analysis results,and the contributions of climate change and human activities to vegetation variation were quantified.The results demonstrated that the vegetation coverage in Altay Prefecture is mainly concentrated in the north.The vegetation areas representing significant restoration and degradation from 2000 to 2019 accounted for 24.08% and 1.24% of Altay Prefecture,respectively.Moreover,spatial correlation analysis showed that the areas with significant correlations between NDVI and temperature,precipitation and sunlight hours accounted for 3.3%,6.9% and 20.3% of Altay Prefecture,respectively.In the significant restoration area,18.94% was dominated by multiple factors,while 3.4% was dominated by human activities,and 1.74% was dominated by climate change.Within the significant degradation area,abnormal degradation and climate change controlled 1.07% and 0.17%,respectively.This study revealed the dynamic changes of vegetation and their driving mechanisms in Altay Prefecture,and can provide scientific support for further research on life community mechanism theory and key remediation technology of mountain-water-forest-farmland-lake-grass in Altay Prefecture.