计算机模拟高温下温度波动对简化环氧分子结构参数的影响

对４００Ｋ下简化环氧分子结构的键长、键角、四原子扭转角及非键合原子间距离等结构参数在微小温度波动时进行动态模拟，分析了这些结构参数在该条件下的变形刚性。     

A set of systems for labor standards computer-aided design

A set of systems for labor standard computer-aided design is described, namely, initial developments, advance and state-of-the art.     

M40/4211 复合材料层合板铣削加工试验

通过分析碳纤维复合材料的性能特点及对切削加工性能的影响,提出了铣削刀具材料和几何结构形式的选用原则,介绍了几种适于碳纤维复合材料铣削的加工刀具。针对碳纤维复合材料中常用的M40/4211复合材料层合板进行加工缺陷试验和切削试验,总结出影响M40/4211复合材料层合板加工质量的因素及规律,得到每种刀具加工M40/4211复合材料层合板的最佳加工参数,较高的切削速度配合恰当的进给速度可以有效提高M40/4211复合材料层合板的加工质量和加工效率。     

航空发动机燃油计量装置特性仿真与试验研究

燃油计量装置作为航空发动机燃油控制系统的执行机构对航空发动机的性能有直接影响,全面掌握燃油计量装置特性是非常重要的。基于AMESim软件建立了航空发动机燃油计量装置的热液压模型,分析了燃油计量装置特性及受温度影响的规律,并通过试验验证了仿真结果。结果表明:建立的模型具有较高的精度,在控制器指令不变的情况下,随着油温的升高,燃油质量流量会有一定程度减小。     

RTS-20A便携式低温恒温槽

介绍了一种便携式低温恒温槽的工作原理及组成结构，并给出了试验数据。     

基于虚拟仪器的切削力监控技术研究

研制了一种基于虚拟仪器界面、供现场使用的高精度、高效率的金属切削过程监控系统。研究中采用回归分析、叠加原理及抛物线插值的方法建立切削力模型 ,并基于该模型进行参数估计来提取切削状态特征 ,进而监控整个切削过程     

微特电机全温度自动补偿原理及参数的确定

设计了全温度自动补偿电路，提高微特电机主要性能指标的温度稳定性．它的工作原理简单；电路参数的确定采用计算机辅助计算方法——具有连续延伸和自动改变初值的加速寻优的单纯形方法，不仅快捷、准确，而且稍加修改也可适用于任何多元非线性方程组的求解     

机械加工切削用量的优化

本文探讨了机械加工中,切削用量优化目标函数,优化数学模型,优化方法步骤。以期用该模式取代凭经验选定切削用量的方法,从而提高经济效益。     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.     

Establishment of atmospheric weighted mean temperature model in the polar regions

Due to the special geographical location and extreme climate environment, the polar regions (Antarctic and Arctic) have an important impact on global climate change. Atmospheric weighted mean temperature (Tm) is a crucial parameter in the retrieval of precipitable water vapor (PWV) from the zenith wet delay (ZWD) of ground-based Global Navigation Satellite System (GNSS) signal propagation. In this paper, the correlation between weighted mean temperature and surface temperature (Ts) is studied firstly. It is shown that the correlation coefficients between Tm and Ts are 0.93 in the Antarctic and 0.94 in the Arctic. The linear regression Tm model and quadratic function Tm model of the Antarctic and the Arctic are established respectively using the radiosonde profiles of 12 stations in the Antarctic and 58 stations in the Arctic from 2008 to 2015. The accuracies of the linear regression Tm model, the quadratic function Tm model and GPT2w Tm model which is a state-of-the-art global Tm model are verified using the radiosonde profiles from 2016 to 2018 in the Antarctic and Arctic. Root Mean Square (RMS) errors of the linear regression Tm model, the quadratic function Tm model and GPT2w Tm model in the Antarctic are 3.07 K, 2.87 K and 4.32 K respectively, and those in the Arctic are 3.53 K, 3.38 K and 4.82 K, which indicates that the quadratic function Tm model has a higher accuracy compared to linear regression Tm model, and the accuracies of the two regional Tm models are better than that of GPT2w Tm model in the polar regions. In order to better evaluate the accuracy of Tm in the PWV retrieval, the PWV values of radiosondes are used for comparisons as the reference value. The RMS errors of PWV derived from the two Tm models are similar for 1.28 mm in the Antarctic and 1 mm in the Arctic respectively. In addition, the spatial and temporal variation characteristics of Tm are analyzed in the polar regions by spectral analysis of Tm data using fast Fourier transform. The results show that the Tm has obvious seasonality and annual periodicity in the polar regions, and the maximum difference between warm season and cold season is about 63 K. After comparing and analyzing the influences of latitude, longitude and elevation on the Tm in the polar regions, it is found that latitude and elevation have a greater influence on the Tm than the longitude. As the latitude and elevation increase, the Tm decreases, and vice versa in the polar regions.