GaInP2外延膜中施主—受主对复合发光带的能量关量

通过变温与变激发强度的近红外光致发光研究了用ＭＯＣＶＤ方法、生长在ＧａＡｓ衬底上的Ｇａ０．５Ｉｎ０．５Ｐ（ＧａＩｎＰ２）外延薄膜的１．１７ｅＶ发射带的发光特性。１．１７ｅＶ发光带性质与０．９９ｅＶ及０．８５ｅＶ发光带的性质有着明显的差别。１．１７ｅＶ发光带的机理可用施主－受主对的复合发光来解释，其中施主－受主对系白处在Ｇａ格位上的Ｓｉ（ＳｉＧａ）及其最邻近的Ｇａ空位（ＶＧａ）所组成，记作ＳｉＧａ－ＶＧａ。考虑到ＧａＩｎＰ２中存在着很强的电子－格子耦合作用及其Ⅲ族子格子为部分有序，所以在施主－受主对复合发光中应计及Ｆｒａｎｃｋ－Ｃｏｎｄｏｎ位移△ＦＣ及该对在等效的部分有序势场中的相互作用能Ｅｓ（ＤＡＰ）。Ｘ—射线衍射实验表明，部分有序结构相当于成分调制，因而可用Ｋｒｏｎｉｇ－Ｐｅｎｎｅｙ模型来计算Ｅｓ（ＤＡＰ）值。这样，我们就导出了施主－受主对复合发光的新的能量表示式。     

一种新型恒温—温补晶体振荡器

提出了一种ＯＣＸＯ的恒温控制方法。该方法是利用乙醇的沸点制成换态式恒温箱。这种温度控制方法既可以用作中准确度的ＯＣＸＯ，又可以作为精密双层控温ＯＣＸＯ的外层恒温装置，还可以与简单的温补线路结合，构成高准确度的ＯＴＣＸＯ。     

一种用于光传飞控系统的光纤温度传感器研究

利用半导体光吸收原理，设计出一种光纤温度传感器，它可实现强电磁干扰下高空无人机内的环境温度测量，具有体积小，结构简单的特点。该测试仪用GaAs晶片作为温度敏感元件，采用透射式结构，利用双光束补偿原理消除了光路扰动产生的误差。实验结果表明该传感器在-20-85℃的范围内有良好的温度响应。     

超高强度钢300M含碳量,等温组织与力学行为的关系

研究了四种含碳量、三种等温温度与力学行为的关系，并与淬火回火３００Ｍ钢进行比较得出，３００Ｍ钢在Ｍｓ点以下温度等温获得Ｍ＋Ｂ＿下＋Ａ＿Ｒ混合组织、超高强度和优良的韧性。断裂韧性对含碳量不敏感，冲击韧性随含碳量升高而降低。较高温度等温时，钢的冲击韧性和断裂韧性显著提高且对含碳量不敏感。     

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。     

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。     

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     

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.