Numerical simulation of mesoscopic mechanical behaviors of gradual multi-fiber-reinforced polymer matrix composites

To simulate the deformation and the fracture of gradual multi-fiber-reinforced matrix composites, a numerical simulation method for the mesoscopic mechanical behaviors was developed on the basis of the finite element and the Monte Carlo methods. The results indicate that the strength of a composite increases if the variability of statistical fiber strengths is decreased.

碳纤维复合材料

最近,碳纤维复合材料(CFRP)从大型客机的二次构造材发展到一次构造材,这一重要进展是多年来碳纤维在强度和弹性模量方面不断改进,母体树脂以及复合工艺的进一步完善的基础上出现的。一次构造材要求CFRP具有更高的强度和弹性模量,而且要有优良的耐冲击性。满足了这些要求,表明CFRP已达到一个新的里程碑。简单地评介了碳纤维、母体树脂及其复合工艺、CFRP的应用前景。

生物碱类药物的液/液界面电化学研究

本文用循环伏安法(CV)和循环线扫电流计时电位法(CLC)研究了生物碱类药物盐酸麻黄碱及d-氯化筒箭毒碱在水/硝基苯界面的转移行为,论证了界面转移机制,估算了与界面行为有关的参数。

胆碱类药物的液液界面电化学研究

用循环线性电流扫描计时电位法(CLC)、循环伏安法(CV)和微分脉冲伏安法(DPV)研究了五种胆碱类药物在水/硝基苯界面(W/NB)上的转移行为.在水相溶液呈碱性时,观察到了伴有不可逆水解反应的相转移过程.讨论了药物结构中的取代基效应,并依据离子转移的标准 Gibbs 能△_o~wG_(tr)~o 度量了取代基的疏水性效应及药物的脂溶性.

ELECTROCHEMICAL TRANSFER OF 12-SILICOTUNGSTATE ANION ACROSS THE WATER NITROBENZENE INTERFACE

It has been firstly found by means of cyclic voltammetry (CV) and chronopotentiometry with linear current-scanning (CLC)that 12-silicotungstate anion (SiW_(12)O_(40)~(4-)) with high charge numbers, large molecular volume and symmetric structure can cross

季铵酚离子在水/硝基苯界面的转移

油/水界面上的电化学研究是近年来电化学研究中的一个新领域,对膜电化学的发展具有重要意义。目前研究油/水界面电化学中普遍使用循环伏安(CV)法和循环线扫电流计时电位(CLC)法。有关抗生素在油/水界面的转移已有报导,本文用CLC法和CV法对肌肉松弛剂季铵酚离子在水/硝基苯界面的转移行为进行了研究。 所用三碘季铵酚为中国科学院生物化学研究所生产的化学试剂,其他试剂及仪器均与前文相同

12-硅钨酸根离子在水/硝基苯界面的电化学转移

用循环伏安(CV)法和线性循环扫描电流计时电位(CLC)法首次研究发现带有高价电荷、体积大和高对称性的12-硅钨酸根离子(SiW_(12)O_(40)~(4-))可以在水/硝基苯界面进行电化学转移。SiW_(12)O_(40)~(4-)离子的CV曲线的特征

普鲁卡因在水/硝基苯界面的转移

本文用循环线扫电流计时电位(CLC)法及循环伏安(CV)法研究了局部麻醉药普鲁卡因在水/硝基苯界面的转移行为,同时根据转移电位和电流表达式计算出质子化普鲁卡因的标准转移电位,⊿_O~Wφ·转移自由能⊿G_(tr)~(OiW·O)和两相的分配系数及扩散系数。

Monitoring the vegetation start of season (SOS) across the island of Ireland using the MERIS global vegetation index

The aim of this study was to develop a methodology, based on satellite remote sensing, to estimate the vegetation Start of Season (SOS) across the whole island of Ireland on an annual basis. This growing body of research is known as Land Surface Phenology (LSP) monitoring. The SOS was estimated for each year from a 7-year time series of 10-day composited, 1.2 km reduced resolution MERIS Global Vegetation Index (MGVI) data from 2003 to 2009, using the time series analysis software, TIMESAT. The selection of a 10-day composite period was guided by in-situ observations of leaf unfolding and cloud cover at representative point locations on the island. The MGVI time series was smoothed and the SOS metric extracted at a point corresponding to 20% of the seasonal MGVI amplitude. The SOS metric was extracted on a per pixel basis and gridded for national scale coverage. There were consistent spatial patterns in the SOS grids which were replicated on an annual basis and were qualitatively linked to variation in landcover. Analysis revealed that three statistically separable groups of CORINE Land Cover (CLC) classes could be derived from differences in the SOS, namely agricultural and forest land cover types, peat bogs, and natural and semi-natural vegetation types. These groups demonstrated that managed vegetation, e.g. pastures has a significantly earlier SOS than in unmanaged vegetation e.g. natural grasslands. There was also interannual spatio-temporal variability in the SOS. Such variability was highlighted in a series of anomaly grids showing variation from the 7-year mean SOS. An initial climate analysis indicated that an anomalously cold winter and spring in 2005/2006, linked to a negative North Atlantic Oscillation index value, delayed the 2006 SOS countrywide, while in other years the SOS anomalies showed more complex variation. A correlation study using air temperature as a climate variable revealed the spatial complexity of the air temperature-SOS relationship across the Republic of Ireland as the timing of maximum correlation varied from November to April depending on location. The SOS was found to occur earlier due to warmer winters in the Southeast while it was later with warmer winters in the Northwest. The inverse pattern emerged in the spatial patterns of the spring correlates. This contrasting pattern would appear to be linked to vegetation management as arable cropping is typically practiced in the southeast while there is mixed agriculture and mostly pastures to the west. Therefore, land use as well as air temperature appears to be an important determinant of national scale patterns in the SOS. The TIMESAT tool formed a crucial component of the estimation of SOS across the country in all seven years as it minimised the negative impact of noise and data dropouts in the MGVI time series by applying a smoothing algorithm. The extracted SOS metric was sensitive to temporal and spatial variation in land surface vegetation seasonality while the spatial patterns in the gridded SOS estimates aligned with those in landcover type. The methodology can be extended for a longer time series of FAPAR as MERIS will be replaced by the ESA Sentinel mission in 2013, while the availability of full resolution (300m) MERIS FAPAR and equivalent sensor products holds the possibility of monitoring finer scale seasonality variation. This study has shown the utility of the SOS metric as an indicator of spatiotemporal variability in vegetation phenology, as well as a correlate of other environmental variables such as air temperature. However, the satellite-based method is not seen as a replacement of ground-based observations, but rather as a complementary approach to studying vegetation phenology at the national scale. In future, the method can be extended to extract other metrics of the seasonal cycle in order to gain a more comprehensive view of seasonal vegetation development.