为解决桩基工程BIM(Building Information Modeling)技术应用常见的桩基建模、地质建模、模型整合方法问题,提出了一种通过BIM软件与可视化编程软件Dynamo相结合的桩基工程BIM技术应用方法。详细论述了此方法如何应用于桩基建模、地质...为解决桩基工程BIM(Building Information Modeling)技术应用常见的桩基建模、地质建模、模型整合方法问题,提出了一种通过BIM软件与可视化编程软件Dynamo相结合的桩基工程BIM技术应用方法。详细论述了此方法如何应用于桩基建模、地质建模、模型整合及数据提取,并将该方法的应用效果与其他方法进行了对比。分析结果表明,该方法可提升桩基工程模型搭建精度及效率,辅助确定桩长,能推动BIM技术在桩基工程中的应用。展开更多
Phytoplankton group-specific growth and microzooplankton grazing were determined seasonally using the dilution technique with high-performance liquid chromatography （HPLC） in the Xiamen Bay, a subtropical bay in sou...Phytoplankton group-specific growth and microzooplankton grazing were determined seasonally using the dilution technique with high-performance liquid chromatography （HPLC） in the Xiamen Bay, a subtropical bay in southeast China, between May 2003 and February 2004. The results showed that growth rates of phytoplankton ranged from 0.71 to 2.2 d^-1 with the highest value occurred in the inner bay in May. Mierozooplankton grazing rates ranged from 0.5 to 3.1 d^-1 with the highest value occurred in the inner bay in August. Microzooplankton grazing impact ranged from 39% to 95% on total phytoplankton Chl a biomass, and 65% to 181% on primary production. The growth and grazing rates of each phytoplankton group varied, the highest growth rate （up to 3.3 d^-1 ） was recorded for diatoms in August, while the maximum grazing rate （ up to 2.1 d ^-1 ） was recorded for chlorophytes in February in the inner bay. Among main phytoplankton groups, grazing pressure of microzooplankton ranged from 10% to 83% on Chl a biomass, and from 14% to 151% on primary production. The highest grazing pressure on biomass was observed for cryptophytes （83%） in August, while the maximum grazing pressure on primary production was observed for eyanobacteria （up to 151% ） in December in the inner bay. Net growth rates of larger phytoplanktons （diatoms and dinoflagellates） were higher than those of smaller groups （ prasinophytes, chlorophytes and cyanobacteria）. Relative preference index showed that microzooplankton grazed preferentially on prasinophytes and avoided to harvest diatoms in cold seasons （December and February）.展开更多
利用ECMWF-ERA5和NCEP-FNL再分析资料作为中尺度气象模式WRF(The Weather Research and Forecasting)初始场,对四川盆地2018年1月一次大气污染过程气象要素进行了模拟,对比分析了气温、风速、风向、相对湿度、边界层高度、温廓线的模拟...利用ECMWF-ERA5和NCEP-FNL再分析资料作为中尺度气象模式WRF(The Weather Research and Forecasting)初始场,对四川盆地2018年1月一次大气污染过程气象要素进行了模拟,对比分析了气温、风速、风向、相对湿度、边界层高度、温廓线的模拟效果,并结合大气超级站观测数据对模拟结果进行评估.结果表明:两种资料均能较好地模拟出气象要素的变化情况,但由于两套资料时空分辨率、采用的模式、同化方案、数据来源和质量控制方案存在一定区别,导致各要素模拟效果并不一致.与NCEP-FNL相比,ECMWF-ERA5模拟的平均相对湿度(59.23%)与观测值差异更小,且均方根误差、偏差较小,分别为9.83%和-0.83%,但NCEP-FNL模拟的平均气温(8.99℃)更接近观测值,且偏差值较小,为-0.04℃.两组模拟结果均显示盆地内部为模拟区域的低风速区,相对湿度模拟值在60%以上,气温高于西部山地地区.NCEP-FNL模拟的盆地内部气温、相对湿度、风速小于ECMWF-ERA5模拟值,但边界层高度模拟值较大.ECMWF-ERA5模拟的逆温强度相比较小,且温度露点差较小.此次污染过程PM2.5和PM10日均浓度最大值分别为190.1μg·m-3和261.0μg·m-3,相对湿度增大引发的颗粒物吸湿增长是导致PM2.5和PM10质量浓度突增的主要原因.展开更多
文摘为解决桩基工程BIM(Building Information Modeling)技术应用常见的桩基建模、地质建模、模型整合方法问题,提出了一种通过BIM软件与可视化编程软件Dynamo相结合的桩基工程BIM技术应用方法。详细论述了此方法如何应用于桩基建模、地质建模、模型整合及数据提取,并将该方法的应用效果与其他方法进行了对比。分析结果表明,该方法可提升桩基工程模型搭建精度及效率,辅助确定桩长,能推动BIM技术在桩基工程中的应用。
基金The National Natural Science Foundatisn of China under contract Nos 40730846 and 40521003the National Basic Key Research Program of the Ministry of Science and Technology of China (China GLOBEC-IMBER Program) under contract No.2006CB400604
文摘Phytoplankton group-specific growth and microzooplankton grazing were determined seasonally using the dilution technique with high-performance liquid chromatography （HPLC） in the Xiamen Bay, a subtropical bay in southeast China, between May 2003 and February 2004. The results showed that growth rates of phytoplankton ranged from 0.71 to 2.2 d^-1 with the highest value occurred in the inner bay in May. Mierozooplankton grazing rates ranged from 0.5 to 3.1 d^-1 with the highest value occurred in the inner bay in August. Microzooplankton grazing impact ranged from 39% to 95% on total phytoplankton Chl a biomass, and 65% to 181% on primary production. The growth and grazing rates of each phytoplankton group varied, the highest growth rate （up to 3.3 d^-1 ） was recorded for diatoms in August, while the maximum grazing rate （ up to 2.1 d ^-1 ） was recorded for chlorophytes in February in the inner bay. Among main phytoplankton groups, grazing pressure of microzooplankton ranged from 10% to 83% on Chl a biomass, and from 14% to 151% on primary production. The highest grazing pressure on biomass was observed for cryptophytes （83%） in August, while the maximum grazing pressure on primary production was observed for eyanobacteria （up to 151% ） in December in the inner bay. Net growth rates of larger phytoplanktons （diatoms and dinoflagellates） were higher than those of smaller groups （ prasinophytes, chlorophytes and cyanobacteria）. Relative preference index showed that microzooplankton grazed preferentially on prasinophytes and avoided to harvest diatoms in cold seasons （December and February）.
文摘利用ECMWF-ERA5和NCEP-FNL再分析资料作为中尺度气象模式WRF(The Weather Research and Forecasting)初始场,对四川盆地2018年1月一次大气污染过程气象要素进行了模拟,对比分析了气温、风速、风向、相对湿度、边界层高度、温廓线的模拟效果,并结合大气超级站观测数据对模拟结果进行评估.结果表明:两种资料均能较好地模拟出气象要素的变化情况,但由于两套资料时空分辨率、采用的模式、同化方案、数据来源和质量控制方案存在一定区别,导致各要素模拟效果并不一致.与NCEP-FNL相比,ECMWF-ERA5模拟的平均相对湿度(59.23%)与观测值差异更小,且均方根误差、偏差较小,分别为9.83%和-0.83%,但NCEP-FNL模拟的平均气温(8.99℃)更接近观测值,且偏差值较小,为-0.04℃.两组模拟结果均显示盆地内部为模拟区域的低风速区,相对湿度模拟值在60%以上,气温高于西部山地地区.NCEP-FNL模拟的盆地内部气温、相对湿度、风速小于ECMWF-ERA5模拟值,但边界层高度模拟值较大.ECMWF-ERA5模拟的逆温强度相比较小,且温度露点差较小.此次污染过程PM2.5和PM10日均浓度最大值分别为190.1μg·m-3和261.0μg·m-3,相对湿度增大引发的颗粒物吸湿增长是导致PM2.5和PM10质量浓度突增的主要原因.
