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带低正则外力项的分数次阻尼波方程的长时间行为
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作者 刘存才 孟凤娟 张昶 《南京大学学报(数学半年刊)》 2020年第1期43-54,共12页
本文主要考虑三维空间中有界区域上带低正则外力项的分数次阻尼波方程的长时间行为.利用分数次拉普拉斯算子生成的算子半群的解析性,我们改进了分数次阻尼波方程Strichartz估计.由于超临界非线性下波方程的弱解唯一性无法验证,为了克服... 本文主要考虑三维空间中有界区域上带低正则外力项的分数次阻尼波方程的长时间行为.利用分数次拉普拉斯算子生成的算子半群的解析性,我们改进了分数次阻尼波方程Strichartz估计.由于超临界非线性下波方程的弱解唯一性无法验证,为了克服这个困难,我们对弱解增加了适当的限制条件,考虑了平移正则解.然后证明了平移正则解的适定性.进一步得到了全局吸引子的存在性. 展开更多
关键词 波方程 超临界非线性 Strichartz不等式 全局吸引子 低正则
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A Fully Flexible Potential Model for Carbon Dioxide 被引量:2
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作者 朱爱梅 张新波 +1 位作者 刘庆林 张秋根 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2009年第2期268-272,共5页
A fully flexible potential model for carbon dioxide has been developed to predict the vapor-liquid coexistence properties using the NVT-Gibbs ensemble Monte Carlo technique(GEMC).The average absolute deviation between... A fully flexible potential model for carbon dioxide has been developed to predict the vapor-liquid coexistence properties using the NVT-Gibbs ensemble Monte Carlo technique(GEMC).The average absolute deviation between our simulation and the literature experimental data for saturated liquid and vapor densities is 0.3% and 2.0%,respectively.Compared with the experimental data,our calculated results of critical properties(7.39 MPa,304.04 K,and 0.4679 g?cm-3) are acceptable and are better than those from the rescaling the potential parameters of elementary physical model(EPM2).The agreement of our simulated densities of supercritical carbon dioxide with the experimental data is acceptable in a wide range of pressure and temperature.The radial distribution function estimated at the supercritical conditions suggests that the carbon dioxide is a nonlinear molecule with the C O bond length of 0.117 nm and the O C O bond angle of 176.4°,which are consistent with Car-Parrinello molecular-dynamics(CPMD),whereas the EPM2 model shows large deviation at supercritical state.The predicted self-diffusion coefficients are in agreement with the experiments. 展开更多
关键词 molecular simulations radial distributions fully flexible potential model carbon dioxide
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