已选(0)清除
条数/页: 排序方式: |
| A comparative study of the nanopore structure characteristics of coals and Longmaxi shales in China 期刊论文 ENERGY SCIENCE & ENGINEERING, 2019, 页码: 14 作者: Zhou SW; Liu HL; Chen H; Wang HY; Guo W; Liu DX; Zhang Q; Wu J; Shen WJ (沈伟军) 浏览  |  Adobe PDF(991Kb)  |  收藏  |  浏览/下载:622/203  |  提交时间:2019/09/09 adsorption capacity CBM nanopore structure SEM shale gas specific surface area |
| A theoretical model to estimate inactivation effects of OH radicals on marine Vibrio sp. in bubble-shock interaction 期刊论文 ULTRASONICS SONOCHEMISTRY, 2019, 卷号: 55, 页码: 359-368 作者: Huang Y; Wang JZ(王静竹); Abe A; Wang YW(王一伟); Du TZ(杜特专); Huang CG(黄晨光) 浏览  |  Adobe PDF(2175Kb)  |  收藏  |  浏览/下载:261/72  |  提交时间:2019/09/09 Theoretical model Bubble-shock interaction Chemical inactivation Biological probability model Generation and diffusion of OH radicals |
| 融合深度学习的点阵夹层板动力学损伤识别方法研究 学位论文 硕士论文,北京: 中国科学院大学, 2019 作者: 王亚博 Adobe PDF(6423Kb)  |  收藏  |  浏览/下载:352/9  |  提交时间:2019/06/05 深度学习 点阵夹层板 损伤识别 卷积神经网络 |
| Swelling Mechanism of Core-Shell Polymeric Nanoparticles and Their Application in Enhanced Oil Recovery for Low-Permeability Reservoirs 期刊论文 ENERGY & FUELS, 2019, 卷号: 33, 期号: 4, 页码: 3077-3088 作者: Long YQ; Huang XH; Gao Y(高颖); Chen LQ; Song FQ; Zhang HQ 浏览  |  Adobe PDF(4290Kb)  |  收藏  |  浏览/下载:167/63  |  提交时间:2019/12/02 |
| Three-dimensional Eulerian modeling of gas-liquid-solid flow with gas hydrate dissociation in a vertical pipe 期刊论文 CHEMICAL ENGINEERING SCIENCE, 2019, 卷号: 196, 页码: 145-165 作者: Li P(李鹏); Zhang XH(张旭辉); Lu XB(鲁晓兵) Adobe PDF(3454Kb)  |  收藏  |  浏览/下载:373/141  |  提交时间:2019/04/11 Marine gas hydrate-bearing sediment Hydrate dissociation model CFD Gas-liquid-solid Eulerian model |
| Application of deep learning method to Reynolds stress models of channel flow based on reduced-order modeling of DNS data 期刊论文 JOURNAL OF HYDRODYNAMICS, 2019, 卷号: 31, 期号: 1, 页码: 58-65 作者: Zhang Z(张珍); Song XD; Ye SR; Wang YW(王一伟); Huang CG(黄晨光); An YR; Chen YS 浏览  |  Adobe PDF(1492Kb)  |  收藏  |  浏览/下载:347/147  |  提交时间:2019/04/11 Deep neural network channel flow turbulence model Reynolds stress |