E3S Web Conf.
Volume 198, 20202020 10th Chinese Geosynthetics Conference & International Symposium on Civil Engineering and Geosynthetics (ISCEG 2020)
|Number of page(s)||7|
|Section||Geosynthetics Applied Design Theory and Method|
|Published online||26 October 2020|
- Secrieru E, Mohamed W, Fataei S, et al. (2020) Assessment and prediction of concrete flow and pumping pressure in pipeline. Cem. Concr. Compos., 107: 1-13. [Google Scholar]
- Ngo T-T, Kadri E-H, Cussigh F, et al. (2011) Measurement and modeling of fresh concrete viscous constant to predict pumping pressures. Can. J. Civ. Eng., 38: 944-956. [CrossRef] [Google Scholar]
- Wu B, Chen B, Xu J, et al. (2011) Analysis on pumping pressure loss of high-strength and high-performance concrete. Concrete, 33: 142-144. (in Chinese) [Google Scholar]
- Kwon SH, Jang KP, Kim JH, et al. (2016) State of the art on prediction of concrete pumping. Int. J. Concr. Struct. Mater., 10: S75-S85. [Google Scholar]
- Kaplan D, Larrard Fd, Sedran T. (2005) Design of concrete pumping circuit. ACI Mater. J., 102: 110-117. [Google Scholar]
- Feys D, Khayat KH, Perez-Schell A, et al. (2015) Prediction of pumping pressure by means of new tribometer for highly-workable concrete. Cem. Concr. Compos., 57: 102-115. [Google Scholar]
- Chen J, Xie H, Guo J, et al. (2019) Preliminarily experimental research on local pressure loss of fresh concrete during pumping. Measurement, 147: 1-9. [CrossRef] [Google Scholar]
- Mai C-T, Kadri E-H, Ngo T-T, et al. (2014) Estimation of the pumping pressure from concrete composition based on the identified tribological parameters. Adv. Mater. Sci. Eng., 2014: 1-18. [CrossRef] [Google Scholar]
- Chen M, Xu Z. (2009) Study on damage detection of concrete based on ultrasonic pulse compression method. China Safty Sci. J., 19: 100-104. (in Chinese) [Google Scholar]
- Xie X, Yi W, Wang X, et al. (2008) Review of structural damage detecting based on dynamics system identification in time domain. China Safty Sci. J., 18: 110-115.(in Chinese) [Google Scholar]
- Trtnik G, Kavcic F, Turk G. (2009) Prediction of concrete strength using ultrasonic pulse velocity and artificial neural networks. Ultrasonics, 49: 53-60. [PubMed] [Google Scholar]
- He W. (2019) Mechanical signal recognizng based on semi-supervised manifold learning. Sh. Electron. Eng., 39: 207-212.(in Chinese) [Google Scholar]
- Anastasopoulos A, Kourousis D, Bollas K. (2009) Acoustic emission leak detection of liquid filled buried pipeline. J. Acoustic Emission. 27: 27-39 [Google Scholar]
- Theodoridis S, Koutroumbas K. (2009) Pattern recognition, fourth edition. Elsevier, Singapore. [Google Scholar]
- Zhao H, Zhang L, Chen Z. (2009) Using mixed window function and subband spectrum centroid in MFCC feature extractmn process. J. Comput. Appl., 29: 49-51.(in Chinese) [Google Scholar]
- Li H. (2019) Statistical learning method. Tsinghua University Press, Beijing.(in Chinese) [Google Scholar]
- O’Rourke J. (1998) Computational geometry in C, 2nd edition. Cambridge University Press, England. [CrossRef] [Google Scholar]
- Wang N, Chen K. (2009) Application of sub-band spectral centroid features to recognizing underwater targets. Acta Armamentarii, 30: 144-149.(in Chinese) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.